Perceived Beliefs,Uncertainty,and Behavioral Responses During the COVID-19 Outbreak in China: Findings From a Convenience Sample

Abstract

Purpose:

To investigate perceived beliefs, uncertainty, and behavioral responses among Chinese residents toward the COVID-19 outbreak, and explore their relationships amid an incipient pandemic.

Design:

A cross-sectional correlational survey with a combination of a convenience and snowball sampling design.

Setting:

This study was conducted online from February 7 to 14, 2020, the third week after the lockdown of Wuhan city on January 23.

Participants:

A total of 2,654 residents was contacted, 2,534 agreed to participate, and 2,215 completed valid questionnaires. The sample covered 30 provinces, municipalities, autonomous regions of China, and a broader region.

Measures:

The Uncertainty About COVID-19 Scale was applied to assess perceived public uncertainty. Five dimensions of health beliefs about COVID-19 and 12 health-related response behaviors were measured.

Analysis:

Univariate analysis and multiple linear regression models were used to identify associations. Mediation was assessed by a bootstrapping technique.

Results:

Five constructs of health beliefs were found to be significant predictors of multiple response behaviors. Uncertainty about COVID-19 has a direct relationship with general response behaviors (β=-0.119**) and sanitization practices (β=-0.068**). Emergency coping behaviors aside, uncertainty also partially mediated associations between perceived susceptibility, perceived effectiveness, and perceived barriers influencing general response behaviors and sanitization practices, respectively.

Conclusion:

Findings provide evidence-based information to government and policymakers for designing effective health communication messages and intervention strategies by targeting the key constructs of the health belief model and reducing perceived uncertainty about COVID-19. They support public health-related response behaviors to prevent COVID-19 spread among the population.

Keywords

uncertainty COVID-19 perceived belief behavioral response health-related behaviors

Purpose

A novel coronavirus, SARS-CoV-2, the agent for Coronavirus Disease-2019 (COVID-19), has generated a global pandemic. In order to contain its spread, the World Health Organization (WHO) issued a set of recommendations for the public, such as maintaining social distancing, frequent handwashing, staying aware of the latest information on COVID-19 from national and local public health authorities, and avoiding touching eyes, nose, mouth and other bodily regions. The effectiveness of these mitigation and control measures fundamentally depends on public willingness to comply.¹ However, behavioral adherence to recommended personal precautions is not spontaneous. Transmission of infectious disease is impacted by dynamic human behavioral change and a situational awareness that enables people to modify their deleterious behaviors.² Thus, it is necessary to address specific determinants of such changes during outbreaks.³

According to the extended Health Belief Model (HBM), individual health promotion behavior is motivated and influenced by several well-defined core belief variables.^4

-7 Previous studies have demonstrated that risk perception and perception of benefits could influence willingness and motivation to adopt precautionary health behaviors.^1,3,8,9

Since COVID-19 is a totally new disease, the current situation is replete with uncertainty given lack of vaccination and use of antiviral drugs for COVID-19 in the general population, its highly contagious nature, and limited knowledge of viral transmission routes, diagnosis, therapies and prognosis. Besides uncertainty inherent in the severity of the illness, COVID-19 generates enormous uncertainty due to its global reach, pervasive transmission, urgent nature and gross disruption of societal functioning and people’s routines. Previous studies demonstrated that uncertainty is associated with lower engagement in risk-reducing behavior.¹⁰ Unknown is how uncertainty impacts the public in cognitively processing a COVID-19-related stimulus, as well as how they respond behaviorally to outbreak-related events. As a potential determinant of behavior, uncertainty about risk judgments merits further consideration for integration into theories of health behavior.¹⁰ A research imperative is whether perceived uncertainty about a COVID-19 outbreak will influence response behaviors—not only for protecting oneself but avoiding others who are at risk. Innovative thinking about how perceptions of uncertainty are presumed to relate to behavior might enhance understanding of the nature of risk, and potentially improve health behavior interventions.¹⁰

To develop effective health communication strategies and devise containment interventions for the public among the COVID-19 outbreak, it is important to gain insights on people’s perceived beliefs and uncertainty about COVID-19, and the related health-promoting response behaviors that would be used to calibrate its prevention. This study had 3 key objectives: 1) to describe the status quo of perceived beliefs, uncertainty, and response behaviors toward COVID-19, and 2) to identify the direct relationships between perceived beliefs and uncertainty in response behaviors, and 3) to explore the mediating role of uncertainty between the perceived beliefs and response behaviors.

