The need to consume: Hoarding as a shared psychological feature of compulsive buying and binge eating
Bibliographic record
Abstract
INTRODUCTION: Compulsive buying and binge eating are two frequently co-occurring psychiatric conditions. Hoarding, which is the psychological need to excessively gather and store items, is frequently associated with both compulsive buying severity and binge eating severity. In the present study, we explored whether different dimensions of hoarding are a shared feature of compulsive buying and binge eating. METHOD: Participants consisted of 434 people seeking treatment for compulsive buying disorder. Registered psychiatrists confirmed the diagnosis of compulsive buying through semi-structured clinical interviews. Participants also completed measures to assess compulsive buying severity, binge eating severity, and dimensions of hoarding (acquisition, difficulty discarding, and clutter). Two-hundred and seven participants completed all three measures. RESULTS: Significant correlations were found between compulsive buying severity and the acquisition dimension of hoarding. Binge eating severity was significantly correlated with all three dimensions of hoarding. Hierarchical regression analysis found that compulsive buying severity was a significant predictor of binge eating severity. However, compulsive buying severity no longer predicted binge eating severity when the dimensions of hoarding were included simultaneously in the model. Clutter was the only subscale of hoarding to predict binge eating severity in step two of the regression analysis. CONCLUSION: Our results suggest that the psychological need to excessively gather and store items may constitute a shared process that is important in understanding behaviors characterized by excessive consumption such as compulsive buying and binge eating.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".