This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.
COVID-19 resulted in considerable mental health burden in the Chinese general population and among health care workers at the beginning and peak of the pandemic. However, little is known about potentially vulnerable groups during the final stage of the lockdown.
The aim of this survey study was to assess the mental health burden of different professions in China in order to find vulnerable groups, possible influencing factors, and successful ways of coping during the last 4 weeks of the lockdown in Hubei Province.
A cross-sectional online survey asked participants about current residence, daily working hours, exposure to COVID-19 at work, and media preferences. We used a shortened version of the Depression, Anxiety and Stress Scale (DASS-21) to assess mental health. Further assessments included perceived stress (Simplified Chinese version of the 14-item Perceived Stress Scale), coping strategies for all participants, and specific stressors for health care workers. We followed the reporting guidelines of the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) statement for observational studies.
The sample (N=687) consisted of 158 doctors, 221 nurses, 24 other medical staff, 43 students, 60 teachers/government staff, 135 economy staff, 26 workers/farmers, and 20 professions designated under the “other” category. We found increased depression (n=123, 17.9%), anxiety (n=208, 30.3%), and stress (n=94, 13.7%) in our sample. Professions that were vulnerable to depression were other medical staff and students. Doctors, nurses, and students were vulnerable to anxiety; and other medical staff, students, and economy staff were vulnerable to stress. Coping strategies were reduced to three factors: active, mental, and emotional. Being female and emotional coping were independently associated with depression, anxiety, or stress. Applying active coping strategies showed lower odds for anxiety while mental coping strategies showed lower odds for depression, anxiety, and stress. Age, being inside a lockdown area, exposure to COVID-19 at work, and having a high workload (8-12 hours per day) were not associated with depression, anxiety, or stress. WeChat was the preferred way of staying informed across all groups.
By the end of the lockdown, a considerable part of the Chinese population showed increased levels of depression and anxiety. Students and other medical staff were the most affected, while economy staff were highly stressed. Doctors and nurses need support regarding potential anxiety disorders. Future work should focus on longitudinal results of the pandemic and develop targeted preventive measures.
In December 2019, pneumonia cases of unknown etiology in Wuhan, Hubei Province, were reported by Chinese authorities. By January 3, 2020, 44 cases requiring hospitalization were officially confirmed [
The pandemic put a considerable psychological burden on citizens, which was not simply due to fear of infection but also isolation, helplessness, and grief over the loss of relatives without having the opportunity to take leave or to organize a funeral. Even more aggravating was that trusted persons, like family and friends, could be infected, and thus, became part of an invisible danger [
Previous epidemics, like the severe acute respiratory syndrome (SARS) in Hong Kong in 2003 or the Middle East respiratory syndrome (MERS) in Saudi Arabia in 2012, have taught us to care for the mental health of the general population and frontline health care workers [
Several studies have investigated the mental health consequences of the ongoing pandemic in the Chinese population and its strategies to successfully cope with the demanding situation. Wang et al [
Besides the obvious impact of the pandemic on mental health like the fear of infection and isolation due to quarantine measures [
Since health care workers at the frontline were exposed to particularly demanding conditions during the peak of the pandemic, their mental health and coping strategies have become an early issue of concern. One of the first studies on this topic focused on medical and nursing staff in Wuhan and found elevated levels of subthreshold mental health disturbances in nearly 40% of the 994 participants surveyed [
There were some specific results on the psychological burden felt by nurses. Nurses in Anhui showed strong emotional responses. Increased exposure to COVID-19 cases evoked more anxiety and anger [
Another vulnerable group included students, the majority of whom lived in quarantine with their families and reported victimization by facing or witnessing various stressful events related to COVID-19 [
In spite of the many studies regarding the mental health of the general population and health care workers on the frontline of the pandemic, we found no data on further vulnerable groups and professions that may be mentally or emotionally affected by indirect means. Although Huang and Zhao [
The aim of this survey study was to assess the psychological burden of COVID-19 on the mental health of the Chinese population during the last 4 weeks of the lockdown in Hubei Province. We examined different professions in order to find vulnerable groups, possible influencing factors, and successful ways of coping. Moreover, we looked for specific stressors among doctors and nurses.
