Effect of transcranial direct current stimulation on the number of smoked cigarettes in tobacco smokers
Bibliographic record
Abstract
BACKGROUND: Recent studies reported that transcranial direct current stimulation (tDCS) applied over the dorsolateral prefrontal cortex (DLPFC) reduced craving and cigarette smoking. We aimed to evaluate whether 3 sessions of tDCS over the DLPFC modulate cigarette smoking which is a critical factor in tobacco smokers. METHODS: In a double-blinded, sham-controlled, parallel experimental study, 22 participants who wished to quit smoking received tDCS with the cathodal over the right DLPFC and anodal over the left DLPFC based on the 10-20 EEG international system (F4, F3) at an intensity of 1.5 mA for 20 minutes during three consecutive days. For sham stimulation, the electrodes placement was the same as for the active stimulation. RESULTS: For the short time interval (8 days after the end of the tDCS regimen), the number of smoked cigarettes was reduced similarly in the active and sham groups (p < 0.001). Also, at the long time-interval (4 months after the end of the tDCS regimen) as compared to pre-tDCS, there was no significant difference in the number of smoked cigarettes in the active (p = 0.806) or the sham (p = 0.573) groups. Overall, there were no statistically significant differences between the active and sham tDCS groups on cigarette smoking. CONCLUSION: These findings suggested that 3 sessions of tDCS over the right and left DLPFC may reduce number of smoked cigarettes for short-time period but might not be significantly more effective than sham to decrease cigarette smoking.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".