Validity and reliability of the Norwegian version of the eHealth Literacy Scale (eHEALS) among patients after percutaneous coronary intervention
Notice bibliographique
Résumé
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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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,007 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».