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Record W2303926026 · doi:10.7146/pl.v26i1.8202

Addiction in Adolescence: Why don't adolescent addicts turn up for treatment?

2005· article· en· W2303926026 on OpenAlexaff
Mark D. Griffiths, Serge Chevalier

Bibliographic record

VenuePsyke & Logos · 2005
Typearticle
Languageen
FieldPsychology
TopicGambling Behavior and Treatments
Canadian institutionsMcGill University
Fundersnot available
KeywordsAddictionLyingPsychologyWarrantPsychiatryAddiction treatmentAdolescent suicideClinical psychologyMedicineHuman factors and ergonomicsPoison controlMedical emergency

Abstract

fetched live from OpenAlex

It has been well established that prevalence rates of addiction are reportedly higher among youth than adults. It is also widely reported that very few adolescent addicts turn up for treatment. This paper outlines some of the possible reasons as to why this is the case. These are that (i) adolescents don’t seek treatment in general, (ii) treating other underlying problems may help adolescent addiction problems, (iii) attending treatment programs may be stigmatizing for adolescents, (iv) adolescents may have committed suicide before getting treatment, (v) addicts may be lying or distorting the truth when they fill out survey questionnaires, (vi) adolescents may not understand what they are asked in questionnaires, (vii) screening instruments for adolescent addicts may be being used incorrectly, (viii) adolescent addiction may be socially constructed to be non-problematic and (ix) adolescent excesses may change too quickly to warrant treatment.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0040.001

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 head0.092
GPT teacher head0.386
Teacher spread0.294 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations1
Published2005
Admission routes1
Has abstractyes

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