Depression and interpersonal problems in adolescents: their relationship with alexithymia and coping styles.
Bibliographic record
Abstract
OBJECTIVE: The aim of the present research was to determine whether depression and interpersonal problems had relationships with alexithymia and coping styles in adolescents. METHODS: The study population was randomly selected from all of the adolescent students in the schools of Sari in Iran; 441 adolescents (228 boys and 213 girls) were included in the study. The participants completed the Toronto Alexithymia Scale, the Coping Inventory for Stressful Situations, the Inventory of Interpersonal Problems, and the Beck Depression Inventory. The data was analyzed using descriptive and inferential statistics and was expressed in means, standard deviations, and Pearson correlation coefficient. RESULTS: Alexithymia was related to depression and interpersonal problems; the adolescents who defined themselves as more alexithymic obtained higher scores in depression and interpersonal problems than the adolescents who classified themselves as less- and non-alexithymic. Furthermore, coping styles were related to depression and interpersonal problems. Regression analyses showed that both alexithymia and coping styles accounted for a unique and significant proportion of the variance in depression and interpersonal problems in adolescents. CONCLUSION: These findings support the positive correlation of alexithymia and maladaptive coping styles with depression and interpersonal problems.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".