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Record W1999917202 · doi:10.12968/ijtr.2008.15.1.27946

Measuring occupational performance and client priorities in the community: The COPM

2008· article· en· W1999917202 on OpenAlexaboutno aff
AEK Roberts, Anthony James, J. Grahame Drew, Sam G. Moreton, Richard J. Thompson, Michele Dickson

Bibliographic record

VenueInternational Journal of Therapy and Rehabilitation · 2008
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Therapy Practice and Research
Canadian institutionsnot available
Fundersnot available
KeywordsOccupational therapyIntervention (counseling)Psychological interventionPsychologyNursingMedicinePsychiatry

Abstract

fetched live from OpenAlex

The primary aim of this study was to examine changes in clients' occupational performance and satisfaction with their performance within a community trust setting, using the Canadian Occupational Performance Measure (COPM). Given the rapid throughput of clients and the pressure of limited resources, the authors postulated that occupational therapy interventions were focusing on clients' self-care needs as a matter of priority for clients to be independent at home. Therefore, at a time when services are seeking to be increasingly client-focused, the authors' secondary aim was to explore whether self-care needs were also the clients' highest priorities. Fourteen occupational therapists and 62 clients took part in the study. The therapists used the COPM to assess the client; the clients completed the COPM at initial interview and at the end of the intervention. Inferential statistics were then used to ascertain any change over the intervention period. The findings showed a statistically significant change in clients' occupational performance and satisfaction with their performance, in all settings, following occupational therapy. There were notable differences in occupational performance goals between men and women, in that a higher percentage of self-care goals were identified by the men. Self-care goals were the most frequently cited goals in all of the settings.

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.

How this classification was reachedexpand

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.084
Threshold uncertainty score0.643

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.212
GPT teacher head0.458
Teacher spread0.245 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations13
Published2008
Admission routes1
Has abstractyes

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