Methods

Study Design and Participants

This study utilized a cross-sectional correlational design. Our survey was developed on the Wenjuanxing Platform (https://www.wjx.cn/app/survey.aspx), and conducted online from February 7 to 14, 2020, the third week after the lockdown of Wuhan City. Twenty psychology students were trained as research assistants to recruit participants through WeChat and other websites using a combination of convenience and snowball sampling. These assistants were required to distribute the survey link to their family, relatives and friends on their WeChat contact list, group, and moments (friends’ circles). Their family, relatives and friends were also encouraged to send the link to their own WeChat social networks. Meanwhile, the assistants also sent the survey link through QQ, Sina-microblog, Baidu PostBar, and other social network platforms to recruit participants. They are all major Chinese social networking platforms. Our sample covered 30 provinces, municipalities, autonomous regions of China, and a broader region. Participants took approximately 15-minutes to complete the questionnaire. A total of 2,654 potential participants were contacted online, and 2,534 agreed to participate in the survey- a 95.5% response rate. The study protocol was approved by the Ethics Committee at Shenzhen University, and written consent was obtained from all participants prior to administration of the questionnaire.

Development and Piloting of the Questionnaire

The questionnaire was developed in accordance with the conceptual framework of the Health Belief Theory and Uncertainty in illness Theory.^5,11 Questions for each domain were selected by the principal investigator. Six experts from different disciplines reviewed the preliminary draft of the questionnaire for content and clarity. The survey was pilot tested with 20 psychological students to obtain logistical information on administration, and to improve the face validity of the questionnaire.

Measures

Demographic characteristics

The following sociodemographic information was collected during the survey: date of birth, gender, place of residence, ethnicity, marital status, educational attainment, occupation and per capita annual family income, and regional location. Specific experience with COVID-19, including infection and quarantine status, were also measured.

Uncertainty about COVID-19

The 10-item Uncertainty about COVID-19 Scale was developed with reference to the Mishel Uncertainty in Illness Scale.¹¹ We applied a 5-point Likert type scale ranging from strongly agree to strongly disagree in tapping public perception of uncertainty about the COVID-19 outbreak. Item scores were summated to obtain a total uncertainty score. The higher the score, the greater the perceived uncertainty about the disease. The Kaiser-Meyer-Olkin measure of sampling adequacy was 0.866, and Bartlett’s test of sphericity was significant (P < 0.001), suggesting the sample was factorable. The factor loading on each item exceeded 0.5. Finally, 2 distinct factors were extracted, and accounted for 59% of the variance. The factor of “lack of information and clarity” was loaded on 5 items: “I have many unanswered questions about COVID-19,” “I am unsure how to deal with a fever, cough or other symptoms,” “The effectiveness of the treatments or medications COVID-19 patients are receiving is undetermined,” “The transmission route of COVID-19 is unclear,” “There are so many different opinions about the prognosis of COVID-19.” The factor of “unpredictability” was loaded on another 5 items: “Because of the unpredictability of the COVID-19 outbreak, I cannot plan for the future,” “Because of the COVID-19 outbreak, what I can do and cannot do is in flux,” “I am unsure when the COVID-19 outbreak will end,” “I am unsure when the social normal order will return,” “It is unclear what is going to happen to me.” The Cronbach’s alpha coefficients were 0.75 for lack of information and clarity, and 0.85 for unpredictably, respectively. The reliability coefficient for the Uncertainty about COVID-19 Scale was 0.85, indicating good reliability.

Perceived beliefs about COVID-19

Five dimensions of perceived beliefs were assessed, including perceived severity about COVID-19, perceived susceptibility of contracting COVID-19, perceived benefits of individual protective behaviors, perceived effectiveness of policy measures, and perceived barriers to adoption of protective behaviors. Perceived severity, perceived susceptibility, perceived benefits, and perceived barriers, which came from 4 key concepts in the Health Belief Model, were measured by a single item as implemented in prior studies.^3,7 Perceived effectiveness was measured by 2 items, that included policy measures conducted at both community and clinical levels. A 5-point Likert scale was the metric for all dimensions, ranging from 1 (strongly disagree) to 5 (strongly agree). The Cronbach’s alpha coefficient for total health beliefs was 0.73, which indicated acceptable reliability.

