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Selective Personality-Targeted Intervention and the Escalation of Substance Use During Adolescence

2025· article· en· W4417465569 on OpenAlexaffabout
Samantha Lynch, Sherry H. Stewart, Patricia Conrod

Bibliographic record

VenueJAMA Network Open · 2025
Typearticle
Languageen
FieldPsychology
TopicPersonality Traits and Psychology
Canadian institutionsDalhousie UniversityUniversité de MontréalCentre Hospitalier Universitaire Sainte-Justine
Fundersnot available
KeywordsSubstance useIntervention (counseling)Substance abuseAddictionMEDLINE

Abstract

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Importance: Substance use is a leading cause of burden of disease worldwide. Selective prevention programs can help reduce the development of problematic substance use and disorders. Objective: To examine effects of a selective, personality-targeted substance use prevention program on alcohol, cannabis, tobacco, nonmedical opioid, and illicit polysubstance use among adolescents with elevated levels of personality traits associated with frequent and risky substance use. Design, Setting, and Participants: This prespecified secondary analysis of a cluster-randomized clinical trial assessed the effectiveness of a personality-targeted cognitive-behavioral intervention (PreVenture) in reducing substance use during adolescence. Participants included grade 7 students attending 31 secondary schools in the Greater Montreal Area, Canada (2012-2013 school year), who screened as having elevated levels of anxiety sensitivity, hopelessness, impulsivity, or sensation seeking. Schools were randomized to either the intervention (15 schools) or the control group (16 schools). Data were analyzed in January to March 2025. Interventions: Schools delivered a 2-session, personality-targeted group-based cognitive-behavioral intervention designed to help students recognize, challenge, and manage personality-specific emotions, behaviors, and cognitions associated with substance use in adolescence. Main Outcomes and Measures: Self-reported frequency of alcohol, cannabis, smoking tobacco, nonmedical use of opioids, and illicit polysubstance use were measured by the Detection of Alcohol and Drug Problems in Adolescents. Results: A total of 3861 students from 31 schools were screened; 1669 students (847 [50.7%] female; mean [SD] age, 12.83 [0.47] years) were at elevated risk of substance use and included in the intention-to-treat sample. The 31 schools were randomized, with 16 schools with 964 students in the control group and 15 schools with 705 students in the intervention group. Multilevel bayesian mixed-effects models indicated that students in the intervention group had slower increases in the frequency of alcohol (odds ratio [OR], 0.92; 95% credible interval [CrI], 0.85-1.00), cannabis (OR, 0.75; 95% CrI, 0.66-0.86), tobacco smoking (OR, 0.79; 95% CrI, 0.70-0.96), and illicit polysubstance use (OR, 0.56; 95% CrI, 0.35-0.89) over 4 years. Effects did not differ by sex. Conclusions and Relevance: This secondary analysis of a cluster-randomized clinical trial found that personality-targeted interventions protected against the escalation in substance use during adolescence, with similar effects for males and females. Trial Registration: ClinicalTrials.gov Identifier: NCT01655615.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
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)0.0020.000

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 head0.028
GPT teacher head0.331
Teacher spread0.302 · 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 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

Citations0
Published2025
Admission routes2
Has abstractyes

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