Published online Feb 19, 2025. doi: 10.5498/wjp.v15.i2.97971
Revised: November 8, 2024
Accepted: December 10, 2024
Published online: February 19, 2025
Processing time: 214 Days and 5.9 Hours
The coronavirus disease 2019 (COVID-19) outbreak lasted several months, having started in December 2019. This study aimed to report the impacts of various factors on the depression levels of the general public and ascertain how emotional measures could be affected by psychosocial factors during the COVID-19 pandemic.
To investigate the depression levels of the general public in China during the COVID-19 pandemic.
A total of 2001 self-reported questionnaires about Beck Depression Inventory (BDI) were collected on August 22, 2022 via the website. Each questionnaire included four levels of depression and other demographic information. The BDI scores and incidences of different depression levels were compared between various groups of respondents. χ2 analysis and the two-tailed t-test were used to assess categorical and continuous data, respectively. Multiple linear regressions and logistic regressions were employed for correlation analysis.
The averaged BDI score in this study was higher than that for the non-epidemic periods, as reported in previous studies. Even higher BDI scores and incidences of moderate and severe depression were recorded for people who were quarantined for suspected COVID-19 infection, compared to the respondents who were not quarantined. The participants who did not take protective measures were associated with higher BDI scores than those who made efforts to keep themselves relatively safer. Similarly, the people who did not return to work had higher BDI scores compared to those managed to. A significant association existed between the depression levels of the subgroups and each of the factors, except gender and location of residence. However, quarantine was the most relative predictor for depression levels, followed by failure to take preventive measures and losing a partner, either through divorce or death.
Based on these data, psychological interventions for the various subpopulations in the general public can be implemented during and after the COVID-19 pandemic. Other countries can also use the data as a reference.
Core Tip: This study aims to report the impacts of various factors on the depression levels of members of the public and ascertain how emotional measures can be affected by psychosocial factors during the coronavirus disease 2019 pandemic. Comparisons of the Beck Depression Inventory scores and incidences of different depression levels in various groups of respondents were made. Based on the findings from this study, psychological interventions for the various subpopulations in the general public can be implemented during and after the coronavirus disease 2019 pandemic. Moreover, other countries may also use them as a reference.
- Citation: Qiu QM, Xiao Y. Depression levels of the general public increases during the COVID-19 pandemic in China: A web-based cross-sectional survey. World J Psychiatry 2025; 15(2): 97971
- URL: https://www.wjgnet.com/2220-3206/full/v15/i2/97971.htm
- DOI: https://dx.doi.org/10.5498/wjp.v15.i2.97971
For several months, from December 2019, coronavirus disease 2019 (COVID-19) has been spreading all over the world. However, the outbreak in China was basically under control. As of 10:33 a.m. CEST, on August 28 2020, COVID-19 situation dashboard of the World Health Organization showed that over 2400000 had been infected while more than 820000 had died globally. The clinical characteristics of COVID-19 vary from the asymptomatic state to severe acute respiratory distress syndrome and multi organ dysfunction[1]. Respiratory distress is the most typical symptom in COVID-19 patients, considering that most of the patients could not breathe properly, leading to their admission to intensive care. Some of the patients infected with COVID-19 also presented neurologic signs such as nausea, headache, and vomiting. An increasing body of evidence suggests that coronaviruses not only infect the respiratory tract but also central nervous system, which partly explains its involvement in neurological diseases[2].
Regardless of the success of specific treatments against nCov, the psychological impact will be unavoidable due to the widespread contagion and lockdown measures[3,4]. After a prolonged and distressing struggle with the community health trouble epidemic, even when the outbreak was brought under control, there was a significant impact on psychological and emotional well-being, with many experiencing significant distress. During the COVID-19 pandemic, some studies reported that the general public experienced lower psychological well-being and relatively higher depression scores compared to the period before COVID-19[5]. Similarly, a Beck Anxiety Inventory (BAI) questionnaire with responses from February 4 to 6, 2020 showed that the BAI score of all respondents was higher than before the COVID-19 pandemic. Significantly higher BAI scores were observed in people who were either quarantined or in high epidemic areas[6]. It’s worth noting that, even after the COVID-19 outbreak, psychobehavioral problems still existed. For example, after the severe acute respiratory syndrome (SARS) pandemic, depression was common in survivors. In fact, findings from studies revealed the presence of persistent psychological symptoms in 41%-65% of the SARS survivors, in addition to the increased depression/depressive symptoms in health care workers[7,8]. Therefore, it is necessary to investigate the depression levels in the Chinese population even in the late stages of the epidemic.
