A comparison of the effect of two types of brief psychodynamic group therapy on perfectionism-related attitudes, self-relatedness, and self-esteem
Bibliographic record
Abstract
Objective: This randomized controlled trial investigated the efficacy of dynamic relational group therapy (DRT) relative to group psychodynamic supportive therapy (PST) in improving perfectionism-related attitudes and components of the perfectionistic self-relationship. Method: Based on a comprehensive conceptualization of perfectionism, 80 community-recruited, highly perfectionistic individuals were randomly allocated to 12 sessions of group DRT (n = 41; 5 groups) or group PST (n = 39; 5 groups). Patients completed measures of dysfunctional attitudes, self-criticism, self-esteem, and self-reassurance at pre-, mid-, and post-treatment, and six months post-treatment. Results: Multigroup latent growth curve modeling revealed significant (p < .05) decreases in dysfunctional attitudes, concern over mistakes, two types of self-criticism, and self-esteem problems, along with a significant increase in self-reassurance, from pre-treatment to six-month follow-up in both DRT and PST. Moderate-to-large between-group differences favoring DRT over PST were found for dysfunctional attitudes and self-reassurance. A majority of patients in both conditions maintained reliable improvement at six-month follow-up in dysfunctional attitudes, concern over mistakes, and self-criticism focused on inadequacy. Conclusion: Findings provide evidence for the use of psychodynamic group therapy approaches in treating perfectionism-related attitudes and self-relational elements of perfectionism, and support the relative efficacy of DRT for dysfunctional attitudes and self-reassurance.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".