What triggers online help-seeking retransmission during the COVID-19 period? Empirical evidence from Chinese social media

Coping with Unknown Health Crisis via Social Media: A Content Analysis of Online Mutual Aid Group in the Beginning of the COVID-19 Pandemic

OBJECTIVE

The initial emergence of SARS-CoV-2 created uncertainty for humanity, driving people to seek assistance on social media. This study aims to understand the role of social media in coping with crises and to offer guidance for future uncertainties by examining the experiences of Wuhan during the early stages of the pandemic.

METHODS

Using quantitative content analysis, this study investigated 2207 Weibo posts tagged with "COVID-19 Mutual Aid" from individuals located in Wuhan during the early lockdown period from January 23, 2020, to March 23, 2020.

RESULTS

At the start of pandemic, messages seeking tangible support were most common. A hurdle regression model showed that deeper self-disclosure led to more retransmission of help-seeking messages. The Chi-Square and Mann-Whitney U tests revealed that health professionals and laypeople had different self-disclosure strategies.

CONCLUSIONS

This study provides insight into the online social support exchange during the early stages of the COVID-19 pandemic in Wuhan, highlighting the importance of self-disclosure on message retransmission, and the differences in self-disclosure strategies between health professionals and laypeople in online help-seeking.

Help-Seeking Preferences and Influencing Factors Among Chinese Nurses Exposed to COVID-19: A Person-Centered Approach

PURPOSE

This study aimed to explore help-seeking preference categories and crucial influencing factors among community nurses exposed to COVID-19 in China using a new person-centered approach.

DESIGN

A cross-sectional design including an online self-reported questionnaire survey was used.

METHODS

A total of 667 nurses who participated in COVID-19 prevention and control work were recruited. Latent class analysis and logistic regression were used to analyze the data using Mplus and SPSS.

FINDINGS

Two latent classes of help-seeking preferences were identified: high help-seeking preferences (33.58%) and low help-seeking preferences (66.42%). Most sampled nurses had relatively low help-seeking preferences when facing psychological threats during COVID-19. Logistic regression showed that career duration, perceived social support, online help-seeking intention, and social media exposure negatively affected low help-seeking preferences.

CONCLUSIONS

Career duration, perceived social support, online help-seeking intention, and social media exposure could be key factors influencing help-seeking preferences among Chinese nurses exposed to public emergencies. It is necessary to implement relevant intervention measures, such as focusing on nurses whose career durations are shorter, improving nurses' perceived social support, strengthening positive media publicity, and developing comprehensive online mental health services that promote nurses' help-seeking preferences and behaviors to reduce mental illness during public health emergencies.

CLINICAL EVIDENCE

Help-seeking preferences are relatively low among Chinese nurses during public emergencies. Based on the major influencing factors of help-seeking preferences, including social support and social media exposure, more interventions must be developed for prompting psychological help-seeking intentions among Chinese nurses.

Low-Cost Recruitment Approach: Utilizing Facebook Groups to Recruit COVID-19 Long-Haulers

Introduction

The accessibility of social media (e.g., Facebook groups) presents long-haulers with the ability to connect with others with similar experiences and symptomology that are likely outside of their physical social networks. Social media sites may serve as promising platforms for research recruitment, public health campaigns, or interventions. The present study aims to assess, and comprehensively present, the effectiveness of a low-cost approach to recruitment through groups on Facebook within the context of a broader study of COVID-19 long-haulers.

Methods

Facebook groups were searched using a variety of COVID-related terminology and included if they were in English, COVID-19 specific, public, and have or were approaching 1,000 or more members. Group administrators were either contacted for permission to post recruitment materials or posts were made and left pending administrator approval, depending on group settings. Group members were able to follow a link to the online survey platform (i.e., RedCap) where they provided informed consent and completed an online assessment of their COVID-19 experiences and psychosocial wellbeing. Upon survey completion participants were able to opt-in to a raffle-based incentive. The characteristics of the Facebook groups and demographic background of participants were assessed.

Findings

Contacting administrators and posts made between January and March of 2022 within 17 COVID-19 specific groups yielded a sample size of 460 long-haulers. The groups relied upon for recruitment had a mean size of 21,022 (SD=45,645.3), most had three or more administrators (43%), and a majority were state specific (60%). The long-hauler participants enrolled from the posts had an average age of 32 years (SD=6.19), approximately split between men (48.91%) and women (50.22%), a majority white (70%), having earned a bachelor's or postgraduate degree (63.48%), and reporting an annual income between $50,000 and $100,000 (56.09%).

