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Record W2950345940 · doi:10.1177/0008417419839867

Portrait des pratiques évaluatives des ergothérapeutes œuvrant au Québec

2019· article· fr· W2950345940 on OpenAlexvenueaboutno aff
Janie Gobeil, Nadine Larivière, Annie Carrier, Nathalie Bier, Carolina Bottari, Nathalie Veillette, Suzanne Rouleau, Isabelle Gélinas, Véronique Provencher, Mélanie Couture, Mélanie Levasseur

Bibliographic record

VenueCanadian Journal of Occupational Therapy · 2019
Typearticle
Languagefr
FieldHealth Professions
TopicOccupational Therapy Practice and Research
Canadian institutionsnot available
Fundersnot available
KeywordsOccupational therapyPsychological interventionPsychologyOccupational safety and healthMedicineNursingPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND.: In occupational therapy practice, client assessments are essential for establishing treatment priorities and determining the effectiveness of interventions. However, occupational therapists' assessment practices are not well documented. PURPOSE.: This work aimed to provide an overview of the assessment practices of Quebec occupational therapists based on the person-environment-occupation components and clienteles. METHOD.: A cross-sectional survey was conducted using an online survey that was sent to occupational therapists in Quebec. FINDINGS.: In paediatrics, occupational therapists tend to use standardized tools to assess physical and neurological abilities. Adult assessment focuses mainly on physical abilities and productivity. For seniors, assessment focuses mainly on functional aspects (physical abilities, personal care, and home safety) and screening for cognitive difficulties. IMPLICATIONS.: Occupational therapy assessment mostly focuses on physicial abilities. To ensure a holistic approach, more occupational and environmental components should be included in the assessment practices.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.943
Threshold uncertainty score0.415

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0040.001
Scholarly communication0.0030.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.331
GPT teacher head0.499
Teacher spread0.169 · 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 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

Citations5
Published2019
Admission routes2
Has abstractyes

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