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Record W2898845878 · doi:10.1177/0706743718809339

The Effect of Age of Initiation of Cannabis Use on Psychosis, Depression, and Anxiety among Youth under 25 Years

2018· review· en· W2898845878 on OpenAlexaffvenueabout
Shera Hosseini, Mark Oremus

Bibliographic record

VenueThe Canadian Journal of Psychiatry · 2018
Typereview
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsPsychosisAnxietyDepression (economics)CannabisPsychologyPsychiatryClinical psychologyYoung adultDevelopmental psychology

Abstract

fetched live from OpenAlex

OBJECTIVES: This study was conducted to review the current state of evidence on the association between age of initiation of cannabis use and symptoms of psychosis, depression, or anxiety among youth under 25 years of age. METHODS: We conducted a systematic review of articles published prior to March 2018 by searching OVID MEDLINE, PsycINFO, EMBASE, and the references of included studies. We included comparative studies (cohort, case-control, cross-sectional) that reported on cannabis use in persons <25 years of age (exposure) and symptoms of psychosis, depression, or anxiety (outcome). We narratively synthesized the studies according to design (cohort, etc.) and psychiatric outcome. We used the Newcastle-Ottawa Scale to assess risk of bias. RESULTS: Of the 534 citations identified through the literature search, 23 met the eligibility criteria and were included in this review. With psychosis as the outcome, all except one study found that earlier cannabis use was generally associated with higher risks. With depression/anxiety as the outcome, 6 of the 11 included studies reported findings indicating that earlier use of cannabis was linked to higher symptom levels. CONCLUSION: In persons <25 years old, greater cannabis use is associated with more psychological symptoms, especially among those with a predisposition or existing vulnerability to such outcomes (Oxford Centre for Evidence-Based Medicine level 3 or 4). Policy makers need to consider the adverse effects of cannabis use in youth when planning a public health approach to cannabis legalization.

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)0.002
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.343
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.027
GPT teacher head0.319
Teacher spread0.292 · 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 designNot applicable
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

Citations82
Published2018
Admission routes3
Has abstractyes

Explore more

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