Attitudes, knowledge and behaviors related to evidence-based practice in health professionals involved in pain management
Notice bibliographique
Résumé
BACKGROUND: Healthcare professionals involved in pain management come from different disciplines, which may have different perspectives and training about evidence-based practice (EBP). A common concern for health professionals is pain management. Understanding how different professions involved in pain management view EBP forms the ideal context to study professional differences in EPP, and how this might influence pain management. PURPOSE: The purpose of this study was to compare different professions with respect to knowledge, attitudes and self-reported behavior toward EBP. STUDY DESIGN: Cross-sectional study. METHODS: Physicians, nurses, occupational therapists, physical therapists and psychologists who were involved in pain management (n = 675) completed an online survey on a single occasion. The survey included demographic questions and the EBP-knowledge, attitude, behavior questionnaire (EBP-KABQ). This is a 27-item questionnaire that has been validated for use with different health professionals, and measures four constructs related to EBP (knowledge, attitude, behavior and outcome/decision). Differences between professionals were identified using a one-way between groups analysis of variance, with post-hoc testing (statistical significance was set at P value less than 0.05; clinical significance set at a mean difference of 10%). RESULTS: The score on three of the four subscales of the KABQ were statistically different across professions. In general, knowledge scores were high for all professions (83-87%). Nurses demonstrated statistically higher levels of EBP knowledge (87%) when compared with other groups (F = 4.79, P = 0.001), but the differences were not deemed clinically relevant. Behavior was the lowest subscale and the most variable across professions (37-56%). Physicians had statistically significant (F = 25.69; P = 0.001), and clinically relevant, higher behavior subscale scores (56%) when compared with other professional groups. Physicians (73%) also had higher outcome/decision subscale scores (F = 6.50; P = 0.001), but this was only marginally different from other professions (65-73%). The attitude subscale scores were low and were not different across professions (range 57-59%; F = 1.65, P = 0.16; NS). CONCLUSION: The current study indicates that physicians and allied health professionals have similar EBP attitudes and knowledge. All professional groups seem to have suboptimal implementation of EBP. The nature of medical decision-making, its evidentiary pool, or longer experience with EBP may contribute to greater implementation amongst physicians.
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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 | 0,003 | 0,016 |
| 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 | 0,001 |
| 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) | 0,003 | 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 ».