Adhering to COVID-19 health guidelines: Examining demographic and psychological predictors of adherence.

ABSTRACT: The effort to limit the spread of the coronavirus (COVID-19) has relied heavily on the general public's compliance with health guidelines limiting social contact and mitigating risk when contact occurs. The aim of this study was to identify latent variables underlying adherence to COVID-19 guidelines and to examine demographic and psychological predictors of adherence. A sample of US adults (N = 1,200) were surveyed in late April to mid-May 2020. The factor structure of adherence was examined using exploratory factor analysis. Machine learning regression models using elastic net regularization were used to examine predictors of adherence. Two factors characterized adherence: avoidance and cleaning. Elastic net models identified differential demographic and psychological predictors of these

SUBMITTER: Bailey B 

PROVIDER: S-EPMC8239601 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature