ArticleFrontiers in global women's health2026
Construct validation of HER-WELL: a bifactor exploratory structural equation modeling evaluation of an eight-domain wellness scale for women.
Article in Frontiers in global women's health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Toward the HER-WELL Framework: A Qualitative Mind-Map Study of Wellness Dimensions Among Women in Saudi Arabia.Journal of multidisciplinary healthcare · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Wellness is a multidimensional latent construct whose valid assessment requires psychometrically robust, culturally adapted instruments; however, existing scales have been predominantly developed in Western contexts and remain inadequate for capturing the gendered and sociocultural dimensions of women's wellness in non-Western settings. This study aimed to develop and psychometrically validate the HER-WELL scale, a culturally adapted multidimensional measure of holistic wellness for Saudi women. Methods: Scale development followed Boateng et al.'s (2018) framework, and construct validity was tested in RStudio and Mplus by comparing six measurement models (final CFA, ESEM, second-order CFA, bifactor CFA, second-order ESEM, bifactor ESEM) estimated with robust WLSMV and TARGET rotation in a stratified community sample of Saudi women (N = 1,068; 531 employed, 537 non-employed), with model fit (CFI, TLI, RMSEA, SRMR) evaluated against conventional and Dynamic Fit Index cutoffs. Results: HER-WELL items showed adequate variability, with the highest endorsement for Home Environment, social, and spiritual wellness and the lowest for physical wellness. Across employed, non-employed, and full samples, bifactor ESEM consistently provided the best representation of the data, with excellent fit (CFI ≈.99, TLI ≈.98, RMSEA ≈.03, SRMR ≈.02) that exceeded both conventional and DFI-tailored cutoffs. This structure supported a strong general women's wellness factor, with Physical, Financial, Mental, and Occupational wellness retaining sufficient domain-specific variance, while Emotional, Social, Spiritual, and Home Environmental wellness were more strongly saturated by the general factor and are best interpreted as expressions of overall wellness. Internal consistency was acceptable for most domains ( Conclusion: ER-WELL demonstrates strong psychometric properties as a culturally validated measure of holistic wellness for Saudi women. The bifactor ESEM solution supports the simultaneous use of overall wellness scores alongside domain-specific profiles for Physical, Financial, Mental, and Occupational wellness for research, surveillance, and intervention evaluation in Saudi Arabia and similar Arab and Muslim-majority contexts.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.