Psychological, social and lifestyle screening of people with low back pain treated by physiotherapists in a National Health Service musculoskeletal service: an audit
Bibliographic record
Abstract
Psychological, social and lifestyle (multidimensional) factors predict low back pain (LBP). The Short Form Örebro Musculoskeletal Questionnaire (SFÖQ) helps clinicians identify these factors in people with LBP and was mandated in a physiotherapy department at one NHS Hospital Trust in the UK. This study examined (i) use of the SFÖQ by physiotherapists with varying levels of clinical experience; (ii) whether psychological, social, and lifestyle factors were documented in patient records; and (iii) physiotherapists views on using the SFÖQ, and screening for these factors. A retrospective audit of the physiotherapy records of 100 people referred with LBP. Eighty-one patient records were eligible for analysis. The SFÖQ was completed in 52 records. Fourteen of the completed SFÖQ’s were used by physiotherapists. Screening for, and documentation of, multidimensional factors varied between factors ((i) psychological: cognitive (20%), emotional (26%); (ii) social (41%) and (iii) lifestyle (62%)). 67% of the most senior physiotherapists screened and documented emotional factors. Physiotherapists identified a lack of training, confidence and time as barriers to screening for multidimensional factors and using the SFÖQ. Physiotherapists rarely used the SFÖQ and did not consistently screen or document multidimensional factors. However, more senior physiotherapists more consistently screened and documented emotional factors.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".