Music engagement is negatively correlated with depressive symptoms during the COVID‐19 pandemic via reward‐related mechanisms
Bibliographic record
Abstract
The COVID-19 pandemic has deeply affected the mental health of millions of people. We assessed which of many leisure activities correlated with positive mental health outputs, with particular attention to music, which has been reported to be important for coping with the psychological burden of the pandemic. Questionnaire data from about 1000 individuals primarily from Italy, Spain, and the United States during May-June 2020 show that people picked music activities (listening to, playing, singing, etc.) most often as the leisure experiences that helped them the most to cope with psychological distress related with the pandemic. During the pandemic, hours of engagement in music and food-related activities were associated with lower depressive symptoms. The negative correlation between music and depression was mediated by individual differences in sensitivity to reward, whereas the correlation between food-related activities and improved mental health outputs was explained by differences in emotion suppression strategies. Our results, while correlational, suggest that engaging in music activities could be related to improved well-being with the underlying mechanism being related to reward, consistent with neuroscience findings. Our data have practical significance in pointing to effective strategies to cope with mental health issues beyond those related to the COVID-19 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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| 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".