Validity and reliability of the Norwegian version of the eHealth Literacy Scale (eHEALS) among patients after percutaneous coronary intervention
Bibliographic record
Abstract
Abstract Funding Acknowledgements The Western Norway Health Authority. OnBehalf The CONCARD-PCI Investigators Background In recent years an internet-based technology has become an important source for providing health information to patients after an acute cardiac event. Therefore, consideration of patients’ perceived eHealth literacy skills, is crucial for improving patient-centred health information after percutaneous coronary intervention (PCI). Purpose The aim of this study was to translate and adapt the eHealth literacy Scale (eHEALS) to conditions in Norway, and to determine the psychometric properties of the eHEALS in self-report format administered to patients after PCI. Methods The original English version of the eHEALS was translated into Norwegian, following a cross-cultural adaptation process. Further, we set out to determine the reliability (internal consistency, test-retest) and construct validity (structural validity, hypotheses testing and cross-cultural validity). Internal consistency was calculated using Cronbach alpha. Intra-class correlation (ICC) was used to assess test-retest reliability. A confirmatory factor analysis (CFA) was performed for a priori hypotheses 1-, 2- and 3-factor model. Demographic information, health-related internet use, health literacy and health status were collected to correlate with eHEALS scores. Results For the validation, 1695 patients were included after PCI. Mean age was 66 years. Most of the patients were male (78%). Cronbach’s alpha for the eHEALS was >0.999. The corresponding Cronbach’s alpha for the 2-week retest was >0.937. The ICC for eHEALS was 0.605 (95% CI 0.419-0.743, P < 0.001). CFA showed a modest model fit of the 1- and 2-factor model. After modifications in the 3-factor model, all the goodness-of-fit indices indicated a good fit. A weak correlation with age (r=-0.206) was found. Employed and higher educated patients scored higher on the eHEALS: There was a higher eHEALS score for the patients with higher education level compared with those with lower education level (mean difference between 2.24 (P = 0.002) and 4.61 (P < 0.001)), and for the patients who were employed compared to those who were retired (mean difference 2.31, P < 0.001). The eHEALS score was higher among the patients who reported to use the internet to find health information (95% CI -21.40, -17.21 (P < 0.001)). There was a moderate correlation with perceived usefulness (r = 0.587) and importance (r = 0.574) of using the internet for health information. There was a moderate correlation with the health literacy dimensions for appraisal of health information (r= 0.380) and ability to find good health information (r = 0.561). Conclusions The study provides additional information on the psychometric properties of the eHEALS for patients after PCI, suggesting a multidimensional construct rather than unidimensional. The high internal consistency indicated a redundancy of items. Therefore, further validation studies of the eHEALS is required.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".