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The effects tailored interventions on cannabis use motives

2022· article· en· W4214761503 on OpenAlexaboutno aff
Alejandra Contreras, Bonnie J. Leadbeater, Sybil Goulet-Stock

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicReligion, Spirituality, and Psychology
Canadian institutionsnot available
Fundersnot available
KeywordsCannabisPsychological interventionPsychologyCoping (psychology)Clinical psychologyConfirmatory factor analysisPsychiatryStructural equation modeling

Abstract

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Background: The motives for cannabis affect on cannabis use and cannabis use consequences. Coping with stress is among the frequent motives for cannabis use. However, non stressed youth may use cannabis for self-enhancing motives like boosting confidence. Both motives are associated with higher frequency of cannabis use and more negative consequences (e.g., effects on schoolwork quality). Interventions targeting these distinctive motives may need to be tailored to assist youth trying to reduce cannabis use. The purposes of this study were: to examine the effect of cannabis use interventions on the change in motives of use; and whether motives for use are associated with hours per week using cannabis. Methods: Participants were from a cross national study including US and Canadian youth (n= 781). Participants included in the current analysis were from two Canadian Universities (n = 397, 54% female, median age = 21) were randomized into either the Cannabis eCHECKUP TO GO or Healthy Stress Management (HSM) intervention. Both interventions were administrated online and assessed at baseline and at a 4- to 6-week follow-up. Eligible youth reported using cannabis more than once a week and wanted to reduce their cannabis use. The 19 items to the question “what do you like about cannabis” were used as an assessment of motives for use (e.g., I feel more courageous, I feel more confident, cannabis helps me reduce stress, cannabis helps me sleep). Confirmatory Factor Analysis showed that a 2-factor model of cannabis use motives (self-confidence and stress-coping) fit the data adequately (CFI = 0.795, RMSEA [90% CI] = .063 [.057, .069]) after removing 2 poorly fitting items. Results: Across conditions self-confidence motives (T1: eCHECKUP condition M = 4.05(2.55), HSM condition M = 4.13(2.43); T2: eCHECKUP condition M = 4.09(2.50), HSM condition M = 4.36(2.28)) were endorse less than stress-coping motives (T1: eCHECKUP condition M = 6.48(1.92), HSM condition M = 6.25(1.78); T2: eCHECKUP condition M = 6.20(1.99), HSM condition M = 6.32(1.96)). Stress-coping motives were significantly correlated with the time spent high (hours a week) (T1 r= .21, T2: r=.26). A repeated measures MANOVA showed a significant interaction between time and intervention condition for the stress-coping motives only (F(1)= 4.08, p = .04). Participants in the Healthy Stress Management condition reported a significant decrease in the amount of stress-coping motives at the follow-up. Conclusions: These results demonstrate that motives of cannabis use can change over the course of a short online intervention for students seeking to reduce their use. In particular, the Healthy Stress Management condition helped participants reduce their stress-coping motives at T2. Neither intervention affected self confidence motives in the short term. These may be harder to address and may fuel continued use over time, even for youth hoping to change.

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)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.038
Threshold uncertainty score0.076

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0100.000

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 head0.053
GPT teacher head0.383
Teacher spread0.329 · 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
Published2022
Admission routes1
Has abstractyes

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