Mental health problems and social media exposure during COVID-19 outbreak Junling Gao Pinpin Zheng Yingnan Jia Hao Chen Yimeng Mao Suhong Chen Yi Wang Hua Fu Junming Dai

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 Mental health problems and social media exposure during COVID-19 outbreak 2020 PLoS ONE 10.1371/journal.pone.0231924 gao2020-mental-health-problems-and-social gao2020-mental-health-problems-and-social.txt, the project's staged copy 4ef634dfab69f7ba16abb372dcdb1fd35c4adc66 cc-by health-psychology

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 136 spans located by searching the stored text for the quote's exact words, allowing any whitespace between them depression and anxiety in the Chinese general population during the first weeks of COVID-19, and their association with how often people used social media how prevalent depression and anxiety were, and whether frequent social media exposure was associated with them after covariates prevalences with confidence intervals from established scales, and an adjusted association between social media exposure and anxiety existence population-scale depression and anxiety during a quarantine, co-occurring with near-universal social media use surveysurvey the proposed pathway is exposure to information rather than to the virus: frequent social media exposure carries higher odds of anxiety (OR 1.72) and of combined depression-and-anxiety (OR 1.91) after covariates THE DEPRESSION SCALE IS A WELL-BEING SCALE, AND THE PAPER SAYS SO IN THE SAME PARAGRAPH: WHO-5's five items `reflect the presence or absence of well-being rather than depressive symptomatology`, and a summed score below 13 `indicates depression`. 48.3% DEPRESSION IS 48.3% SCORING LOW ON WELL-BEING the design cannot support the direction of the association: `it is difficult to accurately elucidate causal relationships between SME and mental health`, with longitudinal designs named as what would the sample is online and its skew is named with its direction - `some respondent bias, such as few elder citizens' participation, may have affected the results` and the adjustment is not claimed to be complete: `we cannot exclude the possibility of some residual confounding caused by unmeasured factors` the association is estimated AFTER controlling for demographic covariates, and the adjusted odds ratios are reported with intervals rather than raw proportionseliminates: an association that is really an age or education difference between frequent and infrequent social media users · outcome: held whether the direction of the association can be establishedeliminates: nothing - the design is cross-sectional and the paper says causal relationships are difficult to elucidate from it, naming cohort and nested case-control as what would be needed · outcome: failed whether covariate adjustment removed the confoundingeliminates: nothing beyond what was measured - 'we cannot exclude the possibility of some residual confounding caused by unmeasured factors' · outcome: failed whether the online sample represents the population the prevalence is quoted foreliminates: nothing, and the direction is named: few elder citizens participated · outcome: failed WHO-5WHO-5 GAD-7GAD-7 depressive symptomatologydepressive symptomatology AnxietyAnxiety residual confoundingresidual confounding social media exposuresocial media exposure mental health problemsmental health problems depressiondepression Chinese citizens aged≥18 years oldChinese citizens aged≥18 years old 31 provinces and autonomous regions31 provinces and autonomous regions Online surveyOnline survey multivariable logistic regressionsmultivariable logistic regressions combination of depression and anxiety (CDA)combination of depression and anxiety (CDA) public health emergencypublic health emergency novel coronavirus disease (COVID-19)novel coronavirus disease (COVID-19) psychological crisis interventionpsychological crisis intervention surveillance and active casessurveillance and active cases Social mediaSocial media self-media and netizensself-media and netizens (mis)information overload(mis)information overload fear, anxiety and stigmafear, anxiety and stigma indirect exposure to mass traumaindirect exposure to mass trauma post-traumatic stress disorder (PTSD) symptomspost-traumatic stress disorder (PTSD) symptoms risk perceptionsrisk perceptions rapid assessmentrapid assessment cross-sectional studycross-sectional study studystudy Wenjuanxing platformWenjuanxing platform completed questionnairescompleted questionnaires written consentwritten consent Institutional Review BoardInstitutional Review Board The Chinese version of WHO-Five Well-Being