Reducing Heavy Drinking Through the “Sober Curious” Movement in Australia: Protocol for a Mixed Methods Study
Bibliographic record
Abstract
BACKGROUND: Alcohol consumption is a major public health problem. Its socially engrained nature adds complexity to designing successful reduction approaches. Rather than implementing another intervention, we will undertake a natural experiment on the "sober curious" movement, which gained momentum through social media influencers promoting the idea of reducing alcohol consumption for wellness. We focus on ways to reduce alcohol consumption, through sober curiosity, with 4 heavy-drinking population groups: male construction workers; lesbian, gay, or bisexual women; hospitality workers; and tertiary education students. OBJECTIVE: Aim 1 analyzes the sober curious movement from the "supply side" using qualitative interviews with sober curious stakeholders and a citizen science study of social media content with the 4 case study groups. We will also undertake citizen science and social media studies with a representative sample of the population. Aim 2 examines the sober curious movement from the "demand side" using qualitative interviews with the 4 case study groups to investigate their knowledge and attitudes toward sober curiosity. We will also undertake a representative national survey and ethnography with a representative sample of the population. For aim 3, we will develop evidence-based interventions leveraging sober curiosity and using citizens' juries, industry symposia, and policy symposia to develop feasible public health measures and options tailored to the needs of the 4 case study groups. METHODS: The project involves 3 stages. Stage 1 will examine the supply side of alcohol-free products. A social media analysis of marketing by alcohol-free producers and distributors will generate an understanding of their techniques and population groups they target. In-depth interviews with producers will create evidence on the intentions behind making alcohol-free products available, their target market, and if and how they balance providing nonalcoholic products alongside alcohol. Stage 2 will be a qualitative study with 4 case study groups with high alcohol consumption: male construction workers; lesbian, gay, or bisexual women; hospitality workers; and tertiary education students. This stage will provide a deep understanding of the reasons for alcohol consumption, potential for alcohol-free product use, and possible interventions to sustainably reduce consumption. Stage 3 will involve deliberative symposia with non-alcoholic beverage producers and distributors, representatives from our case study groups, public health professionals, and policy makers to develop co-designed interventions for alcohol reduction. RESULTS: This 3-year research protocol was funded by the Australian National Health and Medical Research Council via their Ideas Grants funding scheme (grant ID GNT2038211). The study will commence in July 2025. Human Research Ethics Committee approval has been granted. CONCLUSIONS: Our study will provide a template for interventions designed to enable reduced drinking within heavy-drinking social worlds with huge potential for scalability of knowledge, expanding the economic, environmental, social, and cultural benefits within and across Australia and internationally. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/72631.
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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 | 0.075 | 0.058 |
| Meta-epidemiology (narrow) | 0.004 | 0.004 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.049 | 0.011 |
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".