This paper is in the following e-collection/theme issue:

Mobile Devices and Apps for Seniors and Healthy Aging (167) Mobile Health (mhealth) (2941) Prevention and Health Promotion (987) User Needs and Competencies (303)

Published on in Vol 6 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/41429, first published .
Factors Predicting Older People’s Acceptance of a Personalized Health Care Service App and the Effect of Chronic Disease: Cross-Sectional Questionnaire Study

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

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

Authors of this article:

Jun Hyuk Koo1 Author Orcid Image ;   You Hyun Park2 Author Orcid Image ;   Dae Ryong Kang2, 3 Author Orcid Image
Article Authors Cited by (2) Tweetations (2) Metrics

Journals

  1. Putri L, Kurniawan A, Mamesah M, Trisnawuri S. Perspektif Pasien Hipertensi Terhadap Implementasi Personal Health Record Berdasarkan Technology Acceptance Model. Jurnal Manajemen Kesehatan Yayasan RS.Dr. Soetomo 2023;9(2):332 View
  2. Lee H, Cho J, Park J, Lee H, Fond G, Boyer L, Kim H, Park S, Cho W, Lee H, Lee J, Yon D. Machine Learning–Based Prediction of Suicidality in Adolescents With Allergic Rhinitis: Derivation and Validation in 2 Independent Nationwide Cohorts. Journal of Medical Internet Research 2024;26:e51473 View