Index (WHO-5)The Chinese version of WHO-Five Well-Being Index (WHO-5) five positively worded itemsfive positively worded items presence or absence of well-beingpresence or absence of well-being 6-point scale6-point scale summed score below 13summed score below 13 Chinese version of generalized anxiety disorder scale (GAD-7)Chinese version of generalized anxiety disorder scale (GAD-7) 7 symptoms7 symptoms score of 10 or greaterscore of 10 or greater Sina weibo, Zhihu, Douban, WeChatSina weibo, Zhihu, Douban, WeChat “less” (“never” and “once in a while”), “sometimes” and “frequently” (“often” and “very often”)“less” (“never” and “once in a while”), “sometimes” and “frequently” (“often” and “very often”) covariatescovariates gendergender age (10-year categories)age (10-year categories) educational leveleducational level marital statusmarital status self-rated healthself-rated health occupationoccupation areaarea χ 2 /trend testsχ 2 /trend tests Logistic regression analysesLogistic regression analyses adjusted ORsadjusted ORs 95% confidence intervals (CIs)95% confidence intervals (CIs) STATA version 13.0 programSTATA version 13.0 program frequently SMEfrequently SME less SMEless SME high odds of anxietyhigh odds of anxiety higher frequency of SMEhigher frequency of SME adjusted odds of depressionadjusted odds of depression rural arearural area urban areaurban area disinformation and false reportsdisinformation and false reports unfounded fearsunfounded fears negative feelingsnegative feelings ‘infodemics’ team‘infodemics’ team lockdown of Wuhanlockdown of Wuhan transmission of the virustransmission of the virus longitudinal studieslongitudinal studies cohort studiescohort studies nested case-control studiesnested case-control studies respondent biasrespondent bias few elder citizens’ participationfew elder citizens’ participation resultsresults unmeasured factorsunmeasured factors mental health servicesmental health services hotline, online consultation, online course and outpatient consultationhotline, online consultation, online course and outpatient consultation monitoring and filtering out false informationmonitoring and filtering out false information promoting accurate informationpromoting accurate information cross-section collaborationscross-section collaborations Sina weibo, Zhihu, Douban, WeChat → social media exposureThe named platforms are examples delimiting the exposure question; exemplifies is absent from the eight governed types. cohort studies → longitudinal studiesCohort studies are offered as an example of longitudinal work needed next; exemplifies is absent from the eight types. nested case-control studies → longitudinal studiesNested case-control studies are offered as another longitudinal design; exemplifies is absent from the eight types. lockdown of Wuhan → transmission of the virusThe lockdown is described as a way to interrupt transmission; used-for or purpose-of is absent from the eight types. — the relation stated: Discussion The latest national sample indicated the prevalence of any disorder (excluding dementia), anxiety disorders and depressive disorders was 16.6% (95%CI: 13.0–20.2), 7.6% (95%CI: 6.3–8.8) and 6.9% (95%CI: 6.6–7.2) in China[ 13 ]. Comparing with this national data, the current cross-sectional study found that much higher prevalence of depression (48.3%, 95%CI: 46.9%-49.7%), anxiety (22.6%, 95%CI: 21.4%-23.8%) and CDA (19.4%, 95%CI: 18.3%-20.6%) during COVID-19 outbroke in Wuhan, China. These findings are consistent with the previous studies’ that exposing public health emergency can cause public mental health problems, such as Wenchuan and Lushan earthquakes[ 17 ], 2014 Ebola Outbreak[ 7 , 18 ], and SARS[ 19 ]. Social media is one of main channels updating the COVID-19 information[ 3 ]. This study also found that 82.0% of participants frequently expose them to social media, and frequently SME associated high odds of anxiety and CDA, which is consistent with previous studies [ 11 ]. there may be two reasons explaining the association between frequently SME and mental health. During COVID-19 outbreak, disinformation and false reports about the COVID-19 have bombarded social media and stoked unfounded fears among many netizens[ 20 ], which may confuse people and harm people’s mental health[ 9 ]. Besides, many citizens expressed their negative feelings, such as fear, worry, nervous, anxiety et al. on social media, which are contagious social network[ 21 , 22 ]. So, WHO’s ‘infodemics’ team is working hand in glove with countries’ communications department to deliver information to a broader public audience[ 23 ]. Finally, we also found that SME was not different between