We used a cross-sectional online survey design in order to investigate the impact of the COVID-19 pandemic on the mental health, stress, specific stressors, and coping strategies of different groups of the Chinese population. The study team of Heidelberg University Hospital developed the concept and the questionnaire, which was translated into Chinese. Its implementation into an online format and sampling was carried out by a publicity enterprise in Wuhan. The Tongji Medical College of the Huazhong University of Science and Technology supported the study by disseminating the link. The study started on March 19 and data were included until April 7. The lockdown in Hubei was officially ended on April 8 by the government [
Ethical approval for this study was granted by the Ethics Commission of the Medical Faculty of Heidelberg (S-361/2020). We followed the reporting guidelines of the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) statement for observational studies [
The questionnaire was derived from validated instruments and structured into four major parts. The first part asked for demographic data (place of residence, gender, age, marital status, educational background, and occupation), exposure to people infected with COVID-19 in general and at work, working hours per day, and media platforms used to obtain information (multiple choice). The second part asked for mental health parameters like depression, anxiety, and stress, measured by a shortened version of the 21-item Depression, Anxiety and Stress Scale (DASS-21) using a 4-point Likert scale [
The responses of the participants were downloaded from the online survey tool and further processed and analyzed using SPSS 24 (IBM Corp) [
Participants answering from Hubei and Zhejiang provinces were regarded as being affected by the lockdown (n=460). All other participants were not directly affected by the lockdown (n=226).
The scoring of the DASS-21 are calculated as sum scores that have to be multiplied by two. The total depression subscale score was divided into normal (0-9), mild (10-13), moderate (14-20), severe (21-27), and extremely severe depression (28+). The anxiety subscale score was divided into normal (0-7), mild (8-9), moderate (10-14), severe (15-19), and extremely severe anxiety (20+). The total stress subscale score was divided into normal (0-14), mild (15-18), moderate (19-25), severe (26-33), and extremely severe stress (34+). Next, we grouped the levels of severity into normal–mild and moderate–extremely severe for each score. We decided to put mild symptoms into one group together with the normal level, since we considered mild symptoms of depression and anxiety to exist regardless of the pandemic [
The CPSS-14 scores were calculated by sum scores as well. We reported the CPSS-14 scores and DASS-21 scores nationwide for each profession. For deeper analysis we calculated Pearson correlations in order to assess the relationship of perceived stress during the past 4 weeks and mental health scores for depression, anxiety, and stress during the past week.
The coping strategies and major stressors were calculated as means and standard deviations. We carried out a factor analysis (principal component analysis [PCA] with varimax rotation) for all coping strategies. The Kaiser-Meyer-Olkin (KMO) and Bartlett Test indicated a sufficient cohesion of the variables (KMO=0.76) [
In all analyses,
The sample included 687 participants, 72.3% (n=496) of whom were female and 27.7% were (n=190) male. The mean age was 36.92 years (SD 9.83) with a range of 18-71 years. The participants consisted of doctors (n=158, 23.0%), nurses (n=221, 32.2%), other medical staff (n=24, 3.5%), students (n=43, 6.6%), teachers/government staff (n=60, 8.7%), economy staff (n=135, 19.7%), workers/farmers (n=26, 3.8%), and others (n=20, 2.9%). We combined doctors and dentists into one category. Other medical staff referred to health care professionals who were not doctors or nurses. Economy staff consisted of employees and self-employed individuals in the IT (information technology) and finance sectors.
A majority of the participants were from Hubei Province (n=449, 65.4%); 30 (4.4%) came from Jiangsu and 21 (3.1%) each from Shanxi and Guangdong. A small group (n=11, 1.6%) came from Zhejiang, which was affected by a lockdown like Hubei. Demographic characteristics and details of each professional group are summarized in
Demographic characteristics of the study participants.
