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Record W2146593592 · doi:10.1682/jrrd.2010.06.0110

Responsiveness of the Canadian Occupational Performance Measure

2011· article· en· W2146593592 on OpenAlex

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

VenueThe Journal of Rehabilitation Research and Development · 2011
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Therapy Practice and Research
Canadian institutionsnot available
FundersVrije Universiteit AmsterdamZonMw
KeywordsMeasure (data warehouse)PsychologyPhysical medicine and rehabilitationComputer scienceMedicineData mining

Abstract

fetched live from OpenAlex

This study evaluated the responsiveness of the Canadian Occupational Performance Measure (COPM), an individualized, client-centered outcome measure for the identification and evaluation of self-perceived occupational performance problems. We recruited 152 consecutive patients with various diagnoses, admitted to the outpatient clinic of two occupational therapy departments, to complete a COPM interview and three self-reported health status questionnaires on two occasions: prior to the start of occupational therapy treatment and 3 months later. The three questionnaires were the Sickness Impact Profile (SIP68), the Disability and Impact Profile (DIP), and the Impact on Participation and Autonomy (IPA). We assessed criterion responsiveness by calculating the area under the curve (AUC) for the receiver operating characteristic curve and the optimal cutoff values for the COPM scores.To determine construct responsiveness, we calculated correlations between the change in COPM scores and the change in the SIP68, DIP, and IPA scores. The AUC ranged from 0.79 to 0.85, and the optimal cut-off values for the performance scores and satisfaction scores ranged from 0.9 to 1.9.We found significant positive correlations between the COPM scores and the SIP68, DIP, and IPA scores. The capability of the COPM to detect changes in perceived occupational performance issues is supported.

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)0.016
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.054
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0160.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.246
GPT teacher head0.480
Teacher spread0.234 · 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