Physiotherapists’ attitudes and beliefs in the management of low back pain: Protocol for a systematic review
Bibliographic record
Abstract
BACKGROUND: Low back pain (LBP) poses a significant global health burden where a biopsychosocial model of care has been recommended. Physiotherapists (PTs) play a crucial role in LBP management; however, their attitudes and beliefs towards LBP were not reviewed in detail. OBJECTIVE: This systematic review aims to summarise the attitudes and beliefs of PTs towards LBP and the factors influencing them. METHODS: The review protocol and methods adhere to the PRISMA-P and Meta Analyses and Systematic Reviews for Observational Studies in Epidemiology (MOOSE) guidelines. A comprehensive search of PubMed, Scopus, CINAHL, Web of Science, PEDro and Ovid databases will be conducted to search for cross-sectional studies evaluating PTs' attitudes and beliefs towards LBP. Two reviewers will independently screen the articles, conduct data extraction and assess methodological quality using the Joanna Briggs Institute's critical appraisal tool for prevalence studies. Data synthesis will involve a narrative synthesis of study characteristics, attitudes, beliefs, and methodological quality. If feasible, a meta-analysis will be performed to quantify the pooled effects. CONCLUSION: Despite the emphasis on biopsychosocial approaches for managing LBP, the adoption of such approaches in physiotherapy practice is still suboptimal, with attitudes and beliefs of PTs being considered an important factor influencing treatment practices. Our review will summarise the literature on attitudes and beliefs of PTs towards LBP. Such knowledge would inform the need for development of additional interventions addressing the attitudes and beliefs that would eventually enhance the update of the biopsychosocial model of care in physiotherapy management of LBP.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.067 | 0.084 |
| Meta-epidemiology (narrow) | 0.006 | 0.005 |
| Meta-epidemiology (broad) | 0.018 | 0.019 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.070 | 0.009 |
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".