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Cannabis Use Among Older Adults

2025· article· en· W4410362360 on OpenAlexaff
Vira Pravosud, Emily Lum, Marzieh Vali, Beth E. Cohen, Katherine J. Hoggatt, Amy L. Byers, Peter C. Austin, Louise C. Walter, Deborah S. Hasin, Tauheed Zaman, Salomeh Keyhani

Bibliographic record

VenueJAMA Network Open · 2025
Typearticle
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsUniversity of Toronto
FundersNational Institute on AgingU.S. Department of Veterans Affairs
KeywordsCannabisMedicineMental healthLogistic regressionMoodPsychiatryDemographyInternal medicine

Abstract

fetched live from OpenAlex

Importance: Little is known about patterns (forms, frequency, and reasons) and factors associated with cannabis use in older veterans (aged ≥65 years). Objective: To examine factors associated with past 30-day cannabis use and cannabis use disorder (CUD) in older veterans. Design, Setting, and Participants: In this cross-sectional study, community-dwelling adults aged 65 to 84 years who used Veterans Health Administration care were interviewed between February 5, 2020, and August 29, 2023. Exposure: Sociodemographic, behavioral, and health-related characteristics. Main Outcomes and Measures: Past 30-day cannabis use (smoking, vaping, dabbing, or edibles) and any CUD (≥2 criteria based on Diagnostic and Statistical Manual of Mental Disorders [Fifth Edition]) were assessed using weighted multivariable logistic regressions. Results: Of the 4503 participants (weighted mean age, 73.3 years [95% CI, 73.0-73.5 years]; 85.4% [95% CI, 83.6%-87.2%] men), 58.2% (95% CI, 55.3%-61.0%) had ever used cannabis, 28.9% (95% CI, 26.0%-31.8%) of whom reported using cannabis for medical reasons, most commonly for pain (56.4%; 95% CI, 50.9%-61.9%), mood or mental health (18.4%; 95% CI, 14.7%-22.1%), and sleep (16.0%; 95% CI, 11.9%-20.0%). More than 1 in 10 reported past 30-day cannabis use (10.3%; 95% CI, 8.9%-11.7%), with 52.4% (95% CI, 45.4%-59.4%) of these using cannabis for 20 days or more; smoking (72.4%; 95% CI, 65.4%-79.3%) and edibles (36.9%; 95% CI, 29.8%-43.9%) were the most common forms of use. Characteristics associated with past 30-day use included younger age (65-75 years), economic hardship, tobacco and illicit drug use, and residing in a state with recreationally legal cannabis. Among those with past 30-day cannabis use, 36.3% (95% CI, 30.1%-42.6%) screened positive for CUD, with higher odds among younger respondents, those reporting anxiety, those with 1 or more deficits in activities of daily living, those with illicit drug use, those with frequent cannabis use, and those using cannabis recreationally. Past 30-day inhaled cannabis use, compared with edibles only, was associated with increased odds of any CUD (adjusted odds ratio, 3.56; 95% CI, 1.12-11.26). Conclusions and Relevance: In this cross-sectional study of cannabis use in older veterans, use was common, and more than one-third who used in the past 30 days had any CUD. The prevalence of past 30-day cannabis use was close to tobacco use prevalence, and risk factors for cannabis use were similar to those observed in other populations. Frequent and inhaled cannabis use was associated with higher odds of any CUD. Routine health screening for cannabis use in Veterans Health Administration clinical settings is necessary to identify older adults with cannabis use.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.423
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.014
GPT teacher head0.307
Teacher spread0.293 · 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 designNot applicable
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

Citations23
Published2025
Admission routes1
Has abstractyes

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