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Record W4414565464 · doi:10.1177/00220426251384849

Illicit Drug Use During Travel: A Longitudinal Study of Risk in Emerging Adults

2025· article· en· W4414565464 on OpenAlexaff
Osnat C. Melamed, Sophie D. Walsh, Shmuel Shulman

Bibliographic record

VenueJournal of Drug Issues · 2025
Typearticle
Languageen
FieldMedicine
TopicSubstance Abuse Treatment and Outcomes
Canadian institutionsUniversity of TorontoCentre for Addiction and Mental Health
Fundersnot available
KeywordsLongitudinal studyNoveltyVulnerability (computing)Illicit drugContext (archaeology)Young adultLongitudinal dataHuman factors and ergonomicsDrug

Abstract

fetched live from OpenAlex

International travel by emerging adults is increasingly recognized as a context for experimentation with illicit drugs. This longitudinal study examined predictors of drug use trajectories among 249 young adults traveling to South America or Southeast Asia. Participants completed assessments before departure and after their return. Latent profile analysis identified three use trajectories: Stable Low (48.4%), Experimental Increasing (28.4%), and Consistently High (23.2%). Use of illicit substances such as cocaine and LSD increased markedly during travel in the Consistently High group. Higher novelty seeking and lower commitment to developmental goals predicted membership in this group, while elevated depressive symptoms predicted membership in the Experimental Increasing group, which showed a temporary escalation. These findings highlight the role of personality, motivation, and emotional vulnerability in shaping responses to permissive environments. This study contributes to international drug research by identifying at-risk youth and informing targeted prevention strategies in youth health, and public drug policy.

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 score0.019
Threshold uncertainty score0.474

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
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 head0.019
GPT teacher head0.317
Teacher spread0.298 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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