Abstract
Introduction: The Health Belief Model (HBM) has been successfully applied to understanding adherence to COVID-19 prevention practices. It has not, however, been used to understand behavior in people who use drugs (PWUD). The aim of this study was to use the HBM to better understand COVID-19 perceptions among PWUD and understand how resiliency affects those perceptions.
Materials and methods: A cross-sectional survey was completed from September to December 2021 with PWUD (n = 75) who utilize services at a large harm reduction organization in Philadelphia. Segmentation analysis was done using a k-means clustering approach. Two clusters emerged based on perceived COVID-19 personal impact and resiliency (Less COVID impact/High resilience (NoCOV/HR) and High COVID impact/Low resilience (COV/LR). Differences in responses by cluster to perceptions of COVID-19 and individual pandemic response grouped by HBM constructs were assessed using Student’s t-test and chi squares.
Results: Significant differences in HBM constructs were seen between clusters. Those in the COV/LR cluster were more likely to think they were susceptible to getting COVID-19 and less likely to believe they knew how to protect themselves. The NoCOV/HR cluster believed they were able to protect themselves from COVID-19 and that they were able to easily understand messages about protecting themselves.
Conclusion: Understanding how PWUD conceptualize disease threat and using HBM can better inform interventions to improve future pandemic response. Findings suggest that resilience is key to protecting PWUD from future infectious disease outbreaks. Interventions aimed at increasing resiliency among PWUD may improve preventative behavior and decrease disease burden in this vulnerable population.
Paulus, K., Bass, S. B., Kelly, P. J., Pilla, J., Otor, A., Scialanca, M., Arroyo, A., & Faison, N. (2024). Using health belief model constructs to understand the role of perceived disease threat and resilience in responding to covid-19 among people who use drugs: A cluster analysis. Advances in Drug and Alcohol Research, 4. https://doi.org/10.3389/adar.2024.12197