Program evaluation of a model to integrate internationally educated health professionals into clinical practice
Bibliographic record
Abstract
BACKGROUND: The demand for health professionals continues to increase, partially due to the aging population and the high proportion of practitioners nearing retirement. The University of British Columbia (UBC) has developed a program to address this demand, by providing support for internationally trained Physiotherapists in their preparation for taking the National Physiotherapy competency examinations.The aim was to create a program comprised of the educational tools and infrastructure to support internationally educated physiotherapists (IEPs) in their preparation for entry to practice in Canada and, to improve their pass rate on the national competency examination. METHODS: The program was developed using a logic model and evaluated using program evaluation methodology. Program tools and resources included educational modules and curricular packages which were developed and refined based on feedback from clinical experts, IEPs and clinical physical therapy mentors. An examination bank was created and used to include test-enhanced education. Clinical mentors were recruited and trained to provide clinical and cultural support for participants. RESULTS: The IEP program has recruited 124 IEPs, with 69 now integrated into the Canadian physiotherapy workforce, and more IEPs continuing to apply to the program. International graduates who participated in the program had an improved pass rate on the national Physiotherapy Competency Examination (PCE); participation in the program resulted in them having a 28% (95% CI, 2% to 59%) greater possibility of passing the written section than their counterparts who did not take the program. In 2010, 81% of all IEP candidates who completed the UBC program passed the written component, and 82% passed the clinical component. CONCLUSION: The program has proven to be successful and sustainable. This program model could be replicated to support the successful integration of other international health professionals into the workforce.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.031 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".