participants from Hubei province and others, but the formers faced higher odds of anxiety. It indicated that participants from Hubei province- the infectious focus directly expose to public health emergency, and may suffer more mental health problemes[ 17 , 19 ]. Compared with the control measures taken by other cities, Wuhan have sealed off the city from all outside contact to stop the spread of the COVID-19. As the prevention and control measures called new standard by WHO[ 24 ], the lockdown of Wuhan is a very effective way to interrupt the transmission of the virus, however, the strictest measures in Wuhan might lead to more serious mental health problems of local people hotline, online consultation, online course and outpatient consultation → mental health servicesThe listed channels deliver mental-health services; delivered-through is absent from the eight types. — the relation stated: Conclusions In conclusion, our findings show there are high prevalence of mental health problems, which positively associated with frequently SME during the COVID-19 outbreak. These findings implicated the government need pay more attention to mental health among general population while combating with COVID-19. Fortunately, The China government have provided mental health services by varied channel including hotline, online consultation, online course and outpatient consultation[ 6 ], but more attention should be paid to depression and anxiety. The next implication is to combat with “infodemic” by monitoring and filtering out false information and promoting accurate information though cross-section collaborations depression, AS MEASURED HERE - A WHO-5 SCORE BELOW 13. The instrument's own description, quoted by this paper, is that its items reflect WELL-BEING rather than depressive symptomatology. THE RESULT IS NAMED FOR A CONSTRUCT THE SCALE SAYS IT DOES NOT MEASURE, and the substitution is declared rather than hidden anxiety, AS MEASURED HERE - GAD-7 at 10 or above, described as `a reasonable cut point` and carrying two citations. The hedge and the citation are what qiu2020's cut-offs lack, and the difference is the whole comparison between the two records social media exposure - a self-reported FREQUENCY, and the exposure variable in a cross-sectional design. `Frequently exposed` people are more anxious; whether the exposure or the anxiety came first is what the paper says it cannot tell Social-media exposure - self-reported frequency of seeing COVID-19 news and information on named platforms during the prior week Frequent SME - the merged response category combining often and very often, contrasted with less SME as the regression reference CDA - simultaneous classification for depression by WHO-5 and anxiety by GAD-7 Adjusted association - odds ratios from multivariable logistic regressions controlling the listed demographic and contextual covariates Information-overload pathway - social media may create misinformation overload, which may in turn cause mental-health problems Online-sample bias - participation through a web survey may underrepresent older citizens Causal-status boundary - the study is cross-sectional and calls for longitudinal cohort or nested case-control designs Infodemic response - monitor and filter false information while promoting accurate information through collaboration critiques → unmoderated social media during a public health emergency - the paper's 'infodemic' recommendation follows directly from the association it measures Anxiety —operationalised-as→ GAD-7AnxietyGAD-7 cross-sectional study —is-a→ studythe relation itself is separately evidenced · strength of the relation: 1 · note: Compound-name subsumption, explicitly marked as name-derived.cross-sectional studystudy depression —operationalised-as→ WHO-5the relation itself is separately evidenced · strength of the relation: 1 · note: The paper says depression was assessed by WHO-5 and specifies the threshold.depressionWHO-5 social media exposure —operationalised-as→ “less” (“never” and “once in a while”), “sometimes” and “frequently” (“often” and “very often”)the relation itself is separately evidenced · strength of the relation: 1 · note: The exposure question is measured by frequency and recoded into three levels.social media exposure“less” (“never” and “once in a while”), “sometimes” and “frequently” (“often” and “very often”) covariates —part-of→ studythe relation itself is separately evidenced · strength of the relation: 1 · note: The listed covariates are explicitly included in the study.covariatesstudy Social media —causes→ (mis)information overloaddirection on the measure: increases · the relation itself is separately evidenced · strength of the relation: 0.7 · note: Hedged with may: social media may lead to information overload. Audit 2026-09-28: DOUBTFUL - read against its full span and kept, but social media 'may lead to' overload; hedged, and cited.Social media(mis)information overload (mis)information overload —causes→ mental health problemsdirection on the measure: increases · the relation itself is separately evidenced · strength of the relation: 0.7 · note: Hedged with may: overload may in turn cause mental-health problems. Audit 2026-09-28: DOUBTFUL - read against its full span and kept, but overload 'may cause' mental health problems; hedged, and cited.