Victimization History and Aggressive Behavior Among Adults with Intellectual Disabilities: The Mediating Role of Mental Health
Bibliographic record
Abstract
Over the past few decades, considerable research has focused on the risk and protective factors associated with aggressive behavior among adults with intellectual disability (ID). The primary objective of this study was to examine the factors underlying the association between victimization history (sexual or physical) and risk for aggressive behavior among adults with ID. To do so, 215 adults with mild or moderate ID living in the community and receiving services from specialized ID agencies were recruited. Through interviews, primary case managers completed measures assessing aggressive behavior and potential mental health problems. Victimization history was assessed through a review of participants' charts and interviews with the primary case manager. Consistent with previous research, we found a significant association between victimization history and aggressive behavior. Mental health problems mediated this association. More specifically, results showed that symptoms of psychosis and personality disorders, but not symptoms of depression, mediated the association between victimization history and outward aggressive behavior. The discussion addresses cognitive and emotional factors that might contribute to the association between victimization history, mental health problems and aggressive behavior among adults with ID. Clinical implications are also 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 | 0.000 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".