Effectiveness of preventive and treatment interventions for primary headaches in the workplace: A systematic review of the literature
Bibliographic record
Abstract
Aim The purpose of this systematic literature review is to assess the benefits of workplace-based occupational therapies and interventions, including acute and preventive medication, on headache intensity and frequency, related disability as well as work-related outcomes. Methods A search of the literature was conducted in PubMed, MEDLINE, Cochrane library, CINAHL and Embase using terms related to headache, workplace and occupational health. The Cochrane Collaboration's risk of bias assessment tool was used on individual studies to assess internal validity and the Grading of Recommendations Assessment, Development, and Evaluation system was applied to studies by clinical outcome and used to rate quality of evidence. Results Fifteen articles were included in the systematic review. None of them were classified as low risk of bias according to the Cochrane Collaboration's tool for assessing risk of bias. This systematic review found preliminary low-quality evidence suggesting that exercise and acupuncture can reduce workers' headache pain intensity, frequency and related disability. Conclusion Although this systematic review provided preliminary low evidence in favour of work-based intervention, studies with more rigorous designs and methodologies are needed to provide further evidence of the effectiveness of workplace-based headache management strategies.
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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 | 0.009 | 0.040 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.007 |
| Bibliometrics | 0.009 | 0.007 |
| 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) | 0.004 | 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".