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.
250 related articles for article (PubMed ID: 25937699)
1. Bridging the Divide: Using UTAUT to predict multigenerational tablet adoption practices. Magsamen-Conrad K; Upadhyaya S; Joa CY; Dowd J Comput Human Behav; 2015 Sep; 50():186-196. PubMed ID: 25937699 [TBL] [Abstract][Full Text] [Related]
2. 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]
3. Patients' intention to use online postings of ED wait times: A modified UTAUT model. Jewer J Int J Med Inform; 2018 Apr; 112():34-39. PubMed ID: 29500019 [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. Using the UTAUT model to understand students' usage of e-learning systems in developing countries. Abbad MMM Educ Inf Technol (Dordr); 2021; 26(6):7205-7224. PubMed ID: 34025204 [TBL] [Abstract][Full Text] [Related]
6. What factors determine therapists' acceptance of new technologies for rehabilitation – a study using the Unified Theory of Acceptance and Use of Technology (UTAUT). Liu L; Miguel Cruz A; Rios Rincon A; Buttar V; Ranson Q; Goertzen D Disabil Rehabil; 2015; 37(5):447-55. PubMed ID: 24901351 [TBL] [Abstract][Full Text] [Related]
7. Predictors of Health Care Practitioners' Intention to Use AI-Enabled Clinical Decision Support Systems: Meta-Analysis Based on the Unified Theory of Acceptance and Use of Technology. Dingel J; Kleine AK; Cecil J; Sigl AL; Lermer E; Gaube S J Med Internet Res; 2024 Aug; 26():e57224. PubMed ID: 39102675 [TBL] [Abstract][Full Text] [Related]
8. Acceptance of Mobile Health Applications: Examining Key Determinants and Moderators. Nunes A; Limpo T; Castro SL Front Psychol; 2019; 10():2791. PubMed ID: 31920836 [TBL] [Abstract][Full Text] [Related]
9. Factors Determining the Behavioral Intention to Use Mobile Learning: An Application and Extension of the UTAUT Model. Chao CM Front Psychol; 2019; 10():1652. PubMed ID: 31379679 [TBL] [Abstract][Full Text] [Related]
10. Assessing AI adoption in developing country academia: A trust and privacy-augmented UTAUT framework. Rana MM; Siddiqee MS; Sakib MN; Ahamed MR Heliyon; 2024 Sep; 10(18):e37569. PubMed ID: 39315142 [TBL] [Abstract][Full Text] [Related]
11. Understanding consumer acceptance of healthcare wearable devices: An integrated model of UTAUT and TTF. Wang H; Tao D; Yu N; Qu X Int J Med Inform; 2020 Jul; 139():104156. PubMed ID: 32387819 [TBL] [Abstract][Full Text] [Related]
12. Determining Acceptance of e-Mental Health Interventions in Digital Psychodiabetology Using a Quantitative Web-Based Survey: Cross-sectional Study. Damerau M; Teufel M; Musche V; Dinse H; Schweda A; Beckord J; Steinbach J; Schmidt K; Skoda EM; Bäuerle A JMIR Form Res; 2021 Jul; 5(7):e27436. PubMed ID: 34328429 [TBL] [Abstract][Full Text] [Related]
13. Predicting Acceptance of e-Mental Health Interventions in Patients With Obesity by Using an Extended Unified Theory of Acceptance Model: Cross-sectional Study. Rentrop V; Damerau M; Schweda A; Steinbach J; Schüren LC; Niedergethmann M; Skoda EM; Teufel M; Bäuerle A JMIR Form Res; 2022 Mar; 6(3):e31229. PubMed ID: 35297769 [TBL] [Abstract][Full Text] [Related]
14. 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]
15. Factors That Influence the Intention of Smallholder Rice Farmers to Adopt Cleaner Production Practices: An Empirical Study of Precision Agriculture Adoption. Nguyen LLH; Khuu DT; Halibas A; Nguyen TQ Eval Rev; 2024 Aug; 48(4):692-735. PubMed ID: 37678818 [TBL] [Abstract][Full Text] [Related]
16. Assessing Older Adults' Intentions to Use a Smartphone: Using the Meta-Unified Theory of the Acceptance and Use of Technology. Yang CC; Li CL; Yeh TF; Chang YC Int J Environ Res Public Health; 2022 Apr; 19(9):. PubMed ID: 35564798 [TBL] [Abstract][Full Text] [Related]
17. A priori acceptance of highly automated cars in Australia, France, and Sweden: A theoretically-informed investigation guided by the TPB and UTAUT. Kaye SA; Lewis I; Forward S; Delhomme P Accid Anal Prev; 2020 Mar; 137():105441. PubMed ID: 32007779 [TBL] [Abstract][Full Text] [Related]
18. Using the Unified Theory of Acceptance and Use of Technology (UTAUT) to Investigate the Intention to Use Physical Activity Apps: Cross-Sectional Survey. Liu D; Maimaitijiang R; Gu J; Zhong S; Zhou M; Wu Z; Luo A; Lu C; Hao Y JMIR Mhealth Uhealth; 2019 Aug; 7(9):e13127. PubMed ID: 31507269 [TBL] [Abstract][Full Text] [Related]
19. Predicting Patients' Intention to Use a Personal Health Record Using an Adapted Unified Theory of Acceptance and Use of Technology Model: Secondary Data Analysis. Yousef CC; Salgado TM; Farooq A; Burnett K; McClelland LE; Thomas A; Alenazi AO; Abu Esba LC; AlAzmi A; Alhameed AF; Hattan A; Elgadi S; Almekhloof S; AlShammary MA; Alanezi NA; Alhamdan HS; Khoshhal S; DeShazo JP JMIR Med Inform; 2021 Aug; 9(8):e30214. PubMed ID: 34304150 [TBL] [Abstract][Full Text] [Related]
20. The Role of Ageism in the Acceptance and Use of Digital Technology. Mannheim I; Varlamova M; van Zaalen Y; Wouters EJM J Appl Gerontol; 2023 Jun; 42(6):1283-1294. PubMed ID: 36917039 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]