The Collaborative Outcome Study on Health and Functioning during Infection Times (COH-FIT): Results from Cyprus
Bibliographic record
Abstract
Many studies have shown that COVID-19 caused many problems in mental health. This paper presents the results of the Cyprus sample, part of the global initiative named “The Collaborative Outcomes Study on Health and Functioning during Infection Times” (COH-FIT). Methods: The study took place from April 2019 to January 2022, using the Greek version of the online standard COH-FIT questionnaire on 917 Cypriot adults. Weighted t-tests were applied to test the differences between pre-pandemic and intra-pandemic scores using the anesrake package. Results: Participant responses indicated a significant negative impact of the pandemic on measures of mental health (−7.55; 95% CI: −9.01 to −6.07), with worsening in the scores for anxiety (12.05; 95% CI: 9.33 to 14.77), well-being (−11.06; 95% CI: −12.69 to −9.45) and depression (4.60; 95% CI: 2.06 to 7.14). Similar negative effects were observed for feelings of anger (12.92; 95% CI: 10.54 to 15.29), helplessness (9.66; 95% CI: 7.25 to 12.07), fear (22.25; 95% CI: 19.25 to 25.26), and loneliness (12.52; 95% CI: 9.94 to15.11). Increased use of social media (0.89; 95% CI: 0.71 to 1.09), internet (0.86; 95% CI: 0.67 to 1.04), and substance consumption (0.06; 95% CI: 0.00 to 0.11) were reported, along with a significant decrease in physical health (−3.45; 95% CI: −4.59 to −2.32), self-care (−7.10; 95% CI: −9.00 to −5.20), and social function (−11.27; 95% CI: −13.19 to −9.35), including support (−0.72; 95% CI: −1.09 to −0.34) and family function (−7.97; 95% CI: −9.90 to −6.05). Conclusions: The COVID-19 pandemic significantly affected the daily life and emotional well-being of Cypriots. Identifying factors that influence vulnerability and resilience is essential to prioritize mental health support and address the long-term effects of the pandemic.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".