Experiences and Perspectives of Physical Therapists Managing Patients Covered by Workers' Compensation in Queensland, Australia
Bibliographic record
Abstract
BACKGROUND: Physical therapists have an active role in the rehabilitation of injured workers. However, regulations in Queensland, Australia, do not afford them the opportunity to participate in return-to-work (RTW) decisions in a standardized way. No prior research has explored the experiences and perceptions of therapists in determining work capacity. OBJECTIVES: The aim of this study was to investigate physical therapists' experiences with and perspectives on their role in determining readiness for RTW and work capacity for patients receiving workers' compensation in Queensland. Design A qualitative design was used. Participants were physical therapists who manage injured workers. METHODS: Novice (n=5) and experienced (n=20) therapists managing patients receiving workers' compensation were selected through purposeful sampling to participate in a focus group or semistructured telephone interviews. Data obtained were audio-recorded and transcribed verbatim. Transcripts were thematically analyzed. Physical therapists' confidence in making RTW decisions was determined with 1 question scored on a 0 to 10 scale. RESULTS: Themes identified were: (1) physical therapists believe they are important in RTW, (2) physical therapists use a variety of methods to determine work capacity, and (3) physical therapists experience a lack of role clarity. Therapists made recommendations for RTW using clinical judgment informed by subjective and objective information gathered from the injured worker. Novice therapists were less confident in making RTW decisions. CONCLUSION: Therapists are well situated to gather and interpret the information necessary to make RTW recommendations. Strategies targeting the Australian Physiotherapy Association, physical therapists, and the regulators are needed to standardize assessment of readiness for RTW, improve role clarity, and assist novice practitioners.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".