MétaCan
Menu
Back to cohort
Record W6907855503 · doi:10.25384/sage.c.4773911

Integration of occupational therapists into family medicine groups: Physicians’ perspectives

2019· other· en· W6907855503 on OpenAlexaboutno aff

Bibliographic record

VenueSage Journals Data · 2019
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsThematic analysisOccupational therapyInclusion (mineral)Primary careQuality (philosophy)Perception

Abstract

fetched live from OpenAlex

IntroductionOccupational therapists remain poorly integrated into family medicine groups in Canada. Physicians are key partners because they can advocate for resources and formulate recommendations to improve the quality of services delivered in their clinics. It is important to explore their perception of the occupational therapist’s role in family medicine groups and the factors influencing their integration.MethodA descriptive qualitative study was conducted. Six family physicians participated in an individual interview. Results were analysed using thematic analysis.ResultsPhysicians consider that occupational therapists can meet the needs of diverse primary care clients. Benefits of this integration include improved clients’ functional status, early screening for developmental and age-related problems, and timely access to required care. The main barriers to integration are lack of funding, space and knowledge of the occupational therapist’s role. The strategies identified to facilitate integration are promoting and clarifying the role of occupational therapists in family medicine groups and developing effective integration models.ConclusionAccording to physicians, the inclusion of occupational therapists in family medicine groups could help primary care teams address many of their clients’ needs and improve the overall quality of primary care services. Targeted strategies are needed to promote the integration of occupational therapists into this practice context.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.348
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0000.001
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 head0.093
GPT teacher head0.391
Teacher spread0.298 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueSage Journals DataFrench-language works237,207