Comparison of pathological narcissism and its dimensions in people with substance use disorders with non-clinical people
Bibliographic record
Abstract
Introduction: Pathological narcissism is a sophisticated psychological construct that has two dimensions i.e. grandiosity and vulnerability. Substance use disorders have been related to grandiosity in the literature, but their relationship with vulnerability have not been well known Aim: The aim of this study was to compare pathological narcissism and its dimensions in people with substance use disorders with non-clinical individuals. Method: The research design was analytic-cross sectional study with ex-post facto (comparative) procedure. The statistical population included all people with substance use disorders who had referred to the addiction clinic of Roozbeh Hospital in Tehran from June to January 2019. The sample consisted of 93 people with substance use disorders and 92 people from non-clinical population who were included in the study by convenience sampling method. Both groups completed the Alcohol, Smoking, and Substance Involvement Screening Test, the Pathological Narcissism Inventory & the General Health Questionnaire (for screening in non-clinical population). Data were analyzed using two-way and one-way analysis of variances and Spearmen correlation coefficient in SPSS-24. Results: People with substance use disorders had significantly higher scores in pathological narcissism and its dimensions compared to the non-clinical group (P<0.001). Spearman correlation coefficient between the variables of addiction severity and pathological narcissism (p<0.001), grandiose narcissism (p<0.001) and vulnerable narcissism (p<0.001) were significant and positive. Conclusion: The present study highlighted the importance of evaluation and treatment planning for pathological narcissism especially vulnerability domain in substance use disorders.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".