Does the content and source credibility of health and risk messages related to nicotine vaping products have an impact on harm perception and behavioural intentions? A systematic review
Bibliographic record
Abstract
AIMS: To systematically review the literature on (i) whether and how various risk messages about nicotine vaping products (NVPs) alter harm perception and behavioural intentions of smokers and non-smokers and (ii) how trust in sources of NVP risk communication affects message reception and behavioural intentions. METHODS: Seven electronic databases and reference lists of relevant articles were searched for articles published up to April 2020. Experimental and quasi-experimental studies on message effects and cross-sectional studies on source credibility were included. The Newcastle-Ottawa Scale and the Evidence Project Risk of Bias Tool were used to assess the quality of observational and intervention studies, respectively. For each outcome variable, we indicated whether there was an effect (as a 'yes' or 'no') and used effect direction plots to display information on the direction of effects. RESULTS: Nicotine addiction messages resulted in greater health and addiction risk perceptions, relative risk messages comparing the health risks of NVPs to cigarette smoking increased the perception that NVPs are less harmful than combustible cigarettes, and a nicotine fact sheet corrected misperceptions of nicotine and NVPs. Smokers' intention to purchase, try or switch to NVPs was higher when exposed to a relative risk message and lower when exposed to nicotine addiction warnings. Trust in NVP risk information from public health agencies was associated with lower odds of; (i) NVP use and (ii) perceiving NVPs as less harmful, whereas those who trusted information from NVP companies were more likely to perceive NVPs as less harmful than combustible cigarettes. CONCLUSIONS: Relative risk messages may help improve the accuracy of harm perceptions of nicotine vaping products and increase smokers' intentions to quit smoking and/or to switch to vaping, although the literature is nascent.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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) | 0.000 | 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 teacher head, 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".