The use of transcranial direct current stimulation (tDCS) to reduce impulsivity and aggression in adults with mild intellectual developmental disabilities: the tDCS-RIADD randomised controlled trial protocol
Bibliographic record
Abstract
BACKGROUND: Challenging behaviours, in particular aggressive behaviours, are prevalent among people with intellectual developmental disabilities. Predictors of challenging behaviours are numerous, including past history of aggression, poor coping skills and impulsivity. Factors like motor or rapid-response impulsivity (RRI) have neurobiological underpinnings that may be amenable to change via neuromodulation using non-invasive brain stimulation techniques like transcranial direct current stimulation (tDCS). METHODS: This study aims to determine the efficacy of anodal tDCS in reducing RRI and incidents of aggression in people with intellectual developmental disabilities (IDD) in residential or hospital settings. Using a single blind, randomised, sham-controlled trial design, adults with IDD, with a history of impulsivity leading to aggression, will be randomised to receive either repetitive anodal or sham tDCS applied to the left dorsolateral prefrontal cortex. Outcome measures assessing impulsivity and aggression will be collected for up to 1 month following the last tDCS session. DISCUSSION: The results of this study may pave the way for developing targeted interventions for impulsivity and aggressive behaviours in people with IDD.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.019 | 0.002 |
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".