Next Article in Journal
(Tele)Work and Care during Lockdown: Labour and Socio-Familial Restructuring in Times of COVID-19
Previous Article in Journal
Spatial and Temporal Trends of SARS-CoV-2 RNA from Wastewater Treatment Plants over 6 Weeks in Cape Town, South Africa
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
IJERPH
Volume 18
Issue 22
10.3390/ijerph182212086
ijerph-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

The Mediating Effect of Coping Style on Physical Activity and Negative Affect Caused by Public Health Emergencies: Evidence from Chinese College Students

by
Yuetao Liu
,
Zhiyuan Wang
* and
Songhui You
*
International College of Football, Tongji University, Shanghai 200092, China
*
Authors to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2021, 18(22), 12086; https://doi.org/10.3390/ijerph182212086
Submission received: 24 August 2021 / Revised: 24 October 2021 / Accepted: 10 November 2021 / Published: 17 November 2021
(This article belongs to the Topic Burden of COVID-19 in Different Countries)
Browse Figures
Versions Notes

Abstract

:
In this study, we explored the relationship between physical activity (PA), coping style (CS) and negative affect caused by public health emergencies (PHENA), to examine if CS can play a mediating role between PA and PHENA, and analyzed the different effects of positive coping (PC) and negative coping (NC). Using the method of random sampling, 700 students from four universities in Beijing and Shanghai were recruited to complete questionnaires about PA, CS and PHENA. Data collection was conducted through online and offline questionnaires. Firstly, there is a significant correlation between PA, CS and PHENA. Secondly, PA can negatively predict PHENA, and PA has positive impact on PC and negative impact on NC. Thirdly, the mediating role of NC related to PHENA is significant, the mediating role of PC related to PHENA is not significant. College students’ participation in physical activity can reduce the probability of adopting negative coping mechanisms, thereby alleviating the PHENA.

1. Introduction

Every public health emergency (such as SARS, H1N1, Ebola) is a disaster for public health. The most recent COVID-19 pandemic has imposed enormous pressure on governments, medical and healthcare providers and the general public [1], and the pressure is still going on. The pandemic brought not only the risk of death from the viral infection but also unbearable psychological pressure to people in China and the rest of the world [2]. The physical damage caused by public health emergencies may recover in a short time, but the psychological impact will last for a long time. Public health messages often use persuasive language to change attitudes and behaviors, which can evoke a wide range of negative and positive emotional responses [3]. As COVID-19 continues, the public is experiencing different levels of psychological distress, such as nervousness, fear of infection, anxiety, depression, sleep problems, and inattention [4,5]. The college years represent a period of increased vulnerability for a wide range of mental health challenges [6]. Younger people are at especially high risk of being psychologically affected by the pandemic when they spend too much time thinking about the outbreak [7]. College students are in a special period of physical and mental development, and therefore public health emergencies can affect them psychologically in an irreversible and profound way [8].

1.1. Negative Affect Caused by Public Health Emergencies

Life events are an important factor in inducing negative affect, which can lead to an increase in problem behaviors and affective disorders [9]. The adverse effects created from one external crisis event (e.g., public health emergencies) will spill over and interfere with the judgment of the decision maker on other routine matters through negative affect [10]. According to research conducted by Gao during SARS, negative affect caused by public health emergencies (PHENA) includes neurasthenia, depression, obsession, anxiety, fear, and hypochondriasis [11,12]. Among them, obsession, fear, and hypochondriasis are negative affects which are unique during the special period of public health emergencies. Numerous studies have confirmed the existence of PHENA among college students. The emotional changes of college students during the SARS period are highlighted by fear [11]. During COVID-19, negative affect such as anxiety and depression are relatively common. A study of Chinese college students found that 24.9% of respondents had symptoms of anxiety, of which 3.6% were moderate or severe anxiety [13].

1.2. Physical Activity

Exercise intervention has long been regarded as an alternative or supplementary method for the treatment of psychological problems [14]. A wealth of evidence supports the positive impact of physical activity (PA) on mental health [15,16,17,18,19,20]. For mild-to-moderate depression, the effect of PA may be comparable to antidepressant medication and psychotherapy [21]. PA is positively associated with college students’ positive affect. PA appears to enhance positive affect during a global pandemic [22,23]. PA can also reduce the impact of anticipated negative affect [24]. Associations between PA and affect may differ depending on the extent to which one experiences stressful life events [25]. In the period of public health emergencies, whether PA can still play a role in reducing negative affect is a question worth exploring.

1.3. Coping Style

Coping is one of the most extensively studied concepts in psychology [26], it encompasses two concepts. The first is that of stable coping style (CS) which characterizes an individual’s interaction with his or her stressful environment, and the second involves coping skills or techniques that people use to manage specific stressful situations [27,28,29]. CS refers to the cognitive and behavioral styles used by individuals in the face of frustration and pressure [30]. Assessing an individual’s coping style and understanding its relationship with mental health is an important content of psychological research. Lazarus and Folkman proposed eight specific coping methods based on the results of factor analysis, such as confrontation, avoidance, self-control, and seeking support, etc. [31]. Stone and Neate also proposed eight coping styles, such as distraction, re-evaluation of the environment, catharsis, and relaxation [32]. Yang put forward six types of coping methods, such as selective neglect, changing the value system, recklessness or taking risks [33]. From the perspectives of different researchers, it can be seen that there are many types of coping styles. However, further analysis found that the coping styles proposed by different researchers have common characteristics, that is, some coping styles have more positive components, such as seeking support and trying to change, while others are dominated by negative components, such as avoidance and venting [34]. Many coping style assessment methods have been developed, such as the “Ways of Coping Questionnaire” compiled by Folkman and Lararus. Some scholars have tried to apply the questionnaire to the Chinese population and found that due to differences in cultural background, foreign scales are not suitable for the Chinese population. One reason is that some content is not suitable, and the other is that the results of factor analysis are inconsistent. Based on the characteristics of Chinese culture, Xie simplified and revised the foreign coping style scales, and compiled the “Simple Coping Style Questionnaire” with two dimensions, positive coping (PC) and negative coping (NC). The scale has been widely used in Chinese psychology circles. A large number of studies based on this have shown that when the NC score is high, the score for psychological problems or symptoms is also high; while when the PC score is high, the score for psychological problems or symptoms is low. Additionally, many scholars use it as an important intermediary variable for research.

