Research evidence shows that health literacy development is a key factor influencing non-communicable diseases care and patient outcomes. Healthcare professionals with strong health literacy skills are essential for providing quality care. We aimed to report the validation testing of the Health Literacy Questionnaire (HLQ) among health professional students in Nepal. A cross-sectional study was conducted with 419 health sciences students using the HLQ in Nepal. Validation testing and reporting were conducted using five sources outlined by ‘the 2014 Standards for Educational and Psychological Testing’. The average difficulty was lowest (17.4%) for Scale 4. Social support for health, and highest (51.9%) for Scale 6. Ability to actively engage with healthcare providers. One factor Confirmatory Factor Analysis (CFA) model showed a good fit for Scale 2, Scale 7 and Scale 9 and a reasonable fit for Scale 3 and Scale 4. The restricted nine-factor CFA model showed a satisfactory level of fit. The use of HLQ is seen to be meaningful in Nepal and warrants translation into native Nepali and other dominant local languages with careful consideration of cultural appropriateness using cognitive interviews.

Background: Contrary to common usage in the health sciences, the term “valid” refers not to the properties of a measurement instrument but to the extent to which data-derived inferences are appropriate, meaningful, and useful for intended decision making. The aim of this study was to determine how validity testing theory (the Standards for Educational and Psychological Testing) and methodology (Kane’s argument-based approach to validation) from education and psychology can be applied to validation practices for patient-reported outcomes that are measured by instruments that assess theoretical constructs in health. Methods: The Health Literacy Questionnaire (HLQ) was used as an example of a theory-based self-report assessment for the purposes of this study. Kane’s five inferences (scoring, generalisation, extrapolation, theory-based interpretation, and implications) for theoretical constructs were applied to the general interpretive argument for the HLQ. Existing validity evidence for the HLQ was identified and collated (as per the Standards recommendation) through a literature review and mapped to the five inferences. Evaluation of the evidence was not within the scope of this study. Results: The general HLQ interpretive argument was built to demonstrate Kane’s five inferences (and associated warrants and assumptions) for theoretical constructs, and which connect raw data to the intended interpretation and use of the data. The literature review identified 11 HLQ articles from which 57 sources of validity evidence were extracted and mapped to the general interpretive argument. Conclusions: Kane’s five inferences and associated warrants and assumptions were demonstrated in relation to the HLQ. However, the process developed in this study is likely to be suitable for validation planning for other measurement instruments. Systematic and transparent validation planning and the generation (or, as in this study, collation) of relevant validity evidence supports developers and users of PRO instruments to determine the extent to which inferences about data are appropriate, meaningful and useful (i.e., valid) for intended decisions about the health and care of individuals, groups and populations.

Rapid growth in digital health technologies has increased demand for eHealth literacy of all stakeholders within health and social care environments. The digital future of health care services requires the next generation of health professionals to be well-prepared to confidently provide high-quality and safe health care. The aim of this study was to explore the eHealth literacy of undergraduate health profession students to inform undergraduate curriculum development to promote work-readiness. A cross-sectional survey was undertaken at an Australian university using the seven-domain eHealth Literacy Questionnaire (eHLQ), with 610 students participating. A one-way Multivariate Analysis of Variance (MANOVA) with follow-up univariate analysis (ANOVA) was used to determine if there were differences in eHLQ scores across 11 sociodemographic variables. Students generally had good knowledge of health (Scale 2); however, they had concerns over the security of online health data (Scale 4). There were also significant differences in age and ownership of digital devices. Students who were younger reported higher scores across all seven eHLQ scales than older students. This research provided an understanding of eHealth literacy of health profession students and revealed sub-groups that have lower eHealth literacy, suggesting that digital health skills should be integrated into university curriculums, especially related to practice-based digital applications with special focus to address privacy and security concerns. Preparation of health profession students so they can efficiently address their own needs, and the needs of others, is recommended to minimise the digital divide within health and social care environments.

Background: Health literacy is considered a determinant of self-management behaviors and health outcomes among people with diabetes. The assessment of health literacy is central to understanding the health needs of a population. This study aimed to adapt the Health Literacy Questionnaire (HLQ) to the Portuguese context and to examine the psychometric properties of a population of people with diabetes. Methods: Data were collected using a self-administrated questionnaire from 453 people with diabetes in a specialized diabetes care unit. Analysis included item difficulty level, composite scale reliability, and confirmatory factor analysis (CFA). Results: The HLQ showed that the items were easily understood by participants. Composite reliability ranged from 0.74 to 0.83. A nine-factor CFA model was fitted to the 44 items. Given the very restricted model, the fit was quite satisfactory [χ²_wlsmv = 2147.3 (df = 866), p = 0.001; CFI = 0.931, TLI = 0.925, RMSEA = 0.057 (90% C.I. 0.054–0.060), and WRMR = 1.528]. Conclusion: The Portuguese version of the HLQ has shown satisfactory psychometric properties across its nine separate scales in people with diabetes. Given the strong observed properties of the HLQ across cultures, languages, and diseases, the HLQ is likely to be a useful tool in a range of Portuguese settings.

Objectives: Self-report measures of health literacy frequently encompass a group of conceptually distinct but related domains scored as either a single scale or separately for each domain. Psychometric studies of the 44-item Health Literacy Questionnaire, scored as nine separate scales, typically report the results of correlated factors confirmatory factor analyses as validity evidence. However, some scales are quite strongly correlated, raising the question of whether there is sufficient discriminant validity to warrant separate scoring. This psychometric study aims to contrast the results of fitting higher-order and bifactor models as alternative options to illuminate the issue. Methods: Correlated factors, higher-order and bifactor confirmatory factor analysis models were fitted to an Australian sample of responses to the Health Literacy Questionnaire (N = 813) using Bayesian confirmatory factor analysis methods. Results: All models representing a nine-factor structure for the Health Literacy Questionnaire fitted well. The correlated factors model replicated previous findings, showing inter-factor correlations between 0.19 and 0.93. A higher-order model showed relatively high loadings of all nine first-order factors on the second-order factor with particularly high loadings (⩾0.97) for three. Two bifactor models showed that the majority of Health Literacy Questionnaire items were multifactorial, each containing systematic variance from both a General Health Literacy factor and a domain-specific factor. Seven items from four scales were identified as strongly associated with the General Health Literacy factor, with item content suggesting that this factor indexes a broad sense of agency and efficacy in interacting with health-related information and healthcare providers. Conclusion: Contrasting correlated factors, higher-order and bifactor models fitted to the Health Literacy Questionnaire suggest that constituent items in self-report health literacy questionnaires might be anticipated to represent at least two sources of reliable and substantive common factor variance: variance associated with General Health Literacy and variance associated with a more specific domain, suggesting that items may be ‘irreducibly’ heterogeneous. Implications for test development and validation practice are discussed.