LitCovid-sentences  

PMC:7143846 / 1804-19864 JSONTXT 12 Projects

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Id Subject Object Predicate Lexical cue
T13 0-2 Sentence denotes 1.
T14 3-15 Sentence denotes Introduction
T15 16-199 Sentence denotes COVID-19 (Corona Virus Disease 2019) is a highly infectious disease with a long incubation period which was caused by Sars-Cov-2 (Severe Acute Respiratory Syndrome Coronavirus 2) [1].
T16 200-337 Sentence denotes The number of COVID-19 patients increased dramatically due to hundreds of millions of people traveling during the Spring Festival period.
T17 338-547 Sentence denotes The severity of COVID-19 had been underestimated until the National Health Commission classified it as a B type infectious disease officially and took actions to fight against this disease on 20 January, 2020.
T18 548-696 Sentence denotes Ever since then, epidemic prevention was comprehensively upgraded and marked the real beginning of universal concern, indicating widespread impacts.
T19 697-905 Sentence denotes The uncertainty and low predictability of COVID-19 not only threaten people’s physical health, but also affect people’s mental health, especially in terms of emotions and cognition, as many theories indicate.
T20 906-1107 Sentence denotes According to Behavioral Immune System (BIS) theory [2], people are likely to develop negative emotions (e.g., aversion, anxiety, etc.) [3,4] and negative cognitive assessment [5,6] for self-protection.
T21 1108-1312 Sentence denotes Faced with potential disease threat, people tend to develop avoidant behaviors (e.g., avoid contact with people who have pneumonia-like symptoms) [7] and obey social norms strictly (e.g., conformity) [8].
T22 1313-1473 Sentence denotes According to stress theory [9] and perceived risk theory [10], public health emergencies trigger more negative emotions and affect cognitive assessment as well.
T23 1474-1570 Sentence denotes These negative emotions keep people away from potential pathogens when it refers to the disease.
T24 1571-1719 Sentence denotes However, long-term negative emotions may reduce the immune function of people and destroy the balance of their normal physiological mechanisms [11].
T25 1720-1903 Sentence denotes Meanwhile, individuals may overreact to any disease in case of less appropriate guidance from authorities, which may result in excessively avoidant behaviors and blind conformity [8].
T26 1904-2019 Sentence denotes Therefore, it is essential to understand the potential psychological changes caused by COVID-19 in a timely manner.
T27 2020-2334 Sentence denotes Since psychological changes caused by public health emergencies can be reflected directly in emotions and cognition [3,4,5,6], we can monitor psychological changes in time through emotional (e.g., negative emotions and positive emotions) and cognitive indicators (e.g., social risk judgment and life satisfaction).
T28 2335-2580 Sentence denotes The emotions and cognition are usually measured by retrospective questionnaires, such as Oxford Happiness Inventory (OHI) [12], Symptom Checklist 90 (SCL-90) [13], Satisfaction with Life Scale (SWLS) [14], and Likert Type Attitude Scale [15,16].
T29 2581-2877 Sentence denotes However, at the time of the COVID-19 outbreak in China, it was very difficult to conduct a traditional paper survey in the affected areas; online surveys rely on the cooperation of participants, and it is difficult to meet the requirements in time, and even brings extra burdens for participants.
T30 2878-3030 Sentence denotes Since we did not know the time of COVID-19 declaration, it was impossible to measure people’s emotions and cognition by a traditional survey in advance.
T31 3031-3134 Sentence denotes There may be a certain deviation when requiring people to recall their mental state a week or more ago.
T32 3135-3269 Sentence denotes Weibo data is emerging as a key online medium and data source for researchers to understand this social problem in a non-invasive way.
T33 3270-3385 Sentence denotes Sina Weibo is a leading Chinese Online Social Networks (OSN) with more than 462 million active daily users in 2019.
T34 3386-3504 Sentence denotes These users use Weibo functions (e.g., reply, @function) to interact with each other, forming rich user behavior data.
