Emotion-focused coping mediates the relationship between COVID-related distress and compulsive buying
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND AND AIMS: COVID-19 posits psychological challenges worldwide and has given rise to nonadaptive behavior, especially in the presence of maladaptive coping. In the current study, we assessed whether the relationship between COVID-related distress and compulsive buying is mediated by task-focused and emotion-focused coping. We also examined whether these associations were invariant over time as the pandemic unfolded. METHODS: Self-report surveys were administered online in the United States in the first six months of the pandemic (March-October 2020) in sampling batches of 25 participants every three days, resulting in a total sample of N = 1,418 (40% female, mean age = 36.6). We carried out structural equation modeling to assess whether the relationship between distress related to COVID-19 and compulsive buying is mediated by task-focused and emotion-focused coping. Time was used as a grouping variable based on events related to the pandemic in the U.S. to calculate model invariance across three time periods. RESULTS: The results indicated significant mediation between distress, emotion-focused coping, and compulsive buying, but not between task-focused coping and compulsive buying. The mediation model showed excellent fit to the data (χ² = 1119.377, df = 420, RMSEA = 0.059 [0.055-0.064], SRMR = 0.049, CFI = 0.951, TLI = 0.947). Models were not invariant across the three examined time periods. CONCLUSIONS: Our results indicate that compulsive buying is more likely to occur in relation to emotion-focused coping as a response to COVID-related distress than in relation to task-focused coping, especially during periods of increasing distress. However, model paths varied during the course of the pandemic.
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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 | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 it