Noninvasive brain stimulation in children and adults with attention-deficit/hyperactivity disorder: a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Repetitive transcranial magnetic stimulation (rTMS) or transcranial direct current stimulation (tDCS) could provide treatment alternatives to stimulant medication for attention-deficit/hyperactivity disorder (ADHD), given some evidence for improvements in cognition and clinical symptoms. However, despite a lack of solid evidence for their use, rTMS and tDCS are already offered clinically and commercially in ADHD. This systematic review and meta-analysis aimed to critically appraise rTMS and tDCS studies in ADHD to inform good research and clinical practice. METHODS: A systematic search (up to February 2019) identified 18 studies (rTMS 4, tDCS 14; 311 children and adults with ADHD) stimulating mainly the dorsolateral prefrontal cortex (dlPFC). We included 12 anodal tDCS studies (232 children and adults with ADHD) in 3 random-effects meta-analyses of cognitive measures of attention, inhibition and processing speed. RESULTS: The review of rTMS and tDCS showed positive effects in some functions but not others, and little evidence for clinical improvement. The meta-analyses of 1 to 5 sessions of anodal tDCS over mainly the left or bilateral dlPFC showed trend-level improvements in inhibition and processing speed, but not in attention. LIMITATIONS: Heterogeneity in stimulation parameters, patient age and outcome measures limited the interpretation of findings. CONCLUSION: The review and meta-analysis showed limited evidence that 1 to 5 sessions of rTMS and tDCS, mostly of the dlPFC, improved clinical or cognitive measures of ADHD. These findings did not support using rTMS or tDCS of the dlPFC as an alternative neurotherapy for ADHD as yet. Larger, multi-session stimulation studies identifying more optimal sites and stimulation parameters in combination with cognitive training could achieve larger effects.
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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 | 0.018 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.024 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".