1.4. The Present Study and Hypothetical Model

The effect of PA has been inquired in different ages of people such as children [35,36,37], adolescents [37,38,39,40], middle-aged people [41,42] and older adults [43,44,45,46]. There have also been studies on different populations, for instance, pregnant women and mothers [47,48], nurses [49], patients [50,51,52,53,54], and people with overweight/obesity [55,56]. Some scholars have also emphasized the benefits of family members exercising together, such as father–daughter [57,58] and mother–child [59]. The overwhelming majority of studies support that PA can reduce negative affect and promote mental health. The effect varies with the intensity [42] and frequency [60] of PA, age [46], gender [61], etc. A small number of studies do not support the role of PA, and they believe that both positive affect and negative affect precede rather than follow PA engagement [62].
Researches on PA during COVID-19 show that it was associated with higher resilience [46,63], less negative affect [23,37,46], and better psychological wellbeing [64,65]. Although there have been kinds studies in the literature revealing the association between PA and general negative affect such as depression and anxiety, the relationship between PA and PHENA is still unclear.
When faced with stress or traumatic events, people will adopt different CS; some will respond positively while others negatively [40]. There is widespread conviction among healthcare professionals that coping influences affect [66]. NC may be related to psychological distress or mental illnesses such as anxiety and depression [67,68]. People with NC show a higher level of psychological distress [69]. Coping research has shown that NC, such as indulging in negative topics, can exacerbate negative affects such as anxiety [70]. In contrast, PC may promote emotional wellbeing [71]. Fredrickson believes that affect and coping can influence each other [71]. Which direction of causation is of greater importance depends on the research question, if the question is how best to intervene to reduce depression, the direction of interest is from coping to affect [72]. Coping is an important mediator in the regulation of affect [66]. Though CS is stable [73], it is not unchangeable. Many studies have confirmed that PA can affect CS [74,75,76,77]. Firstly, PA can affect people’s CS through changes in their physiological functions and mood. Secondly, through the unique cluster environment of PA, it can also affect the individual’s CS and emotional regulation [78]. To our knowledge, research on the mediating role of CS between PA and PHENA is still blank. We aim to overcome limitations of other studies that only focus on general negative affect. This study will discuss the relationship between PA and PHENA, and further try to explain its mechanism of action.
After review of previous studies, the present study believes that CS may be an important intermediary variable between PA and PHENA. Based on this, this study takes college students as subjects and proposes the following hypotheses H1: PA is significantly negatively correlated with PHENA; H2: CS plays a mediating role between PA and PHENA. The hypothetical model is shown in Figure 1.

2. Materials and Methods

2.1. Participants and Procedure

Using the method of simple random sampling, from September to October 2020, 700 students from Renmin University of China, Beijing Sport University, Tongji University and East China Normal University were selected randomly to conduct a questionnaire survey without repeating. The four universities are different types of universities from different regions of China. We recruited respondents randomly through online chats, mailing lists and offline methods. The invitation letter contained the introduction of the research, the reward for filling out the questionnaire, the obligations of the investigator and respondent, the principle of confidentiality and the Informed Consent Form. Respondents were asked to scan a predesigned QR code to fill out the questionnaire online. Before filling out the questionnaire, the Informed Consent Form will be displayed first, and only after the content of the Informed Consent Form has been read and accepted will the respondent be allowed to enter the formal questionnaire survey. Before the start of the questionnaire survey, we carried out a test–retest reliability test with 50 samples. The interval between the two tests is 20 days, and the Pearson’s correlation coefficient is used for testing. Pearson’s correlation coefficient is used to calculate test–retest reliability on SPSS. All questionnaires are compiled, filled out and collected through Wenjuan.com. Each person can only submit the questionnaire once.
The questionnaire has 54 items in total, including three scales and some demographic variables. Bentler [79] proposed that only the ratio of sample number to item number could reach 5:1, to ensure the reliability of parameter estimation. A ratio of 10:1 can guarantee the validity of the significance test. Considering economy and sample reliability, the number of samples in this study is controlled to be between 500 and 800. We set up two screening items in the questionnaire, such as “Please choose 1 for this question”. At the same time, invalid questionnaires were eliminated according to the principle that the answering time of the questionnaires should not be less than 1 min. A total of 906 invitations were randomly distributed, of which 61 people responded and rejected the survey. When 700 samples were collected, we closed the questionnaire entry portal. A total of 700 questionnaires were received, of which 633 were valid questionnaires and therefore the effective rate was 90.43%, with no missing data. Of all valid questionnaires, 58.8% (n = 372) of the sample identified as female and 41.2% (n = 261) were male. On average, participants were 21.53 years old (SD = 2.47, Range 17–29). All participants were Chinese students from universities in Beijing and Shanghai—44.25% are undergraduate students, 49.27% are postgraduate students, and 6.48% are doctoral students.

2.2. Measures

2.2.1. Physical Activity

The “Physical Activity Scale-3” (PARS-3) [80] is used to measure the college students’ amount of exercise from three aspects: frequency, duration and intensity. This questionnaire is the most widely used scale for measuring the amount of PA in China. Likert-5 points, ranging from 1 to 5, are used for scoring. PA intensity is measured by selecting the most suitable option from 1 (light exercise, no sweating), 2 (low intensity exercise, slightly sweating), 3 (medium-intensity, more intense and long-lasting exercise, obviously sweating), 4 (high-intensity intermittent shortness of breath exercise, sweating a lot), 5 (high-intensity continuous shortness of breath exercise, profuse sweating) according to actual situations. PA frequency is the frequency of participating in exercise. Options include 1 (1 time a month or less), 2 (2 to 3 times a month), 3 (1 to 2 times a week), 4 (3 to 5 times a week), 5 (approximately once a day). PA duration is approximately how long each exercise lasts. Options include 1 (10 min and below), 2 (11 to 20 min), 3 (21 to 30 min), 4 (31 to 59 min), 5 (60 min and above). It also surveyed the exercise programs that respondents often participated in. The test–retest reliability of the PARS-3 is 0.82, and the Cronbach α is 0.81.

2.2.2. Coping Style

The “Simple Coping Style Questionnaire” [34] is used for measurement. It includes two subscales, namely positive coping (PC) and negative coping (NC). The questionnaire consists of 20 items, involving different attitudes and measures that people may often take in daily life. Including 12 PC items such as “try to see the good side of things”, “seeking advice from relatives, friends or classmates”, and 8 NC items such as “relieving worries by smoking, drinking, taking medicine and eating”, “accept the reality, because there is no other way”, etc. The questionnaire assessed two dimensions on a 5-point Likert-type scale from 1 (never adopted) to 5 (often adopted). The test–retest reliability of the scale is 0.89. The Cronbach α of the full scale is 0.90. The PC scale is 0.89, and the NC scale is 0.78.

2.2.3. Public Health Emergency Negative Affect

The “Psychological Questionnaire for Sudden Public Health Events” [11] including five scales, namely depression, neurasthenia, fear, obsessive-anxiety and hypochondriasis is employed in the present study. In this study, 5 dimensions were combined into 4, consisting of 23 emotional reactions that may occur during the pandemic: depression-neurasthenia (11 items; e.g., “Feel annoyed and get angry easily.”), fear (4 items; e.g., “In places where people gather, especially near hospitals, feel frightened and nervous.”), obsessive-anxiety (4 items; e.g., “Wash hands repeatedly, but always feel that they are not clean enough.”), hypochondriasis (4 items; e.g., “Very concerned about any physical discomfort.”). The 23-item questionnaire assessed 4 dimensions on a 5-point Likert-type scale from 1 (none) to 5 (severe). The test–retest reliability of the questionnaire is 0.82. The Cronbach α of the questionnaire is 0.95. The depression scale is 0.96, the fear scale is 0.94, the obsessive-anxiety scale is 0.85, and the hypochondriasis scale is 0.86.

