Article ; Online: Using the Alcohol, Smoking, and Substance Involvement Screening Test (ASSIST) to Predict Gambling Disorder Among U.S. College Students.
2024
Abstract: The Alcohol, Smoking, and Substance Involvement Screening Test (ASSIST) screening tool has not previously been used to evaluate risk for gambling disorder (GD). We aimed to assess the level at which each specific substance involvement score (SSIS), ... ...
| Abstract | The Alcohol, Smoking, and Substance Involvement Screening Test (ASSIST) screening tool has not previously been used to evaluate risk for gambling disorder (GD). We aimed to assess the level at which each specific substance involvement score (SSIS), measured by ASSIST, most optimally predicted GD among U.S. college students. Data were analyzed for 141,769 students from the National College Health Assessment (fall 2019-spring 2021) utilizing multivariable logistic regression models. Sensitivities and specificities were utilized to find optimal cutoffs that best identified those with GD, overall and by biological sex and age group. Lower threshold of substance risk related to prescription opioids, cocaine, and hallucinogens (all with SSIS cutoffs of 4) predicts gambling disorder compared to sedatives (SSIS cutoff of 19). Younger students had lower thresholds of substance risk predicting GD than older students for heroin, but for all other substance classifications students 25 years and older had lower thresholds of SSIS predicting GD than students 18-24 years old. This study aids in the understanding that substance use behavior may put students at risk for other addictive behaviors such as GD. This study is the first to utilize the ASSIST tool to predict GD among U.S. college students, extending its application beyond substance use disorders. The identification of optimal cutoffs for each SSIS provides a novel approach to concurrently screen for GD and substance use disorders. This unique contribution could enhance early detection and intervention strategies for GD in the college student population. |
|---|---|
| Language | English |
| Publishing date | 2024-02-15 |
| Publishing country | United States |
| Document type | Journal Article |
| ZDB-ID | 2016895-0 |
| ISSN | 1573-3602 ; 1050-5350 |
| ISSN (online) | 1573-3602 |
| ISSN | 1050-5350 |
| DOI | 10.1007/s10899-024-10283-w |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
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