A longitudinal assessment of depression and anxiety in the Republic of Ireland before and during the COVID-19 pandemic
Bibliographic record
Abstract
Few studies have examined changes in mental health before and after the outbreak of COVID-19. We examined changes in the prevalence of major depression and generalized anxiety disorder (GAD) between February 2019 and March-April 2020; if there were changes in major depression and GAD during six weeks of nationwide lockdown; and we identified factors that predicted major depression and GAD across the six-week lockdown period. Nationally representative samples of Irish adults were gathered using identical methods in February 2019 (N = 1020) and March-April 2020 (N = 1041). The latter was reassessed six weeks later. Significantly more people screened positive for depression in February 2019 (29.8% 95% CI = 27.0, 32.6) than in March-April 2020 (22.8% 95% CI = 20.2, 25.3), and there was no change in GAD. There were no significant changes in depression and GAD during the lockdown. Major depression was predicted by younger age, non-city dwelling, lower resilience, higher loneliness, and higher somatic problems. GAD was predicted by a broader set of variables including several COVID-19 specific variables. These findings indicate that the prevalence of major depression and GAD did not increase as a result of, or during the early phase of the COVID-19 pandemic in Ireland.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".