Problematic use of the internet, smartphones, and social media among medical students and relationship with depression: An exploratory study.

BACKGROUND: Students in sub-Saharan African countries experienced online classes for the first time during the COVID-19 pandemic. For some individuals, greater online engagement can lead to online dependency, which can be associated with depression. The present study explored the association between problematic use of the internet, social media, and smartphones with depression symptoms among Ugandan medical students. METHODS: A pilot study was conducted among 269 medical students at a Ugandan public university. Using a survey, data were collected regarding socio-demographic factors, lifestyle, online use behaviors, smartphone addiction, social media addiction, and internet addiction. Hierarchical linear regression models were performed to explore the associations of different forms of online addiction with depression symptom severity. RESULTS: The findings indicated that 16.73% of the medical students had moderate to severe depression symptoms. The prevalence of being at risk of (i) smartphone addiction was 45.72%, (ii) social media addiction was 74.34%, and (iii) internet addiction use was 8.55%. Online use behaviors (e.g., average hours spent online, types of social media platforms used, the purpose for internet use) and online-related addictions (to smartphones, social media, and the internet) predicted approximately 8% and 10% of the severity of depression symptoms, respectively. However, over the past two weeks, life stressors had the highest predictability for depression (35.9%). The final model predicted a total of 51.9% variance for depression symptoms. In the final model, romantic relationship problems (ß = 2.30, S.E = 0.58; p<0.01) and academic performance problems (ß = 1.76, S.E = 0.60; p<0.01) over the past two weeks; and increased internet addiction severity (ß = 0.05, S.E = 0.02; p<0.01) was associated with significantly increased depression symptom severity, whereas Twitter use was associated with reduced depression symptom severity (ß = 1.88, S.E = 0.57; p<0.05). CONCLUSION: Despite life stressors being the largest predictor of depression symptom score severity, problematic online use also contributed significantly. Therefore, it is recommended that medical students' mental health care services consider digital wellbeing and its relationship with problematic online use as part of a more holistic depression prevention and resilience program.

Risk Factors and Protective Factors of Internet Addiction in University Students during the Pandemic: Implications for Prevention and Treatment.

While the prevalence rates of Internet addiction (IA) amongst young people during the pandemic are disturbing, few studies have investigated the risk and protective factors of IA in Hong Kong university students under COVID-19. In this study, we examined the relationship between COVID-19-related stress and IA and the role of psychological morbidity and positive psychological attributes in the relationship. In summer 2022, 978 university students completed a survey assessing pandemic-related stress, psychological morbidity, and positive psychological attributes. While psychological morbidity was indexed by depression, post-traumatic stress disorder, and suicidal behavior, positive psychological attributes included life satisfaction, flourishing, adversity beliefs, emotional competence, resilience, and family functioning measures. Results showed that stress and psychological morbidity positively predicted IA, and psychological morbidity mediated the association between stress and IA. Positive psychological attributes negatively predicted stress and IA, and mediated the connection between stress and IA. Positive psychological attributes moderated the mediating effect of psychological morbidity on the relationship between stress and IA. In addition to theoretical contributions, this study contributes to IA prevention and treatment: reducing psychological morbidity and promoting positive psychological attributes are promising strategies to address IA issues in young people.

Web-based surveillance of respiratory infection outbreaks: retrospective analysis of Italian COVID-19 epidemic waves using Google Trends.

Introduction: Large-scale diagnostic testing has been proven insufficient to promptly monitor the spread of the Coronavirus disease 2019. Electronic resources may provide better insight into the early detection of epidemics. We aimed to retrospectively explore whether the Google search volume has been useful in detecting Severe Acute Respiratory Syndrome Coronavirus outbreaks early compared to the swab-based surveillance system. Methods: The Google Trends website was used by applying the research to three Italian regions (Lombardy, Marche, and Sicily), covering 16 million Italian citizens. An autoregressive-moving-average model was fitted, and residual charts were plotted to detect outliers in weekly searches of five keywords. Signals that occurred during periods labelled as free from epidemics were used to measure Positive Predictive Values and False Negative Rates in anticipating the epidemic wave occurrence. Results: Signals from "fever," "cough," and "sore throat" showed better performance than those from "loss of smell" and "loss of taste." More than 80% of true epidemic waves were detected early by the occurrence of at least an outlier signal in Lombardy, although this implies a 20% false alarm signals. Performance was poorer for Sicily and Marche. Conclusion: Monitoring the volume of Google searches can be a valuable tool for early detection of respiratory infectious disease outbreaks, particularly in areas with high access to home internet. The inclusion of web-based syndromic keywords is promising as it could facilitate the containment of COVID-19 and perhaps other unknown infectious diseases in the future.

