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An Exploratory Study of the Occupation-Focused Models Included in Occupational Therapy Professional Education Programmes

2010· article· en· W2059411324 on OpenAlexaboutno aff
Samantha Ashby, Bronwyn Chandler

Bibliographic record

VenueBritish Journal of Occupational Therapy · 2010
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Therapy Practice and Research
Canadian institutionsnot available
Fundersnot available
KeywordsOccupational therapyCurriculumInclusion (mineral)Medical educationExploratory researchPsychologyMedicineClinical PracticePedagogyFamily medicineSociologyPhysical therapySocial science

Abstract

fetched live from OpenAlex

Introduction: Occupation-focused models are one method of integrating occupation into occupational therapy education programmes. They offer a theoretical basis for practice by providing explanations about the process and practice of the profession. Method: This exploratory study used a quantitative research framework to investigate which occupation-focused models are included in occupational therapy programmes, the rationale for their inclusion and how the models are integrated into curricula. A survey was sent to 193 occupational therapy programmes in Australia, Canada, the United Kingdom and the United States. Results: The response rate was 33.8% (n = 65). The data showed that each programme included between 3 and 10 occupation-focused models. The Canadian Model of Occupational Performance and Engagement and the Model of Human Occupation were included in 98.5% of all curricula surveyed. Conclusion: The educators used a multilayered decision-making process to determine which occupation-focused models to include in a curriculum. The instructional methods varied, but most programmes used practice placement education as a teaching strategy. Further research is required into how curriculum design influences a practitioner's future use of occupation-focused models in practice. A better understanding is needed of how professional practice education affects students' values and attitudes towards the use of occupation-focused 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 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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.113
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.212
GPT teacher head0.509
Teacher spread0.297 · 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 teacher head, not a consensus.

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

Citations47
Published2010
Admission routes1
Has abstractyes

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