Real-Time Exposure to Alcohol Content in Digital Media in Adolescents: Protocol for a Multiburst Ecological Momentary Assessment Study
Bibliographic record
Abstract
BACKGROUND: Digital media frequently contains positive portrayals of alcohol content, which has been shown to be associated with alcohol-related cognitions and behaviors. Because youth are heavy media consumers and have access to unsupervised, repeat viewing of media content on their personal mobile devices, it is critical to understand the frequency of encountering alcohol content in adolescents' daily lives and how adolescents engage with the content. OBJECTIVE: This paper outlines the study protocol for examining adolescents' exposure to alcohol-related content in digital media within their natural environments. METHODS: Adolescents (N=302; 31.8% boys, 16.2% nonbinary, 51.3% girls; 25.8% Asian, 3.6% American Indian, 21.5% Black, 4.6% other, 52% White, 25.8% Hispanic or Latinx; mean age 16.21, SD 0.77 y) enrolled in high school were recruited through social media to participate in a prospective study involving bursts of ecological momentary assessment (EMA) reports coupled with longer surveys. We conducted group orientation sessions via videoconference and online surveys, followed by a 21-day EMA period that included scheduled reports across 4 daily time blocks, as well as self-initiated reports on media exposure. Reports of alcohol content exposure included details about the platform, level of engagement, source characteristics, beliefs and perceived norms about the content, the viewing context, and whether the content was sponsored or branded. The participants submitted exposures to alcohol content as an image (screenshot or photo) or text description to be objectively coded. The participants completed a weekly online survey assessing alcohol use and related cognitions. EMA reports will be merged with coded image and text entries and with data from baseline, weekly, and follow-up surveys. Self-reported alcohol exposure will be explored descriptively, and differences in exposure tested across subgroups. Event-level data will be compared with random prompt data to examine differences at times of exposure versus nonexposure. Prospective associations between media alcohol content exposure and alcohol use will be explored over 1-week and 4-month time frames. Mediation of the association between media alcohol exposure and drinking will be tested to explore putative mechanisms. RESULTS: EMA data collection took place from February 2022 to August 2023. Data management and preliminary analysis are ongoing. Preliminary data were disseminated through conference presentations in 2024-2025 and manuscripts are ongoing with full results anticipated to be published in 2025-2026. CONCLUSIONS: By characterizing adolescents' real-world exposure to alcohol content in the media, the study provides critical information to develop and implement interventions to target youth behavior that are well suited to delivery via mobile devices. Next steps are to conduct focus groups to understand participants' lived experience of exposure to media alcohol content and reactions to proposed intervention targets. This study and subsequent qualitative work will launch a program of research to counter the effects of alcohol-related media exposure as experienced by adolescents in an effort to minimize underage alcohol involvement. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/50649.
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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 | 0.025 | 0.016 |
| Meta-epidemiology (narrow) | 0.004 | 0.004 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.031 | 0.009 |
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".