Internet addiction and mental health disorders in high school students in a Peruvian region: a cross-sectional study.

OBJECTIVES: To determine the association between internet addiction disorder (IAD) and anxiety and depressive symptomatology in high school students in two private schools in Chiclayo, Peru, during the COVID-19 pandemic. MATERIALS AND METHODS: Analytical cross-sectional investigation of 505 adolescents from two private schools. The dependent variables were anxiety and depressive symptomatology, measured with the Beck Adapted Depression Questionnaire (BDI-IIA) and the Beck Anxiety Inventory (BAI), respectively. The main independent variable was IAD, measured with the Internet Addiction Test instrument(IATI). Prevalence ratios (PR) and 95% confidence intervals (95%CI) were estimated. RESULTS: The average age was 14.16 years and 54.9% were women. 22.2% and 3.2% presented mild and moderate IAD; respectively. 9.3% presented severe anxiety and 34.3% severe depressive symptomatology. In the simple regression, adolescents with mild, moderate and severe IAD presented 19% (PR = 1.19; 95%CI: 1.05-1.35), 25% (PR = 1.25; 95%CI: 1.02-1.53) and 53% (PR = 1.47; 95% CI: 1.47-1.60) higher prevalence of depressive symptomatology; however, this association was not maintained in the multiple model. Anxiety increased 196% in adolescents with severe IAD (PR = 2.96; 95%CI: 1.86-4.71). CONCLUSION: We found that 2, 1, and 3 out of 10 students presented IAD, depressive symptomatology, and anxiety, respectively. We did not find an association between IAD and depressive symptomatology, but we did find an association with anxiety. Among the factors associated with the development of depressive symptomatology were the male sex, the presence of eating disorders, subclinical insomnia, using devices for more than 2 h, and using the Internet for academic activities. About anxiety, the associated factors are the female sex, the presence of eating disorders, subclinical insomnia, and the use of the Internet as social interaction. We recommend implementing counseling programs in view of the imminent introduction of the Internet as a pillar in education.

[Simulators and other tools in orthopedic-trauma surgery training]. / Simulatoren und andere Hilfsmittel in der orthopädisch-unfallchirurgischen Weiterbildung.

INTRODUCTION: The classic paradigm of "learning on the patient in the operating room" is more and more in conflict with the growing requirements of cost-efficient work and patient safety. With the technology available today for simulator systems, the accessibility of digital tools and the development of a metaverse as a digital meeting place result in various application scenarios and alternatives to classic orthopedic training. SIMULATORS: First VR-desktop simulations in orthopedics and traumatology were developed more than 20 years ago. VR-desktop simulators consist of a computer with a video screen and a joint model. Different instruments can be paired with this system and allow haptic feedback. With innovative software, numerous training programs can be selected, and the user receives precise feedback on their performance. Immersive VR simulators have also played an increasingly important role in recent years. OTHER DIGITAL TOOLS: The use of digital media such as audio and video podcasts as learning and information sources increased in the context of COVID-19. There is also an increasing number of orthopedic and trauma surgery topics on social media platforms. In all fields, however, there is a risk of the spread of misinformation. A quality standard must be maintained. EFFECTIVENESS AND UTILITY OF THE TRAINING: In order to evaluate simulators and their value as a training tool, it is important to comply with various validity criteria. Transfer validity plays an essential role for clinical application. Various studies demonstrate that the skills learned on simulators can also be successfully transferred to real clinical scenarios. DISCUSSION: A lack of availability, costs and high effort are limitations of classic training methods. In contrast, there are versatile use cases of VR-based simulations that are individually adapted to the trainees and cannot endanger patients. The still high acquisition costs, technical obstacles and the not yet widespread availability are limiting factors. The metaverse still offers unimaginable possibilities today to transfer VR-based applications to experimental learning methods.

