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Record W4319601111 · doi:10.54097/ehss.v8i.4339

The Influence of Family and Peer on Adolescent Alcohol Addiction

2023· article· en· W4319601111 on OpenAlexaff
Yuwen Niu

Bibliographic record

VenueJournal of Education Humanities and Social Sciences · 2023
Typearticle
Languageen
FieldMedicine
TopicSubstance Abuse Treatment and Outcomes
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsAddictionPsychologyHarmPeer groupAlcoholDevelopmental psychologyAlcohol abuseSubstance abuseClinical psychologyPsychiatrySocial psychology

Abstract

fetched live from OpenAlex

Substance abuse among adolescents is a significant concern today. Alcohol, as the most accessible addictive substance, is also the most likely to lead to adolescent alcohol consumption and eventually to the development of alcohol addiction. Alcohol addiction in adolescents can have harmful, even long-lasting effects on their psychology and physiology. Previous literatures have examined factors contributing to adolescent alcohol addiction from multiple perspectives. However, there are relatively fewer systematic reviews of family and peer influences on adolescent alcohol abuse. Therefore, this article aims to integrate the findings of previous literatures and address the impact of family and peers on adolescent alcohol consumption and alcohol addiction. Parents’ and peers’ open attitudes toward alcohol, negative peer and parent-child relationship, unhappy marital status, as well as peers’ problematic behaviors could assumably increase the likelihood of adolescent alcohol use. By discussing and analyzing two kinds of intimate relationships of adolescents, family and peers, this paper calls for social institutions to devote more attention to adolescent drinking behavior and their social relationships to prevent adolescent alcohol addiction and the harm caused by alcohol abuse. In addition, previous studies were mostly correlational cross-sectional studies, which had some limitations. Future studies could focus on longitudinal experiments and consider excluding confounding factors to obtain causal results.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.273
Threshold uncertainty score0.319

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.108
GPT teacher head0.370
Teacher spread0.263 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2023
Admission routes1
Has abstractyes

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