Measuring Digital Vaccine Literacy: Development and Psychometric Assessment of the Digital Vaccine Literacy Scale.

BACKGROUND: The use of the internet to look for information about vaccines has skyrocketed in the last years, especially with the COVID-19 pandemic. Digital vaccine literacy (DVL) refers to understanding, trust, appraisal, and application of vaccine-related information online. OBJECTIVE: This study aims to develop a tool measuring DVL and assess its psychometric properties. METHODS: A 7-item online questionnaire was administered to 848 French adults. Different psychometric analyses were performed, including descriptive statistics, exploratory factor analysis, confirmatory factor analysis, and convergent and discriminant validity. RESULTS: We developed the 7-item DVL scale composed of 3 factors (understanding and trust official information; understanding and trust information in social media; and appraisal of vaccine information online in terms of evaluation of the information and its application for decision making). The mean DVL score of the baseline sample of 848 participants was 19.5 (SD 2.8) with a range of 7-28. The median score was 20. Scores were significantly different by gender (P=.24), age (P=.03), studying or working in the field of health (P=.01), and receiving regular seasonal flu shots (P=.01). CONCLUSIONS: The DVL tool showed good psychometric proprieties, resulting in a promising measure of DVL.

Identifying Profiles and Symptoms of Patients With Long COVID in France: Data Mining Infodemiology Study Based on Social Media

Background Long COVID—a condition with persistent symptoms post COVID-19 infection—is the first illness arising from social media. In France, the French hashtag #ApresJ20 described symptoms persisting longer than 20 days after contracting COVID-19. Faced with a lack of recognition from medical and official entities, patients formed communities on social media and described their symptoms as long-lasting, fluctuating, and multisystemic. While many studies on long COVID relied on traditional research methods with lengthy processes, social media offers a foundation for large-scale studies with a fast-flowing outburst of data. Objective We aimed to identify and analyze Long Haulers’ main reported symptoms, symptom co-occurrences, topics of discussion, difficulties encountered, and patient profiles. Methods Data were extracted based on a list of pertinent keywords from public sites (eg, Twitter) and health-related forums (eg, Doctissimo). Reported symptoms were identified via the MedDRA dictionary, displayed per the volume of posts mentioning them, and aggregated at the user level. Associations were assessed by computing co-occurrences in users’ messages, as pairs of preferred terms. Discussion topics were analyzed using the Biterm Topic Modeling;difficulties and unmet needs were explored manually. To identify patient profiles in relation to their symptoms, each preferred term’s total was used to create user-level hierarchal clusters. Results Between January 1, 2020, and August 10, 2021, overall, 15,364 messages were identified as originating from 6494 patients of long COVID or their caregivers. Our analyses revealed 3 major symptom co-occurrences: asthenia-dyspnea (102/289, 35.3%), asthenia-anxiety (65/289, 22.5%), and asthenia-headaches (50/289, 17.3%). The main reported difficulties were symptom management (150/424, 35.4% of messages), psychological impact (64/424,15.1%), significant pain (51/424, 12.0%), deterioration in general well-being (52/424, 12.3%), and impact on daily and professional life (40/424, 9.4% and 34/424, 8.0% of messages, respectively). We identified 3 profiles of patients in relation to their symptoms: profile A (n=406 patients) reported exclusively an asthenia symptom;profile B (n=129) expressed anxiety (n=129, 100%), asthenia (n=28, 21.7%), dyspnea (n=15, 11.6%), and ageusia (n=3, 2.3%);and profile C (n=141) described dyspnea (n=141, 100%), and asthenia (n=45, 31.9%). Approximately 49.1% of users (79/161) continued expressing symptoms after more than 3 months post infection, and 20.5% (33/161) after 1 year. Conclusions Long COVID is a lingering condition that affects people worldwide, physically and psychologically. It impacts Long Haulers’ quality of life, everyday tasks, and professional activities. Social media played an undeniable role in raising and delivering Long Haulers’ voices and can potentially rapidly provide large volumes of valuable patient-reported information. Since long COVID was a self-titled condition by patients themselves via social media, it is imperative to continuously include their perspectives in related research. Our results can help design patient-centric instruments to be further used in clinical practice to better capture meaningful dimensions of long COVID.

Contribution of perceived loneliness to suicidal thoughts among French university students during the COVID-19 pandemic.

