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Record W6907843520 · doi:10.25384/sage.c.7257948

Therapists to Therapy Assistants: Experiences of Internationally Educated Physiotherapists and Occupational Therapists

2024· other· en· W6907843520 on OpenAlexaboutno aff

Bibliographic record

VenueSage Journals Data · 2024
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsLicensureThematic analysisIdentity (music)ReflexivityQualitative researchFocus groupHealth careProfessional boundaries

Abstract

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Background: In Canada, internationally educated physiotherapists (IEPTs) and occupational therapists (IEOTs) may work as occupational/physical therapy assistants (OTAs/PTAs) while pursuing Canadian licensure. This experience presents personal and professional opportunities and challenges. Purpose: We explored a) the barriers and facilitators experienced by IEPTs and IEOTs working as OTAs/PTAs while pursuing licensure in Canada and b) how might their professional identity changes during this period. Methods: In this cross-sectional qualitative study, we sampled IEPTs and IEOTs working as assistants using online focus groups. Reflexive thematic analysis of data was used to generate themes. Findings: Fourteen IEPTs or IEOTs participated reporting barriers including financial impacts while working as an OTA/PTA, discrimination, and challenges completing licensing exams. Facilitators while working as OTA/PTAs included social support, acculturation with Canadian systems, and career opportunities. Changes to professional identity encompassed accepting a new identity, reclaiming their old identity, or having a strong sense of identity within a healthcare profession. Participants advocated for bridging programs and modifications for examination processes for IEPTs and IEOTs to improve their experiences while pursuing licensure in Canada. Conclusion: Increased advocacy is needed to address the current experiences of IEPTs and IEOTs working as OTA/PTAs after migration.

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)0.007
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.150
Threshold uncertainty score0.298

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.017
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0160.009
Scholarly communication0.0080.004
Open science0.0020.011
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0050.001

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 head0.074
GPT teacher head0.405
Teacher spread0.330 · 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 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".

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Citations0
Published2024
Admission routes1
Has abstractyes

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Same venueSage Journals DataFrench-language works237,207