Factors Associated With Specialists’ Intention to Adopt New Behaviors After Taking Web-Based Continuing Professional Development Courses: Cross-sectional Study
Notice bibliographique
Résumé
BACKGROUND: Web-based continuing professional development (CPD) is a convenient and low-cost way for physicians to update their knowledge. However, little is known about the factors that influence their intention to put this new knowledge into practice. OBJECTIVE: We aimed to identify sociocognitive factors associated with physicians' intention to adopt new behaviors as well as indications of Bloom's learning levels following their participation in 5 web-based CPD courses. METHODS: We performed a cross-sectional study of specialist physicians who had completed 1 of 5 web-based CPD courses offered by the Federation of Medical Specialists of Quebec. The participants then completed CPD-Reaction, a questionnaire based on Godin's integrated model for health professional behavior change and with evidence of validity that measures behavioral intention (dependent variable) and psychosocial factors influencing intention (n=4). We also assessed variables related to sociodemographics (n=5), course content (n=9), and course format (eg, graphic features and duration) (n=8). Content variables were derived from CanMEDS competencies, Bloom's learning levels, and Godin's integrated model. We conducted ANOVA single-factor analysis, calculated the intraclass correlation coefficient (ICC), and performed bivariate and multivariate analyses. RESULTS: A total of 400 physicians participated in the courses (range: 38-135 physicians per course). Average age was 50 (SD 12) years; 56% (n=223) were female, and 44% (n=177) were male. Among the 259 who completed CPD-Reaction, behavioral intention scores ranged from 5.37 (SD 1.17) to 6.60 (SD 0.88) out of 7 and differed significantly from one course to another (P<.001). The ICC indicated that 17% of the total variation in the outcome of interest, the behavioral intention of physicians, could be explained at the level of the CPD course (ICC=0.17). In bivariate analyses, social influences (P<.001), beliefs about capabilities (P<.001), moral norm (P<.001), beliefs about consequences (P<.001), and psychomotor learning (P=.04) were significantly correlated with physicians' intention to adopt new behaviors. Multivariate analysis showed the same factors, except for social influences and psychomotor learning, as significantly correlated with intention. CONCLUSIONS: We observed average to high behavioral intention scores after all 5 web-based courses, with some variations by course taken. Factors affecting physicians' intention were beliefs about their capabilities and about the consequences of adopting new clinical behaviors, as well as doubts about whether the new behavior aligned with their moral values. Our results will inform design of future web-based CPD courses to ensure they contribute to clinical behavior change.
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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 | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».