These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
151 related articles for article (PubMed ID: 36011615)
1. Determinants of the Mobile Health Continuance Intention of Elders with Chronic Diseases: An Integrated Framework of ECM-ISC and UTAUT. Tian XF; Wu RZ Int J Environ Res Public Health; 2022 Aug; 19(16):. PubMed ID: 36011615 [TBL] [Abstract][Full Text] [Related]
2. Continuous usage intention of mobile health services: model construction and validation. Nie L; Oldenburg B; Cao Y; Ren W BMC Health Serv Res; 2023 May; 23(1):442. PubMed ID: 37143005 [TBL] [Abstract][Full Text] [Related]
3. The Impact of Gamification-Induced Users' Feelings on the Continued Use of mHealth Apps: A Structural Equation Model With the Self-Determination Theory Approach. Wang T; Fan L; Zheng X; Wang W; Liang J; An K; Ju M; Lei J J Med Internet Res; 2021 Aug; 23(8):e24546. PubMed ID: 34387550 [TBL] [Abstract][Full Text] [Related]
4. The Mediating Influence of the Unified Theory of Acceptance and Use of Technology on the Relationship Between Internal Health Locus of Control and Mobile Health Adoption: Cross-sectional Study. Ahadzadeh AS; Wu SL; Ong FS; Deng R J Med Internet Res; 2021 Dec; 23(12):e28086. PubMed ID: 34964718 [TBL] [Abstract][Full Text] [Related]
5. Social Acceptance of Mobile Health among Young Adults in Japan: An Extension of the UTAUT Model. Cao J; Kurata K; Lim Y; Sengoku S; Kodama K Int J Environ Res Public Health; 2022 Nov; 19(22):. PubMed ID: 36429875 [TBL] [Abstract][Full Text] [Related]
6. Determining information system end-user satisfaction and continuance intension with a unified modeling approach. Tessema WM; Cavus N Sci Rep; 2024 Mar; 14(1):6882. PubMed ID: 38519535 [TBL] [Abstract][Full Text] [Related]
7. Understanding Use Intention of mHealth Applications Based on the Unified Theory of Acceptance and Use of Technology 2 (UTAUT-2) Model in China. Zhu Y; Zhao Z; Guo J; Wang Y; Zhang C; Zheng J; Zou Z; Liu W Int J Environ Res Public Health; 2023 Feb; 20(4):. PubMed ID: 36833830 [TBL] [Abstract][Full Text] [Related]
8. Factors influencing the continuance intention of the women's health WeChat public account: an integrated model of UTAUT2 and HBM. Min H; Li J; Di M; Huang S; Sun X; Li T; Wu Y Front Public Health; 2024; 12():1348673. PubMed ID: 38966697 [TBL] [Abstract][Full Text] [Related]
9. Understanding factors influencing the adoption of mHealth by the elderly: An extension of the UTAUT model. Hoque R; Sorwar G Int J Med Inform; 2017 May; 101():75-84. PubMed ID: 28347450 [TBL] [Abstract][Full Text] [Related]
10. Understanding the mobile healthcare applications continuance: The regulatory focus perspective. Han K; Zo H Int J Med Inform; 2023 Sep; 177():105161. PubMed ID: 37544241 [TBL] [Abstract][Full Text] [Related]
11. Influence Mechanism of the Affordances of Chronic Disease Management Apps on Continuance Intention: Questionnaire Study. Liu Y; Jiang F; Lin P JMIR Mhealth Uhealth; 2021 May; 9(5):e21831. PubMed ID: 33983126 [TBL] [Abstract][Full Text] [Related]
12. Effective Factors in Adoption of Mobile Health Applications between Medical Sciences Students Using the UTAUT Model. Garavand A; Samadbeik M; Nadri H; Rahimi B; Asadi H Methods Inf Med; 2019 Nov; 58(4-05):131-139. PubMed ID: 32170717 [TBL] [Abstract][Full Text] [Related]
13. Explaining the Factors Influencing the Individuals' Continuance Intention to Seek Information on Weibo during Rainstorm Disasters. Cheng S; Liu L; Li K Int J Environ Res Public Health; 2020 Aug; 17(17):. PubMed ID: 32825472 [TBL] [Abstract][Full Text] [Related]
14. Healthcare providers' acceptance of telemedicine and preference of modalities during COVID-19 pandemics in a low-resource setting: An extended UTAUT model. Shiferaw KB; Mengiste SA; Gullslett MK; Zeleke AA; Tilahun B; Tebeje T; Wondimu R; Desalegn S; Mehari EA PLoS One; 2021; 16(4):e0250220. PubMed ID: 33886625 [TBL] [Abstract][Full Text] [Related]
15. Understanding Determinants of Health Care Professionals' Perspectives on Mobile Health Continuance and Performance. Hsiao JL; Chen RF JMIR Med Inform; 2019 Mar; 7(1):e12350. PubMed ID: 30882353 [TBL] [Abstract][Full Text] [Related]
16. 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. Zhang Y; Liu C; Luo S; Xie Y; Liu F; Li X; Zhou Z J Med Internet Res; 2019 Aug; 21(8):e15023. PubMed ID: 31411146 [TBL] [Abstract][Full Text] [Related]
17. Acceptance of mHealth Apps for Self-Management Among People with Hypertension. Breil B; Kremer L; Hennemann S; Apolinário-Hagen J Stud Health Technol Inform; 2019 Sep; 267():282-288. PubMed ID: 31483283 [TBL] [Abstract][Full Text] [Related]
18. Factors affecting physicians using mobile health applications: an empirical study. Wu P; Zhang R; Luan J; Zhu M BMC Health Serv Res; 2022 Jan; 22(1):24. PubMed ID: 34983501 [TBL] [Abstract][Full Text] [Related]
19. Identifying major impact factors affecting the continuance intention of mHealth: a systematic review and multi-subgroup meta-analysis. Wang T; Wang W; Liang J; Nuo M; Wen Q; Wei W; Han H; Lei J NPJ Digit Med; 2022 Sep; 5(1):145. PubMed ID: 36109594 [TBL] [Abstract][Full Text] [Related]
20. Understanding the factors of mobile payment continuance intention: empirical test in an African context. Franque FB; Oliveira T; Tam C Heliyon; 2021 Aug; 7(8):e07807. PubMed ID: 34458632 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]