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

Use and User Demographics of mHealth (313) Demographics of Users, Social & Digital Divide (685)

Published on in Vol 6, No 4 (2018): April

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/9002, first published .
Prevalence, Demographic Correlates, and Perceived Impacts of Mobile Health App Use Amongst Chinese Adults: Cross-Sectional Survey Study

Prevalence, Demographic Correlates, and Perceived Impacts of Mobile Health App Use Amongst Chinese Adults: Cross-Sectional Survey Study

Prevalence, Demographic Correlates, and Perceived Impacts of Mobile Health App Use Amongst Chinese Adults: Cross-Sectional Survey Study

Authors of this article:

Zhenzhen Xie1 Author Orcid Image ;   Ahmet Nacioglu1 Author Orcid Image ;   Calvin Or1 Author Orcid Image
Article Authors Cited by (53) Tweetations (1) Metrics

Journals

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  2. Or C, Liu K, So M, Cheung B, Yam L, Tiwari A, Lau Y, Lau T, Hui P, Cheng H, Tan J, Cheung M. Improving Self-Care in Patients With Coexisting Type 2 Diabetes and Hypertension by Technological Surrogate Nursing: Randomized Controlled Trial. Journal of Medical Internet Research 2020;22(3):e16769 View
  3. Steeb T, Wessely A, Mastnik S, Brinker T, French L, Niesert A, Berking C, Heppt M. Patient Attitudes and Their Awareness Towards Skin Cancer–Related Apps: Cross-Sectional Survey. JMIR mHealth and uHealth 2019;7(7):e13844 View
  4. Szinay D, Jones A, Chadborn T, Brown J, Naughton F. Influences on the Uptake of and Engagement With Health and Well-Being Smartphone Apps: Systematic Review. Journal of Medical Internet Research 2020;22(5):e17572 View
  5. Lupton D. Australian women’s use of health and fitness apps and wearable devices: a feminist new materialism analysis. Feminist Media Studies 2020;20(7):983 View
  6. Guzman-Parra J, Barnestein-Fonseca P, Guerrero-Pertiñez G, Anderberg P, Jimenez-Fernandez L, Valero-Moreno E, Goodman-Casanova J, Cuesta-Vargas A, Garolera M, Quintana M, García-Betances R, Lemmens E, Sanmartin Berglund J, Mayoral-Cleries F. Attitudes and Use of Information and Communication Technologies in Older Adults With Mild Cognitive Impairment or Early Stages of Dementia and Their Caregivers: Cross-Sectional Study. Journal of Medical Internet Research 2020;22(6):e17253 View
  7. Ernsting C, Stühmann L, Dombrowski S, Voigt-Antons J, Kuhlmey A, Gellert P. Associations of Health App Use and Perceived Effectiveness in People With Cardiovascular Diseases and Diabetes: Population-Based Survey. JMIR mHealth and uHealth 2019;7(3):e12179 View
  8. Zhang Y, Liu C, Luo S, Huang J, Li X, Zhou Z. Effectiveness of Lilly Connected Care Program (LCCP) App-Based Diabetes Education for Patients With Type 2 Diabetes Treated With Insulin: Retrospective Real-World Study. JMIR mHealth and uHealth 2020;8(3):e17455 View
  9. Zhang L, Qin Y, Li P. Media Complementarity and Health Information Acquisition: A Cross-sectional Analysis of the 2017 HINTS-China Survey. Journal of Health Communication 2020;25(4):291 View
  10. Bach R, Wenz A, Borsci S. Studying health-related internet and mobile device use using web logs and smartphone records. PLOS ONE 2020;15(6):e0234663 View
  11. Liu K, Xie Z, Or C. Effectiveness of Mobile App-Assisted Self-Care Interventions for Improving Patient Outcomes in Type 2 Diabetes and/or Hypertension: Systematic Review and Meta-Analysis of Randomized Controlled Trials. JMIR mHealth and uHealth 2020;8(8):e15779 View
  12. Khan K, Basavarajappa C, Kunigiri G. Ease of Use of the Electroconvulsive Therapy App by Its Users: Cross-Sectional Questionnaire Study. JMIR Biomedical Engineering 2020;5(1):e20730 View
  13. Xie Z, Kalun Or C. Acceptance of mHealth by Elderly Adults: A Path Analysis. Proceedings of the Human Factors and Ergonomics Society Annual Meeting 2020;64(1):755 View
  14. Alshathri D, Alhumaimeedy A, Al-Hudhud G, Alsaleh A, Al-Musharaf S, Aljuraiban G. Weight Management Apps in Saudi Arabia: Evaluation of Features and Quality. JMIR mHealth and uHealth 2020;8(10):e19844 View
