Personality Traits and Identity Styles in Methamphetamine-Dependent Women: A Comparative Study
Bibliographic record
Abstract
BACKGROUND: Studies over the past two decades have shown that various personality traits of substance-dependent men measure differently than compared to normal individuals. However fewer studies have addressed the role of identity as an influential factor in the onset and continuation of drug dependency. METHODS: The objective of this study was to compare the Big Five personality factors and identity styles in methamphetamine dependent women and non-user group. Forty eight methamphetamine dependent women under treatment in Welfare Organization's residential centers filled out the NEO Five-Factor Inventory (NEO-FFI) and the Berzonsky's Identity Style Inventory. They were compared with 48 non-dependent women who were matched in terms of age, education, marital status, and occupation. Data was analyzed with t student test. Statistical analyses were performed using the SPSS V.16 software. Differences were considered significant at P<0.05. RESULTS: Results found that methamphetamine dependent woman had significantly higher levels of neuroticism and lower levels of conscientiousness, agreeableness and openness to experience compared to normative sample of female respondents .In addition, mean scores of diffuse/avoidant identity style in methamphetamine user women was significantly higher than non-user group. This is while non-user women had a significantly higher mean in normative identity style. CONCLUSION: Identity styles along with personality traits can be a key role in drug use in women in this study. Therefore, enhancing understanding about the role of identity can be helpful in treatment programs especially in harm reduction approaches.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".