Predictors of psychological and physiological measures of graduate student health during COVID-19
Bibliographic record
Abstract
Introduction The COVID-19 pandemic brought on higher-than-normal levels of anxiety and depression, especially among graduate students whose academic trajectory was disrupted. However, not all graduate students were affected and therefore, it is important to identify potential protective factors. Method We recruited 61 graduate students whose research was directly impacted by the pandemic and examined their change in academic stressors since the onset of the pandemic. Hierarchical regression analyses were used to evaluate how perceived academic stressors brought on by the COVID-19 pandemic impacted anxiety, depression, and heart rate variability (HRV), and whether physical activity and trait resiliency independently buffered against the effects of stress. Results Graduate students who reported greater changes in academic stressors since the onset for the pandemic were more anxious and depressed. Moderate-intensity physical activity explained significant variance in anxiety whereas resiliency explained significant variance in both anxiety and depression. HRV was higher in males than females, aligning with sex differences in vulnerability to stress and mental illness. Conclusion Overall, the results suggest that resiliency and physical activity may offer unique protection against symptoms of anxiety and depression in graduate students experiencing increased academic stress during COVID-19. Institutions of higher education should consider investing in programs that encourage physical activity and promote resiliency by teaching mindfulness, stress management, and cognitive behavioral approaches.
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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 | 0.001 | 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".