Rapid assessment of psychological and epidemiological correlates of COVID-19 concern, financial strain, and health-related behavior change in a large online sample
Bibliographic record
Abstract
COVID-19 emerged in November 2019 leading to a global pandemic that has not only resulted in widespread medical complications and loss of life, but has also impacted global economies and transformed daily life. The current rapid response study in a convenience online sample quickly recruited 2,065 participants across the United States, Canada, and Europe in late March and early April 2020. Cross-sectional findings indicated elevated anxiety and depressive symptoms compared to historical norms, which were positively associated with COVID-19 concern more strongly than epidemiological data signifying risk (e.g., world and country confirmed cases). Employment loss was positively associated with greater depressive symptoms and COVID-19 concern, and depressive symptoms and COVID-19 concern were significantly associated with more stringent self-quarantine behavior. The rapid collection of data during the early phase of this pandemic is limited by under-representation of non-White and middle age and older adults. Nevertheless, these findings have implications for interventions to slow the spread of COVID-19 infection.
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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 | 0.004 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".