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Record W2091109273 · doi:10.5014/ajot.2011.09010

Cognitive Approach to Improving Participation After Stroke: Two Case Studies

2011· article· en· W2091109273 on OpenAlexaff
Erin J. Henshaw, Helene J. Polatajko, Sara McEwen, Jennifer D. Ryan, Carolyn Baum

Bibliographic record

VenueAmerican Journal of Occupational Therapy · 2011
Typearticle
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsBaycrest HospitalUniversity of Toronto
Fundersnot available
KeywordsOccupational therapyStroke (engine)RehabilitationCognitionCognitive remediation therapyRandomized controlled trialActivities of daily livingPhysical medicine and rehabilitationPsychologyPhysical therapyCognitive rehabilitation therapyMedicinePsychiatry

Abstract

fetched live from OpenAlex

Despite the need for occupational therapy to emphasize client-specific occupational performance, primary emphasis in stroke rehabilitation continues to be on the remediation of client factors and self-care. Such practice leaves many survivors of stroke with continuing performance deficits. Two case studies demonstrate a novel, alternative approach. The Cognitive Orientation to Daily Occupational Performance (CO-OP) treatment is a performance-based, problem-solving approach to developing functional skills that are client centered. CO-OP was used to guide treatment with 2 older women. The findings suggest that the approach has the potential to successfully help clients with stroke achieve their everyday occupational goals and support continued research in this area. This work will lead to a pilot randomized controlled trial.

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)0.002
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.013
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0030.002
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0050.002
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 head0.123
GPT teacher head0.416
Teacher spread0.293 · 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 designCase report
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

Citations44
Published2011
Admission routes1
Has abstractyes

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