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Citing this Article

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Published on 06.12.17 in Vol 5, No 12 (2017): December

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

Works citing "Patients’ Acceptance of Smartphone Health Technology for Chronic Disease Management: A Theoretical Model and Empirical Test"

According to Crossref, the following articles are citing this article (DOI 10.2196/mhealth.7886):

(note that this is only a small subset of citations)

  1. Li J, Chang X. Improving mobile health apps usage: a quantitative study on mPower data of Parkinson's disease. Information Technology & People 2020;ahead-of-print(ahead-of-print)
    CrossRef
  2. Wang Z, Huang H, Cui L, Chen J, An J, Duan H, Ge H, Deng N. Using Natural Language Processing Techniques to Provide Personalized Educational Materials for Chronic Disease Patients in China: Development and Assessment of a Knowledge-Based Health Recommender System. JMIR Medical Informatics 2020;8(4):e17642
    CrossRef
  3. Duan H, Wang Z, Ji Y, Ma L, Liu F, Chi M, Deng N, An J. Using Goal-Directed Design to Create a Mobile Health App to Improve Patient Compliance With Hypertension Self-Management: Development and Deployment. JMIR mHealth and uHealth 2020;8(2):e14466
    CrossRef
  4. Rodriguez Hermosa JL, Fuster Gomila A, Puente Maestu L, Amado Diago CA, Callejas González FJ, Malo De Molina Ruiz R, Fuentes Ferrer ME, Álvarez Sala-Walther JL, Calle Rubio M. Compliance and Utility of a Smartphone App for the Detection of Exacerbations in Patients With Chronic Obstructive Pulmonary Disease: Cohort Study. JMIR mHealth and uHealth 2020;8(3):e15699
    CrossRef
  5. Kabeza CB, Harst L, Schwarz PE, Timpel P. A qualitative study of users’ experiences after 3 months: the first Rwandan diabetes self-management Smartphone application “Kir’App”. Therapeutic Advances in Endocrinology and Metabolism 2020;11:204201882091451
    CrossRef
  6. Thongtipmak S, Buranruk O, Eungpinichpong W, Konharn K. Immediate Effects and Acceptability of an Application-Based Stretching Exercise Incorporating Deep Slow Breathing for Neck Pain Self-management. Healthcare Informatics Research 2020;26(1):50
    CrossRef
  7. Ye Q, Deng Z, Chen Y, Liao J, Li G, Lu Y. How Resource Scarcity and Accessibility Affect Patients’ Usage of Mobile Health in China: Resource Competition Perspective. JMIR mHealth and uHealth 2019;7(8):e13491
    CrossRef
  8. Zhang Y, Liu C, Luo S, Xie Y, Liu F, Li X, Zhou Z. Factors Influencing Patients’ Intentions to Use Diabetes Management Apps Based on an Extended Unified Theory of Acceptance and Use of Technology Model: Web-Based Survey. Journal of Medical Internet Research 2019;21(8):e15023
    CrossRef
  9. Ye T, Xue J, He M, Gu J, Lin H, Xu B, Cheng Y. Psychosocial Factors Affecting Artificial Intelligence Adoption in Health Care in China: Cross-Sectional Study. Journal of Medical Internet Research 2019;21(10):e14316
    CrossRef
  10. Tang Y, Yang Y, Shao Y. Acceptance of Online Medical Websites: An Empirical Study in China. International Journal of Environmental Research and Public Health 2019;16(6):943
    CrossRef
  11. Madrigal L, Escoffery C. Electronic Health Behaviors Among US Adults With Chronic Disease: Cross-Sectional Survey. Journal of Medical Internet Research 2019;21(3):e11240
    CrossRef
  12. Ali R, Zhang Z, Soomro MB. Smoking-Cessation Acceptance Via Mobile Health and Quick Response Code Technologies: Empirical Evidence of a Pilot Study from China and Pakistan. Current Psychology 2019;
    CrossRef
  13. Cher BP, Kembhavi G, Toh KY, Audimulam J, Chia WA, Vrijhoef HJM, Lim YW, Lim TW. Understanding attitudes of clinicians and patients towards a self-management e-health tool for atrial fibrillation (AF): a qualitative study (Preprint). JMIR Human Factors 2019;
    CrossRef
  14. Harst L, Lantzsch H, Scheibe M. Theories Predicting End-User Acceptance of Telemedicine Use: Systematic Review. Journal of Medical Internet Research 2019;21(5):e13117
    CrossRef
  15. Onuma AE, Palmer Kelly E, Chakedis J, Paredes AZ, Tsilimigras DI, Wiemann B, Johnson M, Merath K, Akgul O, Cloyd J, Pawlik TM. Patient preferences on the use of technology in cancer surveillance after curative surgery: A cross-sectional analysis. Surgery 2019;165(4):782
    CrossRef
  16. Salgado T, Tavares J, Oliveira T. Drivers of Mobile Health Acceptance and Use: A Patient Perspective (Preprint). JMIR mHealth and uHealth 2019;
    CrossRef
  17. Balapour A, Reychav I, Sabherwal R, Azuri J. Mobile technology identity and self-efficacy: Implications for the adoption of clinically supported mobile health apps. International Journal of Information Management 2019;49:58
    CrossRef
  18. Ali R, Zhang Z, Bux Soomro M. Smoking-cessation acceptance via mobile health. Human Systems Management 2019;38(3):313
    CrossRef
  19. Chen J, Allman-Farinelli M. Impact of Training and Integration of Apps Into Dietetic Practice on Dietitians’ Self-Efficacy With Using Mobile Health Apps and Patient Satisfaction. JMIR mHealth and uHealth 2019;7(3):e12349
    CrossRef
  20. Apolinário-Hagen J, Menzel M, Hennemann S, Salewski C. Acceptance of Mobile Health Apps for Disease Management Among People With Multiple Sclerosis: Web-Based Survey Study. JMIR Formative Research 2018;2(2):e11977
    CrossRef
  21. Melchiorre MG, Lamura G, Barbabella F, MacLure K. eHealth for people with multimorbidity: Results from the ICARE4EU project and insights from the “10 e’s” by Gunther Eysenbach. PLOS ONE 2018;13(11):e0207292
    CrossRef

According to Crossref, the following books are citing this article (DOI 10.2196/mhealth.7886)

:
  1. Lee DC, Gefen D. Impacts of Information Technology on Patient Care and Empowerment. 2020. chapter 12:219
    CrossRef
  2. Yu P, Zhu Y, Halim UZ, Hailey D. Encyclopedia of Gerontology and Population Aging. 2019. Chapter 440-1:1
    CrossRef