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Record W2256299580 · doi:10.18192/riss-ijhs.v4i1.1218

Parental and Peer Influences on Adolescent Smoking: A Literature Review

2014· review· en· W2256299580 on OpenAlexaffvenue
Cailin Mulvihill

Bibliographic record

VenueRevue interdisciplinaire des sciences de la santé - Interdisciplinary Journal of Health Sciences · 2014
Typereview
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsPsychologyDevelopmental psychologyAddictionAffect (linguistics)Perspective (graphical)Peer groupPeer influenceSocial influencePeer pressurePublic healthSocial supportSocial psychologyMedicinePsychiatry

Abstract

fetched live from OpenAlex

<p>Smoking cigarettes has been widely accepted as a negative health behaviour associated with many serious risks. Adolescent smoking is of particular interest from a public health perspective as the initiation of smoking in adolescence has been associated with higher addiction rates in adulthood. This review of the literature will examine the influence of social support networks, particularly parents and peers, on the initiation and escalation of adolescent smoking. The influence of social support networks primarily operates through the social learning theory, in which the adolescent mimics the behaviour of those in their social network. The literature suggests that while parents are more influential in young adolescence, peers become the main source of influence in later adolescence through processes known as peer selection and peer influence. Parents can positively affect adolescents’ smoking behaviour through effective communication and maintenance of a healthy parent-child relationship. Peers can also positively influence smoking behaviour through the same mechanisms of peer influence and selection. Knowledge of how parents and peers influence adolescent smoking initiation and escalation can potentially assist in developing public health programming that targets this high-risk behaviour.</p>

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)0.016
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.897
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0160.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.002
Science and technology studies0.0020.006
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.002
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 head0.083
GPT teacher head0.492
Teacher spread0.409 · 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; both teacher heads agree on what is shown here.

Study designSystematic review
Domainnot available
GenreReview

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

Citations7
Published2014
Admission routes2
Has abstractyes

Explore more

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