Response behaviors during the COVID-19 outbreak

We assessed 12 health-related response behaviors during the COVID-19 outbreak (Table 1). The Kaiser-Meyer-Olkin measure of sampling adequacy was 0.753, and Bartlett’s test of sphericity was significant (P < 0.001), suggesting the sample was factorable. Based on principal component analysis, 3 factors were extracted. They accounted for 47% of the variance. These 12 behaviors were collapsed into 3 categories: 1) emergency coping behaviors; 2) general response behaviors; and 3) mainly focussing on 4 kinds of sanitization practices. Responses of participants were measured using a binary “yes” or “no” scale for each type of behavior. The homogeneous behavioral dimension score was summed to yield a total score based on the number of affirmative answers.

Table 1.

Twelve-Specific Response Behaviors Toward COVID-19.

Variables	n (%)	95% C.I.
Emergency coping behaviors
1. Staying home almost all day	1711 (77.2)	75.5-79.0
2. Always wearing a mask in public	2148 (97.0)	96.3-97.7
3. Keeping room clean and opening windows frequently	2167 (97.8)	97.2-98.4
4. Handwashing frequently (beyond before meals and after toilet use)	1858 (83.9)	82.4-85.4
5.Keeping up to date on COVID-19 information	2009 (90.7)	89.5-91.9
General response behaviors
6. Continuing to exercise	1532 (69.2)	67.2-71.1
7. Taking general prophylactic drugs	632 (28.5)	26.7-30.4
8. Maintaining good diet with adequate rest	1812 (81.8)	80.2-83.4
Sanitization practices
9. Disinfecting living spaces and indoor furniture	1565 (70.7)	68.8-72.6
10. Disinfecting kitchenware	1740 (78.6)	76.8-80.3
11. Disinfecting clothing	1516 (68.4)	66.5-70.4
12. Handwashing frequently with sanitizers	766 (34.6)	32.6-36.6

Data Analysis

All survey data were entered into a Microsoft Excel database, and then imported into SPSS (version 22.0) for statistical analysis. Cronbach’s alpha coefficient and exploratory factor analysis were used to examine the reliability and validity. Univariate analysis and multiple linear regression models were used to identify the key predictors of the dependent variables. All models adjusted for sociodemographic characteristics and COVID-19 infection experience. We also used exploratory factor analysis to examine the severity of the common method variance. The first factor’s variance—accounting for the total variance in each model—was below 50%, suggesting the common method variance has reached conventional satisfactory criteria. Mediation analysis with bootstrapping was applied to test the indirect effect of uncertainty about COVID-19 between perceived beliefs and health-related response behaviors.¹²

Results

A total of 2,534 contacts agreed to participate in the survey, of whom 2,215 (87.4%) completed valid questionnaires. Table 1 shows a series of specific health-related response behaviors among the participants during the COVID-19 outbreak. The distribution of the demographic characteristics on 3 categories of behaviors in the sample were reported in Table 2. After adjustment for sociodemographic factors, the findings from multiple linear regression analysis showed perceived benefits of individual protective behaviors and perceived effectiveness of policy measures correlated positively with emergency coping behaviors (Table 3). Perceived susceptibility and perceived effectiveness were positively associated with general response behaviors and sanitization practices, whereas perceived barriers and uncertainty about COVID-19 were negatively correlated with these 2 categories of behaviors.

Table 2.

The Distribution of the Demographic Characteristics on 3 Categories of Behaviors Among the Sample.

