Original Article

Alpha Psychiatry 2022;23(3):113-120

DOI: 10.5152/alphapsychiatry.2022.21712

Stress Response on Behavioral Response of University Students During the Peak Period of COVID-19

Jun Ren¹

Honglin Ren2,a

Yueran Bian³

Caihong Yang⁴

Huifen Wu³

Xiaonan Li⁵

Yan Zhang³

Hui Shi⁶

¹ Party Committee teacher work department, Mianyang Normal University, Mianyang, China

² Department of General Education, Wuhan Vocational College of Software and Engineering, Wuhan, China

³ Department of Educational Science, Huazhong University of Science and Technology, Wuhan, China

⁴ Department of Psychology, Central China Normal University, Wuhan, China

⁵ Huazhong University of Science and the University Hospital, Wuhan, China

⁶ Department of Clinical Psychology, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China

a These authors are the co-first authors. They made equal contributions to the article.

Corresponding author: Xiaonan Li ✉ 759601184@qq.com

Cite this article as: Ren J, Ren H, Bian Y, et al. Stress response on behavioral response of university students during the peak period of COVID-19. Alpha Psychiatry. 2022;23(3):113-120.

ABSTRACT:

Background: This study aimed to explore the underlying mechanisms of the relationship between stress response and behavioral response and to develop a moderated mediation model with stress management and risk cognition.

Methods: We developed 4 novel questionnaires, namely, stress response questionnaire, behavioral response questionnaire, stress management questionnaire, and risk cognition questionnaire. A total of 5896 university students in China were investigated during the peak period of the coronavirus disease 2019.

Results: The results showed that stress response had a significant negative predictive effect on behavioral response (r = −0.489, P < .001). Moreover, stress management had a partial mediating effect between stress response and behavioral response. Risk cognition plays a moderating effect on the mediation model (β = −0.109, P = .030), and the effect of high-risk cognition is more significant.

Conclusion: During the coronavirus disease 2019 period, improving the risk awareness of university students will help to enhance the buffering effect of stress management on behavioral response and indirectly reduce their behavioral response.

Keywords: COVID-19; stress response; behavioral response; stress management; risk cognition; moderated mediating model

Introduction

The outbreak of the coronavirus disease 2019 (COVID-19) in 2020 has brought China’s economy and society into a state of stagnation. In the face of home isolation, city closure, and the rising number of infected people, people’s psychology is facing a huge impact.¹ College and university students, more worthy of attention, are not mature in cognitive experience and emergency response.² In addition to the threat of the common virus in the public, colleges students are also facing more serious pressure events: the normal life order is disrupted due to the failure to resume classes in colleges and universities, academic pressure, and interpersonal pressure generated by long-term home stay.³

With the occurrence of public health emergencies, people often have different degrees of psychological stress response.⁴ Stress–response often involves the functions of multiple response systems, including changes in cognitive, emotional, behavioral, and physiological levels, which may have negative effects on individuals.⁵ The negative consequences of stress are related to the imbalance between stress perception and stress limiting system.⁶ Long-term exposure to stressors is a risk factor for mental illness, such as depression and post-traumatic stress disorder.⁷

Serious social and public health events will also affect the behavior of residents.⁸ Behavioral response means that under stress, individuals can have a direct behavioral response and indirect behavioral response. Direct response refers to the behavioral response made by an individual to eliminate or avoid the stimulus when directly facing the stimulus that causes tension; indirect response refers to the behavioral response of individual to temporarily relieve stress experience with the help of some substances.⁹ The study of behavioral response in COVID-19 found that university students frequently or always applied protective measures, such as wearing masks and gloves and avoiding touching the face.¹⁰

Stress response has adaptive protection in the short term.¹¹ When internal homeostasis is threatened, individuals will produce a series of adaptive compensation responses to maintain internal homeostasis.¹² Moderate stress is conducive to improving the adaptability of the body.¹³,¹⁴ Behavioral response and stress response pathways will be integrated within individuals, that is, behavioral response and stress response are highly related.¹⁵ The level of cortisol represents the strength of stress response.¹⁶ The above evidence shows that stress response is significantly correlated with behavioral response. In view of this, we propose hypothesis 1: stress response can positively predict behavioral response.

Individual stress management strategy plays an important role in health.¹⁷ Previous studies found that stress responses are driven by how people manage negative effects of stress.¹⁸ Meanwhile, stress management is also significantly related to behavioral response. The change of stress management strategy needs to change behavior or take a new view on stress.¹⁹ Studies on cancer patients have found that stress management intervention reduces cancer-related negative behavioral reactions.²⁰ Adolescents’ externalized stress-related behaviors are often associated with ineffective cognitive coping strategies (i.e., constructive thinking).²¹ These results indicate that stress management is related to behavioral response and stress response. In view of this, we propose hypothesis 2: stress management has a mediating effect between stress response and behavioral response.

The COVID-19 is a rare outbreak of infectious diseases, and it is a high-risk-threatening stress event to the public. Risk cognition is the individual’s understanding and judgment of these risk events, which is affected by the objective risk degree of the event.²² Different from other risk events, the public’s cognition of epidemic risk has its uniqueness. For example, people in different regions may have different perceptions of the risk of epidemic situations. People in non-epidemic areas even have more negative emotions. Some researchers call it “psychological typhoon eye effect.”²³

Changes in human behavior may be driven by risk cognition. Studies have found that if the cognition of risk associated with epidemics improved, the impact of epidemics is significantly reduced and the rate of self-reducing contact activity is conducive to the effective control of human epidemics.²⁴ A study investigated the disaster area of Wenchuan earthquake in 2008 and the results show that residents’ high-risk cognition has a positive impact on their adaptive evacuation behavior.²⁵ A research has explored farmers’ risk perception and climate change adaptation behavior and found that high-risk cognition and adaptation cognition have a significant positive impact on climate change adaptation behavior.²⁶ There is a positive correlation between individual risk attitude and task performance in dynamic risk decision-making.²⁷ Risk cognition is positively correlated with political support behavior and behavior tendency.²⁸ On the contrary, underestimation of risk is related to exposure enhancement activities, and the positive coping styles of individuals are correspondingly less.²⁹ It is found that heat exposure leads to the decrease of individuals’ cognition of the same environmental risk, which leads to more behavioral reactions of violating safety measures.³⁰

MAIN POINTS

Stress response had a significant negative predictive effect on behavioral response in the epidemic.

Stress management played a mediating role between stress response and behavioral response.

For high-risk cognition people, stress management had a significant predictive effect on behavioral response.

Risk cognition is significantly positively correlated with stress management.³¹,³² The research on workers found that their attention and awareness of occupation-related risks hindered the effectiveness of stress management.³³ Studies have shown that job insecurity affects the perception of psychosocial risks, thus increasing the vulnerability of workers to job-related stress.³⁴ Some researchers have studied the relationship between stress vulnerability and risk perception and other psychological factors in earthquake disasters and they found that people’s stress vulnerability is significantly related to their perception of earthquake risk.³⁵ Combined with the above evidence, it is not difficult to find that individuals with high-risk cognition show more behavioral responses than individuals with low-risk cognition and are accompanied by higher stress strategies. In view of this, we propose hypothesis 3: risk perception moderates the relationship between stress management and behavioral response.

To sum up, this study intends to explore the relationship and mechanism among stress response, stress management, behavioral response, and risk cognition of colleges and university students in the epidemic and tries to explore the impact of the COVID-19 on colleges and university students’ coping style and its influence mode and to provide theoretical support for effectively improving the psychological response mechanism of colleges and university students in the face of emergencies. Based on the theory of stress response and the mechanism of psychological processes, this study proposes a moderated mediating model, as shown in Figure 1.

Figure 1. Hypothetical Model: The Mediating Role of Stress Management and the Moderating role of Risk Cognition.

Methods

Participants and Procedures

Data were collected through the questionnaire satellite platform. The survey time was February 17-19, 2020. The participants were college and university students. The total number of students in this study was 5896. There are 3 sample groups in this study. The study was reviewed and approved by the Ethical Authority of the School of Educational Science, Huazhong University of Science and Technology (approval date: January 30, 2020; Number: 20200130). The participants were informed about the purpose of the study, both verbally and in writing.

In the first part, the sample size of exploratory factor analysis was 2046, of which 959 (46.87%) were male and 1087 (53.13%) were female, with an average age of 19.74 (1.52).

In the second part, the sample size of confirmatory factor analysis was 2030, of which 970 (47.78%) were male, 1060 (52.22%) were female, and the average age was 19.77(1.85).

In the third part, the sample size of mediating effect and moderating effect analysis is 1820, of which 823 (45.22%) were male and 997 (54.78%) were female. The average age stand was 19.72 (1.54) years.

Research Tool

Stress Response Questionnaire:

To understand the stress response of colleges and university students in China during COVID-19, based on literature analysis, expert discussion, and on-the-spot interviews with colleges and university students, graduate students, and counselors, we developed a stress response questionnaire composed of 8 items.³⁶,³⁷ The specific forms of stress response investigated were integrated into 1 major category, with 8 factors in total. The questionnaire adopts 1-4 4-point scoring method. The higher the total score, the more obvious the stress response performance; the lower the total score, the less obvious the stress response performance.

First, we conducted an exploratory factor analysis with a sample size of 2046. Statistical Package for the Social Sciences (SPSS) version 25.0 (IBM SPSS Corp.; Armonk, NY, USA) software was used to analyze the data. Before exploratory factor analysis, the KMO (Kaiser-Meyer-Olkin) value test and Bartlett's spherical test were used to test whether the questionnaire data were suitable for exploratory factor analysis. According to Kaiser’s standard, the KMO value above 0.80 is suitable for factor analysis. The results showed that KMO value was 0.91 and Bartlett’s spherical test results were significant (P < .001), indicating that the items of the questionnaire are suitable for exploratory factor analysis. Then, the principal axis factoring analysis and the maximum variance method were used for factor analysis. Through the above steps, the final number of effective factors was 1, named stress response. The number of questionnaire items formed was 8. The cumulative total variation of interpretation reached 55.63%. Each item had a large load on the corresponding factors, ranging from 0.49 to 0.87.

Second, we conducted confirmatory factor analysis with a sample size of 2030 people. Amos 25.0 software was used to conduct confirmatory factor analysis on the single-factor model of stress response. According to the modification index (MI), the single-factor model was compared with the multi-factor model. Generally, the acceptable standard of structural equation model fitting is NFI (Normed Fit Index), CFI (Comparative Fit Index), IFI (Incremental Fit index), greater than 0.90 (better close to or greater than 0.95), and SRMR (Standardized Root Mean Square Residual) less than 0.08. The results showed that the fitting indexes of single factor were the best; RMSEA (Root Mean Square Error of Approximation) = 0.08, NFI = 0.97, CFI = 0.97, IFI = 0.97, SRMR = 0.03.

Finally, we tested the reliability and validity of the scale. The internal consistency reliability analysis shows that the total internal consistency coefficient of the questionnaire is 0.85, which indicates that the questionnaire has good reliability.

Stress Management Questionnaire:

We developed a stress management questionnaire composed of 2 items and integrated the coping styles investigated into 1 category. The questionnaire adopts 1-5 5-point scoring method. The higher the total score, the more obvious the stress management; the lower the total score, the less obvious the stress management.

First, we conducted an exploratory factor analysis with a sample size of 2046. The KMO value was 0.50, and Bartlett's spherical test was significant (P < .001), indicating that the items of the questionnaire were suitable for exploratory factor analysis. The number of effective factors is 1 and the number of questionnaire items is 2. The cumulative total variation of interpretation is 75.85%. The 2 items have a large load, both of which are 0.87.

Finally, we tested the reliability and validity of the scale. The results of criterion-related validity showed that there was a significant correlation between the 2 items (r = 0.47, P < .001), which indicated that the stress management questionnaire had good criterion-related validity. Internal consistency reliability analysis found that the total internal consistency coefficient of the questionnaire was 0.64, indicating that it had good reliability.

Risk Cognition Questionnaire:

We developed a risk cognition questionnaire composed of 6 items. The risk cognition of the survey was integrated into 2 categories (severity cognition and susceptibility cognition) with a total of 6 factors. Questions 1 and 2 were severity cognition, 3-6 were susceptibility cognition, and 5 and 6 were reverse scoring questions. The questionnaire adopts a scoring method of 1-5 points. The higher the total score, the clearer the risk cognition; the lower the total score, the less clear the risk cognition.

First, we conducted an exploratory factor analysis with a sample size of 2046. The results showed that KMO value was 0.62, and Bartlett’s spherical test was significant (P < .001), indicating that the items of the questionnaire were suitable for exploratory factor analysis. The final number of effective factors is 2, and the number of questionnaire items is 6. The 2 factors are named severity cognition and susceptibility cognition. The total variation of cumulative interpretation is 28.98%. Each item has a large load on the corresponding factors, ranging from 0.33 to 0.75.

Second, we conducted confirmatory factor analysis with a sample size of 2030 people. The results showed that the fitting indexes of 2-factor model were the best; RMSEA = 0.06, NFI = 0.92, CFI = 0.93, IFI = 0.93, SRMR = 0.04, which was significantly better than single-factor model, so the 2-factor model was accepted.

Finally, we tested the reliability and validity of the scale. The results of criterion-related validity showed that there was a significant correlation between the 2 dimensions of risk cognition, severity cognition, and susceptibility cognition (r = 0.17, P < .001). This shows that the risk cognition questionnaire has good criterion-related validity. The internal consistency reliability analysis showed that the internal consistency α coefficients of severity cognition and susceptibility cognition were 0.36 and 0.47, respectively, and the total internal consistency coefficient of the questionnaire was 0.47, indicating that it had good reliability.

Behavioral Response Questionnaire:

We developed a coping style questionnaire composed of 5 items. The coping styles of the survey were integrated into 1 category, with 5 factors in total. The questionnaire was scored from 1 to 5 points. The higher the total score, the more obvious the behavioral response; the lower the total score, the less obvious the behavioral response.

First, we conducted an exploratory factor analysis with a sample size of 2046. The test results showed that KMO value was 0.82 and Bartlett’s spherical test was significant (P < .001), indicating that the items of the questionnaire were suitable for exploratory factor analysis. The final number of effective factors was 1, named behavioral response, and the number of questionnaire items formed was 5, the cumulative total variation of interpretation reached 57.34%, each item had a large load on the corresponding factors, ranging from 0.59 to 0.85.

Secondly, we conducted confirmatory factor analysis with a sample size of 2030 people. The results showed that: the single factor fitting index was the best: RMSEA = 0.06, NFI = 0.99, CFI = 0.99, IFI = 0.99, SRMR = 0.02.

Finally, we tested the reliability and validity of the scale. This indicates that the questionnaire has good criterion-related validity. Internal consistency reliability analysis found that the total internal consistency coefficient of the questionnaire was 0.81, indicating that it had good reliability.

Statistical Analyses:

We used the Bias-corrected percentile Bootstrap method to calculate the moderator effects and mediator effects. Statistical Package for the Social Sciences (SPSS) version 25.0 (IBM SPSS Corp.; Armonk, NY, USA) and Process Syntax by Andrew F. Hayes were used to perform the regression analysis and construct the predicted mediation model. Continuous data are expressed as mean (SD=Standard Deviation). Pearson correlation was used to analyze the correlation among stress response, stress management, behavioral response, and risk cognition. The type I error rate(α) is chosen to be 0.05.

Results

Common Method Bias Analysis

In this study, Harman’s single-factor test was used to test the common method bias. All items of stress response, risk cognition, social function, and coping style were analyzed without rotation to determine the minimum number of factors necessary for variable variation. If only 1 factor or a certain factor was analyzed and the explanatory power of that factor is too high, it can be judged that there is a serious common method bias. The results of data analysis showed that 7 characteristic roots were larger than 1, and the first common factor could explain 29.06% of the total variation, which was far lower than the recommended critical value of 40.00%. Therefore, there was no common method bias in this study.

Descriptive Statistics

We made descriptive statistics on the relevant information of the participants. A total of 1820 participants participated in the moderated mediation model statistics, including 823 (45.22%) male, 997 (54.78%) female; 1099 (60.38%) people in rural areas and 721 (39.62%) people in urban areas; 1488 (81.76%) people had bachelor’s degree, 29 (1.59%) had a master’s degree, 4 (0.22%) had a doctoral degree, and 299 (16.43%) had higher vocational education; 181 (9.95%) people in Wuhan City, 804 (44.18%) people in Hubei Province but outside Wuhan City, 835 (45.88%) people outside Hubei Province. The average age was 19.72 ± 1.54 years (Table 1).

Correlation Analysis

We conducted correlation analysis on the variables. Among them, behavioral response was significantly negatively correlated with stress response (r = −0.489, P < .001), stress management (r = −0.133, P < .001), risk cognition (r = −0.255, P < .001), severity cognition (r = −0.140, P < .001), and susceptibility cognition (r = −0.229, P < .001) (Table 2).

Mediating Effect Test

In order to effectively control the measurement error, the structural equation modeling method is used to test the multiple mediating effects. SPSS 25.0 and Model 4 of the PROCESS macro for SPSS were used to perform the mediating effect test. First, the total effect of stress response on behavioral response was tested, and the path coefficient was found to be significant (β = −0.489, P < .001). Second, stress management as a mediating variable was added to the model to obtain the mediating model as shown in Figure 2. The results show that stress response predicted stress management significantly positively (β = 0.093, P < .001), which would negatively predict behavioral response (β = −0.088, P < .001). This indicates that stress management played a partial mediating role in the influence of stress response on behavioral response (Table 3).

Table 1. Statistical Description of Participants’ Relevant Information (n = 1820)

Descriptive Indicators | n (%)
Gender |
Male | 823 (45.22)
Female | 997 (54.78)
Education |
Bachelor | 1488 (81.76)
Master | 29 (1.59)
Doctoral | 4 (0.22)
Vocational education | 299 (16.43)
Area |
Township | 1099 (60.38)
City | 721 (39.62)
Location |
Wuhan city | 181 (9.95)
Inside Hubei province outside Wuhan city | 804 (44.18)
Outside Hubei province | 835 (45.88)

Table 2. Correlation Analysis of Each Variable

Variable | Mean (SD) |  | 1 | 2 | 3 | 4 | 5 | 6
1. Stress response | 1.58 (0.55) | rs | - |  |  |  |  |
P | - |  |  |  |  |
2. Stress management | 3.34 (0.92) | rs | 0.093 | - |  |  |  |
P | <.001 | - |  |  |  |
3. Behavioral response | 3.56 (0.81) | rs | −0.489 | −0.133 | - |  |  |
P | <.001 | <.001 | - |  |  |
4. Risk cognition | 3.13 (0.48) | rs | 0.329 | 0.003 | −0.255 | - |  |
P | <.001 | .883 | <.001 | - |  |
5. Severity recognition | 2.59 (0.60) | rs | 0.153 | 0.118 | −0.140 | 0.562 | - |
P | <.001 | <.001 | <.001 | <.001 | - |
6. Susceptibility cognition | 4.22 (0.66) | rs | 0.311 | −0.069 | −0.229 | 0.890 | 0.123 | -
P | <.001 | .003 | <.001 | <.001 | <.001 | -

Note: the data have been standardized.
SD, standard deviation.

Figure 2. Mediating Effect of Stress Management on the Relationship between Stress Response and Behavioral Response.aP < .001.

Moderated Mediating Effect Test

Statistical Package for the Social Sciences 25.0 and Model 14 of the PROCESS macro for SPSS were used to perform the moderated mediating effect test. First, in order to reduce multicollinearity, all variables were standardized. The results showed that the interaction between stress management and risk cognition had a significant predictive effect on behavioral response (β = −0.041, P < .001) (Table 4). There was an interaction between stress management and risk cognition in the prediction of behavioral response.

Second, the regulatory effect of risk cognition is shown in Figure 3 and Table 4. After risk cognition was put into model 14, the scores of stress management and risk cognition had a significant predictive effect on behavioral response (β = −0.109, P = .030), indicating that risk cognition plays a moderating role in stress management on behavioral response prediction (Table 4). The further simple slope analysis is shown in Table 5 and Figure 4. For high-risk cognition participants, stress management had significant predictive effect on behavioral response, 95% CI = −0.189, −0.079 (excluding 0); however, for low-risk cognition participants, stress management had no positive predictive effect on behavioral response, 95% CI = −0.106, 0.001 (including 0), which indicated that compared to the participants with the low-risk cognition participants, the stress management of participants with high-risk cognition has a significant negative predictive effect on behavioral response, and the mediating effect between stress management and behavioral response showed a downward trend.

Discussion

The Influence of Stress Response on Behavioral Response of Colleges and University Students in the Epidemic Period

Our main finding reveals a significant negative correlation between behavioral response and stress response, which was inconsistent with hypothesis 1. This result is consistent with previous findings that uncertainty stress was negatively associated with prevention behaviors.³⁸ The possible reason for the abovementioned phenomena is that there may be overlapping psychological mechanisms between behavioral response and stress response, which are both conditioned responses to stress events. When faced with stressful events, especially the sudden and threatening large-scale epidemic disease such as the COVID-19, individuals with weaker stress response will take more adaptive behavioral responses, while individuals with stronger stress response will devote more energy to dealing with stress events.³⁹

Table 3. Regression Analysis of the Mediating Role of Stress Management (n = 1820)

Model | Regression Equation | Significant Regression Coefficient
| Outcome variable | Predictive variable | R2 | F | β | t | P
1 | Behavioral response | Stress response | 0.239 | 571.659a | −0.489 | −23.909a | <.001
2 | Stress management | Stress response | 0.009 | 15.957a | 0.093 | 3.993a | <.001
3 | Behavioral response | Stress response | 0.247 | 297.830a | −0.481 | −23.518a | <.001
|  | Stress management |  |  | −0.088 | −4.301a | <.001
Note: the data have been standardized. aP < .001.

Table 4. Moderator Roles of Risk Cognition in the Effect of Stress Management on Behavior Response (n = 1820)

Model | Regression Equation | Significant Regression Coefficient
| Outcome variable | Predictive variable | R2 | F | β | t | P
1 | Stress management | Stress response | 0.009 | 15.947a | 0.093 | 0.022a | <.001
2 | Behavioral response | Stress response | 0.270 | 336.108a | −0.445 | −0.020a | <.001
|  | Stress management |  |  | −0.093 | −0.021a | <.001
|  | Risk cognition |  |  | −0.109 | −5.110b | .030
|  | SM × RC |  |  | −0.041 | −2.173a | <.001

Note: the data have been standardized. aP < .001, bP < .05.
SM, stress management; RC, risk cognition.

Figure 3. Moderating Effect of Risk Cognition on the Relationship between Stress Management and Behavioral Response. aP < .001, bP < .05.

Table 5. Moderating Effect of Risk Cognition on Mediating Variables

| Effect | SE | 95% CI
High risk cognition (mean + SD) | −0.134 | 0.028 | [−0.189, −0.079]
Average risk cognition | −0.093 | 0.020 | [−0.133, −0.053]
Low risk cognition (mean − SD) | −0.053 | 0.027 | [−0.106, 0.001]
SD, standard deviation.

Figure 4. Simple Slope analyses of Moderating Effects.

Mediating Effect of Stress Management on the Relationship Between Stress Response and Behavioral Response

The second major finding is that stress management plays a mediating role in the relationship between stress response and behavioral response. Stress management is positively correlated with stress response and negatively correlated with behavioral response, which was inconsistent with hypothesis 2. Previous researchers have explored the effect of stress management training on endocrine stress response of healthy adolescents under acute psychological stress and the results showed that stress management training can be proved to be helpful to prevent behavioral responses caused by stress-related neuroendocrine activation, which is consistent with the results of this study.⁴⁰

The possible reason for this result is that when facing stress events, individuals may start-related stress management models and adopt strategies such as pressure regulation and communication with the outside world and information.⁴¹ Stress management represents the individual’s regulation and buffering of stress events, which is an adaptive, positive, and constructive psychological and behavioral process. However, overemphasizing the negative effects of stress and stress management may increase the additional strain on the individuals under already stressful situations, resulting in a reduction in behavioral responses.⁴²

Moderating Effect of Risk Cognition on Mediating Effect

Another key finding is that risk cognition played a moderating role in the relationship between stress management and behavioral response, and is negatively correlated with behavioral response. The moderating effect of high-risk cognition on the participants was highly significant. Thus, hypothesis 3 is supported. This result is consistent with the existing research results. Previous studies have found that risk cognition is significantly positively correlated with information-seeking of stress management dimension.³¹,³² On the contrary, underestimation of risk is related to exposure enhancement activities, and the positive coping styles of individuals are correspondingly less.²⁹ The possible reason for this phenomenon is that compared with low-risk cognition, high-risk cognition means that individuals give high-risk weight to the same stress events; in this situation, individuals are more likely to treat it as a more serious stress event, so they will show more stress management strategies in mind and behavior. In the face of more and more serious epidemic situations and almost uncontrollable risk of infection, individuals’ higher behavioral response means that they take higher protective measures to avoid the harm brought by risks, the risk of subjective feelings may also decrease.⁴³

In view of this, in the face of stress events, especially the sudden and infectious pandemic like the COVID-19, improving the stress management of college and university students helps to buffer the effect of stress response on behavioral response, directly buffering their behavioral response. Moreover, improving the risk cognition of colleges and university students helps to increase better the negative predict effect of stress management on behavioral response, thus indirectly buffering their behavioral response, considering that this study is during the early phase of the pandemic. As the COVID-19 pandemic progresses, changes in stress, risk cognition, and behavioral response may emerge.⁴⁴ Thus, future researchers could use longitudinal studies to track such changes.

Ethics Committee Approval: Ethical committee approval was received from the Ethics Committee of Authority of School of Educational Science, Huazhong University of Science and Technology (Approval Date: January 30, 2020; No. 20200130).

Informed Consent: Written informed consent was obtained from all participants who participated in this study.

Peer-review: Externally peer-reviewed.

Author Contributions: Concept – Y.Z., H.S., J.R.; Design – Y.Z., H.S.; Supervision – X.L., Y.Z., H.S.; Funding – X.L.; Materials – Y.Z., H.S.; Data Collection and/or Processing – C.Y., H.W., Y.B.; Analysis and/or Interpretation – C.Y., H.R.; Literature Review – H.R., H.W.; Writing – C.Y., H.R., Y.B.; Critical Review – H.R., H.W., Y.B.

Declaration of Interests: The authors have no conflicts of interest to declare.

Funding: This study was supported and granted by the “Fundamental Research Funds for the Central Universities: HUST (2020WKZDJC010)” to X.L.

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Appendix

1 Stress Response Questionnaire (1 little time → 4 much time)

1) I feel more nervous and anxious in recent week than usual.

2) I have been afraid for no reason for nearly a week.

3) I am easily upset or frightened in the past week.

4) I feel depressed and depressed in the past week.

5) I feel uneasy and cannot calm down for the past week.

6) I feel tired for no reason for nearly a week.

7) I am very troubled by this epidemic infection.

8) I feel sensitive and suspicious.

2 Stress Management Questionnaire (1 very inconsistent → 5 very consistent)

1) I actively look for ways to relieve pressure.

2) I am happy to tell my troubles to the people close to me.

3 Risk Cognition Questionnaire (1 very inconsistent → 5 very consistent)

1) I think the COVID-19 is very serious now.

2) I think it is necessary to separate villages (between communities).

3) Facing the current epidemic situation, I think I am very dangerous.

4) I think I am very likely to have COVID-19 pneumonia.

5) I think that as long as we take protective measures (wearing masks, washing hands frequently, and disinfecting regularly), we will not be infected.

6) I think the COVID-19 can be cured.

4 Behavioral Response Questionnaire (1 very inconsistent → 5 very consistent)

1) I think strangers have COVID-19 pneumonia.

2) Do not dare to go to crowded places, even if passing by strangers, I will take the initiative to avoid.

3) I dare not talk to strangers.

4) I forced hand washing or cleaning many times, thinking that there were bacteria everywhere, afraid of being infected.

5) I am eager to go to the hospital and ask the doctor to make a thorough examination with reagents.

Received: October 6, 2021
Accepted: February 9, 2022

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