Covid-19 anxiety predicts burnout among university students: The mediating roles of hope, adaptability, and anti-mattering
Bibliographic record
Abstract
The COVID-19 pandemic negatively impacted various aspects of mental health among university students, including their academic performance. The transition to online learning, changes in tasks, and isolation at home all contributed to increased burnout among students. The current study aimed to test the association between COVID-19 anxiety and burnout among university students, and whether hope, adaptability, and anti-mattering mediate the association between COVID-19 anxiety and burnout. The study involved 450 university students from three states Canada, Russia, and Iran, consisting of 390 females and 60 males. Among the participants, 9.8% had a higher diploma, 63.8% held a master’s degree, and 2.2% possessed a PhD. Results of the correlational analysis that COVID-19 anxiety was positively correlated with burnout (r = 0.31, p < .01) and anti-mattering (r = 0.44, p < .01). Conversely, COVID-19 anxiety was negatively correlated with hope (r = −0.20, p < .01) and adaptability (r = −0.10, p < .05). Regarding mediation analysis, the findings revealed that hope, adaptability, and anti-mattering mediated the association between COVID-19 anxiety and burnout among university students. The findings of the current study emphasize the need to promote hope, social adjustment, and a mattering among university students, as these factors could help enhance their mental health and prevent issues such as substance abuse, which students might resort to as negative coping strategies to deal with psychological stress and burnout related to pandemics.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".