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Background: Mental health disorders are currently the main contributor to poor quality of life and years lived with disability. Symptoms common to many mental health disorders lead to impairments or changes in the use of language, which are observable in the routine use of social media. Detection of these linguistic cues has been explored throughout the last quarter century, but interest and methodological development have burgeoned following the COVID-19 pandemic. The next decade may see the development of reliable methods for predicting mental health status using social media data. This might have implications for clinical practice and public health policy, particularly in the context of early intervention in mental health care., Objective: This study aims to examine the state of the art in methods for predicting mental health statuses of social media users. Our focus is the development of artificial intelligence-driven methods, particularly natural language processing, for analyzing large volumes of written text. This study details constraints affecting research in this area. These include the dearth of high-quality public datasets for methodological benchmarking and the need to adopt ethical and privacy frameworks acknowledging the stigma experienced by those with a mental illness., Methods: A Google Scholar search yielded peer-reviewed articles dated between 1999 and 2024. We manually grouped the articles by 4 primary areas of interest: datasets on social media and mental health, methods for predicting mental health status, longitudinal analyses of mental health, and ethical aspects of the data and analysis of mental health. Selected articles from these groups formed our narrative review., Results: Larger datasets with precise dates of participants' diagnoses are needed to support the development of methods for predicting mental health status, particularly in severe disorders such as schizophrenia. Inviting users to donate their social media data for research purposes could help overcome widespread ethical and privacy concerns. In any event, multimodal methods for predicting mental health status appear likely to provide advancements that may not be achievable using natural language processing alone., Conclusions: Multimodal methods for predicting mental health status from voice, image, and video-based social media data need to be further developed before they may be considered for adoption in health care, medical support, or as consumer-facing products. Such methods are likely to garner greater public confidence in their efficacy than those that rely on text alone. To achieve this, more high-quality social media datasets need to be made available and privacy concerns regarding the use of these data must be formally addressed. A social media platform feature that invites users to share their data upon publication is a possible solution. Finally, a review of literature studying the effects of social media use on a user's depression and anxiety is merited., (©David Owen, Amy J Lynham, Sophie E Smart, Antonio F Pardiñas, Jose Camacho Collados. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 15.11.2024.)

Background: Co-use of alcohol and e-cigarettes (often called vaping) has been linked with long-term health outcomes, including increased risk for substance use disorder. Co-use may have been exacerbated by the COVID-19 pandemic. Social networking sites may offer insights into current perspectives on polysubstance use., Objective: The aims of this study were to investigate concurrent mentions of vaping and alcohol on Twitter (subsequently rebranded X) during a time of changing vaping regulations in the United States and the emergence of the COVID-19 pandemic., Methods: Tweets including both vape- and alcohol-related terms posted between October 2019 and September 2020 were analyzed using latent Dirichlet allocation modeling. Distinct topics were identified and described., Results: Three topics were identified across 6437 tweets: (1) flavors and flavor ban (n=3334, 51.8% of tweets), (2) co-use discourse (n=1119, 17.4%), and (3) availability and access regulation (n=1984, 30.8%). Co-use discussions often portrayed co-use as positive and prosocial. Tweets focused on regulation often used alcohol regulations for comparison. Some focused on the perceived overregulation of vaping (compared to alcohol), while others supported limiting youth access but not at the expense of adult access (eg, stronger age verification over product bans). Across topics, vaping was typically portrayed as less harmful than alcohol use. The benefits of flavors for adult smoking cessation were also discussed. The distribution of topics across time varied across both pre- and post-regulatory change and pre- and post-COVID-19 pandemic declaration periods, suggesting shifts in topic focus salience across time., Conclusions: Co-use discussions on social media during this time of regulatory change and social upheaval typically portrayed both vaping and alcohol use in a positive light. It also included debates surrounding the differences in regulation of the 2 substances-particularly as it related to limiting youth access. Emergent themes from the analysis suggest that alcohol was perceived as more harmful but less regulated and more accessible to underage youth than vaping products. Frequent discussions and comparisons of the 2 substances as it relates to their regulation emphasize the still-evolving vaping policy landscape. Social media content analyses during times of change may help regulators and policy makers to better understand and respond to common concerns and potential misconceptions surrounding drug-related policies and accessibility., (©Lynsie R Ranker, David Assefa Tofu, Manyuan Lu, Jiaxi Wu, Aruni Bhatnagar, Rose Marie Robertson, Derry Wijaya, Traci Hong, Jessica L Fetterman, Ziming Xuan. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 12.11.2024.)

Background: A global-scale pandemic, such as the COVID-19 pandemic, greatly impacted communities of color. Moreover, physical distancing recommendations during the height of the COVID-19 pandemic negatively affected people's sense of social connection, especially among young individuals. More research is needed on the use of social media and communication about depression, with a specific focus on young Black Americans., Objective: This paper aims to examine whether there are any differences in social-networking characteristics before and during the pandemic periods (ie, pre-COVID-19 pandemic vs peri-COVID-19 pandemic) among the students of historically black colleges and universities (HBCUs). For the study, the researchers focus on the students who have posted a depression-related tweet or have retweeted such posts on their timeline and also those who have not made such tweets. This is done to understand the collective patterns of both groups., Methods: This paper analyzed the social networks on Twitter (currently known as X; X Corp) of HBCU students through comparing pre-COVID-19 and peri-COVID-19 pandemic data. The researchers quantified the structural properties, such as reciprocity, homophily, and communities, to test the differences in internet-based socializing patterns between the depression-related and non-depression related groups for the 2 periods., Results: During the COVID-19 pandemic period, the group with depression-related tweets saw an increase in internet-based friendships, with the average number of friends rising from 1194 (SD 528.14) to 1371 (SD 824.61; P<.001). Their mutual relationships strengthened (reciprocity: 0.78-0.8; P=.01), and they showed higher assortativity with other depression-related group members (0.6-0.7; P<.001). In a network with only HBCU students, internet-based and physical affiliation memberships aligned closely during the peri-COVID-19 pandemic period, with membership entropy decreasing from 1.0 to 0.5. While users without depression-related tweets engaged more on the internet with other users who shared physical affiliations, those who posted depression-related tweets maintained consistent entropy levels (modularity: 0.75-0.76). Compared with randomized networks before and during the COVID-19 pandemic (P<.001), the users also exhibited high homophily with other members who posted depression-related tweets., Conclusions: The findings of this study provided insight into the social media activities of HBCU students' social networks and communication about depression on social media. Future social media interventions focused on the mental health of Black college students may focus on providing resources to students who communicate about depression. Efforts aimed at providing relevant resources and information to internet-based communities that share institutional affiliation may enhance access to social support, particularly for those who may not proactively seek assistance. This approach may contribute to increased social support for individuals within these communities, especially those with a limited social capacity., (©Eun Lee, Heejun Kim, Yildiz Esener, Terika McCall. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 28.10.2024.)

Background: Consumer technology is increasingly being adopted to support personal stress management, including by teachers. Multidisciplinary research has contributed some knowledge of design and features that can help detect and manage workplace stress. However, there is less understanding of what facilitates engagement with ubiquitous "off the shelf" technologies, particularly in a specific occupational setting. An understanding of features that facilitate or inhibit technology use, and the influences of contexts on the manner of interaction, could improve teachers' stress-management opportunities., Objective: The aim of the study was to investigate the interaction features that facilitated or inhibited engagement with 4 consumer technologies chosen by teachers for stress management, as well as the influence of the educational contexts on their engagement. We also examined how use of well-being technology could be better supported in the school., Methods: The choice of consumer technologies was categorized in a taxonomy for English secondary school teachers according to stress-management strategies and digital features. Due to the COVID-19 pandemic, we adapted the study so that working from home in the summer could be contrasted with being back in school. Thus, a longitudinal study intended for 6 weeks in the summer term (in 2020) was extended into the autumn term, lasting up to 27 weeks. Teachers chose to use either a Withings smartwatch or Wysa, Daylio, or Teacher Tapp apps. Two semistructured interviews and web-based surveys were conducted with 8 teachers in England in the summer term, and 6 (75%) of them took part in a third interview in the autumn term. Interviews were analyzed using reflexive thematic analysis informed by interpretive phenomenological analysis., Results: Technology elements and characteristics such as passive data collation, brevity of interaction, discreet appearance, reminders, and data visualization were described by teachers as facilitators. Lack of instructions and information on features, connectivity, extended interaction requirements, and nondifferentiation of activity and exercise data were described as barriers. Mesocontextual barriers to engagement were also reported, particularly when teachers were back on school premises, including temporal constraints, social stigma, and lack of private space to de-stress. Teachers had ideas for feature improvements and how educational leadership normalizing teachers' stress management with consumer technologies could benefit the school culture., Conclusions: Having preselected their stress-management strategies, teachers were able to harness design features to support themselves over an extended period. There could be an important role for digital interventions as part of teachers' stress management, which the school leadership would need to leverage to maximize their potential. The findings add to the holistic understanding of situated self-care and should inform developers' considerations for occupational digital stress support., (©Julia B Manning, Ann Blandford, Julian Edbrooke-Childs. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 22.10.2024.)

Background: The COVID-19 pandemic has profoundly affected mental health, leading to an increased prevalence of depression and insomnia. Currently, artificial intelligence (AI) and deep learning have thoroughly transformed health care-related mobile apps, offered more effective mental health support, and alleviated the psychological stress that may have emerged during the pandemic. Early reviews outlined the use of mobile apps for dealing with depression and insomnia separately. However, there is now an urgent need for a systematic evaluation of mobile apps that address both depression and insomnia to reveal new applications and research gaps., Objective: This study aims to systematically review and evaluate mobile apps targeting depression and insomnia, highlighting their features, effectiveness, and gaps in the current research., Methods: We systematically searched PubMed, Scopus, and Web of Science for peer-reviewed journal articles published between 2017 and 2023. The inclusion criteria were studies that (1) focused on mobile apps addressing both depression and insomnia, (2) involved young people or adult participants, and (3) provided data on treatment efficacy. Data extraction was independently conducted by 2 reviewers. Title and abstract screening, as well as full-text screening, were completed in duplicate. Data were extracted by a single reviewer and verified by a second reviewer, and risk of bias assessments were completed accordingly., Results: Of the initial 383 studies we found, 365 were excluded after title, abstract screening, and removal of duplicates. Eventually, 18 full-text articles met our criteria and underwent full-text screening. The analysis revealed that mobile apps related to depression and insomnia were primarily utilized for early detection, assessment, and screening (n=5 studies); counseling and psychological support (n=3 studies); and cognitive behavioral therapy (CBT; n=10 studies). Among the 10 studies related to depression, our findings showed that chatbots demonstrated significant advantages in improving depression symptoms, a promising development in the field. Additionally, 2 studies evaluated the effectiveness of mobile apps as alternative interventions for depression and sleep, further expanding the potential applications of this technology., Conclusions: The integration of AI and deep learning into mobile apps, particularly chatbots, is a promising avenue for personalized mental health support. Through innovative features, such as early detection, assessment, counseling, and CBT, these apps significantly contribute toward improving sleep quality and addressing depression. The reviewed chatbots leveraged advanced technologies, including natural language processing, machine learning, and generative dialog, to provide intelligent and autonomous interactions. Compared with traditional face-to-face therapies, their feasibility, acceptability, and potential efficacy highlight their user-friendly, cost-effective, and accessible nature with the aim of enhancing sleep and mental health outcomes., (©Yi-Hang Chiu, Yen-Fen Lee, Huang-Li Lin, Li-Chen Cheng. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 18.10.2024.)

Background: Long COVID has widened the health gap across society and highlighted the vulnerabilities and risks faced by health care systems. For instance, the global trend of medical workers resigning has become a prominent topic on social media. In response to this severe social problem in global public health within the digital society, it is urgent to investigate how the professional identity of medical students, who are digital natives and the future workforce of medical practitioners, is affected by the media environment., Objective: This study aims to examine how media exposure relates to medical students' perceptions of informational and emotional support, and how these perceptions further influence the development of their professional identity., Methods: Building on the Stimulus-Organism-Response (SOR) framework, this study develops a theoretical model to illustrate how media exposure affects medical students' professional identity through the mediation of social support. Specifically, media exposure was assessed through online news media and social media exposure; social support was evaluated in terms of informational and emotional support; and professional identity was measured through medical students' sense of belonging and professional commitment. A survey was conducted at a medical school in China, yielding 1087 valid responses that were analyzed using SmartPLS 4.0., Results: Consistent with our expectations, online news media exposure was positively associated with both informational support (β=.163; P<.001) and emotional support (β=.084; P=.007). Similarly, social media exposure showed positive associations with informational support (β=.122; P<.001) and emotional support (β=.235; P<.001). Thereafter, informational support (β=.228; P<.001) and emotional support (β=.344; P<.001) were positively associated with students' sense of belonging. Meanwhile, both informational support (β=.245; P<.001) and emotional support (β=.412; P<.001) positively impacted medical students' professional commitment. In addition, a mediation test was conducted. The results confirmed that informational support and emotional support partially mediated the effect of online news media, while fully mediating the effect of social media on medical students' sense of belonging and professional commitment., Conclusions: This study finds that exposure to online news media and social media can enhance medical students' sense of belonging and professional commitment through the formation of informational and emotional support. It expands the discussion on the role of media in providing social support and facilitating the development of medical students' professional identity. This is a valuable contribution to addressing complex public health crises through effective media governance in the network era., (©Manli Wu, Jun Yan, Chongming Qiao, Chu Yan. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 17.10.2024.)

