The Relationship Between Uncertainty in Illness,State Anxiety,and the Life Satisfaction of College Students During the COVID-19 Epidemic

Lin Cai,Tian-Liang Fan,Zhi-Han Mei,Qing-Jun Li,Yu Yao,Deng-Hui Lu

1Ideological and Political Theory Teaching Department,Sichuan Institute of Industrial Technology,Sichuan,China.

2Health Culture Research Center of Shaanxi,Key Research Base of Philosophy and Social Sciences in Shaanxi Province,Shaanxi,China.

Abstract

Keywords:COVID-19,Mental health,State anxiety,Life satisfaction,Uncertainty in illness,Psychopathology,College students

Introduction

The coronavirus disease(COVID-19)pandemic is currently spreading worldwide.It has developed into an international public health emergency[1-2].A public health emergency is a type of public crisis event that severely impacts human health[3].A public crisis event is a sudden and catastrophic event that can be a risk to the overall quality of life of individuals and impact the common good.Previous studies have demonstrated that public crisis events impact not only mental health but also life satisfaction[4-5].

Life satisfaction is a summary cognitive assessment of one’s quality of life.Generally,life satisfaction is a construct of subjective well-being related to how people evaluate the quality of specific aspects of their lives such as work,marriage,health,recreation,and religion,as well as the quality of the more general aspects of their lives such as happiness,morale,zest for life,and peace of mind[6].Life satisfaction is an important predictor of mortality,morbidity,depression,and health status over the life course[7-10].This link impacting life satisfaction is especially pronounced in a public health emergency[11].

Mishel and Braden[12]stated that uncertainty arose when people lacked sufficient information about the treatment or did not understand the information they received.Previous studies have shown that uncertainty in illness can adversely affect life satisfaction[13].Anxiety is negatively related to satisfaction in life;higher levels of anxiety have been linked to lower levels of life satisfaction[14].Uncertainty in illness creates anxiety;the higher the levels of uncertainty in illness,the higher the degree of anxiety[15].A longitudinal microcytic anemia study has indicated uncertainty in illness positively predicts anxiety[16].

The number of people with COVID-19 is increasing continuously worldwide,and no specific drug to treat the COVID-19 infection is as yet available.This enables the facile formation of uncertainty in illness.Most previous research has focused on the relationship between uncertainty in illness,state anxiety,and life satisfaction in specifically non-communicable diseases[17-19].These relationships may differ between communicable diseases and non-communicable diseases;therefore,this study is aimed to explore the relationship of uncertainty in illness,state anxiety,and life satisfaction during the COVID-19 crisis.In summary,this study proposed the following hypothesis:That state anxiety plays a mediating role in the relationship between uncertainty in illness and life satisfaction during the COVID-19 crisis.

Subjects and methods

Subjects

Using the method of cluster random sampling,college students in the China University of Petroleum,the College of Science and Technology of China,the Three Gorges University,the Sichuan Institute of Industrial Technology,the Nanchang Institute of Technology,Wenzhou Medical University,Hebei Normal University of Science and Technology,and the Tibet Vocational Technical College were asked to complete a questionnaire.The data collection process started at 17:15 on January 30,2020,and ended at 21:13 on February 20,2020.The questionnaire was completed by the students who matched the listed criteria:

(1)The participants were adequately informed about all relevant aspects of the survey,including the objective and interview procedures.

(2)The survey was voluntary and anonymous.

Design of the questionnaire

There are three questionnaires in this study.Questionnaire 1 is the Uncertainty in Illness Scale(UIS)developed by Mishel and Braden[12].Chen Mengjuan [20] required a revision based on uncertainty in illness during the SARS epidemics.The scale was composed of 15 questions to which participants respond on a Likert-type scale of 1-5.The higher the score,the higher the uncertainty in illness.The internal consistency coefficient in this study was α=0.88.

Questionnaire 2 is the State Anxiety Inventory(SAI).This scale was developed by Spielberger and Gorsuch[21].Li Wenli and Qian Mingyi[22]required a revision.The scale was composed of 20 questions to which participants respond on a Likert-type scale of 1-4.The higher the score,the higher the anxiety.The internal consistency coefficient in this study was α=0.94.

Questionnaire 3 is the Life Satisfaction Scale(LSS).This scale was developed by Diener[23].The scale is composed of five questions to which participants respond on a Likert-type scale of 1-7.The higher the score,the higher the life satisfaction.The internal consistency coefficient in this study was α=0.75.

Before the formal survey began,120 students were selected to conduct a pre-survey,according to the results of which the questionnaire was updated based on the results garnered from the trial run.

Statistical methods

SPSS statistics software 22.0 and Mplus 7.0 were used for result analysis.The normality of the distribution of the data was checked by Shapiro-Wilk’s normality test.All the data met the assumption of normality.The students’t-test after one-way analysis of variance in SPSS was used to analyze the differences between the groups.P＜0.05 suggested that the difference was statistically significant.We used structural equation modeling to assay the relationships between uncertainty in illness,state anxiety,and life satisfaction.

Ethics approval and consent to participate

All participants gave their consent to participate in this study.Necessary permissions to conduct the study were obtained from the Sichuan Institute of Industrial Technology Ethics Committee (Decision No:GYKJ2020/023).All participants were given an explanation regarding research ethics and signed an informed consent form after being fully apprised of the aim of the study,the benefit of participation,and withdrawal of participation.Identifiable personal information was deliberately deleted during the transcription process,and all participants were recorded on the questionnaires’transcripts only as ID numbers.

Results

As shown in Table 1,the results indicated that the hypothesized model with three factors demonstrated excellent fit.The one-factor model and two-factor model demonstrated a poorer fit,which evidenced that the values of χ2/df increased,the values of CFI and TLI(Tucker-Lewis index)decreased,and the values of RMSEA increased,compared with the expected three-factor model.Furthermore,the Chi-square method was used to check for non-response bias,and the Harman one-factor test was used to test the common method bias.The results show that significant heterogeneity exists between the variables,and the data could be seen as evidencing low common bias.

Table 1 The comparative results of alternative models

A total of 1734 questionnaires were collected,including 1522 valid questionnaires.Twenty-five participants were excluded from the analysis because of an extremely short answer time and/or inconsistent answer patterns(e.g.,flatliners and contradictions).The effective rate was 87.77%.Among them,510 respondents were boys(33.51%)and 1012 were girls(66.49%).Rural residence accounted for 858 of the respondents’place of abode(56.37%),and urban living accounted for 664 respondents (43.63%).The proportions of freshmen,sophomores,juniors,and seniors were 54.91%,22.93%,16.82%,and 5.34%,respectively.

The overall UIS score was 2.64(SD=0.60).Female students revealed higher levels of uncertainty in illness than did male students(P=0.004,t-test).Rural students revealed higher levels of uncertainty in illness than urban students(P=0.008,t-test).Overall,the SAI score was 2.02(SD=0.54).Female students revealed higher levels of state anxiety than did male students(P＜0.001,t-test).Overall,the LSS score was 4.40(SD=0.51).Urban students revealed higher levels of life satisfaction than did rural students(p＜0.001,t-test).See Table 2 for specific information.

Uncertainty in illness was positively related to state anxiety(r=0.33,P＜0.001).Uncertainty in illness was negatively correlated with life satisfaction(r=−0.29,P＜0.001).State anxiety was negatively correlated with life satisfaction(r=−0.17,p＜0.001).Gender was positively related to uncertainty in illness and state anxiety.Urban and rural households were negatively correlated with uncertainty in illness.Urban and rural households were positively related to life satisfaction.See Table 3 for specific information.

Table 3 The correlation matrix for ovariables

Our hypothesized model was studied using structural equation modeling.Mplus Version 7.0 was used for the analysis.Three latent variables(Uncertainty in Illness,State Anxiety,and life satisfaction)were included in our hypothesized model.We then used life satisfaction as the dependent variable,uncertainty in illness as the prediction variable,state anxiety as the mediating variable,and gender and place of residence as the control variables.Model fit indices were χ2=37.79,df=8,χ2/df=4.72,CFI=0.99,TLI=0.98,RMSEA=0.05,SRMR=0.02.According to a study by Nunkoo,Ramkissoon,and Gursoy[24],when the sample size is greater than 500,the ratio of Chi-square degrees of freedom is less than five,but not the usual value of three.The sample size for the present study was n=1522,χ2/df=4.74,which is well within the acceptable range.

Plots show results from the model(see also Supplementary Figure 1).Uncertainty in illness had a significant direct effect on life satisfaction(β = −0.29,P＜0.001).Uncertainty in illness positively predicted the components of state anxiety(β=0.36,P ＜ 0.001).State anxiety negatively predicted the components of life satisfaction(β=−0.17,P ＜ 0.01).These results confirm that state anxiety plays a partial mediating role in the relationship between uncertainty in illness and life satisfaction.Effect size=−0.06(P＜ 0.05),explaining 17.43% of the total effect(−0.35).

Figure 1 Final structural equation model,which shows the standardized path coeffificients

We chose a full information maximum likelihood procedure in Mplus 7.0 to analyze the significance of the mediating effects.Particularly,we generated 5,000 bootstrap samples with random sampling with replacement from the data set.Table 4 shows the indirect effects and related 95% confidence intervals.The 95% confidence interval does not contain 0,and the mediated effect is statistically significant.Uncertainty in illness had an indirect prediction on life satisfaction via state anxiety(Effect=−0.024).

Table 4 Bootstrap analysis results for the magnitude of the indirect effects using the final model

Discussion

The present study revealed that female students expressed higher levels of state anxiety than did male students.This is consistent with the findings of Zuo Qun[25]et al during the outbreak of SARS in 2003 but not in agreement with the results of the immediately previous non-epidemic period[26].This suggests that female students showed more anxiety than did male students when emerging infectious diseases manifested as life-threatening with a high mortality rate.A prior study had shown that women are more likely to feel the tension and lose control,and female students showed more uncertainty in illness than did male students when faced with stressful events[27].Rural-based students revealed higher levels of uncertainty in illness than did urban-based students.The possible reason is that college students are at home during the COVID-19 epidemic,and compared with students in cities,students in a rural area had less information.Female students revealed higher levels of uncertainty in illness than did male students.Urban students revealed higher levels of life satisfaction than did rural students.The possible reason is that all of us stay at home to reduce cross-infection.The living area of the city is limited which is helpful to reach close communication.So the life satisfaction of urban students is higher than that of rural students.

The present study revealed that state anxiety had a negative effect on life satisfaction.This is consistent with previous research [28-29].This is because emotion is intrinsically associated with cognition.When individuals experience the impact of external events,state anxiety produced negative impacts on life satisfaction.This suggests that we can improve college students’life satisfaction by reducing individual anxiety during the COVID-19 pandemic.Uncertainty in illness had a negative effect on life satisfaction.Small and Graydon [13]pointed to developing uncertainty in illness when a person is unable to decide what to do or how to address a problem.The greater the pressure,the easier it is to make people feel dissatisfied[30].Uncertainty in illness had a positive effect on state anxiety.Mishel and Braden[12]pointed out that when an individual is faced with uncertainty in illness,they will show more pessimism and make negative evaluations if they are considered dangerous,so they will show more anxiety and other emotions.

Structural equation models indicated that state anxiety plays a partial mediating role in the relationship between uncertainty in illness and life satisfaction.In line with Mishel’s theory of uncertainty in illness,individuals are more prone to pessimistic views and negative evaluation,and anxiety if the uncertainty in illness is considered to be a risk factor[12].Emmons and Diener stated that negative emotions such as anxiety were more likely to affect people than objective events and the wider environment.Anxiety can make people feel dissatisfied,thus reducing life satisfaction[31].Therefore,we can improve college students’life satisfaction from the following two aspects during the COVID-19 epidemic:One is to reduce college students’uncertainty in illness.Following uncertainty in illness theory,education,social support,and reliable authority are the three main factors to reduce uncertainty in illness[32].Therefore,we should strengthen the education of college students about the coronavirus through WeChat and class QQ group during the COVID-19 epidemic and support the individual with their reintegration into the family.College students should consciously pay attention to the interpretation of the epidemic situation by medical authorities and consciously identify the false information about the epidemic situation.The second approach is to reduce the state anxiety of college students.A previous study showed that attention bias training,mindfulness meditation practice,long-term aerobic exercise,and yoga may reduce the anxiety of college students[33-35].Therefore,it is suggested that students engage in the above activities to reduce their state anxiety.

The main study limitation is the cross-sectional study design.Accordingly,the results of the statistical analyses indicate an association but causality cannot be determined.

Conclusions

The main conclusions of this study are as follows:

1.Uncertainty in illness had a negative effect on life satisfaction.Uncertainty in illness had a positive effect on state anxiety.State anxiety had a negative effect on life satisfaction.

2.State anxiety played an important mediating role in the relationship between uncertainty in illness and life satisfaction—its mediating effect accounted for 17.43% of the total effect.