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JMIR Preprints
A preprint server for pre-publication/pre-peer-review preprints intended for community review as well as ahead-of-print (accepted) manuscripts
Background: Antimicrobial resistance [AMR] is a global problem. It’s important to train health care professionals on rational use of antimicrobials to curb AMR Objective: In order to support efforts to reduce antibiotic resistance, the study intends to assess how well a gamified educational intervention might improve healthcare professionals' and students' understanding and usage of appropriate antibiotics. Methods: This is a prospective interventional study conducted for the clinical practitioners, Undergraduates [MBBS/Interns], Post graduates and Pharmacy Students. A total of 50 participants were included in the study. The innovative games were administered for management of infections of all the different systems of the body in accordance with the ICMR treatment guidelines 2022 and latest IDSA guidelines involving different components. Pre-test and Post-test questionnaires were administered and evaluated. Results: After the intervention, the knowledge on differentiating between bacterial and viral symptoms in respiratory tract infections and gastroenteritis improved from 48% to 94%. The practice of using right empirical choice of antimicrobials in the right Conclusions: The gamified intervention successfully improved participants & their knowledge and awareness on rational antimicrobial use. The substantial improvements in all the aforementioned components highlight the positive impact of the intervention in promoting optimal antimicrobial use and curbing AMR. Innovative gamified interventions create better and long-lasting awareness ensuring the appropriate use of antimicrobials
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Background: Antimicrobial resistance [AMR] is a global problem. It’s important to train health care professionals on rational use of antimicrobials to curb AMR Objective: In order to support efforts...
Background: Antimicrobial resistance [AMR] is a global problem. It’s important to train health care professionals on rational use of antimicrobials to curb AMR Objective: In order to support efforts to reduce antibiotic resistance, the study intends to assess how well a gamified educational intervention might improve healthcare professionals' and students' understanding and usage of appropriate antibiotics. Methods: This is a prospective interventional study conducted for the clinical practitioners, Undergraduates [MBBS/Interns], Post graduates and Pharmacy Students. A total of 50 participants were included in the study. The innovative games were administered for management of infections of all the different systems of the body in accordance with the ICMR treatment guidelines 2022 and latest IDSA guidelines involving different components. Pre-test and Post-test questionnaires were administered and evaluated. Results: After the intervention, the knowledge on differentiating between bacterial and viral symptoms in respiratory tract infections and gastroenteritis improved from 48% to 94%. The practice of using right empirical choice of antimicrobials in the right Conclusions: The gamified intervention successfully improved participants & their knowledge and awareness on rational antimicrobial use. The substantial improvements in all the aforementioned components highlight the positive impact of the intervention in promoting optimal antimicrobial use and curbing AMR. Innovative gamified interventions create better and long-lasting awareness ensuring the appropriate use of antimicrobials
Background: Mastering medical terminology is a significant challenge for students in the health sciences due to the extensive and complex nature of the subject matter. Traditional learning methods oft...
Background: Mastering medical terminology is a significant challenge for students in the health sciences due to the extensive and complex nature of the subject matter. Traditional learning methods often lead to surface-level memorization and reduced engagement. Digital serious games offer an innovative, interactive, and adaptive approach to medical education, potentially enhancing learning outcomes and motivation. Objective: This study aimed to evaluate the effectiveness of a mobile-based serious educational game, MedQuiz, in improving medical terminology acquisition and user satisfaction among allied healthcare students. Methods: A randomized controlled trial (RCT) with a parallel-group design was conducted among undergraduate students enrolled in Health Information Technology (HIT) and Speech Therapy programs. Participants were randomly assigned to either the intervention group (n = 30), which used MedQuiz alongside traditional lecture-based instruction, or the control group (n = 30), which received only conventional teaching. The System Usability Scale (SUS) and Heuristic Evaluation of Playability (HEP) frameworks were used to assess usability and engagement. Learning outcomes were measured through pre- and post-test scores, while student perceptions were evaluated using the MEEGA+ questionnaire. Data were analyzed using ANCOVA to control for baseline differences. Results: A total of 60 students completed the study. The intervention group demonstrated a significantly higher post-test mean score (28.23 ± 8.74) compared to the control group (20.8 ± 7.79, P < 0.001), while no significant differences were found in pre-test scores (P = 0.31). The usability of MedQuiz was rated highly, with a SUS score of 90.36%. HEP analysis revealed high ratings for engagement (4.6/5), competitiveness (4.8/5), and feedback system (4.7/5). No significant gender-based differences were observed (P = 0.819). MEEGA+ assessment indicated favorable usability (3.44/5) and learning effectiveness (3.56/5), though entertainment value (2.95/5) suggested room for improvement in gamification features. Conclusions: The findings support MedQuiz as an effective and engaging tool for medical terminology learning, significantly improving knowledge acquisition and student motivation. Its modular and adaptive design allows for potential expansion into other medical education domains. Future research should focus on long-term knowledge retention, cross-disciplinary implementation, and integration of AI-driven personalized learning features to further optimize its educational impact. Clinical Trial: The study protocol has been published (DOI: [10.3233/SHTI220658]), and the study was approved by the ethical committee of MUMS (Approval Number: IR.MUMS.REC.1400.336).
Background: Alzheimer’s disease (AD) presents significant challenges to healthcare systems worldwide. Early and accurate diagnosis of AD is crucial for effective management and care, as it enables t...
Background: Alzheimer’s disease (AD) presents significant challenges to healthcare systems worldwide. Early and accurate diagnosis of AD is crucial for effective management and care, as it enables timely treatment interventions that can preserve cognitive function and improve patient quality of life. However, there are often significant delays in diagnosis. Continuing medical education (CME) has enhanced physician knowledge and confidence in various medical fields, including AD. Notably, web-based CME has been shown to positively influence physician confidence, which can lead to changes in practice and increased adoption of evidence-based treatment selection. Objective: This study investigated the impact of a targeted, web-based CME intervention on healthcare providers’ confidence, competence, and real-world outcomes in diagnosing early AD. Methods: The study employed a two-phase design. Phase I used a pre-post assessment to evaluate immediate changes in knowledge and confidence before and after CME participation. Phase II involved a retrospective, matched case-control study to examine the impact of CME on AD diagnoses in claims data. Results: A one-way analysis of variance (ANOVA) showed a significant effect of CME for change in the volume of AD diagnoses, F(1, 900) = 5.50, P = .0192. Compared to controls, CME learners were 1.6 times more likely to diagnose AD, resulting in an estimated net increase of 7939 new diagnoses annually. Post-CME, being confident was associated with a greater likelihood of diagnosing AD (odds ratio [OR] 1.64; 95% CI 0.92, 2.92; P = .09; n = 219). Conclusions: Web-based CME participation is associated with increased real-world AD diagnoses. Findings offer a mechanism to explain the changes in real-world practice seen as a result of the CME intervention, which improves skills and confidence.
Background: Diabetes has become a significant global health issue, particularly imposing a deep economic burden on developing countries. Innovative and integrated digital solutions can reduce the impa...
Background: Diabetes has become a significant global health issue, particularly imposing a deep economic burden on developing countries. Innovative and integrated digital solutions can reduce the impact of diabetes and enhance the quality of care. However, digital solutions have not been utilized before in Myanmar. Objective: This study aims to demonstrate the novel integrated effect of diabetes knowledge and registry tools on the performance of front-line health workers in primary healthcare settings. Methods: A quasi-experimental study with an intervention and control group was conducted in two townships from October 2022 to April 2023. For the first time, researchers trained the intervention group to use digital tools for diabetes control and monthly follow-up. The study employed multiple linear regression models to explore the novel impact of digital tools on knowledge and performance scores, their correlations, and their association with covariates. Additionally, it assessed the cost-effectiveness of the intervention by using self-administered questionnaires as measurement tools formulated based on the National Diabetes Guidelines. Results: 96 participants were enrolled in the study, divided evenly into two groups. The intervention group exhibited a significant increase in mean knowledge scores from 85.81 to 99.25 (P < .001) and performance scores from 71.22 to 107.16 (P < .001). The intervention accounted for 43.2% of the variance in knowledge scores and 62.5% in performance scores (P < .001). A positive correlation was found between knowledge and performance scores (r = .45, P < .001). The intervention was also cost-effective, with a cost-effectiveness analysis value of 0.711 and an incremental cost-effectiveness ratio of 10127.04 Kyats. Conclusions: Since the new integrated intervention yields significant economic gains and positive effects, researchers suggest policymakers replicate this intervention as a nationwide program and recommend scaling up the utilization of digital tools to improve knowledge and performance for diabetes control in frontier health workers.
Background: Fish plays a vital role in the human diet, with an ever-growing global demand. Over the past 60 years, world fish production has dramatically increased, reaching approximately 179 million...
Background: Fish plays a vital role in the human diet, with an ever-growing global demand. Over the past 60 years, world fish production has dramatically increased, reaching approximately 179 million tons in 2018, with a value of $401 billion. Similarly, global fish consumption rose from 9.0 kg per capita in 1961 to 20.5 kg in 2018, marking a significant transformation in the fishery industry (Hussein, 2014; FAO, 2018). In Africa, fish contributes 19% of animal protein and essential micronutrients, particularly fatty acids that cannot be replaced by other food commodities (Quinlan, 2013). Fish consumption in Africa averages 10.8 kg per person per year, whereas in Ethiopia it is significantly lower at just 0.2 kg per person per year (Breuil and Grima, 2014).
Ethiopia, being a landlocked nation, relies entirely on its inland lakes, reservoirs, and rivers for fishing resources (Seo and Bohach, 2007). The country’s annual fish production potential is estimated at 51,400 tons (Mainous et al., 2006). However, the domestic fish market is relatively small outside major fishing regions. Most lakes are located within the East African Rift Valley system, with Lake Tana being the largest, accounting for over half of Ethiopia’s inland water area (Alazar, 2016).
Fish is an ideal dietary option due to its high nutritional value and easy digestibility (Adugna et al., 2019). However, fish meat is highly susceptible to various bacterial infections, many of which are pathogenic, while others are saprophytic in nature (Bujjamma and Padmavathi, 2015). Bacterial pathogens in fish include zoonotic and pathogenic bacteria such as Edwardsiella, Salmonella, Escherichia coli, Staphylococcus aureus, Vibrio, and Aeromonas. These pathogens have been isolated from fish in various parts of Ethiopia (Otte et al., 2021). Fish diseases caused by bacterial infections include dropsy, epizootic ulcerative syndrome (EUS), swim bladder disease, scale loss disease, fin rot, and tail disease (Adugna et al., 2019). Most pathogenic bacteria are naturally occurring saprophytes and opportunistic pathogens that invade fish tissue under favorable conditions (Hussein, 2014).
Zoonotic diseases are estimated to cause 2.5 billion cases of human illness globally every year (Salyer et al., 2017). More than 60% of existing and 75% of emerging or re-emerging human diseases are zoonotic, with 36% of these diseases linked to food-producing animals (Otte et al., 2021).
Staphylococcus aureus is a major cause of foodborne illnesses, primarily through the consumption of preformed staphylococcal enterotoxins. These enterotoxins are highly heat-stable and often associated with staphylococcal foodborne intoxication (SFI) (Dabassa et al., 2019). Prepared foods containing more than 10³ colony-forming units per gram (cfu/g) of S. aureus are considered unsatisfactory, and counts exceeding 10⁴ cfu/g render the food potentially harmful for consumption. Consuming food contaminated with staphylococcal enterotoxins in amounts as small as nanograms to micrograms can cause severe illness, ranging from mild skin infections to life-threatening conditions (Seo and Bohach, 2007).
Improper refrigeration or exposure to elevated temperatures during food processing often creates conditions favorable for the growth of S. aureus (Dabassa et al., 2019). The bacterium colonizes 30–50% of the healthy human population, with the anterior nares of the nose being the most common carriage site (Wertheim et al., 2005). According to the National Health and Nutrition Examination Survey (2001–2002) in the United States, approximately 32.4% of the non-institutionalized population, including children and adults, were nasal carriers of S. aureus (Mainous et al., 2006).
Preventing staphylococcal food poisoning can be challenging, as carriers often exhibit no symptoms. A cross-sectional study conducted in Gondar revealed that 16.5% of fingernail samples from 127 food workers in cafeterias tested positive for S. aureus (Andargie et al., 2008). Similarly, in Botswana, 57.5% of 200 food workers tested positive for S. aureus (Loeto et al., 2007).
Globally, antimicrobial-resistant S. aureus poses a significant threat to public health. Unhygienic and improper food processing practices are major contributing factors to the emergence of resistant strains (Quinlan, 2013). In developing countries like Ethiopia, where raw fish consumption is common, antimicrobial-resistant S. aureus strains are an emerging concern (Dabassa et al., 2019). The objective of the current research is to provide baseline data on the status of S. aureus along the fish value chain in Gondar town and contribute, if possible, to the development of national food safety strategies (Mulder et al., 2020). Objective: 1.3. Objective of the Study
1.3.1. General objective
To isolate S. aureus and assess its antibiogram and factors associated for its occurrence in unloading sites and selected restaurants of Gondar city North west Ethiopia
1.3.2. Specific objectives
To isolates S. aureus from fresh and ready to eat fish at unloading sites and restaurants. Respectively.
To assess the antimicrobial susceptibility pattern of S. aureus.
To assesses factors associated with fishing activity and food safety in study sites. Methods: 3. MATERIALS AND METHODS
3.1. Study Area
The study was conducted in Gondar city (restaurants) and in Lake Tana unloading sites (miterha, sheha and gorgora). The city of Gondar is situated in North-western parts of Ethiopia, Amhara Regional State. It is at 120 3‟ N latitude and 370 28‟E.Longitude Gondar is located at 727 km from Addis Ababa, the capital city of federal government of Ethiopia, and 120 km from Bahir Dar, the capital city of Amhara National Regional State. Gondar has five sub cities and a total area of 192.3 km2 with undulating mountainous topography. According to the 2023 National Population and Housing Census estimation Gondar consists of a total of 675651peoples. Gondar is the center of political and economic activities of the North Amhara region and it is main city of the central Gondar Zone. It stands at an elevation of 7,500 feet (2,300 meters) on a basaltic ridge from which streams flanking the town flow to Lake Tana, 21 miles (34 km) Gondar City Administration. (2015).
Lake Tana is the head quarter water source of Blue Nile River and is the largest fishing sites in the region and the country which is almost dominated by artisanal fishermen. This lake is found in Amhara Region and has a surface area of 32,000 km2 with a maximum and minimum depth of 14m and 8m respectively. The Lake provides commercially important fish groups; namely, African Cat fish (Clarius gariepinus) locally called “Ambaza”, Nile tilapia (Oreochromis niloticus) locally called “Kereso” and Labeobarbus spp (cypernidie) locally called “Nech Asa”.
Figure 1: Map of the study area and Geographical location of Gondar city and Lake Tana
Source (GIS software, 2020).
3.2. Study Population and Sample Type
The study population consists of raw fish (both fresh unfilleted and filleted), including species such as Nile Tilapia (Oreochromis niloticus), Labeo Barbus (Cyprinidae), and Catfish (Clarias gariepinus), which were collected by fishermen from Lake Tana. Additionally, frozen and cooked fish (ready-to-consume) were included, such as: Asa Tibs (fried fish): A dish prepared by gutting or removing inedible parts of the fish, followed by thorough cooking in oil at high temperatures for human consumption. Asa Lebleb (undercooked fish): A dish made by cutting the muscle into pieces, adding spices, and cooking at low temperatures. Asa Wot (fish stew): A dish prepared by mincing the fish muscle, adding spices, and cooking at high temperatures for human consumption. The types of samples included in the study were: Fish meat swabs from raw and prepared fish, Hand swabs from fisheries and restaurant workers, and Knife swabs from knives used for fish processing.
3.3. Study Design and sample size determination
A cross-sectional study was conducted from December 2023 to September 2024. In addition, an observational checklist and a pre-tested questionnaire were administered to workers along the value chain, including restaurants, to determine possible sources and sites of contamination within the value chain. The sample size was determined using the Thrusfield formula (Thrusfield, 2005), with a calculated total sample size of 384. However, since the fish population in Lake Tana was unknown, the sample distribution was based on data from the Gondar Zuria Wereda Fishery Sector. According to this data, fisheries collect 10% Catfish, 30% Labeo Barbus, and 60% Nile Tilapia. Therefore, a total of 301 samples were investigated.
3.4. Sampling Method
Twelve restaurants were selected using purposive sampling from five sub-cities. These five sub-cities, identified based on Gondar City Administration data (2015), include Arada Kefle Ketema, Azezo Teda Kefle Ketema, Zobel Kefle Ketema, Facile, and Maracie Kefle Ketema.
In Lake Tana, three landing sites—Mitreha, Sheha, and Gorgora—located in Gondar Zuria Wereda and West Denbia Wereda were also selected through purposive sampling. At the fishing sites, fishing activities occurred primarily twice per day (morning and afternoon). Fish samples from unloading sites were collected using a simple random sampling method, based on the number of fishing activities per day and the number of trips made to unloading sites by the fishery.
A total of 301 samples were collected, including 201 samples from unloading sites and 100 samples from restaurants. These were gathered over a total of 18 observations: 12 observations for collecting swab samples from unloading sites and 6 observations for collecting swab samples from restaurants in Gondar City.
3.5. Data Collection Procedure
3.5.1. Sample Collection
Hand swab and knife swab samples were collected from selected restaurants using sterile sampling bottles containing buffered peptone water and kept in an icebox with ice packs. Similarly, swab samples from raw or fresh fish at selected fishing sites were collected and placed in sterile sampling bottles containing buffered peptone water. Sterile cotton swabs were used to transfer the fish swab from the uncooked fish meat plate to the sampling containers.
After labeling and coding with all necessary information, the samples were immediately transported to the University of Gondar College of Veterinary Medicine and Animal Sciences, Veterinary Microbiology Laboratory, using an icebox with ice packs. The samples were processed within 24 hours of collection, and all inoculums were incubated overnight at 37°C for the isolation and identification of Staphylococcus aureus from fish meat swabs and contact surface sampling swabs.
3.5.2. Questionnaire Survey and Observation
A pre-tested questionnaire was designed to collect separate data (Annex V and VI) for fish processors in restaurants and fish harvesters at unloading sites. Questionnaire surveys were conducted to assess factors associated with cross-contamination in raw and ready-to-eat fish-derived foods. The questionnaire also included socio-demographic factors, transport-related issues, educational status, and personal hygiene practices.
Respondents were purposively selected based on their significant roles in food processing and handling. The questionnaire and observational checklists were administered in accordance with the standard guidelines of the Codex Alimentarius Commission of the Food and Agriculture Organization (Annex VII) (FAO, 2009).
3.6. Isolation and Biochemical Tests
The assignment of Staphylococcus aureus species and final identification of staphylococcal organisms were performed using various culturing methods, followed by Gram staining and biochemical tests. The biochemical tests included the catalase test, tube coagulase test, slide coagulase test, Voges-Proskauer test, and mannitol sugar fermentation test. Both coagulase tests, using rabbit plasma, were conducted in parallel to further confirm the identification of S. aureus.
Gram's staining
Gram staining was performed on all suspected Staphylococcus species cultures, and the sizes, shapes, and cell configurations of the cultures were examined under a light microscope. Presumptive Staphylococcus species were identified based on Gram-stained smears of typical colonies, which revealed Gram-positive cocci arranged in irregular grape-like clusters.
Catalase test
Using a bacteriological loop, pure cultures of the isolates to be tested for catalase were removed from the agar plate and mixed with a drop of 3% hydrogen peroxide on a sanitized slide. Within a few seconds, bubbles of oxygen were released, indicating a positive reaction and the presence of Staphylococcus aureus (Quinn et al., 2002).
Mannitol salt Agar (Mannitol fermentation)
The colonies were streaked onto Mannitol Salt Agar plates and incubated at 37°C. Growth was checked after 24 to 48 hours. These colonies were confirmed through Gram staining, hemolysis on blood agar, colony characterization, and a positive catalase test. The presence of growth and a pH shift from red to yellow in the medium indicated the presence of coagulase-positive Staphylococcus aureus. Fermentation of mannitol by S. aureus causes the medium to turn yellow within 24 hours of incubation (Quinn et al., 2002).
Coagulase test
Both slide coagulase and tube coagulase tests were used as coagulase assays. Staphylococcus aureus presumed to be identified from Mannitol Salt Agar was subcultured onto a nutrient agar plate. After 24 hours, the culture colonies of S. aureus were selected using a bacteriological loop, placed on a clean slide, and emulsified. A drop of rabbit plasma was added to the test suspension, and it was thoroughly mixed with a wire loop for five to ten seconds.Clumping of the cocci was interpreted as a positive result (Quinn et al., 2002). For the tube coagulase test, 0.5 ml of selected Staphylococcus isolates cultured in tryptic soy broth at 37°C for 24 hours was added to 0.5 ml of rabbit plasma in sterile tubes. This test was conducted for those isolates that were negative in the slide coagulase test. Any visible clotting inside the tube, ranging from a loose to a firm clot that remained immovable when the tube was inverted (tilted), was considered a positive result. No clotting at all was interpreted as a negative result (Quinn et al., 2002).
Vogues proskauer test
The Voges-Proskauer test is a biochemical test that detects the ability of bacteria to metabolize pyruvate into a neutral intermediate product called acetylmethylcarbinol or acetoin. The test is performed by adding alpha-naphthol and potassium hydroxide to the Voges-Proskauer broth. This test is conducted on Gram-positive, catalase-positive species to identify coagulase-positive Staphylococcus aureus (Quinn et al., 2002).
3.7. Antimicrobial Susceptibility Profile
All isolates of S. aureus were subjected to an antibiotic susceptibility test using the Kirby-Bauer agar disc diffusion method, following the Clinical Laboratory Standards Institute (CLSI) guidelines of the USA, on Mueller-Hinton agar (MHA). The antibiotics were selected based on their availability and relevance for routine testing and reporting on non-fasidious organisms. One representative antibiotic from each subclass of commonly used and widely available antibiotics for treating staphylococcal-related diseases in both animals and humans was chosen. Based on these criteria, seven antibiotics were selected for this study: chloramphenicol (30 µg), ciprofloxacin (5 µg), vancomycin (30 µg), erythromycin (15 µg), gentamicin (10 µg), tetracycline (30 µg), and penicillin (10 units) (CLSI, 2020).
For the susceptibility test, three to five well-isolated colonies of the same morphological type were selected from a nutrient agar plate culture and transferred into test tubes containing sterile saline. The suspension was mixed thoroughly, and the density was adjusted to 0.5 McFarland using saline or additional S. aureus colonies. A sterile swab was dipped into the suspension, and the excess inoculum was removed by pressing it against the sides of the tube to prevent over-inoculation of the plates. The inoculum was spread evenly over the entire surface of the agar plate by swabbing in three directions. Antibiotic discs were applied firmly onto the agar surface, and the plates were incubated for 24 hours at 37°C. The diameter of the zone of inhibition around each disc was measured using a ruler in millimeters (mm) and interpreted according to the CLSI standards as susceptible, intermediate, or resistant. Isolates showing resistance to three or more antibiotics were considered multiple drug-resistant (MDR) (Beyene et al., 2017).
3.9. Data Analysis
All data collected during the study period were checked, coded, and entered into an Excel spreadsheet before being analyzed using STATA software version 16 (Texas 77845, USA). Descriptive statistics, such as percentages and proportions, were used to compute the number of fish samples positive for S. aureus. A univariable logistic regression model was employed, and variables with a p-value of <0.05 were exported to a multivariable logistic regression model to assess the effects of potential confounders. The degree of association between risk factors and the occurrence of S. aureus in fish samples was quantified using the adjusted odds ratio obtained from the multivariable logistic regression models. In all analyses, the confidence level was set at 95%, and a p-value of less than 5% (P < 0.05) was considered statistically significant. Results: 4. RESULTS
4.1. Occurrence of Staphylococcus aureus
From a total of 301 samples taken, 79 (26%) were found positive for S. aureus. Out of this 53(26%) on fish and 26(26%) on hand and knife swabs were found positive for S. aureus. The occurrence of S. aureus on fish and both contact surfaces have statistically significant difference (OR=2.2, p=0.024) (Table 2).
Table 1: Occurrence of Staphylococcus aureus from fish and contact surfaces
Study Site No. of samples No of positives (%) OR P-value 95%CI (n=301) (n=79)
On fish 201 53(26%)
On hand and knife 100 26(26%) 2.2 0.024 1.10304-1.4739
Total 301 79(26%)
Key: OR= Odds Ratio, statistically significant at p<0.05, CI=Confidence Interval
4.2. Isolation of Staphylococcus aureus Related to species.
From a total of 201 fish samples, Nile Tilapia 24% (n=30), Labeobarbus 27% (n=13) and African Cat fish 36% (n=10) were identified positive for S. aureus. Based on the above occurrence of S. aureus on different fish species at different swab sites are statistically non-significant (OR= -1.281561, P=0.272) Table 3 shows the occurrence of S.aureus from different fish species.
Table 2: Isolation of Staphylococcus aureus related to species
Risk factors No. of samples No. of positive (%) OR P-value 95%CI
(n=201) (n=53)
Species
Cat fish 28 10(36%) 1.281561 0.272 0.823-1.996
Labeobarbus 48 13(27%)
Nile Tilapia 125 30(24%)
Total 201 53(26%)
Key: OR= Odds Ratio; statistically significant at p<0.05, CI=confidence interval
4.3. Isolation of Staphylococcus aureus from Fish Samples at different sampling sites
From a total of 201 samples examined the proportion of S.aureus was 36% (n=24) from Miterha, 19% (n=13) from Sheha, and 24% (n=16) from Gorgora were positive for S.aureus showed that the prevalence had statistical insignificant (OR=1.237537 and p= 0.157) but the occurrence of S. aureus in unloading sites 26%(n=53) and in restaurants 26%(n=26) had statistically significant differences (OR=2.2 and p=0.024) among the sampling sites below Table 4
From a total of 201 raw fish samples; 97 fresh unfilleted and 104 fresh filleted fish were sampled at three fish unloading sites. From collected fresh unfilleted fish samples 13 % ( n=13) and fresh filleted fish samples 39% (n=40) of S. aureus were positive. These differences were found statistically significant (OR=2.980519 and p=0.026) (Table 4).
Table 3: Isolation of Staphylococcus aureus from samples at different sampling sites
Sample type and No o f samples No of positives OR P-value 95% CI
Sample site (n=301) (n=79)
Raw unfilleted 97 13(13%)
Raw fillted 104 40(39%) 2.980519 0.026 1.139-7.797
Total 201 53(26%)
Miterha 67 24(36%)
Sheha 67 13(19%) 1.237537 0.157 0.921-1.663
Gorgora 67 16(24%)
Gondar 100 26(26%)
Total 301 79(26%)
In unloading sites 201 53(26%) 2.2 0.024 1.109-4.366
In restaurants 100 26(26%)
Total 301 79(26%)
Key: OR= Odds Ratio; statistically significant at p<0.05, CI=confidence interval
4.4 The Occurrence of S. aureus From Different Swab Sites
The present study result revealed that the prevalence of S. aureus was on hand swabs (from fish handlers) is 20% (n=10), fish meat swabs (from fishes) is 26% (n=53), and 32% (n=16) on Knife swabs (from knives used for processing) Were positive by S.aureus However, there is no statistically significant difference between hand swab, knife swab and fish meat swab (OR=0.9795685, P-value=0.921) as Table 5 shows the occurrence of S.aureus from different swab sites.
Table 4: The occurrence of S. aureus from different swab site
Swab site No of Samples No of positives OR P-value 95%CI
(n=301) (n=79)
Hand Swab 50 10(20%)
Knife Swab 50 16(32%) 0.9795685 0.921 0.652-1.472
Fish meat swab 201 53(26%)
Total 301 79(26%)
Key: OR= Odds Ratio; statistically significant at p<0.05, CI=confidence interval
4.5. Isolation and Identification of Staphylococcus aureus Species
The present study result revealed that from a total of 301 fish, hand and knife swab samples 120 (40%) samples have beta hemolysis, 102 (85%) samples were gram positive, 87 (85%) samples were catalase positive 80 (92%) samples shows mannitol fermentation (yellow zone around colonies, 79(99%) samples were coagulase positive and 79(100%) samples were positive for vogues proskauer.
Figure 2: Image of S. aureus Slide Coagulase Test on Rabbit Plasma
4.6. Questionnaire Survey Results
4.6.1. Demographic Characteristics of the participants
From a total of 90 respondents 66 fishermen and 24 restaurant workers engaged in fishing activity and fish origin food processers were interviewed in the study area. Out of participants 76(84.44%) were males and also 58(64.44%) were literate (Table 6).
Table 5: Demographic characteristics of the participants (n=90).
Variables Description No. of Respondents
Sex Male 76(84.44%)
Female 14(15.55%)
Age 20--30 26(28.88%)
31—40 41(45.55%)
>40 23(25.55%)
Educational- Literate 58(64.44%)
Status Illiterate 32(35.55%)
Years of business- 1-2 years 20(22.22%)
Experience 3-5 years 24(26.66%)
6-10years 24(26.66%)
Above 10 years 22(24.44%)
4.6.2. Questionnaire for Fish Harvesters at unloading Sites
Total number of the respondents transport fishes without ice by using a plastic bag and most of them harvest Nile Tilapia fish 41(62%). above 60(90%) of the respondents did not wash or clean their boats before and after starting of fishing activity and 54(81.8%) of the respondents had known on improper transportation of fish and improper use of hooks and filleting boards can be a source of fish food contamination. Most of the fishery men were sold the caught fishes within 6hrs–12hrs (Table 7).
Table 6: Questionnaire about food safety for fish harvesters and filleters at unloading sites (n=66).
Statements Value No of respondents (%)
Improper transportation, Yes
improper use of hooks
and filleting boards No 54(81.8%)
12(18.2%)
0(0%)
66(100%)
38(57.57%)
28(42.42%)
16(24.24%)
18(27.27%)
32(48.48%)
45(68.18%)
21(31.81%)
66(100%)
0(0%)
Transportation of fish
to the next chain
Time to market all
Harvested fish
Type of containers
Used to carry fish
Wash hands before and
after handling of fish
Wash hands after
Using toilet with ice
Without ice
6 to 12 hours
2 to 6 hours
plastic bag
wooden basket
Others
Yes
No
Yes
No
4.6.3. Data Obtained by Direct Observation on Fish Handlers
To evaluate the hygienic practices and status of the fish handlers operating in the kitchens of several restaurants. From a total of 24 workers 14(58.33%) wash hands before starting work,100% workers no discharge, workers wear 19(79%) hair covers %16(67%) over coat and 18(75%) workers were clean. Table 8 shows data obtained by direct observation.
Table 7: Direct observation on fish handlers in restaurants. (n=24)
Observational points Value Frequency Percentage (%)
Washing of hand before
Starting work Yes
No 14
10 58.33%
41.66%
Discharge from nose, eye, Observed 0 0%
Ear and coughing Not observed 24 100%
Wear of jewelry or ring Observed
Not observed 21
3 87.5%
12.5%
Wear of appropriate Yes 19 79.16%
Hair covers No 5 20.83%
Wear of appropriate overcoat Yes
No 16
8 66.66%
33.33%
Cleanness of overcoat
and visible body part Clean
Not clean 18
6 75%
25%
4.7. Antimicrobial Susceptibility Profile
All 79 S. aureus isolates were tested to seven selected antimicrobial agents on Muller Hinton agar by disc diffusion methods. In the present study, all isolates of S. aureus were susceptible to ciprofloxacin (100%), Chloramphenicol (92%), Vancomycin (84%), and Gentamycin (68%) However Erythromycin (55%), Tetracycline (72%) and Penicillin G (87%) isolates were the highest levels of resistance as shown in table 9.
Table 8: Susceptibility of S. aureus isolates against some selected antimicrobials.
Antimicrobial Antimicrobial Susceptibility pattern of Staphylococcus aureus
drugs concentration
Susceptible Intermediate Resistant
Ciprofloxacin 5 μg 79 (100%) 0 (0%) 0 (0%)
Chloramphenicol 30 μg 73 (92%) 2 (3%) 4 (5%)
Vancomycin 30 μg 66 (84%) 8 (11%) 5 (6%)
Gentamycin 10 μg 54 (68%) 11 (14%) 14 (18%)
Erythromycin 15 μg 22 (28%) 13 (17%) 44 (55%)
Tetracycline 30 μg 14 (17%) 8 (11%) 57 (72%)
Penicillin G 10 Unit 7 (9%) 3 (4%) 69 (87%)
Figure 3: The antimicrobial susceptibility profile of S. aureus to the selected antibiotic discs.
According to the current investigation 57% (n=45) of S. aureus samples tested positive for multidrug resistance (MDR). The results of the antibiotic susceptibility tests indicated that the isolates exhibited traits of a general pattern of multidrug resistance. The highest MDR of drugs which used during susceptibility test (Penicillin G, Tetracycline, and Erythromycin).
Table 9: Patterns of drug resistance of S. aureus isolated from fish and fish contact surfaces.
Frequencies Antimicrobial’s resistance pattern No of resistant %
Three P,TET,ER 29 37%
P,TET,VAN 1 1%
P,TET,GEN 3 4%
P,ER,GEN 2 3%
Total 35 44%
Four TET,P,ER,GEN 2 3%
P,ER,TET,VAN 1 1%
P,TET,VAN,GEN 1 1%
Total 4 5%
Five P,TET,ER,GEN,CHL 3 4%
TET,P ER,GEN,VAN 2 3%
P,TET,ER,GEN,CHL 1 1%
Total 6 8%
TET- Tetracycline, P- Penicillin G, ER- , Erythromycin, GEN- , Gentamycin, VAN- Vancomycin , CHL- Chloramphenicol. Conclusions: 6. CONCLUSION AND RECOMMENDATION
The present study revealed that more than one-fourth of the samples were positive for S. aureus. S. aureus was found in large quantities on knives and hands that came into contact with fish meat. The presence of S. aureus was detected in samples taken from hand swabs, fish meat swabs, and knife swabs. A statistically significant difference was observed between the study sites, with samples from Lake Tana unloading sites and restaurants in Gondar City. Furthermore, a significant difference was found between fresh unfilleted and fresh filleted fish samples. The study revealed that respondents had the habit of handling fish with bare hands at the landing sites, which may explain the high number of S. aureus isolates in fresh filleted fish. This contamination could be attributed to the direct contact of fish handlers' hands and knives during the processing or filleting of fish. It is also likely a result of the poor personal hygiene and sanitation practices of workers at fish meat vendors, as most did not clean their tools with detergents after use.
All S. aureus positive samples were tested using various biochemical tests. Additionally, the S. aureus isolates were tested for susceptibility to seven selected antimicrobial agents on Mueller-Hinton agar using the disc diffusion method. Penicillin and tetracycline exhibited high resistance.
Based on the findings of this study, the following recommendations are made:
1. Improve the awareness of fish meat sellers and workers about safe fish meal preparation, handling, and distribution. Attention should be given to the cleanliness of fish meat seller areas.
2. Regularly monitor the status of antibiotic resistance in S. aureus.
3. The treatment of choice for diseases caused by S. aureus in humans and animals should be ciprofloxacin and chloramphenicol.
4. Further research should be conducted on antimicrobial resistance-producing genes in S. aureus.
5. Continuous training must be provided to fishery societies and restaurant workers on hygiene and food safety practices.
Background: The six-minute walk test (6MWT) measures exercise capacity in cardiorespiratory, neurological and musculoskeletal conditions. It consists in observing how far a patient can walk in 6 minut...
