A Comparison of Alexithymia, Character and Temperament, and Aggression between Addicts and Healthy Individuals
Bibliographic record
Abstract
Aim and Background: The present study was conducted to compare alexithymia, character and temperament, and aggression between addicts and healthy individuals. Methods and Materials: This causal-comparative research was conducted on 80 addicts and 80 healthy individuals. The subjects were selected through convenience sampling method and were matched. The research tools included the Toronto Alexithymia Scale, Temperament and Character Inventory (TCI) (Cloninger et al.), and Buss-Perry Aggression Questionnaire (AGQ). Data were analyzed using MANOVA and ANOVA. Findings: There was a significant difference between addicts and healthy individuals in terms of alexithymia components (difficulty identifying feelings, difficulty describing feelings, and externally-oriented thinking) and aggression components (physical aggression, verbal aggression, and anger and hostility). The scores of alexithymia and aggression components were higher in addicts compared to healthy individuals. Moreover, the scores of damage and novelty seeking components in the character and temperament variable were higher in addcits. The scores of the components of self-leadership, partnership, and persistence were lower in addicts in comparison with healthy individuals. No significant difference was found between the two groups in terms of the components of remuneration, dependency, and self-transcendence. Conclusions: This study, in line with researches focused on investigating the underlying personality aspects involved in addiction, can be helpful in understanding the factors involved in this phenomenon and proposing suitable solutions for the prevention and treatment of addiction.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".