Junling GaopersName, Pinpin ZhengpersName, Yingnan JiapersName, Hao ChenpersName, Yimeng MaopersName, Suhong ChenpersName, Yi WangpersName, Hua FupersName, Junming DaipersName (2020date). “Mental health problems and social media exposure during COVID-19 outbreak.” PLoS ONEtitle·venue.
Object of study — depressionterm and anxietyterm in the Chinese general population during the first weeks of COVID-19, and their association with how often people used social mediaterm
Research question — how prevalent depressionterm and anxietyterm were, and whether frequent social media exposureterm was associated with them after covariatesterm
Contribution — prevalences with confidence intervals from established scales, and an adjusted association between social media exposureterm and anxietyterm
Cross-disciplinary analysis
content-tags & facets:
phenomenon · claim-type · cross-domain-transfer · mechanism · claim-relation · replication-status · limitation — grounded in the full text| phenomenon | population-scale depression and anxiety during a quarantine, co-occurring with near-universal social media use — “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.” | |
| claim-type | existence — “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.” | |
| method — evidence | — “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.” | |
| object of study — evidence | — “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.” | |
| research question — evidence | — “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.” | |
| contribution — evidence | — “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.” | |
| mechanism | 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 — “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.” | mechanisms[0] |
| critiques | unmoderated social media during a public health emergency - the paper's 'infodemic' recommendation follows directly from the association it measures — “The next implication is to combat with “infodemic” by monitoring and filtering out false information and promoting accurate information though cross-section collaborations.” | claim_relations[0] |
| sense | 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 — “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.” | senses[0] |
| sense | 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 — “A score of 10 or greater represents a reasonable cut point for identifying cases of anxiety” | senses[1] |
| sense | 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 — “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.” | senses[2] |
| sense | Social-media exposure - self-reported frequency of seeing COVID-19 news and information on named platforms during the prior week — “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”)” | senses[3] |
| sense | Frequent SME - the merged response category combining often and very often, contrasted with less SME as the regression reference — “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”)” | senses[4] |
| sense | CDA - simultaneous classification for depression by WHO-5 and anxiety by GAD-7 — “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” | senses[5] |
| sense | Adjusted association - odds ratios from multivariable logistic regressions controlling the listed demographic and contextual covariates — “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” | senses[6] |
| sense | Information-overload pathway - social media may create misinformation overload, which may in turn cause mental-health problems — “Social media may lead to (mis)information overload[ 8 , 9 ], which in turn may cause mental health problems” | senses[7] |
| sense | Online-sample bias - participation through a web survey may underrepresent older citizens — “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” | senses[8] |
| sense | Causal-status boundary - the study is cross-sectional and calls for longitudinal cohort or nested case-control designs — “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” | senses[9] |
| sense | Infodemic response - monitor and filter false information while promoting accurate information through collaboration — “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” | senses[10] |
| control | the association is estimated AFTER controlling for demographic covariates, and the adjusted odds ratios are reported with intervals rather than raw proportions — held — “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.” — rules out an association that is really an age or education difference between frequent and infrequent social media users — “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.” | controls[0] |
| control | whether the direction of the association can be established — failed — “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.” — rules out 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 — “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.” | controls[1] |
| control | whether covariate adjustment removed the confounding — failed — “Finally, although we did control for many covariates, we cannot exclude the possibility of some residual confounding caused by unmeasured factors.” — rules out nothing beyond what was measured - 'we cannot exclude the possibility of some residual confounding caused by unmeasured factors' — “Finally, although we did control for many covariates, we cannot exclude the possibility of some residual confounding caused by unmeasured factors.” | controls[2] |
| control | whether the online sample represents the population the prevalence is quoted for — failed — “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.” — rules out nothing, and the direction is named: few elder citizens participated — “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.” | controls[3] |
| weight | unmoderated social media during a public health emergency - the paper's 'infodemic' recommendation follows directly from the association it measures — 0.8 — “The next implication is to combat with “infodemic” by monitoring and filtering out false information and promoting accurate information though cross-section collaborations.” | claim_relations[0] |
