Do Physiotherapists Have the Skill to Engage in the “Psychological” in the Bio-Psychosocial Approach?
Bibliographic record
Abstract
Purpose: To describe a cross-sectional exploration of attitudes of physiotherapists in general practice in Western Australia toward psychiatry and mental illness, how often they treat people with mental illness, their perceptions of how well their undergraduate education prepared them to work with these people, and their opinions about what further education would enable them to provide best-practice care. Methods: A questionnaire that included questions about participants' demographic information, personal experiences with mental illness, the Attitudes to Psychiatry (ATP-30), and open-ended questions about participants' preparedness to work with people with mental illness was distributed through 110 email contacts to physiotherapy departments in Western Australia. Results: A total of 75 completed questionnaires contributed to the findings; 11 returned questionnaires were incomplete and were not included in the data analysis. ATP-30 scores indicated moderately positive attitudes toward psychiatry and mental illness. Women indicated significantly more positive attitudes than men. Of the full sample, 41% (n=31) reported treating someone with a comorbid mental health problem every day and 76% (n=57) reported treating someone every week. Conclusion: Physiotherapists in general practice in Western Australia have generally positive perceptions of psychiatry. The majority of clinicians reported treating patients with mental illness at least once a week. Participants indicated feeling underprepared to work with this patient group, a need for the undergraduate curriculum to be revised, and an overwhelming need for postgraduate training in psychiatry and mental health.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
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".