Background: The six-minute walk test (6MWT) measures exercise capacity in cardiorespiratory, neurological and musculoskeletal conditions. It consists in observing how far a patient can walk in 6 minutes and is usually performed in a corridor in a clinic. During the COVID 19 pandemic, as healthcare systems cancelled nonurgent outpatient appointments, many tests were done online. At the Oxford University Hospitals, cardiac patients were asked to use the open-source Timed Walk app top perform 6MWT in their community, as a substitute for the regular tests in clinic. Objective: (1) To assess participation and user acceptance of the Timed Walk app, (2) to assess the clinical usefulness of the app within the context of the pandemic, and (3) to validate and improve the algorithms that compute the walked distance from the sensors data collected by the phone. Methods: Consented cardiac patients were invited to perform a 6MWT, outdoor, using the app, at least once a month, and report the results at periodic telephone calls and visits. Any clinical decision taken based on the results of the app was registered. Patients were also sent a usability and acceptance questionnaire and 10 of the respondents were selected for interviews. A group of 12 volunteers also provided sensors data collected by the app and a trundle wheel to measure reference distance for 10 tests, 5 of which were intentionally performed without following instructions to walk over straight paths. Results: the study run between 2021-09-29 and 2022-12-30. 55 participants consented (25 female, age: 44.80 ± 17.49)
1) Twenty-four patients performed one or more tests per month, average number of 6MWTs per month per patient was 1.14 ± 1.20. Usability was rated high on all dimensions; acceptance was high except intention to use the app beyond the study. Thematic analysis of the interviews provides useful insights on 3 themes:
2) 741 events were logged. 24% of 51 medical decisions involving 23% of 48 patients who performed at least 1 test, were influenced by the app-based 6MWT. Between 2018 and 2023 a cohort of 49 patients conducted 63 6MWT in the clinic (18 in 2021), whereas the same patients performed 605 tests using the app only in 2021.
3) Sensor data was sent for 107 tests, 52 not following instructions. Difference between reference distance and app distance was within minimal clinically significant difference for tests performed following instructions (limits of agreement: -27m, 34m). Anonymized data has been made publicly available. Conclusions: The use of the Timed Walk app for remote 6MWT allowed clinicians to obtain objective indications of the status of the patient during the pandemic. The distance estimated by the app is accurate when patients follow instructions. Motivation to use the app can vary depending on internal factors such as attitudes and health status, and external factors such as weather, fit into everyday life, how the data is used by clinicians and forgetfulness. Clinical Trial: ClinicalTrials.gov NCT05096819
Background: The global rise in the prevalence of diabetes significantly impacts the quality of life of both patients and their families. Despite advances in diabetes care, numerous challenges remain i...
Background: The global rise in the prevalence of diabetes significantly impacts the quality of life of both patients and their families. Despite advances in diabetes care, numerous challenges remain in its management. In recent years, digital tools have been increasingly integrated into diabetes care, demonstrating some positive outcomes. However, their long-term effectiveness and associated challenges require further investigation. Objective: This study aims to assess the types and current usage of digital tools in diabetes management, analyze their benefits and limitations, and provide recommendations for optimizing their future application in diabetes care. Methods: A scoping review was conducted following the framework of Arksey and O'Malley. Databases including CNKI, Wanfang, VIP, PubMed, Embase, Web of Science, and Cochrane Library were systematically searched for studies published from database inception to July 31, 2024. The selected literature was reviewed and analyzed. Results: A total of 6,263 articles were identified. After two rounds of screening, 45 studies were included, representing research from 7 countries. The included studies comprised randomized controlled trials (n=26), non-randomized controlled trials (n=14), and other study designs. The digital tools evaluated primarily included mobile health applications, information management platforms, diabetes online communities (DOCs), specialized monitoring devices, blood glucose management systems, and electronic remote monitoring systems. Outcome measures included blood glucose control (e.g., fasting blood glucose, postprandial blood glucose, glycated hemoglobin), blood lipid levels, BMI, self-management capacity, quality of life, patient satisfaction, and diabetes knowledge. Conclusions: Digital tools have shown promise in improving blood glucose control and self-management in diabetes patients. However, challenges such as technology acceptance, data security, and privacy concerns remain. Further research is needed to explore the long-term effectiveness of these tools and address the practical challenges in their implementation. Clinical Trial: Not applicable.
Background: Generative Artificial Intelligence (AI) chatbots have the potential to improve mental health care for practitioners and clients. Evidence demonstrates that AI chatbots can assist with task...
Background: Generative Artificial Intelligence (AI) chatbots have the potential to improve mental health care for practitioners and clients. Evidence demonstrates that AI chatbots can assist with tasks such as documentation, research, counselling, and therapeutic exercises. However, research examining practitioners’ perspectives is limited. Objective: Drawing on qualitative and quantitative data, this mixed-methods study investigates: (1) practitioners’ perspectives on different uses of Generative AI chatbots; (2) their likelihood of recommending chatbots to clients; and (3) whether recommendation likelihood increases after viewing a demonstration. Methods: Participants were 23 mental health practitioners (17 female, 6 male; M age = 39.39, SD = 16.20). In forty-five-minute interviews, participants selected their three most helpful uses of chatbots from 11 options and rated their likelihood of recommending chatbots to clients on a Likert-scale before and after a 11-minute chatbot demonstration. Results: Binomial tests found that Generating Case Notes was selected at greater-than-chance levels (p = .001), while Support with Session Planning (p = .863) and Identifying and Suggesting Literature (p = .096) were not. Although 55% (n = 12) were likely to recommend chatbots to clients, a binomial test found no significant difference from the 50% threshold (p = .738). A paired samples t-test found that recommendation likelihood increased significantly (p = .002) from pre-demonstration to post-demonstration. Conclusions: Findings suggest practitioners favour administrative uses of Generative AI and are more likely to recommend chatbots to clients after exposure. This study highlights the need for practitioner education and guidelines to support safe and effective AI integration in mental health care.
Background: Colorectal cancer (CRC) screening rates remain disproportionately low among Hispanic and Latino populations. While artificial intelligence (AI) has shown promise in healthcare delivery, it...
Background: Colorectal cancer (CRC) screening rates remain disproportionately low among Hispanic and Latino populations. While artificial intelligence (AI) has shown promise in healthcare delivery, its impact on health equity remains unclear. Objective: To evaluate the effectiveness of a bilingual generative AI voice agent outreach program in engaging Spanish-speaking patients for CRC screening compared to English-speaking patients. Methods: We conducted a retrospective analysis of AI-powered outreach calls for CRC screening at a large integrated health system serving central Pennsylvania and northern Maryland in September 2024. The study included 1,878 patients (517 Spanish-speaking, 1,361 English-speaking) eligible for colorectal cancer screening. The AI care agent conducted personalized phone calls in the patient's preferred language to discuss screening and facilitate fecal immunochemical test (FIT) kit requests. The primary outcome was FIT test opt-in rate. Secondary outcomes included call connect rates and duration. Results: Spanish-speaking patients demonstrated significantly higher engagement across all measures compared to English-speaking patients: FIT test opt-in rates (18.2% vs. 7.1%, p<0.001), connect rates (88.8% vs. 53.3%, p<0.001), and call duration (6.05 vs. 4.03 minutes, p<0.001). In multivariate analysis, Spanish language preference remained an independent predictor of FIT test opt-in (adjusted OR 2.012, 95% CI 1.340-3.019, p<0.001) after controlling for demographic and other factors (gender, age, state of residence, and call duration). Conclusions: Contrary to concerns about technology exacerbating disparities, AI-powered outreach achieved significantly higher engagement among Spanish-speaking patients. These findings suggest that language-concordant AI interactions may help address healthcare disparities and improve preventive care engagement in traditionally underserved populations.
Background: As the importance of PGHD in healthcare and research has increased, efforts to standardize survey-based PGHD to improve its usability and interoperability have been made. Standardization e...
Background: As the importance of PGHD in healthcare and research has increased, efforts to standardize survey-based PGHD to improve its usability and interoperability have been made. Standardization efforts, such as the Patient-Reported Outcomes Measurement Information System (PROMIS) and the NIH Common Data Elements (CDE) repository, provided effective tools for managing and unifying health survey questions. However, Previous methods using ontology-mediated annotation are not only labor-intensive and difficult to scale, but also face challenges in identifying semantic redundancies in survey questions, especially across multiple languages. Objective: The goal of this work was to compute the semantic similarity among publicly available health survey questions in order to facilitate the standardization of survey-based PGHD. Methods: We compiled various health survey questions authored in both English and Korean from the NIH CDE Repository, PROMIS, Korean public health agencies, and academic publications. Questions were drawn from various health lifelog domains. A randomized question pairing scheme was used to generate a Semantic Text Similarity (STS) dataset consisting of 1758 question pairs. Similarity scores between each question pair were assigned by two human experts. The tagged dataset was then used to build four classifiers featuring: Bag-of-Words, SBERT with BERT-based embeddings, SBRET with LaBSE embeddings, and GPT-4o. The algorithms were evaluated using traditional contingency statistics. Results: Among the three algorithms, SBERT-LaBSE demonstrated the highest performance in assessing question similarity across both languages, achieving an Area Under the Receiver Operating Characteristic (ROC) and Precision-Recall Curves of over 0.99. Additionally, it proved effective in identifying cross-lingual semantic similarities. Conclusions: This study introduces the SBERT-LaBSE algorithm for calculating semantic similarity across two languages, showing it outperforms BERT-based models, GPT-4o model and Bag of Words approach, highlighting its potential to improve semantic interoperability of survey-based PGHD across language barriers.
Background: Latina adolescents report low levels of moderate-vigorous physical activity (MVPA) and high lifetime risk of lifestyle-related diseases. There is a lack of MVPA interventions targeted at t...
Background: Latina adolescents report low levels of moderate-vigorous physical activity (MVPA) and high lifetime risk of lifestyle-related diseases. There is a lack of MVPA interventions targeted at this demographic despite documented health disparities. Given their high rates of using mobile technology, interventions delivered through mobile devices may be effective for this population. Objective: The current paper examines efficacy of the Chicas Fuertes intervention in increasing MVPA across six months in Latina adolescents. Methods: Participants were Latina adolescents (ages 13-18) in San Diego County who reported being underactive (<150 minutes/week of MVPA). All participants received a wearable fitness tracker (Fitbit Inspire HR); half were randomly assigned to also receive the multimedia intervention. Intervention components included a personally tailored website, personalized texting based on Fitbit data, and social media. The primary outcome was change in minutes of weekly MVPA from baseline to six months (6m), measured by ActiGraph accelerometers and the 7-Day Physical Activity Recall Interview. Changes in daily steps using Fitbit devices were also examined to test intervention efficacy. Results: Participants (N=160) were 15.3 years old on average, and mostly second generation in the U.S. For ActiGraph-measured MVPA, participants in the Intervention group (N=83) increased from a median of 0 min/week at baseline (IQR 26) to 64 min/week at 6m (IQR 28) compared to Control participants, who showed increases from a median of 0 at baseline (IQR 24) to 41 min/week at 6m (IQR 21) (p<0.05). Self-reported MVPA increased in the Intervention group from a median of 119 min/week at baseline (IQR 122.5) to 147 min/week at 6m (IQR 85) compared to Control participants, who showed increases from a median of 120 (IQR 186.25) at baseline to 124 min/week at 6m (IQR 69) (p<0.05). Steps also increased in both groups, with the Intervention group showing significantly greater increases (p<0.05). Conclusions: This intervention was successful in using a tailored technology-based strategy to increase MVPA in Latina adolescents and provides a promising approach for addressing a key health behavior. Given the scalable technology used, future studies should focus on broad scale dissemination to address health disparities. Clinical Trial: ClinicalTrials.gov NCT04190225 . Registered on November 20, 2019.
Background: Evidence on digital interventions in mental health has been increasing since the last years. However, available evidence is still heterogenous and limited regarding the use of self-adminis...
Background: Evidence on digital interventions in mental health has been increasing since the last years. However, available evidence is still heterogenous and limited regarding the use of self-administered platforms in the context of university education. Objective: We aimed to evaluate the efficacy of a self-administered digital mental health service in members of a public university to reduce symptoms of depression, anxiety, and perceived stress. Methods: A randomized controlled clinical trial was conducted. Students, teachers, and administrative staff from a public university in Peru were included. Compared to the control group (CG), the intervention group (IG) had access to a self-administered digital mental health service comprised of 6 modules with audiovisual material. Multivariate ANCOVA models and effect size indicators (Cohen's d) were used to compare the reduction of anxiety (PHQ-9), anxiety (GAD-7), and perceived stress (PSS-10) between both groups. Results: 55 participants participated in the IG and 30 in the CG. Age, sex, and baseline mental health characteristics were balanced. The IG had lower values of depressive symptoms, anxiety, and stress compared to the CG, as evidenced by the multivariate models and effect measures (p<0.05). The IG reported a high level of subjective commitment but a low level of satisfaction and usability regarding the digital service received. Conclusions: Digital service for mental health self-care is effective in reducing mental health problems in members of a public university. However, its design should be optimized to improve its usability and satisfaction. Clinical Trial: The clinical trial protocol was registered on the OSF platform (https://osf.io/m4epv/).
Background: Urticaria is a prevalent disease characterized by the appearance of wheals and/or angioedema. The transient, frequently intermittent wheals cause severe pruritus and have a significant imp...
Background: Urticaria is a prevalent disease characterized by the appearance of wheals and/or angioedema. The transient, frequently intermittent wheals cause severe pruritus and have a significant impact on the lives of those affected. Effective disease management is the fundamental basis for successful treatment and a good quality of life. Mobile health applications (MHAs) have the potential to support patient care and can play an important role in this regard. Objective: This investigation sought to identify publicly accessible MHAs for patients diagnosed with chronic urticaria and assess their quality by evaluating user feedback from both patients and medical professionals. Methods: Two reviewers conducted a comprehensive search of the Apple App Store, Google Play Store, and the broader internet for MHAs for CSU. Apps had to support the German or English language, and focus on patient care. A single application was identified that satisfied the established inclusion criteria. The app was evaluated by 23 physicians and 16 patients using the Mobile App Rating Scale (MARS), the Usability Multi-Attribute Scale (uMARS), the German Mobile App Usability Questionnaire (G-MAUQ), and technology affinity tools (ATI and MDPQ-16). Results: This study identified a single patient-centered application for chronic spontaneous urticaria (CSU)—the CRUSE Control app—that met the inclusion criteria, from an initial selection of 15 proposed apps. The initial pool included several non-medical, non-CSU-specific, and non-patient-centered apps.
The quality of the CRUSE Control app was rated similarly by both patients and physicians, with a MARS score of 4.03 (SD 0.45) from physicians and a uMARS score of 4.06 (SD 0.40) from patients (p = 0.826). The only subcategory where patients rated the app significantly higher than physicians was functionality, with patients giving a score of 4.47 (SD 0.55) compared to 3.75 (SD 0.41) from physicians (p = 0.043).
Usability was assessed using the G-MAUQ, and no significant difference was found between the ratings of physicians (5.85, SD 0.71) and patients (5.76, SD 0.41) for the CRUSE Control app (p = 0.638).
Both physicians and CSU patients demonstrated similar overall affinity for technology, as indicated by the ATI, with physicians scoring 3.50 (SD 0.66) and patients scoring 4.00 (SD 0.88) (p = 0.050). MDPQ-16, which specifically measures affinity for technology use in mobile devices, yielded comparable results: physicians scored 4.81 (SD 0.26), while patients scored 4.74 (SD 0.45) (p = 0.601). Conclusions: There are few apps available for patients with CSU. The CRUSE Control app effectively monitors disease activity in CSU, receiving positive feedback from both patients and physicians. It supports self-management, disease control, and reduces physician workload, warranting further long-term testing and refinement.
Background: Declining medication adherence remains a critical healthcare issue, often assessed through unreliable self-reporting methods. Wearable devices (WDs) may offer an objective means to improve...
Background: Declining medication adherence remains a critical healthcare issue, often assessed through unreliable self-reporting methods. Wearable devices (WDs) may offer an objective means to improve adherence monitoring by continuously recording physiological and activity data. Objective: This study aimed to develop and internally validate personalized predictive models for identifying missed medication doses using WD-derived data. Methods: A 30-day prospective observational study was conducted with 8 participants who wore Apple Watches and used a dedicated iOS application. The application collected demographics, medication details, psychological factors, mealtimes, and daily missed dose events. WDs recorded time-series data (activity, heart rate, sleep) at 3-minute intervals. Data were aggregated into 1-hour segments, and lag (6- and 12-hour) as well as rolling (24-hour) features were generated. Light Gradient Boosting Machine models were constructed for each individual’s dosing regimen if the missed dose rate exceeded 20%. Two modeling approaches were compared: a Group Cross-Validation (CV) model that grouped data by day to avoid data leakage from rolling features, and a Non-rolling Feature model that excluded rolling features and used leave-one-out CV. F1 score, accuracy, recall, and precision were assessed. Results: Of the 15 enrolled participants, 8 completed the study; 4 had a missed dose rate above 20%. In these 4 individuals, the Group CV model achieved F1 scores of 0.435 to 0.902, accuracy ranging from 0.711 to 0.911, recall from 0.278 to 0.822, and precision of 1.000 for the most robust regimens. The Non-rolling Feature model yielded F1 scores of 0.667 to 0.910, accuracy ranging from 0.800 to 0.906, recall from 0.500 to 0.835, and precision of 1.000. Morning dosing regimens generally showed higher predictive performance than evening or afternoon. Time-series features, particularly those reflecting 6-, 12-, and 24-hour patterns, emerged as key predictors, indicating that physiological and lifestyle variations prior to dosing strongly influenced missed dose events. Conclusions: Personalized predictive models using WD-derived data demonstrated high precision for detecting missed medication doses, especially in morning and evening regimens. These findings underscore the feasibility of employing objective physiological and activity data to forecast nonadherence and highlight the role of lifestyle patterns in determining missed doses. Future work should involve larger populations for external validation, strategies to improve recall—especially for clinically critical medications—and careful consideration of real-world implementation challenges.
Background: Invasive coronary angiography (ICA) is the gold standard in the diagnosis of coronary artery disease (CAD). Being invasive, it carries rare but serious risks including myocardial infarctio...
Background: Invasive coronary angiography (ICA) is the gold standard in the diagnosis of coronary artery disease (CAD). Being invasive, it carries rare but serious risks including myocardial infarction, stroke, major bleeding and death. A large proportion of elective outpatients undergoing ICA have non-obstructive CAD, highlighting suboptimal use of this test. Coronary computed tomographic angiography (CCTA) is a non-invasive option that provides similar information with less risk, and is recommended as a first-line test for patients with low-to-intermediate risk of CAD. Leveraging artificial intelligence (AI) to appropriately direct patients to ICA or CCTA based on predicted probability of disease may improve efficiency and safety of diagnostic pathways. Objective: The CarDIA-AI study aims to evaluate whether AI-based risk assessment for obstructive CAD implemented within a centralized triage process can optimize the use of ICA in outpatients referred for non-urgent ICA. Methods: CarDIA-AI is a pragmatic, open-label, superiority randomized controlled trial involving two Canadian cardiac centres. A total of 252 adults referred for elective outpatient ICA will be randomized 1:1 to usual care (directly proceeding to ICA) or to triage using an AI-based CAD screening intervention. Participants in the intervention arm will have their ICA referral forms and medical charts reviewed and select details entered into a decision support tool that uses a LightGBM model to predict the probability of obstructive CAD and recommends CCTA or ICA accordingly. The primary outcome is the proportion of normal or non-obstructive CAD diagnosed via ICA. Secondary outcomes include the number of angiograms avoided and the diagnostic yield of ICA. Results: Recruitment began on January 9, 2025 and is expected to conclude in mid-2025. We expect to submit the results for publication in early 2026. Conclusions: CarDIA-AI will be the first randomized controlled trial employing AI to optimize patient selection for CCTA versus ICA, potentially improving diagnostic efficiency, avoiding unnecessary complications of ICA, and improving healthcare resource utilization. Clinical Trial: ClinicalTrials.gov NCT06648239; https://clinicaltrials.gov/study/NCT06648239/
Background: Mental health during pregnancy is a critical factor influencing maternal and fetal outcomes. Anxiety and depression affect up to 25% of pregnant women, with significant consequences for ma...
Background: Mental health during pregnancy is a critical factor influencing maternal and fetal outcomes. Anxiety and depression affect up to 25% of pregnant women, with significant consequences for maternal well-being and child development. Despite this, interventions during pregnancy remain limited, creating a need for innovative, accessible solutions. Objective: This study aimed to evaluate the effectiveness of an immersive virtual reality (IVR) eHealth intervention in reducing anxiety and depression symptoms during pregnancy. Methods: A two-arm, randomized controlled trial was conducted across five primary care centers in Catalonia, Spain, between October 2021 and May 2024. Participants (n=70) were pregnant women aged ≥18 years with moderate anxiety and depression symptoms (EPDS scores: 9-12) at 12–14 weeks of gestation. They were randomized (1:1) to an IVR intervention or standard care group. The intervention group engaged in daily 14-minute IVR mindfulness and relaxation sessions for six weeks. Mental health outcomes were assessed using the Edinburgh Postnatal Depression Scale (EPDS) and State-Trait Anxiety Inventory (STAI). Results: The intervention group demonstrated significant reductions in EPDS scores (mean decrease from 11.32 to 7.25; p<0.001) compared to an increase in the control group (mean increase from 11.32 to 16.23; p<0.001). Similarly, STAI scores improved markedly in the intervention group (coefficient: -30.47; 95% CI: -45.23 to -15.72; p<0.001), while the control group experienced negligible changes. High adherence rates were observed, with 78.8% of participants completing ≥30 sessions. Participant satisfaction was high, with 87% reporting being "very satisfied" with the intervention. Conclusions: The IVR eHealth intervention significantly reduced symptoms of anxiety and depression, demonstrating its potential as an accessible and effective tool for mental health support during pregnancy. High adherence and satisfaction levels underscore its feasibility and acceptability. Future research should explore the long-term effects and scalability of IVR interventions in diverse settings. Clinical Trial: ClinicalTrials.gov NCT05756205
Background: Type 1 Diabetes (T1D) is one of the most common chronic conditions diagnosed during childhood. When a child is first diagnosed with T1D the parent is the primary manager of the condition,...
Background: Type 1 Diabetes (T1D) is one of the most common chronic conditions diagnosed during childhood. When a child is first diagnosed with T1D the parent is the primary manager of the condition, the responsibility begins to switch over to the child during adolescence. Resources to help children with T1D begin to learn about managing during pre-adolescence (8-12 years) will allow them to practice diabetes management skills. By applying serious game mechanisms to virtual reality (VR), it creates an opportunity for pre-adolescents with T1D to practice managing diabetes in a safe and virtual environment. Objective: The goal of this paper was to interview clinical staff to identify themes of T1D management skills for pre-adolescents and to utilize their expertise for designing a skill building VR game. Methods: We conducted 30-minute interviews with 9 clinical staff who manage pediatric patients with T1D to better understand their perspectives about the transition process and their experiences with engaging with diabetes technology. To identify common themes and ideas, the interview data was transcribed, and a pattern coding technique and thematic analysis were applied. Results: Three common themes emerged from the data. The first theme was that peers can influence medical adherence. Secondly, youth naturally seek autonomy and independence during the pre-adolescence years. Lastly, parental interactions impact transition style. Clinical staff suggested personalized gaming options, multi-functionality of avatars, skills, scenarios, and data sharing. Conclusions: Serious games for VR during the pre-adolescent years may allow youths to build a skill set and open conversations on how virtual reality technology can promote adherence to personalized treatment plans in pre-adolescent youth with T1D. Our results lend support that games should include a first-person avatar interacting with other characters, which would contribute components of autonomy and relatedness to the skill-building competency featured in existing T1D serious games.
Background: This study compared the professionalism, readability, and patient education quality of AI-generated responses (ChatGPT and Gemini) with the American Society of Anesthesiologists (ASA) webs...
Background: This study compared the professionalism, readability, and patient education quality of AI-generated responses (ChatGPT and Gemini) with the American Society of Anesthesiologists (ASA) website for eight frequently asked hysterectomy questions Objective: To compare the differences in professionalism, readability, and patient education quality between AI (ChatGPT and Gemini) and the American Society of Anesthesiologists (ASA) website when answering eight common hysterectomy questions, and to evaluate whether AI - generated content can serve as a reliable source of patient education for hysterectomy. Methods: Blinded experts evaluated professionalism, while six readability indices and the Patient Education Materials Assessment Tool (PEMAT) were used to assess content quality. Statistical comparisons were performed with p < 0.05 considered significant. Results: ChatGPT and Gemini demonstrated significantly higher professionalism scores than the ASA website (p < 0.05), but their readability was lower (p < 0.05). There were no significant differences in professionalism or readability between ChatGPT and Gemini (p > 0.05). Although AI-generated responses aligned with clinical guidelines, limited readability remains a concern. Conclusions: AI-driven content provides professional and accurate patient education on hysterectomy. However, further refinements are needed to improve accessibility without compromising quality. Clinical Trial: No patient personal information, clinical data, or health records were involved; therefore, ethical committee approval was not required.
Background: VOCs are a diverse group of organic chemicals with widespread presence in daily life. VOCs may have detrimental health effects on humans, particularly during critical periods such as pregn...
Background: VOCs are a diverse group of organic chemicals with widespread presence in daily life. VOCs may have detrimental health effects on humans, particularly during critical periods such as pregnancy, childhood, and adolescence. Objective: This ongoing scoping review aims to map the current evidence concerning exposure to volatile organic compounds (VOCs) and associations with pregnancy outcomes and health during pregnancy, childhood, and adolescence. Methods: This review will consider studies investigating potential health effects related to exposures to either total VOCs or any of the following six specific VOCs: Benzene, Toluene, Ethylbenzene, Xylene, Trichloroethylene (TCE), and Tetrachloroethylene/perchloroethylene (PCE) during critical windows from pregnancy through adolescence. Original articles published in English from January 1, 2000, through the end of the scoping review period, will be included. This review will follow the JBI methodology for scoping reviews, and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR). The literature search will use Ovid Medline, Embase, and Web of Science databases. Two reviewers will screen and extract the information separately; in case of discrepancy, both will discuss to reach a consensus, and a third reviewer may intervene if needed. Reviewers will provide commentaries of their findings from the included studies and suggest areas of interest for future studies. Results: The literature search yielded 7332 citations with screening underway. After data extraction and a complementary literature search, the results will be submitted for publication in a peer-reviewed journal. Conclusions: The results are expected to summarize the current state of knowledge on the association of VOCs with health at critical life stages (pregnancy, childhood, and adolescence). We anticipate identifying gaps in the literature as well that could guide future research priorities. Clinical Trial: Protocol registration (Open Science Framework): https://osf.io/ep73g
Introduction. Electronic Cigarette (e-cigarette) use is a major public health problem and young adults age 18-24 are at high risk. In addition to e-cigarettes, oral nicotine products (ONP) are growing...
Introduction. Electronic Cigarette (e-cigarette) use is a major public health problem and young adults age 18-24 are at high risk. In addition to e-cigarettes, oral nicotine products (ONP) are growing in popularity in this population. Poly-use is widespread. New methodologies for rigorous online studies using social media have been conducted and shown to reduce nicotine use. This study reports on the design and baseline evaluation of a large-scale social media based randomized controlled trial to evaluate the effects of anti-vaping social media on young adult vaping and determinants of use.
Methods. Using the Virtual Lab social media platform, participants were recruited into the study using an artificial intelligence (AI) chatbot and social media advertising, completed a baseline survey, and were then randomized to 1 of the 4 study arms. The design was to achieve specific numbers of impressions per arm over three survey time points. We recruited N=8,437 participants in total, stratified by vaper (5,026) and non-vaper status (3,321). Questionnaire data were collected using the Qualtrics survey platform. Future analyses will examine the effects of social media content on vaping at endline. Current data analysis presented here describes the two cohort samples; examines balance across the four study arms on baseline variables in each of the cohorts; and evaluates the internal consistency of several multi-indicator measures of psychosocial constructs.
Results. Among vapers, almost three-quarters were current vapers, over 40% were current smokers (use in the past 30 days), and over 48% were current poly-users (using e-cigarettes and one or more other tobacco products). Substantial numbers of current vapers also currently used some other product, including cigars (30.2%), hookah (15.8%), smokeless (9.2%), and oral nicotine products (11.5%). The average age of participants was 21.2 years. Just under 45% of participants were non-Hispanic white (44.7%), just under 47% (46.9%) of the sample was male, over 44% (44.4%) reported completing high school, and 79.3% reported meeting basic needs or better. There were no significance differences between arms/strata by any of these demographics. We also calculated scale scores for depression and co-variates related to nicotine use and found high alphas. Finally, we found that participants who reported having seen anti-tobacco brand advertising were more likely to higher levels of these variables/scales than participants who reported not having seen the advertising. These results will be examined in future studies.
Discussion. Social media can be used as a platform at scale for longitudinal RCTs over extended periods of time, which extends previous research on short-term trials. Interventions delivered by social media can be used with large samples to evaluate social media health behavior change interventions. Future studies based on this research will evaluate intervention effects of social media exposure on vaping behavior and determinants.
Among the countless decisions healthcare providers make daily, many clinical scenarios do not have clear guidelines, despite a recent shift towards the practice of evidence-based medicine. Even in cli...
Among the countless decisions healthcare providers make daily, many clinical scenarios do not have clear guidelines, despite a recent shift towards the practice of evidence-based medicine. Even in clinical scenarios where guidelines do exist, these guidelines do not universally recommend one treatment option over others. As a result, the limitations of existing guidelines presumably create an inherent variability in provider decision-making and the corresponding distribution of provider behavioral variability in a clinical scenario, and such variability differs across clinical scenarios. We define this variability as a marker of provider uncertainty, where scenarios with a wide distribution of provider behaviors have more uncertainty than scenarios with a narrower provider behavior distribution. We propose four exploratory analyses of provider uncertainty: (1) field-wide overview; (2) subgroup analysis; (3) provider guideline adherence; and (4) pre-/post-intervention evaluation. We also propose that uncertainty analysis can also be used to help guide interventions in focusing on clinical decisions with the highest amounts of provider uncertainty and therefore the greatest opportunity to improve care.
Background: Mobile apps are increasingly being used to manage cancer, however not without challenges. Despite their potential, evidence on the actual use of mobile technologies within the cancer care...
Background: Mobile apps are increasingly being used to manage cancer, however not without challenges. Despite their potential, evidence on the actual use of mobile technologies within the cancer care context is not adequate. Areas of concern include healthcare professionals’ (HCP) challenges in identifying the most suitable applications for their specific needs, as well as in evaluating these apps' quality and clinical effectiveness. Objective: The present study aims to: (a) map the landscape of free mobile apps for cancer prevention, treatment, therapy, or support for HCPs, and (b) assess the quality of the applications identified Methods: A systematic search of apps in Google Play and the AppStore was conducted according to predefined keywords words and applying the PRISMA guidelines. Searches were performed in May 2023 and November 2024. Apps were independently assessed by two reviewers using the Mobile App Rating Scale (MARS). Results: The search identified 221 apps. After the screening phase, 20 mobile apps that met the inclusion criteria were evaluated and prioritized by MARS peer review. The mean score was 3.51, with only two applications exceeding the 4-point threshold, which is considered to indicate a ‘good’ level of quality Conclusions: This study provides a ranking of cancer-related apps for HCPs, detailing the strengths and limitations of each to aid in curating useful digital resources. Despite the generally low quality observed, the ONCOassist app showed notable potential utility. The findings underscore a lack of robust evidence in current literature supporting the effectiveness of health apps for cancer care.
Background: Mental health problems are a barrier to the wellbeing of youth living with HIV (YLWH). Many YLWH in Nigeria face peculiar bio-psycho-social vulnerabilities that predispose them to mental h...
Background: Mental health problems are a barrier to the wellbeing of youth living with HIV (YLWH). Many YLWH in Nigeria face peculiar bio-psycho-social vulnerabilities that predispose them to mental health problems including depression and substance use. In addition to improving treatment outcomes like medication adherence and linkage to care, peer engagement has shown some promise in improving the social and emotional wellbeing of this population. Mobile health (mHealth) interventions like SMS may also contribute to better outcomes in YLWH. Emerging evidence suggests that combination interventions may be more effective than single interventions in improving key HIV testing and treatment outcomes among youth in Nigeria. Objective: To explore the impact of Intensive Combination Approach to Rollback the Epidemic in Nigerian Adolescents Study (iCARE Nigeria)— an mHealth+peer navigation intervention primarily aimed at medication adherence and viral suppression— on depressive symptoms and substance use among YLWH in Nigeria. Methods: A single-arm clinical trial was conducted at the Infectious Disease Institute (IDI), College of Medicine, University of Ibadan, Nigeria— primarily to improve medication adherence and viral suppression among YLWH attending its HIV clinic. The intervention combined peer navigation and daily, two-way, text message medication reminders delivered over a period of 48 weeks. Participants were screened at baseline and follow-up visits (24 and 48 weeks) for depression and substance use using standardized measures. Paired t-tests and McNemar’s tests were used to investigate the change in depressive symptoms and the change in the proportion of participants reporting substance use over time, respectively. Results: All 40 enrolled participants (50% male; mean age 19.9, SD 2.5 years) completed baseline and follow-up visits at week 24, while 37 (92.5%) participants completed the week 48 visit. Compared with baseline, there were significantly fewer self-reported depressive symptoms observed at 48 weeks (t36=2.04, P=0.048) but not at 24 weeks (t36=0.47, P=0.644). There were fewer self-reports of substance use at weeks 24 and 48 when compared to baseline, but these were not statistically significant (P=0.50 and P=0.625 respectively). Conclusions: These findings suggest a reduction in depressive symptoms among YLWH over the 48-week intervention period that may be partly due to the iCARE Nigeria intervention.
Background: Wearables are increasingly used in pediatric cardiology for heart rate (HR) monitoring due to advantages over traditional heart rate monitoring, such as prolonged monitoring time, increase...
Background: Wearables are increasingly used in pediatric cardiology for heart rate (HR) monitoring due to advantages over traditional heart rate monitoring, such as prolonged monitoring time, increased patient comfort and ease of use. However, their validation in this population is limited. Objective: This study investigates the HR accuracy and validity of two wearables, the CardioWatch bracelet and Hexoskin shirt, in children attending the pediatric cardiology outpatient clinic. In addition, factors that influence HR accuracy, the Hexoskin shirt's arrhythmia detection efficacy, and patient satisfaction are investigated. Methods: Children indicated for a 24h-Holter ECG were equipped with a 24h-Holter ECG (gold standard), together with both wearables. HR accuracy was defined as percentage of HRs within 10% of Holter values and agreement was assessed using Bland-Altman analysis. Subgroup analyses were conducted based on body mass index (BMI), age and time of wearing, among other factors. A blinded pediatric cardiologist analysed Hexoskin shirt data for rhythm classification. Patient satisfaction was measured using a 5-point Likert-scale questionnaire. Results: Thirty-one participants (mean age 13.2±3.6 years; 45% female) and thirty-six (mean age 13,3±3,9) participants were included for the CardioWatch and Hexoskin measurements respectively. Mean accuracy was 84.8% (±8.7%) for the CardioWatch and 87.4% (±11.0%) for the Hexoskin shirt. Hexoskin shirt accuracy was notably higher in the first 12 hours (94.9±7.4%) compared to the latter 12 (80.0±16.7%, P<.001). Higher accuracy was observed at lower HRs (low vs. high HR: CardioWatch: 90.9±9.3% vs. 79.0±10.6%, P<.001; Hexoskin shirt: 90.6±14.0% vs. 84.5±11.8%, P<.001). Both wearables demonstrated good agreement in their HR measurement with Holter readings (CardioWatch bias: –1.4 beats per minute [BPM]; 95% Limits of Agreement [LoA]: –18.8 to 16.0. Hexoskin shirt bias: –1.1 BPM; 95% LoA: -19.6 to 17.4). Correct classification of the Hexoskin’s shirt rhythm recordings was achieved in 86% (31/36) of cases. Patient satisfaction scores (median[range]) were significantly higher for both the CardioWatch (3.8[3.5–4.3], P<.001) and Hexoskin shirt (3.7 [3.0–4.0], p<0.001) compared to the Holter ECG (2.6 [2.1-3.2]). Conclusions: The Corsano CardioWatch and Hexoskin shirt demonstrate good accuracy in pediatric HR monitoring and provide higher patient comfort than conventional monitoring. Both wearables show good agreement in relation to the gold standard device. However more research is needed to explore the reasons for inaccuracy during higher heart rates. The Hexoskin shirt also shows potential in arrhythmia detection. While further development is warranted, these wearables show promise in enhancing diagnostics, therapeutic monitoring and patient safety in pediatric cardiology.