A Web-Based Method for the Identification of IL6-Based Immunotoxicity in Vaccine Candidates.

Interleukin 6 (IL6) is a major pro-inflammatory cytokine that plays a pivotal role in both innate and adaptive immune responses. In the past, a number of studies reported that high level of IL6 promotes the proliferation of cancer, autoimmune disorders, and cytokine storm in COVID-19 patients. Thus, it is extremely important to identify and remove the antigenic regions from a therapeutic protein or vaccine candidate that may induce IL6-associated immunotoxicity. In order to overcome this challenge, our group has developed a computational tool, IL6pred, for discovering IL6-inducing peptides in a vaccine candidate. The aim of this chapter is to describe the potential applications and methodology of IL6pred. It sheds light on the prediction, designing, and scanning modules of IL6pred webserver and standalone package ( https://webs.iiitd.edu.in/raghava/il6pred/ ).

Prevalence and associated factors of mental health disorders among Brazilian healthcare workers in times of the COVID-19 pandemic: A web-based cross-sectional study.

The COVID-19 pandemic in Brazil affected mental health among healthcare workers. To objective of this study was to evaluate the mental health of healthcare workers in in the central-west region of the Brazil, estimating the prevalence of mental health disorders, and investigating associated factors, perceptions of safety, and self-perceptions about mental health in times of the COVID-19 pandemic. The questionnaire was divided into two parts that included general information and perceptions about the work process and identified symptoms using the Depression Anxiety Stress Scale-21 (DASS-21), and multiple linear regression analysis was conducted. A total of 1,522 healthcare workers participated in the survey. Overall prevalence of symptoms was calculated for depression (58.7%), anxiety (59.7%), and stress (61.7%). Physicians had 3.75 times greater risk of depression (1.59-8.85, 95% CI). Independent variables associated with depression symptoms were not feeling safe with the way services were organized (1.12:1.03-1.21, 95% CI) and self-perception of poor mental health (8.06: 4.03-16.10% CI). Working in management was protective, and married professionals had 12% lower risk of exhibiting symptoms of depression (0.79-0.99, 95% CI). Participants with self-perception of poor mental health had 4.63 greater risk for symptoms of anxiety (2.58-8.31, 95% CI). Protective factors were not having sought support for mental health (0.90: 0.82-0.99, 95% CI), having a graduate degree (0.71: 0.54-0.94, 95% CI), and not having been diagnosed with COVID-19 (0.90: 0.83-0.98, 95% CI). Perception of poor mental health was associated with 6.95-fold greater chance of developing stress symptoms. Protective factors from stress were having a degree in dentistry (0.81: 0.68-0.97, 95% CI), residing in Mato Grosso do Sul (0.91: 0.85-0.98, 95% CI), and not having sought mental health support services (0.88: 0.82-0.95, 95% CI). The prevalence of mental health disorders is high among healthcare workers, and is associated with professional category, organization of services provided, and self-perception of poor mental health, reinforcing the need for preventative measures.

Internet addiction and residual depressive symptoms among clinically stable adolescents with major psychiatric disorders during the COVID-19 pandemic: a network analysis perspective.

To assess the inter-relationships between residual depressive symptoms (RDS) and Internet addiction (IA) using network analysis among clinically stable adolescents with major psychiatric disorders during the COVID-19 pandemic. RDS and IA were assessed using the Patient Health Questionnaire-9 (PHQ-9) and the Internet Addiction Test (IAT), respectively. Central symptoms and bridge symptoms in the network model were examined. A total of 1,454 adolescents met the study criteria and were included in the analyses. The prevalence of IA was 31.2% (95% CI: 28.8%-33.6%). In the network analysis, the nodes IAT15 ("Preoccupation with the Internet"), PHQ2 ("Sad mood"), and PHQ1 ("Anhedonia") were the most central symptoms in the IA-RDS network model. Bridge symptoms included IAT10 ("Sooth disturbing about your Internet use"), PHQ9 ("Suicide ideation"), and IAT3 ("Prefer the excitement online to the time with others"). Additionally, PHQ2 ("Sad mood") was the main node linking "Anhedonia" to other IA clusters. Internet addiction was common among clinically stable adolescents with major psychiatric disorders during the COVID-19 pandemic. Core and bridge symptoms identified in this study could be prioritized as targets for the prevention and treatment of IA in this population.

