Exploring Impact of Marijuana (Cannabis) Abuse on Adults Using Machine Learning
| Autor: | Jeungok Choi, Joohyun Chung, Jeeyae Choi |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Adult
Marijuana Abuse Health Toxicology and Mutagenesis Marijuana Smoking Logistic regression Article Machine Learning Young Adult medicine substance abuse Humans Imputation (statistics) Young adult Depression (differential diagnoses) Cannabis Illicit Substance Public Health Environmental and Occupational Health Middle Aged medicine.disease Social relation Substance abuse health impact assessment Medicine Marijuana Use Psychology Health impact assessment Clinical psychology |
| Zdroj: | International Journal of Environmental Research and Public Health Volume 18 Issue 19 International Journal of Environmental Research and Public Health, Vol 18, Iss 10357, p 10357 (2021) |
| ISSN: | 1660-4601 1661-7827 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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