Trauma exposure and the PTSD symptoms of college teachers during the peak of the COVID‐19 outbreak

1 INTRODUCTION 1.1 Background

On 11 March 2020, the World Health Organisation declared coronavirus disease 2019 (COVID-19) a pandemic (World Health Organisation, 2020). The various experiences and encounters during the pandemic, such as the pain of illness, the sadness of bereavement, the anxiety of isolation, the shock of unemployment and the uncertainty and fear of the future, have brought great distress to people (Duan & Zhu, 2020;   Huang & Zhao, 2020; Jungmann & Witthöft, 2020; S. Li et al., 2020; Liu et al., 2020; McKay et al., 2020; Mertens et al., 2020; Qiu et al., 2020; Taylora et al., 2020; United Nations, 2020; Wang et al., 2020; J. Zhang, Wu et al., 2020; Y. Zhang & Ma, 2020). Particularly, the traumatic experiences of those who diagnosed with COVID-19 disease, lost loved ones to COVID-19, or lived in high-risk geographic areas probably damage their mental health. Previous studies have similarly revealed that people who experienced outbreaks of emerging infectious diseases such as severe acute respiratory syndrome (SARS), Middle East respiratory syndrome (MERS) and Ebola were prone to develop a series of psychological problems such as depression, anxiety and posttraumatic stress disorder (PTSD) (Cheng et al., 2004; Jalloh et al., 2018; Lau et al., 2010; Lee et al., 2018; Main et al., 2011; McMillan et al., 2017; Neria et al., 2008; Park et al., 2020; Saadatian-Elahi et al., 2010; Vyas et al., 2016; Wu et al., 2005; Xiang et al., 2014).

Since 2020, many studies have analysed the psychological impact of the COVID-19 pandemic in different populations, including medical workers (Hoorelbeke et al., 2021; W. R. Zhang, Wang et al., 2020), Chinese residents (Ahmed et al., 2020; Liu et al., 2020), older adults (Rutherford et al., 2021), children and adolescents (Tang et al., 2021) and college students (Benham, 2020; Cao et al., 2020; Tang et al., 2020); however, so far, there has not been any particular study on the educators, such as university teachers. Globally, teachers are a professional group with a large population, and they carry out educational activities with a much larger number of students. The traumatic experiences caused by COVID-19 not only affect the mental health of teachers, but also the quality of education, and even the mental health of students. Wuhan City in China, was the first city to be fiercely hit and severely affected by the large-scale COVID-19 outbreak (Sanche et al., 2020); Meanwhile, Wuhan is one of the cities with the largest number of university teachers and students in the world. According to Hubei Provincial Department of Education, Wuhan has more than 60,000 teachers and more than 1 million college students in 2019. On one hand, teachers have to conduct unprecedented remote online teaching during Wuhan lockdown. On the other hand, they have to face the risk of infection caused by in-person teaching in closed classrooms after the lockdown is lifted. Therefore, this study attempts to use survey data to analyse the impact of traumatic experience on the PTSD symptoms of Wuhan university teachers during the COVID-19 pandemic in 2020.

