Associations between media parenting practices and early adolescent consumption of R-rated movies and mature-rated video games
Bibliographic record
Abstract
OBJECTIVE: To assess whether specific parent media practices are associated with the consumption of R-rated (restricted) movies and mature-rated video game use in early adolescents. METHODS: Data from the Adolescent Brain Cognitive Development (ABCD) Study (N = 10,054, 12-13 years, Year 3, 2019-2021) were analyzed. Ordinal logistic regression models were used to assess associations among media parenting practices and R-rated movies or mature-rated video game use, adjusting for potential confounders. RESULTS: Parental allowance of bedroom screen use (adjusted odds ratio [AOR] 1.44, 95% confidence interval [CI] 1.36-1.53), family mealtime screen use (AOR 1.19, 95% CI 1.13-1.25), and parent screen use (AOR 1.11, 95% CI 1.03-1.20) were positively associated with watching R-rated movies. Parental allowance of bedroom screen use (AOR 1.44, 95% CI 1.36-1.52), family mealtime screen use (AOR 1.26, 95% CI 1.19-1.32), and parent screen use (AOR 1.11, 95% CI 1.02-1.20) were positively associated with playing mature-rated video games. Greater parental monitoring and limiting of screen time were negatively associated with watching R-rated movies (AOR 0.81, 95% CI 0.77-0.85 and AOR 0.73, 95% CI 0.68-0.79 respectively) and playing mature-rated video games (AOR 0.81, 95% CI 0.77-0.86 and AOR 0.72, 95% CI 0.67-0.77). Restricting screen time as a punishment for misbehavior was linked to a higher odds of watching R-rated movies (AOR 1.06, 95% CI 1.01-1.11) and playing mature-rated video games (AOR 1.12, 95% CI 1.07-1.17) while offering screen time to reward for good behavior was negatively associated with watching R-rated movies (AOR 0.95, 95% CI 0.90-0.99). CONCLUSIONS: Media parenting practices such as monitoring or limiting screen use are significantly associated with playing mature-rated video games and watching R-rated movies. Punitive measures, such as restricting screen time as a punishment are slightly associated with increased engagement with such content. These findings highlight the importance of intentional and thoughtful parental strategies in managing children's media consumption effectively.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".