Characteristics | Participants, n (%) | |
Age (years), mean (SD) | 36.92 (9.83) | |
|
|
|
|
Male | 190 (27.7) |
|
Female | 496 (72.3) |
|
|
|
|
Single | 146 (21.3) |
|
Married | 501 (72.9) |
|
Divorced | 30 (4.4) |
|
Widowed | 2 (0.3) |
|
In a relationship | 8 (1.2) |
|
|
|
|
Yes | 499 (72.6) |
|
No | 188 (27.4) |
|
|
|
|
Middle school | 10 (1.5) |
|
High school | 25 (3.6) |
|
Junior college | 168 (24.5) |
|
Bachelor | 384 (55.9) |
|
Master | 77 (11.2) |
|
Doctorate | 23 (3.3) |
|
|
|
|
Doctors/dentists | 158 (23.0) |
|
Nurses | 221 (32.2) |
|
Other medical staff (eg, volunteers, pharmacists, midwives) | 24 (3.5) |
|
Students | 43 (6.3) |
|
Teachers/government staff | 60 (8.7) |
|
Economy (eg, employees, self-employed, salespersons) | 135 (19.7) |
|
Workers/farmers | 26 (3.8) |
|
Others (eg, housewives) | 20 (2.9) |
|
|
|
|
Hubei | 449 (65.4) |
|
Jiangsu | 30 (4.4) |
|
Guangdong | 21 (3.1) |
|
Shanxi | 21 (3.1) |
|
Shandong | 17 (2.5) |
|
Fujian | 16 (2.3) |
|
Sichuan | 15 (2.2) |
|
Shanghai | 15 (2.2) |
|
Hunan | 14 (2.0) |
|
Zhejiang | 11 (1.6) |
|
Provinces with less than 10 participants | 78 (11.2) |
Total | 687 (100) |
Perceived stress was measured with a mean score of 23.70 (SD 7.52). The mean values for DASS-21 depression was 6.62 (SD 7.80), for DASS-21 anxiety was 7.01 (SD 7.00), and for DASS-21 stress was 10.18 (SD 8.63). Perceived stress was significantly correlated with DASS-21 depression (
Findings on mental health status for each profession are reported in
Results of the Simplified Chinese version of the 14-item Perceived Stress Scale (CPSS-14) and the Depression, Anxiety and Stress Scale - 21 Items (DASS-21).
Profession | Participants, n | CPSS-14 | DASS-21 depression | DASS-21 anxiety | DASS-21 stress | |||||
|
|
Mean (SD) | NMa, n (%) | MESb, n (%) | NM, n (%) | MES, n (%) | NM, n (%) | MES, n (%) | ||
Doctors | 158 | 23.16 (7.26) | 134 (84.8) | 24 (15.2) | 106 (67.1) | 52 (32.9) | 138 (87.3) | 20 (12.5) | ||
Nurses | 221 | 23.62 (7.19) | 183 (82.8) | 38 (17.2) | 152 (68.8) | 69 (31.2) | 197 (89.1) | 24 (10.9) | ||
Other medical staff | 24 | 22.25 (8.09) | 19 (79.2) | 5 (20.8) | 17 (70.8) | 7 (29.2) | 20 (83.3) | 4 (16.7) | ||
Students | 43 | 26.30 (7.79) | 33 (76.7) | 10 (23.3) | 25 (58.1) | 18 (41.9) | 34 (79.1) | 9 (20.9) | ||
Teachers/ |
60 | 22.98 (6.09) | 51 (85.0) | 9 (15.0) | 44 (73.3) | 16 (26.7) | 53 (88.3) | 7 (11.7) | ||
Economy staff | 135 | 23.93 (8.68) | 108 (79.4) | 27 (20.0) | 102 (75.6) | 33 (24.4) | 112 (83.0) | 23 (17.0) | ||
Workers/farmers | 26 | 23.15 (6.69) | 21 (77.8) | 5 (19.2) | 19 (73.1) | 7 (26.9) | 23 (85.5) | 3 (11.5) | ||
Others | 20 | 26.25 (7.62) | 15 (75.0) | 5 (25.0) | 14 (70.0) | 6 (30.0) | 16 (80.0) | 4 (20.0) | ||
Total | 687 | 23.70 (7.52) | 564 (82.1) | 123 (17.9) | 479 (69.7) | 208 (30.3) | 593 (86.3) | 94 (13.7) |
aNM: normal–mild.
bMES: moderate–extremely severe.
The majority of the participants reported working 4-8 hours per day (n=427, 61.4%). This was the case in the following groups—nurses: 145/221, 65.6%; students: 39/43, 90.7%; teachers/government staff: 47/60, 78.4%; economy staff: 97/135, 71.9%; workers/farmers: 18/26, 69.3%; others: 15/20, 75.0%.
A sizeable part of the sample reported working 8-12 hours per day (n=260, 37.4%). This high workload typically affected doctors (103/158, 65.2%) and other medical staff (13/24, 54.2%).