(mis)information overloadmental health problems indirect exposure to mass trauma —causes→ post-traumatic stress disorder (PTSD) symptomsdirection on the measure: increases · the relation itself is separately evidenced · strength of the relation: 0.7 · note: The cited prior evidence is stated with can increase.indirect exposure to mass traumapost-traumatic stress disorder (PTSD) symptoms frequently SME —causes→ high odds of anxietystatus: adjusted cross-sectional association; the study cannot establish causal direction · direction on the measure: increases · the relation itself is separately evidenced · strength of the relation: 1 · status (stated by the tagger, no quotation): adjusted cross-sectional association; the study cannot establish causal direction · note: Governed as an association with explicit evidential status, not as an intervention. Audit 2026-09-28: DOUBTFUL - read against its span and kept, but frequent social-media exposure was positively ASSOCIATED with high odds of anxiety (OR = 1.72); causes overstates an association.frequently SMEhigh odds of anxiety higher frequency of SME —causes→ adjusted odds of depressionstatus: insignificant adjusted cross-sectional association · direction on the measure: no-change · the relation itself is separately evidenced · strength of the relation: 0.4 — the record marks this weak · status (stated by the tagger, no quotation): insignificant adjusted cross-sectional association · note: The paper reports the positive association as statistically insignificant.higher frequency of SMEadjusted odds of depression rural area —contrasted-with→ urban areadiffers in: adjusted odds of depression · the relation itself is separately evidenced · strength of the relation: 1 · differs in (stated by the tagger, no quotation): adjusted odds of depression · note: Rural residence has lower adjusted odds than urban residence.rural areaurban area respondent bias —causes→ resultsthe relation itself is separately evidenced · strength of the relation: 0.7 · about this quote: DOUBTFUL, found by an audit that read the edge against its span: signed 'increases' with no direction word ('may have affected the results') - the sign should go, the edge may stay; its effect direction was retired for that reason and is kept under a dated before-key. The edge is kept live; a reader should weigh it with this in mind. · note: The paper says online-survey respondent bias may have affected the results. Audit 2026-09-28: DOUBTFUL - read against its span and kept, but respondent bias 'MAY have affected' the results; causes is hedged.respondent biasresults unmeasured factors —causes→ residual confoundingdirection on the measure: increases · the relation itself is separately evidenced · strength of the relation: 0.7 · note: The authors cannot exclude residual confounding caused by unmeasured factors.unmeasured factorsresidual confounding depression was assessed with the WHO-5, whose five positive items reflect well-being rather than depressive symptomsdepression was assessed with the WHO-5, whose five positive items reflect well-being rather than depressive symptoms prevalence of depression 48.3% (95%CI 46.9-49.7), anxiety 22.6% (21.4-23.8), and both together 19.4% (18.3-20.6) - every figure with an intervalprevalence of depression 48.3% (95%CI 46.9-49.7), anxiety 22.6% (21.4-23.8), and both together 19.4% (18.3-20.6) - every figure with an interval frequent social media exposure carries higher adjusted odds of anxiety (OR 1.72, 95%CI 1.31-2.26) and of combined depression-and-anxiety (OR 1.91, 1.52-2.41)frequent social media exposure carries higher adjusted odds of anxiety (OR 1.72, 95%CI 1.31-2.26) and of combined depression-and-anxiety (OR 1.91, 1.52-2.41) a GAD-7 score of 10 or more is offered as a reasonable cut point for anxiety casesa GAD-7 score of 10 or more is offered as a reasonable cut point for anxiety cases the survey was online, so respondent bias such as few elder citizens taking part may have affected the resultsthe survey was online, so