Examining E-Loyalty in a Sexual Health Website: Cross-Sectional Study
Notice bibliographique
Résumé
BACKGROUND: Web-based sexual health resources are typically evaluated in terms of their efficacy. Information is lacking about how sexual health promotion websites are perceived and used. It is essential to understand website use to address challenges with adherence and attrition to Web-based health interventions. An existing theoretical framework for examining loyalty to electronic health (eHealth) interventions has been not yet been applied in the context of sexual health promotion nor has the association between e-loyalty and intended intervention efficacy outcomes been investigated. OBJECTIVE: The objectives of this study were to investigate users' loyalty toward a sexual health website (ie, e-loyalty), measure user perceptions of the website, and measure the association between e-loyalty and perceived knowledge increase and intent to change behavior. METHODS: Over 4 months, website users (clients and health care providers) participated in an open, online, cross-sectional survey about their user experiences that measured e-loyalty, user perceptions, and intended website efficacy outcomes. Relationships between user perceptions and e-loyalty were investigated using structural equation modeling (SEM). Associations between e-loyalty and website efficacy outcomes were tested using Spearman rank correlation. RESULTS: A total of 173 participants completed user perception questions and were included in the analysis. E-loyalty was high for both clients and providers and was significantly correlated with clients' perceived knowledge increase (ρ(171)=.30, P<.001), their intent to have safer sex (ρ(171)=.24, P=.01), and their intent to get tested for sexually transmitted infections (ρ(171)=.37, P<.001). The SEM showed that trustworthiness, overall experience, active trust, and effectiveness were directly related to e-loyalty. Finding the website "easy to understand" was significantly related to active trust (ie, participants' willingness to act upon information presented on the website). CONCLUSIONS: E-loyalty may be related to the efficacy of the selected website in improving one's sexual health and was significantly associated with all three intended knowledge and behavioral outcomes. To increase e-loyalty, trustworthiness and active trust are important user perceptions to deliberately engender. Our findings indicate that understanding a website contributes to active trust, thereby highlighting the importance of considering eHealth literacy in designing health promotion websites. Our study confirms the relevance of e-loyalty as an outcome for evaluating the antecedents of the use and efficacy of online public health interventions across disciplines by adapting and validating an existing e-loyalty framework to the field of sexual health promotion. Our findings suggest that e-loyalty is positively associated with measures of website efficacy, including increased knowledge and intent to change behavior. Longitudinal research with larger samples could further investigate the relationships between e-loyalty, website understandability, and outcomes of online health interventions to determine how the manipulation of website characteristics may impact user perceptions and e-loyalty.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,006 | 0,007 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,001 |
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 source (Gemma direct ou Codex distillé), 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 ».