Transcranial direct current stimulation (tDCS) therapy combined with varenicline to improve smoking cessation outcomes: a proof-of-concept double-blind sham-controlled trial
Bibliographic record
Abstract
Abstract Background: Transcranial Direct Current Stimulation (tDCS) targets cortical circuits and has been shown to acutely reduce craving and withdrawal symptoms among smokers. However, the efficacy of tDCS as an adjunct to smoking cessation pharmacotherapy has not been studied. This study aimed to investigate the efficacy of tDCS with anode to the left dorsolateral prefrontal cortex (DLPFC) in combination with varenicline for smoking cessation. Methods: This was a double-blind, sham-controlled randomized clinical trial where 41 healthy smokers were randomized 1:1 to either active tDCS (20 minutes at 2 mA; anode=left DLPFC; cathode=right DLPFC) or sham tDCS for 10 daily sessions over the first 2 weeks plus 5 booster sessions, occurring every two weeks for 10 weeks. All participants were also given 12 weeks of standard varenicline treatment concurrently with tDCS. Target quit date was 2 weeks after starting treatment. The primary outcome was 30-day continuous abstinence at end of treatment. Results: At end of treatment, active tDCS was associated with higher 30-day abstinence than sham (67% vs 38% respectively, p=0.12) in treatment completers. Active tDCS also significantly decreased cigarette consumption over time but had no differential effect on nicotine craving compared to sham. There were no significant adverse events associated with active stimulation compared to sham. Discussion: This is the first study to show the efficacy of adjunct tDCS with pharmacotherapy for smoking cessation, with higher end-of-treatment quit rate than varenicline alone. These novel findings illuminate the potential for tDCS as a treatment option for smoking cessation. Research Category and Technology and Methods Clinical Research: 9. Transcranial Direct Current Stimulation (tDCS) Keywords: tobacco, cessation, varenicline, tDCS
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".