2.3. Data Analysis

Harman’s single-factor test method is used for principal component analysis [81,82]. A total of 7 factors with characteristic roots over 1 are generated, and the first one explains 38.44% of the variation, which is less than the critical standard of 40%. Thus, common method bias is not an issue of concern.
KMO and Barlett Test of Sphericity are used to test the data in the scales. The KMO value is 0.923, which is greater than 0.8. The p-value of Bartlett’s test is 0.000, which satisfies the significance test. This result confirms that the data in the scales are very suitable for factor analysis. We used SPSS to perform factor analysis to test whether the measurement items in the questionnaire are consistent with the factors we designed. By extracting principal components, 7 factors with initial eigenvalues over 1 are obtained, and the cumulative explained variance variation is 72.520%. Therefore, the explanation degree is relatively ideal. The feature value does not change significantly when more than 8 components are extracted. Therefore, 7 factors including PA, PC, NC, depression-neurasthenia, fear, obsessive-anxiety and hypochondriasis are finally extracted. The factor load of the above 7 factors corresponding to their topics is greater than 0.5, and the average variance, AVE, is greater than 0.5 as well. Among them, depression and neurasthenia are two independent factors in Gao’s research [11]. However, the concept of neurasthenia has not been universally accepted in academia. It should be noted that the term “neurasthenia” has rarely been used in clinical diagnosis by Chinese psychiatrists since the year 1995 [83]. Arthur-Kleinman believed that the disease named “neurasthenia” in China is the same as “depression” in the West. Chen Jianmei [84] believes that there is almost no essential difference between the symptoms of neurasthenia and depression. The results of this study also confirm this point. Therefore, in the present study, the factor of depression and that of neurasthenia are combined together as depression factors.
In order to test whether there is a correlation between the variables, SPSS was used for Pearson’s correlation analysis, and the mean and standard deviation were calculated. We performed SEM using AMOS 24.0.0. We established a structural equation model in AMOS based on the hypothetical model. Model fitting index χ2/df = 2.221, RMR = 0.046, GFI = 0.970, AGFI = 0.954, NFI = 0.944, RFI = 0.927, IFI = 0.968, TLI = 0.959, CFI = 0.968, RMSEA = 0.042. According to the structural equation model fitting standard proposed by Bollen [85]: χ2/df ≤ 3.00, RMSEA ≤ 0.08, CFI, NFI, RFI, IFI, AGFI ≥ 0.90. All indicators in this study have reached the fitting standard and the model is well fitted. Traditional standard procedure and bootstrap methods were adopted to test mediation.

3. Results

3.1. Descriptive Statistics and Correlations

The Pearson’s correlation analysis of the bivariate of every variable is performed in the present study. Table 1 lists the average value, standard deviation and correlation matrix of each variable. The results show that, except for PA and fear, PC and fear, PC and hypochondriasis, there is a significant correlation between the remaining variables. To be more specific, PA is positively correlated with PC while negatively correlated with NC, depression, obsessive-anxiety and hypochondriasis. Additionally, variables including NC, depression, fear, obsessive-anxiety, and hypochondriasis are all positively correlated with each other.

3.2. Mediating Effects of CS

To test mediation, we followed the standards steps that must be met before a variable may be considered a mediating variable. Table 2 provides the estimates obtained from the structural equation model. Model 1 shows that PA significantly predicted PHENA (β = −0.138, p < 0.01), supporting H1. Model 2 shows the positive impact of PA on PC (β = 0.160, p < 0.01) and negative impact on NC (β = −0.272, p < 0.001). Model 3 shows that the mediating role of NC related to PHENA (β = 0.368, p < 0.001) is significant, and the mediating role of PC related to PHENA (β = −0.073, p > 0.1) is not significant. This suggests that PA influences NC, and NC in turn influences PHENA.
The final step is to show whether or not the strength of the relationship between PA and PHENA is significantly reduced when PC and NC are added to Model 1. When Model 4 includes the mediator of PC and NC, the influence of PA on PHENA is not statistically significant (β = −0.033, p > 0.1), supporting H2. This indicates that the effect of PA is completely mediated by NC. Without considering CS, the direct effect of PA on PHENA is supported by H1. However, while CS was incorporated into Model 1, it is surprising that the effect of PA on PHENA does not seem to have a significant effect. The result provides evidence for the complete mediating role of NC. According to the structural equation model-fitting standard proposed by Bollen [85], all indicators in this study have reached the fitting standard and the model is well fitted. The mediating effect model of CS between PA and PHENA is built as shown in Figure 2. Without considering the mediating effect of CS, the regression coefficient between PA and PHENA is −2.839. After adding CS, the regression coefficient between PA and PHENA is −0.645, PA and PC is 3.015, PA and NC is −4.593, PC and PHENA is −1.775, NC and PHENA is 5.827.
The most popular method to test the mediation effect is the causal steps approach of Baron and Kenny [86]. However, in recent years, the causal steps approach has been criticized and questioned [87,88,89,90]. At present, it is generally believed that the Bootstrap method is a better method to directly test the significance of the coefficient product [90]. The percentile Bootstrap method with offset correction is also used to test the mediating effect of the CS. In the original data, 5000 samples are drawn by repeated random sampling. The results, as shown in Table 3, suggest that the bootstrap 95% confidence interval of the total effect of PA and PHENA contains a value of 0. It indicates that the direct effect of PA on PHENA is not significant. The Bootstrap 95% confidence interval of the indirect effects produced by PC contains a value of 0, which indicates that the mediating effect of PC is not significant as well. On the contrary, the bootstrap 95% confidence interval of the indirect effects produced by NC does not contain a value of 0. It indicates that NC has a significant mediating effect between PA and PHENA. The above results suggest that NC plays a complete mediating role between PA and PHENA, and the mediating effect is 67.83%.