Discussion

The present study presents strengths and recommendations for survey recruitment through Facebook groups as a low-cost recruitment strategy that is easily targeted to populations with a specific health condition and allows users to complete online psycho-behavioral assessments off-site on a HIPPA compliant survey platform.

A multidimensional comparative study of help-seeking messages on Weibo under different stages of COVID-19 pandemic in China

Objective

During the COVID-19 pandemic, people posted help-seeking messages on Weibo, a mainstream social media in China, to solve practical problems. As viruses, policies, and perceptions have all changed, help-seeking behavior on Weibo has been shown to evolve in this paper.

Methods

We compare and analyze the help-seeking messages from three dimensions: content categories, time distribution, and retweeting influencing factors. First, we crawled the help-seeking messages from Weibo, and successively used CNN and xlm-roberta-large models for text classification to analyze the changes of help-seeking messages in different stages from the content categories dimension. Subsequently, we studied the time distribution of help-seeking messages and calculated the time lag using TLCC algorithm. Finally, we analyze the changes of the retweeting influencing factors of help-seeking messages in different stages by negative binomial regression.

Results

(1) Help-seekers in different periods have different emphasis on content. (2) There is a significant correlation between new daily help-seeking messages and new confirmed cases in the middle stage (1/1/2022-5/20/2022), with a 16-day time lag, but there is no correlation in the latter stage (12/10/2022-2/25/2023). (3) In all the periods, pictures or videos, and the length of the text have a significant positive effect on the number of retweets of help-seeking messages, but other factors do not have exactly the same effect on the retweeting volume.

Conclusion

This paper demonstrates the evolution of help-seeking messages during different stages of the COVID-19 pandemic in three dimensions: content categories, time distribution, and retweeting influencing factors, which are worthy of reference for decision-makers and help-seekers, as well as provide thinking for subsequent studies.

Information interaction and social support: exploring help-seeking in online communities during public health emergencies

BACKGROUND

During public health emergencies, online community users can obtain social support and assistance through information interaction in the online community. This study takes the COVID-19 pandemic as the context and aims to analyze the influence of user information interaction in online communities on the acquisition of social support during this public health emergency.

METHODS

Data collected from help-seeking posts in the "COVID-19 Patients Help-Seeking Dialog" subforum on China's Sina Weibo were used as the research sample. The influence of the frequency of interaction and responsiveness on help seekers' receipt of online social support was analyzed, and the moderating effect of help seekers' identity type and intensity of online community use was explored.

RESULTS

The results reveal that the frequency of interaction positively impacts informational support (β = 0.367, p < 0.001) and negatively impacts emotional support (β=-0.240, p < 0.001), and the responsiveness of other users toward help-seeking posts positively impacts emotional support (β = 0.145, p < 0.01). Moreover, help seeker's identity type and intensity of online community use significantly moderate the relationship between the frequency of interaction and the emotional support obtained by the help seeker.

CONCLUSIONS

The study highlights the impact of user information interaction on obtaining help-seeking information from online communities for social support. The initiative would facilitate the resolution of issues related to users' information help-seeking during public health emergencies.

"Help Us!": a content analysis of COVID-19 help-seeking posts on Weibo during the first lockdown

BACKGROUND

Social media is playing an increasingly important role in public emergencies for help-seekers, especially during the global COVID-19 pandemic. Wuhan, China, firstly official reported COVID-19 cases and implemented lockdown measures to prevent the spread of the virus. People during the first lockdown were restricted from seeking help face-to-face. Social media is more prominent as an online tool for people seeking help, especially for patients, than in other stages of the COVID-19 pandemic.

OBJECTIVE

This study aimed to explore the urgent needs presented in help-seeking posts in Wuhan during the first COVID-19 lockdown, the content features of these posts, and how they influenced online user engagement.

METHODS

This study collected posts from Weibo posted with specific help tags during the first COVID-19 lockdown in Wuhan: from 23 January 2020 to 24 March 2020, and eventually received 2055 data, including textual content, comments, retweets, and publishing location. Content analysis was conducted, and manual coding was performed on help-seeking typology, narrative mode, narrative subject, and emotional valence.