1.2 Influencing factors of PTSD

Research on factors that influence the development of PTSD symptoms showed that the severity and incidence of PTSD vary with the degree of trauma exposure (Grubaugh et al., 2011). First, existing studies found that uncertainty of material losses or feelings of uncertainty is an important reason for PTSD caused by trauma exposure (Goto et al., 2006; Xie et al., 2011), and higher intolerance of uncertainty was associated with symptoms of generalised anxiety disorder, social anxiety disorder, panic disorder and obsessive-compulsive disorder (Boswell et al., 2013; Carleton et al., 2012; Rosser, 2019). The uncertainty of the pandemic not only is an important cause of psychological vulnerability (Mertens et al., 2020) but also induces negative emotions such as anxiety and depression (Zandifar & Badrfam, 2020). Looking back at the COVID-19 outbreak in Wuhan, we found that the outbreak caused a highly uncertain environment. SARS-COV-2, the virus of COVID-19 disease, is characterised by a long incubation period, large basic regeneration number and low fatality rate (Song et al., 2020). It can be seen that the virus spread is stealthy and rapid. In the early stage of the pandemic, most medical institutions in Wuhan had limited capacity for admission and treatment. At the same time, there was a major gap in nucleic acid testing capacity. As a result, a large number of infected people could not be effectively screened out. In addition, the local government lacked experience in dealing with such a large-scale pandemic. This situation led to exhaustion of medical resources and cross-infections in hospitals, and the infected people who were not hospitalised for medical treatment in time further caused cluster infections within their families. Thus, compared with those with no symptoms associated with COVID-19, those with mild symptoms are at a higher level of uncertainty during the pandemic, because they are kept at home for observation and are not allowed to leave home for medical treatment voluntarily. People with more severe symptoms have to go through the entire process of diagnosis and treatment, which, as mentioned earlier, is of high uncertainty due to the shortage of medical resources and the low accuracy of diagnosis and treatment. Clearly, the suffering associated with confirmed COVID-19 infection and symptoms similar to COVID-19 are severe trauma exposures that can lead to further psychological harm.

The second important manifestation of trauma exposure is the death of a loved one from COVID-19. The pandemic prevention and control measures require keeping a social distance. Therefore, when family members, relatives, friends, or neighbours are infected with the virus, people have to avoid the risk of infection on the one hand (Xiang et al., 2020); on the other hand, due to home quarantine control measures and the lack of effective protection, it is difficult to offer care and help for the infected (W. R. Zhang, Wang et al., 2020). If infected individuals fail to survive the pandemic, people not only have to suffer from the loss, but they also may have deep feelings of guilt and self-reproach. Relevant research showed that PTSD may occur after bereavement (Kaltman & Bonanno, 2003; Zisook et al., 1998). A study on adolescents showed that having relatives and friends injured in the earthquake, witnessing death in the earthquake were significant predictors for PTSD severity (He et al., 2011). In addition, we found a study showed that the death of family members due to MERS significantly increased the possibility of depression (Park et al., 2020).

The third important manifestation of trauma exposure is the risk of infection and disaster exposure that people endure during the pandemic. In most cases, people assess the risk based on what they heard or saw in their memory. If something is easy to recall, people will determine that it is likely to happen or happens frequently. Such perception strengthens people's fears (Slovic et al., 1982). Obviously, the closer to the severely affected areas an individual is, the greater the risk of infection, the greater the likelihood of witnessing the disaster scene, and the greater the emotional and psychological impact (Van Bortel et al., 2016). In the early stage of the pandemic, the psychological stress was particularly acute for those who lived in environments with rising infection and mortality rates, unpredictable prevention, control and treatment. The COVID-19 pandemic has completely disrupted people's lives and work. People in the pandemic centre are shrouded in an atmosphere of fear of being infected at any time. Stressful situations and fear can increase people's mental health problems (Dar et al., 2017; Mertens et al., 2020), and these problems may even develop into long-term adaptation disorders and PTSD (Banerjee et al., 2020).

Taking college faculty in Wuhan as the research object, We investigated the prevalence of PTSD among college faculty in Wuhan, and explored the effect of trauma exposure (such as suffering symptoms relevant to COVID-19, the loss of loved one to COVID-19 and living in geographic areas with high infection risk) on PTSD, including intrusion, avoidance and hyperarousal symptoms when the pandemic was contained (i.e., 1 month after the Wuhan lockdown was lifted) using multistage random sampling.

