A systematic review of preventive interventions regarding mental health issues in organizations
Bibliographic record
Abstract
The most recent review of the workplace prevention literature was published two decades ago. Since then, interest has been growing in the business and research communities in preventive workplace interventions. At the same time, there has been an increasing recognition of the complexity of developing workplace interventions. This study's purpose is to assess the literature from 2001 to 2006 using Cottrell's conceptualization to: 1) conduct a systematic review of the most recent literature, 2) describe the preventive psychological interventions for workers, 3) summarize the significant work- and health-related outcomes associated with these interventions, and 4) identify where the significant gaps still exist. Twenty-four studies on primary and secondary interventions regarding mental health issues in organizations were included and analyzed in this systematic review. Eight studies were identified as primary interventions, 14 were identified as secondary interventions, and 2 included both. There was a predominance of studies utilizing skills training. One-third of studies used a combination of individual, group and organization level interventions, most often supported by psychosocial intervention or participatory research. These components brought positive and significant results with regard to work and mental health outcomes to workers.
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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 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.012 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".