Investigating the Adoption of Mobile Health Services by Elderly Users: Trust Transfer Model and Survey Study

JMIR Mhealth Uhealth. 2019 Jan 8;7(1):e12269. doi: 10.2196/12269.

Abstract

Background: Although elderly users comprise a major user group in the field of mobile health (mHealth) services, their adoption rate of such services is relatively low compared with their use of traditional health services. Increasing the adoption rate of mHealth services among elderly users is beneficial to the aging process.

Objective: This study aimed to examine the determinants of mHealth service use intentions using a trust transfer model among elderly users facing declining physiological conditions and lacking support from hospitals.

Methods: A survey comprising 395 users aged 60 years and above was conducted in China to validate our research model and hypotheses.

Results: The results reveal that (1) trust in mHealth services positively influences use intentions, (2) trust in offline health services positively influences trust in mHealth services, (3) declining physiological conditions strengthen the effects of trust in offline health services regarding trust in mHealth services, (4) support from hospitals weakens the effects of trust in mHealth services on use intentions, and (5) the relationship between trust in offline health services and intention to use mHealth services is partially mediated by trust in mHealth services. The independent variables and moderators collectively explain a 48.3% variance in the use intention of mHealth services.

Conclusions: We conclude that the trust transfer theory is useful in explaining the development of initial trust in mHealth services. In addition, declining physiological conditions and support from hospitals are important factors for investigating the adoption of mHealth services among elderly users.

Keywords: adoption; health behavior; health services for the elderly; mobile health; trust.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • China
  • Female
  • Humans
  • Intention
  • Male
  • Middle Aged
  • Mobile Applications / statistics & numerical data*
  • Patient Acceptance of Health Care / psychology
  • Patient Acceptance of Health Care / statistics & numerical data*
  • Surveys and Questionnaires
  • Trust / psychology*
  • User-Computer Interface