2 METHODS 2.1 Participants and procedure

This study is part of a large-scale survey, COVID-19 Impact Survey of Faculty and Students of Wuhan Universities and Colleges (CFSW) (X. Li et al., 2021). Wuhan City was closed on 23 January 2020, followed by a nationwide lockdown of varying degrees until Wuhan announced the lifting of the lockdown early April. CFSW is a cross-sectional study that was conducted via an online survey from 26 to 29 April 2020. The survey took college students and in-service teachers from 83 higher education institutions (hereinafter referred to as ‘colleges’) in Wuhan as the participants, and a random sampling survey was conducted with the help of the administrative departments of colleges. The study was conducted according to the guidelines of the Declaration of Helsinki, and approved by the Academic Board of Central China Normal University. The participants included noninfected college teachers, who were selected through random sampling, and infected college teachers, all of whom were included in the survey. The reasons why all infected teachers were included was that their numbers were relatively small and that it may be difficult to obtain sufficient samples through random sampling surveys.

The goals were to select 2000 affected college teachers by multistage random sampling and to include all infected college teachers in this survey. The term ‘infected college teachers’ was defined as those who were diagnosed with COVID-19, and the term ‘noninfected teachers’ was defined as those who suffered home quarantine, social distancing, college closure and anxiety during the COVID-19 outbreak. For noninfected teachers, a multistage random sampling approach was adopted. First, 13 colleges were randomly selected, and the sampled teacher size in each sampled college was proportional to the size of its teacher population. Second, 30% of the schools and departments of the sampled colleges were systematically selected, and the sampled teacher size in each sampled school and department was proportional to the size of its teacher population. Third, the size of the teacher population in each sampled school and department was proportional to the teacher size of different professional qualifications (i.e., assistant lecturer, lecturer, associate professor and professor). Finally, teachers were randomly selected in each group of different professional qualification. In addition, all the infected teachers in all sampled colleges were included in the survey.

The online survey via a professional data collecting platform (http://ringsurvey.com/platform) was used to collect data. The informed consent statement was shown at the beginning of the survey, and the teachers who provided consent were directed to the survey questionnaire. Participants who had not completed the survey received a warning on unanswered questions from the online platform; however, they were free to stop the survey without receiving a warning from the platform. As a result, a total of 1603 noninfected teachers, and all 47 infected teachers, with a total of 1650 teachers were surveyed. Compared with the planned sample size (i.e., 2000) of teachers, the completion rate was 80%.

2.2 Measurements 2.2.1 Impact of Event Scale-Revised

For PTSD symptoms, the question was: ‘Since April 8, how is your mental state consistent with the following statements?’ PTSD was assessed via the Chinese version of the Impact of Event Scale-Revised (IES-R) (Horowitz et al., 1979; Weiss & Marmar, 1997), a 25-item self-reported scale assessing the severity of posttraumatic disorder symptom due to traumatic events, such as the COVID-19 pandemic. Three dimensions, including intrusion, avoidance and hyperarousal symptoms, were assessed. Participants were asked to rate all the items using a 5-point scale (0 = never, 1 = rarely, 2 = sometimes, 3 = often, 4 = always). The word ‘event’ was replaced with ‘COVID-19 pandemic’ in the items. For PTSD screening, a recommended cutoff of ≥1.5 was used for the average of each subscale score and the whole scale score for the subsequent analysis. This cut-off value was established against the PTSD Checklist PCL in a community sample, with an overall diagnostic power of 0.88, a sensitivity of 0.91, a specificity of 0.82, a positive predictive power of 0.90 and a negative predictive power of 0.84 (Creamer et al., 2003). The Cronbach coefficients were 0.92, 0.78, and 0.88, respectively, for the subscale of intrusion, avoidance and hyperarousal, and 0.93 for the whole scale of IES-R. Three items (two from avoidance and one from hyperarousal subscale) were removed from further analysis because the corresponding Cronbach coefficient of the subscale was higher if they were removed.

2.2.2 Trauma exposure

Trauma exposure included three variables: symptoms associated with COVID-19 during the pandemic; the death of family members, relatives or friends due to COVID-19 and living places during the pandemic.

