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Record W4214851736 · doi:10.1155/2022/9963030

Canadian Occupational Performance Measure: Benefits and Limitations Highlighted Using the Delphi Method and Principal Component Analysis

2022· article· en· W4214851736 on OpenAlex
Jean-Michel Caire, Sabrina Maurel-Techene, Thierry Letellier, Margit Heiske, Sarah Warren, Arnaud Schabaille, Florent Destruhaut

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueOccupational Therapy International · 2022
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Therapy Practice and Research
Canadian institutionsnot available
FundersUniversité de PoitiersInstitut National de la Santé et de la Recherche Médicale
KeywordsOccupational therapyDelphi methodDelphiIntervention (counseling)MedicinePsychologyHealth careNursingMedical educationPhysical therapyComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

Introduction: The objective of this study was to establish a baseline of current use in practice of the Canadian Occupational Performance Measure (COPM) by consulting 33 expert French occupational therapists, who trained in this method between 2012 and 2017 and use of the COPM with their clients. The areas of health intervention are pediatrics, psychiatry, neurology, and geriatrics. An email invitation to participate in the research was therefore sent to 113 occupational therapists. We received 33 responses. Methods: A novel mixed method study combined a Delphi method with a lexical analysis of experts' responses and principal component analysis (PCA). Results: The COPM was clearly identified as a tool that supports occupational therapy clinical reasoning, facilitates team decision-making for care pathways, and enables people with disabilities and health conditions to make decisions for their care. Conclusion: The Delphi study revealed that the COPM appears to be well adapted to French culture and should be widely incorporated into preregistration training.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.076
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.254
GPT teacher head0.472
Teacher spread0.218 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it