In total, 6 (0.9%) participants were infected themselves (2 doctors, 3 nurses, and 1 member of the group teachers/government staff). Of all participants, 180 (26.2%) had contact with people infected by the virus at work. The most affected group were doctors (68/158, 43.0% had contact with COVID-19 at work), followed by other medical staff (10/24, 41.7%), nurses (88/221, 39.8%), teachers/government staff (8/60, 13.3%), economy staff (5/135, 3.8%), workers/farmers (1/26, 3.8%). Participants from the other professions category and students did not report contact with COVID-19 at work.
When asked about the primary way participants obtained information in the past month, the majority of respondents indicated having done so through WeChat (n=606, 88.2%) (
Participants’ answers to the multiple-choice question: what was your main way of obtaining information during the last month?
Source | Participants, n (%) |
Newspaper | 53 (7.71) |
Television | 465 (67.69) |
304 (44.25) | |
606 (88.21) | |
Circle of friendsa | 502 (73.07) |
Family/colleagues | 311 (45.27) |
Other | 104 (15.14) |
aIncludes WeChat groups and other social media–related groups.
The three most successful ways of facing the demands of COVID-19 in daily life and work, out of 12 possible answers, were taking protective measures (mean 2.57, SD 0.67), actively acquiring more knowledge about COVID-19 (mean 2.09, SD 0.78), and engaging in recreational activities (mean 1.94, SD 0.77
Three dimensions could be extracted after carrying out the PCA and were named as active coping, mental coping, and emotional coping, after analyzing the content of the items. The dimensions accounted for 47.2% of the variance (
Matrix of coping strategy components and three statistics after varimax rotation (the rotation is converged in five iterations; method of extraction: main component analysis).
Items | Mean (SD) | Factor loadings | |||
|
|
Active | Mental | Emotional | |
|
|
|
|
|
|
|
Taking protective measures (washing hands, wearing a mask, taking one’s own temperature, etc) | 2.57 (0.67) | 0.77 | –0.03 | 0.01 |
|
Actively acquiring more knowledge about COVID-19 (symptoms, transmission pathway, etc) | 2.09 (0.78) | 0.75 | 0.17 | 0.02 |
|
Changing one’s thoughts and facing the situation with a positive attitude | 1.90 (0.83) | 0.53 | 0.44 | –0.12 |
|
Engaging in recreational activities (WeChat, Weibo, TikTok, online shopping, online movies, exercises) | 1.94 (0.77) | 0.42 | 0.23 | –0.06 |
|
Video chatting with family and friends by phone to share concerns and support | 1.69 (0.80) | 0.40 | 0.43 | –0.02 |
|
Engaging in health-promoting behaviors (more rest, exercise, balanced diet, etc) | 1.76 (0.82) | 0.27 | 0.68 | –0.06 |
|
Acquiring mental health knowledge and information | 1.36 (0.91) | 0.27 | 0.63 | 0.01 |
|
Practicing relaxation methods (meditation, yoga, Tai Chi, etc) | 0.88 (0.85) | –0.07 | 0.83 | 0.09 |
|
Limiting oneself from watching too much news about COVID-19 | 0.53 (0.73) | –0.11 | 0.13 | 0.72 |
|
Distracting oneself from thinking about COVID-19 issues by suppression or keeping busy | 0.70 (0.82) | 0.03 | 0.10 | 0.75 |
|
Venting emotions by crying, screaming, smashing things, and so on | 0.23 (0.48) | –0.08 | –0.08 | 0.53 |
|
Using alcohol or drugs | 0.22 (0.53) | 0.07 | –0.10 | 0.53 |
|
|
|
|
|
|
|
Eigenvalue | —a | 2.89 | 1.71 | 1.07 |
|
Percentage of total variance | — | 24.05 | 14.23 | 8.93 |
|
Total variance | — | — | — | 47.21 |
aNot applicable.
