The associations between parenting practices and adolescent alcohol use across mid- and late adolescence: A cohort study from Sweden
Bibliographic record
Abstract
Background and aims: The aim of the present study is to examine the associations between parenting practices and adolescent alcohol use in a longitudinal sample of adolescents from Sweden. Data and methods: A prospective longitudinal sample of 3,999 adolescents in a nationwide study (2017-2019) in Sweden filled out questionnaires. Baseline data (T1) was collected at age 15/16 and a two-year follow-up (T2) was conducted at age 17/18. Alcohol use was measured with AUDIT-C. Parental support and monitoring was measured at both time points with two questions for each dimension. Cross-sectional and prospective associations are examined using linear regressions. Findings: A significant negative association was found for both support and monitoring at both time-points in the crude models. Only monitoring remained significant in the adjusted models. Monitoring at T1 had a significant negative association with alcohol use at T2. Increases in both parenting practices between T1 and T2 was significantly associated with lower alcohol use at T2. Conclusions: Parenting factors during adolescence are closely associated with adolescent drinking. These findings underscore the importance of ongoing parental engagement, particularly in terms of parental monitoring, throughout mid- and late adolescence to prevent drinking.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".