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Record W2057469890 · doi:10.3138/ptc.2014-21

Impact of College-Administered Quality Practice Assessments: A Longitudinal Evaluation of Repeat Peer Assessments of Continuing Competence in Physiotherapists

2015· article· en· W2057469890 on OpenAlexaffvenueabout
Kathleen E. Norman, Mary O'Donovan, Fiona Campbell

Bibliographic record

VenuePhysiotherapy Canada · 2015
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Therapy Practice and Research
Canadian institutionsCanadian Physiotherapy AssociationQueen's University
Fundersnot available
KeywordsCohortMedicineCompetence (human resources)Quality assurancePhysical therapyFamily medicinePsychologyInternal medicine

Abstract

fetched live from OpenAlex

PURPOSE: The College of Physiotherapists of Ontario (CPO) developed its peer practice assessment (PA) process under statutory requirements for quality assurance. Each year, a small percentage of physiotherapists, most selected at random, undergo PA. To shed light on continuing competence, we report outcomes from physiotherapists who have had two PAs. METHODS: Records were extracted for physiotherapists with two unrelated PAs. Demographic features, peer assessors' scores, and consequent outcome decisions were examined. Outcomes were examined cross-sectionally (vs. other PAs in the same time period) and longitudinally (within cohort). RESULTS: Between 2004 and 2012, 117 Ontario physiotherapists underwent two unrelated PAs, typically 5-7 years apart. This cohort was representative of Ontario physiotherapists in terms of sex ratios, education, and years in practice. At the first PA (PA1), this cohort's outcomes were similar to those of other physiotherapists; at the second PA (PA2), they were better than others undergoing PA1 in the same period (p=0.02). The cohort's outcomes were better at PA2 than at PA1 (p<0.001). CONCLUSIONS: Physiotherapists are likely to meet professional standards in a repeat PA 5-7 years after an initial one. Additional research is required to identify risk factors for not meeting standards. The findings provide empirical evidence to guide ongoing development of the CPO's quality management program.

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)0.006
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.453
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.278
GPT teacher head0.630
Teacher spread0.352 · 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.

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

Citations4
Published2015
Admission routes3
Has abstractyes

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