| edge | Anxiety —operationalised-as→ GAD-7 — “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.” | concept_edges[1] |
| note | cross-sectional study —is-a→ study — Compound-name subsumption, explicitly marked as name-derived. — “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” | concept_edges[2] |
| note | depression —operationalised-as→ WHO-5 — The paper says depression was assessed by WHO-5 and specifies the threshold. — “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” | concept_edges[3] |
| note | social media exposure —operationalised-as→ “less” (“never” and “once in a while”), “sometimes” and “frequently” (“often” and “very often”) — The exposure question is measured by frequency and recoded into three levels. — “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”)” | concept_edges[5] |
| note | covariates —part-of→ study — The listed covariates are explicitly included in the study. — “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)” | concept_edges[6] |
| audit | Social media —causes→ (mis)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 may lead to (mis)information overload[ 8 , 9 ], which in turn may cause mental health problems” | concept_edges[7] |
| effect direction | Social media —causes→ (mis)information overload — increases — “Social media may lead to (mis)information overload[ 8 , 9 ], which in turn may cause mental health problems” | concept_edges[7] |
| note | Social media —causes→ (mis)information overload — Hedged with may: social media may lead to information overload. — “Social media may lead to (mis)information overload[ 8 , 9 ], which in turn may cause mental health problems” | concept_edges[7] |
| weight | Social media —causes→ (mis)information overload — 0.7 — “Social media may lead to (mis)information overload[ 8 , 9 ], which in turn may cause mental health problems” | concept_edges[7] |
| audit | (mis)information overload —causes→ 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. — “Social media may lead to (mis)information overload[ 8 , 9 ], which in turn may cause mental health problems” | concept_edges[8] |
| effect direction | (mis)information overload —causes→ mental health problems — increases — “Social media may lead to (mis)information overload[ 8 , 9 ], which in turn may cause mental health problems” | concept_edges[8] |
| note | (mis)information overload —causes→ mental health problems — Hedged with may: overload may in turn cause mental-health problems. — “Social media may lead to (mis)information overload[ 8 , 9 ], which in turn may cause mental health problems” | concept_edges[8] |
| weight | (mis)information overload —causes→ mental health problems — 0.7 — “Social media may lead to (mis)information overload[ 8 , 9 ], which in turn may cause mental health problems” | concept_edges[8] |
| effect direction | indirect exposure to mass trauma —causes→ post-traumatic stress disorder (PTSD) symptoms — increases — “Previous studies indicated that indirect exposure to mass trauma through the media can increase the initial rates of post-traumatic stress disorder (PTSD) symptoms” | concept_edges[9] |
| note | indirect exposure to mass trauma —causes→ post-traumatic stress disorder (PTSD) symptoms — The cited prior evidence is stated with can increase. — “Previous studies indicated that indirect exposure to mass trauma through the media can increase the initial rates of post-traumatic stress disorder (PTSD) symptoms” | concept_edges[9] |
| weight | indirect exposure to mass trauma —causes→ post-traumatic stress disorder (PTSD) symptoms — 0.7 — “Previous studies indicated that indirect exposure to mass trauma through the media can increase the initial rates of post-traumatic stress disorder (PTSD) symptoms” | concept_edges[9] |
| audit | frequently SME —causes→ high odds of anxiety — 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. — “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” | concept_edges[10] |
| effect direction | frequently SME —causes→ high odds of anxiety — increases — “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” | concept_edges[10] |
| evidential status (stated by the tagger, no quotation) | frequently SME —causes→ high odds of anxiety — adjusted cross-sectional association; the study cannot establish causal direction | concept_edges[10] |
| note | frequently SME —causes→ high odds of anxiety — Governed as an association with explicit evidential status, not as an intervention. — “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” | concept_edges[10] |
| effect direction | higher frequency of SME —causes→ adjusted odds of depression — no-change — “higher frequency of SME was insignificantly positively associated with the adjusted odds of depression after controlling for all covariates” | concept_edges[11] |
| evidential status (stated by the tagger, no quotation) | higher frequency of SME —causes→ adjusted odds of depression — insignificant adjusted cross-sectional association | concept_edges[11] |
| note | higher frequency of SME —causes→ adjusted odds of depression — The paper reports the positive association as statistically insignificant. — “higher frequency of SME was insignificantly positively associated with the adjusted odds of depression after controlling for all covariates” | concept_edges[11] |
| weight | higher frequency of SME —causes→ adjusted odds of depression — 0.4 — “higher frequency of SME was insignificantly positively associated with the adjusted odds of depression after controlling for all covariates” | concept_edges[11] |
| differs in (stated by the tagger, no quotation) | rural area —contrasted-with→ urban area — adjusted odds of depression | concept_edges[12] |
| note | rural area —contrasted-with→ urban area — Rural residence has lower adjusted odds than urban residence. — “but those from rural area had lower adjusted odds (OR = 0.74, 95%CI: 0.64–0.87) than those from urban area” | concept_edges[12] |
| audit | respondent bias —causes→ results — Audit 2026-09-28: DOUBTFUL - read against its span and kept, but respondent bias 'MAY have affected' the results; causes is hedged. — “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” | concept_edges[13] |