Background: Digital health interventions based on self-management strategies aim to empower users’ self-reliance by utilizing self-monitoring, self-assessment and sensor-based output. The existing v...
Background: Digital health interventions based on self-management strategies aim to empower users’ self-reliance by utilizing self-monitoring, self-assessment and sensor-based output. The existing variety of digital devices utilizes a wide range of data sources and sensors to collect and monitor users’ output while little comparative data on parameter reliability and utility is available. Objective: This review aims to address the existing methodological and knowledge gap in understanding the efficient common parameters used among digital health interventions for depression that allow precise monitoring and prediction of the course of depression across different modes of digital intervention delivery. Methods: Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews digital databases including PubMed, Embase, Cochrane Library and Web of Science Core Collection were scoped for literature ranging from 2021 to 2024. A five-stage framework by Arksey and O’Malley (2005) was implemented to ensure systematic scoping of the literature. The quality of the retrieved studies was assessed using the Downs and Black Instrument and the Mixed Methods Appraisal Tool. Results: The overall five interdependent categories were defined including 1) Physical activity and Location, 2) Behavioural patterns, 3) Physiological data, 4) Sleep, and 5) Sociability and Self-reported assessments to best describe common assessment parameters across the literature. Eleven common clinical measures and self-report assessments were distinguished across defined categories as assessment combined with digital phenotyping methodology. Conclusions: Synthesis of result sections of the included studies indicated that predicting depressive symptoms by combining clinical assessment and digital phenotyping is a promising approach for further improvement of digital interventions. The overall strongest associations were found in combined approaches using parameters across categories combining sensor data and self-report assessment.
Background: Mycosis fungoides (MF) is the most prevalent type of cutaneous T-cell lymphoma, with a broad spectrum of clinical and histopathological variants. Among these, pigmented purpuric dermatosis...
Background: Mycosis fungoides (MF) is the most prevalent type of cutaneous T-cell lymphoma, with a broad spectrum of clinical and histopathological variants. Among these, pigmented purpuric dermatosis-like MF (PPD-like MF) is an extremely rare subtype that mimics benign pigmented purpuric dermatoses (PPD), posing diagnostic and therapeutic challenges. Objective: To comprehensively review the clinicopathological features, diagnosis, and treatment of PPD-like MF through an analysis of reported cases. Methods: To conduct a thorough review of the existing literature on pigmented purpuric dermatosis-like mycosis fungoides (PPD-like MF), a systematic and comprehensive search strategy was employed. The literature search was performed in August 2024, utilizing the electronic databases MEDLINE (via PubMed) and Google Scholar. Results: Fourteen studies encompassing 21 patients were identified. The mean age of patients was 33.9 years, with a male predominance (76.2%). Lesions predominantly affected the lower extremities (61.9%) and were characterized by erythematous macules, patches, petechiae, and purpuric lesions. Treatment responses varied, with phototherapy (PUVA) and methotrexate being the most effective modalities in the documented cases. Conclusions: PPD-like MF is a rare and challenging variant of MF, requiring a high index of suspicion and careful histopathological evaluation for diagnosis. Awareness of its distinct clinical and pathological features is essential for appropriate management.
Background: Patient similarity is a fundamental concept in precision oncology, offering a pathway to personalized medicine by identifying patterns and shared characteristics among patients. This conce...
Background: Patient similarity is a fundamental concept in precision oncology, offering a pathway to personalized medicine by identifying patterns and shared characteristics among patients. This concept enables stratification into clinically meaningful subgroups, prediction of treatment responses, and the tailoring of therapeutic interventions to individual needs. Despite its transformative potential, the definition, measurement, and clinical application of patient similarity remains inconsistently established, creating challenges in its integration into cancer research and clinical practice. Objective: The goal of this scoping review is to synthesize evidence on the multidimensional concept of patient similarity in cancer research by analyzing its application across different points of possible data types, methodological frameworks, biological contexts, and commonly studied cancer types. Methods: This scoping review followed the PRISMA-ScR framework and the Joanna Briggs Institute guidelines. A systematic search was conducted across PubMed, MEDLINE, LIVIVO, and Web of Science (1998-February 2024), supplemented by snowball sampling and manual searches. Duplicate records were removed, and study selection was carried out in three phases: title and abstract screening, disagreement resolution, and full-text screening. Each step was independently performed by two reviewers in Rayyan, with conflicts resolved by a third reviewer. Data extraction was performed using a predefined template to capture methodological approaches, data types, cancer types, and research objectives related to cancer patient similarity. Results: This scoping review synthesized evidence from 137 studies, emphasizing the multidimensional concept of patient similarity in cancer research, which integrates diverse data types, methodological frameworks, research objectives, and cancer types. Transcriptomic data (67.1%, 92/137) and clinical data (47.4%, 65/137) were the most frequently used, often combined to enhance the comprehensiveness of similarity analyses. Machine learning (55.5%, 76/137) and network-based approaches (52.5%, 72/137) were prominent methods, reflecting their capacity to handle complex, high-dimensional data and uncover intricate relationships. Cancer subtype identification (51.1%, 70/137) and biomarker discovery (29.9%, 41/137) were the primary research objectives, underscoring the centrality of patient similarity in precision oncology. Breast, lung, and brain cancers were the most frequently studied, benefiting from established research frameworks and abundant datasets. Conversely, rare cancers were underrepresented, highlighting a critical gap in the generalizability of current methodologies. Conclusions: This comprehensive scoping review examines the concept of patient similarity in cancer research and highlights the critical role of a multi-layered perspective in capturing its complexity and identification to enhance understanding and application in precision oncology.
Background: Despite extensive research into technology users' privacy concerns, a critical gap remains in understanding why individuals adopt varying standards for data protection across different con...
Background: Despite extensive research into technology users' privacy concerns, a critical gap remains in understanding why individuals adopt varying standards for data protection across different contexts. The emergence of advanced technologies such as the Internet of Things (IoT), artificial intelligence (AI), augmented reality (AR), and Big Data has created rapidly evolving and complex privacy landscapes. However, privacy is frequently treated as a static construct, failing to capture the fluid and context-dependent nature of user concerns. This oversimplification has led to fragmented research, inconsistent findings, and a limited ability to address the nuanced challenges posed by these technologies. Understanding these dynamics is particularly crucial in fields such as digital health and informatics, where sensitive data and user trust are central to technology adoption and ethical innovation. Objective: This study synthesizes existing research on privacy behaviors in emerging technologies, focusing on IoT, AI, AR, and Big Data. Its primary objectives are to identify the psychological antecedents, outcomes, and theoretical frameworks that explain privacy behavior, and to evaluate whether insights from traditional online privacy literature—such as those from e-commerce and social networking sites—apply to these advanced technologies. Additionally, the study advocates for a context-dependent approach to understanding privacy. Methods: In this study, we find that privacy is a context-dependent and fluid concept. A systematic literature review of 179 studies was conducted to synthesize psychological antecedents, outcomes, and theoretical frameworks related to privacy behaviors in emerging technologies. The review followed established guidelines, utilizing leading research databases. Studies were screened for relevance to privacy behaviors, focus on emerging technologies, and empirical grounding, with methodological details analyzed to assess the applicability of traditional privacy findings—e.g., in contexts such as e-commerce and social networking sites—to current cutting-edge technologies. Results: The systematic review reveals significant gaps in the existing privacy literature regarding emerging technologies such as IoT, AI, AR, and Big Data. Contextual dimensions, including data sensitivity, recipient transparency, and transmission principles, are frequently overlooked despite their critical role in shaping privacy concerns and behaviors. The findings also highlight that privacy theories developed for traditional technologies often fail to account for the unique complexities of cutting-edge contexts. By synthesizing psychological antecedents, behavioral outcomes, and theoretical frameworks, this study underscores the need for a context-contingent approach to privacy research. Conclusions: This study advances the understanding of user privacy by emphasizing the critical role of contextual factors in data-sharing scenarios, particularly in the age of ubiquitous and emerging health-related technologies. The findings challenge static interpretations of privacy and highlight the need for tailored frameworks that address dynamic, context-dependent privacy behaviors. Practical implications include guiding healthcare providers, policymakers, and technology developers toward context-sensitive strategies that build trust, enhance data protection, and support the ethical development of digital health practices.
Background: Improved processes around the management of Electronic Health Record (EHR) requests for chronic antihypertensive medication renewals may represent an opportunity to improve blood pressure...
Background: Improved processes around the management of Electronic Health Record (EHR) requests for chronic antihypertensive medication renewals may represent an opportunity to improve blood pressure management at the individual and population level. Objective: This study aimed to evaluate the effectiveness of The eRx HTN Chart Check, an integrated clinical decision support tool available at the point of antihypertensive medication refill request, to facilitate enhanced provider management of chronic hypertension. Methods: The study was conducted at 2 Mayo Clinic sites, Northwest Wisconsin Family Medicine and Rochester Community Internal Medicine practices, with control groups in comparable Mayo Clinic practices. The intervention integrated structured clinical data, including recent blood pressure readings, lab results, and visit dates, into the electronic prescription renewal interface to facilitate prescriber decision making around hypertension management. A Difference-in-Differences (DID) design compared pre- and post-intervention hypertension control rates in the intervention and control groups. Data were collected from the Epic EHR system and analyzed using linear regression models. Results: The baseline blood pressure control rates were slightly higher in intervention clinics. Post-implementation, no significant improvement in population-level hypertension control was observed (DID estimate: 0.07%, 95% CI: -4.0% to 4.1%; p = 0.973). Of the 19,968 refill requests processed, 46% passed all monitoring criteria. However, clinician approval rates remained high (90%), indicating minimal impact on prescribing behavior. Conclusions: Despite successful implementation of the eRx HTN Chart check tool, exposed practices did not see significant improvements in hypertension control, possibly due to competing quality initiatives and high in-basket volumes. Future iterations should focus on enhanced integration with other decision support tools and strategies to improve clinician engagement and patient outcomes. Further research is needed to optimize chronic disease management through EHR-integrated decision support systems. Clinical Trial: N/A
Background: The population of young individuals not in employment, education or training (NEET) are highly diverse but a common problem appears to be their mental health. NEETs due to illness or disab...
Background: The population of young individuals not in employment, education or training (NEET) are highly diverse but a common problem appears to be their mental health. NEETs due to illness or disability are of particular concern for social exclusion but little is known of how NEET with and without disability make use of, and gain from, employment interventions. There is also a scarcity of research on psychological interventions and mental health outcomes on NEET individuals. Acceptance and commitment therapy (ACT) has shown promising results on psychological outcomes on young adults. Objective: The study aimed to expand the knowledge on effects of an app-based intervention built on ACT on NEETs with and without disability. Methods: A two-armed randomized controlled trial was conducted in 2021 including 151 NEET individuals 16-24 years. Participants were recruited mainly via social media platforms and through organizations working with NEET individuals. The intervention group (n=77) used an app for psychological well-being with possibility for digital group meetings for 6 weeks and the control group (n=74) received film clips once a week. Outcomes were self-assessed through questionnaires. Statistical analyses were made using Chi2, Mann-Whitney U-test, GLM and logistic regression. Results: No differences in effects on mental health were seen between intervention and control group, neither overall nor between NEET individuals with or without disability. Usage data show that 68.6% of the participants in the intervention group downloaded the app and 24.7% completed all six modules. Effects on employment and education levels were only seen within the intervention group where those that had completed one or more modules had higher likelihood of being active in terms of employment and education compared to those that did not complete modules. No significant effects were seen in employment and education levels in relation to disability status. A high proportion of the participants had a disability, few were in contact with a youth employment center and female participants were overrepresented in general. Participants with disabilities had lower self-esteem, had less frequently completed high school, fewer had work experience and a larger proportion had been in the NEET situation over a year. A higher drop-out were seen among participants in the intervention group and among male participants. Conclusions: No effects of the app-based intervention were seen for psychological well-being between NEET individuals with disability and those without, but the results showed potential effects on employment and education levels related to engagement in the intervention. NEETs with disability are of particular concern and might need additional efforts or other types of interventions than the one investigated herein. Findings can be considered weak due to the low adherence and high attrition. Clinical Trial: Registered on 12 February 2021 at ISRCTN (#ISRCTN46697028), https://doi.org/10.1186/ISRCTN46697028
Background: The Fast Healthcare Interoperability Resources (FHIR) standard is now well established as a global standard for healthcare information exchange. The value of FHIR is also being actively e...
Background: The Fast Healthcare Interoperability Resources (FHIR) standard is now well established as a global standard for healthcare information exchange. The value of FHIR is also being actively explored to support clinical and healthcare research in areas such as observational studies using “real world data” (RWD) and in clinical studies intended for regulatory submissions where it plays a key role in enabling direct data capture from clinical sites. The goal of the work for clinical trials is to use FHIR resources to define study schedules of activities (SoA) to support operational implementation at research sites. A HL7 FHIR Implementation Guide (IG) has been published that can define basic SoAs, but this does not offer solutions to define some types of study scheduling (e.g. treatment cycles) or other scheduling requirements (e.g. conditional switching such as that found in vaccine studies) Objective: The objective of this work was to re-investigate how the FHIR definitional resources, particularly PlanDefinition might be extended or revised to enable the model to cover the wider range of SoA scheduling requirements that are commonly encountered in clinical research studies. Methods: A previously described SoA graph model was used to investigate, extend and test the fundamental requirements for SoA definitions modelling the complex and conditional requirements outlined above. These requirements were then defined/reflected as FHIR definitional resources with, where necessary, FHIR permitted technical solutions (extensions, value sets, etc.). Specification accuracy was tested by comparing the SoA graph model attributes and relationships with those able to be recovered from the FHIR specifications. Results: Using confirmed graph-based models of clinical SoAs, a SoA FHIR model based on the PlanDefinition resource was developed that can model simple, complex and conditional SoA requirements for a wide variety of SoA use cases. Using example and publically available study SoAs, the SoA FHIR model was able to accurately specify a large range of commonly met study scheduling requirements. Conclusions: A FHIR model for the specification of clinical trial SoAs has been developed that offers a more comprehensive set of scheduling requirements to be defined than previously considered. Particularly it implements methods for specifying conditional scheduling requirements, and clearly separates SoA activity definition from the study scheduling requirments.
Background: Despite stillbirth being the critical quality measure for care during pregnancy and childbirth, it is often overlooked especially amongst marginalized populations. Our study aims to add to...
Background: Despite stillbirth being the critical quality measure for care during pregnancy and childbirth, it is often overlooked especially amongst marginalized populations. Our study aims to add to the limited body of knowledge on stillbirth determinants and barriers to stillbirth data availability, in tribal populations. Objective: The study objectives are; 1) to determine the factors associated with stillbirth, 2) to review the stillbirth reporting system and identify existing barriers, and 3) to make recommendations to address the determinants and improve the stillbirth reporting system in the study area. Methods: A mixed-methods approach integrating aspects of, both, quantitative and qualitative designs is adopted for the study. The quantitative component will be a population-based, matched case-control study with case to control ratio of 1:2. A total of 450 participants i.e. 150 cases and 300 controls will be included. Cases will be the tribal women in age group 15-49 years who delivered a stillborn in last one year. Selection of cases will be based on WHO definition of late fetal deaths i.e. third trimester stillbirths at > 28 completed weeks of gestation. The controls will be the tribal women (15-49 years) who delivered a live baby irrespective of gestation period but during the similar time period. Both cases and controls will be selected randomly from all the six blocks of Jhabua district of Madhya Pradesh, India. The qualitative component will include four focused group discussions and 22 in-depth interviews with various stakeholders. The study has been approved by Research Advisory Board of IIHMR Delhi and is approved at participating study site too. Results: The data collection will take approximately three months and will start from February 2025. The study is scheduled from February 2025 to January 2026. Statistical analysis will be performed on collected data utilizing SPSS V.21.0. Univariate logistic regression will be performed for each independent variable to estimate crude odds ratio at 95% confidence interval. Sensitivity analysis will be carried out to assess the impact of missing data, if any. For qualitative data, we will use ATLAS.ti software to assign preliminary codes. Deductive approach will be utilized for development of themes. The findings of both, quantitative data and qualitative data will be integrated using a mixed-methods matrix. We plan to publish our results in a peer-reviewed journal and present our findings at academic conferences. Conclusions: The study is expected to generate evidence on the gravity of situation in the tribal population of Jhabua district. The critical findings of the study and exploration into association between variables will inform the targeted interventions and policy recommendations to enhance stillbirth surveillance and reporting systems in marginalized communities. The results will be instrumental in addressing data gaps and fostering equitable healthcare practices in resource-limited settings. Clinical Trial: NA
Background: Childhood obesity is a public health concern associated with serious health issues. The food environment, which in recent year undergone widespread changes leading to an increase access to...
Background: Childhood obesity is a public health concern associated with serious health issues. The food environment, which in recent year undergone widespread changes leading to an increase access to ultra-processed foods (UPFs), has been given attention in relation to development of childhood obesity. One part of the food environment is food marketing. Studies from around the world, including Sweden, show that the food marketing landscape is dominated by foods associated with negative health outcomes. However, in previous studies the investigated areas have been determined by researchers. Objective: The aim of this study was to test a new child centric methodology to further advance the understanding of the outdoor food advertisement landscape in Sweden. Methods: A cross sectional study was performed in two Swedish counties (Stockholm and Gävleborg). Initially, 45 students from four schools in areas with varying SES used a smartphone application (app) to take pictures of food advertisements that they encountered in their everyday lives. The app also recorded the GPS location of where the pictures were taken. Pictures with associated GPS-data were automatically uploaded and visualised in a secure cloud-based dashboard allowing for identification of areas where children see many food advertisements, so called “hotspot areas”. The identified hotspot areas were subsequently visited by two researchers who systematically mapped all the food advertisements in the areas using cameras. All pictures of food advertisements taken by the researchers in the hotspot areas were later analysed based on their content of UPFs, health promoting foods such as fruit, berries, vegetables and seafood (FBVS) as well as price promotions. Results: Based on 1310 pictures of food advertisements taken by the students, 34 hotspot areas were identified. A total of 2955 pictures of food advertisements were taken by the researchers in the hotspot areas during the mapping activity. The results of the picture analysis showed that 78 % of the advertisements contained UPFs and 21 % contained FBVS. Out of all food advertisement in all areas combined, 24% contained a price promotion. Out of all price promotions, 74 % advertised UPFs and 20 % advertised FBVS. Conclusions: This study showed that the vast majority of outdoor food advertisements in areas where children spend time advertise UPFs and only a 21 % advertise health promoting food such as FBVS. The findings continues to highlight that the food advertised in the Swedish outdoor environment is not in line with dietary guidelines and that it might be time to consider regulatory measures.
Background: Smart Home Technology (SHT) encompasses Internet-connected interfaces, sensors, monitors, devices, and appliances, which are networked together to allow for automation as well as control o...
Background: Smart Home Technology (SHT) encompasses Internet-connected interfaces, sensors, monitors, devices, and appliances, which are networked together to allow for automation as well as control of the home environment. They can facilitate tasks such as taking medication or send emergency fall alerts. However, their widespread use comes with concerns of power imbalances between users, technology companies, marketers, state actors, and others regarding data collection, its use and disclosure, as well as security issues such as the potential for data breaches. Despite this, little is known about how Canadians perceive and understand their SHTs. Given Canada’s unique demographic diversity and distinct context, examining Canadian perspectives is necessary to advancing this body of research. Objective: This paper explores user perceptions of SHTs in Canada with a focus on four themes: privacy, purpose of data collection, risks and benefits, and safety. Methods: An online cross-sectional survey was conducted between March 7 – April 24, 2023 across Canada to collect self-reported demographic information and perceptions around the four aforementioned themes through multiple-choice and optional short response questions. The quantitative data was exported into SPSS and Python programming language for further analysis. Results: Survey data from a total of 881 SHT users was analysed. The presence of privacy cynicism was displayed via user mistrust (294/881, 33%), uncertainty (281/881, 32%), powerlessness (325/881, 37%), and digital resignation (232/881, 26%) as self-reported by users. Many users displayed a willingness to trade privacy for perceived benefits, such as convenience (503/881, 57%). Users also flagged enhanced safety and daily convenience as a beneficial feature of SHTs (492/881, 56%). Contrary to previous Internet or smart home research, most (801/881, 91%) participants reported having read their SHT Terms of Use documents upon setup. Conclusions: This study illustrates themes of privacy cynicism and digital resignation within Canadian users, which are prevalent within an emerging body of related literature on Internet platforms more generally, and highlights ways in which to mitigate these patterns. The gap between user privacy preferences and options underscores the need for stronger user-centric design and data protection regulation. These insights and suggestions provide valuable guidance for policymakers and industry stakeholders navigating the complex landscape of SHT adoption.
Antimicrobial resistance (AMR) presents a significant challenge to global public health, as overuse and misuse of antibiotics have led to the emergence of resistant bacteria, making infections more di...
Antimicrobial resistance (AMR) presents a significant challenge to global public health, as overuse and misuse of antibiotics have led to the emergence of resistant bacteria, making infections more difficult and expensive to treat. This article explores the rise of antibiotic resistance, its impact on treatment regimens, and case studies highlighting the emergence of resistant organisms like Klebsiella pneumoniae, Mycobacterium tuberculosis, and Enterococcus faecium. It examines the causes of AMR, including overprescription in healthcare, agricultural use of antibiotics, and inadequate infection control measures, alongside the economic and ecological implications. Recent advancements in research, such as new antibiotic development, bacteriophage therapy, and antimicrobial peptides, offer potential solutions, but the need for global collaboration and improved stewardship programs is crucial. The article stresses the importance of continued research, surveillance, and the development of alternative therapies to combat AMR and mitigate its widespread impact on both public health and the economy.
The management of human dissection labs and medical education are significantly impacted by the resurgence and spread of monkeypox (Mpox) as a global health issue, especially in Africa. Human dissecti...
The management of human dissection labs and medical education are significantly impacted by the resurgence and spread of monkeypox (Mpox) as a global health issue, especially in Africa. Human dissection, a crucial part of anatomical education, requires strict procedures to protect medical students and instructors from the spread of infectious diseases. This article highlights important hazards and biohazard concerns while examining the difficulties presented by the Mpox pandemic in the context of cadaveric dissection. Through a review of literature, institutional protocols and epidemiological data, we propose improved personal protective equipment (PPE) regulations and disinfection guidelines tailored for African medical facilities. This article highlights the need for capacity-building programs to equip educators and students with skills to manage infectious disease risks effectively. By tackling these challenges, we aim to advance medical education safely while contributing to discussions on public health emergency adaptations and fostering pandemic resilience.
Background: Endotoxin contamination in conventionally purified water poses serious risks to hemodialysis patients, leading to complications such as inflammation and sepsis. Addressing these risks is e...
Background: Endotoxin contamination in conventionally purified water poses serious risks to hemodialysis patients, leading to complications such as inflammation and sepsis. Addressing these risks is essential for enhancing patient safety and meeting global dialysis water quality standards. Advanced filtration technologies, such as titanium dioxide (TiO₂)-based nanoparticle filters, offer a promising approach to improve water purification processes in renal care. Objective: This study aimed to develop and evaluate the effectiveness of a TiO₂-based nanoparticle microporous filtration system for hemodialysis water purification. The objectives included analyzing the system's performance in reducing chemical contaminants (calcium, magnesium, aluminum, and lead) and microbiological contaminants (total viable count [TVC] and endotoxin units [EU]) across multiple renal centers. Methods: Water samples from three renal centers (RC1, RC2, and RC3) were analyzed pre- and post-filtration. TiO₂ nanoparticles were synthesized using the sol-gel method and characterized via Fourier Transform Infrared (FTIR) spectroscopy and Scanning Electron Microscopy with Energy Dispersive X-ray analysis (SEM/EDX). The microporous filter, fabricated with TiO₂ nanoparticles, silicon dioxide, and polyethylene glycol (PEG), was tested for its ability to remove contaminants. Analytical techniques included spectroscopy for chemical analysis and microbiological assays for contaminant quantification. Results: Post-treatment analysis revealed significant reductions in chemical contaminants, with removal efficiencies averaging 78% for calcium, 80% for magnesium, 81% for aluminum, and 76.6% for lead across all centers. Microbiological contamination was also substantially reduced, with 78–80% removal of TVC and 76–84.6% reduction in EU levels. FTIR analysis confirmed the presence of hydroxyl groups critical for adsorption, while SEM/EDX characterization revealed a crystalline structure with a particle size of 1.45 nm, pore size of 4.11 μm, filter height of 2.56 mm, and bulk density of 0.58 g/cm³. Conclusions: The TiO₂-based nanoparticle filtration system demonstrated high efficacy in removing chemical and microbiological contaminants, significantly improving water quality for hemodialysis. These results highlight its potential as a practical solution for renal centers, especially in resource-constrained settings. Further studies are needed to evaluate its long-term performance and feasibility for widespread adoption. Renal centers should consider adopting TiO₂-based nanoparticle filters to address persistent water quality challenges. Pilot implementations across diverse settings can provide insights into operational feasibility. Additional research should explore scalability, maintenance requirements, and cost-effectiveness to optimize integration into healthcare systems. This study introduces a practical and innovative solution to improve hemodialysis water purification. By effectively reducing both chemical and microbiological contaminants, the TiO₂-based filtration system has the potential to enhance patient safety and outcomes, particularly in settings where maintaining high water quality standards remains challenging.
Background: While mobile health applications (mHealth apps) have been made for various diseases, including sickle cell disease (SCD), most focus on a single purpose. SCD is a chronic disease that requ...
Background: While mobile health applications (mHealth apps) have been made for various diseases, including sickle cell disease (SCD), most focus on a single purpose. SCD is a chronic disease that requires knowledge of the disease, self-management, and adherence to treatment plans. While mHealth apps have been made with single features for SCD, there is limited understanding of using a mHealth app with a more comprehensive set of features that could engage adults with SCD depending on what features they prefer and need to engage and empower them in their disease. Objective: We evaluated the usage of a mHealth app with various features, including pain tracking, quizzes for patient-facing guidelines, pain and asthma action plans, and goal setting. Methods: Adults with SCD were enrolled at two sickle cell centers between 2018-2022 as part of a 6-month feasibility randomized controlled trial with participants completing surveys at baseline and 6 months. Participants were randomized into receiving either a mHealth app + booklet with patient-facing guidelines or a booklet with the guidelines alone. The mHealth app comprised web pages with patient-facing guideline material and a Research Electronic Data Capture (REDCap) project. The REDCap project included a personal profile, a pain tracker, goal setting, quizzes about the guidelines, and pain or asthma action plans. The REDCap project also included the ability to send daily text messages at a time they chose, which contained a message they could create and a link to their profile. Outcomes included SCD-specific knowledge and acute healthcare utilization (emergency room visits and hospitalizations). We evaluated the usage of these different features and relationships with baseline variables, each other, and study outcomes. Results: Approximately 75% (50 of 67) of the enrolled and randomized participants completed all the study components, and 100% (26 of 26) of the participants who were randomized to the mHealth app arm and completed the study used the mHealth app. Further, 15 (50%) participants used multiple features. Baseline sickle cell knowledge and female gender were associated with more usage of pain diary (p=0.04) and mission (p=0.046) features, respectively. While not significant, mission completion was associated with lower hospitalizations (p=0.063). Conclusions: Adults with SCD engaged differently with a mHealth app with multiple features. As this study was not focused on one part of our app, engagement with features in this app was entirely patient-driven, which may demonstrate the expected real-world use of a mHealth app in this population. A multipurpose app can help engage participants in self-management strategies through different features and potentially improve outcomes. Clinical Trial: This clinical trial is registered on https://clinicaltrials.gov/ with study ID: NCT03629678.
Background: Heart failure is a growing global health concern. Exergaming is a promising alternative to conventional exercise programs for patients with heart failure (HF). However, existing research h...
Background: Heart failure is a growing global health concern. Exergaming is a promising alternative to conventional exercise programs for patients with heart failure (HF). However, existing research has limitations, and the integration of exergaming into clinical practice remains challenging. Objective: The aims of this study were to design and develop an exergaming prototype (i.e., HEFMOB), which encompasses a lower limb aerobic exercise game and an upper limb coordination and mobilization game, and to assess the usability of the prototype. Methods: The usability evaluation had two phases: the initial assessment by the researchers, and the user-rated analysis of a single session by 10 patients (4 women) with HF. The sessions were recorded and individually evaluated by two researchers using the Serious Game Usability Evaluator (SGUE) tool. After each session, the participants completed the System Usability Scale (SUS) and a subscale of Intrinsic Motivation Inventory (IMI) to rate the usability of the exergaming prototype and enjoyment, respectively. Participants reported more negative events (e.g., confusion [n = 76]) than neutral (n = 49) and positive events (n = 11). Results: The mean ± standard deviation (SD) SUS score was 71.5 ± 17.8 and the mean ± SD IMI score was 25.1 ± 3.5, showing a good user-rated usability and high level of interest, respectively. Conclusions: HEFMOB represents a significant initial step in developing an exergaming prototype customized for CHF. HEFMOB seems usable, and participants experienced satisfaction in a single session. Future research is required to conclusively demonstrate the efficacy and effectiveness of HEFMOB.
This study investigates the behavioral dynamics of sociopaths, focusing on their reliance on glibness (superficial charm) as a primary manipulation tactic and aggressiveness as a secondary strategy wh...
This study investigates the behavioral dynamics of sociopaths, focusing on their reliance on glibness (superficial charm) as a primary manipulation tactic and aggressiveness as a secondary strategy when charm fails. Sociopathy, characterized by manipulative tendencies and a lack of empathy, often manifests in adaptive yet harmful behaviors aimed at maintaining control and dominance.
Using the Deenz Antisocial Personality Scale (DAPS-24) to collect data from 34 participants, this study examines the prevalence and interplay of these dual strategies. Findings reveal that sociopaths employ glibness to disarm and manipulate, transitioning to aggressiveness in response to resistance. The implications for understanding sociopathic manipulation are discussed, emphasizing the importance of early detection and intervention in both clinical and social contexts.
Background: Stroke is a leading cause of global disability, impacting patients' postural balance. Task-oriented training (TOT) is a method which is commonly used in neurological rehabilitation for the...
Background: Stroke is a leading cause of global disability, impacting patients' postural balance. Task-oriented training (TOT) is a method which is commonly used in neurological rehabilitation for the treatment of physical deficits, including balance dysfunction. Objective: This systematic review and meta-analysis were conducted to assess the efficacy of TOT in the rehabilitation of postural balance for stroke patients. Methods: Four electronic databases were systematically searched for relevant articles published up to May 2024. Randomized controlled trials (RCTs) that investigated the effects of TOT for participants with stroke were included. The risk of bias and the certainty of the evidence were assessed using the Cochrane collaboration’s tool and the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) guideline, respectively. Results: In total, 8 RCTs were included in this systematic review, with 7 (87.5%) providing information for the meta-analysis. A total of 534 participants were included. The statistical analysis showed favorable results for most balance-related outcomes except Berg balance scale (BBS) (MD 1.46, 95% CI −1.95 to 4.87; P=0.40; I2=94%). Subgroup differences were observed in BBS. Conclusions: Existing moderate evidence support that TOT is a beneficial nonpharmacological approach to improve postural balance in patients with stroke. However, the limited quantity and high heterogeneity of the articles limit our findings. Clinical Trial: PROSPERO CRD42024572258
Background: Stroke inevitably results in a range of disabilities. Both virtual reality (VR) and mirror therapy (MT) have shown efficacy in stroke rehabilitation. In recent years, the combination of th...
Background: Stroke inevitably results in a range of disabilities. Both virtual reality (VR) and mirror therapy (MT) have shown efficacy in stroke rehabilitation. In recent years, the combination of these two approaches has emerged as a potential treatment for stroke patients. Objective: This systematic review and meta-analysis aim to assess the efficacy of combination treatment of VR and MT in stroke rehabilitation. Methods: Five electronic databases were systematically searched for relevant articles published up to July 2024. Randomized controlled trials (RCTs) that investigated combination treatment of VR and MT for participants with stroke were included. The risk of bias and the certainty of the evidence were assessed using the Cochrane collaboration’s tool and the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) guideline, respectively. Results: A total of 293 participants across 10 RCTs were included, with 6 RCTs contributing to the meta-analysis. The statistical analysis indicated significant improvements in the Fugl-Meyer Assessment of Upper Extremity (FMA-UE) (MD 3.49, 95% CI 1.43 to 5.55; P=0.0009) and manual function test (MD 2.64, 95% CI 1.78 to 3.49; P<0.00001), and box and block test (MD 1.02, 95% CI 0.16 to 1.88; P=0.02). Subgroup differences were observed in FMA-UE, manual function test and box and block test. Conclusions: Moderate-quality evidence supports the combination treatment of VR and MT as a beneficial nonpharmacological approach to improve upper extremity motor function and hand dexterity in patients with stroke. However, the limited number of studies and small sample sizes restrict the generalizability of these findings, highlighting the need for further research. Clinical Trial: PROSPERO CRD42024572150
Background: The growing adoption of diagnostic and prognostic algorithms in healthcare has led to concerns about the perpetuation of algorithmic bias against disadvantaged groups of individuals. Deep...
Background: The growing adoption of diagnostic and prognostic algorithms in healthcare has led to concerns about the perpetuation of algorithmic bias against disadvantaged groups of individuals. Deep learning methods to detect and mitigate bias have revolved around modifying models, optimization strategies, and threshold calibration with varying levels of success and tradeoffs. However, there have been limited substantive efforts to address bias at the level of the data used to generate algorithms in healthcare datasets. Objective: We create a simple metric (AEquity) that utilizes a learning curve approximation to distinguish and mitigate bias via guided dataset collection or relabeling. Methods: We demonstrate this metric in two well-known examples: chest X-rays and healthcare cost utilization, and detect novel biases in the National Health and Nutrition Examination Survey. Results: We demonstrate that utilizing AEquity to guide data-centric collection for each diagnostic finding in the chest radiograph dataset decreased bias by between 29% and 96.5% when measured by differences in area-under-the-curve. When we examined Black patients on Medicaid, at the intersection of race and socioeconomic status, we found that AEquity-based interventions reduced bias across a number of different fairness metrics including overall false negative rate by 33.3% (Bias Reduction Absolute = 1.88 x 10-1; 95% CI (1.4x10-1, 2.5x10-1); Bias Reduction (%) 33.3% (95% CI, 26.6-40.0)), Precision Bias by 7.50x10-2; 95% CI (7.48x10-2, 7.51x10-2); Bias Reduction (%) 94.6% (95% CI, 94.5-94.7%); False Discovery Rate by 94.5% (Absolute Bias Reduction = 3.50x10-2; 95% CI: (3.49x10-2, 3.50x10-2). Similarly, AEquity-guided data collection demonstrates bias reduction of up to 80% on mortality prediction with the National Health and Nutrition Examination Survey (Bias Reduction Absolute = 0.08; 95% CI (0.07, 0.09)). Additionally, we benchmark against balanced empirical risk minimization and calibration and we show that AEquity-guided data collection outperforms both standard approaches. Moreover, we demonstrate that AEquity works on fully connected networks, convolutional neural networks such as ResNet-50, transformer architectures such as on VIT-B-16, an 86 million parameter Vision Transformer, and nonparametric methods such as LightGBM Conclusions: In short, we demonstrate AEquity is a robust tool by applying it to different datasets and algorithms, intersectional analyses and measuring its effectiveness with respect to a range of traditional fairness metrics.
