A network meta-analysis of non-invasive brain stimulation interventions for autism spectrum disorder: Evidence from randomized controlled trials
Bibliographic record
Abstract
The efficacy and acceptability of various non-invasive brain stimulation (NIBS) interventions for autism spectrum disorder remain unclear. We carried out a systematic review for randomized controlled trials (RCTs) regarding NIBS for reducing autistic symptoms (INPLASY202370003). Sixteen articles (N = 709) met the inclusion criteria for network meta-analysis. Effect sizes were reported as standardized mean differences (SMDs) or odds ratios with 95 % confidence intervals (CIs). Fourteen active NIBS interventions, including transcranial direct current stimulation (tDCS), repetitive transcranial magnetic stimulation, and transcranial pulse stimulation were analyzed. Only anodal tDCS over the left dorsolateral prefrontal cortex paired with cathodal tDCS over an extracephalic location (atDCS_F3 + ctDCS_E) significantly improved autistic symptoms compared to sham controls (SMD = - 1.40, 95 %CIs = - 2.67 to - 0.14). None of the NIBS interventions markedly improved social-communication symptoms or restricted/repetitive behaviors in autistic participants. Moreover, no active NIBS interventions exhibited significant dropout rate differences compared to sham controls, and no serious adverse events were reported for any intervention.
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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 | 0.015 | 0.041 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.029 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".