| evidence status note | respondent bias —causes→ results — 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. — “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” | concept_edges[13] |
| note | respondent bias —causes→ results — The paper says online-survey respondent bias may have affected the results. — “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” | concept_edges[13] |
| weight | respondent bias —causes→ results — 0.7 — “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” | concept_edges[13] |
| effect direction | unmeasured factors —causes→ residual confounding — increases — “Finally, although we did control for many covariates, we cannot exclude the possibility of some residual confounding caused by unmeasured factors” | concept_edges[14] |
| note | unmeasured factors —causes→ residual confounding — The authors cannot exclude residual confounding caused by unmeasured factors. — “Finally, although we did control for many covariates, we cannot exclude the possibility of some residual confounding caused by unmeasured factors” | concept_edges[14] |
| weight | unmeasured factors —causes→ residual confounding — 0.7 — “Finally, although we did control for many covariates, we cannot exclude the possibility of some residual confounding caused by unmeasured factors” | concept_edges[14] |
| outcome | control — held — “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.” | controls[0] |
| outcome | control — failed — “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.” | controls[1] |
| outcome | control — failed — “Finally, although we did control for many covariates, we cannot exclude the possibility of some residual confounding caused by unmeasured factors.” | controls[2] |
| outcome | control — failed — “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.” | controls[3] |
| relation | lockdown of Wuhan → transmission of the virus — 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 — “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” | unhoused_relations[3] |
| relation | hotline, online consultation, online course and outpatient consultation → mental health services — 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 — “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” | unhoused_relations[4] |
| no type for this | Sina weibo, Zhihu, Douban, WeChat → social media exposure — The named platforms are examples delimiting the exposure question; exemplifies is absent from the eight governed types. — “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”)” | unhoused_relations[0] |
| no type for this | cohort studies → longitudinal studies — Cohort studies are offered as an example of longitudinal work needed next; exemplifies is absent from the eight types. — “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” | unhoused_relations[1] |
| no type for this | nested case-control studies → longitudinal studies — Nested case-control studies are offered as another longitudinal design; exemplifies is absent from the eight types. — “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” | unhoused_relations[2] |
| no type for this | lockdown of Wuhan → transmission of the virus — The lockdown is described as a way to interrupt transmission; used-for or purpose-of is absent from the eight types. — “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” | unhoused_relations[3] |
| no type for this | hotline, online consultation, online course and outpatient consultation → mental health services — The listed channels deliver mental-health services; delivered-through is absent from the eight types. — “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” | unhoused_relations[4] |
| limitation | 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 — “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.” | limitations[0] |
| limitation | 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 — “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.” | limitations[1] |
| limitation | 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` — “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.” | limitations[2] |
| limitation | and the adjustment is not claimed to be complete: `we cannot exclude the possibility of some residual confounding caused by unmeasured factors` — “Finally, although we did control for many covariates, we cannot exclude the possibility of some residual confounding caused by unmeasured factors.” | limitations[3] |
Content tags
content-observations:
finding · quantity · variable · definition · key-term — grounded in the full text| finding | — “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.” | content_tags.findings[0] |
| finding | — “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.” | content_tags.findings[1] |
| finding | — “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.” | content_tags.findings[2] |
| finding | — “A score of 10 or greater represents a reasonable cut point for identifying cases of anxiety” | content_tags.findings[3] |
| finding | — “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.” | content_tags.findings[4] |
| quantity | the WHO-5 summed score below which depression is counted - the threshold behind the 48.3% — “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” | content_tags.quantities[0] |
| value source note | quantity — 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%'). | content_tags.quantities[0] |
| quantity | participants from 31 provinces and autonomous regions — “Total of 4872 participants from 31 provinces and autonomous regions were involved in the current study.” | content_tags.quantities[1] |
| variable | SME — “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.” | content_tags.variables[0] |
| definition | WHO-5 — “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.” | content_tags.definitions[0] |
| definition | GAD-7 — “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.” | content_tags.definitions[1] |
Concepts
terms this paper carries, each with the sentence it was cut from — the layer that joins one paper to another. Terms with no quote yet are on CONCEPTS.html.
