Psychological impact of the COVID-19 crisis on young swiss men participating in a cohort study: Differences due to socioeconomic status and work situation
Bibliographic record
Abstract
Introduction The COVID-19 pandemic impacted daily life worldwide. It may also have had a psychological impact, especially on those with less resources already before the crisis and those who reported substantial changes to their work situation. Objectives To investigate whether socioeconomic status before the crisis and changes in work situation during the crisis (unemployment, home-office) are associated with psychological impact in a cohort of young Swiss men. Methods A total of 2345 young Swiss men (mean age = 29) completed assessments shortly before (April 2019 to February 2020) and early during the COVID-19 crisis (May to June 2020). Assessments covered psychological outcomes assessed before and during COVID-19 crisis (depression, perceived stress and sleep quality), and assessed during the crisis (fear, isolation and COVID-19 psychological trauma), socioeconomic status (relative financial status and difficulty to pay bills) before the crisis and changes in work situation (unemployment, home-office). Results About a fifth of the sample were in partial unemployment or lost their job during COVID-19 crisis. Those in partial or full unemployment, those mostly working from home and those with a lower socioeconomic status already prior to the crisis showed overall higher levels of depression, stress, psychological trauma, fear and isolation. Conclusions Even in a country with high social security such as Switzerland, the COVID-19 crisis had a higher psychological impact on those who were already disadvantaged before the crisis or experienced deteriorations in their work situation. Supporting disadvantaged subpopulations during the crisis may help to prevent an amplification of pre-existing inequalities. Disclosure No significant relationships.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".