Background: Obesity is a chronic, multifactorial, and relapsing disease, affecting people of all ages worldwide, and is directly related to multiple complications. Understanding public attitudes and perceptions toward obesity is essential for developing effective health policies, prevention strategies, and treatment approaches., Objective: This study investigated the sentiments of the general public, celebrities, and important organizations regarding obesity using social media data, specifically from Twitter (subsequently rebranded as X)., Methods: The study analyzes a dataset of 53,414 tweets related to obesity posted on Twitter during the COVID-19 pandemic, from April 2019 to December 2022. Sentiment analysis was performed using the XLM-RoBERTa-base model, and topic modeling was conducted using the BERTopic library., Results: The analysis revealed that tweets regarding obesity were predominantly negative. Spikes in Twitter activity correlated with significant political events, such as the exchange of obesity-related comments between US politicians and criticism of the United Kingdom's obesity campaign. Topic modeling identified 243 clusters representing various obesity-related topics, such as childhood obesity; the US President's obesity struggle; COVID-19 vaccinations; the UK government's obesity campaign; body shaming; racism and high obesity rates among Black American people; smoking, substance abuse, and alcohol consumption among people with obesity; environmental risk factors; and surgical treatments., Conclusions: Twitter serves as a valuable source for understanding obesity-related sentiments and attitudes among the public, celebrities, and influential organizations. Sentiments regarding obesity were predominantly negative. Negative portrayals of obesity by influential politicians and celebrities were shown to contribute to negative public sentiments, which can have adverse effects on public health. It is essential for public figures to be mindful of their impact on public opinion and the potential consequences of their statements., (©Jorge César Correia, Sarmad Shaharyar Ahmad, Ahmed Waqas, Hafsa Meraj, Zoltan Pataky. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 11.10.2024.)

Background: Although COVID-19 is no longer a global health emergency, it remains pervasive in Singapore, a city-state situated in Southeast Asia, with periodic waves of infection. In addition to disease management, strong communication strategies are critical in the government's response to the pandemic to keep the public updated and equip them in protecting themselves., Objective: Grounded in the crisis and emergency risk communication (CERC) framework and emotional appeals, this study aimed to analyze public health communication strategies in Singapore during the COVID-19 pandemic., Methods: Quantitative content analysis was conducted on 696 Facebook (Meta Platforms Inc) posts and 83 website articles published by Singapore-based public health institutions between January 2020 and September 2022., Results: The results showed that increasing communication on message themes, such as inquisitive messaging and clarification, can enhance communication strategies. The use of emotional appeals also varies with time and should be carefully used as they are context-specific., Conclusions: Theoretically, this study contributes to advancements in the CERC framework and concepts of emotional appeals by exploring the applications and changes of CERC message types and emotional appeals at different phases. The findings can provide practical guidance for authorities and communication practitioners in developing effective communication strategies., (©Shirley S Ho, Agnes S F Chuah, Vanessa S Ho, Sonny Rosenthal, Hye Kyung Kim, Shannon S H Soh. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 17.09.2024.)

Background: Specialized studies have shown that smartphone-based social interaction data are predictors of depressive and anxiety symptoms. Moreover, at times during the COVID-19 pandemic, social interaction took place primarily remotely. To appropriately test these objective data for their added value for epidemiological research during the pandemic, it is necessary to include established predictors., Objective: Using a comprehensive model, we investigated the extent to which smartphone-based social interaction data contribute to the prediction of depressive and anxiety symptoms, while also taking into account well-established predictors and relevant pandemic-specific factors., Methods: We developed the Corona Health App and obtained participation from 490 Android smartphone users who agreed to allow us to collect smartphone-based social interaction data between July 2020 and February 2021. Using a cross-sectional design, we automatically collected data concerning average app use in terms of the categories video calls and telephony, messenger use, social media use, and SMS text messaging use, as well as pandemic-specific predictors and sociodemographic covariates. We statistically predicted depressive and anxiety symptoms using elastic net regression. To exclude overfitting, we used 10-fold cross-validation., Results: The amount of variance explained (R 2 ) was 0.61 for the prediction of depressive symptoms and 0.57 for the prediction of anxiety symptoms. Of the smartphone-based social interaction data included, only messenger use proved to be a significant negative predictor of depressive and anxiety symptoms. Video calls were negative predictors only for depressive symptoms, and SMS text messaging use was a negative predictor only for anxiety symptoms., Conclusions: The results show the relevance of smartphone-based social interaction data in predicting depressive and anxiety symptoms. However, even taken together in the context of a comprehensive model with well-established predictors, the data only add a small amount of value., (©Johanna-Sophie Edler, Yannik Terhorst, Rüdiger Pryss, Harald Baumeister, Caroline Cohrdes. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 16.09.2024.)

Background: Internet gaming disorder among university students has become a great concern for university counsellors worldwide since the COVID-19 pandemic. The factors influencing the development of internet gaming disorder in students during the COVID-19 pandemic could be different from those before the pandemic., Objective: This study aims to explore the associations among social isolation, self-control, and internet gaming disorder in Chinese university students and to examine whether self-control mediates the positive effects of social isolation on internet gaming disorder., Methods: A cross-sectional survey was employed to collect data from university students in Shandong province of China from April to September 2022. The Isolation subscale of the Self-Compassion Scale, Self-Control Scale, and Internet Gaming Disorder Scale were used to assess the social isolation, self-control, and internet gaming disorder among university students, respectively. Models 4 and 5 of PROCESS software were used to analyze the mediating role of self-control and the moderating role of gender on the association between social isolation and internet gaming disorder., Results: A total of 479 students were recruited from 6 universities located in 3 different regions of Shandong, China. Students had low levels of internet gaming disorder and moderate levels of social isolation and self-control, with mean scores of 8.94 (SD 9.06), 12.04 (SD 3.53), and 57.15 (SD 8.44), respectively. Social isolation was positively correlated with internet gaming disorder (r=0.217; P<.001), and self-control was negatively correlated with social isolation (r=-0.355; P<.001) and internet gaming disorder (r=-0.260; P<.001). Self-control played a mediating role in the association between social isolation and internet gaming disorder (β=-.185, 95% CI -.295 to -.087). The effects of social isolation on internet gaming disorder among female students were lower than those among male students., Conclusions: Self-control was a mediator in the association between social isolation and internet gaming disorder. Moreover, gender played a moderating role in the association between social isolation and internet gaming disorder. This study highlights the need to alleviate the development of internet gaming disorder among students during a pandemic, especially that of male students. Effective interventions that lessen social isolation and promote self-control should be developed., (©Yufang Guo, Fangyan Yue, Xiangyu Lu, Fengye Sun, Meixing Pan, Yannan Jia. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 10.09.2024.)

Background: Anti-Asian hate crimes escalated during the COVID-19 pandemic; however, limited research has explored the association between social media sentiment and hate crimes toward Asian communities., Objective: This study aims to investigate the relationship between Twitter (rebranded as X) sentiment data and the occurrence of anti-Asian hate crimes in New York City from 2019 to 2022, a period encompassing both before and during COVID-19 pandemic conditions., Methods: We used a hate crime dataset from the New York City Police Department. This dataset included detailed information on the occurrence of anti-Asian hate crimes at the police precinct level from 2019 to 2022. We used Twitter's application programming interface for Academic Research to collect a random 1% sample of publicly available Twitter data in New York State, including New York City, that included 1 or more of the selected Asian-related keywords and applied support vector machine to classify sentiment. We measured sentiment toward the Asian community using the rates of negative and positive sentiment expressed in tweets at the monthly level (N=48). We used negative binomial models to explore the associations between sentiment levels and the number of anti-Asian hate crimes in the same month. We further adjusted our models for confounders such as the unemployment rate and the emergence of the COVID-19 pandemic. As sensitivity analyses, we used distributed lag models to capture 1- to 2-month lag times., Results: A point increase of 1% in negative sentiment rate toward the Asian community in the same month was associated with a 24% increase (incidence rate ratio [IRR] 1.24; 95% CI 1.07-1.44; P=.005) in the number of anti-Asian hate crimes. The association was slightly attenuated after adjusting for unemployment and COVID-19 emergence (ie, after March 2020; P=.008). The positive sentiment toward Asian tweets with a 0-month lag was associated with a 12% decrease (IRR 0.88; 95% CI 0.79-0.97; P=.002) in expected anti-Asian hate crimes in the same month, but the relationship was no longer significant after adjusting for the unemployment rate and the emergence of COVID-19 pandemic (P=.11)., Conclusions: A higher negative sentiment level was associated with more hate crimes specifically targeting the Asian community in the same month. The findings highlight the importance of monitoring public sentiment to predict and potentially mitigate hate crimes against Asian individuals., (©Hanxue Wei, Yulin Hswen, Junaid S Merchant, Laura B Drew, Quynh C Nguyen, Xiaohe Yue, Heran Mane, Thu T Nguyen. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 09.09.2024.)

Background: Suicide has emerged as a critical public health concern during the COVID-19 pandemic. With social distancing measures in place, social media has become a significant platform for individuals expressing suicidal thoughts and behaviors. However, existing studies on suicide using social media data often overlook the diversity among users and the temporal dynamics of suicide risk., Objective: By examining the variations in post volume trajectories among users on the r/SuicideWatch subreddit during the COVID-19 pandemic, this study aims to investigate the heterogeneous patterns of change in suicide risk to help identify social media users at high risk of suicide. We also characterized their linguistic features before and during the pandemic., Methods: We collected and analyzed post data every 6 months from March 2019 to August 2022 for users on the r/SuicideWatch subreddit (N=6163). A growth-based trajectory model was then used to investigate the trajectories of post volume to identify patterns of change in suicide risk during the pandemic. Trends in linguistic features within posts were also charted and compared, and linguistic markers were identified across the trajectory groups using regression analysis., Results: We identified 2 distinct trajectories of post volume among r/SuicideWatch subreddit users. A small proportion of users (744/6163, 12.07%) was labeled as having a high risk of suicide, showing a sharp and lasting increase in post volume during the pandemic. By contrast, most users (5419/6163, 87.93%) were categorized as being at low risk of suicide, with a consistently low and mild increase in post volume during the pandemic. In terms of the frequency of most linguistic features, both groups showed increases at the initial stage of the pandemic. Subsequently, the rising trend continued in the high-risk group before declining, while the low-risk group showed an immediate decrease. One year after the pandemic outbreak, the 2 groups exhibited differences in their use of words related to the categories of personal pronouns; affective, social, cognitive, and biological processes; drives; relativity; time orientations; and personal concerns. In particular, the high-risk group was discriminant in using words related to anger (odds ratio [OR] 3.23, P<.001), sadness (OR 3.23, P<.001), health (OR 2.56, P=.005), achievement (OR 1.67, P=.049), motion (OR 4.17, P<.001), future focus (OR 2.86, P<.001), and death (OR 4.35, P<.001) during this stage., Conclusions: Based on the 2 identified trajectories of post volume during the pandemic, this study divided users on the r/SuicideWatch subreddit into suicide high- and low-risk groups. Our findings indicated heterogeneous patterns of change in suicide risk in response to the pandemic. The high-risk group also demonstrated distinct linguistic features. We recommend conducting real-time surveillance of suicide risk using social media data during future public health crises to provide timely support to individuals at potentially high risk of suicide., (©Yifei Yan, Jun Li, Xingyun Liu, Qing Li, Nancy Xiaonan Yu. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 08.08.2024.)

Background: Resilience is a protective factor in healthy aging, helping to maintain and recover physical and mental functions. The Resilience in Illness Model has proven effective in fostering resilience and well-being. Physical activity is crucial for older adults' independence and well-being, even as aging causes a progressive decline. Additionally, older adults face challenges such as spousal loss and physical disability, making preventive intervention strategies necessary., Objective: This study aims to develop and evaluate a web-based program to enhance resilience, physical activity, and well-being among community-dwelling older adults. Additionally, we aim to gather feedback on the program's strengths and limitations., Methods: A 4-week resilience-enhancing program was created, incorporating role-play and talk-in-interaction and focusing on 3 key skills: coping, control belief, and manageability. The program included scenarios such as becoming widowed and suffering a stroke, designed to engage older adults. A pilot test preceded the intervention. As a result of the COVID-19 pandemic, the program shifted from in-person to web-based sessions. A single-blind, parallel-group, randomized controlled trial was conducted. Participants aged over 65 years were recruited offline and randomly assigned to either an intervention or control group. A certified resilience practitioner delivered the program. Outcomes in resilience, physical activity, and well-being were self-assessed at baseline (T0), 4 weeks (T1), and 12 weeks (T2) after the program. A mixed methods approach was used to evaluate feedback., Results: A web-based participatory program enhancing 3 skills-coping, control belief, and manageability for resilience-was well developed. Among 96 participants, 63 were randomized into the intervention group (n=31) and the control group (n=32). The mean age in the intervention group was 69.27 (SD 3.08) years and 74.84 (SD 6.23) years in the control group. Significant between-group differences at baseline were found in age (t45.6=-4.53, P<.001) and physical activity at baseline (t61=2.92, P=.005). No statistically significant between-group differences over time were observed in resilience (SE 7.49, 95% CI -10.74 to 18.61, P=.60), physical activity (SE 15.18, 95% CI -24.74 to 34.74, P=.74), and well-being (SE 3.74, 95% CI -2.68 to 11.98, P=.21) after controlling for baseline differences. The dropout rate was lower in the intervention group (2/31, 6%) compared with the control group (5/32, 16%). Moreover, 77% (24/31) of participants in the intervention group completed the entire program. Program feedback from the participants indicated high satisfaction with the web-based format and mentorship support., Conclusions: This study demonstrated that a web-based resilience-enhancing program is appropriate, acceptable, feasible, and engaging for community-dwelling older adults. The program garnered enthusiasm for its potential to optimize resilience, physical activity, and well-being, with mentorship playing a crucial role in its success. Future studies should aim to refine program content, engagement, and delivery methods to effectively promote healthy aging in this population., Trial Registration: ClinicalTrials.gov NCT05808491; https://clinicaltrials.gov/ct2/show/NCT05808491., (©Yi-Chen Wu, Shu-Fen Shen, Liang-Kung Chen, Heng-Hsin Tung. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 25.07.2024.)