The question asked the participant's physical condition during the pandemic in four categories: no symptoms associated with COVID-19 (value = 0), mild undiagnosed symptoms associated with COVID-19 (including itchy throat, dry cough, fatigue, joint pain and fever, etc., value = 1), confirmed common influenza (including confirmed common influenza and pneumonia caused by common influenza, value = 2),and confirmed COVID-19 (value = 3). These questions are all reported by the participants based on their actual situation. Among them, the most severe trauma exposure is confirmed COVID-19, followed by confirmed influenza and then mild symptoms.

The survey also asked the participants whether they had a loved one who had died of COVID-19. According to the relation closeness, the options were as follows: no one died of COVID-19 (value = 0), friends or neighbours died of COVID-19 (including friends, classmates, colleagues and neighbours, value = 1), and family members or relatives died of COVID-19 (including immediate relatives and other relatives, value = 2). If a participant had both ‘friends or neighbours’ and ‘family members or relatives’ who died of COVID-19, only the answer of ‘family members or relatives’ was recorded for analysis.

According to the severity of the geographical regions affected by COVID-19, the living places during the pandemic included three options: living in Wuhan City (value = 2), living in other places in Hubei Province (value = 1) and living in other provinces (value = 0). According to the pandemic information released by the National Health and Health Commission of China, as of 30 April 2020, a total of 82,862 cases have been confirmed nationwide, including 50,333 cases (60.74%) in Wuhan City, Hubei Province, 17,795 cases (21.48%) in other parts of Hubei Province, and 14,734 cases (17.78%) in other provinces (NHC, 2020); the risk of virus infection in these three places decreased sequentially.

2.2.3 Sociodemographic characteristic

Sociodemographic characteristic variables (as seen in Table 1) include gender (male = 0, female = 1), age (50 years old and above = 0, 40–49 years old = 1, 30–39 years old = 2, 29 years old and below = 3), China Communist Party (CCP) membership (No = 0, Yes = 1), graduation university with highest education (Domestic university = 0, Overseas university = 1), highest education (Junior bachelor = 0, Bachelor = 1, Master's = 2, Doctor = 3), discipline with highest education (Liberal arts = 0, Science and engineering = 1), University category (Province or city-affiliated university = 0, State-affiliated university = 1),1 professional qualification title (Assistant lecturer = 0, Lecturer = 1, Associate professor = 2, Professor = 3), whether they hold a concurrent administrative position (No = 0, Yes = 1), and whether they hold a talent or expert title at or above the provincial level (No = 0, Yes = 1).

