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Record W7161773454 · doi:10.82308/2181

Cannabis use, depression and suicidal ideation/attempt in adolescence:comorbidity and direction of associations in a contemporary Quebec cohort

2019· dissertation· en· W7161773454 on OpenAlexaboutno aff
Despina Bolanis

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsnot available
Fundersnot available
KeywordsCannabisDepression (economics)Longitudinal studyCohortPoison controlSuicide preventionMental healthInjury preventionSuicidal ideation

Abstract

fetched live from OpenAlex

Background: Given Canada’s recent cannabis legalization, its effects on depression and suicidal ideation/attempt in adolescence is of public health importance. Adolescence is a crucial developmental period marked with high consumption of cannabis, depression, and suicidal risk. Yet, most of the research available to date has focused on these associations in adulthood and few longitudinal studies have explored the direction of association between cannabis use, depression, and suicidal ideation/attempt in adolescence. Objective: The purpose of the present study was to explore both the concurrent and developmental sequence of association between cannabis use, depression, and suicidal ideation/attempt by examining the secondary substance use (depression/suicidal ideation/attempt precede cannabis use) and the secondary psychiatric disorder (cannabis use precedes depression/suicidal ideation/attempt) hypotheses. Clarifying the directionality of cannabis use and mental health outcomes will carry important implications for the treatment of adolescents presenting these conditions simultaneously.Methodology: Participants were drawn from the Quebec Longitudinal Study of Child Development, a contemporary birth cohort of Canadian adolescents followed over 20 years (n = 1606). We investigated concurrent associations between validated self-report measures of frequency of cannabis use, depression, and suicidal ideation/attempt at ages 15, 17 and 20 years, using logistic regressions. Longitudinal associations were assessed using cross-lagged panel analyses. Results: The prevalence of weekly cannabis use was 7.0% at age 15 years, 12.7% at age 17 years, and 15.6% at age 20 years. Adolescents who reported using cannabis weekly at one age were 15.81 to 11.31 (Odds Ratios [ORs]) times more likely to continue using cannabis over time. In our cross-lagged analysis, weekly cannabis use was associated with suicidal ideation/attempt, but not depression. Adolescents who used cannabis weekly at age 15 years were at a higher risk of suicidal ideation/attempt at age 17 years (OR = 2.19, 95% CI = 1.04–4.58). However, this association was fully explained by comorbid alcohol and other substance use (OR = 1.38, 95%CI = 0.52–3.20). Further, adolescents who reported having depression at 15 years were at higher risk of weekly cannabis use at 17 years, even after adjusting for comorbid alcohol and other substance use (OR = 2.30, 95% CI = 1.19–4.43). Those who used cannabis weekly at 17 years remained weekly users at 20 years (OR = 11.31, 95%CI = 5.20–24.61). Conclusion: The results of this study demonstrated that depression in adolescence predates weekly cannabis use, supporting the secondary substance use hypothesis. Evidence for the secondary substance use hypothesis has implications for the intervention plans of adolescents presenting with depression. Targeting symptoms of depression during mid-adolescence may prevent increases in cannabis use in late-adolescence. It has been demonstrated that weekly cannabis use is associated with aversive outcomes in young adulthood such as poorer mental health and impaired cognitive function

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.094

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0030.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
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 head0.027
GPT teacher head0.324
Teacher spread0.297 · 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".

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Citations0
Published2019
Admission routes1
Has abstractyes

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