The DOI matches its Crossref record; 60 of the 60 references it cites were found in a registry or an index.
Technology Acceptance among Physicians: A New Take on TAM
Abstract
The proliferation of information technology has been a revolutionary force that has increased efficiency and effectiveness in many industries. However, health care organizations, particularly physician practices, are noticeably lagging in the adoption of such technologies. This article provides a systematic review of the literature on physician acceptance of information technology. An overview of the technology acceptance model (TAM) is discussed, and a modified version of this model is proposed. Finally, ideas for testing this new model in a physician setting are presented. By providing a better understanding of physician technology acceptance, this model will inform health care managers about barriers that make physicians hesitant to embrace new technologies designed to increase efficiency and improve quality in a health care setting.
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“Those in health care who advocate the use of TAM commonly point out how different physicians and other health care providers are from the users of IT in other studies of TAM, and how the general health care context differs from that of the industries where TAM originated [30, 32, 58, 61, 96, 98, 100].”
From The Technology Acceptance Model: Its past and its future in health care (2010) · cites this paper as [30]
In the citing paper
“however, most studies conclude that no clear relationships between these characteristics and attitudes could be established [46, 56, 57].”
From Factors that influence the implementation of e-health: a systematic review of systematic reviews (an update) (2016) · cites this paper as [57]
Citations
Cites
User Acceptance of Information Technology: Toward A Unified View1
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003) · MIS Quarterly · doi:10.2307/30036540 · Cited by 45,035
(1980) · Medical Entomology and Zoology · Cited by 25,810
User Acceptance of Computer Technology: A Comparison of Two Theoretical Models
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989) · Management Science · doi:10.1287/mnsc.35.8.982 · Cited by 25,709
A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies
Venkatesh, V., & Davis, F. D. (2000) · Management Science · doi:10.1287/mnsc.46.2.186.11926 · Cited by 23,066
A meta-analysis of the technology acceptance model
King, W. R., & He, J. (2006) · Information & Management · doi:10.1016/j.im.2006.05.003 · Cited by 2,906
(1984) · PubMed · Cited by 2,436
Examining the technology acceptance model using physician acceptance of telemedicine technology
Hu, P. J., Chau, P. Y. K., Sheng, O. R. L., & Tam, K. Y. (1999) · Journal of Management Information Systems · doi:10.1080/07421222.1999.11518247 · Cited by 1,951
Information technology acceptance by individual professionals: a model comparison approach
Chau, P. Y. K., & Hu, P. J. (2001) · Decision Sciences · doi:10.1111/j.1540-5915.2001.tb00978.x · Cited by 1,409
Testing the technology acceptance model across cultures: A three country study
Straub, D., Keil, M., & Brenner, W. (1997) · Information & Management · doi:10.1016/s0378-7206(97)00026-8 · Cited by 1,246
Chau, P. Y. K., & Hu, P. J. (2002) · Information & Management · doi:10.1016/s0378-7206(01)00098-2 · Cited by 1,145
Research works printed but not linked: 20
- Al-Gahtani, S., 2001, Management Journal, 14, 37
- Amoako-Gyampah, K., 2004, Management, 41, 731
- Ash, J.S., 2004, Journal of the American Medical Informatics Association, 11
- Audet, A., 2004, Medicine, 6, 2
- Burton-Jones, A., 2006, Management, 43, 706
- Hu, P., 1999, Systems, 16, 91
- Hwang, Y., 2005, Journal of Information Systems, 14, 150
- Karsh, B.T., 2006, Ergonomics, 37, 283
- King, W.R., 2006, Management, 43, 740
- Kohn L. T., 1999, To err is human: Building a safer health system. Executive summary
- Lai, V.S., 2005, Management, 42, 373
- Lee, S., 2006, Management, 43, 469
- Liu, L., 2005, Management, 43, 1121
- Mathieson, K., 2001, Systems, 32, 86
- Meyers, S., 2003, Trustee, 56, 13
- Rose, G., 1989, Information Management, 6, 39
- Yang, H., 2004, Systems, 8, 19
- Yi, M.Y., 2006, Management, 43, 350
- Yu, J., 2005, Management, 42, 965
- Zhang, X., 2006, Management Journal, 19, 54
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Wright, E. W., & Marvel, J. (2012) · The Health Care Manager · doi:10.1097/hcm.0b013e3182619e90 · Cited by 20
Kalkhoran, S. M., Appelle, N., Nápoles, A. M., Muñoz, R. F., Lum, P. J., Alvarado, N. J., Gregorich, S. E., & Satterfield, J. M. (2015) · Journal of Substance Abuse Treatment · doi:10.1016/j.jsat.2015.05.009 · Cited by 20
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Smith, T., Grant, G. G., & Ramirez, A. (2014) · Hawaii International Conference on System Sciences (HICSS) · doi:10.1109/hicss.2014.351 · Cited by 20
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Liu, J., Zhang, N., & Yang, Y. (2024) · Heliyon · doi:10.1016/j.heliyon.2024.e30350 · Cited by 22
Metadata
- Authors
- Yarbrough, A. K., & Smith, T. B.
- Affiliations
- University of Florida (US)
- University of Alabama at Birmingham (US)
- Corresponding author
- Yarbrough, Amy K.
- ORCID
- Smith, Todd B.
- Venue
- Medical Care Research and Review
- Publisher
- SAGE Publications
- Published
- 2007-12
- Volume
- 64
- Issue
- 6
- Pages
- 650-672
- ISSN
- 1077-5587 (ISSN-L)
- 1552-6801
- OpenAlex
- W2047540630
- Semantic Scholar
- a1690fa95a5606c43985889bdb0affe3764e5416
- Cited by
- 482
- References
- 60
- Citations by year
- 2026: 13 · 2025: 21 · 2024: 25 · 2023: 21 · 2022: 21 · 2021: 32 · 2020: 35 · 2019: 34 · 2018: 36 · 2017: 22 · 2016: 23 · 2015: 37 · 2014: 31 · 2013: 36 · 2012: 30
- FWCI
- 26.52
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Medical Care Research and Review (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
- Social Sciences › Business, Management and Accounting › Management Information Systems › Information Systems Theories and Implementation
- Keywords
- technology acceptance, physicians, information technology adoption, technology acceptance model, physician practice, health information technology, technology adoption barriers, health care efficiency, quality of care
- MeSH terms
- Attitude to Computers, Diffusion of Innovation, Humans, Models, Theoretical, Physicians
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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