We calculated three binary logistic regression models in order to find associations of gender, lockdown area, contact with COVID-19 infection at work, and coping factors with the odds of belonging to the group for moderate–extremely severe depression, anxiety, or stress. Being female and applying emotional coping strategies increased the probability of belonging to the moderate–extremely severe depression, anxiety, or stress group. Applying active coping strategies reduced the probability of being affected by moderate–extremely severe anxiety, while mental coping strategies reduced the probability in all three moderate–extremely severe mental health groups. Age, being in a lockdown area, having contact with COVID-19 at work, and having a high workload (8-12 hr per day) did not significantly predict the odds of expressing moderate–extremely severe symptoms of depression, anxiety, or stress. The results are displayed in detail in
Results of a logistic regression predicting the probability of experiencing moderate–extremely severe (MES) depression, anxiety, or stress.
Variable | MES depression | MES anxiety | MES stress | |||
|
B (SE) | ORa (95% CI) | B (SE) | OR (95% CI) | B (SE) | OR (95% CI) |
Gender (female) | 0.81 (0.27) | 2.24 (1.33- 3.77) | 0.47 (0.22) | 1.61 (1.05-2.47) | 0.78 (0.30) | 2.19 (1.21-3.96) |
Age | 0.01 (0.01) | 1.01 (0.98-1.03) | –0.01 (0.01) | 0.99 (0.97-1.00) | –0.01 (0.01) | 0.99 (0.96-1.01) |
Hubei/Zhejiang | –0.43 (0.25) | 0.65 (0.40-1.05) | –0.07 (0.21) | 0.93 (0.61-1.41) | –0.22 (0.28) | 0.80 (0.46-1.39) |
Contact with COVID-19 infection at work | 0.07 (0.26) | 1.08 (0.64-1.80) | 0.15 (0.49) | 1.16 (0.76-1.79) | –0.03 (0.30) | 0.97 (0.54-1.74) |
Daily workload (8-12 hr) | 0.06 (0.22) | 1.06 (0.69-1.65) | 0.23 (0.19) | 1.26 (0.87-1.83) | 0.32 (0.25) | 1.38 (0.85-2.25) |
Active coping | –0.14 (0.11) | 0.87 (0.71-1.07) | –0.21 (0.09) | 0.81 (0.68-0.97) | –0.11 (0.12) | 0.89 (0.70-1.13) |
Mental coping | –0.56 (0.12) | 0.57 (0.45-0.72) | –0.42 (0.10) | 0.67 (0.55-0.81) | –0.67 (0.14) | 0.51 (0.39-0.67) |
Emotional coping | 0.63 (0.10) | 1.89 (1.55-2.30) | 0.80 (0.10) | 2.16 (1.80-2.60) | 0.82 (0.11) | 2.27 (1.81-2.84) |
aOR: odds ratio.
Out of 18 stressors, the three most demanding aspects for health care workers (n=375) were related to worries about infecting one’s family with COVID-19 (mean 1.46, SD 0.86), followed by the potential deterioration of their patients’ condition (mean 1.42, SD 0.79) and their patients’ emotional reaction (mean 1.3, SD 0.81) (
Doctors’ and nurses’ responses to the question: when you think about COVID-19 in your life and work, how often did you think or worry about the following things? (0=not at all, 3=very much) (n=375).
Stressor | Response, mean (SD) |
Worries about infecting your family with COVID-19 | 1.46 (0.86) |
Deterioration of patients’ condition | 1.42 (0.79) |
Patients’ emotional reaction | 1.30 (0.81) |
Emotional reaction of patients’ families | 1.29 (0.79) |
Uncertainties about when the epidemic will be under control | 1.27 (0.78) |
Coworkers displaying COVID-19–like symptoms | 1.27 (0.79) |
Worries about getting infected | 1.24 (0.78) |
Worries about being negligent and endangering patients | 1.23 (0.88) |
Worries about lack of proper knowledge and equipment | 1.23 (0.79) |
Worries about being negligent and endangering coworkers | 1.18 (0.83) |
Worries about nosocomial spread | 1.15 (0.82) |
Conflict between duty and safety | 1.15 (0.81) |
Being infected by colleagues | 1.12 (0.81) |
Protective gears being a hinderance to providing quality care | 1.12 (0.80) |
Being blamed by supervisors/managers | 1.10 (0.80) |
Displaying COVID-19–like symptoms yourself | 1.09 (0.77) |
Worries about the lack of manpower | 1.07 (0.91) |
Being without a properly equipped environment | 1.05 (0.84) |
Physical discomfort caused by protective gears | 1.01 (0.79) |
Ambiguity in the responsibilities between doctors and nurses | 1.00 (0.86) |
Frequent modification of infection control procedures | 0.96 (0.81) |
Coworkers being emotionally unstable | 0.96 (0.77) |
Unclear documentation and reporting procedures | 0.92 (0.78) |
This survey aimed to assess the psychological burden and mental health of the Chinese population during the final stages of the lockdown, as well as to determine successful coping strategies and potentially vulnerable professional groups with specific support needs. Our results suggest that being female and, independent of gender, applying certain coping strategies increased the incidence of symptoms of depression, anxiety, and stress. Emotional coping strategies like venting emotions, consuming alcohol, or limiting oneself from information were not helpful for participants dealing with COVID-19–related psychological problems. Active strategies to cope with moderate–extremely severe anxiety, such as taking protective measures and acquiring more knowledge were more beneficial, but the most effective strategy was focusing on mental coping like relaxation techniques and gaining knowledge about mental health. Our results confirm the findings of Guo et al [
