Depressive personality disorder, dysthymia, and their relationship to perfectionism
Bibliographic record
Abstract
This paper reports the results of two studies in a nonclinical (n=105) and primary care outpatient sample (n=110), in which Depressive Personality Disorder (DPD), Dysthymia, and depression were assessed for their distinctive relationship with perfectionism. Results from both studies found that self-reported DPD, Dysthymia, and depressive symptoms were all intercorrelated, and that DPD, Dysthymia, and depressive symptoms were correlated with three dimensions of perfectionism-Concern over Mistakes, Doubts about Actions, and Parental Criticism. In the nonclinical sample, variance in measures of DPD was predicted by measures of perfectionism after controlling for depression and Dysthymia symptoms. A similar pattern of findings was observed in the primary care sample. This relationship with perfectionism did not occur when Dysthymia or depressive symptoms were predicted. Nevertheless, much of the variance in measures of DPD, Dysthymia, and depressive symptoms is associated with each other and not perfectionism. It is concluded that a common factor or set of factors underlies these disorders, but that DPD may be more strongly related to perfectionism than Dysthymia and depression. As a common factor(s) is identified, measures of DPD and Dysthymia may be refined, thereby increasing the discriminant validity of their measures.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".