Profiles and correlates of aggressive behaviour among adults with intellectual disabilities
Bibliographic record
Abstract
BACKGROUND: Despite the heterogeneity in aggressive behaviours observed among individuals with intellectual disabilities (ID), little attention has been paid to the identification of typologies of aggression among individuals with mild or moderate ID and their associated factors. OBJECTIVE: The goal of the present study was to identify profiles of aggressive behaviour and their psychosocial correlates. METHOD: In this cross-sectional study of 296 adults with mild or moderate ID, information was gathered through interviews with the ID participants, their case manager and a significant other. Client files were also reviewed. RESULTS: Multiple correspondence analysis followed by hierarchical cluster analysis generated six distinct profiles of aggressive behaviour in this sample. The 'violent' group clearly stood out as lacking social and vocational involvement, having more severe mental health problems, high levels of impulsivity and antisocial tendencies compared with all other groups. DISCUSSION: The identification of distinct profiles of aggressive behaviour offers new possibilities for studying risk factors and eventually targeting specific risk prevention strategies.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".