Persistence of self‐injury, aggression and property destruction in children and adults with tuberous sclerosis complex
Bibliographic record
Abstract
BACKGROUND: Individuals with tuberous sclerosis complex (TSC) are at increased risk of developing self-injurious behaviour. The persistence of this deleterious behaviour over years is reported in aetiologically heterogeneous samples to be between 60% and 80% but is unknown for TSC. METHOD: In this study, we determined the 3-year persistence of self-injury in a sample (n = 52) of children (with and without ID) and adults (with ID) with TSC and examined characteristics associated with persistence. RESULTS: Findings for self-injury were contrasted to those for aggression and property destruction to examine the specificity of results to this behaviour. Self-injury was persistent in 84.6% of those with TSC who showed this behaviour, in contrast to 66.7% both for aggression and destruction. Persistent self-injury was associated with poor self-help skills, greater overactivity/impulsivity and more behavioural indicators of pain. These latter two characteristics were also associated with persistent aggression. No characteristics were associated with persistence of property destruction. CONCLUSION: These findings suggest that self-injurious behaviours in individuals with TSC, together with aggressive and destructive behaviours, are highly persistent and would benefit from targeted intervention. Poor adaptive skills, overactivity/impulsivity and painful health conditions may differentiate those at most risk for persistent self-injury or aggression.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".