Investigating the relationships between alexithymia characteristics, meta-cognitive features and mental problems in high school students in Istanbul
Bibliographic record
Abstract
Objective: To evaluate the relationships between alexithymic personality traits and meta-cognitive problems, and psychological and behavioral problems associated with alexithymia in adolescents. Methods: This cross-sectional study was conducted on 570 high school students (58% female, n=331; 42% male, n=239) in five high schools in Istanbul. Toronto Alexithymia Scale (TAS-20), Meta-Cognition Questionnaire for Children and Adolescent (MCQ-C) and Strength and Difficulties Questionnaire (SDQ) were used. The parents were asked to complete Sociodemographic Questionnaire. Statistical analysis was performed with SPSS 24 program and statistical significance level was set at p<0.05 and p<0.001. Results: There was no significant difference in terms of age between the alexithymia group (58% female, n=63; 42% male, n=46) and the comparison group (58% female, n=268; 42% male, n=193). Also, there was no significant relationship between gender and alexithymia. Negative meta-worry, superstition beliefs, punishment and responsibility beliefs and total meta-cognitive problem scores of the alexithymia group were significantly higher than comparison group. SDQ total problem scores, attention deficit and hyperactivity scores, peer problems, conduct and emotional problem scores were significantly higher; pro-social behavior scores were significantly lower in the alexithymia group compared to the comparison group. Total TAS-20 scores were positively correlated with total MCQ-C scores and total SDQ scores, significantly. Additionally, total scores of the MCQ-C and SDQ significantly predict the alexithymia. Conclusion: Meta-cognition abilities have functions in checking and regulating the emotions as well as regulating the cognitive processes. It should be kept in mind that the core feature of the individuals with alexithymia is the lack of identifying and expressing emotions, therefore it may be suggested that meta-cognitive problems increase the risk of alexithymia. In addition, the results indicated that alexithymia is frequently associated with attention deficit and hyperactivity, emotional and behavioral problems in adolescents. These results indicate that focusing on meta-cognitive errors may increase the effectiveness of treatment of the adolescents with alexithymia. Additionally, mental and behavioral problems accompanying the alexithymia should not be overlooked.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".