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Record W2114979566 · doi:10.1177/000841740707405s01

A Survey of Occupational Therapists in Canada about Their Knowledge and Use of the ICF

2007· article· en· W2114979566 on OpenAlexaffvenueabout
Jennifer Farrell, S.T. Anderson, Kim Hewitt, Michael H. Livingston, Debra Stewart

Bibliographic record

VenueCanadian Journal of Occupational Therapy · 2007
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Therapy Practice and Research
Canadian institutionsMinistry of Community Safety and Correctional ServicesSummit Pacific College
Fundersnot available
KeywordsOccupational therapyInternational Classification of Functioning, Disability and HealthPsychologySample (material)Medical educationApplied psychologyMedicineRehabilitation

Abstract

fetched live from OpenAlex

BACKGROUND: The current impact of the International Classification of Functioning, Disability and Health (ICF) on the field of occupational therapy within Canada is unknown. PURPOSE: To survey occupational therapists in Canada about their knowledge, use of and suggestions for education about the ICF. METHOD: Mixed methods design included (i) an online survey, with data analyzed using quantitative methods; and (ii) semi-structured interviews with a purposeful sample of 10 therapists, using content analysis. RESULTS: The online survey was completed by 587 occupational therapists (17.6% return). Four hundred and ten respondents (70.0%) indicated some ICF knowledge, and 121 of those individuals (29.5%) reported using it in practice. Interview participants suggested resources, perceived meaning and investment factors impact ICF knowledge. Suggested uses include frameworks and interprofessional collaboration, while ideas for education involve meaningful and accessible formats. PRACTICE IMPLICATIONS: The ICF may be useful to occupational therapists in different settings if it fulfills a meaningful purpose and fits with practice models.

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)0.006
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.982
Threshold uncertainty score0.132

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0030.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.391
GPT teacher head0.498
Teacher spread0.107 · 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

Citations26
Published2007
Admission routes3
Has abstractyes

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