TABLE 1. Sociodemographic characteristics of college teachers in Wuhan Total (n = 1650) Noninfected teachers (n = 1603) Infected teachers (n = 47) χ2 test (p) Sociodemographic characteristics Gender 0.002 Male 795 (48.18) 762 (47.54) 33 (70.21) Female 855 (51.82) 841 (52.46) 14 (29.79) Age cohort 0.000 50 years old and above 216 (13.09) 198 (12.35) 18 (38.30) 40–49 years old 497 (30.12) 487 (30.38) 10 (21.28) 30–39 years old 755 (45.76) 737 (45.98) 18 (38.30) 29 years old and below 182 (11.03) 181 (11.29) 1 (2.13) CCP membership 0.081 No 417 (25.27) 400 (24.95) 17 (36.17) Yes 1233 (74.73) 1203 (75.05) 30 (63.83) Graduation university 0.813 Domestic university 1202 (93.64) 1168 (93.7) 34 (91.49) Overseas university 448 (6.36) 435 (6.30) 13 (8.51) Highest degree 0.000 Junior bachelor 23 (1.39) 19 (1.19) 4 (8.51) Bachelor 221 (13.39) 213 (13.29) 8 (17.02) Master's 771 (46.73) 754 (47.04) 17 (36.17) Doctor 635 (38.48) 617 (38.49) 18 (38.30) Discipline of highest degree 0.982 Liberal arts 775 (46.97) 753 (46.97) 22 (46.81) Science and engineering 875 (53.03) 850 (53.03) 25 (53.19) University category 0.000 Province or city-affiliated university 1089 (66.00) 1078 (67.25) 11 (23.40) State-affiliated university 561 (34.00) 525 (32.75) 36 (76.60) Professional qualification title 0.254 Assistant lecturer 249 (15.09) 242 (15.1) 7 (14.89) Lecturer 590 (35.76) 573 (35.75) 17 (36.17) Associate professor 605 (36.67) 592 (36.93) 13 (27.66) Professor 206 (12.48) 196 (12.23) 10 (21.28) Concurrent administrative position 0.194 No 1275 (77.27) 1235 (77.04) 40 (85.11) Yes 375 (22.73) 368 (22.96) 7 (14.89) Province-level and above talent or expert title 0.449 No 1552 (94.06) 1509 (94.14) 43 (91.49) Yes 98 (5.94) 94 (5.86) 4 (8.51) Type and severity of trauma exposure Physical condition during the pandemic – No symptom 1507 (91.33) 1507 (94.01) 0 (0.00) Mild symptom 48 (2.91) 48 (2.99) 0 (0.00) Confirmed common influenza 48 (2.91) 48 (2.99) 0 (0.00) Confirmed COVID-19 47 (2.85) 0 (0.00) 47 (100) A cared one died of COVID-19 0.184 None 1538 (93.2) 1496 (93.33) 42 (89.36) Friends or neighbours 73 (4.42) 71 (4.43) 2 (4.26) Family members or relatives 39 (2.36) 36 (2.25) 3 (6.38) Living places during the pandemic 0.049 Other provinces 330 (20.00) 325 (20.27) 5 (10.64) Other places in Hubei 342 (20.73) 336 (20.96) 6 (12.77) Wuhan 978 (59.27) 942 (58.76) 36 (76.60) Note: The results in the table are presented as n (%); the term ‘infected college teachers’ was defined as those who were diagnosed with COVID-19, and the term ‘noninfected teachers’ was defined as those who suffered home quarantine, social distancing, college closure, and anxiety during the COVID-19 outbreak. Abbreviation: COVID-19, coronavirus disease 2019. 2.3 Statistical analyses

χ2 Tests were used to compare group differences between the noninfected and infected teachers. Analysis of variance was used to analyse the mean differences of PTSD and three symptoms (including intrusion, avoidance and hyperarousal) between the groups of teachers, and Bonferroni correction was used to compare the mean differences between the categories. Multiple logistics models were used to examine the relationship between trauma exposure and PTSD. Dependent variables include PTSD, Intrusion, Avoidance and Hyperarousal, Intendent variables include physical condition during the pandemic, a cared one died of COVID-19 and living places during the pandemic. Although random sampling was used in this study, there were still two biases in the samples. On the one hand, since all the infected teachers were involved in the survey, they cannot be directly incorporated into the sample of noninfected teachers obtained through multistage random sampling. On the other hand, some colleges did not complete the planned sample size, which led to sample imbalance between colleges. Therefore, we used the population size and sample data to calculate a sampling weight to adjust for these sample imbalances and used them in the logistic regression models. Data were analysed using Stata14.

3 RESULTS 3.1 Sample characteristics

Table 1 presents the sociodemographic characteristic of college teachers in Wuhan, and the differences between noninfected and infected teachers using χ2 tests. Among the 1650 teachers in this survey, 795 (47.54%) were male, average age 40.28 (SD = 8.30), 1252 (75.88%) were 30–39 years old, and 1233 (75%) were CCP members. In terms of highest education, 1202 (93.64%) graduated from domestic university, 635 (38.48%) obtained doctorate degrees and 875 (53.03%) obtained degrees in science and engineering. In terms of work, 561 (34.00%) were from state-affiliated university. In total, 590 and 605 had lecturer and associate professor titles, respectively (72.43% in total). A total of 375 (22.73%) held concurrent administrative positions, and 98 (5.94%) held a talent or expert title at provincial or ministerial level or above.

