Use of General Practitioner Services Among Workers with Work-Related Low Back Pain: A Systematic Review
Bibliographic record
Abstract
PURPOSE: Work-related low back pain (WRLBP) is a highly prevalent health problem worldwide leading to work disability and increased healthcare utilisation. General practitioners (GPs) play an important role in the management of WRLBP. Despite this, understanding of GP service use for WRLBP is limited. This systematic review aimed to determine the prevalence, patterns and determinants of GP service use for WRLBP. METHODS: MEDLINE, Embase via Ovid, Scopus and Web of Science were searched for relevant peer-reviewed articles published in English without any restriction on time of publications. Low back pain (LBP) was considered work-related if the study included workers' compensation claim data analysis, participants with accepted workers' compensation claims or reported a connection with work and LBP. The eligibility criteria for GP service use are met if there is any reported consultation with family practitioner, medical doctor or General Practitioner. Two reviewers screened articles and extracted data independently. Narrative synthesis was conducted. RESULTS: Seven eligible studies reported prevalence of GP service use among workers with WRLBP ranging from 11% to 99.3%. Only studies from Australia, Canada and the United States met the eligibility criteria. The prevalence of GP service use was higher in Australia (70%) and Canada (99.3%) compared to the United States (25.3% to 39%). The mean (standard deviation) number of GP visits ranged from 2.6 (1.6) to 9.6 (12.4) over a two-year time interval post-WRLBP onset. Determinants of higher GP service use included prior history of low back pain, more severe injury, prior GP visits and younger age. CONCLUSION: Only seven studies met the eligibility indicating a relative lack of evidence, despite the acknowledged important role that GPs play in the care of workers with low back pain. More research is needed to understand the prevalence, patterns and determinants to support effective service delivery and policy development.
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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 | 0.007 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.009 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".