Intersection of Perceived COVID-19 Risk, Preparedness, and Preventive Health Behaviors: Latent Class Segmentation Analysis.

Osaro Mgbere Sorochi Iloanusi Ismaeel Yunusa Nchebe-Jah R Iloanusi Shrey Gohil Ekere James Essien

Published in: Online journal of public health informatics (2023)

The clustering patterns highlight the impact of modifiable risk behaviors on COVID-19 preventive practices, which can provide strong empirical support for health prevention policies. Consequently, clusters with individuals at high risk of contracting COVID-19 would benefit from multicomponent interventions delivered in diverse settings to improve the population-based response to the pandemic.

Keyphrases

coronavirus disease
sars cov
public health
healthcare
mental health
respiratory syndrome coronavirus
physical activity
primary care
depressive symptoms
health information
deep learning
social support
single cell
machine learning
climate change
health promotion