Employment and mental health in the working age population: a protocol for a systematic review of longitudinal studies
Bibliographic record
Abstract
BACKGROUND: Employment provides economic security, a social network, and is important for self-identity. A review published by van der Noordt and colleagues in 2014 showed that employment was beneficial for depression and general mental health. However, an updated synthesis including research published in the last decade is lacking. In the planned review, we aim to update, critically assess, and synthesise the current evidence of the association between paid employment (excluding precarious employment) and common mental health outcomes (depression, anxiety, and psychological distress) among the working age population in the labour force. METHODS: We will follow recommended guidelines for conducting and reporting systematic reviews. Four electronic databases (MEDLINE, Embase, APA PsycINFO, and Web of Science) will be searched from 2012, using appropriate MeSH terms and text words related to our inclusion criteria. We will screen the records against predefined eligibility criteria, first by title and abstract using the priority screening function in EPPI-Reviewer, before proceeding to full-text screening. Only studies investigating the longitudinal relationship between employment and common mental health outcomes will be included. We will search for grey literature in OpenAlex and conduct backward and forward citation searches of included studies. The methodological quality of the included studies will be assessed using the Cochrane risk-of-bias tool (RoB 2), Risk Of Bias In Non-randomised Studies of Interventions (ROBINS-I), or the Newcastle-Ottawa scale (NOS). We will conduct a narrative review and, if possible following pre-set criteria, conduct random-effects meta-analyses to estimate the pooled effect of employment on depression, anxiety, and psychological distress, across the included studies. DISCUSSION: An updated review of the association between non-precarious employment and mental health outcomes is needed. In the planned review, we will assess the quality of the included studies and synthesise the results across studies to make them easily accessible to policy makers and researchers. The results from the review can be used to aid in policy decisions and guide future research priorities. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42023405919.
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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 | 0.151 | 0.177 |
| Meta-epidemiology (narrow) | 0.008 | 0.008 |
| Meta-epidemiology (broad) | 0.022 | 0.022 |
| Bibliometrics | 0.024 | 0.026 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.010 | 0.012 |
| Open science | 0.007 | 0.008 |
| Research integrity | 0.010 | 0.010 |
| Insufficient payload (model declined to judge) | 0.065 | 0.014 |
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".