4. Discussion

The findings from this study indicate that PA can negatively predict PHENA. The hypothesis H1 is verified, and this extends the previous research conclusions on PA and negative affect [17,22,23]. PA provides people with a kind of emotional regulation or physical confrontation for coping with stress [91], improve the exerciser’s antistress capability [92], and reduce the intensity of stress response [93]. For example, PA can reduce cortisol concentrations during stress, thereby reducing the impact of stress on health [94].
The above studies have analyzed the relationship between PA and affect. Some other scholars have also discussed the relationship between PA and coping and the relationship between coping and affect. Most research results support that PA can improve mood, and encourage exercisers to adopt more positive CS and reduce negative CS [95]. CS can affect the nature and intensity of the stress response, and further regulate the relationship between stress and physical and psychological health [96]. This study confirms the mediating role of CS between PA and PHENA, and verifies the validity of hypothesis H2. PA can significantly improve the PC level while reducing the NC level, but only NC can significantly and positively predict PHENA. This result also supports the view that PC and NC have different mediating effects [67,68,69].
This study reveals the mechanism between PA and PHENA, with CS playing a mediating role. PA can alleviate PHENA by improving the way of coping with stressful events in the pandemic. CS exerts a completely mediating effect, in which NC plays a mediating role while the PC does not exert a significant mediating effect. The effect of PA on improving CS is probably because PA improves the level of psychological capital appreciation (PCA) and body-esteem of college students [97,98]. Performing moderate-to-high intensity PA can enhance the adolescent’s sense of self-efficacy, which optimizes their CS [77]. PA enables them to have strong confidence in their capability to solve problems and their physical abilities, so that they are more likely to respond to external challenges positively rather than negatively. If more negative CS is used to respond to stressful events, maladaptation may occur, causing individuals to experience higher levels of negative affect [99]. If negative affect is not released in time, it can easily accumulate and finally turn into long-term “chronic diseases” [100]. Furthermore, PA can not only enhance positive mental health but accrue additional health-promoting benefits such as increased immunity among college students [25]. Training regimens during pandemic crises should be introduced as standard habits for health and wellbeing [101].
This study has several limitations and areas that can be addressed in future research. First of all, the questionnaire data in this survey were collected in a specific process, so there will be a certain degree of one-sidedness. We recommend longitudinal analysis at different stages of public health emergencies. Secondly, the college students surveyed in this study are all from China’s megacities, so it cannot accurately reflect the situation of college students in other cities in China and abroad. We suggest that it can be expanded to global research for comparison.

5. Conclusions

College students’ participation in physical activity can alleviate PHENA through reducing the probability of adopting negative coping mechanisms. The main bodies of the response mechanism for public health emergencies mainly include the government, social organizations and individuals. Reducing the impact of public health emergencies depends on the interaction between the three types of subjects. Therefore, during periods of public health emergency, firstly, the active role of PA in public health emergencies should be brought into full play. PA should be included in the Emergent Public Health Incident Preparedness and Response System. For most developing countries, encouraging PA is a cost-effective way to improve the health of the population. Secondly, attention should be paid to high-risk groups such as college students. The government and educational organizations should play a leading role, while doing a good job in safety education and management, fully mobilizing the individual subjective initiative of college students to participate in PA.

Author Contributions

Conceptualization, Y.L., Z.W. and S.Y.; methodology, Y.L., Z.W. and S.Y.; validation, Y.L. and Z.W.; formal analysis, Y.L. and Z.W.; investigation, Y.L. and Z.W.; data curation, Y.L.; writing—original draft preparation, Y.L.; writing—review and editing, Z.W.; supervision, Z.W.; project administration, Y.L., Z.W. and S.Y.; funding acquisition, Y.L., Z.W. and S.Y. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Federation of University Sports of China, grant number 202013511; and the Fundamental Research Funds for the Central Universities, grant number 22120200376.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The data presented in this study are available on request from the corresponding author. The data are not publicly available due to confidentiality.

Conflicts of Interest

The authors declare no conflict of interest. The funders had no role in the design of the study, in the collection, analyses, or interpretation of data, in the writing of the manuscript, or in the decision to publish the results.

