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Record W2014832426 · doi:10.2182/cjot.2011.78.3.2

An Agenda for Occupational Therapy's Contribution to Collaborative Chronic Disease Research

2011· article· en· W2014832426 on OpenAlexafffundvenueabout
Carri Hand, Lori Letts, Claudia M. von Zweck

Bibliographic record

VenueCanadian Journal of Occupational Therapy · 2011
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Therapy Practice and Research
Canadian institutionsCanadian Association of Occupational TherapistsMcMaster University
FundersCanadian Institutes of Health ResearchHealth CanadaCanadian Health Services Research Foundation
KeywordsOccupational therapyMedicinePhysical therapyPsychotherapistPsychology

Abstract

fetched live from OpenAlex

BACKGROUND: To meet the needs of adults with chronic diseases, Canadian health care is moving toward more interdisciplinary, collaborative practice. There is limited high-quality evidence to support practice in this area. Occupational therapists can play a significant role in this area of practice and research. PURPOSE: To develop an agenda of priority areas within collaborative chronic disease research to which occupational therapy can make a contribution. METHODS: The project involved literature and Internet review, a consensus meeting with a range of stakeholders, a survey of occupational therapists, and synthesis of findings to create a research agenda. FINDINGS: An interdisciplinary and intersectoral group of stakeholders identified seven main priority areas. One priority is specific to occupational therapy while the remaining six cross disciplines. IMPLICATIONS: The research agenda can support funding applications and encourage interdisciplinary research collaboration to ultimately produce research evidence that can benefit people with chronic diseases.

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)0.332
metaresearch head score (Gemma)0.209
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.668
Threshold uncertainty score0.823

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.3320.209
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0050.005
Bibliometrics0.0100.008
Science and technology studies0.0300.045
Scholarly communication0.0470.041
Open science0.0080.049
Research integrity0.0510.035
Insufficient payload (model declined to judge)0.0110.001

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 head0.592
GPT teacher head0.598
Teacher spread0.006 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designTheoretical or conceptual
DomainMethods
GenreCommentary

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

Citations10
Published2011
Admission routes4
Has abstractyes

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