A review on the reporting and assessment of adverse effects associated with high-definition transcranial direct current stimulation
Bibliographic record
Abstract
Background: High-definition transcranial direct current stimulation (HD-tDCS) is a non-invasive brain stimulation technique that offers increased spatial precision compared to conventional tDCS. As its use has expanded across research and clinical settings, there has been increasing interest in understanding its safety and tolerability. Objective: This review summarizes adverse events related to HD-tDCS in both healthy and clinical populations, focusing on how stimulation intensity, session frequency, and polarity influence tolerability. Results: In healthy populations, HD-tDCS is most often administered at 1-2 mA for 20 min. The most reported adverse events include tingling, itching and burning localized to the site of stimulation, typically described as mild or transient. Studies comparing active and sham stimulation generally report no significant differences in adverse event frequency or intensity, even at higher intensities of 2-3 mA. Reports of severe adverse events are rare, and participant dropout due to discomfort is uncommon. Multi-session protocols show similar safety profiles, suggesting that repeated stimulation does not increase adverse effects. In clinical populations HD-tDCS is typically delivered across multiple sessions. Reported adverse events are mild and transient, with few reports of severe outcomes. Polarity-specific comparisons suggest that anodal and cathodal stimulation are similarly tolerated, with no notable differences in adverse event profiles. Conclusion: Overall, current evidence indicates that HD-tDCS is a safe and well-tolerated technique across diverse populations and stimulation parameters. Continued use of standardized adverse event reporting will be important to further confirm these findings as clinical application broaden.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".