Perfectionistic Self‐Presentation and Psychopathology: A Systematic Review and Meta‐Analysis
Bibliographic record
Abstract
Decades of research implicate perfectionism as a risk factor for psychopathology. Most research has focused on trait perfectionism (i.e., needing to be perfect), but there is a growing focus on perfectionistic self-presentation (PSP) (i.e., the need to seem perfect). The current article reports the results of a meta-analysis of previous research on the facets of PSP and psychopathology outcomes (either clinical diagnoses of psychiatric disorders or symptoms of these disorders). A systematic literature search retrieved 30 relevant studies (37 samples; N = 15,072), resulting in 192 individual effect-size indexes that were analysed with random-effect meta-analysis. Findings support the notion of PSP as a transdiagnostic factor by showing that PSP facets are associated with various forms of psychopathology, especially social anxiety, depression, vulnerable narcissism and-to lesser extent-grandiose narcissism and anorexia nervosa. The results indicated that there both commonalities across the three PSP and some unique findings highlighting the need to distinguish among appearing perfect, avoiding seeming imperfect and avoiding disclosures of imperfections. Additional analyses yielded little evidence in the results across studies including undergraduates, community samples and clinical samples. Our discussion includes a focus on factors and processes that contribute to the association between PSP and psychopathology.
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How this classification was reachedexpand
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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.004 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".