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Accepted for/Published in: JMIR Aging

Date Submitted: Sep 26, 2022
Open Peer Review Period: Jul 25, 2022 - Sep 19, 2022
Date Accepted: May 21, 2023
(closed for review but you can still tweet)

The final, peer-reviewed published version of this preprint can be found here:

Factors Predicting Older People’s Acceptance of a Personalized Health Care Service App and the Effect of Chronic Disease: Cross-Sectional Questionnaire Study

Koo JH, Park YH, Kang DR

Factors Predicting Older People’s Acceptance of a Personalized Health Care Service App and the Effect of Chronic Disease: Cross-Sectional Questionnaire Study

JMIR Aging 2023;6:e41429

DOI: 10.2196/41429

PMID: 37342076

PMCID: 10334719

Factors Predicting Older People’s Acceptance of a Personalized Healthcare Service App and the Effect of Chronic Disease: A Cross-Sectional Questionnaire Study

  • Jun Hyuk Koo; 
  • You Hyun Park; 
  • Dae Ryong Kang

ABSTRACT

Background:

mHealth services enable real-time measurement of information on individuals' biosignals and environmental risk factors; accordingly, research on health management using mHealth is being actively conducted. This study investigates attitudes toward an mHealth personalized healthcare service app (currently in development, featuring wearable devices) among the elderly in South Korea.

Objective:

The study aims to identify factors that influence older people's intention to use mHealth and to verify whether the presence of chronic disease moderates the effect of the identified factors on their behavioral intentions.

Methods:

A cross-sectional study was conducted among 500 participants aged 60 to 75. The research hypotheses were tested using structural equation modeling, and indirect effects were verified through bootstrapping. Bootstrapping was performed 10,000 times, and the significance of the indirect effects was confirmed through the bias-corrected percentile method.

Results:

Of 477 participants, 278 (58.3%) had at least one chronic disease. Performance expectancy (beta=0.453, P=.003) and social influence (beta=0.693, P=<.001) had direct effects on behavioral intention. As a result of bootstrapping, facilitating conditions (beta=0.325, P=.006, 95% CI 0.115-0.759) were found to have a significant indirect effect on behavioral intention. Multi-group structural equation modeling testing the presence or absence of chronic disease revealed a significant difference in the path of device trust on performance expectancy (critical ratio=-2.165). Bootstrapping also confirmed that device trust (beta=0.122, P=.039, 95% CI 0.007-0.346) had a significant indirect effect on behavioral intention in people with chronic disease.

Conclusions:

To encourage older people to use personalized healthcare services, it is important to clearly demonstrate and emphasize their benefits in terms of healthcare management. The awareness of people around them also plays an important role. In particular, it is necessary to promote such services at the family and community levels; this aspect is particularly important in the Confucian culture. In addition, support from service providers should be strengthened, so that older people trust that they have consistent access to technical support. Overall, if people with chronic diseases have confidence in a wearable device for measuring biosignals, a higher utilization rate could be achieved.


 Citation

Please cite as:

Koo JH, Park YH, Kang DR

Factors Predicting Older People’s Acceptance of a Personalized Health Care Service App and the Effect of Chronic Disease: Cross-Sectional Questionnaire Study

JMIR Aging 2023;6:e41429

DOI: 10.2196/41429

PMID: 37342076

PMCID: 10334719

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