References

  1. Wang, C.; Pan, R.; Wan, X.; Tan, Y.; Xu, L.; Ho, C.S.; Ho, R.C. Immediate psychological responses and associated factors during the initial stage of the 2019 coronavirus disease (COVID-19) epidemic among the general population in China. Int. J. Environ. Res. Public Health 2020, 17, 1729. [Google Scholar] [CrossRef] [Green Version]
  2. Xiao, C. A novel approach of consultation on 2019 novel coronavirus (COVID-19)-related psychological and mental problems: Structured letter therapy. Psychiatry Investig. 2020, 17, 175–176. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  3. Heffner, J.; Vives, M.-L.; FeldmanHall, O. Emotional responses to prosocial messages increase willingness to self-isolate during the COVID-19 pandemic. Personal. Individ. Differ. 2021, 170, 110420. [Google Scholar] [CrossRef]
  4. Kang, L.J.; Li, Y.; Hu, S.H.; Chen, M.; Yang, C.; Yang, B.X.; Wang, Y.; Hu, J.B.; Lai, J.B.; Ma, X.C.; et al. The mental health of medical workers in Wuhan, China dealing with the 2019 novel coronavirus. Lancet Psychiatry 2020, 7, E14. [Google Scholar] [CrossRef] [Green Version]
  5. Xiang, Y.T.; Yang, Y.; Li, W.; Zhang, L.; Zhang, Q.E.; Cheung, T.; Ng, C.H. Timely mental health care for the 2019 novel coronavirus outbreak is urgently needed. Lancet Psychiatry 2020, 7, 228–229. [Google Scholar] [CrossRef] [Green Version]
  6. Liu, C.H.; Stevens, C.; Wong, S.H.M.; Yasui, M.; Chen, J.A. The prevalence and predictors of mental health diagnoses and suicide among US college students: Implications for addressing disparities in service use. Depress. Anxiety 2019, 36, 8–17. [Google Scholar] [CrossRef]
  7. Huang, Y.E.; Zhao, N. Mental health burden for the public affected by the COVID-19 outbreak in China: Who will be the high-risk group? Psychol. Health Med. 2021, 26, 23–34. [Google Scholar] [CrossRef] [Green Version]
  8. Mei, S.L.; Yu, J.X.; He, B.W.; Li, J.Y. Psychological investigation of university students in a university in Jilin province. Med. Soc. 2011, 24, 84–86. [Google Scholar]
  9. Walker, M.S.; Zona, D.M.; Fisher, E.B. Depressive symptoms after lung cancer surgery: Their relation to coping style and social support. Psycho-Oncol. 2006, 15, 684–693. [Google Scholar] [CrossRef]
  10. Li, O.; Zhao, C. How the COVID-19 pandemic influences judgments of risk and benefit: The role of negative emotions. J. Risk Res. 2021, 24, 466–476. [Google Scholar] [CrossRef]
  11. Gao, Y.; Yang, Y.F.; Ma, Y.S.; Yao, K.N. A study on the emotional reaction status of college students during the SARS. Chin. J. Behav. Med. Brain Sci. 2004, 13, 62–64. [Google Scholar]
  12. Hu, W.; Wang, Q.; Chen, H.L.; Jiang, Y.H. The relationship between public risk perception and unintentional/intentional rumor spreading in the COVID-2019: The mediating role of negative emotions. Chin. J. Clin. Psychol. 2020, 28, 734–738. [Google Scholar]
  13. Cao, W.J.; Fang, Z.W.; Hou, G.Q.; Han, M.; Xu, X.R.; Dong, J.X.; Zheng, J.Z. The psychological impact of the COVID-19 epidemic on college students in China. Psychiatry Res. 2020, 287, 112934. [Google Scholar] [CrossRef]
  14. Crone, D.; Guy, H. ‘I know it is only exercise, but to me it is something that keeps me going’: A qualitative approach to understanding mental health service users’ experiences of sports therapy. Int. J. Ment. Health Nurs. 2008, 17, 197–207. [Google Scholar] [CrossRef] [PubMed]
  15. Burton, N.W.; Pakenham, K.I.; Brown, W.J. Are psychologists willing and able to promote physical activity as part of psychological treatment? Int. J. Behav. Med. 2011, 17, 287–297. [Google Scholar] [CrossRef] [PubMed]
  16. Holley, J.; Crone, D.; Tyson, P.; Lovell, G. The effects of physical activity on psychological well-being for those with schizophrenia: A systematic review. Br. J. Clin. Psychol. 2011, 50, 84–105. [Google Scholar] [CrossRef]
  17. Moylan, S.; Eyre, H.A.; Maes, M.; Baune, B.T.; Jacka, F.N.; Berk, M. Exercising the worry away: How inflammation, oxidative and nitrogen stress mediates the beneficial effect of physical activity on anxiety disorder symptoms and behaviours. Neurosci. Biobehav. Rev. 2013, 37, 573–584. [Google Scholar] [CrossRef] [PubMed]
  18. Soucy, I.; Provencher, M.D.; Fortier, M.; McFadden, T. Secondary outcomes of the guided self-help behavioral activation and physical activity for depression trial. J. Ment. Health 2019, 28, 410–418. [Google Scholar] [CrossRef] [PubMed]
  19. Stonerock, G.L.; Hoffman, B.M.; Smith, P.J.; Blumenthal, J.A. Exercise as treatment for anxiety: Systematic review and analysis. Ann. Behav. Med. 2015, 49, 542–556. [Google Scholar] [CrossRef] [Green Version]
  20. Swann, C.; Telenta, J.; Draper, G.; Liddle, S.; Fogarty, A.; Hurley, D.; Vella, S. Youth sport as a context for supporting mental health: Adolescent male perspectives. Psychol. Sport Exerc. 2018, 35, 55–64. [Google Scholar] [CrossRef]
  21. Knapen, J.; Vancampfort, D.; Morien, Y.; Marchal, Y. Exercise therapy improves both mental and physical health in patients with major depression. Disabil. Rehabil. 2015, 37, 1490–1495. [Google Scholar] [CrossRef] [PubMed]
  22. Bird, J.M.; Karageorghis, C.I.; Hamer, M. Relationships among behavioural regulations, physical activity, and mental health pre- and during COVID–19 UK lockdown. Psychol. Sport Exerc. 2021, 55, 101945. [Google Scholar] [CrossRef] [PubMed]
  23. Maher, J.P.; Hevel, D.J.; Reifsteck, E.J.; Drollette, E.S. Physical activity is positively associated with college students’ positive affect regardless of stressful life events during the COVID-19 pandemic. Psychol. Sport Exerc. 2021, 52, 5. [Google Scholar] [CrossRef] [PubMed]
  24. Wang, X. The role of anticipated negative emotions and past behavior in individuals’ physical activity intentions and behaviors. Psychol. Sport Exerc. 2011, 12, 300–305. [Google Scholar] [CrossRef]
  25. Sallis, J.F.; Pratt, M. Multiple benefits of physical activity during the Coronavirus pandemic. Rev. Bras. De Ativ. Física Saúde 2020, 25, 1–5. [Google Scholar] [CrossRef]
  26. Penley, J.A.; Tomaka, J.; Wiebe, J.S. The association of coping to physical and psychological health outcomes: A meta-analytic review. J. Behav. Med. 2002, 25, 551–603. [Google Scholar] [CrossRef]
  27. Beutler, L.E.; Moos, R.H.; Lane, G. Coping, treatment planning, and treatment outcome: Discussion. J. Clin. Psychol. 2003, 59, 1151–1167. [Google Scholar] [CrossRef] [PubMed]
  28. Moos, R.H.; Holahan, C.J. Dispositional and contextual perspectives on coping: Toward an integrative framework. J. Clin. Psychol. 2003, 59, 1387–1403. [Google Scholar] [CrossRef]
  29. Shikai, N.; Nagata, T.; Kitamura, T. Do people cope with situations as they say? Relationship between perceived coping style and actual coping response. Psychiatry Clin. Neurosci. 2014, 68, 154–159. [Google Scholar] [CrossRef]
  30. Folkman, S.; Lazarus, R.S.; Gruen, R.J.; Delongis, A. Appraisal, coping, health-status, and psychological symptoms. J. Personal. Soc. Psychol. 1986, 50, 571–579. [Google Scholar] [CrossRef]