RESULTS

The result showed that help-seeking posts primarily were seeking medical (97.7%). Features of these posts were mainly adopting a mixed narrative mode (46.4%), released by relatives of patients (61.7%), and expressing negative emotions (93.2%). Chi-square tests suggested that help-seeking posts with mixed narrative modes released by relatives express more frequent negative emotions. Results of negative binomial regression indicated posts of seeking information (B = 0.52, p < .001, e0.52 = 1.68), with mixed narrative mode (B = 0.63, p < .001, e0.63 = 1.86), released by themselves (as referential groups) and with neutral emotions increased comments. Posts of seeking medical (B = 0.57, p < .01, e0.57 = 1.77), with mixed narrative mode (B = 1.88, p < .001, e1.88 = 6.53), released by people of unrelated patients (B = 0.47, p < .001, e0.47 = 1.60) and with neutral emotions increased retweets.

CONCLUSIONS

This study provides evidence of what actual public demands are to be considered and addressed by governments and public administrators before implementing closure and lockdown policies to limit the spread of the virus. Meanwhile, our findings offer strategies for people help-seeking on social media in similar public health emergencies.

How did Chinese public health authorities promote COVID-19 vaccination on social media? A content analysis of the vaccination promotion posts

Objective

Drawing upon the health belief model, this study aims to analyze the message characteristics of coronavirus disease 2019 (COVID-19) vaccination promotion messages posted by influential Chinese public health institutions and how those characteristics affect audiences' participative engagement on Weibo, which is a popular social media site in China.

Methods

Two Chinese phrases for the COVID-19 vaccine were adopted as search terms to retrieve qualified posts on Weibo from 1 December 2019 to 18 March 2023. A total of 2546 posts by the top nine most impactful public health institutions were retained for quantitative content analysis. Message characteristics derived from the health belief model and participative engagement indicators were coded by the authors.

Results

Among health belief model constructs, the collective-oriented constructs (i.e., benefits, cues to action, and susceptibility) appeared in almost half of the posts, while the individual-oriented constructs (i.e., barriers, self-efficacy, and severity) were mentioned less. Moreover, negative binomial regression models revealed that collective-oriented constructs and self-efficacy facilitated engagement, while other constructs played impeding roles.

Conclusions

Appearances and functions of the health belief model's constructs in the COVID-19 vaccination promotion context are closely associated with China's collectivistic culture. Furthermore, constructs conforming to people's psychological traits are likely to promote public engagement and may facilitate vaccination behavior.

Patterns and predictors of adolescent life change during the COVID-19 pandemic: a person-centered approach

The present study investigated patterns of adolescent life changes across multiple life domains and utilized a holistic-interactionistic perspective to examine their individual, familial, and societal correlates with a sample of 2544 Chinese parent-adolescent dyads. Adolescents were aged from 10 to 19 years old (50.16% girls). Latent profile analysis revealed five life change profiles, including three improved profiles at various degrees, one unchanged profile, and one worsened profile. The majority of adolescents had an improved or unchanged life. Multinomial logistic regression analyses found that most of the individual, familial, and societal factors predicted the group memberships. Notably, parent-adolescent conflict was a significant factor that predicted memberships of all patterns. These findings show the resilience of adolescents and indicate the need for policies and interventions that consider the holistic nature of adolescents' person-context system, especially during a global crisis such as the COVID-19 pandemic.

What We Ask about When We Ask about Quarantine? Content and Sentiment Analysis on Online Help-Seeking Posts during COVID-19 on a Q&A Platform in China

The COVID-19 outbreak, a recent major public health emergency, was the first national health crisis since China entered the era of mobile social media. In this context, the public posted many quarantine-related posts for help on social media. Most previous studies of social media during the pandemic focused only on people's emotional needs, with less analysis of quarantine help-seeking content. Based on this situation, this study analyzed the relationship between the number of quarantine help-seeking posts and the number of new diagnoses at different time points in the pandemic using Zhihu, the most comprehensive topic discussion platform in China. It showed a positive correlation between the number of help-seeking posts and the pandemic's severity. Given the diversity of people's help-seeking content, this study used topic model analysis and sentiment analysis to explore the key content of people's quarantine help-seeking posts during the pandemic. In light of the framework of uses and gratifications, we found that people posted the most questions in relation to help with information related to pandemic information and quarantine information. Interestingly, the study also found that the content of people's quarantine posts during the pandemic was primarily negative in sentiment. This study can thus help the community understand the changes in people's perceptions, attitudes, and concerns through their reactions to emergencies and then formulate relevant countermeasures to address pandemic control and information regulation, which will have implications for future responses to public health emergencies. Moreover, in terms of psychological aspects, it will help implement future mental health intervention strategies and better address the public's psychological problems.