| concept | WHO-5 — not defined in this paper's own words; the WHO-Five Well-Being Index - five positively worded items, scored 0-25, with below 13 taken here to indicate depression — “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.” | concepts[0] |
| concept | GAD-7 — not defined in this paper's own words; the seven-symptom generalized anxiety disorder scale, with 10 or above as the cut point for a case — “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.” | concepts[1] |
| concept | depressive symptomatology — not defined in this paper's own words; what WHO-5 explicitly does NOT reflect, in the paper's own description of it — “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.” | concepts[2] |
| concept | Anxiety — not defined in this paper's own words; the second outcome, assessed by GAD-7 and counted at a score of 10 or above — “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.” | concepts[3] |
| concept | residual confounding — not defined in this paper's own words; the unmeasured-factor bias the authors say they cannot exclude despite controlling many covariates — “Finally, although we did control for many covariates, we cannot exclude the possibility of some residual confounding caused by unmeasured factors.” | concepts[4] |
| concept | social media exposure — not defined in this paper's own words; frequency of encountering COVID-19 news and information on named social platforms — “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” | concepts[5] |
| concept | mental health problems — not defined in this paper's own words; the paper's umbrella outcome for depression, anxiety, and their combination — “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” | concepts[6] |
| concept | depression — not defined in this paper's own words; WHO-5-below-13 outcome used in the study — “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” | concepts[7] |
| concept | Chinese citizens aged≥18 years old — not defined in this paper's own words; adult target population for the rapid online survey — “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” | concepts[8] |
| concept | 31 provinces and autonomous regions — not defined in this paper's own words; geographic coverage of the analytic sample — “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” | concepts[9] |
| concept | Online survey — not defined in this paper's own words; rapid remote data-collection method — “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” | concepts[10] |
| concept | multivariable logistic regressions — not defined in this paper's own words; adjusted association model used for the three mental-health outcomes — “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” | concepts[11] |
| concept | combination of depression and anxiety (CDA) — not defined in this paper's own words; joint outcome defined by meeting both study thresholds — “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” | concepts[12] |
| concept | public health emergency — not defined in this paper's own words; outbreak context in which the study was conducted — “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” | concepts[13] |
| concept | novel coronavirus disease (COVID-19) — not defined in this paper's own words; international public-health emergency motivating the assessment — “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” | concepts[14] |
| concept | psychological crisis intervention — not defined in this paper's own words; recommended intervention for affected groups during the outbreak — “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” | concepts[15] |
| concept | surveillance and active cases — not defined in this paper's own words; official information updated through websites and social media — “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” | concepts[16] |
| concept | Social media — not defined in this paper's own words; channel for official and user-generated outbreak information — “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” | concepts[17] |
| concept | self-media and netizens — not defined in this paper's own words; non-official actors releasing and transferring outbreak information — “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” | concepts[18] |
| concept | (mis)information overload — not defined in this paper's own words; proposed informational pathway from social media to mental-health problems — “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” | concepts[19] |
| concept | fear, anxiety and stigma — not defined in this paper's own words; drivers said to fuel misinformation and rumour — “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” | concepts[20] |
| concept | indirect exposure to mass trauma — not defined in this paper's own words; media-mediated exposure proposed to increase trauma symptoms — “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” | concepts[21] |
| concept | post-traumatic stress disorder (PTSD) symptoms — not defined in this paper's own words; symptoms reported to rise after indirect mass-trauma exposure — “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” | concepts[22] |
| concept | risk perceptions — not defined in this paper's own words; perceptions previously associated with social-media exposure during MERS — “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” | concepts[23] |
| concept | rapid assessment — not defined in this paper's own words; time-sensitive assessment of outbreak-associated disorders — “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” | concepts[24] |
| concept | cross-sectional study — not defined in this paper's own words; observational design conducted over three days — “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” | concepts[25] |
| concept | study — not defined in this paper's own words; the present observational investigation — “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” | concepts[26] |
| concept | Wenjuanxing platform — not defined in this paper's own words; online platform through which adults were invited — “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” | concepts[27] |
