Abstract No: 423 Physiotherapists’ Attitudes and Beliefs in The Management of Low Back Pain: A Systematic Review
Bibliographic record
Abstract
Background: Low back pain (LBP) poses a significant global health concern. Evidence based guidelines recommend a biopsychosocial approach while managing LBP. Relevance: Physiotherapists (PTs) play a crucial role in LBP management; however, their attitudes and beliefs towards LBP have not been summarized in detail. Purpose: To summarize and appraise the evidence for attitudes and beliefs of PTs towards LBP and the factors influencing them. Methods: The review adheres to the Preferred Reporting Items for Systematic Reviews and Meta- Analyses (PRISMA). A preliminary search of PubMed, CINAHL, Web of Science, Ovid, Embase, and Scopus is ongoing to identify PTs’ attitudes and beliefs toward LBP. Two reviewers will independently screen articles, extract data, and assess methodological quality using the Joanna Briggs Institute’s checklist for prevalence studies. Data synthesis will include a narrative summary of study characteristics, attitudes and beliefs. Results: Nine cross-sectional studies have undergone a preliminary analysis. PTs’ attitudes and beliefs regarding LBP was most frequently assessed using the Pain Attitudes and Beliefs Scale for PT’s (PABS- PT). These studies show that over the past decade, attitudes and beliefs have shifted toward a biopsychosocial approach, and are influenced by factors such as practice setting, personal LBP history, musculoskeletal practice certification, higher education, and work experience. Conclusion: The initial analysis shows PTs’ attitudes toward managing LBP over the past decade align more with recent guidelines, with an association between their treatment orientation and contributing factors. However, these findings are based on research conducted in more developed countries. Implications: The findings of our review highlight the need for further research in developing countries to determine if similar trends are observed. This could highlight gaps in education, resources or guideline dissemination that may need to be addressed to ensure uniformity in evidence-based recommendations worldwide.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | low |
| gpt | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | high |
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 | 0.011 | 0.044 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.006 |
| Bibliometrics | 0.007 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.025 | 0.002 |
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, unvalidatedLabeled directly by 2 models reading the full record.
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".