Embedding the Rehabilitation Treatment Specification System into clinical practice: An evaluation of a pilot teaching programme
Notice bibliographique
Résumé
Abstract Background: Deficiency in the provision and quality of treatment specification by rehabilitation clinicians impairs the ability to differentiate effective from ineffective elements of treatment. The standardized language of the rehabilitation treatment specification system (RTSS) has been proposed as a countermeasure. To date, there is no evidence of its use in clinical practice and what effect it may have. This study aimed to assess the ability of a pilot teaching programme to embed the RTSS into the clinical practice of an inpatient oncology physiotherapy team. The objectives were to evaluate the teaching programme’s effect on; participants’ familiarity and perceived benefit of the RTSS, its uptake, participants’ clinical reasoning, and their feelings and attitudes towards adopting the RTSS. This study provides an evaluation of the pilot teaching programme which will subsequently inform a larger iteration in an ongoing Health Education England (HEE) project aiming to disseminate and embed the RTSS into physiotherapy practice to improve physiotherapists’ treatment specification. Methods A 6-week, multi-modal RTSS pilot teaching programme based upon socio-constructivist theory was delivered to 10 inpatient oncology physiotherapists at a large urban UK trust in 2021. Self-reported measures and clinical case note audits were assessed before and after the RTSS teaching programme to evaluate its effect on RTSS familiarity and perceived benefit, uptake, and clinical reasoning. A post-teaching focus group was undertaken. It was qualitatively analysed using an inductive, independent thematic approach to evaluate clinicians’ reflection and adoption. Results Ten participants (8F, 29.4(±3.5) years) with variable clinical experience completed the RTSS teaching programme (six 1-hour lecture/case-based-learning sessions weekly) with 85% mean attendance. Nine yielded complete data for analyses, and 7 participated in the focus group. There was significant improvement in self-reported familiarity and confidence using the RTSS. Furthermore, there was a significant effect of the teaching on self-reported clinical reasoning overall and specifically in knowledge and theory application. But this was not reflected in clinicians’ uptake of RTSS language, nor in the quality of clinical reasoning emergent in their case notes. Qualitative analyses revealed that while clinicians’ conceptual understanding and the relative advantage of using the RTSS in practice was pervasive, they articulated that translating its perceived academic disposition into their clinical practice a challenge. Conclusions: The RTSS teaching programme was shown to be effective in improving self-reported measures of clinical reasoning, despite clinical uptake of the RTSS remaining low. Future iterations should be tested across physiotherapy specialisms and in a greater sample with consideration of pedagogical and cultural measures to support the clinical diffusion of the RTSS including longer teaching periods, introducing pre-teaching e-learning approaches, incorporating how to document RTSS language into clinical case-notes, and designing the teaching to influence clinical leaders.
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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 | 0,023 | 0,038 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,002 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,003 | 0,003 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 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 ».