| concept | completed questionnaires — not defined in this paper's own words; completion condition used to retain participants — “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” | concepts[28] |
| concept | written consent — not defined in this paper's own words; consent presented before questionnaire completion — “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” | concepts[29] |
| concept | Institutional Review Board — not defined in this paper's own words; Fudan University ethics-review body approving the study — “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” | concepts[30] |
| concept | The Chinese version of WHO-Five Well-Being Index (WHO-5) — not defined in this paper's own words; five-item instrument used as the depression indicator — “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”)” | concepts[31] |
| concept | five positively worded items — not defined in this paper's own words; well-being items composing WHO-5 — “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”)” | concepts[32] |
| concept | presence or absence of well-being — not defined in this paper's own words; property the WHO-5 items explicitly reflect — “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”)” | concepts[33] |
| concept | 6-point scale — not defined in this paper's own words; response scale for the five positive-feeling items — “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”)” | concepts[34] |
| concept | summed score below 13 — not defined in this paper's own words; study threshold indicating depression — “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”)” | concepts[35] |
| concept | Chinese version of generalized anxiety disorder scale (GAD-7) — not defined in this paper's own words; seven-symptom instrument used for anxiety — “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”)” | concepts[36] |
| concept | 7 symptoms — not defined in this paper's own words; symptom set composing GAD-7 — “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”)” | concepts[37] |
| concept | score of 10 or greater — not defined in this paper's own words; cut point used to identify anxiety cases — “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”)” | concepts[38] |
| concept | Sina weibo, Zhihu, Douban, WeChat — not defined in this paper's own words; examples used to delimit the social-media exposure question — “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”)” | concepts[39] |
| concept | “less” (“never” and “once in a while”), “sometimes” and “frequently” (“often” and “very often”) — not defined in this paper's own words; three-category recoding of exposure-frequency responses — “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”)” | concepts[40] |
| concept | covariates — not defined in this paper's own words; demographic and contextual variables included in adjusted models — “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” | concepts[41] |
| concept | gender — not defined in this paper's own words; included covariate — “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).” | concepts[42] |
| concept | age (10-year categories) — not defined in this paper's own words; categorised age covariate — “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).” | concepts[43] |
| concept | educational level — not defined in this paper's own words; education covariate — “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).” | concepts[44] |
| concept | marital status — not defined in this paper's own words; marriage covariate recoded into married versus other — “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).” | concepts[45] |
| concept | self-rated health — not defined in this paper's own words; health-status covariate — “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).” | concepts[46] |
| concept | occupation — not defined in this paper's own words; participant-role covariate — “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).” | concepts[47] |
| concept | area — not defined in this paper's own words; urban-versus-rural covariate — “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).” | concepts[48] |
| concept | χ 2 /trend tests — not defined in this paper's own words; univariate prevalence-comparison tests — “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” | concepts[49] |
| concept | Logistic regression analyses — not defined in this paper's own words; models explaining outcome prevalence by exposure after adjustment — “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” | concepts[50] |
| concept | adjusted ORs — not defined in this paper's own words; effect estimates reported for independent variables — “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” | concepts[51] |
| concept | 95% confidence intervals (CIs) — not defined in this paper's own words; uncertainty intervals around adjusted odds ratios — “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” | concepts[52] |
| concept | STATA version 13.0 program — not defined in this paper's own words; software used for all 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” | concepts[53] |
| concept | frequently SME — not defined in this paper's own words; highest social-media-exposure category — “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.” | concepts[54] |
| concept | less SME — not defined in this paper's own words; reference social-media-exposure category — “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.” | concepts[55] |
| concept | high odds of anxiety — not defined in this paper's own words; adjusted anxiety outcome associated with frequent exposure — “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” | concepts[56] |
| concept | higher frequency of SME — not defined in this paper's own words; exposure gradient tested against depression — “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.” | concepts[57] |
| concept | adjusted odds of depression — not defined in this paper's own words; adjusted depression outcome — “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.” | concepts[58] |
