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Record W2075711166 · doi:10.2340/16501977-0167

A national survey of occupational therapists' practices related to participation post-stroke

2008· article· en· W2075711166 on OpenAlexafffundabout
Nicol Korner‐Bitensky, J. Desrosiers, Annie Rochette

Bibliographic record

VenueJournal of Rehabilitation Medicine · 2008
Typearticle
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsMcGill University
FundersMcGill University
KeywordsRehabilitationIntervention (counseling)Occupational therapyPsychological interventionStroke (engine)Social engagementPsychologyMedicinePhysical therapyNursing

Abstract

fetched live from OpenAlex

OBJECTIVES: First, to identify occupational therapists' stroke rehabilitation practices related to leisure and social aspects of participation and potential explanatory variables associated with these practices. Secondly, to identify occupational therapists' desired assessment and treatment practices related to participation. DESIGN: A Canada-wide telephone survey. SUBJECTS: A random sample of 480 occupational therapists providing stroke rehabilitation. METHODS: Two case studies were created: one representing a patient receiving inpatient stroke rehabilitation; the other receiving community-based rehabilitation. A standardized questionnaire was used to elicit information on: (i) clinician and environmental variables; (ii) management of the patient depicted; (iii) desired assessment and intervention use. RESULTS: 60.2% identified a problem relating to leisure or social aspects of participation, 23.1% would use an assessment and 36.5% would offer an intervention focusing on leisure or social participation. Desired assessment use was low (1%), as was desired intervention use (15.2%). Regression analyses using numerous potential explanatory variables explained little regarding clinician practices. CONCLUSION: Less than half of the occupational therapists focused interventions on leisure and social aspects of participation, suggesting a gap between what could be done to enhance successful community reintegration post-stroke and what is currently done.

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)0.003
metaresearch head score (Gemma)0.055
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.052
Threshold uncertainty score0.953

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.055
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.070
GPT teacher head0.411
Teacher spread0.342 · 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.

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

Citations66
Published2008
Admission routes3
Has abstractyes

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