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Record W4409804427 · doi:10.1002/adaw.34499

Legalization of cannabis leads to increase in use, decrease in use disorder

2025· article· en· W4409804427 on OpenAlexaboutno aff
Alison Knopf

Bibliographic record

VenueAlcoholism & Drug Abuse Weekly · 2025
Typearticle
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsnot available
Fundersnot available
KeywordsLegalizationCannabisPsychiatryPsychology

Abstract

fetched live from OpenAlex

The frequency of cannabis use increased signifcicantly, but misuse discreased, in a study of almost 1,500 adults. A prospective cohort study has found that five years after legalization, the frequency of cannabis use increased modestly, while cannabis misuse decreased modestly. Frequent consumers of cannabis before legalization showed the largest decreases in both frequency of use and cannabis misuse after legalization. The study was conducted on community‐dwelling (living independently in a house or apartment, not an institution) adults assessed 11 times from September 2018 to October 2023 in Ontario. The results, according to study authors, suggest that recreational cannabis legalization was associated with modest negative and positive consequences. The study, “Cannabis Use and Misuse Following Recreational Cannabis Legalization,” is published in the April 23 issue of JAMA Network Open , and by André J. McDonald, PhD, MPH and colleagues. For the study, frequency was defined as the mean proportion of days using cannabis, which went up by 1.75% over 5 years. In cased, cannabis use disorder scores decreased significantly over 5 years. Interestingly, the decrease of cannabis use disorder was most pronounced with the onset of the COVID‐19 pandemic. Over that 5‐year period, product preferences shifted away from dried flower, hashish, concentrates, oil, tinctures, and topics to edibles, liquids, and vape pens.

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)0.002
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 score0.153
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
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 integrity0.0000.000
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 head0.015
GPT teacher head0.302
Teacher spread0.286 · 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

Explore more

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