| concept | rural area — not defined in this paper's own words; residence category with lower adjusted depression odds — “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.” | concepts[59] |
| concept | urban area — not defined in this paper's own words; reference residence category — “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.” | concepts[60] |
| concept | disinformation and false reports — not defined in this paper's own words; content proposed to stoke unfounded fears — “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” | concepts[61] |
| concept | unfounded fears — not defined in this paper's own words; fear response attributed to false outbreak reports — “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” | concepts[62] |
| concept | negative feelings — not defined in this paper's own words; fear, worry, nervousness and anxiety expressed online — “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” | concepts[63] |
| concept | ‘infodemics’ team — not defined in this paper's own words; WHO team coordinating public information delivery — “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” | concepts[64] |
| concept | lockdown of Wuhan — not defined in this paper's own words; city-sealing measure intended to interrupt transmission — “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” | concepts[65] |
| concept | transmission of the virus — not defined in this paper's own words; process the lockdown was intended to interrupt — “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” | concepts[66] |
| concept | longitudinal studies — not defined in this paper's own words; design family proposed to address causal direction — “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” | concepts[67] |
| concept | cohort studies — not defined in this paper's own words; named longitudinal follow-up design — “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” | concepts[68] |
| concept | nested case-control studies — not defined in this paper's own words; named longitudinal comparison design — “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” | concepts[69] |
| concept | respondent bias — not defined in this paper's own words; selection problem attributed to online recruitment — “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” | concepts[70] |
| concept | few elder citizens’ participation — not defined in this paper's own words; specific direction of online-sample bias — “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” | concepts[71] |
| concept | results — not defined in this paper's own words; study estimates that may be affected by online-survey respondent bias — “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” | concepts[72] |
| concept | unmeasured factors — not defined in this paper's own words; possible sources of residual confounding — “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” | concepts[73] |
| concept | mental health services — not defined in this paper's own words; government response delivered through several channels — “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” | concepts[74] |
| concept | hotline, online consultation, online course and outpatient consultation — not defined in this paper's own words; channels listed for mental-health service delivery — “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” | concepts[75] |
| concept | monitoring and filtering out false information — not defined in this paper's own words; recommended infodemic response — “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” | concepts[76] |
| concept | promoting accurate information — not defined in this paper's own words; recommended communication response — “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” | concepts[77] |
| concept | cross-section collaborations — not defined in this paper's own words; collaborative setting proposed for accurate-information promotion — “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” | concepts[78] |
Statistics — cross-field join keys
field-invariant statistical terms, used in their statistical sense (gated on a number / symbol / test). A p-value or a standard deviation means the SAME thing in physics, biology, psychology and sociology — so these are the strongest cross-field join keys. Grounded verbatim.
| 95%CI | — “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.” | content_tags.statistics[0] |
| OR | — “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.” | content_tags.statistics[1] |
Full text — tagged
The reference list is not part of the text we hold for this paper. Our copy was extracted from the publisher's page and the bibliography did not survive that extraction, so the article below ends before its references. Nothing has been removed by us.
Abstract. Huge citizens expose to social mediaterm during a novel coronavirus disease (COVID-19)term outbroke in Wuhan, China. We assess the prevalence of mental health problemsterm and examine their association with social media exposureterm. A cross-sectional studyterm among Chinese citizens aged≥18 years oldterm was conducted during Jan 31 to Feb 2, 2020. Online surveyterm was used to do rapid assessmentterm. Total of 4872 participants from 31 provinces and autonomous regionsterm were involved in the current studyterm. Besides demographics and social media exposureterm (SMEterm·var), depressionterm was assessed by The Chinese version of WHO-Five Well-Being Index (WHO-5)term and anxietyterm was assessed by Chinese version of generalized anxiety disorder scale (GAD-7)term. multivariable logistic regressionsterm were used to identify associations between social media exposureterm with mental health problemsterm after controlling for covariatesterm. The prevalence of depressionterm, anxietyterm and combination of depression and anxiety (CDA)term 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 mediaterm. After controlling for covariatesterm, frequently SMEterm was positively associated with high odds of anxietyterm (OR = 1.72, 95%CI: 1.31–2.26) and