Performance of a Genetic Algorithm for Estimating DeGroot Opinion Diffusion Model Parameters for Health Behavior Interventions.

Kara Layne Johnson,Nicole Bohme Carnegie,Jennifer L Walsh,Yuri A Amirkhanian

doi:10.3390/ijerph182413394

Abstract

Leveraging social influence is an increasingly common strategy to change population behavior or acceptance of public health policies and interventions; however, assessing the effectiveness of these social network interventions and projecting their performance at scale requires modeling of the opinion diffusion process. We previously developed a genetic algorithm to fit the DeGroot opinion diffusion model in settings with small social networks and limited follow-up of opinion change. Here, we present an assessment of the algorithm performance under the less-than-ideal conditions likely to arise in practical applications. We perform a simulation study to assess the performance of the algorithm in the presence of ordinal (rather than continuous) opinion measurements, network sampling, and model misspecification. We found that the method handles alternate models well, performance depends on the precision of the ordinal scale, and sampling the full network is not necessary to use this method. We also apply insights from the simulation study to investigate notable features of opinion diffusion models for a social network intervention to increase uptake of pre-exposure prophylaxis (PrEP) among Black men who have sex with men (BMSM).

Highlights

IntroductionPublisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations
An ongoing study—with a completed pilot—seeks to assess the feasibility of increasing pre-exposure prophylaxis (PrEP) interest for Black men who have sex with men (BMSM) through the use of a social network intervention: engaging and training network leaders to communicate the benefits of PrEP within their social networks [1]
Since the network sampling method and scales used inform the simulation study, we provide an overview of the motivation and detail the network recruitment process and the measures selected for the analysis: self-efficacy and willingness

Summary

Introduction

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. Leveraging social influence is an increasingly common strategy to change population behavior or acceptance of public health policies and interventions. An ongoing study—with a completed pilot—seeks to assess the feasibility of increasing pre-exposure prophylaxis (PrEP) interest for Black men who have sex with men (BMSM) through the use of a social network intervention: engaging and training network leaders to communicate the benefits of PrEP within their social networks [1]. Since the intervention is inherently a social network intervention based on the premise that the network leaders will be more influential than other network members or agents, an assessment of the intervention should incorporate both network structure and varying influence

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Discussion

Conclusion