Restrictive measures during the COVID-19 epidemic have led to increased levels of loneliness, especially among university students, although the influence on suicidal thoughts remains unclear. In this cross-sectional study of 1913 French university students, those with the highest level of loneliness had a fourfold increased risk of suicidal thoughts. Perceived loneliness should be incorporated into suicide risk assessment, and assistance in coping with loneliness should be considered as a means of reducing suicidal risk in vulnerable groups, like university students.

Who is hesitant about Covid-19 vaccines? The profiling of participants in a French online cohort.

OBJECTIVES: To report the characteristics of vaccine-hesitant individuals in a French-speaking adult population in the context of the SARS-CoV-2 pandemic; and to identify predictors of hesitancy about Covid-19-related vaccines. METHODS: Between April and May 2020, 1640 French-speaking adults participating in an online cohort were classified according to their attitudes towards vaccination as: "hesitant", "anti-vaccination", and "pro-vaccination". Descriptive statistics, univariate multinomial regression models and multivariate analyses were compiled and carried out. RESULTS: At the time of inclusion, compared to pro-vaccination participants, hesitant participants were more frequently females (p=0.044), not annually vaccinated against flu (p=0.026), less optimistic about the discovery of a treatment against Covid-19 in a few months (p<0.001), less ready to undergo this treatment (p<0.001), presenting less trust in the ability of public health authorities to control the pandemic (p=0.036) and reporting lower scores on knowledge-related scales (p values from <0.001 to 0.002). Univariate analyses confirmed these results with odds ratios ranging from 1.51 [1.05-2.17] to 2.19 [1.56-3.07]. In the multivariate models, the remaining variables associated with hesitant compared to pro-vaccination attitudes were discovery of a treatment against Covid-19 in a few months (OR=2.57 [1.73-3.81]), being ready to undergo this treatment (OR=7.07 [4.89-10.22]), digital vaccine literacy (OR=1.70 [1.14-2.54]) and general health literacy (OR=1.49 [1.03-2.15]). DISCUSSION: In a continuum of relative acceptance of Covid-19-related vaccines, hesitant individuals were situated in between the behaviours and characteristics of pro-vaccination and anti-vaccination groups. While their characteristics were in line with the literature, this study was the first to report data on health literacy, digital vaccine literacy and capacity to detect fake news associated with vaccine hesitancy. CONCLUSIONS: While failing to identify straightforward predictors, findings suggest that continued education and communication campaigns focused on improving vaccine literacy, particularly among women younger than 35 years, could heighten the proportion of persons accepting vaccination.

A repeated cross-sectional analysis assessing mental health conditions of adults as per student status during key periods of the COVID-19 epidemic in France.

Previous studies have shown the negative impact of the COVID-19 epidemic on students' mental health. It is, however, uncertain whether students are really at higher risk of mental health disturbances than non-students and if they are differentially impacted by lockdown periods over time. The objective of our study was to compare the frequency of depressive symptoms, anxiety, and suicidal thoughts in students and non-students enrolled in the same study in France and during the same key periods of the COVID-19 epidemic. Using a repeated cross-sectional design, we collected data from a sample of 3783 participants in the CONFINS study during three recruitment waves between March 2020 and January 2021. Multivariate logistic regression models, adjusted for potential confounding factors, showed that students were more likely to have high scores of depressive symptoms and anxiety more frequently than non-students. These differences were particularly strong during the first (depressive symptoms: adjusted odds ratio aOR 1.59, 95% CI 1.22-2.08; anxiety: aOR 1.63, 95% CI 1.22-2.18) and second lockdowns (depressive symptoms: aOR 1.80, 95% CI 1.04-3.12; anxiety: aOR 2.25, 95% CI 1.24-4.10). These findings suggest that the restrictive measures-lockdown and curfew-have an alarmingly stronger negative impact on students than on non-students and underline the frailty of students' mental health and the need to pay greater attention to this population in this epidemic-related context.

Mental health condition of college students compared to non-students during COVID-19 lockdown: the CONFINS study.