Variables	n	%	Emergency coping behaviors	General response behaviors	Sanitization practices	Variables	n	%	Emergency coping behaviors	General response behaviors	Sanitization practices
Age			p < 0.001**	p < 0.001**	P = 0.010*	Education			p < 0.001**	p < 0.001**	p < 0.001**
<20	411	18.6	4.53	1.79	2.52	Junior high school or less	196	8.8	4.14	2.19	2.84
20-24	1113	50.2	4.54	1.67	2.43	High school	233	10.5	4.38	2.03	2.70
25-29	240	10.8	4.22	1.87	2.64	Junior college	263	11.9	4.43	1.95	2.69
30-39	209	9.4	4.33	2.02	2.64	College or higher	1523	68.8	4.53	1.68	2.43
40+	242	10.9	4.39	2.12	2.72	Occupation			p < 0.001**	p < 0.001**	p < 0.001**
Gender			p < 0.001**	p < 0.001**	p < 0.001**	Public official /professionals	257	11.6	4.37	1.89	2.57
Male	726	32.8	4.36	1.96	2.69	Enterprise personnel	238	10.7	4.42	2.01	2.67
Female	1489	67.2	4.52	1.71	2.44	Commerce/service/operations	215	9.7	4.06	1.99	2.86
Place of residence			P = 0.028*	P = 0.148	p < 0.001**	Students	1311	59.2	4.58	1.68	2.43
Urban	1522	68.7	4.49	1.78	2.62	Others	194	8.8	4.31	1.93	2.56
Rural	683	31.3	4.41	1.84	2.30	Household annual income (RMB)			p = 0.026*	p = 0.009**	p < 0.001**
Ethnicity			p < 0.001**	p = 0.701	p = 0.875	< 20,000	475	21.4	4.45	1.70	2.17
Han	2155	97.3	4.49	1.80	2.52	20,000-59,999	832	37.6	4.41	1.85	2.56
Minority	60	2.7	3.67	1.75	2.55	60,000-99,999	516	23.3	4.53	1.75	2.70
Marital status			p < 0.001**	p < 0.001**	p < 0.001**	100,000+	392	17.7	4.51	1.85	2.65
Unmarried	1699	75.3	4.53	1.70	2.44	Region			p < 0.001**	p < 0.001**	p = 0.028*
Married	517	23.3	4.30	2.10	2.79	East	1837	82.9	4.49	1.76	2.49
Divorced/widowed	29	1.3	3.83	1.79	2.59	Middle	184	8.3	4.29	1.92	2.58
Infected by COVID-19			p < 0.001**	p < 0.001**	p < 0.001**	West	123	5.6	4.54	1.83	2.65
Yes	54	2.4	3.20	2.54	3.28	Northeast	60	2.7	4.05	2.23	3.00
No	2161	97.6	4.50	1.78	2.50	Abroad	11	0.5	4.64	2.09	3.00
Friends/colleagues/relatives quarantined due to infection or suspected infection by COVID-19			p < 0.001**	p < 0.001**	P = 0.016*	People living in the same community or village quarantined due to infection or suspected infection by COVID-19			p < 0.001**	p = 0.487	p = 0.004**
Yes	132	6.0	3.73	2.08	2.80	Yes	278	12.6	4.17	1.83	2.74
No	2083	94.0	4.51	1.78	2.50	No	1937	87.4	4.51	1.79	2.49

* < 0.05; ** < 0.01.

Table 3.

Multiple Line Regression Models of Health-Related Response Behaviors Toward COVID-19.

Independent variables	Mean (SD)	Dependent variables (Standardized Beta Coefficient) #
Independent variables	Mean (SD)	Emergency copingbehaviors	General response behaviors	Sanitization practices
Perceived severity	4.09 (0.93)	-0.040	0.026	-0.045*
Perceived susceptibility	3.93 (1.01)	0.039	0.094**	0.109**
Perceived benefits	4.65 (0.59)	0.149**	0.013	-0.024
Perceived effectiveness	4.63 (0.53)	0.152**	0.127**	0.083**
Perceived barriers	4.63 (0.64)	-0.024	-0.101**	-0.108**
COVID-19 uncertainty	3.08 (0.65)	0.035	-0.119**	-0.068**
R²		0.182	0.110	0.070

* < 0.05; ** < 0.01. # All models were adjusted for sociodemographic characteristics, infection, and quarantine status.

The results from mediation analysis, using bootstrapping, showed that perceived susceptibility had a partially indirect effect upon general response behaviors (B=-0.017, 95% CI=-0.025, -0.010) and sanitization practices (B=-0.010, 95% CI = -0.017, -0.004) through uncertainty. This analysis also indicated a partially mediation effect of uncertainty between perceived effect of the policy measure and general response behaviors (B = 0.012, 95% CI = 0.002, 0.024) and sanitization practices (B=-0.007, 95% CI = 0.001, 0.016). A partially indirect effect was also affirmed in the relationship between perceived barriers and general response behaviors (B=-0.026, 95% CI=-0.039, -0.015) and sanitization practices (B=-0.015, 95% CI=-0.026, -0.006), respectively, via uncertainty. However, no indirect effect manifested for uncertainty about COVID-19 in the relationship between risk perception and emergency coping behaviors.

Discussion

COVID-19 Related Health Beliefs and Behavioral Responses

COVID-19 related risk perceptions, perception of benefits and effectiveness of preventive measures, and health-related response behaviors evolved rapidly during the third week after the lockdown of Wuhan City on January 23, 2020. Relationships between health beliefs toward COVID-19 and health-related response behaviors were examined in this study.

