The Effectiveness of Dialectical Behavior Therapy on Cognitive Flexibility and Alexithymia in Aggressive Adolescents
Bibliographic record
Abstract
Objective: Intense emotions following physical, psychological, and cognitive changes in adolescents may lead to aggression. Aggressive adolescents, due to negative experiences in relationships, are at risk for multiple psychological problems. Therefore, the present study aimed to investigate the effectiveness of dialectical behavior therapy on cognitive flexibility and alexithymia in aggressive adolescents. Methods and Materials: This quasi-experimental study employed a pre-test, post-test design with a control group. The statistical population included all high school students (grades 1 and 2) in Shahdad County during the 2021-2022 academic year. Thirty students were selected using convenience sampling from these schools, having scored higher than 78 on the Buss-Perry Aggression Questionnaire. Out of these, 30 students were randomly assigned to experimental (n=15) and control (n=15) groups. The research instruments included the Cognitive Flexibility Inventory (Dennis & Vander Wal, 2010), the Toronto Alexithymia Scale (1994), and the Buss-Perry Aggression Questionnaire. Multivariate analysis of covariance (MANCOVA) was used to analyze the data using SPSS-26 software. Findings: The findings indicated that dialectical behavior therapy had a significant effect on cognitive flexibility and alexithymia in aggressive adolescents (p<0.005). Conclusion: Considering the effectiveness of dialectical behavior therapy on cognitive flexibility and alexithymia in aggressive adolescents, the implementation of intervention methods based on dialectical behavior therapy, particularly for emotional regulation and increasing cognitive flexibility, is recommended in schools and for high school students.
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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 | 0.001 |
| 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".