Monitoring Acute Heart Failure Patients Using Internet-of-Things-Based Smart Monitoring System.

With technological advancements, smart health monitoring systems are gaining growing importance and popularity. Today, business trends are changing from physical infrastructure to online services. With the restrictions imposed during COVID-19, medical services have been changed. The concepts of smart homes, smart appliances, and smart medical systems have gained popularity. The Internet of Things (IoT) has revolutionized communication and data collection by incorporating smart sensors for data collection from diverse sources. In addition, it utilizes artificial intelligence (AI) approaches to control a large volume of data for better use, storing, managing, and making decisions. In this research, a health monitoring system based on AI and IoT is designed to deal with the data of heart patients. The system monitors the heart patient's activities, which helps to inform patients about their health status. Moreover, the system can perform disease classification using machine learning models. Experimental results reveal that the proposed system can perform real-time monitoring of patients and classify diseases with higher accuracy.

Lifestyle and Dietary Patterns during the COVID-19 Lockdown in Bahrain: A Web-Based Cross-Sectional Study.

Lifestyle factors such as dietary habits, perceived weight, sleep, and physical activity worsened during the COVID-19 pandemic. Through this study, we aimed to understand the impact of COVID-19 on these lifestyle factors in Bahrain. A cross-sectional study was conducted among 1005 adult Bahrainis. Data were collected online using a structured and validated questionnaire for the assessment of eating habits, physical activity, and lifestyle during the COVID-19 pandemic. Participants were snowballed through those who agreed to answer the online questionnaire. There was a higher consumption of fast food, and a higher dependence on takeaways during the COVID-19 pandemic. About 63.5% of the participants consumed >4 meals per day, compared to 36.5% before the COVID-19. About 30% reported consumption of sugar sweetened beverages from two to three times a day. Weight loss was predominantly observed in persons exercising 1-3 times a week. The consumption of sugar-sweetened beverages was also high, with about 19% reporting drinking sweet beverages once every day, 10.6% from two to three times a day, and 40.4% from one to four times a week. A higher proportion of the participants reported poor sleep quality during the pandemic (31.2%) compared to before (12.2%), and 39.7% of the participants reported feeling lazy. Screen time use also doubled during the pandemic, with participants spending more than five hours per day on screens for entertainment, which went from 22.4% before to 51.9% during the pandemic. The lifestyle and dietary habits changed drastically for our study participants during the pandemic. The increased reliance on processed fast food instead of healthier options is a challenge to be tackled in any future pandemic situation. Future research needs to focus on strategies to promote healthier lifestyle modifications during situations such as the COVID-19 pandemic.

A Review of the Scope of Direct-to-Consumer Sexually Transmitted Infection Testing Services Offered on the Internet.

BACKGROUND: The prevalence of sexually transmitted infections (STIs) is at an all-time high. Direct-to-consumer STI testing services may help alleviate this undue health burden. These products are sold online and rarely require interaction with a health care professional (HCP). Vendors offer STI self-collection kits or prescriptions for HCP specimen collection. The objective was to understand the scope of direct-to-consumer STI testing services offered and provide recommendations for consumers and industry. METHODS: Seven volunteers searched for "STD tests" on Google from February 1 through March 31, 2021 and shared their top 3 results. The study team extracted data from consumer-facing information on each website. Descriptive statistics and thematic qualitative analyses were performed. RESULTS: Twenty vendors were identified. Most vendors (95%) used Clinical Laboratory Improvement Amendments (CLIA)-certified or College of American Pathologists (CAP) accredited laboratories. Analyses distinguished between STI self-collection kits (n = 9) using independent laboratories and HCP specimen collection (n = 10), which used commercial laboratories (n = 1 offered both). The STI self-collection kits were cheaper per test and bundle on average (eg, $79.00 vs. $106.50 for chlamydia/gonorrhea), and more closely aligned with clinical recommendations compared with the HCP specimen collection options. Websites often contained inaccurate or misleading information (n = 13), often promoting testing outside of the recommendations. CONCLUSIONS: Direct-to-consumer STI testing services are part of an emerging market lacking regulation. Consumers should select vendors offering prescriptions for HCP specimen collection at CAP accredited and CLIA-certified laboratories. Vendors should provide a screening tool to assess individual patient risk prior to test purchase.

