Cumulative exposure to psychosocial stressors at work and global cognitive function: the PROspective Quebec Study on Work and Health
Bibliographic record
Abstract
OBJECTIVES: Psychosocial stressors at work have been proposed as modifiable risk factors for mild cognitive impairment (MCI). This study aimed to evaluate the effect of cumulative exposure to psychosocial stressors at work on cognitive function. METHODS: This study was conducted among 9188 white-collar workers recruited in 1991-1993 (T1), with follow-ups 8 (T2) and 24 years later (T3). After excluding death, losses to follow-up and retirees at T2, 5728 participants were included. Psychosocial stressors at work were measured according to the Karasek's questionnaire. Global cognitive function was measured with the Montreal Cognitive Assessment. Cumulative exposures to low psychological demand, low job control, passive job and high strain job were evaluated using marginal structural models including multiple imputation and inverse probability of censoring weighting. RESULTS: In men, cumulative exposures (T1 and T2) to low psychological demand, low job control or passive job were associated with higher prevalences of more severe presentation of MCI (MSMCI) at T3 (Prevalence ratios (PRs) and 95% CIs of 1.50 (1.16 to 1.94); 1.38 (1.07 to 1.79) and 1.55 (1.20 to 2.00), respectively), but not with milder presentation of MCI. In women, only exposure to low psychological demand or passive job at T2 was associated with higher prevalences of MSMCI at T3 (PRs and 95% CI of 1.39 (0.97 to 1.99) and 1.29 (0.94 to 1.76), respectively). CONCLUSIONS: These results support the deleterious effect of a low stimulating job on cognitive function and the cognitive reserve theory. Psychosocial stressors at work could be part of the effort for the primary prevention of cognitive decline.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".