The Role of Metaperception in Personality Disorders: Do People with Personality Problems Know How Others Experience Their Personality?
Bibliographic record
Abstract
Do people with personality problems have insight into how others experience them? In a large community sample of adults (N = 641), the authors examined whether people with personality disorder (PD) symptoms were aware of how a close acquaintance (i.e., a romantic partner, family member, or friend) perceived them by measuring participants' metaperceptions and self-perceptions as well as their acquaintance's impression of them on Five-Factor Model traits. Compared to people with fewer PD symptoms, people with more PD symptoms tended to be less accurate and tended to overestimate the negativity of the impressions they made on their acquaintance, especially for the traits of extraversion, agreeableness, and conscientiousness. Interestingly, these individuals did not necessarily assume that their acquaintance perceived them as they perceived themselves; instead, poor insight was likely due to their inability to detect or utilize information other than their self-perceptions. Implications for the conceptualization, measurement, and treatment of PDs are discussed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".