Barriers to providing internet-based home care services for urban older adults in China: a qualitative study of the service providers.

BACKGROUND: Due to the increasingly aging population in China and the changes in social and family structure, older adults' care problems are becoming more and more prominent. To meet the home care needs of urban older adults, the Chinese government has launched Internet-Based Home Care Services (IBHCS). Although this model innovation can significantly relieve care problems, more and more evidence shows that there are many barriers in the process of IBHCS supply. The current literature is mostly from the perspective of the service users, and there are very few studies on the experience of service providers. METHODS: In this study, we took a qualitative phenomenological approach and used semi-structured interviews to investigate service providers' daily experiences and the barriers they encounter. A total of 34 staff from 14 Home Care Service Centers (HCSCs) were included. Interviews were transcribed and analyzed using thematic analysis. RESULTS: We identified the barriers that service providers encounter in IBHCS supply: (1) bureaucratic repression: unreasonable policy plans, harsh assessment, excessive paperwork, different preferences of government leaders, and obstacles caused by COVID-19 control lead to a shift of focus in their work; (2) profitability crisis in the market: high service costs, dampened effective demand, government intervention in setting prices, and parent companies' excessively high sales targets hinder the service supply process; (3) client-related challenges: the crisis of confidence, the dilemma of popularizing new technology, and communication barriers lead to rejection by older adults; (4) job dissatisfaction: low and unstable salary, heavy tasks, poor social acceptance of occupations, and lack of professional value reduce work enthusiasm. CONCLUSION: We have investigated the barriers faced by service providers when providing IBHCS for urban older adults in China, providing empirical evidence in the Chinese context for the relevant literature. In order to provide IBHCS better, it is necessary to improve the institutional environment and market environment, strengthen publicity and communication, target customer needs, and adjust the working conditions of front-line workers.

A Web-Based Public Health Intervention for Addressing Vaccine Misinformation: Analysis of Learner Engagement and Shift in Hesitancy to Vaccinate.

Web-based public health interventions can be a useful tool for disseminating evidence-based information to the public. However, completion rates are traditionally low, and misinformation often travels at a faster pace than evidence-based sources. This study describes the design of a web-based public health intervention to address COVID-19 vaccine hesitancy. A quasi-experimental approach was used in which a validated instrument, the Adult Vaccine Hesitancy Survey, was given to learners both pre and post intervention to observe any change in attitude towards vaccination. Our pilot observed a small positive shift in vaccine hesitancy and experienced higher than average completion rates. By integrating motivational learning design into public health interventions we increase the likelihood that learners finish the entire intervention, creating greater chance for positive behavior change.

nCoVDock2: a docking server to predict the binding modes between COVID-19 targets and its potential ligands.

The rapid emergence of SARS-CoV-2 variants with multi-sites mutations is considered as a major obstacle for the development of drugs and vaccines. Although most of the functional proteins essential for SARS-CoV-2 have been determined, the understanding of the COVID-19 target-ligand interactions remains a key challenge. The old version of this COVID-19 docking server was built in 2020, and free and open to all users. Here, we present nCoVDock2, a new docking server to predict the binding modes for targets from SARS-CoV-2. First, the new server supports more targets. We replaced the modeled structures with newly resolved structures and added more potential targets of COVID-19, especially for the variants. Second, for small molecule docking, Autodock Vina was upgraded to the latest version 1.2.0, and a new scoring function was added for peptide or antibody docking. Third, the input interface and molecular visualization were updated for a better user experience. The web server, together with an extensive help and tutorial, are freely available at: https://ncovdock2.schanglab.org.cn.

