The effects of beliefs regarding drug assignment in experimental and field studies of nicotine delivery devices: A review
Bibliographic record
Abstract
The placebo effect of a psychoactive drug can be defined as the effect of expecting the drug in the absence of its pharmacological actions. As nicotine is widely believed to be the primary factor driving cigarette smoking, smokers are likely to expect nicotine to alleviate craving and withdrawal. The present review examines the extent to which any observed effects of nicotine, and especially its craving- and withdrawal-reducing effects, can be attributed to placebo. We begin by reviewing studies that examined the placebo effects of nicotine in the laboratory and follow with a review of potential placebo effects that are typically not controlled in placebo-controlled studies of nicotine replacement therapy (NRT). In laboratory studies, nicotine instructions decrease tobacco smoking, craving and/or withdrawal, while nicotine-specific effects have not been consistently reported. In field trials of NRT, there is a general failure to assess smokers' beliefs regarding their drug assignment. This omission makes it difficult to unequivocally attribute findings of placebo-controlled NRT studies to the physiological effects of nicotine. In sum, our review indicates that the placebo effects of nicotine, and specifically nicotine content expectations, may account for many of the benefits associated with nicotine delivery devices in both laboratory and field studies.
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".