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Record W2897222276 · doi:10.1177/1049732318803589

Tensions Living Out Professional Values for Physical Therapists Treating Injured Workers

2018· article· en· W2897222276 on OpenAlexafffundabout
Anne Hudon, Debbie Ehrmann Feldman, Matthew Hunt

Bibliographic record

VenueQualitative Health Research · 2018
Typearticle
Languageen
FieldHealth Professions
TopicEthics in medical practice
Canadian institutionsMcGill UniversityUniversité de MontréalCentre for Interdisciplinary Research in RehabilitationUniversity of OttawaUniversity of Waterloo
FundersInstitute of Musculoskeletal Health and ArthritisCanadian Institutes of Health ResearchPhysiotherapy Foundation of CanadaMcGill University
KeywordsAutonomyNursingHealth careCompensation (psychology)Competence (human resources)PsychologyQualitative researchMedicineSocial psychologySociology

Abstract

fetched live from OpenAlex

Health care services provided by workers' compensation systems aim to facilitate recovery for injured workers. However, some features of these systems pose barriers to high quality care and challenge health care professionals in their everyday work. We used interpretive description methodology to explore ethical tensions experienced by physical therapists caring for patients with musculoskeletal injuries compensated by Workers' Compensation Boards. We conducted in-depth interviews with 40 physical therapists and leaders in the physical therapy and workers' compensation fields from three Canadian provinces and analyzed transcripts using concurrent and constant comparative techniques. Through our analysis, we developed inductive themes reflecting significant challenges experienced by participants in upholding three core professional values: equity, competence, and autonomy. These challenges illustrate multiple facets of physical therapists' struggles to uphold moral commitments and preserve their sense of professional integrity while providing care to injured workers within a complex health service system.

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)0.098
metaresearch head score (Gemma)0.160
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.460
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0980.160
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0110.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.008
Insufficient payload (model declined to judge)0.0000.001

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 head0.744
GPT teacher head0.771
Teacher spread0.027 · 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; both teacher heads agree on what is shown here.

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

Citations6
Published2018
Admission routes3
Has abstractyes

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