Background: Retrospecting the trust gaps and their dynamics during the pandemic is crucial for understanding the root causes of postpandemic challenges and offers valuable insights into preparing for future public health emergencies. The COVID-19 pandemic eroded people's trust in strangers and acquaintances, while their trust in family members remained relatively stable. This resulted in 2 trust gaps, namely, the family members-strangers trust gap and the family members-acquaintances trust gap. Widening trust gaps impede social integration and undermine the effective management of public health crises. However, little is known about how digital media use shaped trust gaps during a pandemic., Objective: This study aims to investigate the relationships between digital media use, negative emotions, the family members-strangers trust gap, and the family members-acquaintances trust gap during the COVID-19 pandemic in China. We test the mediating role of negative emotions between digital media use and 2 trust gaps and compare the indirect effect of digital media use on 2 trust gaps through negative emotions., Methods: A cross-sectional web-based survey was conducted in China between January 31, 2020, and February 9, 2020. A total of 1568 adults participated in the survey. Questions related to digital media use, negative emotions, trust in family members, trust in acquaintances, and trust in strangers during the pandemic were asked. Regression analyses were performed to test the associations between the examined variables. We used a 95% bootstrap CI approach to estimate the mediation effects., Results: Digital media use was positively associated with negative emotions (B=0.17, SE 0.03; P<.001), which in turn were positively associated with the family members-strangers trust gap (B=0.15, SE 0.03; P<.001). Likewise, digital media use was positively associated with negative emotions (B=0.17, SE 0.03; P<.001), while negative emotions were positively associated with the family members-acquaintances trust gap (B=0.08, SE 0.03; P=.01). Moreover, the indirect effect of digital media use on the family members-strangers trust gap (B=0.03, SE 0.01; 95% CI 0.01-0.04) was stronger than that on the family members-acquaintances trust gap (B=0.01, SE 0.01; 95% CI 0.003-0.027)., Conclusions: The results demonstrate that negative emotions resulting from the frequent use of digital media are a key factor that accounts for the widening trust gaps. Considering the increasing reliance on digital media, the findings indicate that the appropriate use of digital media can prevent the overamplification of negative emotions and curb the enlargement of trust gaps. This may help restore social trust and prepare for future public health crises in the postpandemic era., (©Lu Wei, Qing Huang. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 10.07.2024.)

Background: The emergence of the COVID-19 pandemic rapidly accelerated the need and implementation of digital innovations, especially in medicine., Objective: To gain a better understanding of the stress associated with digital transformation in physicians, this study aims to identify working conditions that are stress relevant for physicians and differ in dependence on digital transformation. In addition, we examined the potential role of individual characteristics (ie, age, gender, and actual implementation of a digital innovation within the last 3 years) in digitalization-associated differences in these working conditions., Methods: Cross-sectional web-based questionnaire data of 268 physicians (mean age 40.9, SD 12.3 y; n=150, 56% women) in Germany were analyzed. Physicians rated their chronic stress level and 11 relevant working conditions (ie, work stressors such as time pressure and work resources such as influence on sequence) both before and after either a fictional or real implementation of a relevant digital transformation at their workplace. In addition, a subsample of individuals (60; n=33, 55% women) submitted self-collected hair samples for cortisol analysis., Results: The stress relevance of the selected working conditions was confirmed by significant correlations with self-rated chronic stress and hair cortisol levels (hair F) within the sample, all of them in the expected direction (P values between .01 and <.001). Multilevel modeling revealed significant differences associated with digital transformation in the rating of 8 (73%) out of 11 working conditions. More precisely, digital transformation was associated with potentially stress-enhancing effects in 6 working conditions (ie, influence on procedures and complexity of tasks) and stress-reducing effects in 2 other working conditions (ie, perceived workload and time pressure). Younger individuals, women, and individuals whose workplaces have implemented digital innovations tended to perceive digitalization-related differences in working conditions as rather stress-reducing., Conclusions: Our study lays the foundation for future hypothesis-based longitudinal research by identifying those working conditions that are stress relevant for physicians and prone to differ as a function of digital transformation and individual characteristics., (©Magdalena Katharina Wekenborg, Katharina Förster, Florian Schweden, Robin Weidemann, Felix von Bechtolsheim, Clemens Kirschbaum, Jürgen Weitz, Beate Ditzen. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 17.06.2024.)

Background: Social media has become an increasingly popular and critical tool for users to digest diverse information and express their perceptions and attitudes. While most studies endeavor to delineate the emotional responses of social media users, there is limited research exploring the factors associated with the emergence of emotions, particularly negative ones, during news consumption., Objective: We aim to first depict the web coverage by news organizations on social media and then explore the crucial elements of news coverage that trigger the public's negative emotions. Our findings can act as a reference for responsible parties and news organizations in times of crisis., Methods: We collected 23,705 Facebook posts with 1,019,317 comments from the public pages of representative news organizations in Hong Kong. We used text mining techniques, such as topic models and Bidirectional Encoder Representations from Transformers, to analyze news components and public reactions. Beyond descriptive analysis, we used regression models to shed light on how news coverage on social media is associated with the public's negative emotional responses., Results: Our results suggest that occurrences of issues regarding pandemic situations, antipandemic measures, and supportive actions are likely to reduce the public's negative emotions, while comments on the posts mentioning the central government and the Government of Hong Kong reveal more negativeness. Negative and neutral media tones can alleviate the rage and interact with the subjects and issues in the news to affect users' negative emotions. Post length is found to have a curvilinear relationship with users' negative emotions., Conclusions: This study sheds light on the impacts of various components of news coverage (issues, subjects, media tone, and length) on social media on the public's negative emotions (anger, fear, and sadness). Our comprehensive analysis provides a reference framework for efficient crisis communication for similar pandemics at present or in the future. This research, although first extending the analysis between the components of news coverage and negative user emotions to the scenario of social media, echoes previous studies drawn from traditional media and its derivatives, such as web newspapers. Although the era of COVID-19 pandemic gradually brings down the curtain, the commonality of this research and previous studies also contributes to establishing a clearer territory in the field of health crises., (©Hanjing Wang, Yupeng Li, Xuan Ning. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 06.06.2024.)

Background: Construction and nursing are critical industries. Although both careers involve physically and mentally demanding work, the risks to workers during the COVID-19 pandemic are not well understood. Nurses (both younger and older) are more likely to experience the ill effects of burnout and stress than construction workers, likely due to accelerated work demands and increased pressure on nurses during the COVID-19 pandemic. In this study, we analyzed a large social media data set using advanced natural language processing techniques to explore indicators of the mental status of workers across both industries before and during the COVID-19 pandemic., Objective: This social media analysis aims to fill a knowledge gap by comparing the tweets of younger and older construction workers and nurses to obtain insights into any potential risks to their mental health due to work health and safety issues., Methods: We analyzed 1,505,638 tweets published on Twitter (subsequently rebranded as X) by younger and older (aged <45 vs >45 years) construction workers and nurses. The study period spanned 54 months, from January 2018 to June 2022, which equates to approximately 27 months before and 27 months after the World Health Organization declared COVID-19 a global pandemic on March 11, 2020. The tweets were analyzed using big data analytics and computational linguistic analyses., Results: Text analyses revealed that nurses made greater use of hashtags and keywords (both monograms and bigrams) associated with burnout, health issues, and mental health compared to construction workers. The COVID-19 pandemic had a pronounced effect on nurses' tweets, and this was especially noticeable in younger nurses. Tweets about health and well-being contained more first-person singular pronouns and affect words, and health-related tweets contained more affect words. Sentiment analyses revealed that, overall, nurses had a higher proportion of positive sentiment in their tweets than construction workers. However, this changed markedly during the COVID-19 pandemic. Since early 2020, sentiment switched, and negative sentiment dominated the tweets of nurses. No such crossover was observed in the tweets of construction workers., Conclusions: The social media analysis revealed that younger nurses had language use patterns consistent with someone experiencing the ill effects of burnout and stress. Older construction workers had more negative sentiments than younger workers, who were more focused on communicating about social and recreational activities rather than work matters. More broadly, these findings demonstrate the utility of large data sets enabled by social media to understand the well-being of target populations, especially during times of rapid societal change., (©Weicong Li, Liyaning Maggie Tang, Jed Montayre, Celia B Harris, Sancia West, Mark Antoniou. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 05.06.2024.)

Background: The overall pandemic created enormous pressure on long-term care workers (LTCWs), making them particularly vulnerable to mental disorders. Despite this, most of the available evidence on professional well-being during COVID-19 has exclusively focused on frontline health care workers., Objective: This study aimed to identify the long-term psychological needs of LTCWs derived from the COVID-19 pandemic and to explore barriers and facilitators related to digital mental health tools. This is part of a project that seeks to develop a digital mental health intervention to reduce psychological distress in this population group., Methods: We performed a qualitative study with a rapid research approach. Participants were LTCWs of the autonomous community of Catalonia. We conducted 30 semistructured interviews between April and September 2022. We used a qualitative content analysis method with an inductive-deductive approach., Results: The period of the pandemic with the highest mental health burden was the COVID-19 outbreak, with almost all workers having experienced some form of emotional distress. Emotional distress persisted over time in more than half of the participants, with fatigue and nervousness being the main emotions expressed at the time of the interview. High workload, the feeling that pandemic times are not over, and poor working conditions that have remained since then have been the most frequently expressed determinants of such emotions. Potential barriers and facilitators to engagement with digital tools were also identified in terms of previous experience and beliefs of the target population, possibilities for the integration of a digital tool into daily life, preferences regarding the level of guidance, the possibility of social connectedness through the tool, and privacy and confidentiality. The identified factors may become especially relevant in the context of the pandemic remission phase., Conclusions: More than 2 years after the pandemic outbreak, emotional distress is still relevant. The persistent burden of psychological distress points to a need for institutions to take action to improve working conditions and promote employees' well-being. Considering factors that act as barriers and facilitators for the use of digital mental health tools, it is important to develop tailored tools that could offer valuable support to this population during and after a pandemic., (©Leticia González-Spinoglio, Anna Monistrol-Mula, Cecilia Vindrola-Padros, Salvatore Aguilar-Ortiz, Bernat Carreras, Josep Maria Haro, Mireia Felez-Nobrega. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 29.05.2024.)

Background: The pandemic has accelerated digital work transformation, yet little is known about individuals' willingness to sustain such digital modes and its associated factors. A better understanding of this willingness and its drivers is crucial for guiding the development of future digital work infrastructure, training programs, and strategies to monitor and prevent related health issues., Objective: This study aims to quantify the general population's willingness to sustain pandemic-induced digital work, identify its associated factors, and examine how screen time moderates these relationships., Methods: A cross-sectional study was conducted targeting Hong Kong residents aged ≥18 years who have increased engagement in digital work since the pandemic. Data were collected through self-reported, web-based surveys. Descriptive statistics determined prevalence rates, while structured multiphase logistic regression identified associated factors and explored the moderating effects of screen hour levels., Results: This unfunded study enrolled 1014 participants from May 2 to June 24, 2022, and completed data analysis within 3 months after data collection. A total of 391 (38.6%; 95% CI 35.6%-41.6%) participants expressed willingness to sustain digital work. Positive factors associated with this willingness included being an employee (odds ratio [OR] 3.12, 95% CI 1.59-6.45; P=.001), being health professionals (OR 3.32, 95% CI 1.49-7.82; P=.004), longer screen hours (OR 1.09, 95% CI 1.03-1.15; P=.002), and higher depression levels (OR 1.20, 95% CI 1.01-1.44; P=.04). Conversely, negatively associated factors included older age (OR 0.87, 95% CI 0.81-0.94; P=.001), extroversion (OR 0.66, 95% CI 0.51-0.86; P=.002), higher eHealth literacy (OR 0.96, 95% CI 0.93-0.98; P<.001), perceived greater susceptibility to COVID-19 (OR 0.84, 95% CI 0.74-0.96; P=.009), residence in a high-severity COVID-19 community (OR 0.73, 95% CI 0.63-0.84; P<.001), having infected individuals in the immediate social circle (OR 0.64, 95% CI 0.46-0.88; P=.006), higher BMI (OR 0.94, 95% CI 0.90-0.99; P=.02), feelings of being out of control (OR 0.96, 95% CI 0.93-0.98; P=.002), and higher fear of COVID-19 (OR 0.96, 95% CI 0.94-0.98; P=.001). In addition, a moderating effect of screen hour level (high: >8 h/d; low: ≤8 h/d) influenced the association among 10 factors related to willingness to sustain pandemic-induced digital work, including age, education level, household size, needs for regular medical care, BMI, frequency of both vigorous and moderate physical activities, perceived COVID-19 severity, immediate social circle COVID-19 presence, and fear of COVID-19 (all P values for interaction <.05)., Conclusions: The substantial willingness of the general population to sustain digital work after the pandemic highlights the need for robust telework infrastructure, thorough monitoring of adverse health outcomes, and the potential to expand telehealth services among this group. The identification of factors influencing this willingness and the moderating role of screen hours inform the development of personalized strategies to enhance digital work acceptance where needed., (©Jiaying Li, Daniel Yee Tak Fong, Mandy Man Ho, Edmond Pui Hang Choi, Kris Yuet Wan Lok, Jung Jae Lee, WenJie Duan, Janet Yuen Ha Wong, Chia-Chin Lin. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 28.05.2024.)