respondent bias such as few elder citizens taking part may have affected the results five positively worded items reflecting the presence or absence of well-being rather than depressive symptomatology, with a summed score below 13 taken to indicate depressionWHO-5 seven symptoms rated over the last two weeks from `not at all` to `nearly every day`, scored 0 to 3GAD-7 the WHO-5 summed score below which depression is counted - the threshold behind the 48.3%value source note: THE DESCRIPTION DRAWS ON THE PAPER BEYOND THIS QUOTE: the 48.3% is the abstract's prevalence ('The prevalence of depression, anxiety and combination of depression and anxiety (CDA) was 48.3%').13 participants from 31 provinces and autonomous regions4872 95%CI95%CI OROR SMESME

Abstract. Huge citizens expose to social media during a novel coronavirus disease (COVID-19) outbroke in Wuhan, China. We assess the prevalence of mental health problems and examine their association with social media exposure. A cross-sectional study among Chinese citizens aged≥18 years old was conducted during Jan 31 to Feb 2, 2020. Online survey was used to do rapid assessment. Total of 4872 participants from 31 provinces and autonomous regions were involved in the current study. Besides demographics and social media exposure (SME), depression was assessed by The Chinese version of WHO-Five Well-Being Index (WHO-5) and anxiety was assessed by Chinese version of generalized anxiety disorder scale (GAD-7). multivariable logistic regressions were used to identify associations between social media exposure with mental health problems after controlling for covariates. The prevalence of depression, anxiety and combination of depression and anxiety (CDA) was 48.3% (95%CI: 46.9%-49.7%), 22.6% (95%CI: 21.4%-23.8%) and 19.4% (95%CI: 18.3%-20.6%) during COVID-19 outbroke in Wuhan, China. More than 80% (95%CI:80.9%-83.1%) of participants reported frequently exposed to social media. After controlling for covariates, frequently SME was positively associated with high odds of anxiety (OR = 1.72, 95%CI: 1.31–2.26) and CDA (OR = 1.91, 95%CI: 1.52–2.41) compared with less SME. Our findings show there are high prevalence of mental health problems, which positively associated with frequently SME during the COVID-19 outbreak. These findings implicated the government need pay more attention to mental health problems, especially depression and anxiety among general population and combating with “infodemic” while combating during public health emergency. Introduction A public health emergency of international concern-novel coronavirus disease (COVID-19) outbroke[ 1 ] in Wuhan, China on 31 December 2019, which has been spread to 24 countries outside of China and infected 37,558 patients globally (37,251 in China) by 9 February 2020[ 2 ]. The outbreak of COVID-19 in China has caused mental health problems among the public in China[ 3 ] and Japan[ 4 ] and medical workers in Wuhan[ 5 ]. The National Health Commission has released guideline for local authorities to promote psychological crisis intervention for patients, medical personnel, people under medical observation and civilians during the COVID-19 outbreak[ 6 ]. However, what type of mental disorders are prevalent and how they distribute among population are not know. So, a rapid assessment of outbreak-associated mental disorders for both civilians and health care workers, is needed[ 7 ]. The official departments strive to improve the public’s awareness of prevention and intervention strategies by providing daily updates about surveillance and active cases on websites and social media[ 3 ]. Besides, many self-media and netizens also release and transfer related information on social media, such as WeChat and Weibo. Social media may lead to (mis)information overload[ 8 , 9 ], which in turn may cause mental health problems. WHO pointed out that identifying the underlying drivers of fear, anxiety and stigma that fuel misinformation and rumour, particularly through social media[ 10 ]. Previous studies indicated that indirect exposure to mass trauma through the media can increase the initial rates of post-traumatic stress disorder (PTSD) symptoms[ 11 ]. A previous study also shown social media exposure may positively related to forming risk perceptions during the MERS outbreak in South Korea[ 12 ]. But there was no study to examine the association between social media exposure and mental health problems. So, the current study aims to describes the prevalence and distribution of two major mental disorders-anxiety and depression among Chinese population [ 13 ], and examine their associations with social media exposure by rapid