Formal versus informal interventions for challenging behaviour in persons with intellectual disabilities
Bibliographic record
Abstract
BACKGROUND: Although effective, humane treatments exist for persons with intellectual disabilities (ID) who have challenging behaviour, little research has examined the extent to which clients receive formal, documented vs. undocumented interventions. METHODS: Caregivers (of 625 persons with ID living in community and institutional residences in Ontario, Canada) were interviewed to examine the prevalence of different types of interventions. RESULTS: Overall, 55% of the 2506 different interventions (for 1464 target behaviours) were informal (i.e. lacking documented input from a professional, written intervention plans, and systematic evaluation). No significant differences emerged on formality of intervention across participant gender, age, level of ID, and type of residence. There were significantly more informal than formal behavioural interventions and counselling/psychotherapy, and no significant difference in the overall prevalence of formal and informal intrusive procedures. Behaviour control medications were paired more often with formal (67%) than informal interventions for dangerous behaviours. Formal interventions were associated with higher caregiver-reported estimates of behavioural improvement, higher inter-rater agreement on the descriptions of an individual client's target behaviours and interventions, and more caregiver training and supervision. CONCLUSIONS: The low levels of intervention accountability, training and supervision may place many clients with challenging behaviour at increased risk for ineffective and unnecessary restrictive interventions, and physical abuse. The results of this survey stimulated the government to write province-wide standards (that have yet to be implemented).
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".