CDA (OR = 1.91, 95%CI: 1.52–2.41) compared with less SMEterm. Our findings show there are high prevalence of mental health problemsterm, which positively associated with frequently SMEterm during the COVID-19 outbreak. These findings implicated the government need pay more attention to mental health problemsterm, especially depressionterm and anxietyterm among general population and combating with “infodemic” while combating during public health emergencyterm. Introduction A public health emergencyterm 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 problemsterm 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 interventionterm 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 assessmentterm 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 casesterm on websites and social mediaterm[ 3 ]. Besides, many self-media and netizensterm also release and transfer related information on social mediaterm, such as WeChat and Weibo. Social mediaterm may lead to (mis)information overloadterm[ 8 , 9 ], which in turn may cause mental health problemsterm. WHO pointed out that identifying the underlying drivers of fear, anxiety and stigmaterm that fuel misinformation and rumour, particularly through social mediaterm[ 10 ]. Previous studies indicated that indirect exposure to mass traumaterm through the media can increase the initial rates of post-traumatic stress disorder (PTSD) symptomsterm[ 11 ]. A previous studyterm also shown social media exposureterm may positively related to forming risk perceptionsterm during the MERS outbreak in South Korea[ 12 ]. But there was no studyterm to examine the association between social media exposureterm and mental health problemsterm. So, the current studyterm aims to describes the prevalence and distribution of two major mental disorders-anxiety and depressionterm among Chinese population [ 13 ], and examine their associations with social media exposureterm by rapid assessmentterm during COVID-19 outbreak. Materials and methods Design and participants This cross-sectional studyterm was online conducted during Jan 31 to Feb 2, 2020. Chinese citizens aged≥18 years oldterm were invited to participate online surveyterm though Wenjuanxing platformterm( https://www.wjx.cn/app/surveyterm·mth.aspx ). In total, 5,851 participants took part in the surveyterm·mth. After removing the participants without completed questionnairesterm, 4872 participants from 31 provinces and autonomous regionsterm were involved in the current studyterm. A written consentterm in the first section of online surveyterm was given to all participants before filling the questionnaire. This studyterm has been approved by the Institutional Review Boardterm of Fudan University, School of Public Health(IRB#2020-01-0800). Measurements Mental health problemsterm According to a previous studyterm two major mental disorders-depression and anxietyterm [ 13 ] were assessed in the current studyterm. Depressionterm was assessed by The Chinese version of WHO-Five Well-Being Index (WHO-5)term[ 14 ], which consists of five positively worded itemsterm that reflect the presence or absence of well-beingterm rather than depressive symptomatologyterm. Participants are asked to report the presence of these positive feelings in the last 2 weeks on a 6-point scaleterm ranging from all of the time (5 points) to at no time (0 points). A summed score below 13term indicates depressionterm[ 14 ]. Anxietyterm was assessed by Chinese version of generalized anxiety disorder scale (GAD-7)term[ 15 , 16 ], which consists 7 symptomsterm. 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 greaterterm represents a reasonable cut point for identifying cases of anxietyterm[ 15 , 16 ]( S1 Table ). Social media exposureterm (SMEterm·var) Social media exposureterm was measured by asking how often respondents during the past week were exposed to news and information about COVID-19 on social mediaterm, such as Sina weibo, Zhihu, Douban, WeChatterm 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 exposureterm into “less” (“never” and “once in a while”), “sometimes” and “frequently” (“often” and “very often”)term. Covariatesterm The following covariatesterm were included in this studyterm: genderterm, age (10-year categories)term, educational levelterm (junior high school, senior high school, college and master and higher), marital statusterm (recoded into married and other [including unmarried, divorced, and widowed]), self-rated healthterm (categorized as excellent, very good and good or low), occupationterm(students/retired, health care worker and others), cities(Wuhan and others), areaterm(urban and rural). Statistical analyses The χ 2 /trend teststerm were used to determine the prevalence of depressionterm, anxietyterm and combination of depressionterm and anxietyterm by categorical variables including social media exposureterm and covariatesterm. Logistic regression analysesterm were used to explain the association between the prevalence of depressionterm, anxietyterm and combination of depressionterm and anxietyterm and SMEterm·var after controlling for covariatesterm. We estimated the adjusted ORsterm and their 95% confidence intervals (CIs)term of independent variables for frailty. The STATA version 13.0 programterm (StataCorp LP., College Station, TX, USA) was used to carry out all analyses. Resultsterm Social media exposureterm 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 SMEterm·var 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 areaterm. Most of them reported “excellent” (43.9%) or “very good” (45.6%) health. Univariate analyses found that the proportion of frequently SMEterm 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 SMEterm 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 SMEterm than who with high education (college and master). Participants who are students or retired had higher proportion of frequently SMEterm. The proportion of SMEterm·var was not different between participants from Hubei province and others, however, participants from rural areaterm reported higher proportion of frequently SMEterm than who from urban areaterm. Participants who were excellent health had higher proportion of frequently SMEterm than others. 