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

Information Retrieval (287) eHealth Literacy / Digital Literacy (390) Quality/Credibility of eHealth Information and Trust Issues (531) Information Seeking, Information Needs (465)

Published on in Vol 24, No 11 (2022): November

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/42447, first published .
Online Health Information Seeking Among Patients With Chronic Conditions: Integrating the Health Belief Model and Social Support Theory

Online Health Information Seeking Among Patients With Chronic Conditions: Integrating the Health Belief Model and Social Support Theory

Online Health Information Seeking Among Patients With Chronic Conditions: Integrating the Health Belief Model and Social Support Theory

Authors of this article:

Yuxiang Chris Zhao1 Author Orcid Image ;   Mengyuan Zhao2 Author Orcid Image ;   Shijie Song3, 4 Author Orcid Image
Article Authors Cited by (22) Tweetations (8) Metrics

Journals

  1. Park M, Oh K, Kim H, Fan X, Giap T, Song R. Cognitive and Emotional Motivation to Explain Infection-Prevention Behaviors with Social Support as a Mediator During the COVID-19 Pandemic: A Nationwide Cross-Sectional Study in Korea. Patient Preference and Adherence 2023;Volume 17:1063 View
  2. Wang J, Zhen X, Coyte P, Shao D, Zhao N, Chang L, Feng Y, Sun X. Association Between Online Health Information–Seeking Behaviors by Caregivers and Delays in Pediatric Cancer: Mixed Methods Study in China. Journal of Medical Internet Research 2023;25:e46953 View
  3. Liu J, Wang S. Factors Influencing the Purchase Intention for Online Health Popular Science Information Based on the Health Belief Model. Behavioral Sciences 2023;13(8):693 View
  4. Zhu G, Li F, Yan Y, Guenis H. Privacy paradox resolution in mHealth: the moderating effect of rationality degree. Journal of Enterprise Information Management 2023 View
  5. Wu Y, Wen J, Wang X, Wang Q, Wang W, Wang X, Xie J, Cong L. Chinese Community Home-Based Aging Institution Elders’ Self-Management of Chronic Non-Communicable Diseases and Its Interrelationships with Social Support, E-Health Literacy, and Self Efficacy: A Serial Multiple Mediation Model. Patient Preference and Adherence 2023;Volume 17:1311 View
  6. Blanco G, Lourenço A. A multilayered graph-based framework to explore behavioural phenomena in social media conversations. International Journal of Medical Informatics 2023;179:105236 View
  7. Yoon H, Oh S. Female College Students' Perceptions on the Internet Use for Reproductive Health Information. Proceedings of the Association for Information Science and Technology 2023;60(1):1203 View
  8. Luo L, Huang J, Li H. Characteristics of Chinese women in need of enhanced sexual health attention and at risk of hypoactive sexual desire disorder. BMC Women's Health 2023;23(1) View
  9. SALBAŞ E. An Assessment of the Content, Readability, and Reliability of Turkish Websites That Provide Information About Facial Paralysis. Genel Tıp Dergisi 2023;33(2):188 View
  10. Luo L, Huang J, Li H. Barriers to sexual health-seeking behaviors for Chinese women. Archives of Women's Mental Health 2023;26(5):581 View
  11. Zheng Y, Wang X, Xia C. Effects of different intervention methods on psychological flexibility, negative emotions and sleep quality in chronic hepatitis B. World Journal of Psychiatry 2023;13(10):753 View
  12. Yang E, Kim M, Lee K. Internet use and difficulties in acquiring health resources among older adults with disabilities during the COVID-19 pandemic: a population-based cross-sectional study. BMC Public Health 2024;24(1) View
  13. Sinha J, Serin N. Online Health Information Seeking and Preventative Health Actions: Cross-Generational Online Survey Study. Journal of Medical Internet Research 2024;26:e48977 View
  14. Liu Z, Liao Y, Hwang C, Rethorst C, Zhang X. Associations of online health information seeking with health behaviors of cancer survivors. DIGITAL HEALTH 2024;10 View
  15. Zhao B, Huang L, Cheng X, Chen T, Li S, Wang X, Huang S, Hu R, Li H. Digital health literacy and associated factors among internet users from China: a cross-sectional study. BMC Public Health 2024;24(1) View
  16. Maida E, Moccia M, Palladino R, Borriello G, Affinito G, Clerico M, Repice A, Di Sapio A, Iodice R, Spiezia A, Sparaco M, Miele G, Bile F, Scandurra C, Ferraro D, Stromillo M, Docimo R, De Martino A, Mancinelli L, Abbadessa G, Smolik K, Lorusso L, Leone M, Leveraro E, Lauro F, Trojsi F, Streito L, Gabriele F, Marinelli F, Ianniello A, De Santis F, Foschi M, De Stefano N, Morra V, Bisecco A, Coghe G, Cocco E, Romoli M, Corea F, Leocani L, Frau J, Sacco S, Inglese M, Carotenuto A, Lanzillo R, Padovani A, Triassi M, Bonavita S, Lavorgna L. ChatGPT vs. neurologists: a cross-sectional study investigating preference, satisfaction ratings and perceived empathy in responses among people living with multiple sclerosis. Journal of Neurology 2024;271(7):4057 View
  17. Ren R, Li H, Zhang J, Li X, Yuan L, Li D, Shan S, Shi B, Jiang J. Knowledge, attitudes, and practices among Chinese reproductive-age women toward uterine adenomyosis. Frontiers in Medicine 2024;11 View
  18. Kim N, Lee S, Andreu-Perez L, Pitluk A, Kim J. Coping with Non-COVID-19 Health Problems Through Communicative Action in Cyberspace. Journal of Health Communication 2024;29(7):450 View
  19. Halder S, Tiwari V, Ali S. Exploring health knowledge: An extensive review of information seeking behaviors, health literacy, and the relevance of libraries and community resources. IP Indian Journal of Library Science and Information Technology 2024;9(1):4 View
  20. Wang Q, Lee R, Hunter S, Zhu A, Chan S. Patient Engagement in a Mobile App–Based Rehabilitation Program for Total Hip or Knee Arthroplasty: Secondary Data Analysis of a Randomized Controlled Trial. JMIR mHealth and uHealth 2024;12:e57635 View
  21. Wang L, Zhang S, Naeem S. Modeling the predictors of health information avoidance behavior: Implications from the stimulus organism response (S-O-R) theory. Journal of Librarianship and Information Science 2024 View

Books/Policy Documents

  1. Komalasari R. Federated Learning and Privacy-Preserving in Healthcare AI. View