Prospective association between screen use modalities and substance use experimentation in early adolescents
Bibliographic record
Abstract
BACKGROUND: There are limited large-scale, prospective analyses examining contemporary screen use and substance use experimentation in early adolescents. The current study aimed to determine associations between eight forms of contemporary screen modalities and substance use experimentation one year later in a national cohort of 11-12-year-olds in the United States. METHODS: The sample consisted of 8006 early adolescents (47.9 % female and 41.6 % racial/ethnic minority) from the prospective cohort data of the Adolescent Brain Cognitive Development (ABCD) Study. Logistic regression analyses were conducted to evaluate the prospective associations between screen time (eight different types and total) in Year 2 and substance use experimentation (alcohol, nicotine, cannabis, any substance use) in Year 3, adjusting for covariates and Year 2 substance use experimentation. RESULTS: Total screen time was prospectively associated with alcohol, nicotine, and cannabis experimentation. Each additional hour spent on social media (AOR 1.20; 95 % CI 1.14-1.26), texting (AOR 1.18; 95 % CI 1.12-1.24), and video chatting (AOR 1.09; 95 % CI 1.03-1.16) was associated with higher odds of any substance experimentation. Social media use and texting were also associated with higher odds of alcohol, cannabis, and nicotine experimentation; however, television/movies, videos, video games, and the internet were not. Moreover, video chatting was associated with higher odds of cannabis and nicotine experimentation. CONCLUSIONS: Our findings indicate that digital social connections, such as via social media, texting, and video chatting, are the contemporary screen modalities that are associated with early adolescent substance experimentation. Future research could explore the mechanisms underlying these associations to inform intervention strategies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| 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".