Background: Commercial wearables like Fitbits quantify sleep metrics using fixed calendar times as the default measurement periods, which may not adequately account for individual variations in sleep...
Background: Commercial wearables like Fitbits quantify sleep metrics using fixed calendar times as the default measurement periods, which may not adequately account for individual variations in sleep patterns. To address this, experts in sleep medicine and wearables developed a user-centric algorithm that more accurately reflects actual sleep behaviors, aiming to improve wearable-derived sleep metrics. Objective: The study aimed to describe the development of the new (user-centric) algorithm, and how it compares with the default (calendar-relative), and offers best practices for analyzing All of Us Fitbit sleep data on a cloud platform. Methods: The default and new algorithms was implemented to pre-process and then compute sleep metrics related to schedule, duration, and disturbances using high-resolution Fitbit sleep data from 8,563 participants (median age 58.1 years, 72% female) in the All of Us Research Program (v7 Controlled Tier). Variation in typical sleep patterns was computed by taking the differences in the mean number of primary sleep logs classified by each algorithm. Linear mixed-effects models were used to compare differences in sleep metrics across quartiles of variation in typical sleep patterns. Results: Out of 8,452,630 total sleep logs over a median of 4.2 years of Fitbit monitoring, 401,777 (5%) non-primary sleep logs identified by default algorithm were reclassified to primary sleep by the user-centric algorithm. Variation in typical sleep patterns ranged from -0.08 to 1. Among participants with the most variation in typical sleep patterns, the new algorithm identified more total sleep time (by 17.6 minutes; P<0.001), more wake after sleep onset (by 13.9 minutes; P<0.001), and lower sleep efficiency (by 2.0%; P<0.001), on average. There were only modest differences in sleep stage metrics between the two algorithms. Conclusions: The user-centric algorithm captures the natural variability in sleep schedules, offering an alternative way to pre-process and evaluate sleep metrics related to schedule, duration, and disturbances. R package is publicly available to facilitate the implementation of this algorithm for clinical and translational use.
Background: Mood disorders, including bipolar disorder (BP) and major depressive disorder (MDD), are characterized by significant psychological and behavioral fluctuations, with mobility patterns serv...
Background: Mood disorders, including bipolar disorder (BP) and major depressive disorder (MDD), are characterized by significant psychological and behavioral fluctuations, with mobility patterns serving as potential markers of emotional states. Objective: Leveraging GPS data as an objective measure, this study explores the diagnostic and monitoring capabilities of Fourier transform, a frequency-domain analysis method, in mood disorders. Methods: A total of 62 participants (BP: 20; MDD: 27; healthy controls: 15) contributed 5,177 person-days of data over observation periods ranging from 5 days to 6 months. Key GPS indicators—location variance (LV), transition time (TT), and entropy (EN)—were identified as reflective of mood fluctuations and diagnostic differences between BP and MDD. Results: Fourier transform analysis revealed that the maximum power spectra of LV and EN differed significantly between BP and MDD groups, with BP patients exhibiting greater periodicity and intensity in mobility patterns. Notably, BP participants demonstrated consistent periodic waves (e.g., 1-day, 4-day, and 9-day cycles), while such patterns were absent in MDD. Daily GPS data showed stronger correlations with ecological momentary assessment (EMA)-reported mood states compared to weekly or monthly aggregations, emphasizing the importance of day-to-day monitoring. Depressive states were associated with reduced LV and TT on weekdays, and lower EN on weekends, indicating that mobility features vary with social and temporal contexts. Conclusions: This study underscores the potential of GPS-derived mobility data, analyzed through Fourier transform, as a non-invasive and real-time diagnostic and monitoring tool for mood disorders. The findings suggest that the intensity of mobility patterns, rather than their frequency, may better differentiate BP from MDD. Integrating GPS data with EMA could enhance the precision of clinical assessments, provide early warnings for mood episodes, and support personalized interventions, ultimately improving mental health outcomes. This approach represents a promising step toward digital phenotyping and advanced mental health monitoring strategies.
Background: Digital skills training in health is crucial to ensure that the healthcare workforce is equipped to leverage the potential of digital technologies in delivering efficient and effective car...
Background: Digital skills training in health is crucial to ensure that the healthcare workforce is equipped to leverage the potential of digital technologies in delivering efficient and effective care. Identifying the existing training programs can be valuable to describe gaps and opportunities for acceleration in the digital age. Objective: The mapping of the existing continuous education and professional development training options in digital skills in health and their assessment was the aim of this study. Methods: As part of the EU funded project entitled “TRANSiTION” - Digital TRANSition and dIgiTal resiIlience in Oncology, an expert-based approach was implemented for identifying training programmes in 14 European Countries. The data was collected via an online survey that was developed for the purpose of this study, and was consisted of twenty-three questions which were catecorised in five domains (general information, reaction, learning, behaviour, and results). The analysis was performed by using Kirkpatrick’s four levels model and the Digital Competence Framework for Citizens. Results: The analysis of the data showed that in a percentage of 39.6% there is no official training in digital skills for the healthcare workforce, even the fact in the 95.8% of the cases digital solutions were used in the daily practice. Countries scored lower than the mean in the overall performance status according to the Kirkpatrick’s model that reflects the gap in knowledge and skills of HCPs and health managers. The quality of the programmes was poor and the evaluation reflects the great need and the gaps in health workforce’s education in digital skills and health technologies application in practice. Conclusions: There was variance in the availability and quality of digital skills training across Europe. The development of a comprehensive training programme targeted to improve HCPs and health managers knowledge and skills but also digital tools incorporation into practice is crucial.
Background: Background: Increasing reliance on digital health resources can create disparities among older patients. Understanding health-related, mobility and socioeconomic factors associated with th...
Background: Background: Increasing reliance on digital health resources can create disparities among older patients. Understanding health-related, mobility and socioeconomic factors associated with the use of eHealth technologies is important for addressing inequitable access to healthcare. Objective: We sought to assess digital health literacy among patients aged ≥ 65 years and identify factors associated with their ability to access, understand, and use digital health resources. Methods: We conducted a cross-sectional survey including 871 patients aged ≥ 65 years. Analyses were performed to identify associations between digital health literacy and self-rated health, mobility and socioeconomic deprivation assessed with the area deprivation index (ADI). Results: Respondents with lower self-rated health had lower levels of digital health literacy with only 54.2% with poor self-rated health able to send a message to their doctor compared to 89.5% of patients with excellent self-rated health. All comparisons across the digital health literacy domains were statistically significant by self-rated health (P<0.05). Respondents with mobility restrictions had lower levels of digital health literacy across several domains with only 32.6% able to use a video/camera with their doctor compared to 48% without mobility restrictions (P=0.0010). Respondents with a high ADI (≥80%) also had lower levels of digital health literacy across several domains with only 57.4% able to send a message to their doctor compared to 80.2% without a high ADI. Conclusions: Our findings highlight the need for targeted interventions to improve engagement with eHealth among patients aged ≥ 65 years which is impacted by poor health, limited mobility, and socioeconomic deprivation. Enhancing digital health literacy can help bridge the gap in access to digital health resources and improve overall health outcomes for this population.
Artificial intelligence (AI), particularly large-scale language models (LLMs) such as ChatGPT, has emerged as a technology of significant impact in various fields, including medicine. This rapid devel...
Artificial intelligence (AI), particularly large-scale language models (LLMs) such as ChatGPT, has emerged as a technology of significant impact in various fields, including medicine. This rapid development presents both opportunities and risks, particularly in the context of emergency medicine, where AI could transform clinical practices, but also raises concerns regarding the safety and reliability of its applications. This update aims to evaluate the implications of AI in the medical field, examining its potential applications in emergency medicine, its benefits and limitations, and the challenges of achieving general artificial intelligence (GAI). A literature review was conducted to analyze the current capabilities of AIs in health data processing, medical imaging, and clinical process improvement, while addressing concerns raised by hallucination phenomena and LLM performance in the context of rare or atypical cases. AI models offer substantial advantages in triage, patient flow optimization, bed management, and care prioritization in emergency medicine. However, significant risks remain, including AI hallucinations that can generate erroneous information and LLM limitations for infrequent clinical situations, potentially compromising patient safety. AI represents revolutionary potential for emergency medicine, but it necessitates a rigorous regulatory and safety approach to mitigate associated risks. The implementation of safety standards and supervisory practices becomes essential to ensure the safe and effective integration of AI into clinical medicine.
Background: In the project SATURN (Smart physician portal for patients with unclear disease) the prototype of a clinical decision support system based on artificial intelligence is being developed spe...
Background: In the project SATURN (Smart physician portal for patients with unclear disease) the prototype of a clinical decision support system based on artificial intelligence is being developed specifically for primary care in Germany. It aims to reduce diagnostic uncertainty in cases of unclear and rare diseases and focuses on three medical fields. A user-centered design approach is applied for prototype development and evaluation. Objective: This study explores the usability of a high-fidelity prototype. Aspects of user experience like the subjective impression, satisfaction, and improvement requests are also investigated. Methods: Five general practitioners participated in the evaluation of the prototype which consisted of (1) a remote think-aloud test, (2) a post-session interview, and (3) a survey with the System Usability Scale. All three parts were consecutively carried out in individual remote sessions. During the think-aloud tests, which were video- and audiotaped, the participants verbalized their thoughts and actions and had to solve several tasks which were based on a primary care case vignette. Remarkable observations were logged, transcribed with quotes, and analyzed for usability problems and positive findings. All observations and interview responses were deductively assigned to the following categories: (1) Content, (2) Comprehensibility, (3) User-friendliness, (4) Layout, (5) Feedback, (6) Navigation. Usability problems were described in detail and solutions for improvement proposed. Median and total scores were calculated for all questionnaire items. Results: The evaluation detected both strengths and areas for improvement. Key issues identified were content-related limitations, such as the inability to enter unlisted symptoms, medications, and examination findings in the dropdown menus. Participants also found the terminology for laboratory values did not match their day-to-day vocabulary, as common abbreviations were not recognized. Suggestions for improving the content of the system were also made and included adding symptom duration, weighting symptoms, and incorporating hereditary factors.
Another key issue was a lack of user-friendliness concerning the time required to input medication plans and lab values. This aspect was criticized for being cumbersome, with participants expressing a need for faster data entry, potentially through direct imports from practice management systems or laboratory files.
Despite these challenges, participants praised other aspects of user-friendliness (use of stored diagnoses and symptoms) and navigation (top navigation bar), and particularly liked the clear and well-structured layout. Overall, the SATURN prototype was deemed useful and promising for future clinical use, despite the need for further refinements, particularly in the areas of data entry. Conclusions: The usability evaluation methods combined proved to be location independent and easy to use, and were apt to detect usability problems in detail. Technically demanding user requirements, such as direct data transfer from the practice management system and entry options that require complex data models were beyond the scope of this project. However, they should be considered in future development projects. Clinical Trial: not applicable
Background: Patients with mood or psychotic disorders experience high rates of unplanned hospital readmissions. Predicting the likelihood of readmission can guide discharge decisions and optimize pati...
Background: Patients with mood or psychotic disorders experience high rates of unplanned hospital readmissions. Predicting the likelihood of readmission can guide discharge decisions and optimize patient care. Objective: The purpose of this study is to evaluate the predictive power of structured variables from electronic health records (EHRs) for all-cause readmission across multiple sites within the Mass General Brigham (MGB) health systems and to assess the transportability of prediction models between sites. Methods: This retrospective, multi-site study analyzed structured variables from EHRs separately for each site to develop in-site prediction models. The transportability of these models was evaluated by applying them across different sites. The predictive performance was measured using the F1 score, and additional adjustments were made to account for differences in predictor distributions. Results: The study found that the relevant predictors of readmission varied significantly across sites. For instance, the length of stay was a strong predictor at only three of the four sites. In-site prediction models achieved an average F1 score of 0.666, whereas cross-site predictions resulted in a lower average F1 score of 0.551. Efforts to improve transportability by adjusting for differences in predictor distributions did not lead to better performance. Conclusions: The findings indicate that individual site-specific models are necessary to achieve reliable prediction accuracy. Furthermore, the results suggest that the current set of predictors may be insufficient for cross-site model transportability, highlighting the need for more advanced predictor variables and predictive algorithms to gain robust insights into the factors influencing early psychiatric readmissions.
Background: Background: Different studies conducted by different researchers about the metabolism of lipids among postmenopausal women is related with the level of estrogen but recent evidence has pro...
Background: Background: Different studies conducted by different researchers about the metabolism of lipids among postmenopausal women is related with the level of estrogen but recent evidence has provided evidence for extragonadal effects of FSH on lipids. However, the findings are still unclear and inconsistent that necessitated systematic review and metanalysis Objective: Objective: To determine the effect of follicle stimulating hormone on the level of triglycerides among postmenopausal women Methods: Method: PubMed, Cochran library, Scopus and Google scholar was used to search literatures systematically and a total of 747 papers published between 1998-2021 were retrieved. Studies with postmenopausal women as study participants and had reported either of the correlation coefficient or beta coefficient of triglycerides were included. The pooled estimated correlation coefficient between triglycerides and follicle stimulating hormone was computed using random effect model. Heterogeneity test was conducted by using forest plot. Publication bias was checked using eggers test. Meta-regression and subgroup analysis was done to find out the responsible modifiers for the overall correlation coefficient. Results: Result: A total of 11 papers ,8 cross-sectional,2 retrospective cohort and 1 prospective cohort were included in this systematic review and meta-analysis. The pooled correlation coefficient was calculated for triglycerides and follicle stimulating hormone and positive association were observed between triglycerides and follicle stimulating hormone. Conclusions: Conclusion
The levels of FSH positively associated with TG and but the relationship was not significant.
Background: The impact of COVID-19 has primarily been studied in the context of language delays or developmental disorders in infants and children. However, the effects on young adults have received l...
Background: The impact of COVID-19 has primarily been studied in the context of language delays or developmental disorders in infants and children. However, the effects on young adults have received less attention. COVID-19 not only affects physical health but also cognitive and language functions, which is an emerging area of research. While previous studies have focused on developmental stages, the effects of COVID-19 on the language abilities of healthy young adults remain underexplored. This study aimed to investigate the impact of COVID-19 on the spoken language, particularly in story retelling and working memory, in young adults. Objective: The objective of this study was to assess the effects of COVID-19 on spoken language abilities, particularly story retelling and working memory, in young adults. The study sought to understand how COVID-19 might influence the spoken discourse abilities of young adults, and whether these effects are temporary or long-lasting. Methods: The study involved 77 young adult participants, of whom 39 were in the non-COVID group and 38 were in the COVID group. Participants underwent the Story Retelling Procedure (SRP) and working memory tests. The SRP test, which heavily relies on auditory comprehension and memory, was used to evaluate the impact of COVID-19 on spoken discourse. Working memory was also assessed to examine potential COVID-related disruptions in cognitive functions. Results: The results revealed a significant reduction in performance on the SRP test in the COVID group compared to the non-COVID group. The mean score for the COVID group was 5.67 (SD = 2.01), while the non-COVID group’s mean was 7.15 (SD = 1.78), with a statistically significant difference (p = 0.03). This suggests that COVID-19 had a negative impact on the ability to retell stories. However, no significant differences were found in working memory performance between the two groups (p = 0.45), indicating that working memory was not notably affected by COVID-19 in this sample. Conclusions: COVID-19 was found to negatively affect spoken discourse, particularly story retelling abilities, in young adults, although it did not impact working memory. The findings suggest that COVID-19 may cause temporary disruptions in language abilities in healthy young adults, with implications for future studies on long-term effects, particularly regarding long-COVID symptoms. Further research is needed to explore the lasting impact of COVID-19 on language processing, especially in individuals experiencing persistent symptoms.
Background: Diabetes is a pervasive chronic condition requiring early detection and effective management to mitigate severe complications. While traditional predictive models often use statistical or...
Background: Diabetes is a pervasive chronic condition requiring early detection and effective management to mitigate severe complications. While traditional predictive models often use statistical or machine learning algorithms, these methods may lack the contextual understanding of medical data. Combining data-driven clustering techniques with ontology-based frameworks offers a promising avenue for more interpretable and effective prediction systems Objective: This study aims to enhance diabetes prediction accuracy by integrating improved clustering methods with ontology-based knowledge representation, enabling semantic reasoning and contextual insights. Methods: The proposed approach applies an optimized Louvain Community Detection algorithm to cluster patient data, revealing inherent patterns and groupings. Ontology development using Protégé enriches the dataset with semantic annotations, enabling meaningful analysis. A dual-phase predictive model leverages clustering and semantic querying to predict diabetes outcomes based on patient-specific parameters. Results: The integrated approach demonstrated superior performance on the Pima Indians Diabetes dataset. Experimental evaluations using an 80-20 dataset split and 10-fold cross-validation yielded accuracy scores of 97.56% and 96.74%, respectively. Other metrics, including precision, recall, and F1-score, confirmed the model's robustness and generalizability compared to existing methods. Conclusions: By combining clustering techniques with ontology-based frameworks, this study provides a robust, interpretable, and accurate approach to diabetes prediction. The integration of semantic reasoning enhances model adaptability and relevance, paving the way for advanced, personalized healthcare solutions.
Background: Clinicians currently lack an effective means for identifying youth with type 1 diabetes (T1D) who are at risk for experiencing glycemic deterioration between diabetes clinic visits. As a r...
Background: Clinicians currently lack an effective means for identifying youth with type 1 diabetes (T1D) who are at risk for experiencing glycemic deterioration between diabetes clinic visits. As a result, their ability to identify youth who may optimally benefit from targeted interventions designed to address rising glycemic levels is limited. Although electronic health records (EHR)-based risk predictions have been used to forecast some health outcomes in T1D, no study has investigated the potential for using EHR data to identify youth with T1D who will experience a clinically significant rise in HbA1c ≥0.3% (~3 mmol/mol) between diabetes clinic visits. Objective: We evaluated the feasibility of using routinely collected EHR data to develop a machine learning model to predict 90-day unit-change in HbA1c (in % units) in youth (ages 10-17) with T1D. We assessed our model's ability to augment clinical decision-making by identifying a percent change cut-point that optimized identification of youth who would experience a clinically significant rise in HbA1c. Methods: From a cohort of 2,757 youth with T1D who received care from a network of pediatric diabetes clinics in the Midwestern United States (January 2012-August 2017), we identified 1,743 youth with 9,643 HbA1c observation windows (i.e., 2 HbA1c measurements separated by 70-110 days, approximating the 90-day time interval between routine diabetes clinic visits). We used up to 5 years of youths' longitudinal EHR data to transform 17,466 features (demographics, laboratory results, vital signs, anthropometric measures, medications, diagnosis codes, procedure codes, and free text data) for model training. We performed three-fold cross-validation to train random forest regression models to predict 90-day unit-change in HbA1c(%). Results: Across all 3 folds of our cross-validation model, average root mean squared error was 0.88 (95% CI, 0.85-0.90). Predicted HbA1c(%) strongly correlated with true HbA1c(%) (r=0.79; 95% CI, 0.78-0.80). The top 10 features impacting model predictions included postal code, various metrics related to HbA1c, and the frequency of a diagnosis code indicating difficulty with treatment engagement. At a clinically significant percent rise threshold of ≥0.3% (~3 mmol/mol), our model's positive predictive value (PPV) was 60.3%, indicating a 1.5-fold enrichment (relative to the observed frequency that youth experienced this outcome [40.7%]). Model sensitivity and PPV improved when thresholds for clinical significance included smaller changes in HbA1c, whereas specificity and negative predictive value improved when thresholds required larger changes in HbA1c. Conclusions: Routinely collected EHR data can be used to create an ML model for predicting unit-change in HbA1c between diabetes clinic visits among youth with T1D. Future work will focus on optimizing model performance and validating the model in additional cohorts and in other diabetes clinics.
Background: Wearable self-tracking technologies are increasingly recognized for their potential to enhance therapeutic engagement and personalize treatment. While many instruments emphasize passive da...
Background: Wearable self-tracking technologies are increasingly recognized for their potential to enhance therapeutic engagement and personalize treatment. While many instruments emphasize passive data collection, their role in actively mediating therapeutic processes remains underexplored. This study explores how the One Button Tracker (OBT), a novel single-purpose wearable self-tracking instrument, supports psychotherapeutic treatment by enabling patients to track self-defined, personally relevant phenomena during their daily lives. Objective: To explore how the OBT mediates the psychotherapeutic process in patients’ daily lives, focusing on its impact on therapeutic engagement, self-awareness, and the therapeutic relationship. Methods: This qualitative study was part of a larger Participatory Action Research project conducted at a specialized clinic for trauma survivors in Denmark. Nine patients, refugees diagnosed with Complex PTSD, used the OBT as part of their therapy. Semi-structured interviews were conducted at three stages: before, during, and after treatment. Thematic analysis was used to analyze the data, guided by postphenomenological framework focusing on technologies mediation of the human-world relations. Results: Thematic analysis identified five key themes describing the OBT’s multistable roles: (1) From external instrument to extension of the self (2) mental switch (3) a faithful companion (4) scarlet letter, and (5) emergency lifeline. The OBT supported engagement in therapeutic interventions during moments of distress, enhanced emotional regulation, and strengthened the therapeutic relationship by extending its influence beyond clinical sessions. Its simplicity and vibrotactile feedback facilitated engagement and usability, while its multistability allowed patients to adapt its use to their intentions and contexts. However, the presence and sometimes visibility of the OBT introduced complex social dynamics, amplifying both engagement and stigma depending on individual circumstances and context. Conclusions: The findings suggest that the OBT acts as an active mediator in the therapeutic process, fostering agency, emotional regulation, and engagement. By shifting the focus from passive data collection to meaningful interaction with the instrument, the OBT highlights the potential of wearable self-tracking instruments to actively shape therapeutic experiences. These insights underscore the value of designing digital mental health instruments that prioritize simplicity, multistability, and relational engagement to support personalized and context-sensitive care.
Background: Venous thromboembolism (VTE) is a common vascular disorder requiring extended anticoagulation therapy post-discharge to reduce recurrence risk. Home rehabilitation management systems that...
Background: Venous thromboembolism (VTE) is a common vascular disorder requiring extended anticoagulation therapy post-discharge to reduce recurrence risk. Home rehabilitation management systems that utilize electronic health records (EHR) from hospital care provide opportunities for continuous patient monitoring. However, transferring medical data from clinical to home settings raises significant concerns about privacy and security. Conventional methods such as manual data entry, optical character recognition, and dedicated data transmission lines face notable technical and operational challenges. Objective: The aim of this study is to develop a QR code-based secure transmission algorithm (QRST-AB) using Avro and Byte Pair Encoding (BPE). The algorithm facilitates the creation of out-of-hospital health records by enabling patients to scan QR codes via a dedicated mobile application, ensuring data security and user privacy. Methods: Between January and October 2024, 300 hospitalized VTE patients were recruited at the Sixth Medical Center of the Chinese PLA General Hospital. Post-discharge, participants used a home rehabilitation application tailored for VTE management. The QRST-AB algorithm was developed to securely transfer in-hospital EHR to the application. It incorporates cryptographic hash functions for authentication and employs BPE, Avro, and Gzip for optimized data compression. Specifically, BPE tokenizes medical text, while Avro serializes JSON objects, contributing to data encryption. A proprietary tokenizer was trained using a "Chinese Medical Text Dataset," and compression efficiency was evaluated using a "Performance Benchmark Dataset." Comparative analyses were conducted to assess the compression efficiency of JSON serialization methods, Avro and ASN.1, and tokenization algorithms, BPE and unigram. Results: The dataset consisted of JSON files from 300 patients, averaging 240.1 fields per file (range: 89–623) and 7,095 bytes in size (range: 2,748–17,425 bytes). Using the BPE + Avro + Gzip algorithm, the average file size was reduced to 1,048 bytes, achieving a compression ratio of 6.67. This was 1.82 times more efficient than traditional Gzip compression (average file size: 1,907 bytes; compression ratio: 3.66; P < 0.001). For Chinese medical text tokenization, BPE outperformed unigram with a compression ratio of 4.68 versus 4.55 (P < 0.001). Avro and ASN.1 demonstrated comparable compression ratios of 2.57 and 2.59, respectively, when used alone (P = 0.299). However, Avro combined with BPE and Gzip significantly outperformed ASN.1, achieving compression ratios of 6.67 versus 5.21 (P < 0.001). Additionally, 84.7% of patients needed to scan only one QR code, requiring an average of 3.1 seconds. Conclusions: The QRST-AB algorithm efficiently compresses and transmits data in an encrypted manner and authenticates the identity of the scanning users, ensuring the privacy and security of medical data. Delivered as a software development kit, the algorithm offers straightforward implementation and usability, supporting its broad adoption across various applications.
Background: The rising prevalence of chronic diseases among older adults in China highlights the need for a more robust and efficient healthcare system. The existing system, characterized by fragmenta...
Background: The rising prevalence of chronic diseases among older adults in China highlights the need for a more robust and efficient healthcare system. The existing system, characterized by fragmentation and limited coordination, faces challenges in delivering comprehensive care for chronic diseases among community-dwelling older adults with multiple comorbidities. There is a pressing need for tailored and integrated care for chronic conditions that promotes resource sharing, enhances access to advanced facilities, offers expert guidance, and ensures safe and effective management. Objective: The objectives are to investigate the unmet healthcare needs of Chinese community-dwelling older adults, explore the acceptability of the PRISMA model, and examine their needs for integrated care by case managers. Additionally, the study seeks to develop a comprehensive questionnaire to assess general and specific expectations, analyze expectation levels, identify sociodemographic factors influencing these expectations, and ultimately formulate an evidence-based integrated care model tailored to optimize healthcare delivery for ageing population. Methods: An exploratory sequential mixed-methods approach, including three sequential phases, incorporates elements from the PRISMA integrated care model and considers specific expectations of community-dwelling older adults with multiple comorbidities. Phase I involves a qualitative study to gather in-depth evidence on healthcare needs and integrated care expectations. Phase II focuses on developing and validating a comprehensive questionnaire. Phase III comprises a quantitative survey conducted across three cities representing central, eastern, and western China. Data integration will follow a data-building approach, combining qualitative and quantitative findings in the final analysis to provide a comprehensive understanding and refine insights into expectations towards integrated care for community-dwelling older adults. Results: The data collection process for this study will begin in October 2025. The duration of the study is planned to be 24 months. Ethical approval has been obtained from the Institutional Ethics Committee. Conclusions: This study aims to address significant gaps in the current healthcare provision while improving the quality, accessibility, and efficiency of services. By exploring how integrated care can be facilitated through a centralized point of access managed by a case manager, it seeks to enhance community care. The findings have the potential to inform policy decisions, guide the implementation of integrated care delivery, and ultimately improve health outcomes and the quality of life for older adults in China. Clinical Trial: Protocol Registration:
The study protocol has been registered on osf.io
(Registration DOI: https://doi.org/10.17605/OSF.IO/825AH).
Background: Sexually transmissible infections (STIs) typically concentrate in core areas, or risk spaces, that can be defined geographically. These infections co-existence with HIV may result in sever...
Background: Sexually transmissible infections (STIs) typically concentrate in core areas, or risk spaces, that can be defined geographically. These infections co-existence with HIV may result in severe health complications. Objective: (a) determining the seroprevalence of hepatitis B, syphilis and chlamydia infections among people living with HIV (PLWHIV) from the rural and urban communities, (b) evaluate the effect of co-morbidity of STIs on Hematological parameters among PLHIV infection within these communities, (c) assess the factors exacerbating the morbidity of sexually transmissible diseases among PLWHIV and develop context-specific policy recommendations to facilitate the mitigation of socio-cultural and (d) socio-economic drivers of the morbidity of these infections in the rural and urban settings in Meme division Methods: A hospital-based cross-sectional design was adopted that will recruit a minimum of 178 PLWHIV from within the urban and rural communities in Meme division from December 2024 to March 2025. Data will be collected using well-structured questionnaires with the help of kobo tool box software and about 4mL of blood will be collected from which syphilis, hepatitis B, chlamydia, full blood count and ABO blood grouping serological assays will be done. Data will be analyzed using STATA and GraphPad prism statistical packages and p-values <0.05 will be considered as statistically significant. Results: The seroprevalence of syphilis, hepatitis and chlamydia will be determined among PLHIV from rural and urban communities, association between the different WBCs parameters and the occurrence of STIs will be determined, factors exacerbating the spread of these infections among PLHIV from the rural and urban communities will be determined, and context-specific policy recommendations to facilitate the mitigation of socio-cultural and socio-economic drivers of the morbidity of these infections in the rural and urban settings will be developed. Conclusions: The prevalence of STIs among PLWHIV is high and this has an effect on hematological parameters with factors such as multiple sexual partners, age, HIV status, dental procedures outside health facilities exacerbating these infections morbidity.
Background: Healthcare systems are increasingly confronted by the challenge posed by the aging population. In particular, hospitalization, both initial and subsequent, is often observed among the poly...
Background: Healthcare systems are increasingly confronted by the challenge posed by the aging population. In particular, hospitalization, both initial and subsequent, is often observed among the polypathological elderly, while it is estimated that over 30% of such hospitalizations could be avoided. In this context, remote patient monitoring (RPM) systems offer a promising solution, enabling early detection and management of patient complexity. Objective: This study aims to provide a complementary analysis of the impact of the EPOCA RPM system for polypathological elderly people, on the total number of unplanned hospitalization days and admissions, as well as emergency department (ED) visits. In an earlier study, we evaluated the EPOCA PRM system when the system operator is a geriatrician; in the current one, we evaluate the case when the general practitioner (GP) is the operator. Methods: A retrospective, before-and-after cohort design was used for the purposes of this study. Patients who benefited from the EPOCA RPM system for more than one year (between February 2022 and August 2024), aged over 70 and with two or more pathologies were included in the analysis. We compared the total number of unplanned hospital admissions, hospitalization days and ED visits between the previous year (Y-1) and the year (Y) of follow-up by the EPOCA RPM system. Statistical analyses were significant at P-value < .05 Results: A total of 80 patients were included, with an average age of 87. Our study showed a significant reduction in hospitalization days by 49% between Y-1 and Y. There was also a significant decrease in the number of unplanned hospital admissions (-57%) and ED visits (-62%). These results were seen by a significant decrease from 0.99 to 0.42 per patient in the number of hospitalizations, from 0.99 to 0.37 in emergency room visits and a reduction of 9.7 hospital days per year per patient, P-value< .001. In addition, there was no observed increase in mortality or transfers to intensive care units Conclusions: The results of this study support our earlier findings on the potential benefits of EPOCA RPM for managing complex, polypathological elderly patients, this time with the GP as system operator. RPM systems can support GPs and caregivers manage complex geriatric patient care, help reduce healthcare costs and the burden on hospital services, while enabling patients to remain safely at home. Further evidence on the effectiveness of EPOCA RPM system may be obtained in a future large randomized controlled trial
Background: Social determinants of health (SDOH) are the conditions in which people are born, grow, live, work, and age, encompassing social and economic factors that shape health outcomes. There is a...
Background: Social determinants of health (SDOH) are the conditions in which people are born, grow, live, work, and age, encompassing social and economic factors that shape health outcomes. There is an increasing call to leverage digital health technology (DHT) to address SDOH and health-related social needs and establish connections to resources and services. Objective: This study aimed to: 1) identify the DHT-related characteristics of DHT users with low socioeconomic status (SES), 2) determine the needs and preferences of DHT users with low SES, and 3) explore how current SDOH-DHT address these needs and preferences. Methods: We employed a multi-phase, mixed-method, user-centered design approach. In Phase 1, we developed a user profile based on a literature review, aggregate data, interviews with 26 low-SES individuals, and focus groups with 28 professionals. In Phase 2, we conducted a landscape analysis of 17 existing SDOH-DHT. Results: DHT users of low SES had diverse social and technology characteristics. Five key themes emerged regarding user needs and preferences: 1) user-centered design, including multilingual support, visual guidance, and customization; 2) efficient, solution-based assessment of social risks, assets, and needs; 3) e-caring support features; 4) user education and feedback mechanisms; and 5) trust, privacy, and security. The landscape analysis revealed that current SDOH-DHT features do not adequately meet these needs. Conclusions: Discrepancies between target user needs and current DHT features represent missed opportunities in developing user-centered tools for individuals of low SES. Findings underscore the importance of inclusive, empowering, and responsive design in SDOH-DHT to bridge health disparities and advance public health.
Background: As a phenomenon that has been the subject of scientific research for many years, early marriages occur in almost all geographies. However, it is noticeable that scientific studies on child...
Background: As a phenomenon that has been the subject of scientific research for many years, early marriages occur in almost all geographies. However, it is noticeable that scientific studies on children born from early marriages are quite limited. Objective: Aim of study was to compare height-weight-head circumference development of infants/children aged 7days-60 months born to mothers who married at an early age with WHO Multicentre Growth Reference Study (MGRS) data. Methods: The Study sample consisted of2209 infants/children between 7days-60 months of age born to adolescent mothers living in Ankara, the capital city of Turkey, who were followed up in Infant/Child Follow-up Data Set system of Ministry Of Health. The measurements of infants/children and mean MGRS height-weight-head circumference were compared by one-sample t-test. Results: As a result of analysis, it was found that mean height of children born to mothers who married at an early age was significantly lower than MGRS averages in both sexes, mean weight of children born to adolescent mothers was significantly lower than MGRS averages in first periods of birth (p<.o5), but difference disappeared over time and exceeded MGRS averages in following periods, and head circumference measurements of children born to adolescent mothers were significantly lower (p<.o5) than MGRS averages in both sexes. Conclusions: Early marriages pose health risks not only for the children who are married, but also for the children born from these marriages.
Background: Social media is a promising tool for adolescent health promotion due to its accessibility, cost-effectiveness, and integration into daily routines. Platforms like Instagram offer unique op...
Background: Social media is a promising tool for adolescent health promotion due to its accessibility, cost-effectiveness, and integration into daily routines. Platforms like Instagram offer unique opportunities to engage adolescents through interactive features like quizzes and polls, fostering active participation and behavior change. However, risks such as exposure to harmful content highlight the need for carefully designed interventions. Objective: This study examines Instagram's potential for health promotion by exploring adolescents' preferences and needs to inform effective, engaging strategies. Methods: A qualitative approach was employed, involving semi-structured interviews and focus groups with 67 adolescents aged 14-17, recruited through schools and Instagram advertisements in Germany. Data were analyzed using content analysis with a combined deductive-inductive coding approach. The study is grounded in co-design principles, the Social Media Uses and Gratifications (SMUG) theory, and a cultural sensitivity framework. Results: Adolescents favor Instagram for health promotion due to its interactive features like quizzes, polls, and Stories. These elements were found to enhance engagement and reduce dropout rates. Barriers included perceptions of extra workload and privacy concerns. Recommendations emphasized simplicity, authenticity, and relatable content tailored to user preferences. While traditional posts and Reels were appreciated for quick information, live sessions were less favored due to logistical challenges. Conclusions: Findings align with SMUG theory, highlighting the importance of interactivity and cultural sensitivity in digital interventions. The study challenges the assumption that live sessions are universally engaging, suggesting asynchronous content may better suit adolescents. The results underscore the need for user-centered design in health promotion to balance education with entertainment. Instagram offers unique opportunities for adolescent health promotion through interactive and culturally sensitive content. Future research should explore long-term impacts and diversify participant profiles to ensure broad applicability.
