Relationship among indecisiveness, perfectionism, and hoarding symptoms in individuals with and without hoarding disorder
Bibliographic record
Abstract
Cognitive-behavioral approaches to understanding hoarding disorder propose that indecisiveness driven by a fear of making mistakes about discarding may contribute to hoarding psychopathology. The current study examined the relationship between indecisiveness, hoarding, and related constructs in a sample of individuals with hoarding disorder. Forty individuals with hoarding disorder and 36 individuals without hoarding disorder completed questionnaires measuring hoarding symptoms, depression symptoms, indecisiveness, and perfectionism. Results indicated that individuals with versus without hoarding disorder demonstrated significant differences in indecisiveness and some types of perfectionism. This group difference in indecisiveness disappeared when controlling for perfectionism, but not vice versa. Follow-up analyses controlling for OCD symptoms suggest that these main findings may be true only for those with both OCD and hoarding symptomatology. These results suggest that perfectionism may play an important role in the relationship between indecisiveness and hoarding disorder, shedding light on possible mechanisms behind hoarding symptoms, and offering possible treatment targets. • Indecisiveness and hoarding scores were significantly correlated for those with hoarding. • Individuals with hoarding self-reported significantly higher perfectionism and indecisiveness scores compared to individuals without hoarding. • The group difference in indecisiveness disappeared when controlling for perfectionism. • The group difference in perfectionism did not disappear when controlling for indecisiveness.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".