Evaluating the Effectiveness of Return-to-Work Interventions for Individuals with Work-Related Mental Health Conditions: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
The workplace is a vital setting to support positive mental health. Mental health conditions in the workforce contribute to decreased work engagement and participation. There is existing literature on return-to-work (RTW) interventions for individuals with work-related mental health conditions, however, there lacks consensus on their effectiveness. Therefore, the primary aim of this systematic review was to synthesize the literature and evaluate the effectiveness of return-to-work interventions on return-to-work rates, quality of life, and psychological wellbeing for individuals with work-related mental health conditions. Selected articles were organized and identified using the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines and the Population/Intervention/Comparison/Outcome (PICO) framework. Quality assessment of the included studies was completed using the Critical Appraisal Skills Programme randomized controlled trials checklist and the Joanna Briggs Institute quasi-experimental studies checklist. A random effects meta-analysis model was performed using DerSimonian-Laird weighting to calculate standard mean difference and risk ratios to assess the impact of RTW interventions on return-to-work rates, absenteeism, stress symptoms, depression symptoms, and quality of life. A total of 28 out of 26,153 articles met the inclusion criteria. Diagnoses for participants in the studies ranged from work-related stress to work-related PTSD following exposure to a psychologically traumatizing event in the workplace. No significant differences were found for the meta-analyses examining return-to-work rates, absenteeism, depression, stress, and quality of life. The most effective interventions were found to be a multi-domain intervention (67% of participants RTW full time) and a health-focused intervention (85% RTW rate). Future research may consider establishing effective interventions to develop programs or policies supporting the RTW of employees and promote mental well-being among employees experiencing work-related mental health conditions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.033 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.013 | 0.003 |
| Bibliometrics | 0.001 | 0.006 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".