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Record W2318687995 · doi:10.1177/0008417414545869

Occupational Performance Coaching for stroke survivors: A pilot randomized controlled trial protocol

2014· article· en· W2318687995 on OpenAlexvenueno aff
Dorothy Kessler, Mary Egan, Claire‐Jehanne Dubouloz, Fiona Graham, Sara McEwen

Bibliographic record

VenueCanadian Journal of Occupational Therapy · 2014
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Therapy Practice and Research
Canadian institutionsnot available
Fundersnot available
KeywordsCoachingStroke (engine)Randomized controlled trialOccupational therapyPhysical therapyPsychologyMedicineProtocol (science)Physical medicine and rehabilitationAlternative medicinePsychotherapist

Abstract

fetched live from OpenAlex

BACKGROUND: Many stroke survivors report participation challenges. Occupational Performance Coaching for stroke survivors (OPC-Stroke) is designed to assist stroke survivors to develop the ability to plan and manage engagement in occupation. This approach combines emotional support, individualized education, and goal-focused problem solving to promote occupational engagement. PURPOSE: This study will explore the potential efficacy of OPC-Stroke and the feasibility of the research methods for use in a larger trial. METHOD: A pilot randomized controlled trial will be undertaken. Participants will be randomly assigned to receive 10 sessions of OPC-Stroke or usual care. Participation, perceived goal performance, satisfaction and self-efficacy, emotional well-being, and cognition will be measured at three time points. IMPLICATIONS: This research will test the potential usefulness of OPC-Stroke as well as the study methods, and thereby inform the continuing development of OPC-Stroke and further studies to measure its effectiveness.

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)0.035
metaresearch head score (Gemma)0.028
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.058
Threshold uncertainty score0.195

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0350.028
Meta-epidemiology (narrow)0.0060.003
Meta-epidemiology (broad)0.0120.004
Bibliometrics0.0030.004
Science and technology studies0.0040.004
Scholarly communication0.0030.003
Open science0.0030.002
Research integrity0.0070.007
Insufficient payload (model declined to judge)0.0580.008

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 head0.238
GPT teacher head0.501
Teacher spread0.263 · 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 designRandomized trial
Domainnot available
GenreProtocol

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

Citations23
Published2014
Admission routes1
Has abstractyes

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