Background: Early assessment of mild cognitive impairment (MCI) in older adults is crucial, as it enables timely interventions and decision-making. In recent years, researchers have been exploring the...
Background: Early assessment of mild cognitive impairment (MCI) in older adults is crucial, as it enables timely interventions and decision-making. In recent years, researchers have been exploring the potential of gamified interactive systems (GIS) to assess pathological cognitive decline. Yet, researchers are still investigating effective methods for system integration, designing GIS that are perceived as engaging whilst also improving the accuracy in assessing cognitive decline. Objective: This review aims to comprehensively investigate GIS used to assess MCI. Specifically, we reviewed the existing systems to understand the different game types (including genres and interaction paradigms) employed for assessment. Additionally, we examined the cognitive functions targeted. Finally, we investigated the evidence for the performance of assessing MCI through GIS by looking at the quality of validation for these systems in assessing MCI and the diagnostic performance reported. Methods: A systematic search was conducted in IEEE Xplore, ACM Digital Library, and Scopus to identify interactive gamified systems developed for assessing MCI. Game types were categorized according to genres and interaction paradigms. The cognitive functions targeted by the systems were compared with those assessed in the MoCA. Lastly, we examined the quality of validation on ground truth, relevance of controls, and sample size. The diagnostic performance on sensitivity, specificity, and AUC are reported. Results: A total of 81 papers covering 49 GIS were included in this review. The primary game types used for MCI assessment were classified as casual games (n = 30), simulation games (n = 17), full-body movement games (n=4), and dedicated interactive games (n = 3). Only six out of 49 systems assess cognitive functions comprehensively, compared to those functions assessed via the MoCA. The reported diagnostic performances of GIS were comparable to common screening instruments like MMSE and MoCA, with some systems reporting near-perfect performance (100% sensitivity and specificity). Conclusions: This review provides a comprehensive summary of the literature on GIS for assessing MCI, explores the cognitive functions assessed by these systems, and evaluates their diagnostic performance. The results indicate that current GIS hold significant promise for the assessment of MCI, with several systems demonstrating diagnostic performance comparable to established screening tools. However, these systems' model training and validation exhibited significant deficiencies. Hence, despite some systems reporting impressive performance, there is a need for improvement in the validation studies, particularly concerning sample size and methodological rigor. Finally, we advocate for increased longitudinal research to enhance the reliability of these systems in evaluating MCI.
Background: Atopic dermatitis (AD) is a chronic, relapsing skin condition that significantly impact patients' quality of life. In clinical practice, AD is commonly managed through the use of emollient...
Background: Atopic dermatitis (AD) is a chronic, relapsing skin condition that significantly impact patients' quality of life. In clinical practice, AD is commonly managed through the use of emollients and topical corticosteroids. Haidebao body lotion (HBL) with the incorporation of Calcium-based antimicrobial peptide compounds (CAPCS) has demonstrated clinical benefits for patients with mild AD, but lack of high quality clinical trial evidence. Objective: In this study, we will implement a multi-center, double blind, randomized and placebo controlled trial to evaluate the efficacy and safety of HBL incorporated with CAPCS as an adjunctive therapy in ameliorating mild AD. Methods: This multi-center, randomized, double blind, placebo controlled trial will recruit 200 eligible participants in ten hospitals in China from October, 2023 to October, 2025. In this study, AD is confirmed in accordance with the Williams diagnostic criteria, and AD patients aged 18-55 years with the signed informed consent forms will be recruited. However, AD patients with pregnancy, serious underlying diseases, with communication barriers, and the violation of medication regulations will be excluded. In this study, 200 AD patients will be randomly assigned (1:1) to the treatment group (HBL with CAPCS, n=100) and the control group (HBL without CAPCS, placebo, n=100), and each participants in both groups will receive 3 sessions of treatments per day for 4 weeks. The primary outcome is the proportion of patients who has achieved at least 60% improvement in eczema area and severity index (EASI) score from baseline to week 2. The secondary outcomes include the numeric rating scale (NRS), dermatology life quality index (DLQI) at week 2 and week 4, and the adherence and adverse events will also be recorded. The full analysis set (FAS) and perprotocol set (PPS) will be analyzed by SAS 9.3 software package, and a P value less than 0.05 is considered as statistically significant. Results: This study is reviewed and approved by the Institutional Ethics Review Committee of Shanghai Skin Diseases Hospital in 2023 (2023-33), the participant recruitment work begins in January, 2024 and is proposed to be finished in December, 2024. This study was submitted for registration in Chinese Clinical Trial Registry on May 8, 2024, and approved on July 24, 2024. The registration number is ChiCTR2400087274. The study will be conducted in strict accordance with the Declaration of Helsinki. Conclusions: This study will evaluate the clinical efficacy and safety of HBL incorporated with CAPCS in the treatment of patients with mild AD. If the treatment efficacy is proven, HBL incorporated with CAPCS could be clinically used as an adjunctive therapy in ameliorating mild AD.
Background: Chronic insomnia, or insomnia disorder, is a major health issue with a prevalence of up to 15%. The recommended first-line treatment is cognitive and behavioral therapy for insomnia (CBTi)...
Background: Chronic insomnia, or insomnia disorder, is a major health issue with a prevalence of up to 15%. The recommended first-line treatment is cognitive and behavioral therapy for insomnia (CBTi), which, unfortunately, remains insufficiently accessible. Digitalization has the potential to reduce healthcare access inequalities by offering more flexible and accessible care options. Digital CBTi (dCBTi) has been shown to be as effective as in-person CBTi, highlighting its potential for broader implementation. Objective: This study aimed to develop an evidence-based dCBTi program grounded in theoretical and clinical knowledge, designed for efficient integration into healthcare systems, and to establish it as the first prescribed digital treatment in France Methods: The program was constructed based on validated CBTi theory and practice, incorporating the latest scientific data on CBT for insomnia. It was designed as a robust multicomponent therapy, integrating an initial standardized assessment and daily intelligent adaptation to enable digital phenotyping and provide personalized treatment. Results: We developed an innovative digital solution that combines scientific rigor with practical application. The program includes a standardized initial evaluation and dynamic personalization through intelligent algorithms. These features allow for the adaptation of therapy based on patient progress and needs, ensuring individualized care. Conclusions: The development of this dCBTi program represents a significant milestone in digital healthcare, offering a scalable solution to the accessibility challenges of traditional CBTi. Future steps involve conducting clinical studies to further evaluate its effectiveness and optimize its implementation within healthcare systems.
Background: Snakebite envenoming is an important yet neglected public health problem that predominantly affects rural populations living in tropical countries. Globally, an estimated 5.4 million peo...
Background: Snakebite envenoming is an important yet neglected public health problem that predominantly affects rural populations living in tropical countries. Globally, an estimated 5.4 million people have snakebites, leading to approximately 81,410–137,880 deaths annually, indicating digital health interventions may be novel solutions to enhance snakebite management and reduce mortality. Objective: The objective of this scoping review was to find, analyze, and synthesize evidence about existing digital health interventions, particularly mobile health applications, for the management of snakebites in various geographical regions. Methods: A systematic search was performed on PubMed, Google Scholar, and Research Gate following the PRISMA 2024 guidelines. We further searched on Google Search Engine and Google Play Store. The review used mobile apps that offered structured guidance for snakebite management and was published in English. Data were extracted by paying attention to application features, functions, and user experiences. Results: Our search identified 19 studies that evaluated 16 mobile health applications spanning five countries (India, the United Kingdom, the United States, South Africa, and Sri Lanka). Of the 16 applications examined, the vast majority provided free access (15/16), with 10 of the 16 being Android-based and 6 supporting both Android and iOS platforms. The phone app featured snake species identification, first aid protocols, mapping anti-venom stock, and emergency contact information, including multilingual support. Patient user feedback also suggested a positive impact in terms of applications delivering important information and connecting patients to medical support. Conclusions: Digital health interventions, especially mobile applications, are promising for overcoming snakebite management challenges through timely access to information, localizing emergency care, and enhancing health service delivery. However, challenges, like accessibility in remote areas, reliability, and the need for continual updating, must be overcome. This will include integrating artificial intelligence to facilitate the collaborative sharing of available data and inform policy and programs for the greatest impact in achieving the 2030 Global Snakebite Initiative target of reducing snakebite mortality.
Background: As individuals experiencing suicidal thoughts increasingly turn to the internet for support, digital tools offer a scalable and accessible means to address this urgent need. Platforms like...
Background: As individuals experiencing suicidal thoughts increasingly turn to the internet for support, digital tools offer a scalable and accessible means to address this urgent need. Platforms like NowMattersNow.org, grounded in Dialectical Behavior Therapy (DBT) principles, have demonstrated reductions in suicidal ideation and negative emotions, suggesting the potential of web-based interventions in suicide prevention. However, further investigation is needed to identify which features of the website contribute most effectively to these outcomes. Objective: This study examines the impact of NowMattersNow.org, a web-based resource providing Dialectical Behavior Therapy-based skills and personal stories, on reducing suicidal thoughts and negative emotions in users. The goal was to identify reasons for these reductions and evaluate the resource’s effectiveness as online self-help. Methods: Data were collected from 3,185 respondents who completed a 7-item retrospective survey measuring changes in suicidal ideation and emotional distress. The survey, triggered after a preset time on the site, used a 1-5 scale to measure 'Intensity of suicidal thoughts' and 'Intensity of negative emotions' at baseline and post-visit. Longitudinal regression analyses evaluated the statistical significance of changes in these measures, while cross-tabulation identified reasons users found the site helpful. Results: Respondents reported a 0.5-point reduction in suicidal ideation (average 3.0 to 2.5) and a 0.62-point reduction in negative emotions (3.66 to 3.04). Among those with high baseline suicidal thoughts, 54.1% improved after viewing. LGBTQI individuals, those with substance use issues, and users reporting unusual experiences showed greater improvements compared to other groups. The most frequently cited reasons for improvement included “It distracted me,” “I felt less alone,” and “I learned something.” Conclusions: The findings suggest that NowMattersNow.org is an accessible, scalable digital intervention that shows promise for reducing suicidal ideation and emotional distress, particularly in vulnerable populations. Key elements, such as fostering social connectedness, distraction, and educational content, appear to be critical components of its effectiveness, indicating that web-based self-help tools like NowMattersNow.org can provide short-term management of suicidal thoughts and negative emotions. Clinical Trial: NA
Background: Scores and prediction models, such as the MESS score for trauma, and the Wifi classification for diabetic foot ulcers, help in the decision-making process of amputation. However, they can...
Background: Scores and prediction models, such as the MESS score for trauma, and the Wifi classification for diabetic foot ulcers, help in the decision-making process of amputation. However, they can be subjective as they depend on the experience of the medical staff applying them. Objective: Assess the impact of temperature measurement using infrared thermal imaging in extremities salvage. Methods: We included 29 patients who sought a second opinion after an amputation recommendation, infrared thermographic images were acquired to measure the temperature differences (ΔT) between the injured and uninjured limbs. For the saved limbs, we provided clinical follow until 12 weeks. Results: Of the patients enrolled in the study, 27 limbs were salvaged, thermographic images allowed the discrimination of two groups: the first group of 18 patients with negative deltas, ΔT -3.6°C ± 1.99, and a second group of 9 patients with positive deltas, ΔT of 3.36°C ±2.71. None of the groups had a progression to enlargement of their delta in the first 5 days, and at the twelfth week approached to ΔT of 0°C at wound closure. For the two patients who required amputation, one patient showed an initial negative ΔT of -4.3°C, which worsened to -5°C by the fifth day, the other patient showed an initial negative of -4.5°C, which worsened to -5.8°C by the fifth day. Conclusions: Digital infrared thermography is a tool that can help guide limb salvage in patients with uncertain clinical diagnoses. This imaging modality allows visualization of thermal differences and patterns derived from thermal changes in patients at risk of limb amputation. Clinical Trial: This study was approved under registry 08-23 by the Research Ethics Committee of the Hospital Central “Dr. Ignacio Morones Prieto” (CONBIOÉTICA-24-CEI-001-20160427).
Background: The rising prevalence of Parkinson’s disease and the growing demand on the healthcare system underscore the need for accessible and innovative care solutions such as Reality DTx® - an...
Background: The rising prevalence of Parkinson’s disease and the growing demand on the healthcare system underscore the need for accessible and innovative care solutions such as Reality DTx® - an augmented-reality neurorehabilitation program with remotely-prescribed gait-and-balance exercises at home for people with Parkinson’s disease. Objective: At a pre-implementation stage, this qualitative study aimed to explore the acceptability of Reality DTx®. Methods: We conducted semi-structured interviews, guided by the Theoretical Framework of Acceptability, with 22 people with Parkinson’s disease who used Reality DTx® at home for six weeks as part of a clinical feasibility trial. Data was thematically analyzed and thoroughly discussed in triangulation. Results: Participants reported variable perceptions of effectiveness and variable experiences of effort to complete the Reality DTx® program. They viewed Reality DTx® as a valuable complement to supervised physical therapy and emphasized the indispensable role of the physical therapist for external control of long-term exercise adherence and for meaningful feedback on motor performance, as well as the desire for social connection. Flexibility in time and location was mentioned as a very important program characteristic, supporting long-term exercise adherence. Suggestions for improvement included enhanced visibility of progression in scores, increased variation in games, and integration of competitive elements. Conclusions: Remotely-prescribed augmented-reality exercises at home, complementary to supervised physical therapy, are acceptable to people with Parkinson’s disease. The findings inform future Reality DTx® development and implementation from the perspective of people with Parkinson’s, which should be weighted with the perspectives of other stakeholders like clinicians and other key decision makers.
Background: Although chronic pain (CP) is highly prevalent, current modalities are not sufficient in addressing the needs of people living with this condition. Pharmacological treatments for CP can ha...
Background: Although chronic pain (CP) is highly prevalent, current modalities are not sufficient in addressing the needs of people living with this condition. Pharmacological treatments for CP can have severe side effects and increase likelihood of patients overdosing or developing addiction. Behavioral treatments are often indicated for the treatment of CP, but barriers to treatment are common. Virtual reality (VR)-based interventions have shown promise as an effective and potentially accessible form of treatment for CP. However, previous research into VR interventions for people living with CP has not often included diverse populations, including people of racial and ethnic minorities and low socio-economic status. Objective: This study sought to gauge interest of patients with chronic pain in participating in a hypothetical study of at-home VR for CP. Patients were recruited from a low socio-economic and racially and ethnically diverse population. Additionally, the study sought to identify predictors of interest in the intervention. Methods: 42 participants living with CP, recruited from an EMR database, a research participant database, and a pain clinic, completed surveys about demographics, pain levels, technology usage, and knowledge of VR. Bivariate testing was used to determine which, if any, of the above constructs were associated with interest in a hypothetical study of at-home VR for CP. Participants also answered an open-ended question about interest in participating in a VR intervention for CP, that were coded using a thematic analysis framework. Results: Despite low technology use and little knowledge and experience with VR, results showed high interest among patients in participating in a hypothetical study of at-home VR for CP. More frequent email usage and using Facebook predicted being somewhat or very interested in participating in a VR clinical trial for pain. Majority of participants cited interest due to the novelty of VR, followed by desperation for pain relief. Conclusions: Contrary to a comprehensive body of evidence, we did not find attitudinal barriers to participating in a clinical trial of VR. While we found that use of technology and knowledge of VR was low, interest in a virtual reality intervention for CP was high. Future, fully powered studies should seek to confirm the effectiveness of VR treatments for people with CP, especially those from lower socio-economic, and racially/ethnically diverse backgrounds.
Background: Mental health (MH) issues are the leading cause of mortality for young people, highlighting the importance of timely, high-quality, and affordable care. However, recent trends show a decel...
Background: Mental health (MH) issues are the leading cause of mortality for young people, highlighting the importance of timely, high-quality, and affordable care. However, recent trends show a deceleration in the growth of youth mental health (YMH) services capacity in Australia. Meanwhile, digital interventions hold significant potential to sustain and enhance youth mental health outcomes. Objective: This study aimed to evaluate the impact of digital interventions and varying service capacity growth trajectories on YMH outcomes using systems modelling, offering insights into strategic resource allocation for sustained improvements. Methods: Participatory System Dynamics (SD) modelling was used to investigate YMH outcomes, with simulation results projected for 2025-2035. The study focused on individuals aged 15-24 years from a culturally diverse, rapidly expanding urban population, using the WesternSydney PrimaryHealthNetwork(WSPHN) catchment area as the case study. Results: Doubling recent growth rates for specialised MH services, headspace, and referrals to online services, together, could significantly enhance YMH outcomes. Compared to baseline, this strategic investment approach is projected to reduce cumulative years of being in state of moderate to very high psychological distress with disorders, cumulative MH-related emergency department(ED) presentations, and cumulative self-harm hospitalisations, by 14%, 6.4%, and 4.1%,respectively, from 2025 to 2035. Combining digital interventions alongside doubling growth in specialised services yields comparable reductions of 15%, 5.1%, and 4.4% in these indicators. Conclusions: This study emphasises digital technologies as an effective interim and long-term solution to mitigate the slow and uncertain growth in the specialised MH workforce. However, achieving sustained long-term improvements necessitates concurrent investment in expanding the specialised MH workforce.
Background: Cardiac surgeries in Chile lack a national registry for systematic data collection and analysis, limiting insights into procedural outcomes and patient demographics. In response to this ga...
Background: Cardiac surgeries in Chile lack a national registry for systematic data collection and analysis, limiting insights into procedural outcomes and patient demographics. In response to this gap, we developed a web-based platform to support the documentation of high-complexity cardiac surgeries. Objective: Design, develop and implement a cardiac surgery data collection and analysis platform that conforms to international standards to support clinical decision-making and research initiatives. Methods: A web-based platform was developed using the Model-View-Controller (MVC) architecture, incorporating input from healthcare professionals and based on the fourth European Association for Cardio-Thoracic Surgery (EACTS) adult cardiac surgical database report. The platform captures over 160 clinical variables across 15 categories spanning pre-operative, intra-operative, and post-operative stages. Results: The most important result of this study is the creation of the first online platform for documenting cardiac surgeries in Chile.
Since its implementation in 2014, the platform has documented over 4,800 cardiac surgeries, establishing it as the largest database for a single institution in Latin America. The platform offers real-time access to data, supports planning and resource allocation, and enables the systematic evaluation of clinical outcomes. Integrating the EURO SCORE II risk model facilitates a standardized mortality risk assessment. Conclusions: The platform contributes to cardiac surgery data collection in Chile, enabling evidence-based clinical decision-making and public health planning.
It has documented cardiac surgeries for 10 years and has become the official hospital registry tool.
By 2025, its application will be extended to two more centers, with the expectation that it will soon become the national database of cardiac surgeries.
Future developments should improve scalability, interoperability and data analysis to establish a national registry and further align Chilean cardiac surgery practices with international standards.
Background: The opioid crisis remains a critical public health challenge, with opioid use disorder (OUD) imposing significant societal and healthcare burdens. Online communities, such as the Reddit co...
Background: The opioid crisis remains a critical public health challenge, with opioid use disorder (OUD) imposing significant societal and healthcare burdens. Online communities, such as the Reddit community r/OpiatesRecovery, provide an anonymous and accessible platform for individuals in recovery. Despite the increasing use of Reddit for substance use research, limited studies have explored the content and interactions of self-disclosure and social support within these communities. Objective: This study aims to address the following research questions: (1) What content do users disclose in the community? (2) What types of social support do users receive? (3) How does the content disclosed relate to the type and extent of social support received? Methods: We analyzed 32,810 posts and 324,224 comments from r/OpiatesRecovery spanning eight years (2014–2022) using a mixed-method approach. Posts were coded for recovery stages, self-disclosure, and goals, while comments were categorized into informational and emotional support types. A machine learning-based classifier was employed to scale the analysis. Regression analyses were conducted to examine the relationship between post content and received support. Results: The majority of posts were made by individuals using opioids (22.0%) or in initial recovery stages (less than 1 month of abstinence; 27.7%). However, posts by individuals in stable recovery (abstinence for more than five years) accounted for only 1.8%. Informational self-disclosure appeared in 88.3% of posts, while emotional self-disclosure was present in 75.6%. Posts seeking informational support (58.4%) were far more common than those seeking emotional support (2.4%). On average, each post received 9.88 comments (SD = 11.36). The most frequent types of support were fact and situational appraisal (M = 5.62, SD = 6.82) and personal experience (M = 4.88, SD = 5.98), while referral was least common (M = 0.61, SD = 0.50). Regression analyses revealed significant relationships between self-disclosure and received support. Posts containing informational self-disclosure were more likely to receive advice (β = 0.17, p < .001), facts (β = 0.30, p < .001), and opinions (β = 0.11, p < .001). Emotional self-disclosure predicted higher levels of emotional support (β = 0.17, p < .001) and personal experiences (β = 0.07, p < .001). Posts from individuals in addiction stage received more advice (β = -0.06, p < .001) but less emotional support (β = -0.05, p < .001) compared to posts from individuals in later recovery stages. Conclusions: This study highlights the role of self-disclosure in fostering social support within online OUD recovery communities. Findings suggest a need for increasing engagement from individuals in stable recovery stages and improving the diversity and quality of social support. By uncovering interaction patterns, this study provides valuable insights for leveraging online platforms as complementary resources to traditional recovery interventions.
Background: First responders, military personnel and veterans face a disproportionate risk for mental health and wellness issues due to the stress of their occupations. Stigma and confidentiality conc...
Background: First responders, military personnel and veterans face a disproportionate risk for mental health and wellness issues due to the stress of their occupations. Stigma and confidentiality concerns are common barriers to use of traditional mental health services. Digital interventions offer a promising alternative, as they can be anonymous, convenient, and cost-effective. Objective: This study aimed to test GUIDE, a digital wellness app designed for first responders, military personnel, and veterans. We explored the impact of GUIDE on various aspects of wellness, emotional wellbeing, mental health, social connectedness, and personal growth. Methods: This randomized waitlist-controlled trial enrolled 115 participants allocated into 3 groups: GUIDE with financial incentives (GUIDE+Incentives, n=37), GUIDE-only (n=39), or waitlisted GUIDE control (waitlist, n=39). Surveys assessed baseline and post-trial wellness (PERMA total score, WHO-5 score, Personal Wellbeing Score, PERMA Health sub-scale score), emotional wellbeing (PERMA Positive, Negative, and Happiness sub-scale scores; Difficulties in Emotion Regulation Scale), mental health/health (PHQ-8 for depression and GAD-7 for anxiety), social connectedness (PERMA Relationships and Loneliness sub-scale scores), and personal growth (PERMA Accomplishment, Meaning, and Engagement sub-scale scores). App engagement and technical merit were also evaluated. Results: Overall, 93.04% of enrolled participants (107/115) completed the post-trial assessment and were included in our intent-to-treat analyses. In repeated measures ANOVAs, there were no significant group × time interactions. In post-hoc pairwise comparisons of pre-post deltas per group, the GUIDE-only group improved significantly over the Waitlist in wellness, emotional wellbeing, and mental health. No group differences were significant for social connectedness or personal growth measures. Of participants allocated to GUIDE intervention groups, 67.10% (51/76) completed at least three activities per week for all four weeks. GUIDE+Incentives completed significantly more activities, posts and replies compared to the GUIDE-only group – but not lessons, likes, or mood surveys. App engagement was correlated with improvements on wellness, emotional wellbeing, mental health, and personal growth measures, driven mostly by lessons, posts and replies – the educational and peer support aspects of GUIDE. Participants who engaged more felt more accomplished, regardless of feature used. Participants gave GUIDE good appropriateness and feasibility scores, and satisfactory acceptability and usability scores. Exploratory subgroup analyses suggest the app may be most beneficial to military-affiliated individuals and males. Conclusions: This trial indicates that GUIDE-only participants improved significantly compared to the waitlist and that GUIDE is a feasible and appropriate intervention with the potential to improve mental health and wellbeing of first responders, veterans and active military. Financial incentives increased engagement with peer support aspects of GUIDE, but did not lead to significant improvements over the waitlist. Future research should test the effect of longer-term GUIDE use and whether improvements sustain. Clinical Trial: clinicaltrials.gov (NCT06336967)
Background: The use of information technologies, especially virtual reality (VR), to enhance learning experiences in higher education has become a trend. Students face emotional challenges that affect...
Background: The use of information technologies, especially virtual reality (VR), to enhance learning experiences in higher education has become a trend. Students face emotional challenges that affect their academic and personal development, which has led to the need for innovative pedagogical strategies that consider the emotional dimension of learning. VR, along with other emerging technologies, is transforming the teaching-learning process, providing immersive experiences that can enhance students' motivation and academic success. Objective: The main objective of the study is to investigate the usability, user experience and acceptability of an immersive learning experience called ‘EmotionLab’, designed to promote emotional regulation in higher education students through the use of Oculus Quest 2 virtual reality goggles. Methods: The study is based on a post-positivist research paradigm and uses a quasi-experimental design with a single test in each case, considering the subjects as multiple case studies. A non-probabilistic purposive sampling was used with 12 students from DuocUC, Viña del Mar, from different careers. The instruments used include the ‘EmotionLab’ prototype built with Unreal Engine 5, Oculus Quest 2 glasses, and user experience questionnaires (UEQ) and Net Promoter Score (NPS). The key performance indicators (KPIs) evaluated were time on task, error rate and abandonment rate. Results: The results show a predominantly positive user experience, with high scores for usability and overall satisfaction. The pragmatic quality (usability) scored a mean of 2.0, and the hedonic quality (user experience) scored a mean of 2.64. The NPS was 91.67, indicating a high level of satisfaction and loyalty among users. No signs of ‘cybermare’ or dropouts were reported during the experience. Participants perceived a sense of calm and emotional control, highlighting the usefulness of the emotional regulation techniques offered. Conclusions: The ‘EmotionLab’ prototype proves to be a valuable tool for emotional regulation in academic contexts, with potential to transform higher education by providing a more interactive and engaging learning environment. Future studies with larger and more diverse samples are suggested to confirm these results and explore long-term impacts. Furthermore, it is recommended to investigate how this tool could be adapted to different educational contexts and age groups, and to consider the integration of complementary technologies such as artificial intelligence to further personalise the learning experience.
Background: Falls among older adults are a significant public health concern, often leading to severe injuries, decreased quality of life, and substantial healthcare costs. Smart wearable technology s...
Background: Falls among older adults are a significant public health concern, often leading to severe injuries, decreased quality of life, and substantial healthcare costs. Smart wearable technology systems for balance rehabilitation present a promising avenue for addressing the falls epidemic, capable of providing detailed objective movement data, engaging visuals, and real-time feedback. With the recent and rapid evolution of innovative technologies, including artificial intelligence (AI), augmented reality (AR)/virtual reality (VR), and motion tracking, there is a need to evaluate the market to identify the most effective and accessible smart balance systems currently available Objective: This review aims to evaluate the current landscape of smart wearable technology solutions for balance rehabilitation in older adults at risk of falls. Additionally, it aims to compare market available systems to TeleRehab DSS, a recently developed smart balance system Methods: A scoping review and SWOT analysis was completed, exploring the landscape of smart balance systems in older adults at risk of falls. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews guidelines, electronic databases PUBMED, MEDLINE, and Cochrane were systematically searched for articles in English from July 1, 2014, to July 1, 2024. Grey literature searches of relevant institutions and webpages were also conducted. The database search and commercial systems were then compared against the TeleRehab DSS in a SWOT analysis Results: The scoping review yielded 17 systems that met the inclusion criteria; 10 investigational systems and 7 commercially available systems. Only one study reported the use of intelligent learning/AI. Eight studies reported the use of motion tracking, with two protocols not reporting its use. Of the studies incorporating motion tracking, three provided feedback as either visual or auditory. Nine of the 10 included studies incorporated either AR or VR, with one study using a computer interface. All but two studies reported the use of gamification, and seven studies incorporated balance exercises. Two studies reported remote delivery, with five being clinician-supervised and four providing a clinician report. The SWOT analysis of TeleRehab DSS against the 7 market-available smart balance systems revealed several unique advantages including personalized therapy with AI-DSS, AR for real-world interaction, enhanced clinician involvement, and comprehensive data analytics.
Conclusions: Despite limitations such as cost, accessibility, and user training requirements. Conclusions: Despite limitations such as cost, accessibility, and user training requirements, TeleRehab DSS emerges as a significant innovation in smart balance systems. It offers a unique blend of AI personalization, AR, and real-time clinician monitoring for balance rehabilitation among middle-aged and older adults at risk of falls. These features position it as a next-generation solution that aligns closely with the evolving needs of patients and clinicians.
Background: Resistant hypertension presents significant clinical challenges, often precipitating a spectrum of cardiovascular complications. Particular attention recently has focused on the role of Ma...
Background: Resistant hypertension presents significant clinical challenges, often precipitating a spectrum of cardiovascular complications. Particular attention recently has focused on the role of Matrix metalloproteinase-2 (MMP-2) gene polymorphisms, implicated in hypertensive target organ damage. Despite growing interest, the specific contribution of MMP-2 polymorphisms to such damage in resistant hypertension remains inadequately defined. Objective: This study is the first to examine the rs243865 (-1306C>T) polymorphism in the MMP-2 gene in the Vietnamese population and in patients with resistant hypertension (RH), underscoring its critical role as a genetic determinant of target organ damage (TOD). Methods: A cross-sectional study with both descriptive and analytical components, in 78 patients with resistant hypertension at the Can Tho Central General Hospital and Can Tho University of Medicine and Pharmacy Hospital from July 2023 to February 2024. Results: More than three-quarters of RH patients had carotid-femoral PWV >10 m/s and microalbuminuria at prevalence of 79.5% and 75.6%, respectively. And more than half of RH patients had LVMI, relative wall thickness and carotid artery stenosis with the prevalence of 56.4%, 55.1% and 52.6%, respectively. Of 78 studied resistent hypertension patients, the presence of genotype CC was 76.9%, genotype CT accounted for 20.5% and 2.6% of genotype TT. The percentage of SNP rs243865(-1306C>T) carring allele T was 23.1%. The MMP-2 gene polymorphism 1306C/T (rs243865) was significantly associated with EF and carotid artery stenosis with OR (95%CI) of 8.1(1.3-51.4); p=0.026 and 4.5(1.1-20.1); p=0.048 respectively. The allele T was found to be significantly associated with arterial stiffness including Brachial-ankle PWV and Carotid-Femoral PWV with the correlation coefficient (95%CI) of 2.2 (0.6-3.8) and 1.8 (0.5-3.2) respectively. Conclusions: The MMP-2 gene polymorphism rs243865 (-1306C>T) may have an association with measurable target organ damage in resistant hypertension.
Background: Freezing of gait (FOG) is a common and debilitating symptom of parkinsonism. Although visual cues have proven efficacy in alleviating FOG, current visual cues are fixed, and mobile open-lo...
Background: Freezing of gait (FOG) is a common and debilitating symptom of parkinsonism. Although visual cues have proven efficacy in alleviating FOG, current visual cues are fixed, and mobile open-loop system may be too difficult to use in some patients, leading to equivocal results in improving gait performance. Objective: To assess the efficacy of an ankle bracelet laser, a new mobile visual cue with practical use, in improving gait performance in parkinsonism patients with FOG. Methods: A randomized controlled two-period crossover trial was conducted from June 15th, 2020 to October 1st, 2020 at Ramathibodi Hospital. Ten parkinsonism patients with FOG were enrolled in two conditions: walking with laser-off first and walking with laser-on first. Gait speed, the Timed Up and Go (TUG) test, stride length, and the locomotor rehabilitation index (LRI) were assessed twice in each trial with a 10-minute washout period. Results: The results showed favorable results of improvement in all parameters. Gait speed and stride length improved by 0.07 m/s (95% confidence interval [CI]: 0.04–0.09; P < 0.001) and 0.17 m (95% CI: 0.11–0.23; P < 0.001), respectively, with laser-on. The TUG test duration was reduced by 7.69 s (95% CI: 2.82–12.55; P=0.002). The locomotor rehabilitation index (LRI) improved by 4.46% (95% CI: 2.56–6.36; P<0.001). When using the device, there were no adverse effects, such as dizziness or blurred vision. Conclusions: The ankle bracelet laser improved walking performance in parkinsonism patients with FOG immediately and might have the potential to provide cueing during daily life. Clinical Trial: TCTR20210511001
Objective: To explore the feasibility of using publicly available mainstream large language models (LLMs) to evaluate the consistency and diagnostic accuracy of standardized ultrasound imaging reports...
Objective: To explore the feasibility of using publicly available mainstream large language models (LLMs) to evaluate the consistency and diagnostic accuracy of standardized ultrasound imaging reports, using pathology as the reference standard.
Materials and Methods: This retrospective study collected ultrasound imaging data of breast nodules with pathological diagnoses obtained at our hospital from June 2019 to June 2024. ChatGPT-4 was employed to evaluate the BI-RADS classification and benign or malignant nature of the nodules. The diagnostic performance of the LLM and the human-machine dialogue method (image-to-text–LLM) was assessed, including accuracy, sensitivity, specificity, and the area under the receiver operating characteristic curve (AUC).
Results: A total of 671 patients (mean age 45.82 ± 9.20 years [SD]; age range 26–75 years) with 671 breast nodule ultrasound images (385 benign, 286 malignant) were included. ChatGPT-4 achieved an overall accuracy of 96.87% in identifying BI-RADS classifications, surpassing the performance of two junior radiologists. For image interpretation, ChatGPT-4 achieved an AUC of 0.82 (95% CI: 0.79–0.85), an accuracy of 80.63% (541 of 671 cases), a sensitivity of 90.56% (259 of 286 cases), and a specificity of 73.51% (283 of 385 cases). Its diagnostic performance was comparable to that of two senior radiologists and superior to two junior radiologists. When utilizing the image-to-text–LLM, diagnostic performance, including AUC, accuracy, sensitivity, and specificity, improved for all four radiologists.
Conclusion: The application of LLMs (particularly the image-to-text–LLM) demonstrates potential value in diagnosing breast ultrasound imaging data.
Background: In modern, high-speed work settings, the significance of mental health disorders is increasingly acknowledged as a pressing health issue, with potential adverse consequences for organizati...
Background: In modern, high-speed work settings, the significance of mental health disorders is increasingly acknowledged as a pressing health issue, with potential adverse consequences for organizations, including reduced productivity and increased absenteeism. Over the past few years, various mental health management solutions, such as biofeedback applications, have surfaced as promising avenues to improve employees' mental well-being. Objective: To gain deeper insights into the suitability and effectiveness of employing biofeedback-based mental health interventions in real-world workplace settings, given that most research has predominantly been conducted within controlled laboratory conditions. Methods: A systematic review was conducted to identify studies that used biofeedback interventions in workplace settings. The review focused on traditional biofeedback, mindfulness, app-directed interventions, immersive scenarios, and in-depth physiological data presentation. Results: The review identified nine studies employing biofeedback interventions in the workplace. Breathing techniques showed great promise in decreasing stress and physiological parameters, especially when coupled with visual and/or auditory cues. Conclusions: Future research should focus on developing and implementing interventions to improve well-being and mental health in the workplace, with the goal of creating safer and healthier work environments and contributing to the sustainability of organizations.
Background: Brain or central nervous system injuries often lead to impaired walking ability, and traditional ankle-foot orthosis (AFO) can improve gait but is cumbersome to produce and difficult to me...