assessment during COVID-19 outbreak. Materials and methods Design and participants This cross-sectional study was online conducted during Jan 31 to Feb 2, 2020. Chinese citizens aged≥18 years old were invited to participate online survey though Wenjuanxing platform( https://www.wjx.cn/app/survey.aspx ). In total, 5,851 participants took part in the survey. After removing the participants without completed questionnaires, 4872 participants from 31 provinces and autonomous regions were involved in the current study. A written consent in the first section of online survey was given to all participants before filling the questionnaire. This study has been approved by the Institutional Review Board of Fudan University, School of Public Health(IRB#2020-01-0800). Measurements Mental health problems According to a previous study two major mental disorders-depression and anxiety [ 13 ] were assessed in the current study. Depression was assessed by The Chinese version of WHO-Five Well-Being Index (WHO-5)[ 14 ], which consists of five positively worded items that reflect the presence or absence of well-being rather than depressive symptomatology. Participants are asked to report the presence of these positive feelings in the last 2 weeks on a 6-point scale ranging from all of the time (5 points) to at no time (0 points). A summed score below 13 indicates depression[ 14 ]. Anxiety was assessed by Chinese version of generalized anxiety disorder scale (GAD-7)[ 15 , 16 ], which consists 7 symptoms. Participants were asked how often they were bothered by each symptom during the last 2 weeks. Response options were “not at all,” “several days,” “more than half the days,” and “nearly every day,” scored as 0, 1, 2, and 3, respectively. A score of 10 or greater represents a reasonable cut point for identifying cases of anxiety[ 15 , 16 ]( S1 Table ). Social media exposure (SME) Social media exposure was measured by asking how often respondents during the past week were exposed to news and information about COVID-19 on social media, such as Sina weibo, Zhihu, Douban, WeChat and etc ( S1 Table ). Response options were “never”, “once in a while”, “sometimes”, “often” and “very often”. Because of less proportion of “never”, so we recoded social media exposure into “less” (“never” and “once in a while”), “sometimes” and “frequently” (“often” and “very often”). Covariates The following covariates were included in this study: gender, age (10-year categories), educational level (junior high school, senior high school, college and master and higher), marital status (recoded into married and other [including unmarried, divorced, and widowed]), self-rated health (categorized as excellent, very good and good or low), occupation(students/retired, health care worker and others), cities(Wuhan and others), area(urban and rural). Statistical analyses The χ 2 /trend tests were used to determine the prevalence of depression, anxiety and combination of depression and anxiety by categorical variables including social media exposure and covariates. Logistic regression analyses were used to explain the association between the prevalence of depression, anxiety and combination of depression and anxiety and SME after controlling for covariates. We estimated the adjusted ORs and their 95% confidence intervals (CIs) of independent variables for frailty. The STATA version 13.0 program (StataCorp LP., College Station, TX, USA) was used to carry out all analyses. Results Social media exposure Of all 4827 participants, the mean age of was 32.3±10.0 years (ranged 18–85), the proportion of “less”, “sometimes”, and “frequently” of SME was 8.8%(95%CI:8.0%-9.6%), 9.2%(95%CI:8.4%-10.0%) and 82.0%(95%CI:80.9%-83.1%). As shown in Table 1 , more than 60% of them (67.7%) were women, and most (47.9%) were aged 21–30 years. Many participants (62.2%) had achieved a college education, more than half of them were married. Only 5.2% of them were health care workers and 2.7% were from Hubei province, and 81.2% were from urban area. Most of them reported “excellent” (43.9%) or “very good” (45.6%) health. Univariate analyses found that the proportion of frequently SME among men (78.4%, 95%CI: 76.3%-80.3%) was lower than among women (83.8%, 95%CI: 82.4%-85.0%), the proportion of frequently SME among youngers (aged -30 years) was higher than among elders (aged 41- years). Participants with low education (middle school and high school) had lower proportion of frequently SME than who with high education (college and master). Participants who are students or retired had higher proportion of frequently SME. The proportion of SME was not different between participants from Hubei province and others, however, participants from rural area reported higher proportion of frequently SME than who from urban area. Participants who were excellent health had higher proportion of frequently SME than others. 