Impact of COVID-19 pandemic-related restrictive measures on overall mental and physical health and well-being, specific psychopathologies and emotional states in representative adult Greek population: Results from the largest multi-wave, online national survey in Greece (COH-FIT)
Bibliographic record
Abstract
BACKGROUND: Greece faced particular COVID-19-pandemic-related challenges, due to specific socio-cultural-economic/public-health factors and drastic restrictive policies. OBJECTIVES: To understand trajectories of overall mental and physical health, well-being, emotional states and individual psychopathology in response to pandemic-related restrictive measures within general adult Greek population across the first two pandemic waves. METHODS: Using multiple time-point cross-sectional data from the "Collaborative Outcomes study on Health and Functioning during Infection Times" (COH-FIT), we examined changes in outcomes from retrospective pre-pandemic ratings (T0) to three distinct intra-pandemic time points (lockdown 1: T1, between lockdowns: T2, lockdown 2: T3). Primary outcomes included WHO-5 well-being scores and a composite overall psychopathology "P-score", followed by a wide range of secondary outcomes. RESULTS: 10,377 participant responses were evaluated, including 2737 representative-matched participants. Statistically significant differences in well-being and overall psychopathology before and after quarantine (T0 vs. T1-T3), as well as across the assessed time frames (T1, T2, and T3) emerged in both samples. Global mental and physical health, individual psychopathology scores (anxiety, depression, PTSD, OCD, panic, mania, mood swings, sleep and concentration problems), emotional states (anger, helplessness, fear of infection, boredom, frustration, loneliness and overall stress scores), BMI and pain scores also showed statistically significant time differences in both samples, with the exemption of self-injury and suicidal attempt scores, showing lower intra-pandemic scores. CONCLUSIONS: This is the largest multi-wave report on well-being, mental and physical health across different pandemic restriction periods in Greece, suggesting a substantial negative effect of lockdowns on most outcomes at least during the acute pandemic waves.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".