Previously submitted to: JMIR mHealth and uHealth (no longer under consideration since Jan 12, 2024)
Date Submitted: Mar 13, 2023
Open Peer Review Period: Mar 13, 2023 - May 8, 2023
(closed for review but you can still tweet)
NOTE: This is an unreviewed Preprint
Warning: This is a unreviewed preprint (What is a preprint?). Readers are warned that the document has not been peer-reviewed by expert/patient reviewers or an academic editor, may contain misleading claims, and is likely to undergo changes before final publication, if accepted, or may have been rejected/withdrawn (a note "no longer under consideration" will appear above).
Peer review me: Readers with interest and expertise are encouraged to sign up as peer-reviewer, if the paper is within an open peer-review period (in this case, a "Peer Review Me" button to sign up as reviewer is displayed above). All preprints currently open for review are listed here. Outside of the formal open peer-review period we encourage you to tweet about the preprint.
Citation: Please cite this preprint only for review purposes or for grant applications and CVs (if you are the author).
Final version: If our system detects a final peer-reviewed "version of record" (VoR) published in any journal, a link to that VoR will appear below. Readers are then encourage to cite the VoR instead of this preprint.
Settings: If you are the author, you can login and change the preprint display settings, but the preprint URL/DOI is supposed to be stable and citable, so it should not be removed once posted.
Submit: To post your own preprint, simply submit to any JMIR journal, and choose the appropriate settings to expose your submitted version as preprint.
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Mapping the evidence on the impact of mHealth interventions on patient-reported outcomes in breast cancer patients: A systematic review
ABSTRACT
Background:
The field of mHealth has grown exponentially in the last decade due to the widespread use of smartphones and the advancements in mobile technology, which has created opportunities to find solutions to unmet healthcare needs for patients with chronic diseases. Furthermore, healthcare is entering a new value-based paradigm, founded on three main pillars: efficiency, safety, and value for patients.
Objective:
The objective of this review is to summarize the current knowledge on the impact of mHealth on patient-reported outcomes in breast cancer (BC) patients.
Methods:
Three databases were systematically searched to identify studies that met eligibility criteria: PubMed, PsychInfo, and Google Scholar. Relevant systematic reviews and the references of the research articles they contained were also searched in case that studies were missed during the initial search. Searches were made on December 17th, 2021. Two investigators independently reviewed the titles and abstracts of the identified studies and then read the full text of all selected papers. In case a discrepancy was found, It was discussed with a third investigator in order to make a final decision. The quality of the included studies was analyzed by the Cochrane Collaboration Risk of Bias Tool and the Methodological Index for Non-Randomized Studies.
Results:
Twenty-two unique studies involving 3,502 patients were included. The focus of the interventions in the studies included in the review were physical activity (11 studies), tailored information for better self-management of the disease (8 studies), mental health therapies (6 studies), symptom tracker (4 studies), and others (6 studies). All interventions were at least 8 weeks long of duration, with a median duration of 12 weeks (interquartile range 4-18 weeks). mHealth interventions showed better results on symptom burden, fatigue, quality of life and physical activity. Likewise, tailored information, symptom tracker, nutrition and physical activity were the interventions that yielded better results. Apps with interactive support had a higher rate of positive findings, while interventions targeted to survivors showed worse results.
Conclusions:
mHealth applications in BC patients is a highly heterogeneous field. Our study suggests that interventions focused on newly diagnosed patients or patients while on chemotherapy, interventions with interactive human support and those with a duration of 12 weeks or more showed better results in terms of patient-reported outcome. Interventions must be adapted to each patient鈥檚 characteristics and disease stage to meet their specific needs at the time of deployment. Positive impact on endpoints show what can be achieved with the right mHealth intervention. The reproducibility of the studies reporting mHealth interventions is currently uncertain.
Citation
Request queued. Please wait while the file is being generated. It may take some time.
Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.