T35 3505-3810 Sentence denotes The aim of this study is to explore the impacts of public health emergency COVID-19 on people’s mental health, to assist policy makers to develop actionable policies, and help clinical practitioners (e.g., social workers, psychiatrists, and psychologists) provide services to affected populations in time.
T36 3812-3814 Sentence denotes 2.
T37 3815-3836 Sentence denotes Materials and Methods
T38 3838-3842 Sentence denotes 2.1.
T39 3843-3875 Sentence denotes Participants and Data Collection
T40 3876-3946 Sentence denotes The samples in this study were from the original Weibo data pool [17].
T41 3947-4013 Sentence denotes The data pool contained more than 1.16 million active Weibo users.
T42 4014-4147 Sentence denotes Weibo is a popular platform to share and discuss individual information and life activities, as well as celebrity news in China [18].
T43 4148-4254 Sentence denotes The retrieved data included (1) user’s profile information, (2) network behaviors, and (3) Weibo messages.
T44 4255-4349 Sentence denotes Privacy was strictly protected during the procedure, referring to the ethical principles [19].
T45 4350-4429 Sentence denotes We have obtained the Ethical Committee’s approval and the ethic code is H15009.
T46 4430-4525 Sentence denotes The following inclusion criteria were employed to select active Weibo users from the data pool.
T47 4526-4652 Sentence denotes First, they had published at least 50 original Weibo posts around a month in total from 31 December, 2019 to 26 January, 2020.
T48 4653-4738 Sentence denotes Second, their authentication type is non-institutional (e.g., individual user, etc.).
T49 4739-4815 Sentence denotes Third, their regional authentication is in China, not “overseas” or “other”.
T50 4816-4997 Sentence denotes We acquired 17,865 active Weibo users finally, then fetched all their original posts published during 13 January, 2020 to 26 January, 2020 into the two-week period for the analysis.
T51 4999-5003 Sentence denotes 2.2.
T52 5004-5054 Sentence denotes Measurement of Psychological Traits and Procedures
T53 5055-5308 Sentence denotes In this study, we used Online Ecological Recognition (OER) [20], which referred to the automatic recognition of psychological profile (e.g., anxiety, well-being, etc.) by using predictive models [17,20,21] based on ecological behavioral data from Weibo.
T54 5309-5573 Sentence denotes We employed Text Mind system developed by the Computational Cyber Psychology Laboratory at the Institute of Psychology, Chinese Academy of Sciences to extract content features [22], including Chinese word segmentation tool [17], and psychoanalytic dictionary [23].
T55 5574-5904 Sentence denotes We used the Chinese word segmentation tool to divide users’ original microblog content into words/phrases with linguistic annotations, such as verbs, nouns, adverbials, and objects [24], and then extracted psychologically meaningful categories through the simplified Chinese LIWC (Language Inquiry and Word Count) dictionary [23].
T56 5905-5974 Sentence denotes These lexical features were data sources for word frequency analysis.
T57 5975-6153 Sentence denotes After feature extraction, we used the psychological prediction model [25] obtained from the preliminary training to predict the psychological profile of these active Weibo users.
T58 6154-6445 Sentence denotes These predictive models are tools developed for online psychology research based on big data and deep learning technologies, including emotional indicators (anxiety, depression, indignation, and Oxford happiness), cognitive indicators (social risk judgment and life satisfaction), and so on.
T59 6446-6540 Sentence denotes Figure 1 portrays the procedure from feature extraction to psychological indicator prediction.
T60 6541-6629 Sentence denotes All the prediction models have reached a moderate correlation with questionnaire scores.
T61 6630-6711 Sentence denotes The feasibility of predictive models has been repeatedly demonstrated [26,27,28].
T62 6712-6977 Sentence denotes We calculated word frequency, scores of negative emotional indicators (i.e., anxiety, depression, and indignation), positive emotional indicators (i.e., Oxford happiness), and cognitive indicators (i.e., social risk and life satisfaction) of the collected messages.