  31. Zeidner, M.; Endler, N.S. Handbook of Coping: Theory, Research, Applications; John Wiley & Sons: Hoboken, NJ, USA, 1995; Volume 195. [Google Scholar]
  32. Parker, G.; Brown, L.; Blignault, I. Coping behaviors as predictors of the course of clinical depression. Arch. Gen. Psychiatry 1986, 43, 561–565. [Google Scholar] [CrossRef]
  33. Yang, D.S. Behavioral Medicine; Hunan Science and Technology Press: Changsha, China, 2008. [Google Scholar]
  34. Xie, Y.N. A preliminary study on the reliability and validity of the simple coping style scale. Chin. J. Clin. Psychol. 1998, 6, 53–54. [Google Scholar]
  35. Do, B.; Mason, T.B.; Yi, L.; Yang, C.H.; Dunton, G.F. Momentary associations between stress and physical activity among children using ecological momentary assessment. Psychol. Sport Exerc. 2021, 55, 101935. [Google Scholar] [CrossRef]
  36. Vasilopoulos, F.; Ellefson, M.R. Investigation of the associations between physical activity, self-regulation and educational outcomes in childhood. PLoS ONE 2021, 16, e0250984. [Google Scholar] [CrossRef]
  37. Zhang, X.X.; Zhu, W.F.; Kang, S.F.; Qiu, L.K.; Lu, Z.J.; Sun, Y.L. Association between physical activity and mood states of children and adolescents in social isolation during the COVID-19 epidemic. Int. J. Environ. Res. Public Health 2020, 17, 7666. [Google Scholar] [CrossRef] [PubMed]
  38. Belcher, B.R.; Zink, J.; Azad, A.; Campbell, E.; Chakravartti, S.P.; Herting, M.M. The roles of physical activity, exercise, and fitness in promoting resilience during adolescence: Effects on mental well-being and brain development. Biol. Psychiatry-Cogn. Neurosci. Neuroimaging 2021, 6, 225–237. [Google Scholar] [CrossRef] [PubMed]
  39. Bowe, A.K.; Healy, C.; Cannon, M.; Codd, M.B. Physical activity and emotional-behavioural difficulties in young people: A longitudinal population-based cohort study. Eur. J. Public Health 2021, 31, 167–173. [Google Scholar] [CrossRef] [PubMed]
  40. Wang, H.Y.; Shen, B.; Bo, J. Profiles of health-related quality of life and their relationships with happiness, physical activity, and fitness. Res. Q. Exerc. Sport 2020, 91, 80. [Google Scholar] [CrossRef] [PubMed]
  41. Jeong, Y.W.; Jin-Sub, S. Effects of middle-aged women’s emotions on resilience elasticity and psychological happiness in physical activities. Korean Soc. Wellness 2019, 14, 347–362. [Google Scholar]
  42. Qiu, Y.; Zhang, G. The current situation of beijing residents’ physical activities and its influence on their emotion. Chin. J. Sports Med. 2019, 38, 1054–1061. [Google Scholar]
  43. Franke, T.; Sims-Gould, J.; Nettlefold, L.; Ottoni, C.; McKay, H.A. “It makes me feel not so alone”: Features of the choose to move physical activity intervention that reduce loneliness in older adults. BMC Public Health 2021, 21, 1–15. [Google Scholar] [CrossRef]
  44. Lindsay-Smith, G.; Eime, R.; O’Sullivan, G.; Harvey, J.; van Uffelen, J.G.Z. A mixed-methods case study exploring the impact of participation in community activity groups for older adults on physical activity, health and wellbeing. BMC Geriatr. 2019, 19, 1–15. [Google Scholar] [CrossRef] [Green Version]
  45. Martinez-Moreno, A.; Ibanez-Perez, R.J.; Cavas-Garcia, F.; Cano-Noguera, F. Older adults’ gender, age and physical activity effects on anxiety, optimism, resilience and engagement. Int. J. Environ. Res. Public Health 2020, 17, 7561. [Google Scholar] [CrossRef] [PubMed]
  46. Zach, S.; Zeev, A.; Ophir, M.; Eilat-Adar, S. Physical activity, resilience, emotions, moods, and weight control of older adults during the COVID-19 global crisis. Eur. Rev. Aging Phys. Act. 2021, 18, 5. [Google Scholar] [CrossRef] [PubMed]
  47. Kolomanska-Bogucka, D.; Mazur-Bialy, A.I. Physical activity and the occurrence of postnatal depression-A systematic review. Med. -Lith. 2019, 55, 560. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  48. Limbers, C.A.; McCollum, C.; Greenwood, E. Physical activity moderates the association between parenting stress and quality of life in working mothers during the COVID-19 pandemic. Ment. Health Phys. Act. 2020, 19, 100358. [Google Scholar] [CrossRef] [PubMed]
  49. Owusu-Sekyere, F. Assessing the effect of physical activity and exercise on nurses’ well-being. Nurs. Stand. 2020, 35, 45–50. [Google Scholar] [CrossRef] [PubMed]
  50. Bahmani, D.S.; Razazian, N.; Motl, R.W.; Farnia, V.; Alikhani, M.; Puehse, U.; Gerber, M.; Brand, S. Physical activity interventions can improve emotion regulation and dimensions of empathy in persons with multiple sclerosis: An exploratory study. Mult. Scler. Relat. Disord. 2020, 37, 101380. [Google Scholar] [CrossRef]
  51. Bennett, E.V.; Voss, C.; Faulkner, G.; Harris, K.C. From ‘it makes me feel free’ to ‘they won’t let me play’: The body and physical activity-related perceptions and experiences of children with congenital heart disease and their parents. Qual. Res. Sport Exerc. Health 2021, 13, 325–341. [Google Scholar] [CrossRef]
  52. Papadopoulos, E.; Alibhai, S.M.H.; Dore, I.; Matthew, A.G.; Tomlinson, G.A.; Nesbitt, M.; Finelli, A.; Trachtenberg, J.; Santa Mina, D. Associations between self-reported physical activity, quality of life, and emotional well-being in men with prostate cancer on active surveillance. Psycho-Oncology 2020, 29, 1044–1050. [Google Scholar] [CrossRef] [PubMed]
  53. Park, J.-T.; Kim, Y.-W. A brain science study on the effects of inclusive physical activities on the emotion and cognition of the disabled. Asia-Pac. J. Intellect. Disabil. 2020, 7, 1–20. [Google Scholar]
  54. Tull, M.T.; Lee, A.A.; Geers, A.L.; Gratz, K.L. Exploring the role of sedentary behavior and physical activity in depression and anxiety symptom severity among patients with substance use disorders. Ment. Health Phys. Act. 2018, 14, 98–102. [Google Scholar] [CrossRef]
  55. Kerrigan, S.G.; Schumacher, L.; Manasse, S.M.; Loyka, C.; Butryn, M.L.; Forman, E.M. The association between negative affect and physical activity among adults in a behavioral weight loss treatment. Psychol. Sport Exerc. 2020, 47, 101507. [Google Scholar] [CrossRef] [PubMed]
  56. Smith, K.E.; Haedt-Matt, A.; Mason, T.B.; Wang, S.; Yang, C.H.; Unick, J.L.; Bond, D.; Goldschmidt, A.B. Associations between naturalistically assessed physical activity patterns, affect, and eating in youth with overweight and obesity. J. Behav. Med. 2020, 43, 916–931. [Google Scholar] [CrossRef]
  57. Pollock, E.R.; Young, M.D.; Lubans, D.R.; Barnes, A.T.; Eather, N.; Coffey, J.E.; Hansen, V.; Morgan, P.J. Impact of a father-daughter physical activity intervention: An exploration of fathers’ experiences. J. Child Fam. Stud. 2020, 29, 3609–3620. [Google Scholar] [CrossRef]
  58. Young, M.D.; Lubans, D.R.; Barnes, A.T.; Eather, N.; Pollock, E.R.; Morgan, P.J. Impact of a father-daughter physical activity program on girls’ social-emotional well-being: A randomized controlled trial. J. Consult. Clin. Psychol. 2019, 87, 294–307. [Google Scholar] [CrossRef] [PubMed]
