Uncertainty and risk during the COVID-19 pandemic: A latent profile analysis

被引:1
作者
Johnson, Angela E. [1 ]
Hua, Jacqueline [1 ]
Hinojosa, Bianca [1 ]
Meese, William B. [1 ]
Gray, Avia [1 ]
Howell, Jennifer L. [1 ]
机构
[1] Univ Calif Merced, Psychol Sci, 5200 Lake Rd, Merced, CA 95343 USA
关键词
COVID-19; latent profile analysis; preventative behavior; risk perception; uncertainty;
D O I
10.1111/spc3.12890
中图分类号
B84 [心理学];
学科分类号
04 ; 0402 ;
摘要
In the present study, we examine how subgroups of people are characterized by different profiles of uncertainty surrounding COVID-19, susceptibility, and recovery. Participants (N = 199) were U.S. residents recruited online for a longitudinal study during the summer of 2020. We first, identified groups using latent profile analysis (LPA) and then examined whether these profiles predicted differences in COVID-related risky and preventative behaviors. LPA identified five distinct profiles of people representing a combination of low and high uncertainty and low, moderate, and high risk perceptions. Results revealed that latent-profile group membership predicted intention to interact with others outside of the household, intention to engage in non-essential shopping, intention to attend an in-person religious gathering, intention to wear a mask in public, and self-reported physical distancing in the past week. Profile membership did not predict intentions to: dine out, go to the nail/hair salon, go to the gym, nor physically distance from others in the future, nor did it predict handwashing in the past week.
引用
收藏
页数:12
相关论文
共 34 条
[1]   Neighborhood environment profiles related to physical activity and weight status: A latent profile analysis [J].
Adams, Marc A. ;
Sallis, James F. ;
Kerr, Jacqueline ;
Conway, Terry L. ;
Saelens, Brian E. ;
Frank, Lawrence D. ;
Norman, Gregory J. ;
Cain, Kelli L. .
PREVENTIVE MEDICINE, 2011, 52 (05) :326-331
[2]   FACTOR-ANALYSIS AND AIC [J].
AKAIKE, H .
PSYCHOMETRIKA, 1987, 52 (03) :317-332
[3]  
[Anonymous], 2019, IBM SPSS STAT WINDOW
[4]   Auxiliary Variables in Mixture Modeling: Three-Step Approaches Using Mplus [J].
Asparouhov, Tihomir ;
Muthen, Bengt .
STRUCTURAL EQUATION MODELING-A MULTIDISCIPLINARY JOURNAL, 2014, 21 (03) :329-341
[5]  
Brashers DE, 2001, J COMMUN, V51, P477, DOI 10.1111/j.1460-2466.2001.tb02892.x
[6]   Risk perceptions and their relation to risk behavior [J].
Brewer, NT ;
Weinstein, ND ;
Cuite, CL ;
Herrington, JE .
ANNALS OF BEHAVIORAL MEDICINE, 2004, 27 (02) :125-130
[7]   Relationships Between Initial COVID-19 Risk Perceptions and Protective Health Behaviors: A National Survey [J].
de Bruin, Wandi Bruine ;
Bennett, Daniel .
AMERICAN JOURNAL OF PREVENTIVE MEDICINE, 2020, 59 (02) :157-167
[8]   Uncertainty and previvors' cancer risk management: understanding the decision-making process [J].
Dean, Marleah ;
Fisher, Carla L. .
JOURNAL OF APPLIED COMMUNICATION RESEARCH, 2019, 47 (04) :460-483
[9]  
Dhama K, 2020, CLIN MICROBIOL REV, V33, DOI [10.1038/s41432-020-0088-4, 10.46945/bpj.10.1.03.01, 10.1128/CMR.00028-20, 10.1038/s41432-020-0088-4]
[10]   Finding latent groups in observed data: A primer on latent profile analysis in Mplus for applied researchers [J].
Ferguson, Sarah L. ;
Moore, E. Whitney G. ;
Hull, Darrell M. .
INTERNATIONAL JOURNAL OF BEHAVIORAL DEVELOPMENT, 2020, 44 (05) :458-468