Digital Disease Surveillance for Emerging Infectious Diseases: An Early Warning System Using the Internet and Social Media Data for COVID-19 Forecasting in Canada.

BACKGROUND: Emerging Infectious Diseases (EID) are a significant threat to population health globally. We aimed to examine the relationship between internet search engine queries and social media data on COVID-19 and determine if they can predict COVID-19 cases in Canada. METHODS: We analyzed Google Trends (GT) and Twitter data from 1/1/2020 to 3/31/2020 in Canada and used various signal-processing techniques to remove noise from the data. Data on COVID-19 cases was obtained from the COVID-19 Canada Open Data Working Group. We conducted time-lagged cross-correlation analyses and developed the long short-term memory model for forecasting daily COVID-19 cases. RESULTS: Among symptom keywords, "cough," "runny nose," and "anosmia" were strong signals with high cross-correlation coefficients >0.8 ( rCough = 0.825, t - 9; rRunnyNose = 0.816, t - 11; rAnosmia = 0.812, t - 3 ), showing that searching for "cough," "runny nose," and "anosmia" on GT correlated with the incidence of COVID-19 and peaked 9, 11, and 3 days earlier than the incidence peak, respectively. For symptoms- and COVID-related Tweet counts, the cross-correlations of Tweet signals and daily cases were rTweetSymptoms = 0.868, t - 11 and tTweetCOVID = 0.840, t - 10, respectively. The LSTM forecasting model achieved the best performance (MSE = 124.78, R2 = 0.88, adjusted R2 = 0.87) using GT signals with cross-correlation coefficients >0.75. Combining GT and Tweet signals did not improve the model performance. CONCLUSION: Internet search engine queries and social media data can be used as early warning signals for creating a real-time surveillance system for COVID-19 forecasting, but challenges remain in modelling.

Comparing the Use of a Mobile App and a Web-Based Notification Platform for Surveillance of Adverse Events Following Influenza Immunization: Randomized Controlled Trial.

BACKGROUND: Vaccine safety surveillance is a core component of vaccine pharmacovigilance. In Canada, active, participant-centered vaccine surveillance is available for influenza vaccines and has been used for COVID-19 vaccines. OBJECTIVE: The objective of this study is to evaluate the effectiveness and feasibility of using a mobile app for reporting participant-centered seasonal influenza adverse events following immunization (AEFIs) compared to a web-based notification system. METHODS: Participants were randomized to influenza vaccine safety reporting via a mobile app or a web-based notification platform. All participants were invited to complete a user experience survey. RESULTS: Among the 2408 randomized participants, 1319 (54%) completed their safety survey 1 week after vaccination, with a higher completion rate among the web-based notification platform users (767/1196, 64%) than among mobile app users (552/1212, 45%; P<.001). Ease-of-use ratings were high for the web-based notification platform users (99% strongly agree or agree) and 88.8% of them strongly agreed or agreed that the system made reporting AEFIs easier. Web-based notification platform users supported the statement that a web-based notification-only approach would make it easier for public health professionals to detect vaccine safety signals (91.4%, agreed or strongly agreed). CONCLUSIONS: Participants in this study were significantly more likely to respond to a web-based safety survey rather than within a mobile app. These results suggest that mobile apps present an additional barrier for use compared to the web-based notification-only approach. TRIAL REGISTRATION: ClinicalTrials.gov NCT05794113; https://clinicaltrials.gov/show/NCT05794113.

The association between online learning, parents' marital status, and internet addiction among adolescents during the COVID-19 pandemic period: A cross-lagged panel network approach.

INTRODUCTION: Previous research has identified the association between online learning and Internet addiction (IA) and the role of family factors in it. However, few studies have treated IA as a multidimensional mechanism and explored the underlying linkage of online learning, IA, and parental marital status with a cross-lagged network approach. The study aimed to examine the relationship between online learning during the COVID-19 pandemic, Internet addiction (IA), and parental marital status among Chinese adolescents. METHODS: The sample consisted of 2356 adolescents who completed the Internet Addiction Test twice over a four-month period. Four symptom networks and two cross-lagged panel networks were performed. RESULTS: The results showed that adolescents from divorced families had a higher prevalence of IA (27 %) compared to those from non-divorced families (17 %). The strongest cross-lagged association was found between "spending more time online" and "preferring the excitement online". In the divorced group, "school grades suffering" had the highest influence, while in the non-divorced group, "anticipation" had the highest influence. CONCLUSION: This study highlights the relationship between online learning, IA, and parental divorce and suggests that long-term online learning may contribute to IA, and parental divorce may exacerbate problematic Internet use and increase IA levels.