  59. Kanning, M.; Do, B.; Mason, T.B.; Belcher, B.R.; Yang, C.H.; Dunton, G.F. Doing exercise or sport together with one’s child is positively associated with mothers’ momentary affect in daily life, but not with higher levels of overall physical activity. BMC Public Health 2020, 20, 1–10. [Google Scholar] [CrossRef] [PubMed]
  60. Liu, M.L.; Zhang, J.; Kamper-DeMarco, K.E.; Hu, E.W.; Yao, S.Q. Associations of moderate-to-vigorous physical activity with psychological problems and suicidality in Chinese high school students: A cross-sectional study. PeerJ 2020, 8, e8775. [Google Scholar] [CrossRef] [PubMed]
  61. Galdon Lopez, S.; Zurita Ortega, F.; Ubago Jimenez, J.L.; Gonzalez Valero, G. Impact of physical activity on emotional intelligence and sex differences. Retos-Nuevas Tend. En Educ. Fis. Deporte Y Recreacion 2021, 42, 636–642. [Google Scholar]
  62. Kruk, M.; Zarychta, K.; Horodyska, K.; Boberska, M.; Scholz, U.; Radtke, T.; Luszczynska, A. What comes first, negative emotions, positive emotions, or moderate-to-vigorous physical activity? Ment. Health Phys. Act. 2019, 16, 38–42. [Google Scholar] [CrossRef]
  63. Dursun, M.; Yarayan, Y.E.; Ari, C.; Ulun, C.; Adas, S.K. Covid-19 in Turkey: Leisure boredom, psychological resilience, physical activity and emotional state. IJERI-Int. J. Educ. Res. Innov. 2021, 15, 460–486. [Google Scholar] [CrossRef]
  64. Leon-Zarceno, E.; Moreno-Tenas, A.; Boix Vilella, S.; Garcia-Naveira, A.; Serrano-Rosa, M.A. Habits and psychological factors associated with changes in physical activity due to COVID-19 confinement. Front. Psychol. 2021, 12, 620745. [Google Scholar] [CrossRef]
  65. Qin, F.; Song, Y.Q.; Nassis, G.P.; Zhao, L.N.; Dong, Y.N.; Zhao, C.C.; Feng, Y.W.; Zhao, J.X. Physical activity, screen time, and emotional well-being during the 2019 novel coronavirus outbreak in China. Int. J. Environ. Res. Public Health 2020, 17, 5170. [Google Scholar] [CrossRef]
  66. Folkman, S.; Lazarus, R.S. Coping as a mediator of emotion. J. Personal. Soc. Psychol. 1988, 54, 466–475. [Google Scholar] [CrossRef]
  67. Hollifield, M.; Hewage, C.; Gunawardena, C.N.; Kodituwakku, P.; Bopagoda, K.; Weerarathnege, K. International post-tsunami study group symptoms and coping in Sri Lanka 20–21 months after the 2004 tsunami. Br. J. Psychiatry 2008, 192, 39–44. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  68. Sliter, M.; Kale, A.; Yuan, Z.Y. Is humor the best medicine? The buffering effect of coping humor on traumatic stressors in firefighters. J. Organ. Behav. 2014, 35, 257–272. [Google Scholar] [CrossRef]
  69. Wang, H.Y.; Xia, Q.; Xiong, Z.Z.; Li, Z.X.; Xiang, W.Y.; Yuan, Y.W.; Liu, Y.Y.; Li, Z. The psychological distress and coping styles in the early stages of the 2019 coronavirus disease (COVID-19) epidemic in the general mainland Chinese population: A web-based survey. PLoS ONE 2020, 15, e0233410. [Google Scholar] [CrossRef] [PubMed]
  70. Rose, A.J. Co-rumination in the friendships of girls and boys. Child Dev. 2002, 73, 1830–1843. [Google Scholar] [CrossRef]
  71. Fredrickson, B.L.; Joiner, T. Positive emotions trigger upward spirals toward emotional well-being. Psychol. Sci. 2002, 13, 172–175. [Google Scholar] [CrossRef]
  72. Folkman, S.; Moskowitz, J.T. Positive affect and the other side of coping. Am. Psychol. 2000, 55, 647–654. [Google Scholar] [CrossRef]
  73. Bolger, N. Coping as a personality process-A prospective-study. J. Personal. Soc. Psychol. 1990, 59, 525–537. [Google Scholar] [CrossRef]
  74. Chen, Y.; Li, X.; Sheng, W.W.; Zhou, Y.; Zhu, X.Y. The influence of middle school students’ physical exercise on their coping style: The mediating role of mental resilience. Basic Clin. Pharmacol. Toxicol. 2019, 125, 154–156. [Google Scholar]
  75. Luo, L.; Zeng, X.; Liao, X. Disease cognition, coping style and exercise behavior among the public during novel coronavirus epidemic: An online survey. China J. Public Health 2020, 36, 156–159. [Google Scholar]
  76. Ma, C.H.; Ma, L.X.; Helwan, A.; Maaitah, M.K.S.; Jami, S.A.; Mobarak, S.A.; Das, N.K.; Haque, M.A. An online survey and review about the awareness, coping style, and exercise behavior during the “COVID-19 pandemic situation” by implementing the cloud-based medical treatment technology system in China among the public. Sci. Prog. 2021, 104, 76. [Google Scholar] [CrossRef] [PubMed]
  77. Xu, T.; Li, Y.; Chen, X.; Wang, J.L.; Zhang, G.D. Effect of physical activity volume on active coping style among martial arts practicing adolescents: The mediating role of self-efficacy and positive affect. Arch. Budo 2020, 16, 315–324. [Google Scholar]
  78. Yin, J.C.; Ji, L. Can physical exercise cushion the psychological stress?—Based on the review of Hill’s 7 methodological standards. Sports Sci. 2013, 34, 24–29+23. [Google Scholar]
  79. Bentler, P.M.; Chou, C.P. Practical issues in structural modeling. Sociol. Methods Res. 1987, 16, 78–117. [Google Scholar] [CrossRef]
  80. Liang, D.Q. The stress level of college students and its relationship with physical exercise. Chin. Ment. Health J. 1994, 8, 5–6. [Google Scholar]
  81. Podsakoff, P.M.; MacKenzie, S.B.; Lee, J.Y.; Podsakoff, N.P. Common method biases in behavioral research: A critical review of the literature and recommended remedies. J. Appl. Psychol. 2003, 88, 879–903. [Google Scholar] [CrossRef] [PubMed]
  82. Zhou, H.; Long, L.R. Statistical test and control method of common method deviation. Adv. Psychol. Sci. 2004, 12, 942–950. [Google Scholar]
  83. Dai, Y.F.; Xiao, Z.P. Comparison of the 3rd edition of the Chinese classification and diagnostic criteria of mental disorders and the 10th edition of the international classification of diseases. J. Clin. Psychiatry 2013, 23, 426–427. [Google Scholar]
  84. Chen, J.M. How “neurasthenia” turned into “depression”: An analysis from the perspective of sociology. Med. Philos. 2011, 32, 35–36+78. [Google Scholar]
  85. Bollen, K.A.; Stine, R.A. Bootstrapping goodness-of-fit measures in structural equation models. Sociol. Methods Res. 1992, 21, 205–229. [Google Scholar] [CrossRef]
  86. Baron, R.M.; Kenny, D.A. The moderator mediator variable distinction in social psychological-research-conceptual, strategic, and statistical considerations. J. Personal. Soc. Psychol. 1986, 51, 1173–1182. [Google Scholar] [CrossRef]
  87. Edwards, J.R.; Lambert, L.S. Methods for integrating moderation and mediation: A general analytical framework using moderated path analysis. Psychol. Methods 2007, 12, 1–22. [Google Scholar] [CrossRef] [Green Version]
  88. Hayes, A.F. Beyond Baron and Kenny: Statistical mediation analysis in the new millennium. Commun. Monogr. 2009, 76, 408–420. [Google Scholar] [CrossRef]