Background: Brain or central nervous system injuries often lead to impaired walking ability, and traditional ankle-foot orthosis (AFO) can improve gait but is cumbersome to produce and difficult to meet individual needs. In recent years, 3D printing technology has shown potential for assistive device manufacturing due to its high efficiency and accuracy, but clinical research in AFO is still limited. Objective: Individualized AFO was created using 3D scanning and printing technology, and a nine-week training program was used to test its effect on improving stroke patients' walking speed, balance, and gait. Methods: This study, 20 stroke patients were recruited to wear 3D AFO to test lower limb function, walking speed, and balance. Methods include the "Walking Speed Test (GST)", "Borg Balance Scale (BBS)" and "Stand Up Walking Test (TUG)" to measure the clinical effect of patients wearing AFO. Results: Patients wearing 3D AFO walked significantly faster and performed better than those with conventional AFO versus those without AFO. Statistical analysis showed that the improvement in the withdrawal period reached a significant level (Z = 2.64, p < 0.01) and the observer confidence of the Borg balance scale reached 90.45%. Besides, the gait cycle was shortened to 9.8 seconds, and the walking speed was increased to 0.79 m/s, which effectively enhanced the patient's gait stability and walking ability. Conclusions: The experimental results showed that 3D AFO could effectively improve the walking speed and gait compensation of stroke patients. In the future, the influence of long-distance testing and the friction coefficient between different materials and the ground on adaptability can be discussed.
Background: Non-small cell lung cancer (NSCLC) is one of the leading causes of cancer-related mortality worldwide. PD-1 immunotherapy has shown promising results in the treatment of NSCLC; however, no...
Background: Non-small cell lung cancer (NSCLC) is one of the leading causes of cancer-related mortality worldwide. PD-1 immunotherapy has shown promising results in the treatment of NSCLC; however, not all patients respond effectively to this treatment. Identifying predictive biomarkers for PD-1 therapy response is critical to improving patient outcomes and optimizing treatment strategies. Traditional methods of biomarker discovery often fall short in terms of accuracy and comprehensiveness. Recent advancements in deep learning provide a powerful approach to analyze complex genomic data and identify novel biomarkers that may predict therapeutic responses. Objective: This study aims to leverage machine learning techniques, particularly deep neural networks (DNN), to identify genomic biomarkers for predicting responses to PD-1 immunotherapy in NSCLC patients. By applying the DeepImmunoGene model to RNA-seq data, the study compares the performance of DNN, SVM, and XGBoost in predicting patient responses. It focuses on identifying key biomarkers through feature selection and deep learning that can enhance patient stratification and improve the accuracy of PD-1 immunotherapy predictions, contributing to more personalized treatment strategies. Methods: Differentially expressed genes (DEGs) were identified in RNA-seq data from 355 NSCLC patients using the LIMMA package in R, followed by preprocessing with log2 transformation. Machine learning models, including Support Vector Machines (SVM), XGBoost, and Deep Neural Networks (DNN), were employed to analyze gene expression data, with hyperparameters optimized using GridSearchCV. The DNN model's predictive performance was evaluated with permutation importance to identify genes critical for immunotherapy response. The models were trained on 284 patients, with 71 used for testing. Evaluation metrics like accuracy, AUC, precision, recall, specificity, and F1 score were used to assess performance. Statistical significance was tested using the Kruskal-Wallis test. Results: Initially, we identified 1,093 differentially expressed genes from RNA-seq data of 355 patients. We then trained models using SVM, XGBoost, and DNN to predict immunotherapy response. The DNN model outperformed both SVM and XGBoost with an accuracy of 82%, AUC of 90%, and recall of 0.85, significantly improving predictive performance by capturing non-linear relationships in gene expression data. To identify key biomarkers, we performed a permutation importance analysis, narrowing down the gene set to 98 genes. DeepImmunoGene, trained on these 98 genes, showed superior results, with an accuracy of 85% and an AUC of 90%. The top 36 upregulated genes in responders and 62 upregulated genes in non-responders were identified, which could serve as potential biomarkers for predicting response to PD-1 inhibitors. These findings suggest that the DeepImmunoGene model, with its ability to capture complex gene interactions, can reliably predict immunotherapy outcomes and provide insights into the molecular mechanisms of response, paving the way for more personalized treatment strategies. Conclusions: The DeepImmunoGene predictive model has successfully identified 36 upregulated genes that may serve as potential genomic biomarkers for predicting NSCLC patient responses to PD-1 immunotherapy. Notably, the ten most significant genes—GSTT2B, HMGA2, AC135050.2, ANKRD33B, MMP13, PLA2G2D, RASGEF1A, BIRC7, DCAF4L2, and CHMP7—offer valuable insights into the underlying mechanisms of treatment responses. These biomarkers not only help predict which patients are most likely to respond to PD-1 immunotherapy but also shed light on the molecular factors that explain non-response.
Background: Heart transplant patients (HTx) are expected to perform self- management behaviors to maximize transplant-related health outcomes. Using mobile health(m-Health) care applications could sup...
Background: Heart transplant patients (HTx) are expected to perform self- management behaviors to maximize transplant-related health outcomes. Using mobile health(m-Health) care applications could support disease self-management. Prior studies showed that mHealth information needs for HTx self-management were identified through: medical care related reminders, laboratory querying, experience sharing, diet and nutrition, and expert counseling. Objective: To develop and evaluate the application (iHeart App) acceptability, employing mixed methods including a Technology Acceptance Model of Mobile Services (TAMM) questionnaire, narrative pros and cons feedback, and log data analysis. Methods: Post HTx patients in northern Taiwan participated from April to July 2019. Six TAMM factors assessed perceived values, ease of use, adoption, trust, intention to use, and actual usage. Open-ended questions collected pros and cons feedback at baseline and one-month follow up. Log database analysis considered administering medication, blood pressure, and symptom self-recording over one year. Results: A total of 53 eligible patients participated, with a mean age of 48.9 years (SD=11.67); the average transplant time was 9.2 years (SD=6.93); mostly male (n=46, 86.8%); and with a high school degree (n=19, 35.8%). Participants had higher acceptance at baseline than one-month follow up in six TAMM perceived factors (mean of difference between 0.321and 0.582, p≦ .001). The number of positive feedbacks was more than the negative feedback (85 vs. 57) and mostly on perceived ease of use (42). The actual usage of iHeart App were high at first month on administering medication(n=740), blood pressure(n=348), and symptoms(n=20), respectively, but significantly decreased over the 12 months. Conclusions: The study showed that patients with HTx accepted iHeart App as the supportive technology to facilitate their self-management. The negative feedback and one-year actual usage analysis provided useful information to optimize the App on the communication with the health care professional team to sustain the long-term usage. Clinical Trial: IRB CHGH-IRB (669)107A-41
Background: Effective data management is crucial in clinical studies for precise tracking, secure storage, and reliable analysis of samples. Traditional systems often encounter challenges like barcode...
Background: Effective data management is crucial in clinical studies for precise tracking, secure storage, and reliable analysis of samples. Traditional systems often encounter challenges like barcode recognition errors, inadequate data detail, and diminished performance under heavy workloads. Objective: This paper aims to enhance clinical data management by improving barcode robustness, increasing data granularity, and boosting system throughput. These improvements address key challenges in barcode informatics systems, as highlighted in prior studies, to better support real clinical applications. Additionally, we aim to validate the design criteria on various gastrointestinal (GI) related studies, ensuring it can be easily integrated into other clinical data management workflows. Methods: We evaluated the robustness of various barcode technologies under significant blurring conditions, implemented a dynamic organ-specific archive in the REDCap database for various clinical study data collection criteria, and utilized Docker to containerize the informatics software for different studies. Additionally, we proposed a local cache system to reduce interaction times with REDCap for large-scale data records. Experimental setups include assessing barcode recognition accuracy under various levels of image blurring, showcasing different study types managed with the organ-specific archive, and measuring system throughput and response times with and without the proposed local cache system. Results: Our findings demonstrate that the DataMatrix barcode exhibits superior resilience, maintaining high recognition accuracy under blurred conditions. The dynamic organ-specific archive in REDCap enabled precise tracking of sample origins, improving data granularity. Docker containerization streamlines software deployment and ensures consistency across studies. The local cache system significantly reduces interaction times with REDCap, decreasing operating time by nearly eightfold compared to the naïve strategy when handling large patient datasets. Conclusions: The proposed enhancements significantly improve barcode robustness, data granularity, and system throughput in the informatics system, addressing key limitations identified in previous studies. These optimizations ensure efficient data management and robust support for diverse clinical research needs. Clinical Trial: Combinatorial Single Cell Strategies for a Crohn's Disease Gut Cell Atlas (NCT04113733, https://clinicaltrials.gov/study/NCT04113733?cond=NCT04113733&rank=1&tab=table)
BCCMA: Targeting Gut-Microbiome in Veterans Deployment Related Gastrointestinal and Liver Diseases: Dysbiosis, PTSD, and Epithelial and Immune Biology in Inflammatory Bowel Disease in Veterans (I01CX002473-01A2, https://research.va.gov/about/funded_research/proj-details-FY2024.cfm?pid=759730)
Dysregulated Polyamine Metabolism in H. pylori-associated Gastric Inflammation and Disease Progression (I01CX002171-01, https://research.va.gov/about/funded_research/proj-details-FY2024.cfm?pid=759730)
The Role of CCL11 in Inflammatory and Sporadic Colorectal Cancer.
(I01CX002662-01A2, https://www.research.va.gov/about/funded_research/proj-details-FY2025.cfm?pid=802842)
CCL11 as a New Therapeutic Target for Colitis and Colon Cancer (I01BX004366-01A2, https://research.va.gov/about/funded_research/proj-details-FY2024.cfm?pid=636361)
Background: As Virtual Reality (VR) technology becomes increasingly prevalent, its potential for collecting objective behavioral data in psychiatric settings has been widely recognized. However, the l...
Background: As Virtual Reality (VR) technology becomes increasingly prevalent, its potential for collecting objective behavioral data in psychiatric settings has been widely recognized. However, the lack of standardized methodologies limits reproducibility and data integration across studies, particularly in assessing attention deficit hyperactivity disorder (ADHD) and associated behaviors such as irritability and aggression. Objective: This study examines the utility of VR-based movement data to operationalize core ADHD symptoms (hyperactivity and inattention) and comorbid disruptive behaviors (irritability and aggression), aiming to identify reproducible and clinically actionable metrics. Methods: Forty-five children (mean age = 9.06 years, SD = 2.11; 14 female) participated, including 28 diagnosed with ADHD and 17 controls. Seven VR-derived movement variables were analyzed: average speed, acceleration, total distance, area occupied, distance between hands and head, frequency of movement, and time spent still. Correlation and regression analyses identified which variables best predicted ADHD symptoms and comorbid behaviors. Results: Total distance emerged as the strongest predictor of hyperactivity (β = 0.52, p < 0.01), while average speed was inversely associated with inattention (β = -0.45, p < 0.05) and positively correlated with aggression (β = 0.38, p < 0.05). More frequent but less intense movements predicted lower irritability (β = -0.41, p < 0.05) and aggression (β = -0.36, p < 0.05). These findings highlight consistent patterns, underscoring the potential of VR-derived movement variables as standardized metrics. Conclusions: This study emphasizes the importance of standardized VR methodologies to enhance reproducibility and data integration in psychiatric research. By identifying specific movement variables that reliably predict ADHD and comorbid behaviors, the findings establish a foundation for developing scalable VR tools for clinical assessment and intervention.
Background: Pediatric and adolescent firearm injuries and fatalities have reached levels not seen since the mid-1990s, indicating a critical juncture in US public health. Young Black males, ages 15-24...
Background: Pediatric and adolescent firearm injuries and fatalities have reached levels not seen since the mid-1990s, indicating a critical juncture in US public health. Young Black males, ages 15-24, represent the worst affected demographic, exhibiting a 24-fold higher probability of firearm-related fatalities compared to their White peers. This crisis is compounded by low engagement in firearm violence intervention programs among young Black males, emphasizing the urgent need for timely, culturally appropriate, and innovative interventions addressing the socioemotional, relational, and behavioral factors driving violence in this demographic. Objective: This pilot study aims to evaluate the efficacy of a novel app-based intervention (BrotherlyACT)—a nurse-led, culturally tailored, multicomponent smartphone application—to reduce the risk and effects of firearm injuries and homicides and to improve access to pre-crisis and mental health resources for young Black male individuals (aged 15-24 years) in low-resource and high-violence settings. Methods: Seventy young Black males with a SaFETy score between 1 and 5 (indicating low to moderate firearm violence risk) were enrolled in this prospective pretest/posttest study. The study assessed a psychoeducational intervention (seven video-based modules) via the BrotherlyACT app. Following consent, participants completed a 63-item survey battery pre- and post-intervention, evaluating Attitudes Towards Guns and Violence (AGVQTM), aggression (Reactive-Proactive Aggression Questionnaire), Psychological Distress (Kessler Psychological Distress Scale [K10]), and depression (Patient Health Questionnaire [PHQ-8]). Surveys were re-administered 4 weeks after the pretest. Outcome measures were reported as total and subscale scores. Paired-sample t-tests analyzed pre-post outcome changes. Results: 70 YBM enrolled (Mage = 21.21 ± 3.16 years, 10% Hispanic); 26.3% had some high school education. Nearly half (48.6%) worked part-time, with 66.4% reporting an annual household income of US $40,000-$59,999. Almost all participants (96.9%) finished the video modules in one session, and 67.7% did so within an hour. Statistically significant reductions in attitudes towards guns and violence were observed from pretest (M = 29.8) to posttest (M = 26.1), with a mean difference of 3.69 (p < .0001, Cohen’s d = 0.53). The ‘Aggressive Response to Shame’ subscale showed the highest reduction (↓28%), followed by ‘Excitement Towards Guns and Violence’ (↓14.8%). Reactive aggression scores significantly decreased from 10.48 to 8.67 (p = 0.003), while proactive aggression scores showed no significant reduction (p = 0.305). No significant changes were observed in depression, anxiety, or overall psychological distress. Conclusions: BrotherlyACT demonstrated efficacy in reducing negative attitudes towards firearms and violence, and reactive aggression among young Black males. These findings indicate that this digital intervention has the potential to address both attitudinal and behavioral factors in a medium to high-risk population, presenting a unique opportunity for the primary prevention of firearm violence and associated risk factors for youth violence. Clinical Trial: Title Registration: ClinicalTrials.gov NCT06359990.
IRRID: RR2-10.2196/43842
Background: The utilisation of conversational agents (CAs) in mental health therapy is gaining traction due to their accessibility, anonymity, and nonjudgmental nature. However, understanding the psyc...
Background: The utilisation of conversational agents (CAs) in mental health therapy is gaining traction due to their accessibility, anonymity, and nonjudgmental nature. However, understanding the psychological factors driving preferences for CA-based therapy remains critical to ensure ethical and effective application. Variables such as epistemic trust, attachment styles, personality traits, and fear of intimacy appear central in shaping attitudes toward these AI-driven interventions. Objective: This study aimed to investigate the psychological determinants influencing individuals’ willingness to engage with CA-based therapy, focusing on epistemic trust, attachment styles, personality traits, and fear of intimacy. Methods: An online survey was administered to 876 students enrolled in a master's program in psychology, yielding 736 responses (84.01% response rate). After excluding one outlier, the final sample included 735 participants (mean age = 27.69, SD = 12.31; 25.98% males). Variables measured included epistemic trust (ETCMQ, Cronbach’s α = 0.95), attachment styles (RQ, α = 0.97), personality traits (PID-5-BF, α = 0.87), and fear of intimacy (FIS-HP, α = 0.94). A five-point ordinal scale assessed willingness to engage in CA-based therapy. The data were analysed using ordinal logistic regression models, including Proportional Odds Models (POM), Non-Proportional Odds Models (NPOM), and Partial Proportional Odds Models (PPOM), with residual deviance used to compare model fit. Results: The PPOM provided the best fit (residual deviance = 3530.472) compared to NPOM (6244.009). Epistemic trust significantly increased willingness to engage with CA-based therapy across all levels (OR = 1.745, p < 0.0001). Fear of sharing exhibited a non-uniform effect, with greater fear correlating with higher willingness at advanced thresholds (OR = 1.086, p = 0.001). Personality traits, particularly detachment (OR = 0.95, p = 0.001) and psychoticism (OR = 1.12, p = 0.003), were significant predictors, as were relational factors such as being single (OR = 3.717, p < 0.0001). Attachment patterns showed nuanced effects, with fearful-avoidant styles less likely to prefer human interactions (p = 0.34). Conclusions: Epistemic trust and fear of intimacy emerged as pivotal factors influencing preferences for CA-based therapy, underscoring the role of interpersonal dynamics and emotional vulnerabilities. The findings suggest that individuals with avoidant attachment styles or maladaptive personality traits are more inclined toward AI-mediated interventions, driven by reduced fear of judgment and increased perceived safety. These insights highlight the need for ethical considerations and personalised approaches in deploying CA-based mental health tools to balance user reliance with human-centric therapeutic values. Clinical Trial: Not applicable.
Background: Effective communication is fundamental to high-quality healthcare delivery, influencing patient satisfaction, adherence to treatment plans, and clinical outcomes. However, communication sk...
Background: Effective communication is fundamental to high-quality healthcare delivery, influencing patient satisfaction, adherence to treatment plans, and clinical outcomes. However, communication skills training for medical undergraduates often faces challenges in scalability, resource allocation, and personalization. Traditional methods, such as role-playing with standardized patients, are resource-intensive and may not provide consistent feedback tailored to individual learners' needs. Artificial Intelligence (AI) offers realistic patient interactions for education. Objective: This study aims to investigate the application of Artificial Intelligence (AI) -powered communication training tools in medical undergraduate education within a primary care context. The study evaluates the effectiveness, usability, and impact of AI virtual patients (VPs) on medical students' experience in communication skills practice Methods: A mixed methods sequential explanatory design was employed, comprising a quantitative survey followed by qualitative focus group discussions. Eighteen participants, including 15 medical students and 3 practicing doctors, engaged with an AI VP simulating a primary care consultation for prostate cancer risk assessment. The AI VP was designed using a large language model (LLM) and natural voice synthesis to create realistic patient interactions. The survey assessed five domains: fidelity, immersion, intrinsic motivation, debrief, and system usability. Focus groups explored participants' experiences, challenges, and perceived educational value of the AI tool. Results: A mixed methods sequential explanatory design was employed, comprising a quantitative survey followed by qualitative focus group discussions. Eighteen participants, including 15 medical students and 3 practicing doctors, engaged with an AI VP simulating a primary care consultation for prostate cancer risk assessment. The AI VP was designed using a large language model (LLM) and natural voice synthesis to create realistic patient interactions. The survey assessed five domains: fidelity, immersion, intrinsic motivation, debrief, and system usability. Focus groups explored participants' experiences, challenges, and perceived educational value of the AI tool. Conclusions: AI can significantly enhance communication skills training for medical undergraduates by providing a scalable, accessible, and realistic simulation environment. Despite some technical challenges, the AI tool was well-received, indicating its potential for broader adoption in medical education. Continued development and refinement of AI technologies will be essential to prepare future healthcare professionals for real-world patient interactions.
Background: Healthcare chatbots can be used to support patients with everyday decision-making. While there is some research on integrating artificial intelligence (AI) into paediatric care, no study h...
Background: Healthcare chatbots can be used to support patients with everyday decision-making. While there is some research on integrating artificial intelligence (AI) into paediatric care, no study has focused on the opportunity of implementing a generative AI (genAI) chatbot for paediatric rheumatology. Paediatric Rheumatology conditions require intense family input, which can often leave families struggling to navigate disease flares, pain, fatigue, medication side effects and adherence and support of their child, often when paediatric rheumatology departments are shut. Understanding how we can support families better, without the need for increased personnel, will have implications for the healthcare systems. Objective: The study aimed to explore children and young peoples (CYP) and parental acceptance of chatbot use in a paediatric context and understand how a chatbot can be specifically utilised for managing a child’s chronic health condition. Methods: This study was a mixed-methods design, utilising both a family workshop and subsequent questionnaire. Results: In total, 22 participants contributed to the table at the world care methodology workshop and 47 participants (36 parents and 11 children and young people) completed the questionnaire. Participants expressed their likelihood of using chatbot technology, including ChatGPT, due to its accessibility. However, participants had significantly greater intention (CYP: p=.006; Parents: p <.001) to use a specific chatbot over ChatGPT, due to increased trust, credibility, and specificity in design. CYP and parents should be distinguished as two user groups in chatbot design, reflecting their specific needs in chatbot features and personalisation. Conclusions: Overall, the study reinforced the need for a specialised and trusted chatbot designed with input from health professionals to assist families in managing complex chronic health conditions. Future research should evaluate users’ engagement with a functional prototype to investigate its usefulness and explore its implementation into families’ everyday life. Importantly, the current findings have broader implications for the field of paediatric healthcare, as similarly tailored chatbot interventions could benefit families who are managing other chronic health conditions.
Background: Compensatory cognitive training (CCT) is an evidence-based treatment for improving cognitive function in patients with schizophrenia. However, the need for patients to commute to treatment...
Background: Compensatory cognitive training (CCT) is an evidence-based treatment for improving cognitive function in patients with schizophrenia. However, the need for patients to commute to treatment sites hinders its widespread use. Using a remote device to conduct CCT could improve its accessibility, making it easier for participants to adjust their schedules and reducing their burden. Objective: The purpose of this study was threefold: to investigate the creation and participant acceptability of CCT using a remote device (r-CCT); to determine the feasibility of implementing the created training; and to collect preliminary data for future studies of the effectiveness of r-CCT in Japan. Methods: To reduce participant movement during training, CCT was conducted once a week for 2 h, for a total of 12 sessions, using remote equipment. Four patients with schizophrenia who underwent r-CCT were recruited to determine participation or dropout rates across 12 training sessions. In addition, their diagnostic assessment, cognitive function, social functioning, and quality of life (QOL) were assessed before, immediately after, and 3 months after implementation. Results: The average participation rate of the three participants (a male in his thirties was excluded) was 92%. Immediately after the r-CCT, their cognitive function and QOL—except for prospective memory¬—were similar to those reported in previous studies. Their QOL was also similar to levels reported in previous studies after 3 months. Conclusions: Despite this study’s small number of participants and lack of randomization, it suggests that the accessibility and implementation potential of r-CCT may be high. The ability to participate in training from any location could be expected to increase participation rates or reduce dropout rates. In the future, the authors will develop the implementation method further and increase the sample size to demonstrate the training’s effectiveness.
Background: This research examines the equitable distribution of healthcare resources and its impact on patient outcomes, along with the relationship between resource allocation strategies, health car...
Background: This research examines the equitable distribution of healthcare resources and its impact on patient outcomes, along with the relationship between resource allocation strategies, health care quality and operational efficiency in Taiwan's healthcare system. Objective: It also investigates the role of Artificial Intelligence (AI) in optimizing the operational efficiency and improving patient outcomes Methods: A mixed-methods approach integrates qualitative data from semi-structured interviews, analyzed with NVIVO software, and quantitative data from surveys administered to hospital administrators, safety teams, and financial personnel. This methodology provides a comprehensive understanding of resource allocation strategies and their effects on healthcare outcomes and efficiency. Seven healthcare institutions were selected through sequential random sampling based on size, location, and specialty services, ensuring a diverse representation for analyzing resource allocation strategies. The qualitative component involved semi-structured interviews with 29 patients, while the quantitative component included surveys with 129 participants, including hospital administrators, safety teams, and financial personnel Results: Qualitative data were analyzed using NVIVO for thematic exploration, while quantitative data were analyzed with Partial Least Squares Structural Equation Modeling (PLS-SEM) to examine relationships and test hypotheses. The study finds a strong correlation between AI adoption, improved healthcare quality, increased patient care service utilization, and better patient outcomes. Resource allocation alone does not directly affect patient outcomes; rather, operational efficiency serves as a crucial mediating factor Conclusions: Integrating efficient resource management with operational practices is essential for improving patient outcomes. The study provides actionable insights for healthcare administrators to enhance care quality and accessibility and highlights the need for tailored resource management strategies that consider regional and organizational differences within Taiwan’s healthcare system
Background: Hypertension is a significant risk factor for cardiovascular diseases and is associated with an increased risk of mild cognitive impairment (MCI).The lack of effective treatments for these...
Background: Hypertension is a significant risk factor for cardiovascular diseases and is associated with an increased risk of mild cognitive impairment (MCI).The lack of effective treatments for these conditions underscores the urgent need for novel therapeutic approaches. Previous studies have indicated that microcirculation serves as the pathological basis for the comorbidity of hypertension and cognitive dysfunction. Our initial clinical studies have indicated that acupuncture could be a safe and effective treatment for managing hypertension and mild cognitive impairment. Whether acupuncture can enhance hypertension and cognitive impairment by modulating microcirculation, and the precise mechanisms involved, warrants further exploration. Objective: The objective of the trial is to evaluate the clinical efficacy of electroacupunctureon mild cognitive impairment of hypertension patients and to explore whether it can improve hypertension and cognitive impairment by regulating microcirculation. Methods: In this multi-center, large-scale, single-blind, randomized controlled trial, a total of 252 patients with hypertension and cognitive impairment will be recruited from 3 hospitals and randomly assigned to three groups: electroacupuncture(EA) group, sham electroacupuncture(SEA) group, and waiting-list group in a 1:1:1 ratio. The EA group and SEA group will receive either electroacupuncture or sham electroacupuncture for 12 weeks, while the waiting-list group will not receive acupuncture treatment for the first 12 weeks. The primary outcome will be the changes in overall cognitive function as measured by the Montreal Cognitive Assessment (MoCA). The secondary outcomes include blood pressure status, subdomain cognitive function, mental status, sleep quality, hemodynamics, and microcirculation indicators. Results: The study protocol has been approved by the IRB of The First Affiliated Hospital of Tianjin University of TCM. This study was registered on April 26, 2024, with the Chinese Clinical Trial Registry. Data collection began on May 2024 and is expected to end on April 2025. Currently, data from this trial are in the collection phase, and no data analysis has been performed. As of January 1, 2025, we have collected data from 65 patients. The results of this trial are expected to be submitted for publication in July 2026. Conclusions: This clinical trial aims to compare the efficacy of electroacupuncture versus sham electroacupuncture or waiting-list control in treatment of hypertension with cognitive impairment, and to explore its impact on microcirculation through hemodynamic and microcirculatory indices. The results of this trial will contribute to clarifying the microcirculatory mechanisms of electroacupuncture in the treatment of hypertension with cognitive impairment, providing a solid foundation for further research on electroacupuncture therapy. Clinical Trial: The protocol has been approved by the IRB of The First Affiliated Hospital of Tianjin University of TCM(TYLL2023[6]051). Every participant will be informed of detailed information about the study before signing informed consent. The results of this trial will be published in a peer-reviewed journal.
Background: The postpartum period represents a critical period for both birthing and non-birthing parents. Parents navigating this period are often faced with challenges such as exacerbated mental hea...
Background: The postpartum period represents a critical period for both birthing and non-birthing parents. Parents navigating this period are often faced with challenges such as exacerbated mental health conditions, and the complex task of adapting to new caregiving roles. Despite the presence of Collaborative Care Models (CCMs) as a strategic framework to address these multifaceted challenges of this period, the current landscape of postpartum care is fragmented. This fragmentation leads to a lack of continuity of care, failing to address the holistic needs of new parents during the postpartum period. Baby2Home (B2H) is a digital intervention rooted in the CCM, specifically designed to support parents through their transitions into parenthood by addressing their physical, emotional, and psychosocial needs. This intervention seeks to close the gaps left by traditional care models by providing continuous, organized, and accessible support throughout the postpartum period. In our qualitative study of the Baby2Home intervention, we reference the Parallel Journeys Framework and use it as part of our analysis to evaluate whether mHealth technology addresses the holistic needs (postpartum and psychosocial) of new parents. This framework assesses not only the effectiveness of the B2H app in supporting new parents but also in identifying ways in which mHealth can overcome gaps that lie at the intersection of the postpartum care and psychosocial care journeys. Objective: The objective of this study is to evaluate how B2H supports the holistic (postpartum and psychosocial) needs of new parents and addresses any gaps identified by parents in usual care settings. Methods: Semi-structured interviews were conducted to gather insights from both birthing and non-birthing parents who participated in the B2H intervention. A purposive sampling technique was used, and a total of 20 parents (n=20) were selected based on their app usage. The Postpartum Parallel Journeys Framework (PPJF) was utilized as a guiding lens to organize and interpret our analyses. The phases of the PPJF were first created, after which we used an inductive, open-coding methodology for our data analysis. Results: Our findings demonstrate the comprehensive impact of the B2H intervention in addressing both the physical and psychosocial needs of new parents. Parents reported that the B2H app supported the postpartum care journey by: (1) helping them navigate uncertainties during the postpartum period, (2) enhancing communication and collaboration between parents and their healthcare providers, (3) promoting self-care practices, and (4) boosting parental self-efficacy. In terms of psychosocial care, the app supported parents by (5) helping them identify mental health symptoms, (6) providing timely assessments via care manager support, (7) facilitating treatment through coordinated care, and (8) offering resources for a smooth transition out of the Collaborative Care Program.
Our findings also reveal several gaps identified at the intersection of the postpartum and psychosocial care journey. Parents reported ways in which the B2H intervention addresses these gaps by (1) promoting inclusivity by extending mental health support to non-birthing parents, (2) bridging the transition from screening to treatment, (3) helping parents navigate their treatment options in real-time (4) ensure continuity of care by closing the gaps caused by different endpoints in the care journey. Conclusions: This study demonstrates that the use of mHealth technology, such as the B2H app, can effectively support the multifaceted needs of new parents during their postpartum care period. By applying the Parallel Journeys Framework (PJF), the research also uncovers gaps in care addressed by the B2H app, presenting unique opportunities for future development and research. Clinical Trial: NCT05595486
Background: Recent studies have demonstrated that AI can surpass medical practitioners in diagnostic accuracy, underscoring the increasing importance of AI-assisted diagnosis in healthcare. This resea...
Background: Recent studies have demonstrated that AI can surpass medical practitioners in diagnostic accuracy, underscoring the increasing importance of AI-assisted diagnosis in healthcare. This research introduces SMART-Pred (Shiny Multi-Algorithm R Tool for Predictive Modeling), an innovative AI-based application for Alzheimer's disease (AD) prediction utilizing handwriting analysis Objective: Our objective is to develop and evaluate a non-invasive, cost-effective, and efficient AI tool for early AD detection, addressing the need for accessible and accurate screening methods. Methods: Our methodology employs a comprehensive approach to AI-driven Alzheimer's disease (AD) prediction. We begin with Principal Component Analysis for dimensionality reduction, ensuring efficient processing of complex handwriting data. This is followed by the training and evaluation of ten diverse, highly optimized AI models, including logistic regression, Naïve Bayes, random forest, AdaBoost, Support Vector Machine, and neural networks. This multi-model approach allows for a robust comparison of different machine learning techniques in AD prediction. To rigorously assess model performance, we utilize a range of metrics including accuracy, sensitivity, specificity, F1-score, and ROC-AUC. These comprehensive metrics provide a holistic view of each model's predictive capabilities. For validation, we leveraged the DARWIN dataset, which comprises handwriting samples from 174 participants (89 AD patients and 85 healthy controls). This balanced dataset ensures a fair evaluation of our models' ability to distinguish between AD patients and healthy individuals based on handwriting characteristics. Results: The random forest model demonstrated strong performance, achieving an accuracy of 88.68% on the test set during comprehensive model analysis. Meanwhile, the AdaBoost algorithm exhibited even higher accuracy, reaching 92.00% after leveraging AI models to identify the most significant variables for predicting Alzheimer's disease. These results surpass current clinical diagnostic tools, which typically achieve around 81.00% accuracy. SMART-Pred's performance aligns with recent AI advancements in AD prediction, such as the Cambridge scientists' AI tool achieving 82.00% accuracy in identifying AD progression within three years using cognitive tests and MRI scans. Furthermore, our comprehensive analysis utilizing SMART-Pred revealed a consistent pattern across all ten AI models employed. The variables "air_time" and "paper_time" consistently stood out as critical predictors for Alzheimer's disease (AD). These two factors were repeatedly identified as the most influential variables in assessing the probability of AD onset, underscoring their potential importance in early detection and risk assessment of the disease. Conclusions: Even though some limitations exist with SMART-Pred, it offers several advantages, including being non-invasive, cost-effective, efficient, and customizable for complex datasets and disease diagnostics. The study demonstrates the transformative potential of AI in healthcare, particularly in AD prediction, and may contribute to improved patient outcomes through early detection and intervention. Clinical validation is necessary to confirm whether the key variables identified in this study are sufficient for accurately predicting Alzheimer's disease in real-world medical settings. This step is crucial to ensure the practical applicability and reliability of these findings in clinical practice.
Background: Social media platforms, particularly TikTok, have emerged as influential sources of medical information and treatment trends. In early 2024, red light therapy gained substantial attention...
Background: Social media platforms, particularly TikTok, have emerged as influential sources of medical information and treatment trends. In early 2024, red light therapy gained substantial attention on TikTok for skincare applications, despite limited scientific understanding of its long-term effects and safety profile with home use. Objective: To quantify the impact of TikTok exposure on public interest in red light therapy and compare interest trends with conventional skincare treatments. Methods: We analyzed Google Trends data from November 2019 to November 2024 for red light therapy-related terms and control terms. Statistical analyses included trend analysis and structural break detection. Results: Search interest for red light therapy terms showed significant increases post-February 2024 (p<0.001) compared to the previous year. Linear regression revealed significant positive trends for red light therapy terms while control terms showed either no significant trends or slight declines. Conclusions: TikTok's influence significantly increased public interest in red light therapy, surpassing traditional skincare treatments. These findings highlight social media's role in shaping healthcare trends and underscore the need for healthcare providers to stay informed about viral treatments.
Background: Background
Continuous monitoring of patients’ vital signs is critical for early detection of postoperative complications. Traditional manual monitoring by nursing staff is time-consumin...
Background: Background
Continuous monitoring of patients’ vital signs is critical for early detection of postoperative complications. Traditional manual monitoring by nursing staff is time-consuming and provides only intermittent data. Wearable devices offer continuous monitoring capabilities, potentially enhancing early warning systems, reducing nurse workload, and facilitating earlier patient discharge. However, research on their implementation and effectiveness in clinical settings remains limited. Objective: Objectives
This study aims to evaluate the implementation and feasibility of continuous monitoring using PPG-sensor technology (viQtor device) in a surgical ward. It will also assess the impact on nursing workload and the usability of the technology. Methods: Methods
The REQUEST study is a prospective observational study conducted over eight months in a surgical ward. The vital signs of 500 postoperative patients will be continuously monitored using the viQtor device, which measures heart rate, respiratory rate, and oxygenation. The study will be conducted in two phases: a baseline period with manual spot-checks three times daily, followed by a phase where manual checks are conducted on demand. Outcomes will be evaluated using the Integrated Workload Scale (IWS) for nursing workload and a framework examining acceptability, appropriateness, feasibility, adoption, penetration, implementation cost, and sustainability. Data collection will also include device performance metrics, questionnaires (Evidence-Based Practice Attitude and System Usability Scale), and thematic analysis of focus groups. Results: Results
Enrollment will commence in October 2024. Training for staff is underway, and the full implementation of the viQtor device is expected by Month 5. Initial findings are anticipated in early 2025, with outcomes such as feasibility, nursing workload, and device usability under evaluation. Conclusions: Conclusions
The REQUEST study will provide valuable insights into the practical implementation of continuous monitoring in a surgical ward, focusing on its impact on workload and overall feasibility. The findings aim to guide future integration of wearable technology into clinical practice, improving patient outcomes and optimizing resource allocation. Clinical Trial: Trial Registration ClinicalTrials.gov: NCT06574867, Registered on 27 August 2024
Background: The COVID-19 pandemic initiated an unprecedented increase in demand for remote management of type 2 diabetes using secure messaging, or patient-provider text-based communication. Prior res...
Background: The COVID-19 pandemic initiated an unprecedented increase in demand for remote management of type 2 diabetes using secure messaging, or patient-provider text-based communication. Prior research on secure messaging has described the content of messages sent for type 2 diabetes management and demonstrated its impact on clinical outcomes. Additional research is needed to understand providers’ perspectives on the benefits and challenges of using secure messaging to communicate with patients about specific clinical tasks that support diabetes management. Objective: To investigate physicians’ experience using secure messaging to communicate with patients about type 2 diabetes management. Methods: We interviewed a sample of endocrinologists and internists who have used secure messaging to communicate with adult patients about type 2 diabetes management. Semi-structured interviews were used to solicit physicians’ experience using secure messaging for six specific tasks that support diabetes management; refilling prescriptions, answering non-urgent medical questions, scheduling appointments, discussing test results, making referral requests, and discussing visit follow up. Interviews were conducted until we achieved saturation of themes for these six tasks. Data was coded and analyzed using the Framework Method. Results: Ten physicians were interviewed; six internists and four endocrinologists. Physicians reported spending between two and five hours per day messaging with patients. They observed that secure messaging increased the frequency and timeliness of communication, which improved care coordination and facilitated care delivery between visits. This served as a time-efficient way to iterate specific components of treatment plans, including discussing test results, visit follow-up, scheduling, and prescription refill. Physicians were frustrated with the unstructured nature of secure messages. Patients wrote messages that were often disorganized, confusing, or did not have enough information for the provider to take action. In many cases, poorly structured secure messages resulted in lengthy back-and-forth communications between patients and physicians, which sometimes required a phone call or office visit to resolve. Conclusions: Physicians reported that secure messaging supports a longitudinal model of care, where patients can iterate their treatment plan between visits. For tasks with well-defined information boundaries, like scheduling and prescription refill, physicians reported that secure messaging improved the time-efficiency of care delivery. Providers experienced challenges using secure messaging for more complex tasks and often reported not receiving sufficient clinical information. We identified a demand for workflow technologies to process incoming secure messages and fill information gaps so that the messages that reach physicians’ inboxes are clear and have sufficient information for physicians to make a decision about how to proceed with treatment.
Background: Youth and young adult mental health concerns are rising globally, with digital mental health platforms offering a promising solution for accessible support. Among the various features thes...
Background: Youth and young adult mental health concerns are rising globally, with digital mental health platforms offering a promising solution for accessible support. Among the various features these platforms provide, goal-setting and achievement have been shown to positively influence behavior change and mental health outcomes. However, there is limited understanding of how user-set goals compare to those set collaboratively with a practitioner regarding their impact on user engagement and mental health outcomes in digital mental health platforms. Objective: The purpose of this study was to examine the relationship between various goal-related variables (e.g., the number of goals created, progress in user-set and practitioner-set goals) and user engagement, as well as mental health (i.e., psychological distress), within a free digital mental health platform. A secondary exploratory aim was to assess how different user presenting issues were associated with platform engagement. Methods: We leveraged secondary data from a free, web-based mental health platform for youth aged 10-26 in the UK that offers goal-setting features, emotional journaling, peer support, asynchronous chat with practitioners, and various self-guided wellbeing activities. Data included in the analyses were from youth and young adults (average age = 15.84; 75.5% female) who engaged with the goal-setting feature and completed both pre- and post-engagement psychological distress measures (N=691) between January 2020 to December 2023. We examined the relationship between user-set goals and practitioner-set goals on user engagement and psychological distress via linear regressions. The impact of different user presenting issues on engagement was also explored via linear regression. Results: The number of goals and goal progress, whether user-set or practitioner-set, were not significantly associated with platform engagement. Regarding goal progress, greater goal progress in practitioner-set goals was significantly associated with reduced psychological distress (β=-0.27, P<.001), while user-set goal progress showed no significant association (P=.16). School-related and physical health presenting issues were the two strongest predictors of increased platform engagement (β=.23, P<.001 and β=.20, P<.001, respectively). Conclusions: These findings underscore the importance of collaborative goal-setting in improving mental health outcomes for youth and young adults in digital mental health platforms. By highlighting the role of guided support and goal progression, this paper enhances our understanding of how digital mental health platforms can better support young people’s mental health and well-being. This paper also highlights how digital mental health platforms can serve as a valuable resource for addressing a wide range of mental health needs. Clinical Trial: n/a
Socially vulnerable populations have less access to quality gastrointestinal (GI) care. Digital telehealth services provided by GI-focused Registered Dietitian Nutritionists (RDNs) and Digestive Healt...
Socially vulnerable populations have less access to quality gastrointestinal (GI) care. Digital telehealth services provided by GI-focused Registered Dietitian Nutritionists (RDNs) and Digestive Health Coaches (HCs) may improve digestive health outcomes by facilitating access to GI care and thereby reducing healthcare disparities among vulnerable populations. The objectives of this study were to 1) evaluate the impact of a digital digestive health program on reducing GI symptoms among socially vulnerable populations and 2) assess whether telehealth visits with digital application (app)-usage provide additional benefits in symptom reduction compared to digital app-usage alone among socially vulnerable populations. A comprehensive digital digestive care program with optional telehealth visits with RDNs and HCs was provided to US employees of participating companies via their employee benefits. We enrolled participants in the program between 2022-2023, and they tracked symptoms at least twice within 30-90 days. We measured changes in GI symptoms from baseline to up to 3 months, comparing those who opted for telehealth visits with those who used the app only. We stratified participants by the median Social Vulnerability Index (SVI) in our cohort to evaluate symptom improvement across socially vulnerable populations. Multivariable regressions adjusted for age, gender, race, BMI, and pre-existing GI conditions. 1656 participants met inclusion criteria, of which 1362 (82%) scheduled at least one telehealth visit and 18% used only app-based resources. The majority (86%) of participants saw GI symptom improvement, with an average reduction of 60% in symptom burden (p<0.001). Participants who used telehealth services and the app had a symptom reduction of 16% greater than that of app-only users (p=0.01). High SVI participants (>0.4, median), indicating greater social vulnerability, had a 22% greater reduction in a GI symptom severity score than app-only high SVI participants (p=0.04). Digital health solutions may be an important resource in advancing equitable access to quality GI care and addressing disparities among populations with high social vulnerability. Virtual telehealth visits with RDNs and HCs appear to be particularly beneficial in improving digestive symptoms in such populations.
Background: Loss of teeth and occlusal imbalance are major dental risk factors for Temporomandibular Disorders. When the teeth are lost, the opposing teeth supra-erupt, and the adjacent teeth shift, l...
Background: Loss of teeth and occlusal imbalance are major dental risk factors for Temporomandibular Disorders. When the teeth are lost, the opposing teeth supra-erupt, and the adjacent teeth shift, leading to biomechanical imbalance in the stomatognathic system. Such an imbalance will stress the TMJ and masticatory muscles, which usually progress to TMD. Prosthetic rehabilitation is essential in the management of TMD in edentulous patients, but no standardized guidelines exist for treatment, and a systematic approach must be taken to address the complex etiology and patient variability. This study was designed to assess the effects of prosthetic rehabilitation on TMD symptoms. Objective: The objectives of the study are 1) to determine the effectiveness of prosthetic rehabilitation in reduction of pain in edentulous patients with temporomandibular disorder and 2) to determine the effect of span of edentulism, number of quadrants involved, pathological migration, the type of Kennedy’s classification, and the prosthetic status on temporomandibular joint (TMJ) dysfunction signs and symptoms. Methods: Patients with TMD were categorized into three intervention groups based on their edentulous status: Group A (Kennedy's Class I and II), Group B (Kennedy's Class III and IV), and Group C (completely edentulous arches). All groups received symptomatic treatment and counseling. Primary outcomes included pain assessment using the Visual Analog Scale (VAS) and electromyographic (EMG) readings. Secondary outcomes measured pain drawing, the Graded Chronic Pain Scale (GCPS), Jaw Functional Limitation Scale (JFLS), Oral Behaviors Checklist (OBC), Patient Health Questionnaire-9 (PHQ-9), PHQ-15, and General Anxiety Disorder–7 (GAD-7). Data analysis was performed using IBM SPSS Statistics (version 28.0). Statistical significance was set at p < 0.05. Results: Significant improvements were observed across groups over 90 days. Pain intensity reduced by 56% in Group A (VAS: 7.08 to 3.30, p < 0.001) and 52% in Group B (VAS: 7.47 to 6.57, p < 0.001). Jaw functionality scores decreased significantly in Group A (1.70 to 1.38, p < 0.001) and Group B (1.68 to 1.56, p < 0.01). Depressive symptoms and anxiety scores also showed notable reductions. EMG activity of the masseter muscle dropped by 33.5% in Group A and 28.2% in Group B (p < 0.001). Conclusions: Prosthetic rehabilitation significantly improved pain intensity, jaw functionality, and muscle activity in TMD patients. The findings underscore the effectiveness of prosthetic protocols in managing TMD across different patient groups. Clinical Trial: http://ctri.nic.in. (Registration no: CTRI/2020/06/026169],http://ctri.nic.in/Clinicaltrials/pdf_generate.php?trialid=42381&EncHid=21929.52001&modid=1&compid=19%27,%2742381det%27
Background: The government of India has launched various digital health interventions (DHIs) at the primary healthcare level to improve health services and health-seeking behaviors. Objective: To asse...
Background: The government of India has launched various digital health interventions (DHIs) at the primary healthcare level to improve health services and health-seeking behaviors. Objective: To assess the implementation status of DHIs and the response of the target-end-users and health care workers (HCWs) in health and wellness centres (HWCs) in Chandigarh, Union Territory India. Methods: A cross-sectional study was conducted in four randomly selected HWCs using a pretested data extraction form and observation checklist during June-September 2022. Respective pretested interview schedules were used to assess the awareness and usability of DHIs among 120 target end users and 120 HCWs. The logic model with a scoring system was used to assess the implementation status of DHIs. Status of DHI implementation estimated as percentage cumulative scores obtained Results: Implementation status of the Electronic Vaccine Intelligence Network (eVIN)and Reproductive and Child Health (RCH) portal was in the range of 70-90%, Health Management Information System (HMIS) portal, HWC portal, Comprehensive Primary Healthcare- Non-Communicable Disease (CPHC NCD) portal, and FP_LIMS in 25-50%, eSanjeevani and IDSP-IHIP portal 51-70%. Community awareness of DHIs ranged from 1% to 22%, except for Aarogya Setu (78.3%) and the COVID-19 Vaccine Intelligence Network (CoWin) app (35.8%). While 66% of HCWs reported working with DHIs easy, 88% acknowledged that dual data entry increased their workload Conclusions: RCH and eVIN portals were effectively implemented, eSanjeevani was fairly implemented, and HMIS, HWC portal, CPHC, and FP_LIMS were weakly implemented. Community awareness of DHIs was low except for the Aarogya Setu and CoWin app. HCWs reported working with DHIs was easy but it had increased their workload.
Background: Artificially Intelligent (AI) Chatbots that deploy natural language processing (NLP) and machine learning (ML) are becoming more common in healthcare to facilitate patient education and ou...
Background: Artificially Intelligent (AI) Chatbots that deploy natural language processing (NLP) and machine learning (ML) are becoming more common in healthcare to facilitate patient education and outreach, but generative chatbots such as Chat GPT face challenges because they can misinform and hallucinate. Healthcare systems are increasingly interested in using these tools for patient education, access to care and self-management, but need reassurances that AI systems can be secure and credible. Objective: To build a secure system that people can use to send messages via SMS with questions about substance use, and where they can screen for substance use disorder. The system will rely on data transfer via third party vendors and will thus require reliable and trustworthy encryption of protected health information (PHI). Methods: We describe the process and specifications for building an AI chatbot that users can access to gain information about and screen for substance use disorder (SUD) from Be Well Texas, a clinical provider affiliated with the University of Texas Health Sciences at San Antonio. Results: The AI chatbot system utilizes NLP and ML to classify expert curated content related to SUD illustrates how we can comply with best practices in HIPAA compliance in data encryption for data transfer and data at rest while still offering a state-of-the-art system that utilizes dynamic user driven conversation to dialogue about SUD, screen for SUD and access SUD treatment services. Conclusions: Recent calls for attention to user friendly design that attend to user rights that honor digital rights and regulations for digital substance use offerings suggests this work is timely and appropriate while still advancing the field of AI. Clinical Trial: Not applicable, this is not a clinical trial.
Background: Due to public health restrictions, the COVID-19 pandemic required significant changes in the delivery of mental health services. The use of virtual care for balancing access with treatmen...
Background: Due to public health restrictions, the COVID-19 pandemic required significant changes in the delivery of mental health services. The use of virtual care for balancing access with treatment needs requires a shared decision between clients, caregivers, and clinicians. One aspect for consideration is the length of treatment and whether it differs by treatment modality. Therefore, it is essential to quantify and compare episodes of care conducted virtually and in-person, while accounting for individual and system level factors that may influence length of episodes. Objective: To operationalise a means of measuring episodes of care using administrative data to improve our understanding of how treatment modality impacts treatment duration for children and adolescents accessing Community Mental Health & Addictions services at IWK Health. Methods: Episodes of care were created using administrative data collected by the IWK Mental Health and Addictions program. A multilevel mixed-effects negative binomial model and time-to-event analysis were used to model the association between treatment modality and treatment duration, both in visits and days, adjusting for client and system characteristics. A zero-inflated negative binomial model was used to analyze the association between treatment modality and the ratio of days to visits within an episode of care. Results: Virtual episodes of care had more visits compared to in-person episodes between April 1, 2020, and March 31, 2021, whereas between April 1, 2022, and March 31, 2023 virtual episodes of care were associated with fewer visits. These patterns were consistent after adjusting for client and system characteristics. Additionally, there was no significant difference in the ratio of days to visits between the virtual and in-person treatment modalities throughout each time period, indicating intersession wait times were not driving any differences in the treatment lengths in days between the modalities. Conclusions: To our knowledge, this is the first study to examine the association between treatment modality and treatment duration. While initially longer than in-person episodes of care, over time the average length of episodes conducted mainly virtually has attenuated, perhaps due to growing comfort with the technology or client factors not adequately captured in administrative data. This information can be valuable to clinicians, clients, and their families regarding expected treatment timelines and aid in informing service planning.
Background: Video-assisted thoracoscopic surgical (VATS) ablation is a minimally invasive and highly effective technique for treating atrial fibrillation (AF). Amiodarone, a class III antiarrhythmic a...
Background: Video-assisted thoracoscopic surgical (VATS) ablation is a minimally invasive and highly effective technique for treating atrial fibrillation (AF). Amiodarone, a class III antiarrhythmic agent, is widely recognized for its efficacy in maintaining sinus rhythm in AF. Objective: This study investigated the effects of perioperative intravenous amiodarone on cardioversion of persistent atrial fibrillation (PersAF) and long-standing persistent atrial fibrillation (LSPAF) 24 hours following VATS ablation. Methods: A total of 176 patients undergoing VATS ablation for PersAF or LSPAF were enrolled and were randomly assigned to the amiodarone group (group A) or the placebo group (group P). Both groups received a bolus dose and a maintenance dose. In group A, the bolus dose was 150 mg of amiodarone which was pumped in 10 minutes, and the maintenance dose was 1 mg/min for 6 hours, followed by 0.5 mg/min for 18 hours. In group P, the same volume of normal saline was administered at the same rate as in group A. The primary outcome was freedom from atrial tachyarrhythmias (FAA) within 24 hours after VATS ablation. Results: According to Kaplan-Meier time-to-event curves, FAA within 24 hours after VATS ablation was higher in group A than in group P (90.7% vs 75.3%, P=.001). FAA was also higher in group A at the end of VATS ablation than in group P (55.8% vs 36.4%, P=.01). MAP and global heart rate were both lower in group A than in group P both intraoperatively and postoperatively (P<.001). In group A, dopamine and norepinephrine consumption was higher than in group P (P<.001). Conclusions: This study shows that intravenous amiodarone given perioperatively could reduce the recurrence of atrial tachyarrhythmias within 24 hours following VATS ablation in patients with PersAF or LSPAF. Clinical Trial: This trial was registered at the China Clinical Trial Registration Center (ChiCTR2000035031); https://www.chictr.org.cn/showprojEN.html?proj=50305
Background: An unhealthy diet is a well-established risk factor for the development of non-communicable diseases (NCD) and office workers are at a higher risk of NCD due to their sedentary work style....
Background: An unhealthy diet is a well-established risk factor for the development of non-communicable diseases (NCD) and office workers are at a higher risk of NCD due to their sedentary work style. Transtheoretical model-based (TTM) and stage-matched interventions effectively influenced dietary behavioural changes. The effectiveness of such interventions in the context of developing countries is yet to be assessed. Objective: To assess the effectiveness of a transtheoretical model-based, stage-matched intervention for healthy dietary intake among sedentary office workers in the Galle district Methods: A cluster randomised trial will be conducted in 20 clusters divided into intervention and control arms. A cluster will be an office with 30 clerical-type workers who are sedentary at work. A stage-matched intervention based on processes of behaviour change will be implemented in intervention clusters for three months. Participants will be provided with an intervention matched with their stage of change at the baseline. Pre-contemplators and contemplators will receive awareness-raising and emotional arousal interventions. Others will receive goal-setting and self-monitoring interventions. Stage of change and dietary intake will be assessed at the baseline and post-intervention through a staging algorithm and 24-hour dietary recall supplemented by a picture guide and computer software. Adherence to intervention will be assessed monthly. We hypothesise that participants will achieve a progressive change in the stage of change and healthy dietary intake in intervention clusters compared to control clusters Results: By December 2024, planned intervention was completed and baseline data was published and data analysis on effectiveness of the intervention is completed and to be published. Conclusions: The current study will assess the effectiveness of a stage-matched intervention based on TTM enriching the current knowledge base with new evidence from sedentary office workers in a developing country. Clinical Trial: The study was registered in the Sri Lankan Clinical Trial Registry (Registration No. SLCTR/2020/025; Date 15th December 2020)
Background: There is an increased focus on involving members of the public in health research. These types of groups such as ‘health consumers’ bring different expertise in informing the design of...
Background: There is an increased focus on involving members of the public in health research. These types of groups such as ‘health consumers’ bring different expertise in informing the design of a research study. There is a growing general concern about older adults’ acceptance and use of technologies. Objective: To explore the perspectives of a health consumer about using social robots with older adults in an Australian context. Based on this information, further explore how Australian older adults will come to accept and use a social robot. Methods: Researchers recruited members of an expert health consumer group, the Age and Ageing Clinical Academic Group (AAA CAG) for interviews regarding social robots and older adults. Semi-structured interviews were conducted via zoom with 5 panel members of the AAA CAG. Results: The health consumer panel provided invaluable insights into their perceptions of social robots and how they could best be propositioned to Australia’s older adults. There was some consensus among panel members on the need for professional input, education and experience building with the technology. Furthermore, overcoming hesitancy barriers could be resolved by building experience with the technology over time as with other forms of assistive technologies. The panel members expressed that aesthetic qualities and a perception of usefulness or benefits needed to be evident to gain the adoption and use of social robots by older adults. Finally, none of the panel members raised concerns about serious resistance or hesitancy they or other older adults would raise in accepting and using a social robot. Conclusions: Having now been pre-tested among an expert healthcare consumer panel by the authors, the findings of this study should provide confidence to the other element of the triple helix model: Industry. However, as mentioned in the limitations of this study, social robot research among older adults in Australia is still emerging. This study represents nascent exploratory research that requires further testing. It is the recommendation of the authors, in conjunction with industry partners that field testing of social robots among older adults is critical to exploring their acceptance and use by this demographic as they will become the end users of the technology Clinical Trial: N/A
Background: Traditional personality assessment tools, such as questionnaires, were prone to social desirability bias and response distortions, leading to inaccurate measurements and misdiagnosis. Thes...
Background: Traditional personality assessment tools, such as questionnaires, were prone to social desirability bias and response distortions, leading to inaccurate measurements and misdiagnosis. These issues undermined the effectiveness of interventions and treatments, necessitating the development of more reliable assessment methods. Objective: This study aimed to develop and validate a gamified assessment tool (ASP-ECD-G) based on Evidence-Centered Design (ECD) to measure antisocial personality traits through participant behavior in a virtual workplace environment. Methods: The ASP-ECD-G was designed using game elements like narrative, immersion, and feedback to assess antisocial traits. It was based on the DSM-5’s alternative model for diagnosing antisocial personality disorder, which includes traits such as Machiavellism, callousness, deceitfulness, hostility, risk-taking, impulsivity, and irresponsibility. The tool’s development was validated through three sub-studies: Study 1 focused on creating the assessment ontology, Study 2 constructed the assessment model, and Study 3 validated the tool’s characteristics using a 2×2 mixed experimental design. Results: The validity tests showed that ASP-ECD-G effectively reflected individual antisocial traits with high robustness in content validity, construct validity, and criterion validity. The tool demonstrated strong resistance to manipulation, preventing participants from altering responses in high-risk scenarios. Conclusions: ASP-ECD-G proved to be a reliable and effective tool for measuring antisocial personality traits in psychological research and organizational contexts, including recruitment and employee management. Its applicability and validity in different cultural contexts and scenarios were also explored.
Background: With an aging population, patients complaining about low urinary tract symptoms (LUTS) increased year by year. For functional evaluation of low urinary tract (LUT), bladder diary (BD) and...
Background: With an aging population, patients complaining about low urinary tract symptoms (LUTS) increased year by year. For functional evaluation of low urinary tract (LUT), bladder diary (BD) and uroflowmetry (UFM) are both common non-invasive examinations for patients with LUTS. Voiding pattern of a patient is currently measured by hospital uroflowmetry and/or home bladder diaries. However, bladder diaries are less objective and often contain missed data, while hospital uroflowmetry lacks repeated measurements and convenience. Thus, it is important to develop a convenient and artificial intelligence(AI) based at-home uroflow monitoring. Objective: This study developed an innovative home vibration-based uroflowmetry for uroflow-curve pattern recognition and voiding parameters measurement and compared it with other home uroflowmetry. Methods: Seventy-six male participants with informed consents received uroflowmetry for voiding symptoms. An accelerometer attached on the urine bucket of the uroflowmeter detects vibration signals generating root mean square (RMS), maximal amplitude (Mmax) and the uroflowmeter measures voiding parameters and creates uroflow curves simultaneously. Vibration signals were processed with an artificial intelligence (AI) model (Convolution Neural Network) to recognize six patterns of uroflow curves to assist diagnosis. Results: Seventy-six participants’ voiding volume ranged from 50 ml to 690 ml (average: 192.50 ±155.58 ml). The correlation analysis revealed positive correlations between voided volume and RMS (R=0.768, p<.001), maximal flow rate (Qmax) and Mmax (R=0.684, p<.001), voiding time and signal time (R=0.838, p<.001), time to Qmax and time to Mmax (R=0.477, p<.001). AI pattern recognition demonstrated high accuracy with all three indicators (precision, recall, and F1 score) surpassing 0.97. Conclusions: Usage of home uroflowmetry increases because of convenience, repeated measurement, and big data application. This vibration-based home uroflowmetry with AI assistance is feasible for at-home voiding parameters measurement and uroflow-curve pattern recognition. Compared with other technologies, vibration-based uroflowmetry demonstrates advantages for intuitive and contact-free usage of home uroflowmetry. Clinical Trial: The research protocol was approved by the institutional review board (IRB: 107-B-10-01).
Background: Medical, mental, and social challenges associated with menopause are significant in the field of women’s health. Exercise therapy can serve as an alternative treatment for alleviating me...
Background: Medical, mental, and social challenges associated with menopause are significant in the field of women’s health. Exercise therapy can serve as an alternative treatment for alleviating menopausal symptoms, and it is crucial to engage in regular physical activity to experience its benefits. Mobile-based exercise applications can help establish exercise habits and provide guidance on workouts. Given that menopause is experienced by all women, mobile health (mHealth) services may have great social value. Furthermore, the various changes that begin after menopause increase the risk of chronic diseases. Thus, prevention and treatment can reduce the demand for medical care and lower overall medical costs. Objective: This study aimed to design and implement a mobile application (app), Rebone, specifically for menopausal women. It also sought to determine the initial feasibility of a combined exercise program, consisting of aerobic exercise and resistance exercise, provided by the app to alleviate menopausal symptoms. Methods: During April 2022, we collected data related to menopausal symptoms, quality of life, depression, insomnia, and stress from 33 individuals with similar characteristics (age, gender, height, weight). Subsequently, we compared the data collected before and after implementing an eight-week, mixed exercise program consisting of aerobic and resistance exercises, provided via a mobile app, conducted at least three times a week. Results: An independent sample t-test was performed after the normality test to compare the differences between the two groups pre- and post-program. After eight weeks, MRS (p = 0.002), MENQOL (p = 0.002), CES-D (p = 0.001), SRI (p = 0.027), and ISI (p = 0.000) all showed statistically significant differences between the two groups. In addition, the treatment group exercised more frequently and performed more appropriate workouts than the control group. Conclusions: Statistically significant differences between the two groups were found for all collected data after the intervention. Furthermore, the frequency of exercise by group and qualitative feedback from participants indicate that mobile-based interventions for menopausal women are effective. Clinical Trial: This study was approved by the Basic Science Research Program through the ICONS (Institute of Convergence Science), Yonsei University Science and Technology, and the National Research Foundation of Korea (NRF).
It was also approved by Yonsei University’s Industry-Academic Cooperation Group's In-School Research Promotion Project (2022YSRESEARCH) and was funded by the Ministry of Education (NRF-2016R1D1A1B02015987).
Lastly, this research was supported by a grant of the Information and Communications Promotion Fund through the National IT Industry Promotion Agency (NIPA), funded by the Ministry of Science and ICT (MSIT), Republic of Korea.
Background: Neurodevelopmental disorders are complex and heterogeneous, impacting efficacy in treatment design. Multiple syndromes are associated with executive function (EF) deficits, however theorie...
Background: Neurodevelopmental disorders are complex and heterogeneous, impacting efficacy in treatment design. Multiple syndromes are associated with executive function (EF) deficits, however theories of attention-deficit hyperactivity disorder (ADHD) centralise outcomes arising from impairments in EF for adult treatment. Transdiagnostic approaches are recommended to gain new insights on mental health challenges. Self-Determination Theory (SDT) is a transdiagnostic approach prioritising satisfaction of basic psychological needs and aims to enhance quality of life, identity formation, motivation, and self-regulation. Objective: This study examines the feasibility and acceptability of a randomised controlled trial to evaluate effectiveness of an SDT-based quality-of-life therapeutic intervention for ADHD adults. Methods: Recruitment aims were 30 adult participants aged 18+ with a confirmed diagnosis of ADHD and access to a computer or smartphone with an internet connection. Participants were recruited from the Adult ADHD Clinic at the South West Yorkshire Partnership NHS Foundation Trust and allocated through four block randomisation by a non-blinded researcher to an 11-session therapeutic coaching intervention (n=11) or control waitlist (n=9) condition. Feasibility was evaluated by pre- and post- measurements of health-related quality-of-life, psychological distress, ADHD symptomology, ADHD-related quality-of-life, self-reflection and insight, autonomous functioning, and per-session measure of participant impairment issues. Participants also responded to a qualitative feedback interview question on intervention value. Results: Of the seven measures, only two—the EQ-5D-5L (a brief measure of well-being) and the Index of Autonomous Functioning—failed to detect significant differences across assessment moments. All other measures related to symptomatology, well-being, impairment, and self-reflection detected significant changes. Most participants also provided positive qualitative feedback regarding the intervention's usefulness. Conclusions: The study suggests that a randomised controlled trial of a Self-Determination Theory-based intervention for adults with ADHD is feasible. Future research should focus on incorporating long-term adherence measures and exploring alternative outcome measures to enhance longitudinal assessment of treatment effects.
Background: Loneliness has sharply increased since the start of the global COVID-19 pandemic, in part, due to disruptions in social relationships and routines, with college students exhibiting the gre...
Background: Loneliness has sharply increased since the start of the global COVID-19 pandemic, in part, due to disruptions in social relationships and routines, with college students exhibiting the greatest increases. Preventions to address loneliness have been developed but have not achieved high rates of success, perhaps because a key factor in addressing loneliness is focusing on the quality of existing relationships as opposed to promoting social interactions during moments of peak loneliness. Objective: Relational savoring, an intervention grounded in principles of attachment theory and positive psychology, was designed to encourage savoring positive experiences and facilitate connectedness with others. The goal of this study was to evaluate the feasibility, acceptability and preliminary outcomes of an mhealth adaptation of relational savoring (mSavorUs)delivered to college students in the service of preventing loneliness. Methods: Using a randomized controlled design, this pilot study evaluated a just-in-time digital health prevention and intervention for loneliness prevention. A smart ring, smart watch, and smartphone application were used for ubiquitous monitoring of loneliness and health (i.e., physiology, sleep, behavior). Within a diverse sample of n=29 college students (43.3% Latinx, 40% Asian American, 16.7% White), we tested two aims. First, we examined the utility, benefits, and problems of each feature of the intervention along with the ubiquitous monitoring systems. Second, we examined whether the prevention resulted in reductions in feelings of loneliness and increased connectedness. Results: Aim One qualitative results indicated that participants found the intervention to be rewarding and helpful, but found the timing of the intervention disruptive. Aim Two quantitative results did not reveal reductions in loneliness or increased connectedness, suggesting modifications are needed. Conclusions: Findings suggest that the content of the prevention program (mSavorUs) may be beneficial but the just-in-time-delivery modality reduce program benefits. Clinical Trial: The study was not preregistered.
Background: Type 2 diabetes mellitus (T2DM) significantly impacts public health, with approximately 21 million US adults diagnosed. Telehealth interventions show promise for improving T2DM outcomes th...
Background: Type 2 diabetes mellitus (T2DM) significantly impacts public health, with approximately 21 million US adults diagnosed. Telehealth interventions show promise for improving T2DM outcomes through digital self-management techniques, but face challenges due to disparities in digital literacy and access, especially in rural areas. There is a need for sustainable T2DM management interventions that require minimal digital literacy and are widely accessible. We propose an innovative, individualized lifestyle modification intervention delivered via standard phone service to control blood glucose levels in individuals with T2DM. Objective: This paper outlines the protocol of a pilot study aiming to assess the feasibility of implementing and preliminary effectiveness of an artificial intelligence-assisted individualized lifestyle modification intervention for glycemic control in rural populations delivered via landline telephone service. Methods: This study employs a multiphase optimization strategy (MOST) and includes two experimental intervention components: automated vs. human health coaching and adapted vs. fixed gamified reward levels based on daily automated monitoring calls. We aim to recruit 88 patients with diabetes and HbA1C levels 6.5–11.5%. Participants receive daily behavioral monitoring phone calls to evaluate self-management behaviors. Participants also receive either weekly human health coaching or automated AI-driven health coaching for six months. In the fixed-reward arm, participants earn 60 cents per day for answering daily calls, while in the adapted gamified reward arm, rewards start at 20 cents per day and increase weekly, with penalties for missed days. Both arms can earn up to $100.80 over six months. Semi-structured exit interviews will gather patient insights post-trial. Primary outcomes include feasibility measures, HbA1c levels, and lipid profiles. Results: We have screened 813 people with diabetes and enrolled 54 participants since the launch of the study. We project that enrollment and analyses to assess feasibility completed in 2025. Conclusions: This intervention lays the groundwork for a future optimization trial addressing T2DM management, reaching populations through digital health while requiring minimal digital skills. It has the potential to be a scalable low-cost AI-assisted diabetes management solution that is accessible to rural communities and those with low digital literacy or smartphone access. Clinical Trial: ClinicalTrials.gov Identifier: NCT05344859
Background: Research efforts focusing on long covid have so far produced insights into the dysregulation of body processes. Development of therapeutics has been limited to a few options which have lar...
Background: Research efforts focusing on long covid have so far produced insights into the dysregulation of body processes. Development of therapeutics has been limited to a few options which have largely panned out. However, the research work has found some useful relationships between different diseases, and one important finding which lends itself to subsequent therapeutic work are the metabolic discoveries in long covid patients. Objective: This study aims to determine effective treatment options for patients presenting with post vaccination syndrome, and aims to find which biomarkers are most predictive of disease severity. Methods: Patients presenting with post vaccination syndrome will be tested at baseline for their general health (PAC-19QoL inventory, 6 Minute Walk Test and Heart Rate Variability), prevalence of spike protein, inflammatory markers (High sensitivity C-reactive protein, Tumour necrosis factor alpha, IL-6, and Antinuclear Antibody), as well as markers of coagulation (Von Willebrand Factor and D-Dimer), metabolic markers (Acylcarnitine profile, free fatty acids, Hemoglobin A1c, β-Hydroxybutyrate, uric acid, amino acid panel, fatty acid oxidation percentage, and post-exercise lactate). Patients will also be asked to get a commercial whole genome sequence to identify risk loci for vaccine injury or any interactions with the treatment protocols.
Patients will take a combined nutraceutical supplement daily for three months. Biomarker measurements will be taken interim and after three months to assess non-inferiority to a control group. Results: This is a trial protocol, so results will be analyzed to see if there is a difference between baseline parameters and follow up measurements performed 1.5 months into the trial, as well as after 3 months of following the combined nutraceutical protocol. Conclusions: The treatment of a novel disease entity ‘long vax’, which shares similar etiology and features with long Covid, which are in the class of spike protein related diseases (SPRD), is a high priority which addresses an underserved patient population. While different therapeutics have been suggested with different levels of evidence, from mechanistic hypothesis, to in vitro data, to clinical trials for related conditions (acute Covid-19 infection), very few trials exist for long vax. Our study aims to evaluate the treatment effectiveness of a combined nutraceutical protocol for the treatment of long covid and long vax. Clinical Trial: The trial will be registered on clinicaltrials.gov.
Background: Palliative and End-of-Life Care (PEoLC) systems are expanding in a multitude of dimensions and becoming increasingly complex. Understanding these systems is crucial for improving patient o...
Background: Palliative and End-of-Life Care (PEoLC) systems are expanding in a multitude of dimensions and becoming increasingly complex. Understanding these systems is crucial for improving patient outcomes and service delivery in the face of changing demographics and shifting demands and resources. Hospice care is key to the future of PEoLC as hospices currently represent multifaceted service provision and engage with diverse stakeholders of PEoLC. This study aimed to understand the hospice care system using participatory system mapping with representative stakeholders of the system. Objective: 1- To capture the system variables and their causal interrelationships in a hospice in Northwest England as defined by stakeholders through participatory design workshops.
2- To identify leverage points within the system map of hospice care from the perspective of a hospice in Northwest England.
3- To explore the suitability of participatory system mapping with stakeholders as a method for capturing complex system dynamics in hospice care setting. Methods: Aimed at engaging stakeholders of a North West UK hospice in a participatory system mapping method, an innovative hybrid, asynchronous multi-modal design workshop series was iteratively developed. Causal Loop Diagrams (CLDs) generated by stakeholders were used to create a composite representative participatory map of the hospice care system. 27 participants representing various hospice stakeholder groups spanning patients, healthcare professionals, volunteers, management, maintenance and chaplaincy, participated in the workshops. The resulting system map was analysed using quantitative Network Analysis and qualitative interpretation. Results: The participatory hospice system map contained 84 variables with 175 connections. Network Analysis revealed key variables such as Patient Experience (highest in-degree, 20), Advanced Care Planning (highest out-degree, 8), Fundraising (highest betweenness centrality, 0.19), and Relationships with Community Organisations and External Stakeholders (highest closeness centrality, 0.23). Qualitative analysis identified important system dynamics including the impact of hospital admissions and hospice stereotypes, and the unknown influencers of advanced care planning. Conclusions: This study contributes to participatory system mapping in healthcare, offering both empirical insights and methodological implications for engaging with and improving complex PEoLC systems through diverse stakeholder inclusion, and integration of quantitative and qualitative analyses. The study demonstrates the potential of participatory system mapping with hospice stakeholders as an accessible and informative method for discovering complex dynamics in hospice care systems. The study introduces an iteratively refined asynchronous, multi-modal hybrid design workshop approach with an emphasis on enhanced access, flexible engagement, and diverse interaction.
