Assessing Therapist Competence: Development of a Performance-Based Measure and Its Comparison With a Web-Based Measure
Notice bibliographique
Résumé
BACKGROUND: Recent research interest in how best to train therapists to deliver psychological treatments has highlighted the need for rigorous, but scalable, means of measuring therapist competence. There are at least two components involved in assessing therapist competence: the assessment of their knowledge of the treatment concerned, including how and when to use its strategies and procedures, and an evaluation of their ability to apply such knowledge skillfully in practice. While the assessment of therapists' knowledge has the potential to be completed efficiently on the Web, the assessment of skill has generally involved a labor-intensive process carried out by clinicians, and as such, may not be suitable for assessing training outcome in certain circumstances. OBJECTIVES: The aims of this study were to develop and evaluate a role-play-based measure of skill suitable for assessing training outcome and to compare its performance with a highly scalable Web-based measure of applied knowledge. METHODS: Using enhanced cognitive behavioral therapy (CBT-E) for eating disorders as an exemplar, clinical scenarios for role-play assessment were developed and piloted together with a rating scheme for assessing trainee therapists' performance. These scenarios were evaluated by examining the performance of 93 therapists from different professional backgrounds and at different levels of training in implementing CBT-E. These therapists also completed a previously developed Web-based measure of applied knowledge, and the ability of the Web-based measure to efficiently predict competence on the role-play measure was investigated. RESULTS: The role-play measure assessed performance at implementing a range of CBT-E procedures. The majority of the therapists rated their performance as moderately or closely resembling their usual clinical performance. Trained raters were able to achieve good-to-excellent reliability for averaged competence, with intraclass correlation coefficients ranging from .653 to 909. The measure was also sensitive to change, with scores being significantly higher after training than before as might be expected (mean difference 0.758, P<.001) even when taking account of repeated data (mean difference 0.667, P<.001). The major shortcoming of the role-play measure was that it required considerable time and resources. This shortcoming is inherent in the method. Given this, of most interest for assessing training outcome, scores on the Web-based measure efficiently predicted therapist competence, as judged by the role-play measure (with the Web-based measure having a positive predictive value of 77% and specificity of 78%). CONCLUSIONS: The results of this study suggest that while it was feasible and acceptable to assess performance using the newly developed role-play measure, the highly scalable Web-based measure could be used in certain circumstances as a substitute for the more labor-intensive, and hence, more costly role-play method.
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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 | 0,030 | 0,051 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,004 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,001 | 0,002 |
| Science ouverte | 0,001 | 0,002 |
| 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 ».