The Role of Emotion Regulation Strategies and Behavioral Activation System (BAS) in Social Adjustment of Adolescents With Conduct Disorder
Bibliographic record
Abstract
The purpose of this research was to explain the role of emotion regulation strategies and behavioral activation system (BAS) in social adjustment of adolescents with conduct disorder. The method of study is descriptive-correlation. The statistical population included all junior high school students in Ardabil in 2016. The sampling was conducted by the multistage cluster method and then 50 subjects with conduct disorder were selected as the sample group using this method. Data of the present study were collected using Rutter behavioral disorders questionnaire (form B), students adjustment questionnaire, emotion regulation questionnaire and activation system and behavioral inhibition questionnaire. The obtained data were analyzed using Pearson correlation coefficient test and regression analysis using SPSS software. The findings showed that there is a significant relationship between social adjustment and behavioral activation (BAS) and emotion regulation system (P<0.05). Also, the results of regression analysis showed that behavioral activation and emotion regulation system can significantly explain 16% variances in social adjustment of students with conduct disorders. Accordingly, it can be concluded that behavioral activation and emotion regulation system plays a role in social adjustment.
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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 | 0.001 | 0.000 |
| 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".