In this study, we designed a web-based cross-sectional survey, reported depression levels of the general public in China during COVID-19 pandemic. The data were collected on August 22, 2020, when people were allowed to return to their workplaces and schools. At this time, the government dedicated itself to rebuilding the healthcare system and revitalizing the economy once the outbreak was brought under control in China. We explored the impacts of various factors on public’s depression levels and ascertained how emotional measures are affected by psychosocial factors during the COVID-19 pandemic.
On August 22, 2020, self-reported Beck Depression Inventory (BDI) questionnaires were distributed to the general public via a website in mainland China. The participants were asked to provide demographic information such as age, gender, marital status, education level, location of residence, occupation (specifically whether they work at a hospital or have medical education), quarantined status, preventive measures taken, and whether they returned to work during the survey period. No exclusion criteria were applied to the respondents, except for those under 13 years of age. Only one completed questionnaire was accepted from each participant, all of whom provided informed consent. All 2001 responses were valid. All the personal information provided by the respondents was kept confidential and will be solely used for this study, which was reviewed and approved by the Institutional Review Board of Mental Health Center, Shantou University Medical College, China.
Based on demographic information, respondents were grouped into various sub-samples including age (13-30, 31-50, and > 50 years old), gender (male and female), marital status (unmarried, married, and divorced/widow), education (high school or below, college or above), location of residence. High epidemic areas included Xinjiang, Guangdong, Shanghai, and Shandong provinces, each with more than 20 COVID-19 infected cases as of August 22, 2020. Low epidemic areas included other mainland regions of China with relatively fewer cases until the same date. The respondents were also categorized by occupation (working in a hospital or studying at a medical school), quarantine status, preventative measures or not, and whether they had returned to work after the survey period.
The BDI, a structured self-reported questionnaire, was used to assess the depression levels of the participants in this project. This questionnaire, designed by Aaron T Beck, has been validated in previous studies that involve Chinese populations and is widely used to evaluate depressive symptoms in both mental patients and healthy people[9]. The BDI consisted of 21 questions, each addressing a common depression symptoms. The respondents rated how much they had been affected by the symptoms over the previous week was rated, using a 4-point (0-3) scale. The final scores ranged from 0 to 63, and were classified into four levels as follows: None or normal (0-13); mild (14-19); moderate (20-28); and severe depression (29-63)[10,11].
Data were analyzed using SPSS version 24.0. Descriptive statistics described the sample’s demographic characteristics and respondents’ BDI scores. Counts were expressed as number of cases and percentages, along with means ± SD. Kolmogorov-Smirnov test was used to assess data normality. χ2 analyses and two-tailed t-tests were conducted for categorical and continuous data, respectively. Multiple linear regressions and logistic regressions were performed for correlation analysis and to predict factors of depression. The level of statistical significance was set at 0.05.
This study collected 2001 questionnaires on August 22, 2020, during the epidemic period. The participants were divided into subgroups based on factors such as occupation, age, gender, marital status, education level, location of residence, occupation, quarantine status, precautionary measures taken, and whether they had returned to work or not. Each subgroup represented a different percentage of the total sample (Table 1).
| Demographic factors | n (%) |
| Gender | |
| Male | 740 (36.98) |
| Female | 1261 (63.02) |
| Age (years old) | |
| 13-30 | 1177 (58.82) |
| 31-50 | 770 (38.48) |
| > 50 | 54 (2.70) |
| Education level | |
| High school or below | 309 (15.44) |
| College or above | 1692 (84.56) |
| Marital status | |
| Unmarried | 874 (43.68) |
| Married | 1057 (52.82) |
| Divorced/widow | 70 (3.50) |
| Occupation | |
| Health professional | 384 (19.19) |
| The others | 1617 (80.81) |
| Location of residence | |
| High epidemic areas | 577 (28.84) |
| Low epidemic areas | 1424 (71.16) |
| Quarantine status | |
| No | 1965 (98.20) |
| Yes | 36 (1.80) |
| Preventative measures taken | |
| Yes | 1828 (91.35) |
| No | 173 (8.65) |
| If returned to work | |
| Yes | 1621 (81.01) |
| No | 380 (18.99) |
The average BDI score of all participants in this study (12.50 ± 11.103, n = 2001) was compared to that of the healthy people in China during the pandemic period (1.88 ± 2.72, n = 41) in China. This was done to determine if public depression levels increased during the COVID-19 pandemic[9]. The results clearly indicated that the depression levels among the general public were higher during the pandemic than in non-pandemic times.
The BDI scores of all participants are shown in Table 2, with the participants divided into different subgroups as previously described. We hypothesized that quarantine measures associated with the COVID-19 infection may have contributed to higher BDI scores observed in this study, compared to reports from previous research. Therefore, the average BDI scores of the quarantined participants were compared with those for those who were not quarantined. As expected, the BDI score of the quarantined participants was significantly higher than that of the non-quarantined ones (27.50 ± 10.56 vs 12.23 ± 10.93, P < 0.01) at the time of the survey. We anticipated that BDI scores would decrease if individuals took protective measures, such as wearing masks, goggles, protective clothing. Thus, it was unsurprising that the BDI scores of the participants who did not take protective measures were higher than for those who did (27.20 ± 11.26 vs 11.11 ± 10.03, P < 0.01). In addition, the incidence of moderate and severe depression were compared among the quarantined and non-quarantined individuals. It was evident that the incidence of moderate (16.69%) and severe (10.13%) depression among the non-quarantined participants was lower than the incidence of moderate (38.89%) and severe (44.44%) depression among the quarantined individuals.
| Sub-samples | BDI scores | |||||
| 0-13 | 14-19 | 20-28 | 29-63 | χ2 | P value | |
| Gender | 4.417 | 0.220 | ||||
| Male (n = 740) | 441 (59.59) | 81 (10.95) | 137 (18.51) | 81 (10.95) | ||
| Female (n = 1261) | 748 (59.32) | 174 (13.80) | 205 (16.26) | 134 (10.63) | ||
| Age (years old) | 32.143 | < 0.001 | ||||
| 13-30 (n = 1177) | 730 (62.02) | 156 (13.25) | 200 (16.99) | 91 (7.73) | ||
| 31-50 (n = 770) | 425 (55.19) | 91 (11.82) | 138 (17.92) | 116 (15.06) | ||
| > 50 (n = 54) | 34 (62.96) | 8 (14.81) | 4 (7.41) | 8 (14.81) | ||
| Education level | 106.745 | < 0.001 | ||||
| High school or below (n = 309) | 125 (40.45) | 31 (10.03) | 75 (24.27) | 78 (25.24) | ||
| College or above (n = 1692) | 1064 (62.88) | 224 (13.24) | 267 (15.78) | 137 (8.10) | ||
| Marital status | 247.439 | < 0.001 | ||||
| Unmarried (n = 874) | 558 (63.84) | 119 (13.62) | 146 (16.70) | 51 (5.84) | ||
| Married (n = 1057) | 621 (58.75) | 132 (12.49) | 186 (17.60) | 118 (11.16) | ||
| Divorced/widow (n = 70) | 10 (14.29) | 4 (5.71) | 10 (14.29) | 46 (65.71) | ||
| Occupation | 26.911 | < 0.001 | ||||
| Health professional (n = 384) | 188 (48.96) | 51 (13.28) | 84 (21.88) | 61 (15.89) | ||
| The others (n = 1617) | 1001 (61.90) | 204 (12.62) | 258 (15.96) | 154 (9.52) | ||
| Location of residence | 9.508 | 0.023 | ||||
| High epidemic areas (n = 577) | 324 (56.15) | 70 (12.13) | 122 (21.14) | 61 (10.57) | ||
| Low epidemic areas (n = 1424) | 865 (60.74) | 185 (12.99) | 220 (15.45) | 154 (10.81) | ||
| Quarantine status | 65.600 | < 0.001 | ||||
| No (n = 1965) | 1186 (60.36) | 252 (12.82) | 328 (16.69) | 199 (10.13) | ||
| Yes (n = 36) | 3 (8.33) | 3 (8.33) | 14 (38.89) | 16 (44.44) | ||
| If preventative measures taken | 426.533 | < 0.001 | ||||
| Yes (n = 1828) | 1169 (63.95) | 244 (13.35) | 294 (16.08) | 121 (6.62) | ||
| More than seven (n = 173) | 20 (11.56) | 11 (6.36) | 48 (27.75) | 94 (54.34) | ||
| If returned to work | 46.804 | < 0.001 | ||||
| Yes (n = 1621) | 1003 (61.88) | 208 (12.83) | 271 (16.72) | 139 (8.57) | ||
| No (n = 380) | 186 (48.95) | 47 (12.37) | 71 (18.68) | 76 (20.00) | ||
Upon comparing the two subsamples, various observations were made and recorded. First, there was no significant difference in BDI scores between the individuals in high epidemic areas and those in low epidemic regions (13.12 ± 11.35 vs 12.25 ± 11.00, P = 0.12). Second, no significant difference was observed in the incidence of moderate (21.14% vs 15.45%) and severe (10.57% vs 10.81%) depression between people in high and low epidemic areas. This finding contradicted our prediction that participants in high epidemic areas would show higher levels of depression level than those in low epidemic regions. One possible reason is that the epidemic has been largely contained domestically, and with fewer than a hundred cases in high epidemic areas, which may not be sufficient to cause widespread panic. The issue of whether to return to work and schools amidst the pressures of the pandemic is now a common challenge for all countries. The findings from this study indicated that the severe depression levels were lower among those who returned to work than among those who did not (8.57% vs 20.00%, respectively). This indicated that returning to work tends to reduce severe depression levels.
This project also aimed to identify the psychosocial factors that potentially contribute to public depression during the COVID-19 pandemic. To achieve this, the BDI scores for the participants from different subsamples were compared. Five factors, including age, marital status, education and medical background, significantly impacted the BDI score of the participants. Specifically, people under the age of 30 had significantly lower BDI scores compared to those aged 31-50 (11.92 ± 10.19 vs 13.45 ± 12.06, P < 0.01). Regarding marital status, divorced or widowed individuals exhibited higher depression scores than those who were unmarried (28.83 ± 12.80 vs 11.57 ± 9.69, P < 0.01) and married people (28.83 ± 12.80 vs 12.19 ± 11.26, P < 0.01). Additionally, the participants with a high school education had higher BDI scores than those with a college degree or above (18.02 ± 12.17 vs 11.49 ± 10.59, P < 0.01). Finally, higher BDI scores were recorded for people with medical background (14.83 ± 11.49 vs 11.95 ± 10.94, P < 0.01).
The impact of demographic factors on the incidence of moderate and severe depression among respondents was also analyzed. Except for gender, demographic factors significantly influenced depression rates. The age group 31-50 had the highest prevalence of moderate and severe depression. Among marital statuses, divorced or widowed people exhibited highest rates of severe depression compared with the unmarried (65.71% vs 5.84%) and married (65.71% vs 11.16%) people. The married individuals also had higher incidences of severe depression than their unmarried counterparts (11.16% vs 5.84%). In terms of education, those with a college degree or higher had notably lower incidences of moderate (15.78% vs 24.27%) and severe (8.10% vs 25.24%) depression, compared to those with a high school education or below. Interestingly, the respondents who worked in hospitals or attended medical school had higher incidences of both moderate (21.88% vs 15.96%) and severe depression (15.89% vs 9.52%) than the other participants.
Multiple linear regression and correlation analyses revealed predictors of BDI scores among the respondents (Table 3). Most variables significantly affected BDI scores, except gender, location and the decision to return to work. Notably, higher depression levels among individuals who were quarantined, divorced or widowed, took no preventive measures, had lower education levels, and/or medical. Logistic regression analysis showed that factors such as education level, marital status, occupation, quarantine status, preventive measures taken, and return-to-work status, were associated with the respondents’ depression levels (Table 4). The quarantine status was the most significant factor, followed by failure to take preventive measures and being divorced or widowed. The other factors presented smaller but significant impacts on the depression levels of the participants. In conclusion, People who were quarantined, divorced/widow, took no measures, with low education and medical background appeared to increase the level of depression.
| R2 = 0.201 | Beta | P value |
| Gender | 0.256 | 0.584 |
| Age | -1.209 | 0.020 |
| Education level | -2.928 | < 0.001 |
| Marital status | 1.778 | 0.001 |
| Location of residence | -0.757 | 0.125 |
| Occupation | -1.900 | 0.001 |
| Quarantine status | 9.091 | < 0.001 |
| If preventative measures taken | 13.193 | < 0.001 |
| If returned to work | 1.144 | 0.064 |
| Variables | OR | 95%CI | P value |
| Gender | 0.993 | 0.812-1.214 | 0.942 |
| Age (years old) | 0.157 | ||
| 13-30 | 1.887 | 0.949-3.753 | 0.070 |
| 31-50 | 1.926 | 0.988-3.756 | 0.054 |
| > 50 | |||
| Education level | 1.623 | 1.227-2.148 | 0.001 |
| Marital status | 0.002 | ||
| Unmarried | 0.239 | 0.109-0.523 | < 0.001 |
| Married | 0.259 | 0.121-0.552 | < 0.001 |
| Divorced/widow | |||
| Occupation | 1.580 | 1.242-2.011 | < 0.001 |
| Location of residence | 1.211 | 0.981-1.494 | 0.074 |
| Quarantine status | 0.106 | 0.031-0.363 | < 0.001 |
| If take preventative measures taken | 0.116 | 0.070-0.192 | < 0.001 |
| If returned to work | 0.866 | 0.658-1.141 | 0.307 |
This study demonstrated that the COVID-19 outbreak increased depression levels among the Chinese population as extrapolated from various pieces of evidence. First, the average depression scores of all the participants in this study were significantly higher than those of the Chinese individuals in previous years without the pandemic[9]. Second, the respondents who were quarantined due to potential exposure to COVID-19 showed higher BDI scores and greater incidences of moderate and severe depression than those who were not. Third, the absence of adequate of adequate epidemic prevention measures was a major contributor to increased depression level in the general population. These data suggest that infectious disease outbreaks may have profound effects on the lives and health of humans. Indeed, over the past decades, the frequency of pandemics appears to have increased year by year (for example, SARS, influenza A, Middle East respiratory syndrome and Ebola)[12]. The indirect effects of outbreaks on public mental health are a growing concern, with particularly pessimistic outcomes since the SARS outbreak (2002-2003), which was associated with psychiatric complications[5]. A study on SARS and suicide found that the SARS outbreak led to an increase in suicide rates[13,14].
Of the 2001 respondents, 36 were quarantined for possible COVID-19 infection during the survey period. Compared to the on-quarantined group (10.13%), the quarantined group (44.44%) had higher depression levels. The data from this study provided valuable insights into the primary causes of elevated depression levels and help analyze the influence of psychosocial factors on mood. This study holds considerable practical significance.
The primary reason for the increased rate of depression may be linked to symptoms associated with COVID-19 infection. These symptoms, such as respiratory distress, headache, nausea, and vomiting, and neurological issues[2], can lead to quarantine. The depression was not only due to the symptoms themselves, but also from the impact of quarantine measures, which forced people to suffer from irritability, boredom and frustration during lockdown periods[15]. In support this view, patients during similar pandemics, such as SARS, experienced depression, fear, loneliness, panic, angry suicidal thoughts and depressive reactions[16]. Similarly, a study reported that the Ebola virus outbreak in West Africa (2013-2016) caused severe psychological trauma for patients, as well as immense psychological stress and emotional pain for their family members[17]. Families not only faced the potential loss of their loved ones, but also the risk of infection themselves, and the possibility of quarantine due to close contact with confirmed patients. Both mental and physical stressors may aggravate depressive symptoms related to COVID-19 infection. Another study reported that the COVID-19 pandemic is associated with negative psychosocial consequences, including depressive symptoms, anxiety, anger, stress, sleep disorders, social isolation, loneliness, and stigmatization[18].