Topical and emotional expressions regarding extreme weather disasters on social media: a comparison of posts from official media and the public

Understanding media frames and the public resonance during disasters is essential for making inclusive climate change and adaptation policies in the context of increasingly extreme weather events. In this study, we use the extreme weather and flood event that occurred in July 2021 in Zhengzhou, China, as a case study to investigate how official media in China reported this event and how the public responded. Moreover, since one accountability investigation report regarding this disaster was released in January 2022, we also compared these posts between the emergency response period and the post-crisis learning period after the report's release. Topic modeling using the LDA (Latent Dirichlet Allocation) method and emotion analysis were conducted to analyze the posts from Weibo, China's primary social media platform. The results demonstrated that the posts from official media and the public comments differed in both topics and emotions, with relatively little coherence. During the emergency response period, the media's posts focused more on the facts, such as the extreme weather event, the places where it occurred, the impacts, and the search and rescue efforts, while the public comments were more about help appeals from the neglected ones in the rural areas, and emotional expressions such as moral support, condolence or encouragement to the victims and their families. After the accountability investigation in January, the media's posts primarily covered the investigation process, the punishment, the attribution of disaster consequences, and the lessons learned, while the public's comments were relatively emotional, praised the good, condoled the victims, and condemned the villains. The dominant emotion from the media's posts was "like" in July 2021, but it became depression in January 2022. Anger was the prevalent emotion from the public during all the stages. This study provided valuable knowledge to the current understanding of the different patterns and dynamics of official media reports and the public's resonance in disaster management.

Can people hear others' crying?: A computational analysis of help-seeking on Weibo during COVID-19 outbreak in China

Social media like Weibo has become an important platform for people to ask for help during COVID-19 pandemic. Using a complete dataset of help-seeking posts on Weibo during the COVID-19 outbreak in China (N = 3,705,188), this study mapped their characteristics and analyzed their relationship with the epidemic development at the aggregate level, and examined the influential factors to determine whether and the extent the help-seeking crying could be heard at the individual level using computational methods for the first time. It finds that the number of help-seeking posts on Weibo has a Granger causality relationship with the number of confirmed COVID-19 cases with a time lag of eight days. This study then proposes a 3C framework to examine the direct influence of content, context, and connection on the responses (measured by retweets and comments) and assistance that help-seekers might receive as well as their indirect effects on assistance through the mediation of both retweets and comments. The differential influences of content (theme and negative sentiment), context (Super topic community, spatial location of posting, and the period of sending time), and connection (the number of followers, whether mentioning others, and verified status of authors and sharers) have been reported and discussed.

Understanding the Association between Online Social Support Obtainment and Coping during a Public Crisis

This study aims to examine how the process of online support obtainment may affect cognitive and behavioral coping during a public crisis. A cross-sectional online survey (N = 555) was conducted during the early stage of the COVID-19 pandemic in the U.S. Our findings revealed that informational support, obtained primarily through passive and private online involvement, led to increased risk perceptions of COVID-19; emotional support, obtained mainly via private online involvement, appeared to elicit higher perceived efficacy to cope with the crisis. People's engagement in preventive behaviors was found to be affected by efficacy perceptions, but not by risk perceptions. The results suggested that online social support functioned as a double-edged sword to affect people's coping with a public crisis.

