Exploring Impact of Marijuana (Cannabis) Abuse on Adults Using Machine Learning

Bibliographic Data

ID15501180
AuthorsJeeyae Choi (0000-0001-7287-6384, University of North Carolina Wilmington), Joohyun Chung (0000-0003-4670-097X, University of Massachusetts Amherst), Jeungok Choi (University of North Carolina Wilmington, corresponding author)
Year2021
Volume18
Issue19
Pages10357-10357
Publication date2021-10-01
Open AccessYes
TypeARTICLE
VenueInternational Journal of Environmental Research and Public Health (JOURNAL)
Journal identifiersISSN: 1661-7827 • E-ISSN: 1660-4601
PublisherMultidisciplinary Digital Publishing Institute (PUBLISHER • CH)
DOI10.3390/ijerph181910357
PMID34639657
OpenAlexW3202247598
LanguageEN
Citations received1
References cited36

Marijuana is the most common illicit substance globally. The rate of marijuana use is increasing in young adults in the US. The current environment of legalizing marijuana use is further contributing to an increase of users. The purpose of this study was to explore the characteristics of adults who abuse marijuana (20-49 years old) and analyze behavior and social relation variables related to depression and suicide risk using machine-learning algorithms. A total of 698 participants were identified from the 2019 National Survey on Drug Use and Health survey as marijuana dependent in the previous year. Principal Component Analysis and Chi-square were used to select features (variables) and mean imputation method was applied for missing data. Logistic regression, Random Forest, and K-Nearest Neighbor machine-learning algorithms were used to build depression and suicide risk prediction models. The results showed unique characteristics of the group and well-performing prediction models with influential risk variables. Identified risk variables were aligned with previous studies and suggested the development of marijuana abuse prevention programs targeting 20-29 year olds with a regular depression and suicide screening. Further study is suggested for identifying specific barriers to receiving timely treatment for depression and suicide risk

Cannabis · Environmental health · Injury prevention · Occupational safety and health · Poison control · Psychiatry · Suicide prevention · Alcohol Consumption and Health Effects · Cannabis and Cannabinoid Research · Clinical Psychology · Human Factors and Ergonomics · Medicine · Psychology · Substance Abuse Treatment and Outcomes

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