T63 6978-7303 Sentence denotes We then compared the differences of psychological characteristics before and after the declaration of outbreak of COVID-19 on 20 January, 2020 through the paired sample t-test by using SPSS (Statistical Product and Service Solutions) 22, which is published by IBM (International Business Machines Corporation), New York, USA.
T64 7305-7307 Sentence denotes 3.
T65 7308-7315 Sentence denotes Results
T66 7317-7321 Sentence denotes 3.1.
T67 7322-7334 Sentence denotes Demographics
T68 7335-7470 Sentence denotes Among 17,865 active Weibo users, 25.23% were males and 77.95% were from Eastern China, which is considered the richest region in China.
T69 7471-7611 Sentence denotes Ages of users who registered their birth date in their profile (n = 4156, 23.26%) ranged from 8 to 56 years with the median age of 33 years.
T70 7612-7659 Sentence denotes The demographic profile is depicted in Table 1.
T71 7661-7665 Sentence denotes 3.2.
T72 7666-7687 Sentence denotes Linguistic Difference
T73 7688-7818 Sentence denotes In this study, we compare the LIWC categories between the week before (T-before) and after (T-after) 20 January, shown in Table 2.
T74 7819-7901 Sentence denotes It contains two types of LIWC categories: words of emotions and words of concerns.
T75 7902-8115 Sentence denotes Words of emotions include positive emotion (e.g., faith, contentment, and blessing), negative emotion (e.g., worry, suspicion, and jealousy), anxiety (e.g., upset, nervous, and crazy), and anger (e.g., complaint).
T76 8116-8494 Sentence denotes Words of concerns include health (e.g., insomnia, doctor, and exercise), leisure (e.g., cooking, chatting, and movies), family (e.g., family and house), friend (e.g., companion and guest), money (e.g., bills, cash, and borrowing), death (e.g., burial, killing, and funeral), and religion (e.g., church, mosque, and temple), which can reflect what people are paying attention to.
T77 8495-8696 Sentence denotes After 20 January, the number of words increased in positive emotion (t (17,747) = −24.411, p < 0.001), negative emotion (t (17,747) = −15.273, p < 0.001), and anxiety (t (17,747) = −15.294, p < 0.001).
T78 8697-9046 Sentence denotes Word frequency significantly increased in the category “concerns,” including health (t (17,747) = −72.392, p < 0.05), family (t (17,747) = −12.571, p < 0.001), death (t (17,747) = −6.707, p < 0.001), and religion (t (17,747) = −13.816, p < 0.001), but decreased in leisure (t (17,747) = 21.963, p < 0.001) and friend (t (17,747) = 6.202, p < 0.001).
T79 9048-9052 Sentence denotes 3.3.
T80 9053-9073 Sentence denotes Emotional Indicators
T81 9074-9233 Sentence denotes Results indicate significant differences of emotional indicators between T-before (13–19 January, 2020) and T-after (20–26 January, 2020), as shown in Table 3.
T82 9234-9578 Sentence denotes After 20 January, negative emotional indicators of psychological traits increased in anxiety (t (17,747) = −35.962, p < 0.001), depression (t (17,747) = −10.717, p < 0.001), and indignation (t (17,747) = 5.500, p < 0.001), while positive emotional indicators of psychological traits decreased in Oxford happiness (t (17,747) = 3.120, p < 0.01).
T83 9580-9584 Sentence denotes 3.4.
T84 9585-9605 Sentence denotes Cognitive Indicators
T85 9606-9757 Sentence denotes We found significant differences in cognitive indicators between T-before (13–19 January, 2020) and T-after (20–26 January, 2020), as shown in Table 4.
T86 9758-9955 Sentence denotes After 20 January, cognitive indicators of psychological traits increased in social risk judgement (t (17,747) = 3.120, p < 0.01), but decreased in life satisfaction (t (17,747) = 5.500, p < 0.001).
T87 9957-9959 Sentence denotes 4.
T88 9960-9970 Sentence denotes Discussion
T89 9971-10139 Sentence denotes Since the National Health Commission identified COVID-19 as a B type infectious disease officially, COVID-19 influenced the psychological states of people across China.