  15. Chen T, Or C, Chen J. Effects of technology-supported exercise programs on the knee pain, physical function, and quality of life of individuals with knee osteoarthritis and/or chronic knee pain: A systematic review and meta-analysis of randomized controlled trials. Journal of the American Medical Informatics Association 2021;28(2):414 View
  16. Baek Y, Jeong K, Lee S, Kim H, Seo B, Jin H. Feasibility and Effectiveness of Assessing Subhealth Using a Mobile Health Management App (MibyeongBogam) in Early Middle-Aged Koreans: Randomized Controlled Trial. JMIR mHealth and uHealth 2021;9(8):e27455 View
  17. Kongjit C, Nimmolrat A, Khamaksorn A. Mobile health application for Thai women: investigation and model. BMC Medical Informatics and Decision Making 2022;22(1) View
  18. Chen T, Or C. Development and pilot test of a machine learning-based knee exercise system with video demonstration, real-time feedback, and exercise performance score. Proceedings of the Human Factors and Ergonomics Society Annual Meeting 2021;65(1):1519 View
  19. Cao L, Chongsuvivatwong V, McNeil E. The Sociodemographic Digital Divide in Mobile Health App Use Among Clients at Outpatient Departments in Inner Mongolia, China: Cross-sectional Survey Study. JMIR Human Factors 2022;9(2):e36962 View
  20. Song J, Li Y, Guo X, Shen K, Ju X. Making Mobile Health Information Advice Persuasive. Journal of Organizational and End User Computing 2022;34(4):1 View
  21. Alzahrani A, Gay V, Alturki R. Exploring Saudi Individuals’ Perspectives and Needs to Design a Hypertension Management Mobile Technology Solution: Qualitative Study. International Journal of Environmental Research and Public Health 2022;19(19):12956 View
  22. Wang X, Wu Y, Meng Z, Li J, Xu L, Sun X, Zang S. Willingness to Use Mobile Health Devices in the Post–COVID-19 Era: Nationwide Cross-sectional Study in China. Journal of Medical Internet Research 2023;25:e44225 View
  23. Ali Z, Dang H. Factors impacting the use of the NZ COVID Tracer application in New Zealand". Smart Health 2022;24:100278 View
  24. Buss V, Varnfield M, Harris M, Barr M. Mobile Health Use by Older Individuals at Risk of Cardiovascular Disease and Type 2 Diabetes Mellitus in an Australian Cohort: Cross-sectional Survey Study. JMIR mHealth and uHealth 2022;10(9):e37343 View
  25. Ahmadi M, Shahrokhi S, Khavaninzadeh M, Alipour J. Development of a Mobile-Based Self-care Application for Patients with Breast Cancer-Related Lymphedema in Iran. Applied Clinical Informatics 2022;13(05):935 View
  26. Xie Z, Chen J, Or C. Consumers’ Willingness to Pay for eHealth and Its Influencing Factors: Systematic Review and Meta-analysis. Journal of Medical Internet Research 2022;24(9):e25959 View
  27. Fang P, Shi S, Menhas R, Laar R, Saeed M. Demographic Characteristics and Digital Platforms for Physical Activity Among the Chinese Residents During the COVID-19 Pandemic: A Mediating Analysis. Journal of Multidisciplinary Healthcare 2022;Volume 15:515 View
  28. Fu S, Fang J, Cai Z, Lim E, Tan C, Yang H. Advancing health-related abilities and behaviors via health apps: a large-scale survey from self-regulation perspective. Internet Research 2022;32(4):1097 View
  29. Ping Y, Visaria A, Suppiah S, Tan Y, Malhotra R. Prevalence and correlates of medication reminder app ‘use and use intention’ among older adults. Exploratory Research in Clinical and Social Pharmacy 2022;6:100150 View
  30. Mustafa A, Ali N, Dhillon J, Alkawsi G, Baashar Y. User Engagement and Abandonment of mHealth: A Cross-Sectional Survey. Healthcare 2022;10(2):221 View
  31. Amer S, Bahumayim A, Shah J, Aleisa N, Hani B, Omar D. Prevalence and Determinants of Mobile Health Applications Usage: A National Descriptive Study. Frontiers in Public Health 2022;10 View
