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Record W7084622411 · doi:10.17605/osf.io/83h72

What are the primary biopsychosocial and structural factors contributing to youth substance use initiation?

2025· other· en· W7084622411 on OpenAlexaboutno aff

Bibliographic record

VenueOpen Science Framework · 2025
Typeother
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural risk and resilience
Canadian institutionsnot available
Fundersnot available
KeywordsBiopsychosocial modelVulnerability (computing)HarmPsychological interventionAddictionSubstance useSubstance abusePublic healthPoison control

Abstract

fetched live from OpenAlex

Canada is facing a national public health emergency due to a significant rise in substance-related overdoses, with illicit drug overdoses now the leading cause of death among youth aged 10 to 18 in Western Canada. Understanding risk and protective factors that contribute to youth substance initiation can help identify interventions focused on prevention and harm reduction. The biopsychosocial model of addiction can be used to understand these risk and protective factors. This framework addresses the interconnected influences of biological, psychological, and social factors on a youth’s susceptibility to substance use initiation. Guided by Arksey and O’Malley’s methodological framework and in consultation with a librarian, multiple databases will be searched and articles will be screened using Covidence. Data will be extracted on individual and contextual factors shaping youth vulnerability to alcohol and nicotine (vaping and smoking), including social, cultural, structural, and psychological dimensions, with attention to differences by substance and vulnerability subgroup. A descriptive analysis will explore patterns across substances and vulnerability subgroups, providing a comprehensive overview to inform the subsequent qualitative interviews and survey development.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.124
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0020.001
Scholarly communication0.0030.001
Open science0.0030.001
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 head0.029
GPT teacher head0.286
Teacher spread0.257 · 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.

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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