10.1371/journal.pone.0231924.t001 Table 1 Participants characteristic and social media exposureterm. N(%) Social media exposureterm 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) Genderterm 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) Occupationterm 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) Areaterm 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) Depressionterm and SMEterm·var The prevalence of depressionterm was 48.3% (95%CI: 46.9%-49.7%). As shown Fig 1 , Multivariate analyses found that the adjusted odds of depressionterm 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 areaterm had lower adjusted odds (OR = 0.74, 95%CI: 0.64–0.87) than those from urban areaterm. The decrease of self-rated healthterm significantly accompanied the increased odds of depressionterm. About the focus of this studyterm, higher frequency of SMEterm was insignificantly positively associated with the adjusted odds of depressionterm after controlling for all covariatesterm. 10.1371/journal.pone.0231924.g001 Fig 1 Prevalence of depressionterm and relevant factors. Anxietyterm and SMEterm·var The prevalence of anxietyterm was 22.6% (95%CI: 21.4%-23.8%). As shown Fig 2 , Multivariate analyses found that that the adjusted odds of depressionterm 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 depressionterm 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 depressionterm 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 studyterm, frequently SMEterm can increase the adjusted odds (OR = 1.72, 95%CI: 1.31–2.26) of anxietyterm compared with less SMEterm after controlling for all covariatesterm. 10.1371/journal.pone.0231924.g002 Fig 2 Prevalence of anxietyterm and relevant factors. Combination of depressionterm and anxietyterm and SMEterm·var The prevalence of combination of depression and anxiety (CDA)term was 19.4% (95%CI: 18.3%-20.6%). As shown Fig 3 , Multivariate analyses found that that the adjusted odds of depressionterm 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 depressionterm among unmarried participants (OR = 0.79, 95%CI: 0.64–0.97) was lower than among married ones. The adjusted odds of depressionterm 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 studyterm, frequently SMEterm can increase the adjusted odds (OR = 1.91, 95%CI: 1.52–2.41) of CDA compared with less SEM after controlling for all covariatesterm. 10.1371/journal.pone.0231924.g003 Fig 3 Prevalence of combination of depressionterm and anxietyterm and relevant factors. Discussion The latest national sample indicated the prevalence of any disorder (excluding dementia), anxietyterm 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 studyterm found that much higher prevalence of depressionterm (48.3%, 95%CI: 46.9%-49.7%), anxietyterm (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 emergencyterm can cause public mental health problemsterm, such as Wenchuan and Lushan earthquakes[ 17 ], 2014 Ebola Outbreak[ 7 , 18 ], and SARS[ 19 ]. Social mediaterm is one of main channels updating the COVID-19 information[ 3 ]. This studyterm also found that 82.0% of participants frequently expose them to social mediaterm, and frequently SMEterm associated high odds of anxietyterm and CDA, which is consistent with previous studies [ 11 ]. there may be two reasons explaining the association between frequently SMEterm and mental health. During COVID-19 outbreak, disinformation and false reportsterm about the COVID-19 have bombarded social mediaterm and stoked unfounded fearsterm among many netizens[ 20 ], which may confuse people and harm people’s mental health[ 9 ]. Besides, many citizens expressed their negative feelingsterm, such as fear, worry, nervous, anxietyterm et al. on social mediaterm, which are contagious social network[ 21 , 22 ]. So, WHO’s ‘infodemics’ teamterm is working hand in glove with countries’ communications department to deliver information to a broader public audience[ 23 ]. Finally, we also found that SMEterm·var was not different between participants from Hubei province and others, but the formers faced higher odds of anxietyterm. It indicated that participants from Hubei province- the infectious focus directly expose to public health emergencyterm, 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 Wuhanterm is a very effective way to interrupt the transmission of the virusterm, however, the strictest measures in Wuhan might lead to more serious mental health problemsterm of local people. Some potential limitations should be noted in this studyterm. First, this is a cross-sectional studyterm, so it is difficult to accurately elucidate causal relationships between SMEterm·var and mental health. Additional longitudinal studiesterm, such as cohort studiesterm or nested case-control studiesterm, are essential in the future. Although large sample, the surveyterm·mth was conducted online, which is suitable for rapid assessmentterm, so some respondent biasterm, such as few elder citizens’ participationterm, may have affected the resultsterm. Finally, although we did control for many covariatesterm, we cannot exclude the possibility of some residual confoundingterm caused by unmeasured factorsterm. Conclusions In conclusion, our findings show there are high prevalence of mental health problemsterm, which positively associated with frequently SMEterm 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 servicesterm by varied channel including hotline, online consultation, online course and outpatient consultationterm[ 6 ], but more attention should be paid to depressionterm and anxietyterm. The next implication is to combat with “infodemic” by monitoring and filtering out false informationterm and promoting accurate informationterm though cross-section collaborationsterm. Supporting information S1 Table (DOCX) Click here for additional data file. S1 Data (XLS) Click here for additional data file.