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Record W2156757785 · doi:10.5014/ajot.61.3.328

Occupational Therapy Outcomes for Clients With Traumatic Brain Injury and Stroke Using the Canadian Occupational Performance Measure

2007· article· en· W2156757785 on OpenAlexaboutno aff
Shawn Phipps, Pamela Richardson

Bibliographic record

VenueAmerican Journal of Occupational Therapy · 2007
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Therapy Practice and Research
Canadian institutionsnot available
Fundersnot available
KeywordsOccupational therapyTraumatic brain injuryMedicinePhysical therapyIntervention (counseling)Stroke (engine)Activities of daily livingPhysical medicine and rehabilitationPsychologyClinical psychologyPsychiatry

Abstract

fetched live from OpenAlex

The purpose of this study was to determine whether 155 ethnically diverse clients with traumatic brain injury (TBI) and stroke (cerebrovascular accident; CVA) who received occupational therapy services perceived that they reached self-identified goals related to tasks of daily life as measured by the Canadian Occupational Performance Measure (COPM). This study found that a statistically and clinically significant change in self-perceived performance and satisfaction with tasks of daily life occurred at the end of a client-centered occupational therapy program (p < .001). There were no significant differences in performance and satisfaction between the TBI and CVA groups. However, the group with right CVA reported a higher level of satisfaction with performance in daily activities than the group with left CVA (p = .03). The COPM process can effectively assist clients with neurological impairments in identifying meaningful occupational performance goals. The occupational therapist also can use the COPM to design occupation-based and client-centered intervention programs and measure occupational therapy outcomes.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.779
Threshold uncertainty score0.445

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.239
GPT teacher head0.510
Teacher spread0.271 · 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 source (direct Gemma or distilled Codex), 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

Citations109
Published2007
Admission routes1
Has abstractyes

Explore more

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