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.
163 related articles for article (PubMed ID: 35610577)
1. Gender differences regarding intention to use mHealth applications in the Dutch elderly population: a cross-sectional study. van Elburg FRT; Klaver NS; Nieboer AP; Askari M BMC Geriatr; 2022 May; 22(1):449. PubMed ID: 35610577 [TBL] [Abstract][Full Text] [Related]
2. The intention to use mHealth applications among Dutch older adults prior and during the COVID pandemic. van Elburg FRT; van de Klundert J; Nieboer AP; Askari M Front Public Health; 2023; 11():1130570. PubMed ID: 37383259 [TBL] [Abstract][Full Text] [Related]
3. Intention to use Medical Apps Among Older Adults in the Netherlands: Cross-Sectional Study. Askari M; Klaver NS; van Gestel TJ; van de Klundert J J Med Internet Res; 2020 Sep; 22(9):e18080. PubMed ID: 32624465 [TBL] [Abstract][Full Text] [Related]
4. Relationship Between Perceived Risks of Using mHealth Applications and the Intention to Use Them Among Older Adults in the Netherlands: Cross-sectional Study. Klaver NS; van de Klundert J; van den Broek RJGM; Askari M JMIR Mhealth Uhealth; 2021 Aug; 9(8):e26845. PubMed ID: 34459745 [TBL] [Abstract][Full Text] [Related]
5. Intention to Use mHealth in Older Adults With Heart Failure. Cajita MI; Hodgson NA; Budhathoki C; Han HR J Cardiovasc Nurs; 2017; 32(6):E1-E7. PubMed ID: 28248747 [TBL] [Abstract][Full Text] [Related]
6. 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]
7. Factors Associated With Intention to Adopt mHealth Apps Among Dementia Caregivers With a Chronic Condition: Cross-sectional, Correlational Study. Mendez KJW; Budhathoki C; Labrique AB; Sadak T; Tanner EK; Han HR JMIR Mhealth Uhealth; 2021 Aug; 9(8):e27926. PubMed ID: 34463637 [TBL] [Abstract][Full Text] [Related]
8. 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]
9. User acceptance of mobile health services from users' perspectives: The role of self-efficacy and response-efficacy in technology acceptance. Zhang X; Han X; Dang Y; Meng F; Guo X; Lin J Inform Health Soc Care; 2017 Mar; 42(2):194-206. PubMed ID: 27564428 [TBL] [Abstract][Full Text] [Related]
10. Toward a Better Understanding of the Intention to Use mHealth Apps: Exploratory Study. Palos-Sanchez PR; Saura JR; Rios Martin MÁ; Aguayo-Camacho M JMIR Mhealth Uhealth; 2021 Sep; 9(9):e27021. PubMed ID: 34499044 [TBL] [Abstract][Full Text] [Related]
11. Assessment of the Intention to Use Mobile Health Applications Using a Technology Acceptance Model in an Israeli Adult Population. Shemesh T; Barnoy S Telemed J E Health; 2020 Sep; 26(9):1141-1149. PubMed ID: 31930955 [No Abstract] [Full Text] [Related]
12. Comprehensive Senior Technology Acceptance Model of Daily Living Assistive Technology for Older Adults With Frailty: Cross-sectional Study. Shin HR; Um SR; Yoon HJ; Choi EY; Shin WC; Lee HY; Kim YS J Med Internet Res; 2023 Apr; 25():e41935. PubMed ID: 37036760 [TBL] [Abstract][Full Text] [Related]
13. Comparison of Mobile Health Technology Use for Self-Tracking Between Older Adults and the General Adult Population in Canada: Cross-Sectional Survey. Jaana M; Paré G JMIR Mhealth Uhealth; 2020 Nov; 8(11):e24718. PubMed ID: 33104517 [TBL] [Abstract][Full Text] [Related]
14. Perceptions and Acceptance of mHealth in Patients With Cardiovascular Diseases: A Cross-Sectional Study. Jiang J; Zhu Q; Zheng Y; Zhu Y; Li Y; Huo Y JMIR Mhealth Uhealth; 2019 Feb; 7(2):e10117. PubMed ID: 30714942 [TBL] [Abstract][Full Text] [Related]
15. Proposing a mobile apps acceptance model for users in the health area: A systematic literature review and meta-analysis. Binyamin SS; Zafar BA Health Informatics J; 2021; 27(1):1460458220976737. PubMed ID: 33438494 [TBL] [Abstract][Full Text] [Related]
16. A study on smart home use intention of elderly consumers based on technology acceptance models. Zhou C; Qian Y; Kaner J PLoS One; 2024; 19(3):e0300574. PubMed ID: 38536849 [TBL] [Abstract][Full Text] [Related]
17. 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]
18. Modeling the adoption of personal health record (PHR) among individual: the effect of health-care technology self-efficacy and gender concern. Dutta B; Peng MH; Sun SL Libyan J Med; 2018 Dec; 13(1):1500349. PubMed ID: 30037314 [TBL] [Abstract][Full Text] [Related]
19. Applying an Extended UTAUT2 Model to Explain User Acceptance of Lifestyle and Therapy Mobile Health Apps: Survey Study. Schomakers EM; Lidynia C; Vervier LS; Calero Valdez A; Ziefle M JMIR Mhealth Uhealth; 2022 Jan; 10(1):e27095. PubMed ID: 35040801 [TBL] [Abstract][Full Text] [Related]
20. 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] [Next] [New Search]