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Record W1993841294 · doi:10.3138/ptc.2012-02

Perceptions on the Essential Competencies for Intraprofessional Practice

2012· article· en· W1993841294 on OpenAlexaffvenue
Wilma Jelley, Nathalie Larocque, Michael M. Borghese

Bibliographic record

VenuePhysiotherapy Canada · 2012
Typearticle
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsLa Cité CollégialeUniversity of Ottawa
Fundersnot available
KeywordsActive listeningLicensurePerceptionMedical educationMedicinePsychologyNursing

Abstract

fetched live from OpenAlex

PURPOSE: To gather the perspectives of physiotherapists and physiotherapist assistants on essential competencies for intraprofessional (physiotherapist-physiotherapist assistant) collaboration. METHOD: A survey was developed to gather physiotherapist and physiotherapist assistant perceptions of the essential elements of effective and efficient intraprofessional collaborative practice. Participants were asked to rate the importance of 36 elements in 6 different categories (communication, collaboration, consultation, assignment of tasks, conflict management, and roles/responsibilities) involved in intraprofessional practice. RESULTS: A total of 1049 physiotherapists and 121 physiotherapist assistants responded to the survey. Analysis identified 10 competency elements perceived by participants as essential to effective and efficient intraprofessional collaboration. Comparisons using demographic variables consistently yielded the same top 10 elements. CONCLUSIONS: Our results indicated that physiotherapists and physiotherapist assistants working in private and public practice share very similar views on what is essential for effective intraprofessional practice. The consensus is that communication is key; open lines of communication help to determine responsibilities. Physiotherapy pre-licensure and continuing education programmes should include opportunities to work on communication, listening, and the skills needed to interact and collaborate effectively.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.213
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.026
GPT teacher head0.445
Teacher spread0.419 · 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 designNot applicable
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

Citations13
Published2012
Admission routes2
Has abstractyes

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