Social, financial and psychological stress during an emerging pandemic: observations from a population survey in the acute phase of COVID-19
Bibliographic record
Abstract
INTRODUCTION: The negative impacts of COVID-19 have rippled through every facet of society. Understanding the multidimensional impacts of this pandemic is crucial to identify the most critical needs and to inform targeted interventions. This population survey study aimed to investigate the acute phase of the COVID-19 outbreak in terms of perceived threats and concerns, occupational and financial impacts, social impacts and stress between 3 April and 15 May 2020. METHODS: 6040 participants are included in this report. A multivariate linear regression model was used to identify factors associated with stress changes (as measured by the Cohen's Perceived Stress Scale (PSS)) relative to pre-outbreak retrospective estimates. RESULTS: On average, PSS scores increased from low stress levels before the outbreak to moderate stress levels during the outbreak (p<0.001). The independent factors associated with stress worsening were: having a mental disorder, female sex, having underage children, heavier alcohol consumption, working with the general public, shorter sleep duration, younger age, less time elapsed since the start of the outbreak, lower stress before the outbreak, worse symptoms that could be linked to COVID-19, lower coping skills, worse obsessive-compulsive symptoms related to germs and contamination, personalities loading on extraversion, conscientiousness and neuroticism, left wing political views, worse family relationships and spending less time exercising and doing artistic activities. CONCLUSION: Cross-sectional analyses showed a significant increase from low to moderate stress during the COVID-19 outbreak. Identified modifiable factors associated with increased stress may be informative for intervention development. TRIAL REGISTRATION NUMBER: NCT04369690; Results.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".