Identifying Indicators of Advanced Levels of Clinical Competence in Musculoskeletal Physiotherapy: A Francophone Delphi Study
- 1OMT-France (French Orthopaedic Manual Therapy Organization)
Abstract
BackgroundAs musculoskeletal physiotherapy evolves toward advanced practice and direct access, evaluating high levels of clinical competence has become pressing. Quality indicators underpin large-scale audit systems, but indicators discriminating advanced competence remain insufficiently defined.
ObjectiveTo identify and characterize indicators capable of discriminating high levels of clinical competence in musculoskeletal physiotherapy.
MethodsA modified Delphi comprised an exploratory pre-round and two consensus rounds. Experienced French-speaking musculoskeletal physiotherapists were recruited using an expertise scoring grid. Candidate indicators, generated from open-ended responses and existing quality indicators, were rated on 6-point Likert scales for relevance, formulation, and tool adequacy. Consensus was predefined as [≥]75% of ratings [≥]5.
ResultsThirty-two experts completed the pre-round, 29 the first round, and 27 the second (84% retention), generating 49 candidate indicators. Thirteen reached consensus for relevance, and 10 also for formulation. Retained indicators primarily reflected advanced clinical reasoning: real-time adaptation, hypothesis prioritization, decision-making under uncertainty, and error management. Only one outcome indicator reached consensus: clinical performance weighted by case complexity.
ConclusionHigh levels of clinical competence in musculoskeletal physiotherapy appear characterized less by standardized outcome attainment than by managing complexity, uncertainty, and error through advanced clinical reasoning. These findings may inform competence-oriented audit and feedback systems.
Trials registrationNot applicable.
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BibTeX
@misc{mounierpoulat2026identifying,
title = {{Identifying Indicators of Advanced Levels of Clinical Competence in Musculoskeletal Physiotherapy: A Francophone Delphi Study}},
author = {A. Mounier-Poulat and N. Pinsault and R. Artico},
howpublished = {medRxiv},
year = {2026},
month = sep,
doi = {10.64898/2026.09.29.26363758},
url = {https://www.medrxiv.org/content/10.64898/2026.09.29.26363758v1},
note = {CC BY},
}
RIS
TY - UNPB
TI - Identifying Indicators of Advanced Levels of Clinical Competence in Musculoskeletal Physiotherapy: A Francophone Delphi Study
AU - A. Mounier-Poulat
AU - N. Pinsault
AU - R. Artico
PY - 2026
DA - 2026/09/29
PB - medRxiv
DO - 10.64898/2026.09.29.26363758
UR - https://www.medrxiv.org/content/10.64898/2026.09.29.26363758v1
AB - BackgroundAs musculoskeletal physiotherapy evolves toward advanced practice and direct access, evaluating high levels of clinical competence has become pressing. Quality indicators underpin large-scale audit systems, but indicators discriminating advanced competence remain insufficiently defined. ObjectiveTo identify and characterize indicators capable of discriminating high levels of clinical competence in musculoskeletal physiotherapy. MethodsA modified Delphi comprised an exploratory pre-round and two consensus rounds. Experienced French-speaking musculoskeletal physiotherapists were recruited using an expertise scoring grid. Candidate indicators, generated from open-ended responses and existing quality indicators, were rated on 6-point Likert scales for relevance, formulation, and tool adequacy. Consensus was predefined as [≥]75% of ratings [≥]5. ResultsThirty-two experts completed the pre-round, 29 the first round, and 27 the second (84% retention), generating 49 candidate indicators. Thirteen reached consensus for relevance, and 10 also for formulation. Retained indicators primarily reflected advanced clinical reasoning: real-time adaptation, hypothesis prioritization, decision-making under uncertainty, and error management. Only one outcome indicator reached consensus: clinical performance weighted by case complexity. ConclusionHigh levels of clinical competence in musculoskeletal physiotherapy appear characterized less by standardized outcome attainment than by managing complexity, uncertainty, and error through advanced clinical reasoning. These findings may inform competence-oriented audit and feedback systems. Trials registrationNot applicable.
ER -