Treatment of Psychopathology in People with Intellectual and other Disabilities
Bibliographic record
Abstract
OBJECTIVE: To review the psychosocial, pharmacological, and other treatments of psychopathology in people with intellectual disabilities (IDs), autism, and other developmental disabilities (DDs). METHOD: Systematic reviews and meta-analyses of psychosocial, pharmacological, and other treatments for people with DDs are reviewed. RESULTS: There is strong evidence for applied behaviour analysis (ABA) and other behavioural treatments of some forms of psychopathology. There is little good evidence to support the effectiveness of cognitive-behavioural therapy, cognitive therapy, sensory interventions, and other forms of psychosocial interventions. Recently, more randomized controlled trials (RCTs) of psychopharmacology have been published, especially with people with autism spectrum disorders. Most RCTs were for externalizing behaviour problems, rather than for psychopathology. These RCTs offer only preliminary support for the effectiveness of pharmacotherapy. No evidence was found for the effectiveness of other biological treatments. CONCLUSIONS: Current research supports the use of ABA and other behavioural interventions for some forms of psychopathology. Evidence for the effectiveness of other interventions is limited or absent.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".