Enhancing Adolescent's Emotion Regulation with Dialectical Behavior Therapy's Skill Training: The Applications across Borderline, Mild, and Moderate Intellectual Disability
Bibliographic record
Abstract
Intellectual disability (ID) is characterized by significant limitations in intellectual and adaptive functioning emerging before the age of eighteen-years-old. Known as a pervasive developmental disorder, the disability disturbs the individual's functioning on a wide range of cognitive and social realms, which further result in failure at school and interpersonal relationships. Nonetheless, the capacity for emotion regulation (ER) serves as a key role in supporting the individual's adaptation despite having a disability. Researches have found that ER can be taught as a skill for those with ID, specifically using Dialectical Behavior Therapy’s (DBT) skill training as the basis for the program. Therefore, this study aims to examine further the application of this DBT program and its effectiveness in enhancing ER skills. The programs were delivered to three participants of adolescent aged (9-17 years old) in Indonesia, each having a moderate ID, mild ID, and borderline intellectual functioning (BIF). Using a single case study design (A-B-A procedure) where participants' ER skills were measured before and after the program, these studies showed the program was effective. However, in terms of application, it is noteworthy to highlight the adjustments needed during the program's delivery, considering the degree of disability. These adjustments are found in the program sequences, modality used for the program, the evaluation method used to record the participants' improvements, and the degree of skills developed. This paper examines these variations in depth to shed light on the applicability of DBT's program as in improving ER for individuals with ID and BIF.
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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 | 0.000 |
| 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 | 0.001 |
| 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".