Background: In 2023, the United States experienced its highest- recorded number of suicides, exceeding 50,000 deaths. In the realm of psychiatric disorders, major depressive disorder stands out as the most common issue, affecting 15% to 17% of the population and carrying a notable suicide risk of approximately 15%. However, not everyone with depression has suicidal thoughts. While "suicidal depression" is not a clinical diagnosis, it may be observed in daily life, emphasizing the need for awareness., Objective: This study aims to examine the dynamics, emotional tones, and topics discussed in posts within the r/Depression subreddit, with a specific focus on users who had also engaged in the r/SuicideWatch community. The objective was to use natural language processing techniques and models to better understand the complexities of depression among users with potential suicide ideation, with the goal of improving intervention and prevention strategies for suicide., Methods: Archived posts were extracted from the r/Depression and r/SuicideWatch Reddit communities in English spanning from 2019 to 2022, resulting in a final data set of over 150,000 posts contributed by approximately 25,000 unique overlapping users. A broad and comprehensive mix of methods was conducted on these posts, including trend and survival analysis, to explore the dynamic of users in the 2 subreddits. The BERT family of models extracted features from data for sentiment and thematic analysis., Results: On August 16, 2020, the post count in r/SuicideWatch surpassed that of r/Depression. The transition from r/Depression to r/SuicideWatch in 2020 was the shortest, lasting only 26 days. Sadness emerged as the most prevalent emotion among overlapping users in the r/Depression community. In addition, physical activity changes, negative self-view, and suicidal thoughts were identified as the most common depression symptoms, all showing strong positive correlations with the emotion tone of disappointment. Furthermore, the topic "struggles with depression and motivation in school and work" (12%) emerged as the most discussed topic aside from suicidal thoughts, categorizing users based on their inclination toward suicide ideation., Conclusions: Our study underscores the effectiveness of using natural language processing techniques to explore language markers and patterns associated with mental health challenges in online communities like r/Depression and r/SuicideWatch. These insights offer novel perspectives distinct from previous research. In the future, there will be potential for further refinement and optimization of machine classifications using these techniques, which could lead to more effective intervention and prevention strategies., (©Jianfeng Zhu, Ruoming Jin, Deric R Kenne, NhatHai Phan, Wei-Shinn Ku. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 20.05.2024.)

Background: Whether and how the uncertainty about a public health crisis should be communicated to the general public have been important and yet unanswered questions arising over the past few years. As the most threatening contemporary public health crisis, the COVID-19 pandemic has renewed interest in these unresolved issues by both academic scholars and public health practitioners., Objective: The aim of this study was to investigate the impact of communicating uncertainty about COVID-19-related threats and solutions on individuals' risk perceptions and misinformation vulnerability, as well as the sequential impact of these effects on health information processing and preventative behavioral intentions., Methods: A 2×2 (threat uncertainty [presence vs absence]×solution uncertainty [presence vs absence]) full-fractional between-subjects online experiment was conducted with 371 Chinese adults. Focusing on the discussion of whether the asymptomatic cases detected during the COVID-19 pandemic would further lead to an uncontrolled pandemic, news articles were manipulated in terms of whether the infectiousness of asymptomatic cases and the means to control the transmission are presented in terms of their certainty or uncertainty. Participants were randomly assigned to one of the four experimental conditions, being instructed to read one news article. After reading the news article assigned, participants were asked to respond to a series of questions to assess their cognitive and behavioral responses., Results: Individuals were more susceptible to believing false COVID-19-related information when a certain threat and uncertain solution were framed in the news article. Moreover, individuals' perceptions of crisis severity increased when exposed to news information containing uncertain solutions. Both misinformation vulnerability and perceived severity were positively associated with information processing. Information seeking was positively associated with protective behavioral intention, whereas information avoidance was negatively associated with protective behavioral intention., Conclusions: Our findings imply that uncertainty, depending on its aspect, can be effectively communicated to the public during an emerging public health crisis. These results have theoretical and practical implications for health communicators and journalists. Given its limited influence on individuals' cognitive and behavioral responses, uncertainty related to a health threat should be disseminated to meet the public's expectation of information transparency. However, caution is advised when communicating uncertainty related to potential solutions, as this factor exhibited a mixed impact on individual responses during a crisis., (©Rui Zhao, Xuerong Lu, Jiayi Yang, Biao Li. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 14.05.2024.)

Background: In the last 2 decades, new technologies have emerged in health care. The COVID-19 pandemic further accelerated the adoption of technology by both health care professionals and patients. These technologies create remote care practices that bring several benefits to the health care system: easier access to care, improved communication with physicians, and greater continuity of care. However, disparities in the acceptance and use of telehealth tools still exist among patients. These tools also disrupt conventional medical practices and prompt a new reassessment of the perceptions of distance and proximity as physical (ie, time and space dimensions) and nonphysical (ie, behavioral dimensions) concepts. The reasons why patients do or do not adopt telehealth tools for their care and therefore their perspectives on telehealth remain unanswered questions., Objective: We explored the barriers as well as the motivations for patients to adopt telehealth tools. We specifically focused on the social representations of telehealth to establish a comprehensive conceptual framework to get a better understanding of how telehealth is perceived by patients., Methods: This study uses a qualitative design through in-depth individual interviews. Participants were recruited using a convenience sampling method with balanced consideration of gender, age, location (urban/rural), and socioeconomic background. After collecting informed consent, interviews were transcribed and analyzed using the thematic analysis methodology., Results: We conducted 14 interviews, with which data saturation was reached. The 2 main opposed dimensions, perceived proximity and distance, emerged as an essential structure for understanding the social representations of telehealth. A logic of engagement versus hostility emerged as the main tension in adopting telehealth, almost ideological. Interestingly, practical issues emerged regarding the adoption of telehealth: A logic of integration was opposed to a logic of constraints. Altogether, those dimensions enabled us to conceptualize a semiotic square, providing 4 categories with a coherent body of social representations. Due to the dynamic nature of these representations, we proposed 2 "paths" through which adherence to telehealth may improve., Conclusions: Our semiotic square illustrating patients' adherence to telehealth differentiates socially beneficial versus socially dangerous considerations and pragmatic from ideological postures. It shows how crucial it is to consider perceived distance and proximity to better understand barriers and motivations to adopting telehealth. These representations can also be considered as leverage that could be modified to encourage the step-by-step adhesion process. Even if reducing the perceived temporal distance to in-person meeting and enhancing the perceived proximity of access to care may be seen as efficient ways to adopt telehealth tools, telehealth can also be perceived as a care practice that threatens the patient-physician relationship. The patient-oriented perceived value turns out to be critical in the future development of and adherence to telehealth tools., (©Amélie Loriot, Fabrice Larceneux, Valérie Guillard, Jean-Philippe Bertocchio. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 26.04.2024.)

Background: Monitoring the psychological conditions of social media users during rapidly developing public health crises, such as the COVID-19 pandemic, using their posts on social media has rapidly gained popularity as a relatively easy and cost-effective method. However, the characteristics of individuals who created these posts are largely unknown, making it difficult to identify groups of individuals most affected by such crises. In addition, large annotated data sets for mental health conditions are not easily available, and thus, supervised machine learning algorithms can be infeasible or too costly., Objective: This study proposes a machine learning framework for the real-time surveillance of mental health conditions that does not require extensive training data. Using survey-linked tweets, we tracked the level of emotional distress during the COVID-19 pandemic by the attributes and psychological conditions of social media users in Japan., Methods: We conducted online surveys of adults residing in Japan in May 2022 and collected their basic demographic information, socioeconomic status, and mental health conditions, along with their Twitter handles (N=2432). We computed emotional distress scores for all the tweets posted by the study participants between January 1, 2019, and May 30, 2022 (N=2,493,682) using a semisupervised algorithm called latent semantic scaling (LSS), with higher values indicating higher levels of emotional distress. After excluding users by age and other criteria, we examined 495,021 (19.85%) tweets generated by 560 (23.03%) individuals (age 18-49 years) in 2019 and 2020. We estimated fixed-effect regression models to examine their emotional distress levels in 2020 relative to the corresponding weeks in 2019 by the mental health conditions and characteristics of social media users., Results: The estimated level of emotional distress of our study participants increased in the week when school closure started (March 2020), and it peaked at the beginning of the state of emergency (estimated coefficient=0.219, 95% CI 0.162-0.276) in early April 2020. Their level of emotional distress was unrelated to the number of COVID-19 cases. We found that the government-induced restrictions disproportionately affected the psychological conditions of vulnerable individuals, including those with low income, precarious employment, depressive symptoms, and suicidal ideation., Conclusions: This study establishes a framework to implement near-real-time monitoring of the emotional distress level of social media users, highlighting a great potential to continuously monitor their well-being using survey-linked social media posts as a complement to administrative and large-scale survey data. Given its flexibility and adaptability, the proposed framework is easily extendable for other purposes, such as detecting suicidality among social media users, and can be used on streaming data for continuous measurement of the conditions and sentiment of any group of interest., (©Michiko Ueda, Kohei Watanabe, Hajime Sueki. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 16.03.2023.)

Background: Throughout the COVID-19 pandemic, US Centers for Disease Control and Prevention policies on face mask use fluctuated. Understanding how public health communications evolve around key policy decisions may inform future decisions on preventative measures by aiding the design of communication strategies (eg, wording, timing, and channel) that ensure rapid dissemination and maximize both widespread adoption and sustained adherence., Objective: We aimed to assess how sentiment on masks evolved surrounding 2 changes to mask guidelines: (1) the recommendation for mask use on April 3, 2020, and (2) the relaxation of mask use on May 13, 2021., Methods: We applied an interrupted time series method to US Twitter data surrounding each guideline change. Outcomes were changes in the (1) proportion of positive, negative, and neutral tweets and (2) number of words within a tweet tagged with a given emotion (eg, trust). Results were compared to COVID-19 Twitter data without mask keywords for the same period., Results: There were fewer neutral mask-related tweets in 2020 (β=-3.94 percentage points, 95% CI -4.68 to -3.21; P<.001) and 2021 (β=-8.74, 95% CI -9.31 to -8.17; P<.001). Following the April 3 recommendation (β=.51, 95% CI .43-.59; P<.001) and May 13 relaxation (β=3.43, 95% CI 1.61-5.26; P<.001), the percent of negative mask-related tweets increased. The quantity of trust-related terms decreased following the policy change on April 3 (β=-.004, 95% CI -.004 to -.003; P<.001) and May 13 (β=-.001, 95% CI -.002 to 0; P=.008)., Conclusions: The US Twitter population responded negatively and with less trust following guideline shifts related to masking, regardless of whether the guidelines recommended or relaxed mask usage. Federal agencies should ensure that changes in public health recommendations are communicated concisely and rapidly., (©Divya Ramjee, Catherine C Pollack, Marie-Laure Charpignon, Shagun Gupta, Jessica Malaty Rivera, Ghinwa El Hayek, Adam G Dunn, Angel N Desai, Maimuna S Majumder. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 27.02.2023.)

Background: Chatbots have become a promising tool to support public health initiatives. Despite their potential, little research has examined how individuals interacted with chatbots during the COVID-19 pandemic. Understanding user-chatbot interactions is crucial for developing services that can respond to people's needs during a global health emergency., Objective: This study examined the COVID-19 pandemic-related topics online users discussed with a commercially available social chatbot and compared the sentiment expressed by users from 5 culturally different countries., Methods: We analyzed 19,782 conversation utterances related to COVID-19 covering 5 countries (the United States, the United Kingdom, Canada, Malaysia, and the Philippines) between 2020 and 2021, from SimSimi, one of the world's largest open-domain social chatbots. We identified chat topics using natural language processing methods and analyzed their emotional sentiments. Additionally, we compared the topic and sentiment variations in the COVID-19-related chats across countries., Results: Our analysis identified 18 emerging topics, which could be categorized into the following 5 overarching themes: "Questions on COVID-19 asked to the chatbot" (30.6%), "Preventive behaviors" (25.3%), "Outbreak of COVID-19" (16.4%), "Physical and psychological impact of COVID-19" (16.0%), and "People and life in the pandemic" (11.7%). Our data indicated that people considered chatbots as a source of information about the pandemic, for example, by asking health-related questions. Users turned to SimSimi for conversation and emotional messages when offline social interactions became limited during the lockdown period. Users were more likely to express negative sentiments when conversing about topics related to masks, lockdowns, case counts, and their worries about the pandemic. In contrast, small talk with the chatbot was largely accompanied by positive sentiment. We also found cultural differences, with negative words being used more often by users in the United States than by those in Asia when talking about COVID-19., Conclusions: Based on the analysis of user-chatbot interactions on a live platform, this work provides insights into people's informational and emotional needs during a global health crisis. Users sought health-related information and shared emotional messages with the chatbot, indicating the potential use of chatbots to provide accurate health information and emotional support. Future research can look into different support strategies that align with the direction of public health policy., (©Hyojin Chin, Gabriel Lima, Mingi Shin, Assem Zhunis, Chiyoung Cha, Junghoi Choi, Meeyoung Cha. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 27.01.2023.)

Background: During the COVID-19 pandemic, there have been increased reports of racial biases against Asian American and Native Hawaiian and Pacific Islander individuals. However, the extent to which different Asian American and Native Hawaiian and Pacific Islander groups perceive and experience (firsthand or as a witness to such experiences) how COVID-19 has negatively affected people of their race has not received much attention., Objective: This study used data from the COVID-19 Effects on the Mental and Physical Health of Asian Americans and Pacific Islanders Survey Study (COMPASS), a nationwide, multilingual survey, to empirically examine COVID-19-related racial bias beliefs among Asian American and Native Hawaiian and Pacific Islander individuals and the factors associated with these beliefs., Methods: COMPASS participants were Asian American and Native Hawaiian and Pacific Islander adults who were able to speak English, Chinese (Cantonese or Mandarin), Korean, Samoan, or Vietnamese and who resided in the United States during the time of the survey (October 2020 to May 2021). Participants completed the survey on the web, via phone, or in person. The Coronavirus Racial Bias Scale (CRBS) was used to assess COVID-19-related racial bias beliefs toward Asian American and Native Hawaiian and Pacific Islander individuals. Participants were asked to rate the degree to which they agreed with 9 statements on a 5-point Likert scale (ie, 1=strongly disagree to 5=strongly agree). Multivariable linear regression was used to examine the associations between demographic, health, and COVID-19-related characteristics and perceived racial bias., Results: A total of 5068 participants completed the survey (mean age 45.4, SD 16.4 years; range 18-97 years). Overall, 73.97% (3749/5068) agreed or strongly agreed with ≥1 COVID-19-related racial bias belief in the past 6 months (during the COVID-19 pandemic). Across the 9 racial bias beliefs, participants scored an average of 2.59 (SD 0.96, range 1-5). Adjusted analyses revealed that compared with Asian Indians, those who were ethnic Chinese, Filipino, Hmong, Japanese, Korean, Vietnamese, and other or multicultural had significantly higher mean CRBS scores, whereas no significant differences were found among Native Hawaiian and Pacific Islander individuals. Nonheterosexual participants had statistically significant and higher mean CRBS scores than heterosexual participants. Compared with participants aged ≥60 years, those who were younger (aged <30, 30-39, 40-49, and 50-59 years) had significantly higher mean CRBS scores. US-born participants had significantly higher mean CRBS scores than foreign-born participants, whereas those with limited English proficiency (relative to those reporting no limitation) had lower mean CRBS scores., Conclusions: Many COMPASS participants reported racial bias beliefs because of the COVID-19 pandemic. Relevant sociodemographic contexts and pre-existing and COVID-19-specific factors across individual, community, and society levels were associated with the perceived racial bias of being Asian during the pandemic. The findings underscore the importance of addressing the burden of racial bias on Asian American and Native Hawaiian and Pacific Islander communities among other COVID-19-related sequelae., (©Van Ta Park, Janice Y Tsoh, Marcelle Dougan, Bora Nam, Marian Tzuang, Quyen N Vuong, Joon Bang, Oanh L Meyer. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 09.08.2022.)

Background: In the United States, racial and ethnic minorities are disproportionately affected by COVID-19, with persistent social and structural factors contributing to these disparities. At the intersection of race/ethnicity and gender, women of color may be disadvantaged in terms of COVID-19 outcomes due to their role as essential workers, their higher prevalence of pre-existing conditions, their increased stress and anxiety from the loss of wages and caregiving, and domestic violence., Objective: The purpose of this study is to examine racial and ethnic differences in the prevalence of COVID-19 outcomes, stressors, fear, and prevention behaviors among adult women residing in the United States., Methods: Between May and June 2020, women were recruited into the Capturing Women's Experiences in Outbreak and Pandemic Environments (COPE) Study, a web-based cross-sectional study, using advertisements on Facebook; 491 eligible women completed a self-administered internet-based cross-sectional survey. Descriptive statistics were used to examine racial and ethnic differences (White; Asian; Native Hawaiian or other Pacific Islander; Black; Hispanic, Latina, or Spanish Origin; American Indian or Alaskan Native; multiracial or some other race, ethnicity, or origin) on COVID-19 outcomes, stressors, fear, and prevention behaviors., Results: Among our sample of women, 16% (73/470) reported COVID-19 symptoms, 22% (18/82) were concerned about possible exposure from the people they knew who tested positive for COVID-19, and 51.4% (227/442) knew where to get tested; yet, only 5.8% (27/469) had been tested. Racial/ethnic differences were observed, with racial/ethnic minority women being less likely to know where to get tested. Significant differences in race/ethnicity were observed for select stressors (food insecurity, not enough money, homeschooling children, unable to have a doctor or telemedicine appointment) and prevention behaviors (handwashing with soap, self-isolation if sick, public glove use, not leaving home for any activities). Although no racial/ethnic differences emerged from the Fear of COVID-19 Scale, significant racial/ethnic differences were observed for some of the individual scale items (eg, being afraid of getting COVID-19, sleep loss, and heart racing due to worrying about COVID-19)., Conclusions: The low prevalence of COVID-19 testing and knowledge of where to get tested indicate a critical need to expand testing for women in the United States, particularly among racial/ethnic minority women. Although the overall prevalence of engagement in prevention behaviors was high, targeted education and promotion of prevention activities are warranted in communities of color, particularly with consideration for stressors and adverse mental health., (©Jamila K Stockman, Brittany A Wood, Katherine M Anderson. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 12.07.2021.)

Background: Overcoming the COVID-19 crisis requires new ideas and strategies for online communication of personal medical information and patient empowerment. Rapid testing of a large number of subjects is essential for monitoring and delaying the spread of SARS-CoV-2 in order to mitigate the pandemic's consequences. People who do not know that they are infected may not stay in quarantine and, thus, risk infecting others. Unfortunately, the massive number of COVID-19 tests performed is challenging for both laboratories and the units that conduct throat swabs and communicate the results., Objective: The goal of this study was to reduce the communication burden for health care professionals. We developed a secure and easy-to-use tracking system to report COVID-19 test results online that is simple to understand for the tested subjects as soon as these results become available. Instead of personal calls, the system updates the status and the results of the tests automatically. This aims to reduce the delay when informing testees about their results and, consequently, to slow down the virus spread., Methods: The application in this study draws on an existing tracking tool. With this open-source and browser-based online tracking system, we aim to minimize the time required to inform the tested person and the testing units (eg, hospitals or the public health care system). The system can be integrated into the clinical workflow with very modest effort and avoids excessive load to telephone hotlines., Results: The test statuses and results are published on a secured webpage, enabling regular status checks by patients; status checks are performed without the use of smartphones, which has some importance, as smartphone usage diminishes with age. Stress tests and statistics show the performance of our software. CTest is currently running at two university hospitals in Germany-University Hospital Ulm and University Hospital Tübingen-with thousands of tests being performed each week. Results show a mean number of 10 (SD 2.8) views per testee., Conclusions: CTest runs independently of existing infrastructures, aims at straightforward integration, and aims for the safe transmission of information. The system is easy to use for testees. QR (Quick Response) code links allow for quick access to the test results. The mean number of views per entry indicates a reduced amount of time for both health care professionals and testees. The system is quite generic and can be extended and adapted to other communication tasks., (©Gunnar Völkel, Axel Fürstberger, Julian D Schwab, Silke D Werle, Nensi Ikonomi, Thomas Gscheidmeier, Johann M Kraus, Alexander Groß, Martin Holderried, Julien Balig, Franz Jobst, Peter Kuhn, Klaus A Kuhn, Oliver Kohlbacher, Udo X Kaisers, Thomas Seufferlein, Hans A Kestler. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 07.06.2021.)

Background: As policy makers continue to shape the national and local responses to the COVID-19 pandemic, the information they choose to share and how they frame their content provide key insights into the public and health care systems., Objective: We examined the language used by the members of the US House and Senate during the first 10 months of the COVID-19 pandemic and measured content and sentiment based on the tweets that they shared., Methods: We used Quorum (Quorum Analytics Inc) to access more than 300,000 tweets posted by US legislators from January 1 to October 10, 2020. We used differential language analyses to compare the content and sentiment of tweets posted by legislators based on their party affiliation., Results: We found that health care-related themes in Democratic legislators' tweets focused on racial disparities in care (odds ratio [OR] 2.24, 95% CI 2.22-2.27; P<.001), health care and insurance (OR 1.74, 95% CI 1.7-1.77; P<.001), COVID-19 testing (OR 1.15, 95% CI 1.12-1.19; P<.001), and public health guidelines (OR 1.25, 95% CI 1.22-1.29; P<.001). The dominant themes in the Republican legislators' discourse included vaccine development (OR 1.51, 95% CI 1.47-1.55; P<.001) and hospital resources and equipment (OR 1.22, 95% CI 1.18-1.25). Nonhealth care-related topics associated with a Democratic affiliation included protections for essential workers (OR 1.55, 95% CI 1.52-1.59), the 2020 election and voting (OR 1.31, 95% CI 1.27-1.35), unemployment and housing (OR 1.27, 95% CI 1.24-1.31), crime and racism (OR 1.22, 95% CI 1.18-1.26), public town halls (OR 1.2, 95% CI 1.16-1.23), the Trump Administration (OR 1.22, 95% CI 1.19-1.26), immigration (OR 1.16, 95% CI 1.12-1.19), and the loss of life (OR 1.38, 95% CI 1.35-1.42). The themes associated with the Republican affiliation included China (OR 1.89, 95% CI 1.85-1.92), small business assistance (OR 1.27, 95% CI 1.23-1.3), congressional relief bills (OR 1.23, 95% CI 1.2-1.27), press briefings (OR 1.22, 95% CI 1.19-1.26), and economic recovery (OR 1.2, 95% CI 1.16-1.23)., Conclusions: Divergent language use on social media corresponds to the partisan divide in the first several months of the course of the COVID-19 public health crisis., (©Sharath Chandra Guntuku, Jonathan Purtle, Zachary F Meisel, Raina M Merchant, Anish Agarwal. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 03.06.2021.)

Background: In the face of the COVID-19 pandemic, the German government and the 16 German federal states implemented a variety of nonpharmaceutical interventions (NPIs) to decelerate the spread of the SARS-CoV-2 virus and thus prevent a collapse of the health care system. These measures comprised, among others, social distancing, the temporary closure of shops and schools, and a ban of large public gatherings and meetings with people not living in the same household., Objective: It is fair to assume that the issued NPIs have heavily affected social life and psychological functioning. We therefore aimed to examine possible effects of this lockdown in conjunction with daily new infections and the state of the national economy on people's interests, motives, and other psychological states., Methods: We derived 249 keywords from the Google Trends database, tapping into 27 empirically and rationally selected psychological domains. To overcome issues with reliability and specificity of individual indicator variables, broad factors were derived by means of time series factor analysis. All domains were subjected to a change point analysis and time series regression analysis with infection rates, NPIs, and the state of the economy as predictors. All keywords and analyses were preregistered prior to analysis., Results: With the pandemic arriving in Germany, significant increases in people's search interests were observed in virtually all domains. Although most of the changes were short-lasting, each had a distinguishable onset during the lockdown period. Regression analysis of the Google Trends data confirmed pronounced autoregressive effects for the investigated variables, while forecasting by means of the tested predictors (ie, daily new infections, NPIs, and the state of economy) was moderate at best., Conclusions: Our findings indicate that people's interests, motives, and psychological states are heavily affected in times of crisis and lockdown. Specifically, disease- and virus-related domains (eg, pandemic disease, symptoms) peaked early, whereas personal health strategies (eg, masks, homeschooling) peaked later during the lockdown. Domains addressing social life and psychosocial functioning showed long-term increases in public interest. Renovation was the only domain to show a decrease in search interest with the onset of the lockdown. As changes in search behavior are consistent over multiple domains, a Google Trends analysis may provide information for policy makers on how to adapt and develop intervention, information, and prevention strategies, especially when NPIs are in effect., (©Dominik Rotter, Philipp Doebler, Florian Schmitz. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 01.06.2021.)

Background: Frontline health care workers are experiencing a myriad of physical and psychosocial challenges amid the COVID-19 pandemic. There is growing recognition that digital technologies have the potential to improve the well-being of frontline workers. However, there has been limited development of wellness interventions using mobile health (mHealth) technology. More importantly, little research has been conducted on how frontline workers perceive mHealth-based support to promote their well-being., Objective: This study aimed to explore frontline workers' experience of conventional psychological wellness programs and their perceptions of the usefulness of mHealth apps and features for promoting well-being. It also sought to identify factors that could potentially influence uptake and retention of an mHealth-based wellness program., Methods: We conducted semistructured interviews using purposive sampling with frontline workers involved in the COVID-19 response. Various visual materials, collated from existing mHealth app features, were presented to facilitate discussion. Interviews were audio-recorded and transcribed verbatim. Thematic analysis based on grounded theory was undertaken. Themes were subsequently mapped to key nudge strategies-those commonly used for mHealth development-to assess participants' preferences for particular features and their reasoning., Results: A total of 42 frontline workers participated in 12 one-on-one interviews or focus group discussions. Frontline workers generally had a limited ability to identify their own psychological problems and liked the reminders functionality of the app to track their mood over time. A personalized goal-setting feature (ie, tailoring) and in-app resources were generally valued, while frequent coaching and messages (ie, framing) were seen as a distraction. The majority of participants desired a built-in chat function with a counselor (ie, guidance) for reasons of accessibility and protection of privacy. Very few participants appreciated a gamification function. Frontline workers commonly reported the need for ongoing social support and desired access to an in-app peer support community (ie, social influence). There were, however, concerns regarding potential risks from virtual peer interactions. Intrinsic motivational factors, mHealth app technicality, and tangible rewards were identified as critical for uptake and retention., Conclusions: Our study highlights the potential of mHealth apps with relevant features to be used as wellness tools by frontline health care workers. Future work should focus on developing a nonintrusive and personalized mHealth app with in-app counseling, peer support to improve well-being, and tangible and extrinsic rewards to foster continued use., (©Sungwon Yoon, Hendra Goh, Gayathri Devi Nadarajan, Sharon Sung, Irene Teo, Jungup Lee, Marcus E H Ong, Nicholas Graves, Tess Lin Teo. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 31.05.2021.)

Background: Due to widespread SARS-CoV-2 infection, an emergency homeschooling plan was rigorously implemented throughout China., Objective: This study aimed to investigate the experiences and attitudes of elementary school students and their parents (two generations from the same family) toward online learning in China during the pandemic., Methods: A 16-item questionnaire was distributed at the 10-day and 40-day marks after the start of the first online course to 867 parent-child pairs and 141 parent-child pairs, respectively. The questionnaire was comprised of questions pertaining to course and homework completeness, effectiveness, reliability, and abundance as well as the students' enthusiasm for taking part in online classes and their satisfaction with the courses., Results: Our findings indicate that 90.7% (786/867) of students exhibited high or moderate enthusiasm for participating in online classes. However, most students performed poorly in online learning classes and after-school homework. With regard to satisfaction, parents' and students' average scores were 7.35 and 7.25, respectively (10-point scoring system). During the second stage of this study, parents' positive evaluations for online learning declined, including those for the effectiveness and reliability of the courses. Furthermore, the proportion of students who completed the courses and homework on time decreased; this difference proved statistically significant (P=.047). The parents' and students' overall satisfaction with online learning also declined during the second stage (parents: 7.21; students: 7.23); however, the difference in overall satisfaction between the two stages was not statistically significant (parents: P=.53; students: P=.60). Several of the parents (315/867, 36.2%) indicated that assisting with and supervising the students' online learning resulted in increased stress. Further, 36% of parents expressed dissatisfaction with or provided suggestions for online learning; most parents and students hoped to return to face-to-face classes (parents: 823/867, 94.9%; students: 811/867, 93.5%). Finally, our results presented the following six main issues that parents were the most concerned about: (1) disappointment regarding timely interaction in courses; (2) apprehensiveness about students' understanding of the course; (3) the increased burden of annoying adult responsibilities; (4) concern about children's eyesight; (5) the idea that teachers' explanations were not detailed enough; and (6) concerns about the decline of students' interest in and attention toward online courses., Conclusions: Online learning can prevent the spread of infectious diseases while still allowing elementary school students to attain knowledge. However, in our study, children's completion of the courses and homework were not satisfactory. Furthermore, their parents often experienced stress and had many concerns and complaints. Measures such as increasing the interactivity of the courses and prohibiting teachers from assigning tasks to parents could improve the effectiveness of these courses and the mental health of parents and students., (©Shu Cui, Chao Zhang, Shijiang Wang, Xingong Zhang, Lei Wang, Ling Zhang, Qiuyu Yuan, Cui Huang, Fangshuo Cheng, Kai Zhang, Xiaoqin Zhou. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 19.05.2021.)

Background: COVID-19 is one of the greatest threats to human beings in terms of health care, economy, and society in recent history. Up to this moment, there have been no signs of remission, and there is no proven effective cure. Vaccination is the primary biomedical preventive measure against the novel coronavirus. However, public bias or sentiments, as reflected on social media, may have a significant impact on the progression toward achieving herd immunity., Objective: This study aimed to use machine learning methods to extract topics and sentiments relating to COVID-19 vaccination on Twitter., Methods: We collected 31,100 English tweets containing COVID-19 vaccine-related keywords between January and October 2020 from Australian Twitter users. Specifically, we analyzed tweets by visualizing high-frequency word clouds and correlations between word tokens. We built a latent Dirichlet allocation (LDA) topic model to identify commonly discussed topics in a large sample of tweets. We also performed sentiment analysis to understand the overall sentiments and emotions related to COVID-19 vaccination in Australia., Results: Our analysis identified 3 LDA topics: (1) attitudes toward COVID-19 and its vaccination, (2) advocating infection control measures against COVID-19, and (3) misconceptions and complaints about COVID-19 control. Nearly two-thirds of the sentiments of all tweets expressed a positive public opinion about the COVID-19 vaccine; around one-third were negative. Among the 8 basic emotions, trust and anticipation were the two prominent positive emotions observed in the tweets, while fear was the top negative emotion., Conclusions: Our findings indicate that some Twitter users in Australia supported infection control measures against COVID-19 and refuted misinformation. However, those who underestimated the risks and severity of COVID-19 may have rationalized their position on COVID-19 vaccination with conspiracy theories. We also noticed that the level of positive sentiment among the public may not be sufficient to increase vaccination coverage to a level high enough to achieve vaccination-induced herd immunity. Governments should explore public opinion and sentiments toward COVID-19 and COVID-19 vaccination, and implement an effective vaccination promotion scheme in addition to supporting the development and clinical administration of COVID-19 vaccines., (©Stephen Wai Hang Kwok, Sai Kumar Vadde, Guanjin Wang. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 19.05.2021.)

Background: The rapid outbreak of COVID-19 around the world has adversely affected the mental health of the public. The prevalence of anxiety among the public has increased dramatically during the COVID-19 pandemic. However, there are few studies evaluating the effects of positive psychological responses and information-seeking behaviors on anxiety experienced among social media users during the COVID-19 pandemic., Objective: This study evaluated the prevalence of anxiety and its associated factors among WeChat users in mainland China during the early stages of the COVID-19 pandemic., Methods: From February 10 to February 24, 2020, a nationwide, web-based cross-sectional survey study was carried out using convenience sampling. Participants' levels of anxiety, positive psychological responses, and information-seeking behaviors were assessed. The survey was distributed among WeChat users via the WeChat smartphone platform. Chi-square tests and multivariable logistic regression analyses were performed to examine the factors associated with anxiety., Results: This study found that the prevalence of anxiety (Generalized Anxiety Disorder 7-item [GAD-7] scale score ≥7) among WeChat users in China was 17.96% (446/2483) during the early stages of the COVID-19 pandemic. Results of multivariable logistic regression analysis showed that information-seeking behaviors such as cannot stop searching for information on COVID-19, being concerned about the COVID-19 pandemic, and spending more than 1 hour per day consuming information about the pandemic were found to be associated with increased levels of anxiety. Additionally, participants who chose social media and commercial media as the primary sources to obtain information about the COVID-19 pandemic were found more likely to report anxiety. Conversely, participants who were confident or rational about the COVID-19 pandemic were less likely to report anxiety., Conclusions: This study found that positive psychological responses and information-seeking behaviors were closely associated with anxiety among WeChat users during the COVID-19 pandemic in China. It might be paramount to enhance mental well-being by helping people respond to the COVID-19 pandemic more rationally and positively in order to decrease symptoms of anxiety., (©Changqing Zou, Weiyu Zhang, Kristin Sznajder, Fengzhi Yang, Yajing Jia, Ruqing Ma, Can Cui, Xiaoshi Yang. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 17.05.2021.)

Background: The prevalence of depressive and anxiety symptoms in patients with COVID-19 is higher than usual. Previous studies have shown that there are drug-to-drug interactions between antiretroviral drugs and antidepressants. Therefore, an effective and safe treatment method was needed. Cognitive behavioral therapy (CBT) is the first-line psychological therapy in clinical treatment. Computerized CBT (cCBT) was proven to be an effective alternative to CBT and does not require face-to-face therapy between a therapist and the patient, which suited the COVID-19 pandemic response., Objective: This study aims to evaluate the efficacy of the cCBT program we developed in improving depressive and anxiety symptoms among patients with COVID-19., Methods: We customized a cCBT program focused on improving depressive and anxiety symptoms among patients with COVID-19, and then, we assessed its effectiveness. Screening was based on symptoms of depression or anxiety for patients who scored ≥7 on the Hamilton Depression Rating Scale (HAMD 17 ) or the Hamilton Anxiety Scale (HAMA). A total of 252 patients with COVID-19 at five sites were randomized into two groups: cCBT + treatment as usual (TAU; n=126) and TAU without cCBT (n=126). The cCBT + TAU group received the cCBT intervention program for 1 week. The primary efficacy measures were the HAMD 17 and HAMA scores. The secondary outcome measures were the Self-Rating Depression Scale (SDS), Self-Rating Anxiety Scale (SAS), and Athens Insomnia Scale (AIS). Assessments were carried out pre- and postintervention. The patients' symptoms of anxiety and depression in one of the centers were assessed again within 1 month after the postintervention assessment., Results: The cCBT + TAU group displayed a significantly decreased score on the HAMD 17 , HAMA, SDS, SAS, and AIS after the intervention compared to the TAU group (all P<.001). A mixed-effects repeated measures model revealed significant improvement in symptoms of depression (HAMD 17 and SDS scores, both P<.001), anxiety (HAMA and SAS scores, both P<.001), and insomnia (AIS score, P=.002) during the postintervention and follow-up periods in the cCBT + TAU group. Additionally, the improvement of insomnia among females (P=.14) and those with middle school education (P=.48) in the cCBT + TAU group showed no significant differences when compared to the TAU group., Conclusions: The findings of this study suggest that the cCBT program we developed was an effective nonpharmacological treatment for symptoms of anxiety, depression, and insomnia among patients with COVID-19. Further research is warranted to investigate the long-term effects of cCBT for symptoms of anxiety, depression, and insomnia in patients with COVID-19., Trial Registration: Chinese Clinical Trial Registry ChiCTR2000030084; http://www.chictr.org.cn/showprojen.aspx?proj=49952., (©Zhifen Liu, Dan Qiao, Yifan Xu, Wentao Zhao, Yang Yang, Dan Wen, Xinrong Li, Xiaoping Nie, Yongkang Dong, Shiyou Tang, Yi Jiang, Ying Wang, Juan Zhao, Yong Xu. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 14.05.2021.)

One of the most at-risk groups during the COVID-19 crisis is older adults, especially those who live in congregate living settings and seniors' care facilities, are immune-compromised, and/or have other underlying illnesses. Measures undertaken to contain the spread of the virus are far-reaching, and older adults were among the first groups to experience restrictions on face-to-face contact. Although reducing viral transmission is critical, physical distancing is associated with negative psychosocial implications, such as increased rates of depression and anxiety. Promising evidence suggests that participatory digital co-design, defined as the combination of user-centered design and community engagement models, is associated with increased levels of engagement with mobile technologies among individuals with mental health conditions. The COVID-19 pandemic has highlighted shortcomings of existing technologies and challenges in their uptake and usage; however, strategies such as co-design may be leveraged to address these challenges both in the adaptation of existing technologies and the development of new technologies. By incorporating these strategies, it is hoped that we can offset some of the negative mental health implications for older adults in the context of physical distancing both during and beyond the current pandemic., (©Theodore D Cosco, Karen Fortuna, Andrew Wister, Indira Riadi, Kevin Wagner, Andrew Sixsmith. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 06.05.2021.)

Background: The use of information and communication technologies (ICTs) to deliver mental health and addictions (MHA) services is a global priority, especially considering the urgent shift towards virtual delivery of care in response to the COVID-19 pandemic. It is important to monitor the evolving role of technology in MHA services. Given that MHA policy documents represent the highest level of priorities for a government's vision and strategy for mental health care, one starting point is to measure the frequency with which technology is mentioned and the terms used to describe its use in MHA policy documents (before, during, and after COVID-19). Yet, to our knowledge, no such review of the extent to which ICTs are referred to in Canadian MHA policy documents exists to date., Objective: The objective of this systematic policy review was to examine the extent to which technology is addressed in Canadian government-based MHA policy documents prior to the COVID-19 pandemic to establish a baseline for documenting change., Methods: We reviewed 22 government-based MHA policy documents, published between 2011 and 2019 by 13 Canadian provinces and territories. We conducted content analysis to synthesize the policy priorities addressed in these documents into key themes, and then systematically searched for and tabulated the use of 39 technology-related keywords (in English and French) to describe and compare jurisdictions., Results: Technology was addressed in every document, however, to a varying degree. Of the 39 searched keywords, we identified 22 categories of keywords pertaining to the use of technology to deliver MHA services and information. The 6 most common categories were tele (n=16/22), phone (n=12/22), tech (n=11/22), online (n=10/22), line (n=10/22), and web (n=10/22), with n being the number of policy documents in which the category was mentioned out of 22 documents. The use of terms referring to advanced technologies, such as virtual (n=6/22) and app (n= 4/22), were less frequent. Additionally, policy documents from some provinces and territories (eg, Alberta and Newfoundland and Labrador) mentioned a diverse range of ICTs, whereas others described only 1 form of ICT., Conclusions: This review indicates that technology has been given limited strategic attention in Canadian MHA policy. Policy makers may have limited knowledge on the evidence and potential of using technology in this field, highlighting the value for knowledge translation and collaborative initiatives among policy makers and researchers. The development of a pan-Canadian framework for action addressing the integration and coordination of technology in mental health services can also guide initiatives in this field. Our findings provide a prepandemic baseline and replicable methods to monitor how the use of technology-supported services and innovations emerge relative to other priorities in MHA policy during and after the COVID-19 pandemic., (©Shalini Lal, Lyna Siafa, Hajin Lee, Carol E Adair. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 05.05.2021.)

