Research Patterns in the Treatment of Adults with Problem Behaviour and Intellectual and Developmental Disabilities: A Quantitative Systematic Review
Bibliographic record
Abstract
The purpose of this study was to conduct a quantitative systematic literature review to examine research trends and patterns in the treatment of adults diagnosed with intellectual and developmental disabilities who engage in problem behaviour. The aim of the study was three-fold. First, to comment on adult participant and study characteristic trends in the problem behaviour literature. Second, to report on treatment effectiveness outcomes across various applied behaviour analytic treatments in single-case experimental design research using the Tau Baseline Corrected (Tau-BC) effect size estimate. Finally, to report effect size estimates associated with published and unpublished literature. In this review, descriptive findings of 76 single-case experimental design articles were summarized and Tau-BC effect size estimates were calculated for cases across 65 articles (N=125). Overall, adults were featured in approximately 13% of the sample, and aggression and self-injurious behaviour were the most frequently reported problem behaviours. Functional communication training was the most frequently used treatment. An array of 42 unique multi-protocol treatments were observed across studies. Regarding treatment gains as communicated by effect size, multi-protocol treatments were associated with larger effect sizes (i.e., more effective) compared to single-protocol treatments. Multi-protocol treatments featuring reinforcement elements were more commonly observed in the literature; however, multi-protocol treatments that featured a punishment component coincided with the largest effect size. Implications and directions for future research are discussed.
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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 | 0.109 | 0.391 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.040 | 0.042 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".