Association Between Socioeconomic Position and Depression, Anxiety and Eating Disorders in University Students: A Systematic Review
Bibliographic record
Abstract
Abstract The high prevalence of mental disorders in university students emphasizes the need to explore contributing factors. While socioeconomic position affects mental health in the general population, it is crucial to investigate if the same applies to university students. MEDLINE-Ovid, Embase-Ovid and PsycINFO databases were searched. All original peer-reviewed observational studies quantifying the association between socioeconomic position and depression, anxiety or eating disorders were included without language or date restrictions. After initial screening, eligible studies were selected, data was extracted using a spreadsheet, and their quality was assessed with the Newcastle–Ottawa scale. The results were synthesized narratively. Seventy-eight of 20,465 records identified were included. Most studies were published in English and originated from high and upper-middle-income countries. The most common socioeconomic indicators were family socioeconomic status/class, financial stress, and parental education. Most studies found a positive association between socioeconomic indicators and depressive and anxiety symptoms, but not eating disorders. The quality of the studies was mixed, with a small proportion using validated measurement tools and appropriate sample sizes. This study highlights the importance of measuring socioeconomic position accurately and applying new methods that can reveal the causal pathways and interactions of multiple identities that shape mental health disparities for the university student population. Preregistration A protocol for this review was registered in PROSPERO (CRD42022247394).
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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 | 0.006 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 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".