Empirically, this study identifies both structural and conceptual leverage points for hospice system through participatory stakeholder-created causal loop diagram, which could have a wide impact on developing services. The study also reveals gaps in understanding from a systemic perspective and from implicit understanding of a topic by participants, such as advanced care planning and hospital admissions. These insights present actionable areas for policy and practice improvements, demonstrating the method's capacity to inform high-level system changes while remaining grounded in stakeholder realities. Future research should explore the replicability of this approach across diverse healthcare settings and its potential for creating stakeholder-informed system improvements in broader PEoLC contexts.
Background: Latino caregivers spend nearly double their annual household income on caregiving expenses compared to non-Latino caregivers. CONFIDENCE is an asynchronous, web-based, culturally-tailored...
Background: Latino caregivers spend nearly double their annual household income on caregiving expenses compared to non-Latino caregivers. CONFIDENCE is an asynchronous, web-based, culturally-tailored intervention to reduce financial stress among Latino caregivers. Objective: This study examines the program’s acceptability and perceived value to end-users. Methods: We analyzed 14 semi-structured interviews and 27 satisfaction survey responses to evaluate acceptability. Themes included 1) perceived need for financial intervention, 2) perceived intervention effectiveness, 3) positive responses to participation, and 4) recommendations for intervention improvement. Results: Caregivers appreciated the group setting, which allowed for mutual interaction and learning. Participants also praised the content’s trustworthiness and relevance. Although most agreed participation required minimal effort, some noted logistical challenges to participation, like time constraints. Findings will inform CONFIDENCE’s refinements, including limiting burden while maintaining strengths such as group learning opportunities. Conclusions: Considering the economic burdens Latino caregivers face, it is vital to develop and support interventions tailored to their unique needs.
Background: More than a few concepts have been presented in rehabilitation clinics that implement aspects of modern information technology in the arrangement of augmented reality or virtual rehabilita...
Background: More than a few concepts have been presented in rehabilitation clinics that implement aspects of modern information technology in the arrangement of augmented reality or virtual rehabilitation aiming to enhance cognitive or motor learning and rehabilitation motivation. Despite their scientific success, it is currently unknown whether rehabilitants will accept rehabilitation concepts that integrate modern information technologies. Objective: ... Methods: 111 rehabilitation patients were surveyed about the subjective performance expectations of virtual reality in 15 therapeutic fields with a questionnaire. The distribution of the responses was evaluated using box plots. The relationship between the subjective performance expectations for the 15 therapeutic fields was analyzed with Spearman’s rho, while the Mann-Whitney U test was used for comparisons of the subjective performance expectations between age-groups and between genders. Results: For all 15 therapeutic fields the median of the subjective performance expectations was between 2 and 3, while therapeutic fields in the categories “activity / movement”, “competence of daily live / communication” and “education” tended to be rated higher than therapeutic fields in the categories “relaxation / passive measures” and “advisory / conversation”. Significant rank correlation could be observed for 103 out of 105 pairwise comparisons of the therapeutic fields, with distinct patterns of effects sizes within the chosen categories. There was no statistically significant difference in the evaluation between rehabilitants of employable age and those of age 68 years or older. Male rehabil-itation patients reported greater subjective expectations for virtual rehabilitation than female patients, but there was only a significant difference with small effect sizes for 3 of the 15 therapeutic fields. Conclusions: The general trend is that patients can imagine taking part in virtual reality in rehabilitation activities involving active movement (physiotherapy, sports and exercise therapy, occupational therapy) and also in health education. The results of the survey show that there is also a high level of support for the therapeutic field advisory/conversation.
Current circumstances have led to a substantial use of virtual offerings in practice. The limited data available may have encouraged the professional development of virtual reality systems and their widespread use in medical rehabilitation follow-up in the home setting.
Background: A traumatic childbirth experience, sometimes referred to as 'birth trauma,' is a woman's experience of interactions and/or events directly related to childbirth that caused overwhelming di...
Background: A traumatic childbirth experience, sometimes referred to as 'birth trauma,' is a woman's experience of interactions and/or events directly related to childbirth that caused overwhelming distressing emotions and reactions, leading to short- and/or long-term negative impacts on a woman's health and wellbeing. Traumatic childbirth experiences can lead to poor mental health outcomes in postpartum women, severely impacting mother-infant attachment, child development, and the overall mental health of the family unit. Currently, there are no early intervention programmes designed specifically for postpartum mothers who experience birth trauma to decrease the likelihood of postpartum depression, anxiety and/or post-traumatic stress disorder (PTSD). This project will assess the feasibility and acceptability of a telehealth delivered and early-intervention for this group. Objective: To assess the acceptability and feasibility of a telehealth, narrative-informed group-based early intervention programme for postpartum women in reducing the mental health impacts of having experienced a traumatic childbirth. Methods: The intervention is a narrative-informed, group-based therapy delivered via telehealth to postpartum women who self-report having experienced a traumatic childbirth experience in the past six months. Eligible participants were recruited from a specific catchment area (Hunter New England Local Health District) within New South Wales, Australia. The study aimed to recruit a maximum of 16 postpartum women who were randomly assigned to either the intervention group or a waitlist control group. The intervention consists of six weekly sessions, delivered in group format, each lasting 60 to 120 minutes. Results: The study is currently ongoing, but the results will indicate if this early intervention programme is acceptable and feasible, and if it decreases postpartum mental health symptoms of depression, anxiety and posttraumatic stress disorder. Conclusions: This study is expected to improve understanding of how to support postpartum women who have experienced birth trauma and potentially reduce the burden on mental health services in regional (i.e., semi-rural) and rural Australia. Clinical Trial: This project was registered prospectively with the Australian New Zealand Clinical Trials Registry (ANZCTR12624000460505p) on 26 March 2024, with a Universal Trial Number of U1111-1305-9340, and has received ethics approval from the University of New England’s Human Research Ethics Committee (Approval Number HE24-054, valid till 1 June 2025).
Background: Children and adolescents with attention deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) often face structural and psychological barriers in accessing medical care,...
Background: Children and adolescents with attention deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) often face structural and psychological barriers in accessing medical care, including economic costs, long wait times, and stress of attending new medical environments. The coronavirus (COVID-19) pandemic accelerated the adoption of telehealth services to overcome these challenges. However, few studies have assessed the satisfaction levels of children and adolescents diagnosed with neurodevelopmental disorders and their caregivers when they use telehealth, particularly in Japan. This study aimed to evaluate satisfaction by conducting telehealth assessments in children and adolescents diagnosed with ADHD or ASD and their caregivers and identify factors associated with higher satisfaction levels. Objective: This study aimed to evaluate satisfaction by conducting telehealth assessments in children and adolescents diagnosed with ADHD or ASD and their caregivers and identify factors associated with higher satisfaction levels. Methods: A total of 68 patients aged 6–17 years with a confirmed diagnosis of ADHD or ASD and their caregivers participated in this study. The participants were recruited from Keio University Hospital and four collaborating institutions in Japan. Each patient and their caregiver underwent two assessment sessions, one face-to-face and the other via telehealth (a remote video tool), in a randomized order. Upon completing both assessments, the participants completed a satisfaction questionnaire using a five-point Likert scale that covered aspects such as audio and video quality, seamless communication, perceived warmth, reduced burden, and the ability to behave naturally. Spearman's rank correlation coefficients and multiple regression analyses were performed to identify factors associated with overall satisfaction. Results: Among the patients, 70.2 % reported being "satisfied" or "very satisfied" with the telehealth assessment, and 88.3 % of caregivers reported similar satisfaction levels. Multiple regression analysis showed that in patients, high satisfaction was associated with seamless viewing of the screen, reduced burden of hospital visits, and ability to speak naturally during the assessment. For caregivers, visual clarity and the child's natural behavior were crucial factors. Conclusions: Telehealth assessments are an effective and practical option to provide care for children and adolescents diagnosed with ADHD or ASD and their caregivers, offering high levels of satisfaction. Technical reliability and reduced travel burden significantly contributed to positive experiences. However, ensuring that children and adolescents behave naturally and feel a sense of warmth during remote consultations is crucial to maximize their satisfaction. Telehealth services can enhance the quality of health care, making them valuable supplementary tools for clinical practice. Clinical Trial: The study protocol was registered with the UMIN Clinical Trials Registry (UMIN000039860).
Background: The integration of multimodal capabilities in GPT-4V represents advancement in AI's application to clinical fields, particularly neuroradiology. Despite preliminary evidence of capability...
Background: The integration of multimodal capabilities in GPT-4V represents advancement in AI's application to clinical fields, particularly neuroradiology. Despite preliminary evidence of capability in medical imaging interpretation, questions remain about its performance in complex scenarios requiring integrated analysis of clinical history and imaging findings. Objective: To evaluate GPT-4V's diagnostic performance on neuroradiology board-style multiple-choice questions, integrating both clinical data and medical imaging. Methods: Twenty-nine neuroradiology cases from the RSNA Case Collection, each including clinical vignette and CT/MRI images, were presented to GPT-4V. The model evaluated both imaging studies and clinical data, selecting from multiple-choice options while quantifying the relative influence of image versus text data on decision-making. Results: GPT-4V achieved 75.86% diagnostic accuracy, with image data contributing an average of 66.9% to final answers. The model relied more heavily on imaging in incorrectly answered cases (75% image-based) compared to correct ones (61.74%). Conclusions: The findings suggest potential over-reliance on imaging data in complex cases where clinical context is crucial. Our results highlight the need for improved integration of text and image data in AI models, with future development focusing on refining multimodal decision-making processes to enhance clinical accuracy.
Pesticide contamination of agricultural soils poses significant environmental and public health challenges, necessitating eco-friendly soil restoration approaches. Indigenous soil bacteria offer a pro...
Pesticide contamination of agricultural soils poses significant environmental and public health challenges, necessitating eco-friendly soil restoration approaches. Indigenous soil bacteria offer a promising solution for detoxifying pesticide residues and enhancing soil health. This study aimed to: (1) identify bacterial strains in pesticide-contaminated soils with bioremediation potential, (2) evaluate the degradation efficiency of these strains, (3) analyze the influence of soil physicochemical properties on pesticide degradation, and (4) contribute empirical data for sustainable agricultural practices aligned with SDGs. Soil samples were collected from four pesticide-contaminated sites in Otuoke, Nigeria, and analyzed for microbial counts, pesticide residues, and physicochemical parameters. Bacterial isolates were identified using 16S rRNA sequencing, and biodegradation assays were monitored via optical density changes over seven days. Results showed a 60–80% reduction in pesticide residues, particularly when microbial consortia were applied. Actinomycetes exhibited the highest colony counts (9.20 × 10⁷ CFU/g), and Enterobacter hormaechei was notable for possessing the laccase functional gene linked to pesticide degradation. Soil analysis revealed significant disruptions in organic matter, pH, and nitrate levels due to pesticide contamination. These findings underscore the efficacy of microbial consortia in bioremediation and recommend field-scale applications to restore contaminated soils.
Background: Sexual and gender minority (SGM) individuals are at heightened risk for substance use and sexually transmitted infections than their non-SGM peers. Collecting mobile phone usage data pass...
Background: Sexual and gender minority (SGM) individuals are at heightened risk for substance use and sexually transmitted infections than their non-SGM peers. Collecting mobile phone usage data passively may open new opportunities for personalizing interventions, as behavioral risks could be identified without user input. Objective: Our objective was to determine whether passively sensed mobile phone data can be used to identify substance use and sexual risk behaviors for STI and HIV transmission among young SGM who have sex with men. Methods: We developed a mobile phone app to collect participants’ messaging, location, and app use data. Based on community-engaged qualitative research, we trained a machine learning model to identify risk behaviors for STI and HIV transmission, such as condomless anal sex, number of sexual partners, and methamphetamine use. We validated these behaviors using self-report and evaluated their association with mobile phone use data. Results: We recruited 82 SGM young people who have sex to use our data collection app, and among those users, our model was highly predictive of methamphetamine use and having 6+ sexual partners (F1 scores 0.83 and 0.69 respectively). The model was less predictive of condomless anal sex (F1 score 0.38). Overall, text-based features were found to be most predictive, but app use and location data improved the results, particularly for detecting 6+ sexual partners. Conclusions: Our results show that passively collected mobile phone data may be useful in detecting sexual risk behaviors. Expanding data collection may improve the results further, as certain behaviors, such as injection drug use, were quite rare in the study sample. These models may be used to personalize STI and HIV prevention as well as substance use harm reduction interventions.
Background: Large Language Models (LLMs) offer the potential to improve virtual patient-physician communication and reduce healthcare professionals' workload. However, limitations in accuracy, outdate...
Background: Large Language Models (LLMs) offer the potential to improve virtual patient-physician communication and reduce healthcare professionals' workload. However, limitations in accuracy, outdated knowledge, and safety issues restrict their effective use in real clinical settings. Addressing these challenges is crucial for making LLMs a reliable healthcare tool. Objective: This study aims to evaluate the efficacy of Med-RISE, an information retrieval and augmentation tool, in comparison with baseline Large Language Models, focusing on enhancing accuracy and safety in medical question answering across diverse clinical domains. Methods: This comparative study introduces Med-RISE, an enhanced version of the Retrieval-Augmented Generation (RAG) framework, specifically designed to improve question-answering performance across wide-ranging medical domains and diverse disciplines. Med-RISE consists of four key steps: Query rewriting, Information retrieval (providing local and real-time retrieval), Summarization, and Execution (a fact and safety filter before output). The study integrated Med-RISE with four LLMs (GPT-3.5, GPT-4, Vicuna-13B, and ChatGLM-6B) and assessed their performance on four multiple-choice medical question datasets: MedQA (USMLE), PubMedQA (original and revised versions), MedMCQA, and EYE500. Primary outcome measures included answer accuracy and hallucination rates, with hallucinations categorized as factuality (inaccurate information) or faithfulness (inconsistency with instructions) types. The study was performed between March and August 2024. Results: The integration of Med-RISE with each LLM led to a substantial increase in accuracy, with an average improvement of 13.0% across four datasets: MedQA (USMLE), PubMedQA (Revised version), MedMCQA, and EYE500. The enhanced accuracy rates were 16.3% for GPT-3.5, 12.9% for GPT-4, 13.0% for Vicuna-13B, and 9.9% for ChatGLM-6B. Additionally, Med-RISE effectively reduced hallucinations by 15.0%, with factuality hallucinations decreasing by 13.5% and faithfulness hallucinations by 5.8%. The average hallucination rate reductions were 17.6% for GPT-3.5, 12.8% for GPT-4, 18.0% for Vicuna-13B, and 11.8% for ChatGLM-6B. Conclusions: The Med-RISE framework significantly improves accuracy and reduces hallucinations of LLMs in medical question answering across benchmark datasets. By providing local and real-time information retrieval, fact and safety filtering, Med-RISE enhances the reliability and interpretability of LLMs in the medical domain, offering a promising tool for clinical practice and decision support.
Background: Streptococcus mutans (S. mutans) is the primary pathogenic bacterium causing dental caries, and the protein antigen (SpaP) of its P region and the glucan-binding protein (Gbp) with glucan-...
Background: Streptococcus mutans (S. mutans) is the primary pathogenic bacterium causing dental caries, and the protein antigen (SpaP) of its P region and the glucan-binding protein (Gbp) with glucan-binding domain (GBD) exhibit promising immunogenicity. They have been separately utilized in the development of anti-caries vaccines, but their effectiveness needs enhancement. Objective: To construct a novel anti-caries vaccine using a temperature-sensitive sustained-release hydrogel as a carrier and evaluate its immune response in vitro and in vivo, aiming to improve the immune response and address issues such as antigen degradation in the acidic gastrointestinal environment, mucosal barriers, inefficient cellular absorption by immune cells, and rapid enzymatic degradation of vaccines. Methods: The antigen of the P region of the recombinant protein SpaP from S. mutans and the glucan-binding domain (GBD) of GbpA were connected. The anti-caries vaccine pVAX1 - SPG was prepared with the sustained-release temperature-sensitive hydrogel PLGA - PEG - PLGA as a carrier. Firstly, the sustained-release effect of the anti-caries vaccine was observed in vitro. Subsequently, rabbits were immunized orally and by injection to evaluate the vaccine's immune response and conduct general safety testing. Results: pVAX1 - SPG improved vaccine release in vitro and maintained efficacy for a longer time. In rabbits, it induced an increase in SpaP-specific serum IgG and saliva IgA antibodies. Moreover, orally administered pVAX1 - SPG induced stronger SpaP-specific serum IgG and saliva IgA antibodies than the injection route. No abnormalities were detected in various safety indicators. Conclusions: The temperature-sensitive sustained-release hydrogel-encapsulated pVAX1 - SPG anti-caries gene vaccine can elicit a significantly effective and long-term immune response. The oral route is more readily accepted and safer, and has great potential in the prevention and treatment of dental caries.
Background: People from ethnic minority backgrounds have a 2.5 times higher incidence of type 2 diabetes than ethnic Danes. They often face negative experiences with healthcare professionals, leading...
Background: People from ethnic minority backgrounds have a 2.5 times higher incidence of type 2 diabetes than ethnic Danes. They often face negative experiences with healthcare professionals, leading to mistrust and unequal treatment due to diverse health perceptions. A person-centred, culturally adapted approach focusing on knowledge, motivation, culture, beliefs, and socioeconomic support can improve self-care, diabetes management, and treatment adherence among persons from ethnic minority backgrounds. Objective: This mixed-methods realist evaluation protocol aims to understand how a person-centred and culturally sensitive course of treatment in individuals with type 2 diabetes and non-Western Backgrounds (The ACCT2 study) works. Methods: This study, embedded within a randomised controlled trial, the ACCT2 study, utilises a realist evaluation to assess what works, for whom it is most effective, and under what circumstances it is likely to be effective, alongside the causal effectiveness examined in the RCT. Our realist evaluation follows three phases: 1) Developing, 2) Testing, and 3) Refining initial program theories. Data will be collected through semi-structured interviews and survey data. A thematic analysis guided by a predefined codebook based on our initial program theories will be conducted. Results: As of December 2024, 13 participants have been enrolled, with 13 V4 interviews completed. Data analysis is pending. The results will inform revisions to the initial program theories, refining a comprehensive model that accurately captures the interactions between context, mechanisms, and outcomes in the ACCT2 study. We anticipate disseminating the findings in the first half of 2026. Conclusions: This RE is expected to support the RCT by offering insights applicable to real-life clinical settings. The anticipated impact includes aiding the future development and implementation of interventions for persons with ethnic minority backgrounds and T2D. Clinical Trial: This study is registered as a component of the ACCT2 study (ID: NCT06147245)
Background: Identifying and delivering interventions to patients with prediabetes was one strategy for dealing with the rising prevalence of T2DM. Risk assessment tools help in disease detection by al...
Background: Identifying and delivering interventions to patients with prediabetes was one strategy for dealing with the rising prevalence of T2DM. Risk assessment tools help in disease detection by allowing screening of the high risk group. Machine learning was also used to support in the detection and diagnosis of prediabetes. Objective: The purpose of this review is to assess the diagnostic test accuracy of various machine learning algorithms for calculating prediabetes risk. Methods: This protocol was written in accordance with the Preferred Reporting Items for Systematic Review and Meta-Analysis of Protocols (PRISMA-P) statement. The databases that will be used include PubMed, ProQuest, and EBSCO, with access limited to January 1999 and September 2022 in English only. Two reviewers will identify articles independently by reading the titles, abstracts, and full-text articles. Any disagreement will be resolved through consensus. To assess the quality and potential for bias, the Quality Assessment of Diagnostic Accuracy Studies (QUADAS) tool will be used. Data extraction and content analysis will be carried out in a systematic manner. A forest plot with 95% confidence intervals will be used to visualize quantitative data. The summary receiver operating characteristic curve will describe the diagnostic test outcome. The Review Manager 5.3 (Rev Man 5.3) software package will be used to analyze the data. Results: Using the proposed systematic review and meta-analysis, we will determine the diagnostic accuracy of various machine learning algorithms for estimating prediabetes risk. Conclusions: Machine learning classification is a form of artificial intelligence (AI) that allows computers to learn without being specifically programmed. It has been used to develop a scoring method for prediabetes identification and diagnosis. As far as we know, there is no systematic review and meta-analysis regarding machine learning utilization for prediabetes risk estimation. Therefore, we proposed this study to obtain the diagnostic accuracy of machine learning algorithms in estimating prediabetes risk. Clinical Trial: This protocol has been registered in the Prospective Registry of Systematic Review (PROSPERO) database. The registration number is CRD42021251242.
Background: The early detection of pre-symptomatic individuals and the proactive implementation of health guidance through regular primary care visits are essential strategies for the secondary and te...
Background: The early detection of pre-symptomatic individuals and the proactive implementation of health guidance through regular primary care visits are essential strategies for the secondary and tertiary prevention of diabetic complications. An interdisciplinary team approach significantly enhances the care of patients with diabetes, integrating the expertise of physicians, dietitians, clinical navigators, pharmacists, and mental health professionals. Central to this collaborative model is the active participation of patients, who play a vital role in managing their health outcomes. This integrated approach facilitates comprehensive care, promoting better health management and improved quality of life for individuals with diabetes. Objective: We aimed to evaluate the association among regular primary care visits, hemoglobin A1C (HbA1C) and low-density lipoprotein (LDL) levels in patients with type 2 diabetes mellitus. Methods: We randomly sampled data from 200 patients’ electronic medical records. Mann–Whitney and chi-square tests were used to investigate the association between glycemic control lipid profile and the number of patient visits. Results: The mean age of the participants was 61.78 years and the average body mass index was 34.5 kg/m2. Females constituted 61.79% of participants. The predominant race seen at the clinic was Black (43.8%), followed by White (42.69%). Patient adherence to scheduled visits was not statistically significantly associated with either HbA1C or LDL (chi-square = 1.1, p-value = 0.29 for HbA1c and chi-square = 1.12, p-value = 0.99 for LDL). Conclusions: In the sample studied, no statistically significant association existed between adherence to primary care visits and either HbA1C or LDL levels. This data can guide physicians to invest on favoring high-quality primary care contact rather than high frequency of visits. Clinical Trial: IRB approved
Background: Artificial intelligence (AI) is an emerging field that has had a profound impact on medical education. Its growing implementation offers personalized learning environments, promising impro...
Background: Artificial intelligence (AI) is an emerging field that has had a profound impact on medical education. Its growing implementation offers personalized learning environments, promising improvements in the academic performance of medical students. Objective: This study aims to explore how AI tools influence the academic performance of medical students by identifying key applications, benefits and challenges and providing an integrative perspective on their role in medical education. Methods: A scoping review was conducted based on empirical studies, systematic reviews and case studies published between 2014 and 2024. Studies were identified through PubMed, Scopus, and Web of Science, using search strategies developed with AI assistance. Eligible studies involved medical students or trainees and evaluated the impact of AI on academic performance, simulations, and clinical skills development. Results: Initially 173 studies were identified, of which 108 met the inclusion criteria after screening. The final analysis included eight studies. Key findings showed that AI-enhanced teaching methods significantly improved academic performance compared to traditional approaches. In addition, AI-based simulations and personalized learning platforms contributed to improved practical skills and knowledge retention. Conclusions: AI has demonstrated considerable potential to enhance medical education by improving academic performance and practical skills. However, challenges remain, including the need for formal AI education in medical curricula and careful evaluation of the effectiveness of AI tools. Further research is needed to explore the role of AI in specific areas of medical education and ensure its appropriate integration orinto educational systems.
Background: Video games, especially action games, has become increasingly prevalent among adolescents, with studies indicating potential cognitive benefits, particularly on attention and working memor...
Background: Video games, especially action games, has become increasingly prevalent among adolescents, with studies indicating potential cognitive benefits, particularly on attention and working memory. However, the effects of video gaming on underprivileged teenagers remain underexplored, despite the unique cognitive challenges they face due to their level of exposure, level of cognitive abilities, and socioeconomic factors. Objective: The present study aimed to evaluate the effects of action video games on attention span and visual working memory retention among underprivileged adolescents. By comparing cognitive performance between those exposed to action games and those in a control group, as well as a sub-group analysis into the difference between older (16-18) and younger groups (13-15), we sought to determine if gaming could enhance cognitive functions in this population, and whether age has any significant factor to play in memory and attention scores. Methods: A sample of 100 adolescents aged 13-18 from the Panaah Communities Center in Maharashtra, India, was divided into control (n=50) and experimental (n=50) groups. The experimental group engaged in a 20-minute action game before completing two assessments: the Continuous Performance Test (CPT) to measure attention and the Visual Pattern Test (VPT) for visual working memory. Each day, the experimental and control groups sat for different tests to ensure reliable results. Statistical analyses were conducted to compare group performances and assess age-related differences. T-test Assuming Unequal Variance and the Mann-Whitney U Test were utilized to measure statistical significance. Cohen's d was applied to all variables to ensure real-life applicability through effect size. Results: The experimental group scored higher than the control group in both attention (CPT: M = 79.028, SD = 32.0; p = 0.034) and working memory (VPT: M = 77.019, SD = 51.5; p = 0.026), suggesting that video game exposure had a positive effect on cognitive functioning. Further analysis revealed minimal age-related differences in cognitive outcomes. High variability in responses, especially among those in the experimental group, highlighted the influence of individual baseline characteristics inherently present in the population. Conclusions: The findings indicate that action video games can enhance attention and visual working memory in underprivileged adolescents, though individual differences must be considered. These results emphasize the potential for video games as supplementary cognitive training tools in the classroom, especially for those who have cognitive deficits or trouble learning in normal, peer-group settings.
Background: With the increasing reliance on online platforms for health information, understanding user satisfaction, perceived benefits, and associated risks is critical for promoting informed health...
Background: With the increasing reliance on online platforms for health information, understanding user satisfaction, perceived benefits, and associated risks is critical for promoting informed health-seeking behaviors. This study seeks to address the gap in knowledge regarding users' perceptions of online health information and the factors influencing their trust in these sources. Objective: This study aims to evaluate users' satisfaction with online health information sources, identify the perceived benefits and risks associated with seeking health information online, and investigate the factors influencing trust in these information sources. Additionally, the study will explore how these perceptions impact users' health-seeking behaviors. Methods: A cross-sectional survey was conducted with a sample of 376 respondents, using structured questionnaires to collect data on satisfaction levels, types of health information sought, perceived benefits and risks, and trust in online health information sources. Descriptive statistics and chi-square analyses were utilized to analyze the data Results: The findings indicate that a significant proportion of respondents reported high levels of satisfaction with online health information sources, with 52.1% somewhat agreeing and 18.6% agreeing with their overall satisfaction. The most sought types of information included specific medical conditions (27.4%) and symptoms (36.7%). Benefits of online health information were primarily identified as convenience and accessibility, while risks included misinformation and lack of accountability. Trust in information sources was found to be significantly correlated with perceived reliability and the anonymity of the information source. Conclusions: Overall, users express satisfaction with online health information sources, recognizing both benefits and risks associated with their use. Trust emerges as a critical factor influencing satisfaction and health behaviors. It is recommended that health information providers improve the reliability and accountability of online health information to enhance user trust and satisfaction. Public health initiatives should also aim to educate users on evaluating online health information critically. This study underscores the importance of understanding users' perceptions of online health information, which can inform strategies to enhance the quality and effectiveness of digital health communication.
Background: The increasing reliance on the internet for health information necessitates understanding various factors influencing health information-seeking behaviors and satisfaction levels among use...
Background: The increasing reliance on the internet for health information necessitates understanding various factors influencing health information-seeking behaviors and satisfaction levels among users. These insights can inform strategies to improve the quality and accessibility of health information. Objective: This study aimed to investigate the socio-demographic factors affecting internet health information-seeking behaviors, the types of health information sought, the timeliness and trust associated with information sources, and user satisfaction regarding online health information. Methods: A quantitative cross-sectional survey was conducted among 376 participants, utilizing structured questionnaires to collect data on various aspects of health information-seeking behavior. Statistical analyses, including Chi-square tests and frequency distributions, were performed to evaluate the relationships between socio-demographic factors and health information-seeking behaviors. Results: The findings revealed significant associations between the duration of teaching, health insurance status, estimated income, and the duration of employment with health information-seeking behaviors (p < 0.05). The most sought-after health information types included specific medical conditions and treatment methods. Satisfaction levels varied across categories, with a majority of respondents expressing positive sentiments toward online searches, website information sources, and the usefulness of the information received. Conclusions: The study underscores the importance of socio-demographic factors in shaping health information-seeking behaviors and highlights the need for improved credibility and trust in online health information sources. Stakeholders in health communication should prioritize the development of reliable online health information platforms and enhance user education on navigating these resources effectively. This study contributes valuable insights into the dynamics of health information-seeking behaviors, emphasizing the critical role of socio-demographic factors and the need for high-quality, trustworthy health information in promoting informed health decisions.
Background: Abstract (237 words)
The American Civil War has been commemorated with a great variety of monuments,
memorials, and markers. These monuments were erected for a variety of reasons, begi...
Background: Abstract (237 words)
The American Civil War has been commemorated with a great variety of monuments,
memorials, and markers. These monuments were erected for a variety of reasons, beginning with
memorialization of the fallen and later to honor aging veterans, commemoration of significant
anniversaries associated with the conflict, memorialization sites of conflict, and celebration of
the actions of military leaders. Sources reveal that during both the Jim Crow and Civil Rights
eras, many were erected as part of an organized propaganda campaign to terrorize African
American communities and distort the past by promoting a ‘Lost Cause’ narrative. Through
subsequent decades, to this day, complex and emotional narratives have surrounded interpretive
legacies of the Civil War. Instruments of commemoration, through both physical and digital intervention approaches, can be provocative and instructive, as the country deals with a slavery legacy and the commemorated objects and spaces surrounding Confederate inheritances.
Today, all of these potential factors and outcomes, with internationally relevance, are surrounded by swirls of social and political contention and controversy, including the remembering/forgetting dichotomies of cultural heritage. The modern dilemma turns on the question: In today’s new era of social justice, are these monuments primarily symbols of oppression, or can we see them, in select cases, alternatively as sites of conscience and reflection encompassing more inclusive conversations about commemoration? What we save or destroy and assign as the ultimate public value of these monuments rests with how we answer this question. Objective: I describe monuments as symbols in the “Lost Cause” narrative and their place in enduring Confederate legacies. I make the case, and offer documented examples, that remnants of the monuments, such as the “decorated” pedestals, if not the original towering statues themselves, should be left in place as sites of reflection that can be socially useful in public interpretation as disruptions of space, creating disturbances of vision that can be provocative and didactic. I argue that we should see at least some of them as sculptural works of art that invite interpretations of aesthetic and artistic value. I point out how, today, these internationally relevant factors and outcomes of retention vs. removal are engulfed in swirls of social and political contention and controversy within processes of remembering and forgetting and changing public dialogues. Methods: This article addresses several elements within the purview of the Journal: questions of contemporary society, diversity of opinion, recognition of complexity, subject matter of interest to non-specialists, international relevancy, and history. Drawing from the testimony of scholars and artists, I address the contemporary conceptual landscape of approaches to the presentation and evolving participatory narratives of Confederate monuments that range from absolute expungement and removal to more restrained responses such as in situ re-contextualization, removal to museums, and preservation-in-place. In a new era of social justice surrounding the aftermath of dramatic events such as the 2015 Charleston shooting, the 2017 Charlotteville riot, and the murder of George Floyd, should we see them as symbols of oppression, inviting expungement, or selectively as sites of conscience and reflection, inviting various forms of re-interpretation of tangible and intangible relationships?
I describe monuments as symbols in the “Lost Cause” narrative and their place in enduring Confederate legacies. I make the case, and offer documented examples, that remnants of the monuments, such as the “decorated” pedestals, if not the original towering statues themselves, should be left in place as sites of reflection that can be socially useful in public interpretation as disruptions of space, creating disturbances of vision that can be provocative and didactic. I argue that we should see at least some of them as sculptural works of art that invite interpretations of aesthetic and artistic value. I point out how, today, these internationally relevant factors and outcomes of retention vs. removal are engulfed in swirls of social and political contention and controversy within processes of remembering and forgetting and changing public dialogues. Results: I argue that we should see at least some of them as sculptural works of art that invite interpretations of aesthetic and artistic value. I point out how, today, these internationally relevant factors and outcomes of retention vs. removal are engulfed in swirls of social and political contention and controversy within processes of remembering and forgetting and changing public dialogues. Conclusions: Today, all of these potential factors and outcomes, with internationally relevance, are surrounded by swirls of social and political contention and controversy, including the remembering/forgetting dichotomies of cultural heritage. The modern dilemma turns on the question: In today’s new era of social justice, are these monuments primarily symbols of oppression, or can we see them, in select cases, alternatively as sites of conscience and reflection encompassing more inclusive conversations about commemoration? What we save or destroy and assign as the ultimate public value of these monuments rests with how we answer this question.
Background: The COVID19 pandemic has caused a large number of infections and fatalities, causing administrations
at various levels to limit public mobility. This paper analyzes the complex associatio...
Background: The COVID19 pandemic has caused a large number of infections and fatalities, causing administrations
at various levels to limit public mobility. This paper analyzes the complex association between the
stringency of restrictions, public mobility, and reproduction rate (R-value) on a national level for Germany. Objective: The goals were to analyze; a) the correlation between government restrictions and public mobility and b)
the association between public mobilities and virus reproduction. Methods: In addition to correlations, a Gaussian
Process Regression Technique is used to fit the interaction between mobility and R-value. Results: The main
findings are that: (i) Government restrictions has a high association with reduced public mobilities,
especially for non-food stores and public transport, (ii) Out of six measured public mobilities, retail,
recreation, and transit station activities have the most significant impact on COVID19 reproduction rates. Conclusions: A mobility reduction of 30% is required to have a critical negative impact on case number dynamics,
preventing further spread.
Background: Exercise intervention is effective in managing diabetes when delivered in a personalized manner. Personalization of exercise intervention following a systematic fitness assessment can lead...
Background: Exercise intervention is effective in managing diabetes when delivered in a personalized manner. Personalization of exercise intervention following a systematic fitness assessment can lead to better health outcomes Objective: This study aimed to analyze the effect of digitally delivered fitness assessments and exercise prescriptions on the fitness and health outcomes of people with diabetes. Methods: Participants diagnosed with type 2 diabetes (n=86) enrolled in the Fitterfly Diabetes program which included interventions in nutrition, fitness, and mental health delivered via a digital platform. The participants underwent a video call-based fitness assessment consisting of the 1-minute push-up test, wall sit test, 1-minute sit-up test, V-sit and reach test, and 6-minute walk test. Trained physiotherapists conducted the assessments, developed personalized exercise plans, and shared them with the participants via the app. Regular follow-ups were taken. The participants were re-assessed after 90 days. Results: There was a statistically significant improvement in the fitness-related outcome measures (p<0.05), the anthropometric measures (p<0.05), and HbA1c (p<0.05) post-intervention. Improvement in exercise duration was associated with better outcomes in fitness tests and anthropometric measures. Conclusions: Personalized exercise intervention delivered digitally can help achieve better health outcomes in people with type 2 diabetes.