χ2 Test results showed that there were significant differences between noninfected and infected teachers in terms of multiple characteristics. Compared with that among noninfected teachers, the infection rate of males was significantly higher among infected teachers (70.21 vs. 47.54%, χ2 [1, N = 1650] = 9.40, p = 0.002). Teachers who were 50 years old or more were more likely to be infected (38.3 vs. 12.35%, χ2 [3, N = 1650] = 28.80, p < 0.001). Non-CCP members had a higher infection rate (36.17 vs. 24.95%, χ2 [1, N = 1650] = 3.04, p = 0.081). In terms of education and work, teachers with lower education, that is, those with a junior bachelor's degree, had a significantly higher infection rate (8.51 vs. 1.19%, χ2 [3, N = 1650] = 19.21, p < 0.001). Compared to teachers from province or city-affiliated universities, teachers from state-affiliated universities had a significantly higher infection rate (76.60 vs. 32.75%, χ2 [1, N = 1650] = 39.11, p < 0.001).

In terms of the type and severity of trauma exposure, the occurrence of symptoms similar to COVID-19 and the confirmation of COVID-19 during the pandemic were the primary manifestations of trauma exposure. In this survey, 47 (2.85%) teachers were diagnosed with COVID-19 infection. Among the non-infected teachers, 48 (2.91%) were diagnosed with severe symptoms such as common influenza and pneumonia, and 48 (2.91%) had mild symptoms such as itchy throat, dry cough, fatigue and joint pain. The second manifestation of trauma exposure was the death of a loved one from COVID-19. The survey revealed that 39 (2.36%) had family members or other relatives who died, and 73 (4.42%) had friends, colleagues, classmates or neighbours who died. The χ2 test showed no significant difference between infected and noninfected teachers (χ2 [2, N = 1650] = 3.39, p = 0.184). The third manifestation of trauma exposure was the risk of infection in different areas of the severity of the pandemic. Among all the teachers, 978 (59.27%) lived in Wuhan during the pandemic. Among all the infected teachers, 36 (76.60%) lived in Wuhan, the proportion of which was significantly higher than the proportion of those who lived in Wuhan among all the non-infected teachers (76.6 vs. 58.76%, χ2 [2, N = 1650] = 6.05, p = 0.049).

3.2 Trauma exposure and PTSD

Table 2 presents a descriptive analysis of PTSD and its three symptom categories, that is, intrusion, avoidance and hyperarousal. We calculated the proportion of participants with a PTSD score ≥1.5, that is, the incidence of PTSD (Creamer et al., 2003). The analysis showed that the overall incidence of PTSD among college teachers in Wuhan was high (24.55%), but the average level was low (M = 1.06, SD = 0.72). Among them, the level of intrusion symptom was slightly higher (M = 1.36, SD = 0.91), but the levels of avoidance symptom (M = 0.90, SD = 0.69) and hyperarousal symptom (M = 0.79, SD = 0.82) were lower. The results of ANOVA showed that there were significant differences in PTSD scores among college teachers in Wuhan in terms of their age cohort (F = 5.23, p = 0.001), highest degree (F = 4.94, p = 0.002), discipline of highest degree (F = 6.04, p = 0.014) and professional qualification title (F = 5.41, p = 0.001). The group differences in symptoms of intrusion, avoidance and hyperarousal were similar to those of PTSD.

TABLE 2. Psychological manifestations of college faculty PTSD score ≥1.5 PTSD Intrusion Avoidance Hyperarousal M ± SD p Value M ± SD p Value M ± SD p Value M ± SD p Value Total 24.55% 1.06 ± 0.72 1.36 ± 0.91 0.90 ± 0.69 0.79 ± 0.82 Sociodemographic characteristics

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