Insight into Selecting Adolescents for Drinking Intervention Programs: a Simulation Based on Stochastic...

Area of Science:

• Public Health
• Social Network Analysis
• Adolescent Health

Background:

• Adolescent drinking is a significant public health and socioeconomic problem in the USA.
• Existing drinking intervention programs lack clear guidance on effective participant recruitment strategies.
• Computer simulation offers a cost-effective alternative to real-world intervention studies for evaluating recruitment methods.

Purpose of the Study:

• To address the gap in understanding effective participant recruitment for adolescent drinking interventions.
• To utilize computer simulation to compare different recruitment strategies based on drinking levels and network positions.

Main Methods:

• Estimated stochastic actor-oriented models using data from the National Longitudinal Study of Adolescent to Adult Health (Add Health).
• Simulated different participant selection strategies (based on drinking levels and network centrality) within the models.
• Assessed the impact of selection strategies on aggregated school drinking levels over time.

Main Results:

• Recruiting moderate or heavy drinkers for interventions proved more effective than targeting light or casual drinkers.
• Incorporating network position information significantly improved intervention outcomes.
• Selecting adolescents with high in-degree or eigenvector centrality among drinkers yielded the best results.

Conclusions:

• Participant selection criteria significantly impact the effectiveness of adolescent drinking interventions.
• Targeting high-drinking adolescents with central network positions offers a promising strategy for intervention programs.
• Simulation findings provide valuable guidance for optimizing recruitment in future US-based adolescent drinking interventions.