T90 10140-10247 Sentence denotes This study collected active Weibo users’ data, and conducted sentiment analysis during 13–26 January, 2020.
T91 10248-10403 Sentence denotes We used OER to acquire the psychological states, and found that Weibo users’ psychological conditions significantly changed under the outbreak of COVID-19.
T92 10404-10499 Sentence denotes The findings showed that people’s concerns by linguistic expression increased after January 20.
T93 10500-10584 Sentence denotes We observe an increase in health and family, while a decrease in leisure and friend.
T94 10585-10838 Sentence denotes Uncertainty of the upcoming situation causes cognitive dissonance and insecurity; this produces a feeling of mental discomfort, leading to Weibo’s activity oriented toward dissonance reduction and keeping security on health and family relationship [29].
T95 10839-10967 Sentence denotes According to the theory of BIS, people behave in a more reticent and conservative way when they feel threatened by disease [30].
T96 10968-11087 Sentence denotes Therefore, staying at home with family and reducing recreational activities seems to be a safer way to prevent illness.
T97 11088-11446 Sentence denotes It also indicated that people begin to care more about their health and were more likely to seek social support from their families rather than getting together with friends, which suggested that people’ interests and attention were influenced by the restricted travel policy and self-isolation regulations from the health authorities and central government.
T98 11447-11540 Sentence denotes Affected by COVID-19, messages related to death and religion became salient after 20 January.
T99 11541-11601 Sentence denotes Reports showed severity and potential mortality of COVID-19.
T100 11602-11782 Sentence denotes Research confirmed that people tended to respond to emergencies such as stress or death in the way of religion, which can comfort tense moods and bring more positive emotions [31].
T101 11783-11940 Sentence denotes That is why people prayed for the county through religion or other beliefs, leading to the phrase that appeared most frequently on the Internet at that time:
T102 11941-11957 Sentence denotes God bless China.
T103 11958-12232 Sentence denotes People showed more negative emotions (anxiety, depression, and indignation) and less positive emotions (Oxford happiness) after the declaration of COVID-19, which was supported by the theory of BIS, i.e., people did generate more negative emotions for self-protection [3,4].
T104 12233-12468 Sentence denotes These results are consistent to previous studies as well, which found that public health emergencies (e.g., SARS) triggered a series of stress emotional response containing a higher level of anxiety and other negative emotions [32,33].
T105 12469-12804 Sentence denotes Meanwhile, the confirmation that COVID-19 could be passed from person to person on 20 January, which was inconsistent with previous reports, lead to quite a number of people being unsatisfied with misinformation published from provincial governments (e.g., Hubei) and ineffective regulatory actions, causing an increase in indignation.
T106 12805-12960 Sentence denotes However, it’s worth noting that the word frequency of positive emotions increased after 20 January, which seemed to be inconsistent with the theory of BIS.
T107 12961-13137 Sentence denotes In fact, positive emotion includes words such as faith and blessing, which are more inclined to reflect group cohesiveness rather than pure personal emotions (e.g., happiness).
T108 13138-13370 Sentence denotes Researchers found that group threats (e.g., natural disasters and epidemic diseases) made groups a community of interests, resulting in more beneficial behaviors and social solidarity, which indicated higher group cohesiveness [34].
T109 13371-13535 Sentence denotes For example, lots of provinces (e.g., Sichuan Province, Shandong Province, etc.) formed medical teams to help the Hubei province, which was the worst affected area.
T110 13536-13629 Sentence denotes Many people donated money and supplies to Hubei Red Cross to support the control of COVID-19.
T111 13630-13742 Sentence denotes Furthermore, social risk judgement was higher and life satisfaction was lower after the declaration of COVID-19.
T112 13743-14103 Sentence denotes It is consistent with the theory of BIS, which found that when social uncertainty increased, such as unknown etiology and ambiguous route of transmission, people developed the negative cognitive assessment (e.g., higher sensitivity of risk judgment or risk perception) so that they could discover potential infection sources in time and avoid infection [2,35].
