Examining construct and predictive validity of the Health-IT Usability Evaluation Scale: confirmatory factor analysis and structural equation modeling results
Open accessAbstract
BACKGROUND: In a previous study, we developed the Health Information Technology Usability Evaluation Scale (Health-ITUES), which is designed to support customization at the item level. Such customization matches the specific tasks/expectations of a health IT system while retaining comparability at the construct level, and provides evidence of its factorial validity and internal consistency reliability through exploratory factor analysis. OBJECTIVE: In this study, we advanced the development of Health-ITUES to examine its construct validity and predictive validity. METHODS: The health IT system studied was a web-based communication system that supported nurse staffing and scheduling. Using Health-ITUES, we conducted a cross-sectional study to evaluate users' perception toward the web-based communication system after system implementation. We examined Health-ITUES's construct validity through first and second order confirmatory factor analysis (CFA), and its predictive validity via structural equation modeling (SEM). RESULTS: The sample comprised 541 staff nurses in two healthcare organizations. The CFA (n=165) showed that a general usability factor accounted for 78.1%, 93.4%, 51.0%, and 39.9% of the explained variance in 'Quality of Work Life', 'Perceived Usefulness', 'Perceived Ease of Use', and 'User Control', respectively. The SEM (n=541) supported the predictive validity of Health-ITUES, explaining 64% of the variance in intention for system use. CONCLUSIONS: The results of CFA and SEM provide additional evidence for the construct and predictive validity of Health-ITUES. The customizability of Health-ITUES has the potential to support comparisons at the construct level, while allowing variation at the item level. We also illustrate application of Health-ITUES across stages of system development.
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In the original Health ITUES and the modified version for mHealth apps, several statements need to be customized by the questionnaire user.
“In the original Health ITUES and the modified version for mHealth apps, several statements need to be customized by the questionnaire user [12,22].”
From The mHealth App Usability Questionnaire (MAUQ): Development and Validation Study (2019) · cites this paper as [22]
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The mHealth App Usability Questionnaire (MAUQ): Development and Validation Study
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- Authors
- Yen, P.-Y., Sousa, K. H., & Bakken, S.
- Affiliations
- The Ohio State University (US)
- Corresponding author
- Yen, P.-Y.
- ORCID
- Sousa, K. H.
- Venue
- Journal of the American Medical Informatics Association
- Publisher
- Oxford University Press (OUP)
- Published
- 2014-10-01
- Volume
- 21
- Issue
- e2
- Pages
- e241-e248
- ISSN
- 1067-5027 (ISSN-L)
- 1527-974X
- PMC
- PMC4173162
- OpenAlex
- W2207580776
- Cited by
- 75
- References
- 11
- Citations by year
- 2026: 6 · 2025: 4 · 2024: 11 · 2023: 12 · 2022: 8 · 2021: 6 · 2020: 4 · 2019: 7 · 2018: 5 · 2017: 3 · 2016: 6 · 2015: 2 · 2014: 1
- FWCI
- 7.49
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Journal of the American Medical Informatics Association (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institute of Nursing Research (P30NR010677)
- Topics
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
- Physical Sciences › Computer Science › Human-Computer Interaction › Usability and User Interface Design
- Keywords
- construct validity, predictive validity, web-based communication system, perceived usefulness, perceived ease of use, user control, quality of work life, intention to use, staff nurses
- MeSH terms
- Attitude of Health Personnel, Cross-Sectional Studies, Evaluation Studies as Topic, Factor Analysis, Statistical, Humans, Medical Informatics, Models, Theoretical, Nursing Staff, Surveys and Questionnaires, Reproducibility of Results
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