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Using a Technology Acceptance Model to Explore the Intention to Use Digital Health Technologies Among People With

Jae-Hak Kim1, Janghyeon Kim2,3, Bo-Young Youn3

  • 1Department of Fitness Promotion and Rehabilitation Exercise, National Rehabilitation Center, Seoul, Republic of Korea.

Journal of Medical Internet Research
|November 20, 2025
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Summary

Perceived usefulness and ease of use are key to electronic personal health record (e-PHR) adoption for people with disabilities. Designing user-friendly e-PHRs with tailored content and strong support systems is essential for this population.

Keywords:
digital healthdigital health literacydisabilityhealth managementintention to usepeople with disabilitiestechnology acceptance model

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Area of Science:

  • Health Informatics
  • Disability Studies
  • Technology Acceptance Models

Background:

  • Electronic personal health records (e-PHRs) offer potential benefits for health management but present adoption challenges for individuals with disabilities.
  • Understanding the specific factors influencing e-PHR acceptance in this demographic is critical for equitable technology implementation.

Purpose of the Study:

  • To investigate the determinants of e-PHR usage intention among people with disabilities using a Technology Acceptance Model (TAM) framework.
  • To examine the influence of external factors including health consciousness, health information consent, content characteristics, information security, eHealth literacy, and effectiveness on e-PHR adoption.

Main Methods:

  • A nationwide survey of 800 individuals with disabilities in South Korea was conducted using a proportionate stratified and systematic stratified cluster sampling method.
  • Structural equation modeling with bootstrapped mediation and multigroup analyses by disability severity were employed to test the proposed hypotheses.

Main Results:

  • Perceived usefulness (PU) and perceived ease of use (PEU) were primary drivers of e-PHR usage intention, with PEU positively influencing PU.
  • Effectiveness and health information consent significantly predicted PU, while health consciousness, content characteristics, health information consent, information security, and effectiveness predicted PEU.
  • Disability severity influenced the impact of PU and PEU on usage intention, with content characteristics and information security showing differential effects based on severity.

Conclusions:

  • Perceived usefulness and ease of use are critical mediators for e-PHR adoption among people with disabilities.
  • Future digital health solutions should prioritize user-friendliness, robust support, privacy, and tailored content for this population.
  • Acknowledging potential selection bias due to sampling limitations, future research should aim for broader and more diverse participant recruitment.