Literature DB >> 17049917

Key functional characteristics in designing and operating health information websites for user satisfaction: an application of the extended technology acceptance model.

Dohoon Kim1, Hyejung Chang.   

Abstract

OBJECTIVE: With growing demand for health information and rapid development of information technology, health information websites are emerging as the most effective media to meet the public's needs for health information. This article is intended to offer a technical view on the design and operations of health information websites. Along this line, employed here is the Technology Acceptance Model (TAM), which has been widely used to predict user acceptance based on Perceived Ease-of-Use (PEOU) and Perceived Usefulness (PU).
METHODS: We extend the original TAM by including some exogenous variables since it is necessary to understand the role of the antecedents of acceptance constructs when designing an effective health information website for improving user satisfaction. This study focuses on identifying the core functional factors in designing and operating health information websites. Conducted are some multivariate statistical analyses based on data from an extensive survey.
RESULTS: The results from the structural equation analysis suggest that functional characteristics should be categorized into three groups: one affecting PU and PEOU, another affecting only PEOU, and the other having no direct effect on either PU or PEOU. In particular, 'usage support' and 'customization' are two key functional characteristics in the extended TAM framework for health information websites.
CONCLUSION: Contrary to expectations, however, the direct effect of PEOU on usage support is hardly observed, which differentiates health information websites from other commercial websites like online shopping malls. As a result, understanding the antecedents of PU takes on more significance.

Entities:  

Mesh:

Year:  2006        PMID: 17049917     DOI: 10.1016/j.ijmedinf.2006.09.001

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


  28 in total

1.  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

2.  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

3.  Predicting continuance-findings from a longitudinal study of older adults using an eHealth newsletter.

Authors:  Heather A Forquer; John L Christensen; Andy S L Tan
Journal:  Health Commun       Date:  2014-01-21

4.  The Neighborhood Voice: evaluating a mobile research vehicle for recruiting African Americans to participate in cancer control studies.

Authors:  Kassandra I Alcaraz; Nancy L Weaver; Elena M Andresen; Kara Christopher; Matthew W Kreuter
Journal:  Eval Health Prof       Date:  2011-03-16       Impact factor: 2.651

5.  A qualitative framework to assess hospital / medical websites.

Authors:  Vahid Rafe; Maryam Monfaredzadeh
Journal:  J Med Syst       Date:  2011-08-27       Impact factor: 4.460

6.  Determining patient preferences for remote monitoring.

Authors:  Nuri Basoglu; Tugrul U Daim; Umit Topacan
Journal:  J Med Syst       Date:  2010-10-13       Impact factor: 4.460

Review 7.  The technology acceptance model: its past and its future in health care.

Authors:  Richard J Holden; Ben-Tzion Karsh
Journal:  J Biomed Inform       Date:  2009-07-15       Impact factor: 6.317

8.  Design simplicity influences patient portal use: the role of aesthetic evaluations for technology acceptance.

Authors:  Allison J Lazard; Ivan Watkins; Michael S Mackert; Bo Xie; Keri K Stephens; Heidi Shalev
Journal:  J Am Med Inform Assoc       Date:  2015-12-03       Impact factor: 4.497

9.  Hospital-based nurses' perceptions of the adoption of Web 2.0 tools for knowledge sharing, learning, social interaction and the production of collective intelligence.

Authors:  Adela S M Lau
Journal:  J Med Internet Res       Date:  2011-11-11       Impact factor: 5.428

10.  Gender Differences in Searching for Health Information on the Internet and the Virtual Patient-Physician Relationship in Germany: Exploratory Results on How Men and Women Differ and Why.

Authors:  Sonja Bidmon; Ralf Terlutter
Journal:  J Med Internet Res       Date:  2015-06-22       Impact factor: 5.428

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