10.1371/journal.pone.0231924.t001 Table 1 Participants characteristic and social media exposure. N(%) Social media exposure P value Less Sometimes Frequently Overall 4827(100) 424(8.8:8.0–9.6) 444(9.2:8.4–10.0) 3959(82.0:80.9–83.1) Gender Male 1560(32.3) 161(10.3:8.9–11.9) 176(11.3:9.8–13.0) 1223(78.4:76.3–80.3) <0.001 Female 3267(67.7) 263(8.1:7.2–9.0) 268(8.2:7.3–9.2) 2736(83.8:82.4–85.0) Age(years) -20 256(5.3) 11(4.3:2.2–7.6) 14(5.5:3.0–9.0) 231(90.2:85.9–93.6) <0.001 21–30 2312(47.9) 120(5.2:4.3–6.2) 150(6.5:5.5–7.6) 2042(88.3:86.9–89.6) 31–40 1288(26.9) 124(9.6:8.1–11.4) 144(11.2:9.5–13.0) 1020(79.2:76.9–81.4) 41–50 749(15.5) 120(16.0:13.5–18.8) 109(14.6:12.1–17.3) 520(69.4:66.0–72.7) 51- 222(4.6) 49(22.1:16.8–28.1) 27(12.2:8.2–17.2) 146(65.8:59.1–72.0) Education Middle school 257(5.3) 45(17.5:13.1–22.7) 30(11.7:8.0–16.2) 182(70.8:64.8–76.3) <0.001 High School 782(16.2) 85(10.9:8.8–13.3) 96(12.3:10.1–14.8) 601(76.9:73.7–79.8) College 3002(62.2) 224(7.5:6.5–8.5) 256(8.5:7.6–9.6) 2522(84.0:82.6–85.3) Master 786(16.3) 70(8.9:7.0–11.1) 62(7.9:6.1–10.0) 654(83.2:80.4–85.8) Marriage Married 2607(54.0) 314(12.0:10.8–13.5) 306(11.7:10.5–13.0) 1987(76.2:74.5–77.8) <0.001 No married 2220(46.0) 110(5.0:4.1–5.9) 138(6.2:5.2–7.3) 1972(88.8:87.4–90.1) Occupation Students/retired 1189(24.6) 84(7.1:5.7–8.7) 70(5.9:4.7–7.4) 1035(87.1:85.0–88.9) <0.001 Health care workers 251(5.2) 25(10.0:6.5–14.4) 23(9.2:5.9–13.4) 203(80.9:75.5–85.6) others 3387(70.2) 315(9.3:8.3–10.3) 351(10.4:9.4–11.4) 2721(80.3:79.0–81.7) Cities Hubei 130(2.7) 7(5.4:2.2–10.8) 13(10.0:5.4–16.5) 110(84.6:77.2–90.3) 0.375 Others 4697(97.3) 417(8.9:8.1–9.7) 431(9.2:8.4–10.0) 3849(82.0:80.8–83.0) Area Urban 3920(81.2) 363(9.3:8.4–10.2) 371(9.5:8.6–10.4) 3186(81.3:80.0–82.5) 0.015 Rural 907(18.8) 61(6.7:5.2–8.6) 73(8.1:6.4–10.0) 773(85.2:82.7–87.5) Self-rate health Excellent 2118(43.9) 173(8.2:7.0–9.4) 179(8.5:7.3–9.7) 1766(83.4:81.7–84.9) 0.020 Very good 2202(45.6) 191(8.7:7.5–9.9) 209(9.5:8.3–10.8) 1802(81.8:80.2–83.4) Good/general/poor 507(10.5) 60(11.8:9.1–15.0) 56(11.1:8.5–14.1) 391(77.2:73.2–80.7) Depression and SME The prevalence of depression was 48.3% (95%CI: 46.9%-49.7%). As shown Fig 1 , Multivariate analyses found that the adjusted odds of depression were greater among who age 21–30 years (OR = 1.49, 95%CI: 1.12–1.99) and 31–40 years (OR = 1.54, 95%CI: 1.11–2.14) compared with who aged ≤20 years, and lower among those with college (OR = 0.69, 95%CI: 0.53–0.91) and master (OR = 0.46, 95%CI: 0.63–0.85) education than those with middle school. Participants from Hubei province had no higher adjusted odds than those from other province (OR = 1.06, 95%CI: 0.75–1.52), but those from rural area had lower adjusted odds (OR = 0.74, 95%CI: 0.64–0.87) than those from urban area. The decrease of self-rated health significantly accompanied the increased odds of depression. About the focus of this study, higher frequency of SME was insignificantly positively associated with the adjusted odds of depression after controlling for all covariates. 10.1371/journal.pone.0231924.g001 Fig 1 Prevalence of depression and relevant factors. Anxiety and SME The prevalence of anxiety was 22.6% (95%CI: 21.4%-23.8%). As shown Fig 2 , Multivariate analyses found that that the adjusted odds of depression were greater among those aged 31–40 years (OR = 1.63, 95%CI: 1.06–2.51) compared with those aged -20 years, and lower among those with college (OR = 0.40, 95%CI: 0.30–0.53) and master (OR = 0.31, 95%CI: 0.22–0.44) education than those with middle school. The adjusted odds of depression among unmarried participants (OR = 0.80, 95%CI: 0.66–0.96) was lower than among married ones. Participants from other provinces had no higher adjusted odds (OR = 0.49, 95%CI: 0.33–0.71) than those from Hubei province. The adjusted odds of depression were greater among those with good/general/poor SRH (OR = 1.77, 95%CI: 1.41–2.21) compared with those with excellent SRH. About the focus of this study, frequently SME can increase the adjusted odds (OR = 1.72, 95%CI: 1.31–2.26) of anxiety compared with less SME after controlling for all covariates. 