How personality traits of neuroticism and extroversion predict the effects of the COVID-19 on the mental health of Canadians
Bibliographic record
Abstract
The Coronavirus Disease (COVID-19) epidemic was first detected in China in December 2019 and spread to other countries fast. Some studies have found that COVID-19 pandemic has had adverse mental health consequences. Individual differences such as personality could contribute to people's behaviors during a pandemic. In the current study, we examine how personality traits of neuroticism and extroversion (using the Five-Factor Model as our framework) are related to the mental health of Canadians during the COVID-19 pandemic. Using data from an online survey with 1096 responses, this study performed multiple regression analysis to explore how personality traits of neuroticism and extroversion predict the effects of COVID-19 on the mental health of Canadians. The results showed that personality traits of neuroticism and extroversion are associated with the current mental health of Canadians during COVID-19 pandemic, with extroversion positively related to mental health and neuroticism negatively related to it. Results contribute to the management of individual responses to the COVID-19 pandemic and could help public health services provide personality-appropriate mental health services during this pandemic.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".