Literature DB >> 25974361

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

Gillian Strudwick1.   

Abstract

The benefits of healthcare technologies can only be attained if nurses accept and intend to fully use them. One of the most common models utilized to understand user acceptance of technology is the Technology Acceptance Model. This model and modified versions of it have only recently been applied in the healthcare literature among nurse participants. An integrative literature review was conducted on this topic. Ovid/MEDLINE, PubMed, Google Scholar, and CINAHL were searched yielding a total of 982 references. Upon eliminating duplicates and applying the inclusion and exclusion criteria, the review included a total of four dissertations, three symposium proceedings, and 13 peer-reviewed journal articles. These documents were appraised and reviewed. The results show that a modified Technology Acceptance Model with added variables could provide a better explanation of nurses' acceptance of healthcare technology. These added variables to modified versions of the Technology Acceptance Model are discussed, and the studies' methodologies are critiqued. Limitations of the studies included in the integrative review are also examined.

Entities:  

Mesh:

Year:  2015        PMID: 25974361     DOI: 10.1097/CIN.0000000000000142

Source DB:  PubMed          Journal:  Comput Inform Nurs        ISSN: 1538-2931            Impact factor:   1.985


  20 in total

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

Authors:  Bahlol Rahimi; Hamed Nadri; Hadi Lotfnezhad Afshar; Toomas Timpka
Journal:  Appl Clin Inform       Date:  2018-08-15       Impact factor: 2.342

2.  Factors Affecting Acceptance of Hospital Information Systems Based on Extended Technology Acceptance Model: A Case Study in Three Paraclinical Departments.

Authors:  Hamed Nadri; Bahlol Rahimi; Hadi Lotfnezhad Afshar; Mahnaz Samadbeik; Ali Garavand
Journal:  Appl Clin Inform       Date:  2018-04-04       Impact factor: 2.342

3.  Nurses' perceptions of a novel health information technology: A qualitative study in the pediatric intensive care unit.

Authors:  Onur Asan; Kathryn E Flynn; Laila Azam; Matthew C Scanlon
Journal:  Int J Hum Comput Interact       Date:  2017-02-10       Impact factor: 3.353

4.  Exploring genetic counselors' perceptions of usefulness and intentions to use refined risk models in clinical care based on the Technology Acceptance Model (TAM).

Authors:  Christopher Heinlen; Shelly R Hovick; Guy N Brock; Brett G Klamer; Amanda Ewart Toland; Leigha Senter
Journal:  J Genet Couns       Date:  2019-03-07       Impact factor: 2.537

5.  Nurses' perceptions, acceptance, and use of a novel in-room pediatric ICU technology: testing an expanded technology acceptance model.

Authors:  Richard J Holden; Onur Asan; Erica M Wozniak; Kathryn E Flynn; Matthew C Scanlon
Journal:  BMC Med Inform Decis Mak       Date:  2016-11-15       Impact factor: 2.796

6.  A qualitative study to identify barriers to deployment and student training in the use of automated external defibrillators in schools.

Authors:  Line Zinckernagel; Carolina Malta Hansen; Morten Hulvej Rod; Fredrik Folke; Christian Torp-Pedersen; Tine Tjørnhøj-Thomsen
Journal:  BMC Emerg Med       Date:  2017-01-19

7.  A Mobile App (BEDSide Mobility) to Support Nurses' Tasks at the Patient's Bedside: Usability Study.

Authors:  Frederic Ehrler; Thomas Weinhold; Jonathan Joe; Christian Lovis; Katherine Blondon
Journal:  JMIR Mhealth Uhealth       Date:  2018-03-21       Impact factor: 4.773

8.  Exploring critical factors influencing nurses' intention to use tablet PC in Patients' care using an integrated theoretical model.

Authors:  Shu-Lung Sun; Hsin-Ginn Hwang; Bireswar Dutta; Mei-Hui Peng
Journal:  Libyan J Med       Date:  2019-12       Impact factor: 1.743

9.  Factors associated with nurses' user resistance to change of electronic health record systems.

Authors:  Younghee Cho; Mihui Kim; Mona Choi
Journal:  BMC Med Inform Decis Mak       Date:  2021-07-17       Impact factor: 2.796

10.  The acceptance of the clinical photographic posture assessment tool (CPPAT).

Authors:  Carole Fortin; Paul van Schaik; Jean-François Aubin-Fournier; Josette Bettany-Saltikov; Jean-Claude Bernard; Debbie Ehrmann Feldman
Journal:  BMC Musculoskelet Disord       Date:  2018-10-12       Impact factor: 2.362

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