10.1371/journal.pone.0231924.g002 Fig 2 Prevalence of anxiety and relevant factors. Combination of depression and anxiety and SME The prevalence of combination of depression and anxiety (CDA) was 19.4% (95%CI: 18.3%-20.6%). As shown Fig 3 , Multivariate analyses found that that the adjusted odds of depression were greater among those aged 31–40 years (OR = 1.69, 95%CI: 1.07–2.68) compared with those aged -20 years, and lower among those with college (OR = 0.50, 95%CI: 0.37–0.68) and master (OR = 0.40, 95%CI: 0.28–0.57) education than those with middle school. The adjusted odds of depression among unmarried participants (OR = 0.79, 95%CI: 0.64–0.97) was lower than among married ones. The adjusted odds of depression were greater among those with good/general/poor SRH (OR = 1.77, 95%CI: 1.41–2.21) compared with those with excellent SRH. About the focus of this study, frequently SME can increase the adjusted odds (OR = 1.91, 95%CI: 1.52–2.41) of CDA compared with less SEM after controlling for all covariates. 10.1371/journal.pone.0231924.g003 Fig 3 Prevalence of combination of depression and anxiety and relevant factors. Discussion The latest national sample indicated the prevalence of any disorder (excluding dementia), anxiety disorders and depressive disorders was 16.6% (95%CI: 13.0–20.2), 7.6% (95%CI: 6.3–8.8) and 6.9% (95%CI: 6.6–7.2) in China[ 13 ]. Comparing with this national data, the current cross-sectional study found that much higher prevalence of depression (48.3%, 95%CI: 46.9%-49.7%), anxiety (22.6%, 95%CI: 21.4%-23.8%) and CDA (19.4%, 95%CI: 18.3%-20.6%) during COVID-19 outbroke in Wuhan, China. These findings are consistent with the previous studies’ that exposing public health emergency can cause public mental health problems, such as Wenchuan and Lushan earthquakes[ 17 ], 2014 Ebola Outbreak[ 7 , 18 ], and SARS[ 19 ]. Social media is one of main channels updating the COVID-19 information[ 3 ]. This study also found that 82.0% of participants frequently expose them to social media, and frequently SME associated high odds of anxiety and CDA, which is consistent with previous studies [ 11 ]. there may be two reasons explaining the association between frequently SME and mental health. During COVID-19 outbreak, disinformation and false reports about the COVID-19 have bombarded social media and stoked unfounded fears among many netizens[ 20 ], which may confuse people and harm people’s mental health[ 9 ]. Besides, many citizens expressed their negative feelings, such as fear, worry, nervous, anxiety et al. on social media, which are contagious social network[ 21 , 22 ]. So, WHO’s ‘infodemics’ team is working hand in glove with countries’ communications department to deliver information to a broader public audience[ 23 ]. Finally, we also found that SME was not different between participants from Hubei province and others, but the formers faced higher odds of anxiety. It indicated that participants from Hubei province- the infectious focus directly expose to public health emergency, and may suffer more mental health problemes[ 17 , 19 ]. Compared with the control measures taken by other cities, Wuhan have sealed off the city from all outside contact to stop the spread of the COVID-19. As the prevention and control measures called new standard by WHO[ 24 ], the lockdown of Wuhan is a very effective way to interrupt the transmission of the virus, however, the strictest measures in Wuhan might lead to more serious mental health problems of local people. Some potential limitations should be noted in this study. First, this is a cross-sectional study, so it is difficult to accurately elucidate causal relationships between SME and mental health. Additional longitudinal studies, such as cohort studies or nested case-control studies, are essential in the future. Although large sample, the survey was conducted online, which is suitable for rapid assessment, so some respondent bias, such as few elder citizens’ participation, may have affected the results. Finally, although we did control for many covariates, we cannot exclude the possibility of some residual confounding caused by unmeasured factors. Conclusions In conclusion, our findings show there are high prevalence of mental health problems, which positively associated with frequently SME during the COVID-19 outbreak. These findings implicated the government need pay more attention to mental health among general population while combating with COVID-19. Fortunately, The China government have provided mental health services by varied channel including hotline, online consultation, online course and outpatient consultation[ 6 ], but more attention should be paid to depression and anxiety. The next implication is to combat with “infodemic” by monitoring and filtering out false information and promoting accurate information though cross-section collaborations. Supporting information S1 Table (DOCX) Click here for additional data file. S1 Data (XLS) Click here for additional data file.