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Record W4405106340 · doi:10.1080/07448481.2024.2435936

Negative urgency increases risk for coping-motivated cannabis outcomes in socially anxious male emerging adult cannabis users

2024· article· en· W4405106340 on OpenAlexaff
Alanna Single, Natalie Mota, Matthew T. Keough

Bibliographic record

VenueJournal of American College Health · 2024
Typearticle
Languageen
FieldPsychology
TopicAnxiety, Depression, Psychometrics, Treatment, Cognitive Processes
Canadian institutionsYork UniversityUniversity of Manitoba
Fundersnot available
KeywordsCannabisPsychologyCoping (psychology)AnxietyModerationClinical psychologyYoung adultCannabis DependenceSocial supportPsychiatryDevelopmental psychologySocial psychology

Abstract

fetched live from OpenAlex

Tension reduction theory suggests that socially anxious emerging adults use cannabis to cope with negative affect. However, the literature is mixed, indicating that the effect of social anxiety on cannabis use behaviors during emerging adulthood may depend on other moderating factors, such as negative urgency. This study aimed to clarify potential moderators that may strengthen the associations between social anxiety and cannabis outcomes among emerging adults. Emerging adult undergraduates who reported past six-month cannabis use completed an online self-report survey. Results from a mediated moderation revealed that higher social anxiety predicted elevated cannabis use and problems via coping motives, but only for males higher in negative urgency. Findings suggest that socially anxious males higher in negative urgency are at greater risk for coping-motivated cannabis use and related problems. These results may inform screening and treatment approaches aimed at reducing impulsive cannabis use and subsequent harms for these emerging adult males.

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)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.107
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.020
GPT teacher head0.369
Teacher spread0.349 · 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
Published2024
Admission routes1
Has abstractyes

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