Notice bibliographique
Résumé
Clinical education is an integral component of physiotherapy student training, 2,3 comprising approximately one-third of all coursework in physiotherapy programmes across Canada.During clinical placements or internships, physiotherapy students develop and apply the knowledge, skills, and professional behaviours necessary for competent entry-level practice, and they are evaluated on these clinical competencies by physiotherapist supervisors or clinical instructors (CIs).At present, most Canadian physiotherapy schools use the Physical Therapist Clinical Performance Instrument (CPI) 4 to assess students' performance during their clinical placements.The CPI consists of 24 items or performance criteria that, together, are considered to represent all aspects of physiotherapy clinical performance.Developed in the United States, the CPI has undergone rigorous development and testing and has been found to be a valid and reliable measure of physiotherapy student performance. 4hile the CPI's psychometric properties have been established, a recent Canadian study 5 identified the CPI and the evaluation of students as a barrier to physiotherapists' offering to supervise a student.The study also confirms anecdotal reports from Canadian CIs that the CPI is lengthy, takes too long to complete, and is not always suited to the Canadian physiotherapy context. 5The new instrument developed by Mori and colleagues 1 is a welcome addition to the evaluation of Canadian physiotherapy students, and I am sure many CIs will say it is long overdue!In an era of evidence-informed practice, and in light of the principles of research we emphasize to the students in our programmes, both the physiotherapy community and our students should expect assessments of student performance to be grounded in evidence.Like the developers of the CPI, Mori and colleagues document a systematic and rigorous process for the initial development of their new instrument, the Canadian Physiotherapy Assessment of Clinical Performance (ACP). 1 In Phase 1, Mori and colleagues consulted widely with experts in assessment and measurement, as well as with experts in Canadian physiotherapy clinical education.Because the ACP was intended to be a national instrument, members of the National Association for Clinical Education in Physiotherapy (NACEP) and the Canadian Council of Physiotherapy Academic Programs (CCPUP) were invited to participate in the Delphi process, ensuring that the developers received feedback and input from all Canadian physiotherapy programmes before reaching consensus on the competencies to be included in the ACP.Phase 2 gathered feedback from academic experts in measurement and clinical education, as well as from end users (i.e., CIs and recent graduates), on the items to be included in the instrument, their understanding of these items, the rating scale to be used, and their overall impressions of the instrument.Cognitive interviewing is an important step in developing surveys and instruments like the ACP because it ensures that the questions or items are understood by the respondent (in this case, the CI or student) as the developers intended, 6 as well as giving potential users an opportunity to provide input on usability.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
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 | 0,005 | 0,042 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,002 |
| Bibliométrie | 0,003 | 0,002 |
| Études des sciences et des technologies | 0,006 | 0,005 |
| Communication savante | 0,005 | 0,006 |
| Science ouverte | 0,007 | 0,004 |
| Intégrité de la recherche | 0,056 | 0,049 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,021 | 0,022 |
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 ».