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Record W2106679276 · doi:10.2182/cjot.2010.77.1.7

Occupational Therapy Students' Experiences in Learning Occupation-Centred Approaches to Working with Children

2009· article· en· W2106679276 on OpenAlexvenueno aff
Jodie Copley, Sylvia Rodger, Victoria A. Hannay, Fiona Graham

Bibliographic record

VenueCanadian Journal of Occupational Therapy · 2009
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Therapy Practice and Research
Canadian institutionsnot available
Fundersnot available
KeywordsOccupational therapyThematic analysisDocumentationFocus groupPsychologyIntervention (counseling)Medical educationTriangulationQualitative researchPedagogyMedicineComputer scienceSociology

Abstract

fetched live from OpenAlex

BACKGROUND: The increasing emphasis on performance outcomes and the use of occupation-centred approaches has implications for practice education. PURPOSE: This study aimed to describe students' experiences of learning to use occupation-centred approaches when working with children within a university clinic. METHODS: Nine occupational therapy students and two clinical educators completed three indepth interviews at intervals across the students' fieldwork experiences. Therapy observations, review of therapy documentation, and tutorial group e-mails informed data triangulation. Thematic analysis was used to identify key themes. FINDINGS: Students described needing to make a theoretical shift in thinking to focus on occupational performance and identified a number of challenges relating to learning complex techniques and strategies. IMPLICATIONS: Teaching methods that assist in making occupation-centred assessment and intervention techniques more explicit and learner-friendly for new users are required. These findings provide valuable new insights in guiding this process.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Qualitativehigh
grokno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Qualitativehigh
opusno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Qualitativehigh
models agreeAgreement compares identical category sets and study designs across arms.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.477
GPT teacher head0.478
Teacher spread0.001 · 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

Labeled directly by 3 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations10
Published2009
Admission routes1
Has abstractyes

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