Biopsychosocial predictors of short-term success among people with low back pain referred to a physiotherapy spinal triage service
Bibliographic record
Abstract
BACKGROUND: A spinal triage assessment service may impact a wide range of patient outcomes. Investigating potential predictors of success or improvement may reveal why some people improve and some do not, as well as help to begin to explain potential mechanisms for improvements. The objective of this study was to determine which factors were associated with improved short-term self-reported pain, function, general health status, and satisfaction in people undergoing a spinal triage assessment performed by physiotherapists. METHODS: Participants with low back-related complaints were recruited from people referred to a spinal triage assessment program (N=115). Participants completed baseline questionnaires covering a range of sociodemographic, clinical, and psychological features. Self-reported measures of pain, function, quality of life, and satisfaction were completed at 4 weeks following the assessment. Determination of "success" was based on minimal important change scores of select outcome measures. Multivariate logistic regression was used to explore potential predictors of success for each outcome. RESULTS: Despite the complex and chronic presentation of most participants, some reported improvements in outcomes at 4 weeks post assessment with the highest proportion of participants demonstrating improvement (according to the minimal important change scores) in the Medical Outcomes Survey 36-item short-form version 2 physical component summary score (48.6%) and the lowest proportion of participants having improvements in the Numeric Pain Rating Scale (11.5%). A variety of different sociodemographic, psychological, clinical, and other variables were associated with success or improvement in each respective outcome. CONCLUSION: There may be a potential mechanism of reassurance that occurs during the spinal triage assessment process as those with higher psychological distress (measured by the Fear Avoidance Beliefs Questionnaire and the Distress and Risk Assessment Measure) were more likely to improve on certain outcomes. The use of an evaluation framework guided by a biopsychosocial model may help determine potential mechanisms of action for a physiotherapy-delivered triage program.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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 | 0.000 |
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".