P2-115 Demand and control at work and blood pressure: systematic review and meta-analysis
Bibliographic record
Abstract
Karasek postulated that high job strain, an interaction between high psychological demands and low control at work, increases the risk of ill-health. Objective Systematic review/meta-analysis of the association between job strain and blood pressure (BP). Methods Target studies were published on Pubmed, Lilacs, SciELO, PsycInfo, Embase and Web of Science, until July 2009. Data extraction was conducted independently by 2 of 3 reviewers using a standardised form. Results The search retrieved 1377 studies and 51 fulfilled the eligibility criteria, mostly cross-sectional and conducted in Europe or USA. Most of them applied the job content questionnaire (89.4%) and used the Karasek's quadrant categories (78.4%). Casual BP was measured in 26 (50%), ambulatory BP monitored in 22 (84.6%), self-measured BP in two (3.8%) and self-reported hypertension in two studies (3.8%). Hypertension was the outcome in 16 studies (30.8%), 9 of them defined by BP>140/90 mm Hg. High strain was associated with high BP/hypertension in 27/51 (52.9%) studies. Meta-analysis could be only performed for nine hypertension studies, for which the association was not confirmed neither for high strain (ORc=1.08, 95% CI 0.98 to 1.19), high psychological demands (ORc=1.08, 95% CI 0.98 to 1.19) nor for high control (ORc=1.02, 95% CI 0.94 to 1.11), with no evidence of publication bias. Conclusion There is weak evidence in favour of the association between job strain and BP/hypertension. Comparisons were hampered by methods heterogeneity, particularly: inclusion criteria, data collection and exposure/outcome definition. Further research should include longitudinal design, low and middle-income countries and female workers, still lacking.
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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 | 0.013 | 0.040 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.016 | 0.033 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.001 |
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".