Psychometric Evaluation of the Persian eHealth Literacy Scale (eHEALS) Among Elder Iranians With Heart Failure
Abstract
The purpose of the present study was to examine the psychometric properties of the eHealth Literacy Scale (eHEALS) using classical test theory and modern test theory among elderly Iranian individuals with heart failure (HF). Individuals with objectively verified HF ( n = 388, 234 males, mean age = 68.9 ± 3.4) completed the (i) eHEALS, (ii) Hospital Anxiety and Depression Scale, (iii) Short Form 12, (iv) 9-item European Heart Failure Self-Care Behavior Scale, and (v) 5-item Medication Adherence Report Scale. Two types of analyses were carried out to evaluate the factorial structure of the eHEALS: (i) confirmatory factor analysis (CFA) in classical test theory and (ii) Rasch analysis in modern test theory. A regression model was constructed to examine the associations between eHEALS and other instruments. CFA supported the one-factor structure of the eHEALS with significant factor loadings for all items. Rasch analysis also supported the unidimensionality of the eHEALS with item fit statistics ranging between 0.5 and 1.5. The eHEALS was significantly associated with all the external criteria. The eHEALS is suitable for health-care providers to assess eHealth literacy for individuals with HF.
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Different subgroups in the present sample (gender and profession group) share the same interpretations toward all the MBI-HSS-MP items.
“no substantial DIF was displayed for any MBI-HSS-MP items, which implies that different subgroups in the present sample (i.e., gender and profession group) share the same interpretations toward all the MBI-HSS-MP items [23, 35].”
From Psychometric properties of the Maslach Burnout Inventory for Medical Personnel (MBI-HSS-MP) (2022) · cites this paper as [35]
The satisfactory psychometric properties of the MBI-HSS-MP are not influenced by the present sample's characteristics.
“reliability findings from the Rasch model indicate that the satisfactory psychometric properties of the MBI-HSS-MP are not influenced by the present sample's characteristics [23, 35].”
From Psychometric properties of the Maslach Burnout Inventory for Medical Personnel (MBI-HSS-MP) (2022) · cites this paper as [35]
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“…of the eHEALS using the following fit indices to indicate acceptable data model fit: a nonsignificant w2 test, a comparative fit index (CFI), a Tucker– Lewis index (TLI) 0.9, a root mean square error of approximation, and a standardized root mean square residual (SRMR) 0.08 (McDonald & Ho, 2002).”
MethodInfluentialeHEALS: The eHealth Literacy Scale
Norman, C. D., & Skinner, H. A. (2006) · Journal of Medical Internet Research · doi:10.2196/jmir.8.4.e27 · Cited by 2,680 · see citing works
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Psychometric properties of the Maslach Burnout Inventory for Medical Personnel (MBI-HSS-MP)
Lin, C.-Y., Alimoradi, Z., Griffiths, M. D., & Pakpour, A. H. (2022) · Heliyon · doi:10.1016/j.heliyon.2022.e08868 · Cited by 103 · see citing works
Self-citationLin, C.-Y., Lin, C.-K., Imani, V., Griffiths, M. D., & Pakpour, A. H. (2020) · International Journal of Mental Health and Addiction · doi:10.1007/s11469-019-00124-y · Cited by 17 · see citing works
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- Authors
- Lin, C.-Y., Broström, A., Griffiths, M. D., & Pakpour, A. H.
- Affiliations
- Hong Kong Polytechnic University (HK)
- Jönköping University (SE)
- Nottingham Trent University (GB)
- Qazvin University of Medical Sciences (IR)
- Corresponding author
- Pakpour, Amir H.
- Venue
- Evaluation & the Health Professions
- Publisher
- SAGE Publications
- Published
- 2019-02-11
- Volume
- 43
- Issue
- 4
- Pages
- 222-229
- ISSN
- 0163-2787 (ISSN-L)
- 1552-3918
- OpenAlex
- W2910269512
- Cited by
- 80
- References
- 6
- Citations by year
- 2026: 5 · 2025: 9 · 2024: 12 · 2023: 17 · 2022: 17 · 2021: 12 · 2020: 3 · 2019: 5
- FWCI
- 12.67
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Evaluation & the Health Professions (publishedVersion)
- PubMed (publishedVersion)
- Nottingham Trent University's Institutional Repository (Nottingham Trent Repository) (acceptedVersion)
- Topics
- Health Sciences › Health Professions › General Health Professions › Health Literacy and Information Accessibility
- Social Sciences › Demography › Technology Use by Older Adults
- Social Sciences › Education › Health Education and Validation
- Keywords
- digital health literacy, eHealth Literacy Scale, heart failure, older adults, Persian translation, psychometric validation, Rasch analysis, confirmatory factor analysis, unidimensionality, medication adherence, self-care behavior, anxiety and depression, health-related quality of life
- MeSH terms
- Aged, Heart Failure, Humans, Iran, Male, Psychometrics, Surveys and Questionnaires, Reproducibility of Results, Telemedicine, Health Literacy
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