We found no overall increased mean values in perceived stress and depression, anxiety, and stress in comparison to former (pre–COVID-19) samples (eg, compared to the perceived stress levels of patients in Hong Kong [
Some groups in our sample were more affected by symptoms of depression, anxiety, or stress than others. Students were vulnerable to moderate–extremely severe symptoms in all three categories. Outside the pandemic context, Chinese students have been reported to be affected by mental health problems due to stressful academic demands [
Economy staff were highly burdened by stress but did not exhibit more depression or anxiety than other groups. This result does not support that of Huang and Zhao [
Doctors and nurses in our sample were highly affected by anxiety; doctors had the highest workload per day. Nevertheless, perceived stress and DASS-21 stress levels were not higher than other groups, which may be due to a high professional devotion, as reported in previous research [
Finally, other medical staff, a small group consisting of volunteers, midwives, and pharmacists in our sample, was more affected by depression and stress than other groups and was vulnerable to anxiety as well. During the pandemic, many volunteers supported hospitals in a frontline capacity [
By 2017, there were only 33,400 licensed psychiatrists in China [
However, health care workers continue to be in dire need of greater access to specific mental health services [
Although we received 687 responses, the professional groups in this study were not of equal size; numbers were especially limited for the students and other medical staff categories, which reduces the power of statistical analysis. Targeted investigations may be needed to assess the status of underrepresented professions in a differentiated way. Further, online studies are unable to allow a valuable diagnostic assessment, and this limitation applies to all former studies. This is further aggravated due to the great variability in instruments used in different surveys, which reduces the comparability of results. Some authors used the DASS-21 previously [
A considerable part of the general population in China reported elevated symptoms of depression, anxiety, and stress during the final stages of the COVID-19 lockdown. Doctors, nurses, students, and other medical staff were found to be in imminent danger of developing mental health problems. Similarly, economy staff was also highly stressed. Being female was an additional risk factor for potential vulnerability toward developing mental health problems. We recommend providing additional specific information to these subgroups targeting their respective mental health profile and to personalize the successful coping strategies found in our results (ie, active and mental coping). These refer to constructive ways of behavior (eg, actively acquiring knowledge, applying protective measures) and mental health strategies (eg, relaxation techniques, psycho-education, and promoting social contact). Profession-specific mental health prevention programs should be developed and provided in formats preferred by the respective age, gender, or professional groups.
Center for Epidemiology Scale for Depression
Simplified Chinese version of the 14-item Perceived Stress Scale
Depression, Anxiety and Stress Scale - 21 Items
Generalized Anxiety Disorder 7-item
Kaiser-Meyer-Olkin
Middle East respiratory syndrome
principal component analysis
Patient Health Questionnaire
14-item Perceived Stress Scale
Post-Traumatic Stress Disorders Checklist
severe acute respiratory syndrome
Self-rating Depression Scale
Strengthening the Reporting of Observational Studies in Epidemiology
We thank all participants for taking part in our study despite the current challenges imposed by the pandemic. We also thank Wuhan CNweb Pioneer Ltd, which was responsible for the implementation of the online survey in collaboration with the QHealth Trusted Doctors Group (Penguin), Wuhan Saidian Consulting Service Company, and Tao Doctor APP. We appreciate the support of Tongji Medical College for disseminating the questionnaire link.
None declared.