Background: Holding conspiracy beliefs regarding the COVID-19 pandemic in the United States has been associated with reductions in both actions to prevent the spread of the infection (eg, mask wearing) and intentions to accept a vaccine when one becomes available. Patterns of media use have also been associated with acceptance of COVID-19 conspiracy beliefs. Here we ask whether the type of media on which a person relies increased, decreased, or had no additional effect on that person's COVID-19 conspiracy beliefs over a 4-month period., Objective: We used panel data to explore whether use of conservative and social media in the United States, which were previously found to be positively related to holding conspiracy beliefs about the origins and prevention of COVID-19, were associated with a net increase in the strength of those beliefs from March to July of 2020. We also asked whether mainstream news sources, which were previously found to be negatively related to belief in pandemic-related conspiracies, were associated with a net decrease in the strength of such beliefs over the study period. Additionally, we asked whether subsequent changes in pandemic conspiracy beliefs related to the use of media were also related to subsequent mask wearing and vaccination intentions., Methods: A survey that we conducted with a national US probability sample in March of 2020 and again in July with the same 840 respondents assessed belief in pandemic-related conspiracies, use of various types of media information sources, actions taken to prevent the spread of the disease and intentions to vaccinate, and various demographic characteristics. Change across the two waves was analyzed using path analytic techniques., Results: We found that conservative media use predicted an increase in conspiracy beliefs (β=.17, 99% CI .10-.25) and that reliance on mainstream print predicted a decrease in their belief (β=-.08, 99% CI -.14 to -.02). Although many social media platforms reported downgrading or removing false or misleading content, ongoing use of such platforms by respondents predicted growth in conspiracy beliefs as well (β=.072, 99% CI .018-.123). Importantly, conspiracy belief changes related to media use between the two waves of the study were associated with the uptake of mask wearing and changes in vaccination intentions in July. Unlike other media, use of mainstream broadcast television predicted greater mask wearing (β=.17, 99% CI .09-.26) and vaccination intention (β=.08, 95% CI .02-.14), independent of conspiracy beliefs., Conclusions: The findings point to the need for greater efforts on the part of commentators, reporters, and guests on conservative media to report verifiable information about the pandemic. The results also suggest that social media platforms need to be more aggressive in downgrading, blocking, and counteracting claims about COVID-19 vaccines, claims about mask wearing, and conspiracy beliefs that have been judged problematic by public health authorities., (©Daniel Romer, Kathleen Hall Jamieson. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 27.04.2021.)

Background: Communicating scientific uncertainty about public health threats such as COVID-19 is an ethically desirable task endorsed by expert guidelines on crisis communication. However, the communication of scientific uncertainty is challenging because of its potential to promote ambiguity aversion-a well-described syndrome of negative psychological responses consisting of heightened risk perceptions, emotional distress, and decision avoidance. Communication strategies that can inform the public about scientific uncertainty while mitigating ambiguity aversion are a critical unmet need., Objective: This study aimed to evaluate whether an "uncertainty-normalizing" communication strategy-aimed at reinforcing the expected nature of scientific uncertainty about the COVID-19 pandemic-can reduce ambiguity aversion, and to compare its effectiveness to conventional public communication strategies aimed at promoting hope and prosocial values., Methods: In an online factorial experiment conducted from May to June 2020, a national sample of 1497 US adults read one of five versions of an informational message describing the nature, transmission, prevention, and treatment of COVID-19; the versions varied in level of expressed scientific uncertainty and supplemental focus (ie, uncertainty-normalizing, hope-promoting, and prosocial). Participants then completed measures of cognitive, emotional, and behavioral manifestations of ambiguity aversion (ie, perceived likelihood of getting COVID-19, COVID-19 worry, and intentions for COVID-19 risk-reducing behaviors and vaccination). Analyses assessed (1) the extent to which communicating uncertainty produced ambiguity-averse psychological responses; (2) the comparative effectiveness of uncertainty-normalizing, hope-promoting, and prosocial communication strategies in reducing ambiguity-averse responses; and (3) potential moderators of the effects of alternative uncertainty communication strategies., Results: The communication of scientific uncertainty about the COVID-19 pandemic increased perceived likelihood of getting COVID-19 and worry about COVID-19, consistent with ambiguity aversion. However, it did not affect intentions for risk-reducing behaviors or vaccination. The uncertainty-normalizing strategy reduced these aversive effects of communicating scientific uncertainty, resulting in levels of both perceived likelihood of getting COVID-19 and worry about COVID-19 that did not differ from the control message that did not communicate uncertainty. In contrast, the hope-promoting and prosocial strategies did not decrease ambiguity-averse responses to scientific uncertainty. Age and political affiliation, respectively, moderated the effects of uncertainty communication strategies on intentions for COVID-19 risk-reducing behaviors and worry about COVID-19., Conclusions: Communicating scientific uncertainty about the COVID-19 pandemic produces ambiguity-averse cognitive and emotional, but not behavioral, responses among the general public, and an uncertainty-normalizing communication strategy reduces these responses. Normalizing uncertainty may be an effective strategy for mitigating ambiguity aversion in crisis communication efforts. More research is needed to test uncertainty-normalizing communication strategies and to elucidate the factors that moderate their effectiveness., (©Paul K J Han, Elizabeth Scharnetzki, Aaron M Scherer, Alistair Thorpe, Christine Lary, Leo B Waterston, Angela Fagerlin, Nathan F Dieckmann. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 22.04.2021.)

Background: COVID-19 was declared a pandemic by the World Health Organization on March 11, 2020, and as of this writing, Texas, United States, has reported >675,000 cases with over 14,000 deaths. Many of the preventive measures implemented during the pandemic can increase sedentary lifestyles, which can lead to the development of chronic diseases, including obesity, among the general population and cause serious threats to people's physical health and overall quality of life. Individuals with pre-existing comorbidities are at an increased risk of COVID-19 and may hence have higher levels of stress., Objective: This study aimed to investigate the relationship between physical activity levels and mental health status on an individual level and to compare them between those with and those without comorbidities in a cohort of Texas residents, before and after COVID-19 was declared a pandemic., Methods: An electronic survey was disseminated throughout various regions of Texas. In total, 160 individuals were asked questions about their demographic characteristics, time spent on daily physical activities, and daily mental health status before and after COVID-19 was declared a pandemic. Frequency distributions and descriptive statistics were analyzed., Results: Overall, 94 (58%) participants reported having ≥1 medical condition, and 31 (13.1%) had >3 medical conditions. Physical activity levels among participants with ≥1 pre-existing comorbidity drastically-but not significantly-decreased, as evident from a 10% increase in sedentary lifestyles after COVID-19 was declared a pandemic. On the contrary, we observed a 9% increase in the number of individuals without a pre-existing comorbidity who reported 30-60 min of physical activity per week. There was a 2-fold increase in the number of participants reporting more frequent feelings of nervousness, too much worry, trouble relaxing, and the fear of something awful happening after the pandemic. More specifically, individuals with pre-existing medical conditions reported, on average, a 10% higher incidence of feelings of stress, anxiety, and sadness compared to their healthy counterparts after COVID-19 was declared a pandemic., Conclusions: Stressful life conditions and chronic comorbidities are risk factors that can affect mental health and reduce the ability to perform activities of daily life. Therefore, when implementing pandemic protocols, municipalities should consider providing mental health support to their citizens to protect them from this rather inconspicuous adverse effect., (©Darpan I Patel, Yazmin Gamez, Lajja Shah, Jaini Patel. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 22.04.2021.)

Background: A central component of the public health strategy to control the COVID-19 pandemic involves encouraging mask wearing and social distancing to protect individuals from acquiring and transmitting the virus., Objective: This study aims to understand the psychological factors that drive adoption or rejection of these protective behaviors, which can inform public health interventions to control the pandemic., Methods: We conducted an online survey of a representative sample of 1074 US adults and assessed three novel potential predictors of COVID-19 behaviors: trait reactance, COVID-19 conspiracy beliefs, and COVID-19 apocalypse beliefs. Key outcomes (dependent variables) included an index of COVID-19 protective behaviors, the number of trips taken from the home, and COVID-19 knowledge., Results: In bivariate analyses, all three predictors were significantly correlated in the hypothesized direction with the three COVID-19 outcomes. Specifically, each predictor was negatively (P<.01) correlated with the COVID-19 protective behaviors index and COVID-19 knowledge score, and positively correlated with trips taken from home per week (more of which was considered higher risk). COVID-19 protective behaviors and COVID-19 knowledge were significantly lower in the top median compared to the bottom median for all three predictors. In general, these findings remained significant after adjusting for all novel predictors plus age, gender, income, education, race, political party, and religiosity. Self-identified Republicans (vs other political affiliations) reported the highest values for each of the novel predictors., Conclusions: This study can inform the development of health communication interventions to encourage the adoption of COVID-19 protective behaviors. Interestingly, we found that higher scores of all three novel predictors were associated with lower COVID-19 knowledge, suggesting that lack of an accurate understanding of the virus may be driving some of these attitudes; although, it is also possible that these attributes may interfere with one's willingness or ability to seek and absorb accurate health information. These individuals may be particularly immune to accepting new information and yielding their beliefs. Health communication professionals may apply lessons learned from countering similar beliefs around climate change and vaccine hesitancy. Messages designed for individuals prone to reactance may be more effective if they minimize controlling language and emphasize the individual's independence in adopting these behavioral recommendations. Messaging for those who possess conspiracy beliefs should similarly not assume that providing evidence contrary to these beliefs will alone alter behavior. Other communication techniques such as rolling with resistance, a strategy used in motivational interviewing, may be helpful. Messaging for those with apocalyptic beliefs may require using religious leaders as the message source and using scripture that would support the adoption of COVID-19 protection behaviors., (©Ken Resnicow, Elizabeth Bacon, Penny Yang, Sarah Hawley, M Lee Van Horn, Lawrence An. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 20.04.2021.)

Background: During the COVID-19 pandemic, health professionals have been directly confronted with the suffering of patients and their families. By making them main actors in the management of this health crisis, they have been exposed to various psychosocial risks (stress, trauma, fatigue, etc). Paradoxically, stress-related symptoms are often underreported in this vulnerable population but are potentially detectable through passive monitoring of changes in speech behavior., Objective: This study aims to investigate the use of rapid and remote measures of stress levels in health professionals working during the COVID-19 outbreak. This was done through the analysis of participants' speech behavior during a short phone call conversation and, in particular, via positive, negative, and neutral storytelling tasks., Methods: Speech samples from 89 health care professionals were collected over the phone during positive, negative, and neutral storytelling tasks; various voice features were extracted and compared with classical stress measures via standard questionnaires. Additionally, a regression analysis was performed., Results: Certain speech characteristics correlated with stress levels in both genders; mainly, spectral (ie, formant) features, such as the mel-frequency cepstral coefficient, and prosodic characteristics, such as the fundamental frequency, appeared to be sensitive to stress. Overall, for both male and female participants, using vocal features from the positive tasks for regression yielded the most accurate prediction results of stress scores (mean absolute error 5.31)., Conclusions: Automatic speech analysis could help with early detection of subtle signs of stress in vulnerable populations over the phone. By combining the use of this technology with timely intervention strategies, it could contribute to the prevention of burnout and the development of comorbidities, such as depression or anxiety., (©Alexandra König, Kevin Riviere, Nicklas Linz, Hali Lindsay, Julia Elbaum, Roxane Fabre, Alexandre Derreumaux, Philippe Robert. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 19.04.2021.)

Background: Accompanying the rising rates of reported mental distress during the COVID-19 pandemic has been a reported increase in the use of digital technologies to manage health generally, and mental health more specifically., Objective: The objective of this study was to systematically examine whether there was a COVID-19 pandemic-related increase in the self-reported use of digital mental health tools and other technologies to manage mental health., Methods: We analyzed results from a survey of 5907 individuals in the United States using Amazon Mechanical Turk (MTurk); the survey was administered during 4 week-long periods in 2020 and survey respondents were from all 50 states and Washington DC. The first set of analyses employed two different logistic regression models to estimate the likelihood of having symptoms indicative of clinical depression and anxiety, respectively, as a function of the rate of COVID-19 cases per 10 people and survey time point. The second set employed seven different logistic regression models to estimate the likelihood of using seven different types of digital mental health tools and other technologies to manage one's mental health, as a function of symptoms indicative of clinical depression and anxiety, rate of COVID-19 cases per 10 people, and survey time point. These models also examined potential interactions between symptoms of clinical depression and anxiety, respectively, and rate of COVID-19 cases. All models controlled for respondent sociodemographic characteristics and state fixed effects., Results: Higher COVID-19 case rates were associated with a significantly greater likelihood of reporting symptoms of depression (odds ratio [OR] 2.06, 95% CI 1.27-3.35), but not anxiety (OR 1.21, 95% CI 0.77-1.88). Survey time point, a proxy for time, was associated with a greater likelihood of reporting clinically meaningful symptoms of depression and anxiety (OR 1.19, 95% CI 1.12-1.27 and OR 1.12, 95% CI 1.05-1.19, respectively). Reported symptoms of depression and anxiety were associated with a greater likelihood of using each type of technology. Higher COVID-19 case rates were associated with a significantly greater likelihood of using mental health forums, websites, or apps (OR 2.70, 95% CI 1.49-4.88), and other health forums, websites, or apps (OR 2.60, 95% CI 1.55-4.34). Time was associated with increased odds of reported use of mental health forums, websites, or apps (OR 1.20, 95% CI 1.11-1.30), phone-based or text-based crisis lines (OR 1.20, 95% CI 1.10-1.31), and online, computer, or console gaming/video gaming (OR 1.12, 95% CI 1.05-1.19). Interactions between COVID-19 case rate and mental health symptoms were not significantly associated with any of the technology types., Conclusions: Findings suggested increased use of digital mental health tools and other technologies over time during the early stages of the COVID-19 pandemic. As such, additional effort is urgently needed to consider the quality of these products, either by ensuring users have access to evidence-based and evidence-informed technologies and/or by providing them with the skills to make informed decisions around their potential efficacy., (©Dara H Sorkin, Emily A Janio, Elizabeth V Eikey, Margaret Schneider, Katelyn Davis, Stephen M Schueller, Nicole A Stadnick, Kai Zheng, Martha Neary, David Safani, Dana B Mukamel. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 16.04.2021.)

Background: COVID-19 is an emerging infectious disease that has created health care challenges worldwide. Pregnant women are particularly affected by this disease., Objective: The aims of this study are to assess the levels of perceived threat (susceptibility, severity, impact), negative emotions (fear, worry), and self-efficacy of pregnant women in China related to COVID-19 and to examine their associations with mental health (depression and anxiety) and personal protective behavior (wearing a face mask)., Methods: A total of 4087 pregnant women from China completed a cross-sectional web-based survey between March 3 and 10, 2020., Results: The prevalence of probable depression and anxiety was 48.7% (1989/4087) and 33.0% (1347/4087), respectively; 23.8% participants (974/4087) reported always wearing a face mask when going out. Of the 4087 participants, 32.1% (1313) and 36.4% (1490) perceived themselves or their family members to be susceptible to COVID-19 infection, respectively; 3216-3518 (78.7%-86.1%) agreed the disease would have various severe consequences. Additionally, 2275 of the 4087 participants (55.7%) showed self-efficacy in protecting themselves from contracting COVID-19, and 2232 (54.6%) showed efficacy in protecting their family members; 1303 (31.9%) reported a high level of fear of the disease, and 2780-3056 (68.0%-74.8%) expressed worry about various aspects of COVID-19. The results of the multivariate multinominal logistic regression analyses showed that perceived severity, perceived impact, fear, and worry were risk factors for probable depression and anxiety, while self-efficacy was a protective factor. The results of the multivariate logistic regression analysis showed that perceived susceptibility was associated with always wearing a face mask., Conclusions: Chinese pregnant women showed high levels of mental distress but low levels of personal protective behavior during the COVID-19 pandemic. Interventions are needed to promote the mental health and health behavior of pregnant women during the pandemic., (©Phoenix Kit Han Mo, Vivian Wai In Fong, Bo Song, Jiangli Di, Qian Wang, Linhong Wang. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 12.04.2021.)

Background: COVID-19 cases resurged worldwide in the second half of 2020. Not much is known about the changes in public responses to containment measures from the initial outbreak to resurgence. Monitoring public responses is crucial to inform policy measures to prepare for COVID-19 resurgence., Objective: This study aimed to assess and compare public responses to containment measures during the initial outbreak and resurgence of COVID-19 in China., Methods: We curated all COVID-19-related posts from Sina Weibo (China's version of Twitter) during the initial outbreak and resurgence of COVID-19 in Beijing, China. With a Python script, we constructed subsets of Weibo posts focusing on 3 containment measures: lockdown, the test-trace-isolate strategy, and suspension of gatherings. The Baidu open-source sentiment analysis model and latent Dirichlet allocation topic modeling, a widely used machine learning algorithm, were used to assess public engagement, sentiments, and frequently discussed topics on each containment measure., Results: A total of 8,985,221 Weibo posts were curated. In China, the containment measures evolved from a complete lockdown for the general population during the initial outbreak to a more targeted response strategy for high-risk populations during COVID-19 resurgence. Between the initial outbreak and resurgence, the average daily proportion of Weibo posts with negative sentiments decreased from 57% to 47% for the lockdown, 56% to 51% for the test-trace-isolate strategy, and 55% to 48% for the suspension of gatherings. Among the top 3 frequently discussed topics on lockdown measures, discussions on containment measures accounted for approximately 32% in both periods, but those on the second-most frequently discussed topic shifted from the expression of negative emotions (11%) to its impacts on daily life or work (26%). The public expressed a high level of panic (21%) during the initial outbreak but almost no panic (1%) during resurgence. The more targeted test-trace-isolate measure received the most support (60%) among all 3 containment measures in the initial outbreak, and its support rate approached 90% during resurgence., Conclusions: Compared to the initial outbreak, the public expressed less engagement and less negative sentiments on containment measures and were more supportive toward containment measures during resurgence. Targeted test-trace-isolate strategies were more acceptable to the public. Our results indicate that when COVID-19 resurges, more targeted test-trace-isolate strategies for high-risk populations should be promoted to balance pandemic control and its impact on daily life and the economy., (©Xinyu Zhou, Yi Song, Hao Jiang, Qian Wang, Zhiqiang Qu, Xiaoyu Zhou, Mark Jit, Zhiyuan Hou, Leesa Lin. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 05.04.2021.)

Background: Global efforts toward the development and deployment of a vaccine for COVID-19 are rapidly advancing. To achieve herd immunity, widespread administration of vaccines is required, which necessitates significant cooperation from the general public. As such, it is crucial that governments and public health agencies understand public sentiments toward vaccines, which can help guide educational campaigns and other targeted policy interventions., Objective: The aim of this study was to develop and apply an artificial intelligence-based approach to analyze public sentiments on social media in the United Kingdom and the United States toward COVID-19 vaccines to better understand the public attitude and concerns regarding COVID-19 vaccines., Methods: Over 300,000 social media posts related to COVID-19 vaccines were extracted, including 23,571 Facebook posts from the United Kingdom and 144,864 from the United States, along with 40,268 tweets from the United Kingdom and 98,385 from the United States from March 1 to November 22, 2020. We used natural language processing and deep learning-based techniques to predict average sentiments, sentiment trends, and topics of discussion. These factors were analyzed longitudinally and geospatially, and manual reading of randomly selected posts on points of interest helped identify underlying themes and validated insights from the analysis., Results: Overall averaged positive, negative, and neutral sentiments were at 58%, 22%, and 17% in the United Kingdom, compared to 56%, 24%, and 18% in the United States, respectively. Public optimism over vaccine development, effectiveness, and trials as well as concerns over their safety, economic viability, and corporation control were identified. We compared our findings to those of nationwide surveys in both countries and found them to correlate broadly., Conclusions: Artificial intelligence-enabled social media analysis should be considered for adoption by institutions and governments alongside surveys and other conventional methods of assessing public attitude. Such analyses could enable real-time assessment, at scale, of public confidence and trust in COVID-19 vaccines, help address the concerns of vaccine sceptics, and help develop more effective policies and communication strategies to maximize uptake., (©Amir Hussain, Ahsen Tahir, Zain Hussain, Zakariya Sheikh, Mandar Gogate, Kia Dashtipour, Azhar Ali, Aziz Sheikh. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 05.04.2021.)

Background: The dissemination of rumor rebuttal content on social media is vital for rumor control and disease containment during public health crises. Previous research on the effectiveness of rumor rebuttal, to a certain extent, ignored or simplified the structure of dissemination networks and users' cognition as well as decision-making and interaction behaviors., Objective: This study aimed to roughly evaluate the effectiveness of rumor rebuttal; dig deeply into the attitude-based echo chamber effect on users' responses to rumor rebuttal under multiple topics on Weibo, a Chinese social media platform, in the early stage of the COVID-19 epidemic; and evaluate the echo chamber's impact on the information characteristics of user interaction content., Methods: We used Sina Weibo's application programming interface to crawl rumor rebuttal content related to COVID-19 from 10 AM on January 23, 2020, to midnight on April 8, 2020. Using content analysis, sentiment analysis, social network analysis, and statistical analysis, we first analyzed whether and to what extent there was an echo chamber effect on the shaping of individuals' attitudes when retweeting or commenting on others' tweets. Then, we tested the heterogeneity of attitude distribution within communities and the homophily of interactions between communities. Based on the results at user and community levels, we made comprehensive judgments. Finally, we examined users' interaction content from three dimensions-sentiment expression, information seeking and sharing, and civility-to test the impact of the echo chamber effect., Results: Our results indicated that the retweeting mechanism played an essential role in promoting polarization, and the commenting mechanism played a role in consensus building. Our results showed that there might not be a significant echo chamber effect on community interactions and verified that, compared to like-minded interactions, cross-cutting interactions contained significantly more negative sentiment, information seeking and sharing, and incivility. We found that online users' information-seeking behavior was accompanied by incivility, and information-sharing behavior was accompanied by more negative sentiment, which was often accompanied by incivility., Conclusions: Our findings revealed the existence and degree of an echo chamber effect from multiple dimensions, such as topic, interaction mechanism, and interaction level, and its impact on interaction content. Based on these findings, we provide several suggestions for preventing or alleviating group polarization to achieve better rumor rebuttal., (©Dandan Wang, Yuxing Qian. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 25.03.2021.)

Background: The ongoing COVID-19 pandemic has led to an increase in anxiety, depression, posttraumatic stress disorder, and psychological stress experienced by the general public in various degrees worldwide. However, effective, tailored mental health services and interventions cannot be achieved until we understand the patterns of mental health issues emerging after a public health crisis, especially in the context of the rapid transmission of COVID-19. Understanding the public's emotions and needs and their distribution attributes are therefore critical for creating appropriate public policies and eventually responding to the health crisis effectively, efficiently, and equitably., Objective: This study aims to detect the temporal patterns in emotional fluctuation, significant events during the COVID-19 pandemic that affected emotional changes and variations, and hourly variations of emotions within a single day by analyzing data from the Chinese social media platform Weibo., Methods: Based on a longitudinal dataset of 816,556 posts published by 27,912 Weibo users in Wuhan, China, from December 31, 2019, to April 31, 2020, we processed general sentiment inclination rating and the type of sentiments of Weibo posts by using pandas and SnowNLP Python libraries. We also grouped the publication times into 5 time groups to measure changes in netizens' sentiments during different periods in a single day., Results: Overall, negative emotions such as surprise, fear, and anger were the most salient emotions detected on Weibo. These emotions were triggered by certain milestone events such as the confirmation of human-to-human transmission of COVID-19. Emotions varied within a day. Although all emotions were more prevalent in the afternoon and night, fear and anger were more dominant in the morning and afternoon, whereas depression was more salient during the night., Conclusions: Various milestone events during the COVID-19 pandemic were the primary events that ignited netizens' emotions. In addition, Weibo users' emotions varied within a day. Our findings provide insights into providing better-tailored mental health services and interventions., (©Shaobin Yu, David Eisenman, Ziqiang Han. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 18.03.2021.)

Background: Since the beginning of the COVID-19 pandemic, social distancing, self-quarantining, wearing masks, and washing hands have become part of the new norm for many, but not all. It appears that such preventive measures are critical to "flattening the curve" of the spread of COVID-19. The public's adoption of such behaviors is an essential component in the battle against what has been referred to as the "invisible enemy.", Objective: The primary objective of this study was to develop a model for predicting COVID-19 preventive behaviors among US college students. The Health Belief Model has a long history of use and empirical support in predicting preventive health behaviors, but it is not without its purported shortcomings. This study identifies a more optimal and defensible combination of variables to explain preventive behaviors among college students. This segment of the US population is critical in helping slow the spread of COVID-19 because of the relative reluctance of college students to perform the needed behaviors given they do not feel susceptible to or fearful of COVID-19., Methods: For this study, 415 US college students were surveyed via Qualtrics and asked to answer questions regarding their fear of COVID-19, information receptivity (seeking relevant information), perceived knowledge of the disease, self-efficacy, and performance of preventive behaviors. The PROCESS macro (Model 6) was used to test our conceptual model, including predictions involving sequential mediation., Results: Sequential mediation results show that fear of COVID-19 leads individuals to seek out information regarding the disease, which increases their perceived knowledge and fosters self-efficacy; this is key to driving preventive behaviors., Conclusions: Self-imposed preventive measures can drastically impact the rate of infection among populations. Based on this study's newly created sequential mediation model, communication strategies for encouraging COVID-19 preventive behaviors are offered. It is clear that college students, and very possibly adults of all ages, must have a healthy fear of COVID-19 to set in motion a process where concerned individuals seek out COVID-19-related information, increasing their store of knowledge concerning the disease, their self-efficacy, and ultimately their likelihood of performing the needed preventive behaviors., (©James A Roberts, Meredith E David. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 17.03.2021.)