Literature DB >> 16901749

Mobile computing acceptance factors in the healthcare industry: a structural equation model.

Jen-Her Wu1, Shu-Ching Wang, Li-Min Lin.   

Abstract

OBJECTIVE: This paper presents a revised technology acceptance model to examine what determines mobile healthcare systems (MHS) acceptance by healthcare professionals.
METHOD: Conformation factor analysis was performed to test the reliability and validity of the measurement model. The structural equation modeling technique was used to evaluate the causal model.
RESULTS: The results indicated that compatibility, perceived usefulness and perceived ease of use significantly affected healthcare professional behavioral intent. MHS self-efficacy had strong indirect impact on healthcare professional behavioral intent through the mediators of perceived usefulness and perceived ease of use. Yet, the hypotheses for technical support and training effects on the perceived usefulness and perceived ease of use were not supported.
CONCLUSION: This paper provides initial insights into factors that are likely to be significant antecedents of planning and implementing mobile healthcare to enhance professionals' MHS acceptance. The proposed model variables explained 70% of the variance in behavioral intention to use MHS; further study is needed to explore extra significant antecedents of new IT/IS acceptance for mobile healthcare. Such as privacy and security issue, system and information quality, limitations of mobile devices; the above may be other interesting factors for implementing mobile healthcare and could be conducted by qualitative research.

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Mesh:

Year:  2006        PMID: 16901749     DOI: 10.1016/j.ijmedinf.2006.06.006

Source DB:  PubMed          Journal:  Int J Med Inform        ISSN: 1386-5056            Impact factor:   4.046


  52 in total

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2.  Anticoagulation manager: development of a clinical decision support mobile application for management of anticoagulants.

Authors:  Pamela J Thompson; Julie R Taylor; Barbara A Zehnbauer; Karlyn K Wilson; May D Wang
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2016-08

3.  Adding intelligence to mobile asset management in hospitals: the true value of RFID.

Authors:  Linda Castro; Elisabeth Lefebvre; Louis A Lefebvre
Journal:  J Med Syst       Date:  2013-08-13       Impact factor: 4.460

4.  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

5.  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

6.  Clinical information system post-adoption evaluation at the georges pompidou university hospital.

Authors:  Jean-Marc Palm; Thierry Dart; Isabelle Dupuis; Laurence Leneveut; Patrice Degoulet
Journal:  AMIA Annu Symp Proc       Date:  2010-11-13

7.  Effects of body image on college students' attitudes toward diet/fitness apps on smartphones.

Authors:  Jaehee Cho; H Erin Lee; Sun Jin Kim; Dongjin Park
Journal:  Cyberpsychol Behav Soc Netw       Date:  2015-01

8.  Paediatricians' opinions of microneedle-mediated monitoring: a key stage in the translation of microneedle technology from laboratory into clinical practice.

Authors:  Karen Mooney; James C McElnay; Ryan F Donnelly
Journal:  Drug Deliv Transl Res       Date:  2015-08       Impact factor: 4.617

9.  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

10.  Physiotherapists' and Physiotherapy Students' Perspectives on the Use of Mobile or Wearable Technology in Their Practice.

Authors:  Jenna Blumenthal; Andrea Wilkinson; Mark Chignell
Journal:  Physiother Can       Date:  2018       Impact factor: 1.037

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