Literature DB >> 19940621

Factors of adoption of mobile information technology by homecare nurses: a technology acceptance model 2 approach.

Huiying Zhang1, Mihail Cocosila, Norm Archer.   

Abstract

Pervasive healthcare support through mobile information technology solutions is playing an increasing role in the attempt to improve healthcare and reduce costs. Despite the apparent attractiveness, many mobile applications have failed or have not been implemented as predicted. Among factors possibly leading to such outcomes, technology adoption is a key problem. This must be investigated early in the development process because healthcare is a particularly sensitive area with vital social implications. Moreover, it is important to investigate technology acceptance using the support of scientific tools validated for relevant information systems research. This article presents an empirical study based on the Technology Acceptance Model 2 in mobile homecare nursing. The study elicited the perceptions of 91 Canadian nurses who used personal digital assistants for 1 month in their daily activities. A partial least squares modeling data analysis revealed that nurse's perception of usefulness is the main factor in the adoption of mobile technology, having subjective norm and image within the organization as significant antecedents. Overall, this study was the first attempt at investigating scientifically, through a pertinent information systems research model, user adoption of mobile systems by homecare nursing personnel.

Mesh:

Year:  2010        PMID: 19940621     DOI: 10.1097/NCN.0b013e3181c0474a

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


  24 in total

1.  Testing the Electronic Personal Health Record Acceptance Model by Nurses for Managing Their Own Health: A Cross-sectional Survey.

Authors:  K Gartrell; A M Trinkoff; C L Storr; M L Wilson; A P Gurses
Journal:  Appl Clin Inform       Date:  2015-04-08       Impact factor: 2.342

Review 2.  m-Health adoption by healthcare professionals: a systematic review.

Authors:  Marie-Pierre Gagnon; Patrice Ngangue; Julie Payne-Gagnon; Marie Desmartis
Journal:  J Am Med Inform Assoc       Date:  2015-06-15       Impact factor: 4.497

3.  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

4.  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

5.  Feasibility of a mHealth survey application for incarcerated and postrelease people living with HIV in a low-resource setting.

Authors:  Karen Dunn Lopez; Claire Cravero; Archana Krishnan; Vanessa E Carvalho de Sousa Freire; Gabriel J Culbert
Journal:  Res Nurs Health       Date:  2020-12-20       Impact factor: 2.228

6.  Moderating effects of voluntariness on the actual use of electronic health records for allied health professionals.

Authors:  Teresa Ml Chiu; Benny Ps Ku
Journal:  JMIR Med Inform       Date:  2015-02-10

7.  Factors affecting acceptance of smartphone application for management of obesity.

Authors:  Eunjoo Jeon; Hyeoun-Ae Park
Journal:  Healthc Inform Res       Date:  2015-04-30

8.  Interpretive flexibility in mobile health: lessons from a government-sponsored home care program.

Authors:  Jeppe Agger Nielsen; Lars Mathiassen
Journal:  J Med Internet Res       Date:  2013-10-30       Impact factor: 5.428

9.  Factors of accepting pain management decision support systems by nurse anesthetists.

Authors:  Ju-Ling Hsiao; Wen-Chu Wu; Rai-Fu Chen
Journal:  BMC Med Inform Decis Mak       Date:  2013-01-29       Impact factor: 2.796

10.  Comparative evaluation of different medication safety measures for the emergency department: physicians' usage and acceptance of training, poster, checklist and computerized decision support.

Authors:  Brita Sedlmayr; Andrius Patapovas; Melanie Kirchner; Anja Sonst; Fabian Müller; Barbara Pfistermeister; Bettina Plank-Kiegele; Renate Vogler; Manfred Criegee-Rieck; Hans-Ulrich Prokosch; Harald Dormann; Renke Maas; Thomas Bürkle
Journal:  BMC Med Inform Decis Mak       Date:  2013-07-29       Impact factor: 2.796

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