Literature DB >> 30112741

A Systematic Review of the Technology Acceptance Model in Health Informatics.

Bahlol Rahimi1, Hamed Nadri1,2, Hadi Lotfnezhad Afshar1, Toomas Timpka3,4.   

Abstract

BACKGROUND: One common model utilized to understand clinical staff and patients' technology adoption is the technology acceptance model (TAM).
OBJECTIVE: This article reviews published research on TAM use in health information systems development and implementation with regard to application areas and model extensions after its initial introduction.
METHOD: An electronic literature search supplemented by citation searching was conducted on February 2017 of the Web of Science, PubMed, and Scopus databases, yielding a total of 492 references. Upon eliminating duplicates and applying inclusion and exclusion criteria, 134 articles were retained. These articles were appraised and divided into three categories according to research topic: studies using the original TAM, studies using an extended TAM, and acceptance model comparisons including the TAM.
RESULTS: The review identified three main information and communication technology (ICT) application areas for the TAM in health services: telemedicine, electronic health records, and mobile applications. The original TAM was found to have been extended to fit dynamic health service environments by integration of components from theoretical frameworks such as the theory of planned behavior and unified theory of acceptance and use of technology, as well as by adding variables in specific contextual settings. These variables frequently reflected the concepts subjective norm and self-efficacy, but also compatibility, experience, training, anxiety, habit, and facilitators were considered.
CONCLUSION: Telemedicine applications were between 1999 and 2017, the ICT application area most frequently studied using the TAM, implying that acceptance of this technology was a major challenge when exploiting ICT to develop health service organizations during this period. A majority of the reviewed articles reported extensions of the original TAM, suggesting that no optimal TAM version for use in health services has been established. Although the review results indicate a continuous progress, there are still areas that can be expanded and improved to increase the predictive performance of the TAM. Georg Thieme Verlag KG Stuttgart · New York.

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Year:  2018        PMID: 30112741      PMCID: PMC6094026          DOI: 10.1055/s-0038-1668091

Source DB:  PubMed          Journal:  Appl Clin Inform        ISSN: 1869-0327            Impact factor:   2.342


  122 in total

1.  Test of the technology acceptance model for the internet in pediatrics.

Authors:  William G Chismar; Sonja Wiley-Patton
Journal:  Proc AMIA Symp       Date:  2002

2.  EHR acceptance factors in ambulatory care: a survey of physician perceptions.

Authors:  Mary E Morton; Susan Wiedenbeck
Journal:  Perspect Health Inf Manag       Date:  2010-01-01

3.  The adoption of mobile health management services: an empirical study.

Authors:  Ming-Chien Hung; Wen-Yuan Jen
Journal:  J Med Syst       Date:  2010-09-29       Impact factor: 4.460

4.  How common are electronic health records in the United States? A summary of the evidence.

Authors:  Ashish K Jha; Timothy G Ferris; Karen Donelan; Catherine DesRoches; Alexandra Shields; Sara Rosenbaum; David Blumenthal
Journal:  Health Aff (Millwood)       Date:  2006-10-11       Impact factor: 6.301

5.  Understanding the mediating effects of relationship quality on technology acceptance: an empirical study of e-appointment system.

Authors:  Shih-Chih Chen; Shih-Chi Liu; Shing-Han Li; David C Yen
Journal:  J Med Syst       Date:  2013-10-19       Impact factor: 4.460

6.  Evaluation of teledermatology adoption by health-care professionals using a modified Technology Acceptance Model.

Authors:  Estibalitz Orruño; Marie Pierre Gagnon; José Asua; Anis Ben Abdeljelil
Journal:  J Telemed Telecare       Date:  2011-08-15       Impact factor: 6.184

7.  A study of factors affecting acceptance of hospital information systems: a nursing perspective.

Authors:  Ju-Ling Hsiao; Hui-Chuan Chang; Rai-Fu Chen
Journal:  J Nurs Res       Date:  2011-06       Impact factor: 1.682

Review 8.  Predicting nurses' use of healthcare technology using the technology acceptance model: an integrative review.