T113 14104-14272 Sentence denotes Not only that, people’s fear of potential risk and lack of controllability caused by COVID-19 brought about higher risk judgement as perceived risk theory claimed [10].
T114 14273-14444 Sentence denotes Moreover, some preventive policies and regulations in terms of travel restriction and self-isolation made the quality of life worse, reflecting in lower life satisfaction.
T115 14445-14646 Sentence denotes The following briefly foregrounds some of the study’s implications for policy makers and clinical practitioners (e.g., social workers, psychiatrists, and psychologists) plan and fight against COVID-19.
T116 14647-14817 Sentence denotes For policy makers: (1) develop a consistent policy and procedure for reporting the latest confirmed cases, recent death toll, and other data about the epidemic situation.
T117 14818-14978 Sentence denotes For example, the surge of cases on February 12th did not mean that the situation has been out of control, but because of the new diagnostic criteria introduced.
T118 14979-15228 Sentence denotes It is important to let people understand the data properly to reduce excessive stress responses (e.g., anxiety, depression, etc.) brought on by inappropriate perception. (2) Expand public awareness of continuous progress in decision-making measures.
T119 15229-15479 Sentence denotes Since indignation may come mainly from mistakes and deficiencies in preventing and controlling the epidemic, it can effectively decrease indignation if public awareness and involvement are provided. (3) Ensure the supply of medical treatment service.
T120 15480-15593 Sentence denotes It is critical to set up medical service to treat the disease, and let people know how to access it conveniently.
T121 15594-15643 Sentence denotes People can get help in time if they are infected.
T122 15644-15828 Sentence denotes It can improve people’s sense of control over risks, thereby avoiding excessive social risk perception. (4) Provide more in-door entertainment services to address good quality of life.
T123 15829-15972 Sentence denotes People may be more willing to cooperate when their living and entertainment requirements are met, such as online shopping, entertainments, etc.
T124 15973-16078 Sentence denotes For clinical practitioners: (1) adjust consultant configuration rationally and cooperate with each other.
T125 16079-16206 Sentence denotes Psychological consultants should grasp the epidemic information correctly and conduct science popularization during counseling.
T126 16207-16264 Sentence denotes Social workers can help solve practical problems in life.
T127 16265-16409 Sentence denotes These actions can improve the sense of stability and relieve anxiety and depression. (2) Deliver necessary psychosocial therapy in various ways.
T128 16410-16539 Sentence denotes Considering the particularity of self-isolation, relevant hotline counseling and online consulting should be applied in practice.
T129 16540-16622 Sentence denotes Several other points should be considered when generalizing this study’s findings.
T130 16623-16711 Sentence denotes First, as Weibo users are mainly young people, the results may be biased to some extent.
T131 16712-16912 Sentence denotes In addition, the current analysis is based on a weekly basis, with a relatively large granularity, which has certain influences on reflecting the changing trend of social mentality in a timely manner.
T132 16913-17036 Sentence denotes In further studies, we will try to expand the range of sex and age and predict psychological traits in a finer granularity.
T133 17037-17194 Sentence denotes Previous studies indicated that people tended to exaggerate attitudes and prejudices, especially when they felt more vulnerable to disease transmission [36].
T134 17195-17418 Sentence denotes It inspires us to try to build a prediction model which can predict people’s attitudes and beliefs against the virus through online Weibo data for further understanding of psychological impacts of public health emergencies.
T135 17420-17422 Sentence denotes 5.
T136 17423-17434 Sentence denotes Conclusions
T137 17435-17561 Sentence denotes In this study, we compared the difference before and after 20 January on both linguistic categories and psychological profile.
T138 17562-17799 Sentence denotes We found an increase in negative emotions (anxiety, depression, and indignation) and sensitivity to social risks, as well as a decrease in positive emotions (Oxford happiness) and life satisfaction after declaration of COVID-19 in China.
T139 17800-17902 Sentence denotes What’s more, people show more concern for health and family, and less concern for leisure and friends.
T140 17903-18060 Sentence denotes Using social media data may provide timely understanding of the impact of public health emergencies on the public’s mental health during the epidemic period.