Systematic Review and Meta-Analysis of Interventions in Adaptive Behavior for Children and Adolescents with Intellectual Disabilities
Bibliographic record
Abstract
Intellectual disability (ID) represents limitations in intellectual functioning and in adaptive behavior that originate before 22 years of age. Adaptive behavior is a set of conceptual, social, and practical skills that have been learned and are performed by people in their daily lives. Early intervention, followed by continuous and focused adaptive behavior, can increase the quality of life and improve ID presentation. This systematic review and meta-analysis aim to investigate adaptive behavior interventions for children and adolescents with ID and to analyze their effectiveness. We used Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) Statement guidelines. The 20 identified studies vary in terms of participant characteristics and type and duration of interventions. We performed the meta-analysis by examining the differences in the standardized mean or mean differences. Heterogeneity was tested using the I² test. The meta-analysis results indicate a lack of general consensus in the field of ID studies regarding interventions for adaptive behavior. This does not imply that there are insufficient foundations for the construct or the interventions, just a lack of evidence and consensus for using a specific intervention protocol. In subgroup sensitivity analysis, ABA-based interventions showed significant improvement in the experimental group's adaptive behavior compared to the control group. The findings provide information for researchers and practitioners, highlighting areas that need future research and offering implications for practice.
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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 | 0.019 | 0.056 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.020 | 0.038 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".