Post-secondary Student Mental Health During COVID-19: A Meta-Analysis
Bibliographic record
Abstract
The COVID-19 pandemic has posed notable challenges to post-secondary students, causing concern for their psychological well-being. In the face of school closures, academic disruptions, and constraints on social gatherings, it is crucial to understand the extent to which mental health among post-secondary students has been impacted in order to inform support implementation for this population. The present meta-analysis examines the global prevalence of clinically significant depression and anxiety among post-secondary students during the COVID-19 pandemic. Several moderator analyses were also performed to examine sources of variability in depression and anxiety prevalence rates. A systematic search was conducted across six databases on May 3, 2021, yielding a total of 176 studies (1,732,456 participants) which met inclusion criteria. Random-effects meta-analyses of 126 studies assessing depression symptoms and 144 studies assessing anxiety symptoms were conducted. The pooled prevalence estimates of clinically elevated depressive and anxiety symptoms for post-secondary students during the COVID-19 pandemic was 30.6% (95% CI: 0.274, 0.340) and 28.2% (CI: 0.246, 0.321), respectively. The month of data collection and geographical region were determined to be significant moderators. However, student age, sex, type (i.e., healthcare student vs. non-healthcare student), and level of training (i.e., undergraduate, university or college generally; graduate, medical, post-doctorate, fellow, trainee), were not sources of variability in pooled rates of depression and anxiety symptoms during the pandemic. The current study indicates a call for continued access to mental health services to ensure post-secondary students receive adequate support during and after the COVID-19 pandemic. Systematic Review Registration: PROSPERO website: https://www.crd.york.ac.uk/prospero/ , identifier: CRD42021253547.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.006 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 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) | 0.007 | 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".