Neural response to social but not monetary reward predicts increases in depressive symptoms during the COVID‐19 pandemic
Bibliographic record
Abstract
The prevalence of depressive symptoms has increased during the COVID-19 pandemic, especially among those with greater pandemic-related stress exposure; however, not all individuals exposed to pandemic stress will develop depression. Determining which individuals are vulnerable to depressive symptoms as a result of this stress could lead to an improved understanding of the etiology of depression. This study sought to determine whether neural sensitivity to monetary and/or social reward prospectively predicts depressive symptoms during periods of high stress. 121 participants attended pre-pandemic laboratory visits where they completed monetary and social reward tasks while electroencephalogram was recorded. Subsequently, from March to August 2020, we sent eight questionnaires probing depressive symptoms and exposure to pandemic-related stressors. Using repeated-measures multilevel models, we evaluated whether neural response to social or monetary reward predicted increases in depressive symptoms across the early course of the pandemic. Furthermore, we examined whether neural response to social or monetary reward moderated the association between pandemic-related episodic stressors and depressive symptoms. Pandemic-related stress exposure was strongly associated with depressive symptoms. Additionally, we found that blunted neural response to social but not monetary reward predicted increased depressive symptoms during the pandemic. However, neither neural response to social nor monetary reward moderated the association between episodic stress exposure and depressive symptoms. Our findings indicate that neural response to social reward may be a useful predictor of depressive symptomatology under times of chronic stress, particularly stress with a social dimension.
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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 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".