Voluntary suspension of medically-assisted reproduction during the COVID-19 pandemic in Japan: a nationwide internet survey.

We explored whether coronavirus disease 2019 (COVID-19)-related distress was associated with voluntary suspension of medically-assisted reproduction (MAR) treatment from April to May 2020 in Japan. Data for 1,096 candidate respondents were collected from a Japanese nationwide cross-sectional internet survey distributed from August 25 to September 30, 2020. Multiple logistic regression was performed to clarify the association between voluntary suspension of MAR treatment and the Fear of COVID-19 Scale (FVC-19S) score. High FCV-19S score was inversely associated with voluntary suspension of MAR treatment compared to low FCV-19S score among women (OR = 0.28, 95% CI = 0.10-0.84). Age-stratified analyses revealed that low FVC-19S score was significantly associated with voluntary suspension of MAR treatment among women aged < 35 years (OR = 3.86, 95% CI = 1.35-11.0). In contrast, the association between FVC-19S score and voluntary suspension of MAR treatment was reversed and not significant among women aged ≥ 35 years (OR = 0.67, 95% CI = 0.24-1.84). COVID-19-related distress was significantly associated with voluntary suspension of MAR treatment among women aged < 35 years, and this association was reversed but not significant among women aged ≥ 35 years.

Psychological inoculation protects against the social media infodemic.

Misinformation can have a profound detrimental impact on populations' wellbeing. In this large UK-based online experiment (n = 2430), we assessed the performance of false tag and inoculation interventions in protecting against different forms of misinformation ('variants'). While previous experiments have used perception- or intention-based outcome measures, we presented participants with real-life misinformation posts in a social media platform simulation and measured their engagement, a more ecologically valid approach. Our pre-registered mixed-effects models indicated that both interventions reduced engagement with misinformation, but inoculation was most effective. However, random differences analysis revealed that the protection conferred by inoculation differed across posts. Moderation analysis indicated that immunity provided by inoculation is robust to variation in individuals' cognitive reflection. This study provides novel evidence on the general effectiveness of inoculation interventions over false tags, social media platforms' current approach. Given inoculation's effect heterogeneity, a concert of interventions will likely be required for future safeguarding efforts.

What contributes to COVID-19 online disinformation among Black Canadians: a qualitative study.

BACKGROUND: Black Canadians are disproportionately affected by the COVID-19 pandemic, and the literature suggests that online disinformation and misinformation contribute to higher rates of SARS-CoV-2 infection and vaccine hesitancy in Black communities in Canada. Through stakeholder interviews, we sought to describe the nature of COVID-19 online disinformation among Black Canadians and identify the factors contributing to this phenomenon. METHODS: We conducted purposive sampling followed by snowball sampling and completed in-depth qualitative interviews with Black stakeholders with insights into the nature and impact of COVID-19 online disinformation and misinformation in Black communities. We analyzed data using content analysis, drawing on analytical resources from intersectionality theory. RESULTS: The stakeholders (n = 30, 20 purposively sampled and 10 recruited by way of snowball sampling) reported sharing of COVID-19 online disinformation and misinformation in Black Canadian communities, involving social media interaction among family, friends and community members and information shared by prominent Black figures on social media platforms such as WhatsApp and Facebook. Our data analysis shows that poor communication, cultural and religious factors, distrust of health care systems and distrust of governments contributed to COVID-19 disinformation and misinformation in Black communities. INTERPRETATION: Our findings suggest racism and underlying systemic discrimination against Black Canadians immensely catalyzed the spread of disinformation and misinformation in Black communities across Canada, which exacerbated the health inequities Black people experienced. As such, using collaborative interventions to understand challenges within the community to relay information about COVID-19 and vaccines could address vaccine hesitancy.