OBJECTIVES: To estimate the effect of student status on mental health condition during COVID-19 general lockdown in France. DESIGN: Cross-sectional analysis comparing students and non-students recruited in the same study. SETTING: Participants of the web-based CONFINS study implemented during the general lockdown in France in spring 2020. PARTICIPANTS: 2260 participants (78% women) including 1335 students (59%). PRIMARY AND SECONDARY OUTCOME MEASURES: Through an online questionnaire, participants declared if they have experienced suicidal thoughts, coded their perceived stress on a 10-points scale and completed validated mental health scales (Patient Health Questionnaire-9 for depressive symptoms, Generalised Anxiety Disorder-7 for anxiety symptoms) during the last 7 days. The effect of college student status on each mental health condition was estimated using multivariate logistic regression analyses. Stratified models for students and non-students were performed to identify population-specific factors. RESULTS: Student status was associated with a higher frequency of depressive symptoms (adjusted OR (aOR)=1.58; 95% CI 1.17 to 2.14), anxiety symptoms (aOR=1.51; 95% CI 1.10 to 2.07), perceived stress (n=1919, aOR=1.70, 95% CI 1.26 to 2.29) and suicidal thoughts (n=1919, aOR=1.57, 95% CI 0.97 to 2.53). Lockdown conditions that could be potentially aggravating on mental health like isolation had a higher impact on students than on non-students. CONCLUSIONS: College students were at higher risk of mental health disturbances during lockdown than non-students, even after taking into account several potential confounding factors. A close follow-up and monitoring of students' mental health status is warranted during lockdown periods in this vulnerable population.

Fuzzy Matching for Symptom Detection in Tweets: Application to Covid-19 During the First Wave of the Pandemic in France.

The exhaustive automatic detection of symptoms in social media posts is made difficult by the presence of colloquial expressions, misspellings and inflected forms of words. The detection of self-reported symptoms is of major importance for emergent diseases like the Covid-19. In this study, we aimed to (1) develop an algorithm based on fuzzy matching to detect symptoms in tweets, (2) establish a comprehensive list of Covid-19-related symptoms and (3) evaluate the fuzzy matching for Covid-19-related symptom detection in French tweets. The Covid-19-related symptom list was built based on the aggregation of different data sources. French Covid-19-related tweets were automatically extracted using a dedicated data broker during the first wave of the pandemic in France. The fuzzy matching parameters were finetuned using all symptoms from MedDRA and then evaluated on a subset of 5000 Covid-19-related tweets in French for the detection of symptoms from our Covid-19-related list. The fuzzy matching improved the detection by the addition of 42% more correct matches with an 81% precision.

Concerns Discussed on Chinese and French Social Media During the COVID-19 Lockdown: Comparative Infodemiology Study Based on Topic Modeling.

BACKGROUND: During the COVID-19 pandemic, numerous countries, including China and France, have implemented lockdown measures that have been effective in controlling the epidemic. However, little is known about the impact of these measures on the population as expressed on social media from different cultural contexts. OBJECTIVE: This study aims to assess and compare the evolution of the topics discussed on Chinese and French social media during the COVID-19 lockdown. METHODS: We extracted posts containing COVID-19-related or lockdown-related keywords in the most commonly used microblogging social media platforms (ie, Weibo in China and Twitter in France) from 1 week before lockdown to the lifting of the lockdown. A topic model was applied independently for three periods (prelockdown, early lockdown, and mid to late lockdown) to assess the evolution of the topics discussed on Chinese and French social media. RESULTS: A total of 6395; 23,422; and 141,643 Chinese Weibo messages, and 34,327; 119,919; and 282,965 French tweets were extracted in the prelockdown, early lockdown, and mid to late lockdown periods, respectively, in China and France. Four categories of topics were discussed in a continuously evolving way in all three periods: epidemic news and everyday life, scientific information, public measures, and solidarity and encouragement. The most represented category over all periods in both countries was epidemic news and everyday life. Scientific information was far more discussed on Weibo than in French tweets. Misinformation circulated through social media in both countries; however, it was more concerned with the virus and epidemic in China, whereas it was more concerned with the lockdown measures in France. Regarding public measures, more criticisms were identified in French tweets than on Weibo. Advantages and data privacy concerns regarding tracing apps were also addressed in French tweets. All these differences were explained by the different uses of social media, the different timelines of the epidemic, and the different cultural contexts in these two countries. CONCLUSIONS: This study is the first to compare the social media content in eastern and western countries during the unprecedented COVID-19 lockdown. Using general COVID-19-related social media data, our results describe common and different public reactions, behaviors, and concerns in China and France, even covering the topics identified in prior studies focusing on specific interests. We believe our study can help characterize country-specific public needs and appropriately address them during an outbreak.