Prediction of Online Psychological Help-Seeking Behavior During the COVID-19 Pandemic: An Interpretable Machine Learning Method

Online mental health service (OMHS) has been named as the best psychological assistance measure during the COVID-19 pandemic. An interpretable, accurate, and early prediction for the demand of OMHS is crucial to local governments and organizations which need to allocate and make the decision in mental health resources. The present study aimed to investigate the influence of the COVID-19 pandemic on the online psychological help-seeking (OPHS) behavior in the OMHS, then propose a machine learning model to predict and interpret the OPHS number in advance. The data was crawled from two Chinese OMHS platforms. Linguistic inquiry and word count (LIWC), neural embedding-based topic modeling, and time series analysis were utilized to build time series feature sets with lagging one, three, seven, and 14 days. Correlation analysis was used to examine the impact of COVID-19 on OPHS behaviors across different OMHS platforms. Machine learning algorithms and Shapley additive explanation (SHAP) were used to build the prediction. The result showed that the massive growth of OPHS behavior during the COVID-19 pandemic was a common phenomenon. The predictive model based on random forest (RF) and feature sets containing temporal features of the OPHS number, mental health topics, LIWC, and COVID-19 cases achieved the best performance. Temporal features of the OPHS number showed the biggest positive and negative predictive power. The topic features had incremental effects on performance of the prediction across different lag days and were more suitable for OPHS prediction compared to the LIWC features. The interpretable model showed that the increase in the OPHS behaviors was impacted by the cumulative confirmed cases and cumulative deaths, while it was not sensitive in the new confirmed cases or new deaths. The present study was the first to predict the demand for OMHS using machine learning during the COVID-19 pandemic. This study suggests an interpretable machine learning method that can facilitate quick, early, and interpretable prediction of the OPHS behavior and to support the operational decision-making; it also demonstrated the power of utilizing the OMHS platforms as an always-on data source to obtain a high-resolution timeline and real-time prediction of the psychological response of the online public.

What makes an online help-seeking message go far during the COVID-19 crisis in mainland China? A multilevel regression analysis

Various studies have explored the underlying mechanisms that enhance the overall reach of a support-seeking message on social media networks. However, little attention has been paid to an under-examined structural feature of help-seeking message diffusion, information diffusion depth, and how support-seeking messages can traverse vertically into social media networks to reach other users who are not directly connected to the help-seeker. Using the multilevel regression to analyze 705 help-seeking posts regarding COVID-19 on Sina Weibo, we examined sender, content, and environmental factors to investigate what makes help-seeking messages traverse deeply into social media networks. Results suggested that bandwagon cues, anger, instrumental appeal, and intermediate self-disclosure facilitate the diffusion depth of help-seeking messages. However, the effects of these factors were moderated by the epidemic severity. Implications of the findings on support-seeking behavior and narrative strategies on social media were also discussed.

Exploring public perceptions of the COVID-19 vaccine online from a cultural perspective: Semantic network analysis of two social media platforms in the United States and China

The development and uptake of the COVID-19 (coronavirus disease 2019) vaccine is a top priority in stifling the COVID-19 pandemic. How the public perceives the COVID-19 vaccine is directly associated with vaccine compliance and vaccination coverage. This study takes a cultural sensitivity perspective and adopts two well-known social media platforms in the United States (Twitter) and China (Weibo) to conduct a public perception comparison around the COVID-19 vaccine. By implementing semantic network analysis, results demonstrate that the two countries' social media users overlapped in themes concerning domestic vaccination policies, priority groups, challenges from COVID-19 variants, and the global pandemic situation. However, Twitter users were prone to disclose individual vaccination experiences, express anti-vaccine attitudes. In comparison, Weibo users manifested evident deference to authorities and exhibited more positive feelings toward the COVID-19 vaccine. Those disparities were explained by the cultural characteristics' differences between the two countries. The findings provide insights into comprehending public health issues in cross-cultural contexts and illustrate the potential of utilizing social media to conduct health informatics studies and investigate public perceptions during public health crisis time.

Prevalence of depression, anxiety and stress during the COVID-19 pandemic: a cross-sectional study among Palestinian students (10-18 years)

BACKGROUND

The COVID-19 pandemic considers a threat to students' well-being and mental health. The current descriptive cross-sectional study aims to identify psychological distress among school students during the lockdown period.

METHODS

This study was carried out in a sample of 420 primary and secondary school students from June 10 to July 13, 2020, in the Gaza Strip in Palestine. Data was collected using an online questionnaire that included informed consent, socio-demographic questions, and a psychometric scale (DASS-21).