During the pandemic, health workers were more likely to experience higher levels of depression than the general population. This study confirms that 80.81% of individuals working in hospitals or receiving medical education showed symptoms of depression, compared to only 19.19% of those outside these settings. Among 1563 health professionals surveyed, approximately half (50.7%) displayed symptoms of depression[19]. Similarly, during the SARS pandemic, a hospital survey revealed that 29% of the medical staff experienced emotional distress, a rate significantly higher than that observed in the general population[20]. Additionally, healthcare workers who contracted SARS had a high incidence of posttraumatic stress disorder (40.7%), and those who cared for infected patients but were not infected continued to experience substantial psychological distress, even up to 1-2 years after the pandemic, if not mental disorders[20]. These adverse emotional experiences are associated with their direct exposure to COVID-19 infection-related events. Factors contributing to this include the severe depression rate (54.34%) among individuals who did not take anti-epidemic precautions, which was significantly higher than the rate (6.62%) among those who did.
The emotional consequences of coping with COVID-19 were significantly influenced by the participants’ age, marital status, and educational level of the participants. Specifically, divorced/or widowed individuals experienced higher levels of depression than those who were single or married. This result may be attributed to the relative isolation and lack of emotional support faced by divorced or widowed. Similar studies have shown that individuals with partners tend to have more instrumental support and socio-emotional support, resulting in lower depression levels[21].
Regarding age, the depression rate of middle-aged people (31-50 years old) (32.98%) was significantly higher than that of the young people (13-30 years old) (24.72%) and older adults over (> 50 years old) (22.22%). This difference may stem from various socio-economic pressures and family responsibilities, which are often greater for middle-aged individuals than for younger or older adults. Those in the 31-50 age range may be responsible for covering their children’s education and living expenses while also caring for older parents. Concerns about the long-term impact of the pandemic, potential income reduction, and the risk of infection, as well as leaving children and parents at home unattended, further exacerbate their stress. Middle-aged individuals often bear substantial family and work responsibilities and, as the family providers, tend to be more concerned about these issues[6].
The rate of moderate and severe depression was notably higher among those with only high school education or lower, compared to individuals with a college degree or higher. This suggests that education can help reduce depression levels related to the COVID-19 pandemic, mainly due to greater knowledge about the virus and its transmission. A lack of available information about the COVID-19 outbreak, along with discouraging news, may lead to anxiety, fear and uncertainty[22]. Unfortunately, rumors tend to spread during pandemics, and people with lower education levels are more susceptible to believing unscientific information. Consequently, this group is more likely to experience mood disturbances due to false information. This study has some limitations that must be acknowledged. First, as a cross-sectional study, it was unable to track fluctuations in participants’ affective states over time. Second, the sample size was relatively small, thereby limiting further analysis of specific subgroups was not allowed, such as those who took no protective measures (n = 173), were divorced or widowed (n = 70), or were quarantined (n = 36).
In summary, the COVID-19 outbreak has led to increased levels of depression among the public in mainland China. The primary cause of quarantine for some individuals was COVID-19, and factors such as family members contracting the virus or close contact with confirmed patients can aggravate symptoms of depression. People who did not take protective measures were higher than those who took. The people who did not return to work reported higher BDI scores than those who did, and individuals who did not return to work showed higher BDI scores compared to those who resumed work. Psychosocial factors revealed that healthcare workers and individuals lacking emotional support (such as divorced or widowed respondents) experienced significantly higher rates of depression, whereas high level of education provided a protective effect against depression associated with the COVID-19 outbreak. Depression levels also varied across age group, influenced by differing socioeconomic conditions. This information supports the development of targeted psychological interventions for various public subgroups during and after the COVID-19 pandemic and can serve as a reference for other countries.
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