Common Mental Disorders in the Workforce: Recent Findings from Descriptive and Social Epidemiology
Bibliographic record
Abstract
OBJECTIVE: To review the recent descriptive and social epidemiology of common mental disorders in the workplace, including prevalence, participation, work disability, and impact of quality of work, as well as to discuss the implications for identifying targets for clinical and preventive interventions. METHOD: We conducted a structured review of epidemiologic studies in community settings (that is, in the general population or in workplaces). Evidence was restricted to the peer-reviewed, published, English-language literature up to the end of June 2005. We further restricted evidence to studies that used recent classification systems; then, if evidence was insufficient, we reviewed studies that used standardized psychiatric screening scales. To distinguish this article from recent reviews of health and work quality, we focused on new areas of investigation and new evidence for established areas of investigation: underemployment, organizational justice, job control and demand, effort-reward imbalance, and atypical (nonpermanent) employment. RESULTS: Depression and simple phobia were found to be the most prevalent disorders in the working population. The limited data on rates of participation suggested higher participation among people with depression, simple phobia, social phobia, and generalized anxiety disorder. Depression and anxiety were more consistently associated with "presenteeism" (that is, lost productivity while at work) than with absenteeism, whether this was measured by cutback days or by direct questionnaires. Seven longitudinal studies, with an average sample size of 6264, showed a strong association between aspects of low job quality and incident depression and anxiety. There was some evidence that atypical work was associated with poorer mental health, although the findings for fixed-term work were mixed. CONCLUSIONS: Mental health risk reduction in the workplace is an important complement to clinical interventions for reducing the current and future burden of depression and anxiety in the workplace.
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 | 0.013 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.011 | 0.013 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".