The Role of Age, Education, and Digital Health Literacy in the Usability of Internet-Based Cognitive Behavioral Therapy for Chronic Pain: Mixed Methods Study
Notice bibliographique
Résumé
BACKGROUND: Internet-based cognitive behavior therapy (iCBT) can be effective in mental and somatic health care. Research on the feasibility of internet interventions in clinical practice is, however, still scarce. Studies with a focus on the patient regarding usability of interventions and digital health literacy skills are especially lacking. OBJECTIVE: The goal of this study was to assess the usability of an iCBT for chronic pain, Master Your Pain, and the relationship between its usability outcomes and the factors age, educational level, and digital health literacy skills. The aims were to determine what changes were needed in the program for sufficient usability and which individual characteristics were related to the usability of the program. METHODS: Patients were recruited from two mental health care practices. A mixed methods approach was used in this study. A qualitative observational study comprising performance tasks in the iCBT program was used to test usability. A quantitative questionnaire was used to measure possible related constructs. Usability was operationalized as the number of tasks that could be completed and the type and number of problems that occurred while doing so. Performance tasks were set up to measure 6 digital skills: (1) operating the computer and internet browser, (2) navigation and orientation, (3) using search strategies, (4) evaluating relevance of content, (5) adding personal content, and (6) protecting and respecting privacy. Participants were asked to think aloud while performing the tasks, and screen activities and webcam recordings were captured. The qualitative observational data was coded using inductive analysis by two independent researchers. Correlational analyses were performed to test how usability relates to sociodemographics and digital health literacy. RESULTS: A total of 32 patients participated, with a mean age of 49.9 years and 84% (27/32) being female. All performance tasks except one (fill in a diary registration) could be completed independently by more than 50% of the participants. On operational, navigation, and search levels, participants struggled most with logging in, logging out, and finding specific parts of the intervention. Half of the sample experienced problems evaluating the relevance and adding content to the program to some extent. Usability correlated moderately negatively with age and moderately positively with digital health literacy skills but not with educational level. CONCLUSIONS: The results provide insight into what is essential for proper usability regarding the design of an iCBT program considering variations in age, educational level, and digital health literacy. Furthermore, the results provide insight into what type of support is needed by patients to properly use the intervention. Tailoring support among the needs of certain age groups or skill levels could be beneficial and could range from no extra support (only online feedback, as intended) to practical support (an additional usability introduction session) to blended care (combined face-to-face sessions throughout the therapy).
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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 | 0,026 | 0,032 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,005 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 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 ».