Unknown

Dataset Information

0

Exploring the association between compliance with measures to prevent the spread of COVID-19 and big five traits with Bayesian generalized linear model.


ABSTRACT: Research has examined the association between people's compliance with measures to prevent the spread of COVID-19 and personality traits. However, previous studies were conducted with relatively small-size datasets and employed frequentist analysis that does not allow data-driven model exploration. To address the limitations, a large-scale international dataset, COVIDiSTRESS Global Survey dataset, was explored with Bayesian generalized linear model that enables identification of the best regression model. The best regression models predicting participants' compliance with Big Five traits were explored. The findings demonstrated first, all Big Five traits, except extroversion, were positively associated with compliance with general measures and distancing. Second, neuroticism, extroversion, and agreeableness were positively associated with the perceived cost of complying with the measures while conscientiousness showed negative association. The findings and the implications of the present study were discussed.

SUBMITTER: Han H 

PROVIDER: S-EPMC7901385 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature

altmetric image

Publications

Exploring the association between compliance with measures to prevent the spread of COVID-19 and big five traits with Bayesian generalized linear model.

Han Hyemin H  

Personality and individual differences 20210223


Research has examined the association between people's compliance with measures to prevent the spread of COVID-19 and personality traits. However, previous studies were conducted with relatively small-size datasets and employed frequentist analysis that does not allow data-driven model exploration. To address the limitations, a large-scale international dataset, COVIDiSTRESS Global Survey dataset, was explored with Bayesian generalized linear model that enables identification of the best regress  ...[more]

Similar Datasets

| S-EPMC2883299 | biostudies-literature
| S-EPMC9475767 | biostudies-literature
| S-EPMC6620089 | biostudies-other
| S-EPMC5624537 | biostudies-literature
| S-EPMC5505735 | biostudies-literature
| S-EPMC8016495 | biostudies-literature
| S-EPMC7244587 | biostudies-literature
| S-EPMC7269105 | biostudies-literature
| S-EPMC8533901 | biostudies-literature
| S-EPMC4597416 | biostudies-literature