  89. Spencer, S.J.; Zanna, M.P.; Fong, G.T. Establishing a causal chain: Why experiments are often more effective than mediational analyses in examining psychological processes. J. Personal. Soc. Psychol. 2005, 89, 845–851. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  90. Zhao, X.; Lynch, J.G., Jr.; Chen, Q. Reconsidering Baron and Kenny: Myths and truths about mediation analysis. J. Consum. Res. 2010, 37, 197–206. [Google Scholar] [CrossRef]
  91. Yan, J.; Sun, X.M.; Chen, A.G.; Zhu, F.S. The mediating effect of coping style and subjective well-being: An experimental study on the effect of physical exercise on the mental health of college girls. Sports Sci. 2011, 32, 95–99. [Google Scholar]
  92. Javelle, F.; Laborde, S.; Hosang, T.J.; Metcalfe, A.J.; Zimmer, P. The importance of nature exposure and physical activity for psychological health and stress perception: Evidence from the first lockdown period during the coronavirus pandemic 2020 in France and Germany. Front. Psychol. 2021, 12, 623946. [Google Scholar] [CrossRef] [PubMed]
  93. Mobily, K. Using physical activity and recreation to cope with stress and anxiety: A review. Am. Correct. Ther. J. 1982, 36, 77–81. [Google Scholar]
  94. Wood, C.J.; Clow, A.; Hucklebridge, F.; Law, R.; Smyth, N. Physical fitness and prior physical activity are both associated with less cortisol secretion during psychosocial stress. Anxiety Stress Coping 2018, 31, 135–145. [Google Scholar] [CrossRef] [PubMed]
  95. Thome, J.; Espelage, D.L. Relations among exercise, coping, disordered eating, and psychological health among college students. Eat. Behav. 2004, 5, 337–351. [Google Scholar] [CrossRef] [PubMed]
  96. Edwards, J.R.; Cooper, C.L. Research in stress, coping, and health—Theoretical and methodological issues. Psychol. Med. 1988, 18, 15–20. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  97. Craft, L.L. Exercise and clinical depression: Examining two psychological mechanisms. Psychol. Sport Exerc. 2005, 6, 151–171. [Google Scholar] [CrossRef]
  98. Downs, M.; Strachan, L. High school sport participation: Does it have an impact on the physical activity self-efficacy of adolescent males? Int. J. Hum. Mov. Sports Sci. 2016, 4, 6–11. [Google Scholar] [CrossRef] [Green Version]
  99. Kim, Y.; Valdimarsdottir, H.B.; Bovbjerg, D.H. Family histories of breast cancer, coping styles, and psychological adjustment. J. Behav. Med. 2003, 26, 225–243. [Google Scholar] [CrossRef] [PubMed]
  100. Huang, Y.L.; Guo, J.; Huang, F.; Li, Y.M. A sociological survey of sports actions to relieve social anxiety during the COVID-2019. J. Chengdu Sport Univ. 2020, 46, 8–15. [Google Scholar]
  101. Di Fronso, S.; Costa, S.; Montesano, C.; Di Gruttola, F.; Ciofi, E.G.; Morgilli, L.; Robazza, C.; Bertollo, M. The effects of COVID-19 pandemic on perceived stress and psychobiosocial states in Italian athletes. Int. J. Sport Exerc. Psychol. 2020, 1–13. [Google Scholar] [CrossRef]
Ijerph 18 12086 g001 550
Figure 1. Hypothetical model.
Figure 1. Hypothetical model.
Ijerph 18 12086 g001
Ijerph 18 12086 g002 550
Figure 2. Indirect and mediating effect model. The coefficients in the figure are standardized coefficients. The solid line represents the significant effect of the path, and the dashed line represents the insignificant effect of the path. The ovals and rectangles in this figure do not represent observed variables and latent variables. The ovals are structural variables, and the rectangles are the subdivision dimensions of the structural variable but do not participate in the structural model. *** p < 0.001, ** p < 0.01.
Figure 2. Indirect and mediating effect model. The coefficients in the figure are standardized coefficients. The solid line represents the significant effect of the path, and the dashed line represents the insignificant effect of the path. The ovals and rectangles in this figure do not represent observed variables and latent variables. The ovals are structural variables, and the rectangles are the subdivision dimensions of the structural variable but do not participate in the structural model. *** p < 0.001, ** p < 0.01.
Ijerph 18 12086 g002
Table
Table 1. Descriptive Statistics and Correlations.
Table 1. Descriptive Statistics and Correlations.
VariableMSDCorrelations
1234567
1. PA2.6720.9341
2. PC3.6430.7340.123 **1
3. NC2.6770.890−0.186 **−0.096 *1
4. Depression2.4090.955−0.118 **−0.191 **0.318 **1
5. Fear2.2040.995−0.036−0.070.182 **0.564 **1
6. Obsessive-Anxiety2.3360.983−0.131 **−0.095 *0.264**0.543 **0.659 **1
7. Hypochondriasis2.6881.010−0.117 **−0.0150.187 **0.485 **0.604 **0.578 **1
Note. ** p < 0.01, * p < 0.05.
Table
Table 2. Testing mediator effects using structural equation model.
Table 2. Testing mediator effects using structural equation model.
Testing Steps in Mediation ModelModel 1
Coefficients		Model 2
Coefficients		Model 3
Coefficients		Model 4
Coefficients
Testing Step 1
Predictor: PA
Outcomes: PHENA−0.138 (−2.839) **
Testing Step 2
Predictor: PA
Outcome: PC0.160 (3.012) **
NC−0.272 (−4.593) ***
Testing Step 3
Mediator: PC
Outcome: PHENA−0.073 (−1.484)
Mediator: NC
Outcome: PHENA0.368 (6.117) ***
Testing Step 4
Predictor: PA
Mediator: PC0.160 (3.015) **
NC−0.269 (−4.593) ***
Outcome: PHENA−0.033 (−0.645)
Overall fit
χ2/df1.7351.7812.6092.221
RMSEA0.0330.0340.0490.042
GFI0.9910.9850.9760.970
AGFI0.9800.9740.9590.954
NFI0.9860.9610.9550.944
IFI0.9940.9830.9720.968
CFI0.9940.9820.9710.968
RFI0.9770.9440.9360.927
RMR0.0280.0400.0440.046
Note. The coefficients in the table are standardized coefficients. Numbers in parentheses show t-values. *** p < 0.001, ** p < 0.01.
Table
Table 3. Standardized Bootstrap Mediation Effect Test.
Table 3. Standardized Bootstrap Mediation Effect Test.
PathPath EffectSEBias-Corrected 95%CIPercentile 95%CI
LowerUpperpLowerUpperp
PA → PHENA−0.0330.051−0.1290.0680.555−0.1330.0640.502
PA → PC → PHENA−0.0140.011−0.0450.0010.069−0.0380.0050.160
PA → NC → PHE-NA−0.0970.028−0.164−0.0520.000−0.156−0.0470.001
Note. Path Effect is the product of all effect values on the path.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Liu, Y.; Wang, Z.; You, S. The Mediating Effect of Coping Style on Physical Activity and Negative Affect Caused by Public Health Emergencies: Evidence from Chinese College Students. Int. J. Environ. Res. Public Health 2021, 18, 12086. https://doi.org/10.3390/ijerph182212086

AMA Style

Liu Y, Wang Z, You S. The Mediating Effect of Coping Style on Physical Activity and Negative Affect Caused by Public Health Emergencies: Evidence from Chinese College Students. International Journal of Environmental Research and Public Health. 2021; 18(22):12086. https://doi.org/10.3390/ijerph182212086

Chicago/Turabian Style

Liu, Yuetao, Zhiyuan Wang, and Songhui You. 2021. "The Mediating Effect of Coping Style on Physical Activity and Negative Affect Caused by Public Health Emergencies: Evidence from Chinese College Students" International Journal of Environmental Research and Public Health 18, no. 22: 12086. https://doi.org/10.3390/ijerph182212086

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop