Abstract
Purpose: Identify and examine the associations between health behaviors and increased risk of adolescent suicide attempts, while controlling for socio-economic and demographic differences. Design: A data-driven analysis using cross-sectional data. Setting: Communities in the state of Montana from 1999 to 2017. Selected Montana as it persistently ranks among the top 3 vulnerable states in the U.S. over the past years. Subjects: Selected 22,447 adolescents of whom 1,631 adolescents attempted suicide at least once. Measures: Overall 29 variables (predictors) accounting for psychological behaviors, illegal substances consumption, daily activities at schools and demographic backgrounds were considered. Analysis: A library of machine learning algorithms along with the traditionally-used logistic regression were used to model and predict suicide attempt risk. Model performances—goodness-of-fit and predictive accuracy—were measured using accuracy, precision, recall and F-score metrics. Additionally, χ2 analysis was used to evaluate the statistical significance of each variable. Results: The non-parametric Bayesian tree ensemble model outperformed all other models, with 80.0% accuracy in goodness-of-fit (F-score: 0.802) and 78.2% in predictive accuracy (F-score: 0.785). Key health-behaviors identified include: being sad/hopeless (p < 0.0001), followed by safety concerns at school (p < 0.0001), physical fighting (p < 0.0001), inhalant usage (p < 0.0001), illegal drugs consumption at school (p < 0.0001), current cigarette usage (p < 0.0001), and having first sex at an early age (below 15 years of age). Additionally, the minority groups (American Indian/Alaska Natives, Hispanics/Latinos) (p < 0.0001), and females (p < 0.0001) are also found to be highly vulnerable to attempting suicides. Conclusion: Significant contribution of this work is understanding the key health-behaviors and health disparities that lead to higher frequency of suicide attempts among adolescents, while accounting for the non-linearity and complex interactions among the outcome and the exposure variables. Findings provide insights on key health-behaviors that can be viewed as early warning signs/precursors of suicide attempts among adolescents.
| Original language | English |
|---|---|
| Pages (from-to) | 688-693 |
| Number of pages | 6 |
| Journal | American Journal of Health Promotion |
| Volume | 35 |
| Issue number | 5 |
| DOIs | |
| State | Published - Jun 2021 |
Keywords
- health behaviors
- health policy
- mental health
- predictive analytics
- suicide attempts among adolescents
- suicide prevention
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