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Record W105835125

Prevention of substance use in children/adolescents with mental disorders: a systematic review.

2012· article· en· W105835125 on OpenAlexaffabout
Nadia Salvo, Kathryn Bennett, Amy Cheung, Yvonne Chen, Maureen Rice, Brian Rush, Heather L. Bullock, Anne Bowlby

Bibliographic record

VenuePubMed · 2012
Typearticle
Languageen
FieldMedicine
TopicSubstance Abuse Treatment and Outcomes
Canadian institutionsMcMaster University
Fundersnot available
KeywordsObservational studyRandomized controlled trialMental healthSubstance abusePsychological interventionPsychiatryIntervention (counseling)MedicineSystematic reviewSubstance abuse preventionClinical psychologyPsychologyMEDLINE
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVE: WE CONDUCTED A SYSTEMATIC REVIEW TO ANSWER THE QUESTION: Among youth ≤18 years of age with a mental disorder, does substance use prevention compared to no prevention result in reduced rates of substance use/abuse/disorder (SUD)? The review was requested by the Ontario Ministry of Health and Long-term Care through the Canadian Institutes for Health Research Evidence on Tap program. METHODS: A four-step search process was used: Search 1 and 2: Randomized controlled trials (RCTs) that evaluated a SUD prevention intervention in individuals with a mental disorder who were: 1) ≤18 years; or, 2) any age. Search 3: Observational studies of an intervention to prevent SUD in those with mental disorder. Search 4: RCTs that evaluated a SUD primary prevention skills-based intervention in high-risk youth ≤18 years. RESULTS: Searches 1 and 2: one RCT conducted in youth was found; Search 3: two observational studies were found. All three studies reported statistically significant reductions in substance use. Search 4: five RCTs were found with mixed results. Methodological weaknesses including inadequate study power may explain the results. CONCLUSIONS: Little is known about effective interventions to prevent SUD in youth with a mental disorder. Effective SUD primary prevention programs exist and should be evaluated in this high-risk group.

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)0.011
metaresearch head score (Gemma)0.044
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.013
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.044
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0080.006
Bibliometrics0.0080.008
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.022
GPT teacher head0.248
Teacher spread0.226 · 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 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

Citations17
Published2012
Admission routes2
Has abstractyes

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