RESULTS

The results revealed that most students experienced moderate to severe levels of anxiety (89.1%) and depression (72.1%), whereas less than half of them (35.7%) experienced moderate to severe stress. Stress, anxiety and depression scores were significantly different across gender, age groups, family size, and family's economic status. The results showed that gender (β = -0.174, p < 0.001), age (β = -0.155, p = 0.001) and economic level of family (β = -0.147, p = 0.002) were negative predictors correlated with stress. Family size (β = 0.156, p = 0.001) played a positive role in stress. It was found that gender (β = -0.105, p = 0.031), age (β = -0.135, p = 0.006) and economic level of family (β = -0.136, p = 0.005) were negative predictors correlated with anxiety, whereas family size (β = 0.139, p = 0.004) played a positive role in anxiety. For depression, gender (β = -0.162, p = 0.001), age (β = -0.160, p = 0.001) and economic level of family (β = -0.131, p = 0.007) were negative predictors correlated with depression, whereas family size (β = -0.133, p = 0.006) was found to be a positive predictor. Concerns about the influence of COVID-19 on economic, education, and daily life were positively correlated to the levels of depression, anxiety and stress, whereas the availability of social support was negatively correlated.

CONCLUSION

The development of a health protocol for influenced students is urgently needed to maintain them remain resilient during dangerous times.

The Psychological and Behavioral Patterns of Online Psychological Help-Seekers before and during COVID-19 Pandemic: A Text Mining-Based Longitudinal Ecological Study

Online mental health service (OMHS) platforms have contributed significantly to the public’s mental health during the COVID-19 pandemic in China. However, it remains unclear why the public used OMHS platforms for psychological help-seeking (PHS) behavior and how PHS behavior varied across different stages of the COVID-19 pandemic. Based on the ecological PHS behavior data from two OMHS platforms, we extracted population, psychological problems, and influential factors of PHS behavior by text mining and time series analysis methods. Seven top-ranked psychological problems (i.e., depression and anxiety, lack of interest, suicidal tendencies, social phobia, feelings of being worried and afraid, suffering, anger) and seven influential factors (i.e., interpersonal relationships, love, family, work, psychotherapy, personal characteristics, marriage) were found. The online PHS behaviors related to different psychological problems and influential factors remained a growing trend before 2020 and have been increasing significantly due to the COVID-19 outbreak. Four main stages were found during the pandemic according to the changes in the online PHS population: sharp growth, significant decline, slight rebound, and slow decline. This study identified large-scale, spontaneous PHS behaviors among the online public during the COVID-19 pandemic and the various psychological problems and influential factors that varied across different stages of the pandemic, suggesting that the government and health practitioners should adopt effective policies and strategies to prevent and intervene in mental health problems for the online public.

Predicting the U.S. Public's Prosocial Responses during the COVID-19 Pandemic

This research examines three distinct processes that influence Americans' prosocial responses during the COVID-19 pandemic. Employing a nationally representative sample, participants read either a mock-up news article on COVID-19 with a clear responsibility attribution (n = 496) or one without (n = 513) in a survey embedded experiment. Participants exposed to the responsibility attribution condition engaged in less systematic processing; systematic processing and all emotions mediated the relationship between responsibility attribution and support for government response measures. For donation intention, only systematic processing and the two socially oriented emotions were significant mediators. In essence, responsibility attribution in media coverage can exert powerful influence on public perception in an ongoing crisis.

Exploring the Expression Differences Between Professionals and Laypeople Toward the COVID-19 Vaccine: Text Mining Approach

BACKGROUND

COVID-19 is still rampant all over the world. Until now, the COVID-19 vaccine is the most promising measure to subdue contagion and achieve herd immunity. However, public vaccination intention is suboptimal. A clear division lies between medical professionals and laypeople. While most professionals eagerly promote the vaccination campaign, some laypeople exude suspicion, hesitancy, and even opposition toward COVID-19 vaccines.

OBJECTIVE

This study aims to employ a text mining approach to examine expression differences and thematic disparities between the professionals and laypeople within the COVID-19 vaccine context.

METHODS

We collected 3196 answers under 65 filtered questions concerning the COVID-19 vaccine from the China-based question and answer forum Zhihu. The questions were classified into 5 categories depending on their contents and description: adverse reactions, vaccination, vaccine effectiveness, social implications of vaccine, and vaccine development. Respondents were also manually coded into two groups: professional and laypeople. Automated text analysis was performed to calculate fundamental expression characteristics of the 2 groups, including answer length, attitude distribution, and high-frequency words. Furthermore, structural topic modeling (STM), as a cutting-edge branch in the topic modeling family, was used to extract topics under each question category, and thematic disparities were evaluated between the 2 groups.