  32. Liu K, Or C, So M, Cheung B, Chan B, Tiwari A, Tan J. A longitudinal examination of tablet self-management technology acceptance by patients with chronic diseases: Integrating perceived hand function, perceived visual function, and perceived home space adequacy with the TAM and TPB. Applied Ergonomics 2022;100:103667 View
  33. Wang Y, Wu T, Chen Z. Active Usage of Mobile Health Applications: Cross-sectional Study. Journal of Medical Internet Research 2021;23(12):e25330 View
  34. Su B, Chen Y, Shen X, Guo J, Ding Y, Ma X, Yang Y, Liu D. Effectiveness of the Lilly Connected Care Program in Improving Glycemic Management Among Patients With Type 2 Diabetes in China: Retrospective Real-world Study. Journal of Medical Internet Research 2023;25:e38680 View
  35. Inagaki S, Kato K, Abe K, Takahashi H, Matsuda T. Relationship between Diabetes Self-Management and the Use of Health Care Apps: A Cross-Sectional Study. ACI Open 2023;07(01):e23 View
  36. Naranjo-Rojas A, Perula-de Torres L, Cruz-Mosquera F, Molina-Recio G. Usability of a mobile application for the clinical follow-up of patients with chronic obstructive pulmonary disease and home oxygen therapy. International Journal of Medical Informatics 2023;175:105089 View
  37. Qu S, Zhou M, Kong N, Campy K. Factors influencing user acceptance of weight management apps among Chinese obese individuals during the COVID-19 pandemic. Health Policy and Technology 2023;12(2):100758 View
  38. Tundealao S, Titiloye T, Sajja A, Egab I, Odole I, Alufa O, Olarewaju O. Factors associated with the non-use of mobile health applications among adults in the United States. Journal of Public Health 2023 View
  39. Oba T, Takano K, Katahira K, Kimura K. Use Patterns of Smartphone Apps and Wearable Devices Supporting Physical Activity and Exercise: Large-Scale Cross-Sectional Survey. JMIR mHealth and uHealth 2023;11:e49148 View
  40. Chen T, Or C. Perceptions of a machine learning-based lower-limb exercise training system among older adults with knee pain. DIGITAL HEALTH 2023;9 View
  41. Huang J, Pang W, Wong Y, Ko S, Yip S, Chan F, Cheung C, Wong W, Cheung N, Wong M. Evaluation on the adoption of eHealth App for electronic health record sharing system in Hong Kong. Annals of the Academy of Medicine, Singapore 2023;52(8):440 View
  42. Xie Z, Or C. Consumers’ Preferences for Purchasing mHealth Apps: Discrete Choice Experiment. JMIR mHealth and uHealth 2023;11:e25908 View
  43. Assiri G, Alabdulkarim D, Alanazi A, Altamimi S, Alanazi N, Khawagi W. Description of patient characteristics and medication adherence among medication access mobile application users and nonusers: a single-center questionnaire-based cross-sectional study. BMC Digital Health 2023;1(1) View
  44. Heydari M, Mehraeen E, Javaherikiyan E, Mehrabi N, Langarizadeh M, Aghamohammadi V, Moghaddam H, Nasiri K. Design, development and evaluation of a mobile-based self-care application for patients with COVID-19 not requiring hospitalization; a study of Northwest of Iran. BMC Medical Informatics and Decision Making 2023;23(1) View
  45. Rajan R, Muthunarayanan L. A Comparative Study on the Prevalence of Lifestyle Risk Factors Among Users and Non-users of Any Health-Based Mobile App Among University Students in Chennai. Cureus 2024 View
  46. Tao D, Liu K. How do self-motivation and social motivation contribute to consumers’ acceptance of m-health services?. Health Policy and Technology 2024;13(3):100878 View
  47. Jiang J, Zheng Z. Medical Information Protection in Internet Hospital Apps in China: Scale Development and Content Analysis. JMIR mHealth and uHealth 2024;12:e55061 View

Books/Policy Documents

  1. Khan Z, Ahmed R, Sen D. Privacy Concerns Surrounding Personal Information Sharing on Health and Fitness Mobile Apps. View
  2. Khan Z, Ahmed R, Sen D. Research Anthology on Securing Mobile Technologies and Applications. View
  3. Khan Z, Ahmed R, Sen D. Research Anthology on Privatizing and Securing Data. View
  4. Or C, Holden R, Valdez R. Human-Automation Interaction. View
  5. Ruotsalainen I, Valtanen M, Kärsämä R, Umer A, Parikka S, Lundqvist A, Lindström J. Digital Health and Wireless Solutions. View