Authors:  Gillian Strudwick
Journal:  Comput Inform Nurs       Date:  2015-05       Impact factor: 1.985

9.  The Impact of National Cultural Differences on Nurses' Acceptance of Hospital Information Systems.

Authors:  Hsien-Cheng Lin
Journal:  Comput Inform Nurs       Date:  2015-06       Impact factor: 1.985

10.  Evaluation of Electronic Prescribing Decision Support System at a Tertiary Care Pediatric Hospital: The User Acceptance Perspective.

Authors:  Abdurahman Omar; Johan Ellenius; Synnöve Lindemalm
Journal:  Stud Health Technol Inform       Date:  2017
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  64 in total

1.  An evaluation of mHealth adoption and health self-management in emerging adulthood.

Authors:  Connor Drake; Meagan Cannady; Kathryn Howley; Christopher Shea; Ralph Snyderman
Journal:  AMIA Annu Symp Proc       Date:  2020-03-04

Review 2.  WhatsApp in mHealth: an overview on the potentialities and the opportunities in medical imaging.

Authors:  Daniele Giansanti
Journal:  Mhealth       Date:  2020-04-05

3.  Timely Data for Targeted Quality Improvement Interventions: Use of a Visual Analytics Dashboard for Bronchiolitis.

Authors:  Gabrielle Hester; Tom Lang; Laura Madsen; Rabindra Tambyraja; Paul Zenker
Journal:  Appl Clin Inform       Date:  2019-03-06       Impact factor: 2.342

4.  Older people and technology: Time to smarten up our act.

Authors:  Hanad Ahmed; Iqraa Haq; Ammar Rahman; Emma Tonner; Rami Abbass; Faraz Sharif; Shad Asinger; Magda Sbai
Journal:  Future Healthc J       Date:  2021-03

Review 5.  Barriers and Benefits of Information Communication Technologies Used by Health Care Aides.

Authors:  Hector Perez; Noelannah Neubauer; Samantha Marshall; Serrina Philip; Antonio Miguel-Cruz; Lili Liu
Journal:  Appl Clin Inform       Date:  2022-03-09       Impact factor: 2.342

6.  Caregiver Expectations of Interfacing With Voice Assistants to Support Complex Home Care: Mixed Methods Study.

Authors:  Ryan Tennant; Sana Allana; Kate Mercer; Catherine M Burns
Journal:  JMIR Hum Factors       Date:  2022-06-30

7.  Ethical, Legal, and Social Implications of Symptom Checker Apps in Primary Health Care (CHECK.APP): Protocol for an Interdisciplinary Mixed Methods Study.

Authors:  Anna-Jasmin Wetzel; Roland Koch; Christine Preiser; Regina Müller; Malte Klemmt; Robert Ranisch; Hans-Jörg Ehni; Urban Wiesing; Monika A Rieger; Tanja Henking; Stefanie Joos
Journal:  JMIR Res Protoc       Date:  2022-05-16

8.  The Determinants of M-Health Adoption in Developing Countries: An Empirical Investigation.

Authors:  Ahmad Alaiad; Mohammad Alsharo; Yazan Alnsour
Journal:  Appl Clin Inform       Date:  2019-10-30       Impact factor: 2.342

9.  The Use of Digital Healthcare Platforms During the COVID-19 Pandemic: the Consumer Perspective.

Authors:  Fawaz Alharbi
Journal:  Acta Inform Med       Date:  2021-03

10.  Insights Into the Older Adults' World: Concepts of Aging, Care, and Using Assistive Technology in Late Adulthood.

Authors:  Wiktoria Wilkowska; Julia Offermann-van Heek; Thea Laurentius; L Cornelius Bollheimer; Martina Ziefle
Journal:  Front Public Health       Date:  2021-07-02
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