RESULTS

Laypeople are more prevailing in the COVID-19 vaccine-related discussion. Regarding differences in expression characteristics, the professionals posted longer answers and showed a conservative stance toward vaccine effectiveness than did laypeople. Laypeople mentioned countries more frequently, while professionals were inclined to raise medical jargon. STM discloses prominent topics under each question category. Statistical analysis revealed that laypeople preferred the "safety of Chinese-made vaccine" topic and other vaccine-related issues in other countries. However, the professionals paid more attention to medical principles and professional standards underlying the COVID-19 vaccine. With respect to topics associated with the social implications of vaccines, the 2 groups showed no significant difference.

CONCLUSIONS

Our findings indicate that laypeople and professionals share some common grounds but also hold divergent focuses toward the COVID-19 vaccine issue. These incongruities can be summarized as "qualitatively different" in perspective rather than "quantitatively different" in scientific knowledge. Among those questions closely associated with medical expertise, the "qualitatively different" characteristic is quite conspicuous. This study boosts the current understanding of how the public perceives the COVID-19 vaccine, in a more nuanced way. Web-based question and answer forums are a bonanza for examining perception discrepancies among various identities. STM further exhibits unique strengths over the traditional topic modeling method in statistically testing the topic preference of diverse groups. Public health practitioners should be keenly aware of the cognitive differences between professionals and laypeople, and pay special attention to the topics with significant inconsistency across groups to build consensus and promote vaccination effectively.

Psychosocial Effects of the COVID-19 Pandemic: Large-scale Quasi-Experimental Study on Social Media

BACKGROUND

The COVID-19 pandemic has caused several disruptions in personal and collective lives worldwide. The uncertainties surrounding the pandemic have also led to multifaceted mental health concerns, which can be exacerbated with precautionary measures such as social distancing and self-quarantining, as well as societal impacts such as economic downturn and job loss. Despite noting this as a "mental health tsunami", the psychological effects of the COVID-19 crisis remain unexplored at scale. Consequently, public health stakeholders are currently limited in identifying ways to provide timely and tailored support during these circumstances.

OBJECTIVE

Our study aims to provide insights regarding people's psychosocial concerns during the COVID-19 pandemic by leveraging social media data. We aim to study the temporal and linguistic changes in symptomatic mental health and support expressions in the pandemic context.

METHODS

We obtained about 60 million Twitter streaming posts originating from the United States from March 24 to May 24, 2020, and compared these with about 40 million posts from a comparable period in 2019 to attribute the effect of COVID-19 on people's social media self-disclosure. Using these data sets, we studied people's self-disclosure on social media in terms of symptomatic mental health concerns and expressions of support. We employed transfer learning classifiers that identified the social media language indicative of mental health outcomes (anxiety, depression, stress, and suicidal ideation) and support (emotional and informational support). We then examined the changes in psychosocial expressions over time and language, comparing the 2020 and 2019 data sets.

RESULTS

We found that all of the examined psychosocial expressions have significantly increased during the COVID-19 crisis-mental health symptomatic expressions have increased by about 14%, and support expressions have increased by about 5%, both thematically related to COVID-19. We also observed a steady decline and eventual plateauing in these expressions during the COVID-19 pandemic, which may have been due to habituation or due to supportive policy measures enacted during this period. Our language analyses highlighted that people express concerns that are specific to and contextually related to the COVID-19 crisis.

CONCLUSIONS

We studied the psychosocial effects of the COVID-19 crisis by using social media data from 2020, finding that people's mental health symptomatic and support expressions significantly increased during the COVID-19 period as compared to similar data from 2019. However, this effect gradually lessened over time, suggesting that people adapted to the circumstances and their "new normal." Our linguistic analyses revealed that people expressed mental health concerns regarding personal and professional challenges, health care and precautionary measures, and pandemic-related awareness. This study shows the potential to provide insights to mental health care and stakeholders and policy makers in planning and implementing measures to mitigate mental health risks amid the health crisis.