Adolescents’ perspectives on soft drinks after the introduction of the UK Soft Drinks Industry Levy: A focus group study using reflexive thematic analysis
Bibliographic record
Abstract
BACKGROUND: The UK Soft Drinks Industry Levy (SDIL), announced in March 2016 and implemented in April 2018, is a fiscal policy to incentivise reformulation of eligible soft drinks. We aimed to explore perceptions of sugar, sugary drinks and the SDIL among adolescents in the UK post-implementation. METHODS: 23 adolescents aged 11-14 years participated in four focus groups in 2018-2019. A semi-structured topic guide elicited relevant perspectives and included a group task to rank a selection of UK soft drinks based on their sugar content. Braun and Clarke's reflexive thematic analysis was used to undertake inductive analysis. RESULTS: Four main themes were present: 1) Sweetened drinks are bad for you, but some are worse than others; 2) Awareness of the SDIL and ambivalence towards it 3) The influence of drinks marketing: value, pricing, and branding; 4) Openness to population-level interventions. Young people had knowledge of the health implications of excess sugar consumption, which did not always translate to their own consumption. Ambivalence and a mixed awareness surrounding the SDIL was also present. Marketing and parental and school restriction influenced their consumption patterns, as did taste, enjoyment and consuming drinks for functional purposes (e.g., to give them energy). Openness to future population-level interventions to limit consumption was also present. CONCLUSIONS: Our findings suggest that adolescents are accepting of interventions that require little effort from young people in order to reduce their sugar consumption. Further education-based interventions are likely to be unhelpful, in contexts where adolescents understand the negative consequences of excess sugar and SSB consumption.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| 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".