Examining the effect of standardized packaging and limited flavour and brand descriptors of e-liquids among youth in Great Britain.
Bibliographic record
Abstract
Significance: E-cigarette vaping among youth has increased in Great Britain (GB). Many vaping products feature bright colours, novel brand names and flavour descriptions, which may appeal to youth. This study examined the impact of fully branded and white standardized e-liquid packaging (including limiting brand and flavour descriptors) on peer interest in trying e-liquids among youth in GB. Methods: A between-subjects experiment was included in the Action on Smoking and Health Smokefree GB Youth 2021 online survey (age 11-18; n=1628). Participants were randomised to view a set of three images of e-liquids from one of three packaging conditions: (1) fully branded (control), (2) white standardized, or (3) white standardized with coded brand names and limited flavour descriptors. Participants were asked which e-liquid they thought people their age would be most interested in trying, participants could also respond “no interest” or “don’t know”. Multinomial regression models were used to examine differences in selecting ‘interest in trying (ref)’, ‘no interest’ or ‘don’t know’ across the different packaging conditions. Results: Compared with fully branded packaging (22.7%), youth had higher odds of reporting no interest among people their age in trying the e-liquids in white standardized packs with brand codes and limited flavour descriptors (30.3%, AOR=2.07[95%CI=1.53-2.79], p<.001), but not white standardized packs with usual descriptors (23.1%, 1.21[0.89-1.65], p=.214). Youth had higher odds of reporting no interest in trying the e-liquids in white standardized packs with brand codes and limited flavour descriptors (30.3%) compared to white standardized packs with usual descriptors (23.1%, AOR=0.59, 95% CI= 0.44-0.79, p<.001).Conclusion: Standardized e-liquid packaging, which also limits flavour and brand descriptors, may reduce the appeal of e-liquids to youth.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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 | 0.000 |
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".