Treatments for the Challenging Behaviours of Adults with Intellectual Disabilities
Bibliographic record
Abstract
OBJECTIVE: To provide an overview and critical assessment of common problems and best evidence practice in treatments for the challenging behaviours (CBs) of adults with intellectual disabilities (IDs). METHOD: Commonly observed problems that present obstacles to successful treatment plans are discussed, followed by an analysis of available research on the efficacy of behavioural and pharmacological therapies. RESULTS: Behavioural and pharmacological interventions are most commonly used when addressing CBs in people with IDs. However, within each of these techniques, there are methods that have support in the literature for efficacy and those that do not. As clinicians, it is important to follow research so that we are engaging in best practices when developing treatment plans for CBs. CONCLUSIONS: One of the most consuming issues for psychiatrists and other mental health professionals who work with people who evince developmental disabilities, such as IDs, are CBs. These problems are very dangerous and are a major impediment to independent, less restrictive living. However, there is a major gap between what researchers show is effective and much of what occurs in real-world settings.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".