The multiple regression analyses, adjusted for sociodemographic factors, showed perceived severity was negatively correlated with sanitization practices, whereas perceived benefits of personal protective behaviors and perceived effectiveness of policy measures were positively correlated with emergency coping behaviors. People will adopt precautionary behaviors if they believe effective protective actions are generally available.¹³ A plausible explanation for the inverse relationship between perceived severity and sanitization practices is that very high-risk perceptions, such as fatal consequences, instead of mobilizing people might evoke feelings of helplessness that could paralyze them rather than promote protective behaviors.¹ Different from emergency coping behaviors, perceived susceptibility to a disease, rather than its severity, appears to need the most attention regarding the promotion of general response behaviors and sanitization practices.^8,13,14

If the public perceive the regulations and measures taken by the authorities against COVID-19 are effective, this would increase their sense of security and they would have more time and energy to address their suboptimal response behaviors, such as sanitization practices, and enhance personal immunity by pursuing a healthy lifestyle through good diet, regular exercise, and adequate rest.¹³ In a COVID-19 outbreak, the perceived effectiveness of policy measures seem a powerful component in predicting 3 categories of preventive behaviors. They might convey an important message that the perception of effective and reliable interventions conducted by governments could increase personal compliance with recommended protective behaviors.

Uncertainty about COVID-19 and Behavioral Responses

This research represents the evidence-based demonstration of the impact of perceived uncertainty in a major public health crisis such as COVID-19. Uncertainty about COVID-19 was negatively correlated with both general response behaviors and sanitization practices. The public perceived uncertainty when they lacked sufficient information or knowledge about COVID-19 and could not easily comprehend the emerging epidemic. Our results for general health behaviors and sanitization practices were consistent with prior research that showed breast cancer patients would be impeded in engaging in satisfying and appropriate self-care behavior when the disease prognosis or treatment was perceived as difficult to predict.¹⁵ This kind of uncertainty would exhaust an individual’s energy, diminish perceived control, and divert attention from routine healthy behaviors and sanitization practices.¹⁶ Uncertainty also mediated perceived susceptibility, perceived effectiveness and barriers influencing general response behaviors and sanitization practices. Thus, provision of uncertainty management must be an essential component in individual protective interventions for the public.

Limitations

This study has several limitations. The cross-sectional study design precluded causal inference concerning the relationship between the 5 components of health beliefs and uncertainty with a series of health-related response behaviors. Although this sample originated from 30 provinces covering diverse regions and included a wide array of demographic characteristics, the over-representation of college students and participants from Guangdong Province suggests sampling bias. Results should be interpreted with caution, and not generalized beyond the study sample, since we resorted to surveying a convenience sample amid the chaos and disruption emanating from the COVID-19 outbreak. Another limitation was that the measurement of personal experience on infection and quarantine was self-reported, with no confirmation from official records. This study is a preliminary initiative to examine the perceived beliefs and uncertainty toward COVID-19 in predicting health related behaviors, but the impact of demographics and the mediation effect of uncertainty warrants future discussions.

Significance

COVID-19 related perceived beliefs, uncertainty, and the prevalence of corresponding precautionary response behaviors among survey respondents were relatively high, and their relationships were examined during the early stages of the outbreak in China. Study findings provide evidence-based information to authorities and policymakers for designing effective health communication messages and targeting intervention strategies, by applying the Health Belief Model, reducing uncertainty about COVID-19, and promoting public health-related response behaviors to prevent COVID-19 spread among the population.

So What?

What is already known on this topic?

Individual health promoting behavior was motivated and influenced by risk perception and perception of benefits based on the Health Belief Model.

Illness Uncertainty Theory proposed that high uncertainty is associated with reduced ability to adapt to the illness.

Research on uncertainty in a lethal infectious disease outbreak is limited among non-patients.

What does this study add?

Uncertainty about COVID-19 was negatively correlated with general response behaviors and sanitization practices.

Uncertainty partially mediated associations between perceived susceptibility, perceived effectiveness, and perceived barriers influencing general response behaviors and sanitization practices, respectively.

What are the Implications for Health Promotion Practice or Research?

Findings provide evidence-based information to government and policymakers for designing effective health communication message and intervention strategies by targeting the reduction of perceived uncertainty about COVID-19.

Perceived effectiveness of policy measures supports public health-related response behaviors to prevent COVID-19 spread among the population.

Footnotes

Acknowledgments

The author(s) would like to thank the research assistants to help us collect data and the residents who participated in this study. DW drafted the manuscript and participated in the conception and design of the project. TY and XY participated in the conception and design of the study. CJ and MW conducted statistical analysis. IR and CJ edited and revised the manuscript. All authors read and approved the final version of the manuscript.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was partially supported by the Natural Science Foundation of Guangdong Province, China (Grant No. 2018A030307002) and National Natural Science Foundation of China (Major Project No. 7l490733).

ORCID iDs

Dan Wu

Tingzhong Yang

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