Social media uses amongst adolescents: motives, minority stress and eudaimonic well-being / Uso de redes sociales en adolescentes: motivación, estrés de minorías y bienestar eudaimónico

Introduction: The scientific evidence regarding the effects of online social media use on the well-being of adolescents is mixed. In gen-eral, passive uses (receiving, viewing content without interacting) and more screen time are related to lower well-being when compared with active uses (direct interactions and interpersonal exchanges). Objectives:This study ex-amines the types and motives for social media usage amongst adolescents, differentiating them by gender identity and sexual orientation, as well as its effects on eudaimonic well-being and minority stress. Method: A cross-sectional study was conducted with 1259 adolescents, aged 14 to 19 (M= 16.19; SD= 1.08), analysing the Scale of Motives for Using Social Net-working Sites, eudaimonic well-being, the Sexual Minority Adolescent Stress Inventory, screen time and profile type. Results:The results found that longer use time is related to finding partners, social connection and friendships; that gay and bisexual (GB) adolescents perceive more distal stressors online;and that females have higher levels of well-being. Discus-sion: The public profiles of GB males increase self-expression, although minority stress can be related to discrimination, rejection or exclusion. Dif-ferentiated socialization may contribute to a higher level of well-being in females, with both active and passive uses positively effecting eudaimonic well-being in adolescents.(AU)

Introduction: The scientific evidence regarding the effects of online social media use on the well-being of adolescents is mixed. In general, passive uses (receiving, viewing content without interacting) and more screen time are related to lower well-being when compared with active uses (direct interactions and interpersonal exchanges). Objectives: This study examines the types and motives for social media usage amongst adolescents, differentiating them by gender identity and sexual orientation, as well as its effects on eudaimonic well-being and minority stress. Method: A cross-sectional study was conducted with 1259 adolescents, aged 14 to 19 (M = 16.19; SD = 1.08), analysing the Scale of Motives for Using Social Networking Sites, eudaimonic well-being, the Sexual Minority Adolescent Stress Inventory, screen time and profile type. Results: The results found that longer use time is related to finding partners, social connection and friendships; that gay and bisexual (GB) adolescents perceive more distal stressors online; and that females have higher levels of well-being. Discussion: The public profiles of GB males increase self-expression, although minority stress can be related to discrimination, rejection or exclusion. Differentiated socialization may contribute to a higher level of well-being in females, with both active and passive uses positively effecting eudaimonic well-being in adolescents.(AU)

Using machine learning algorithms and techniques for defining the impact of affective temperament types, content search and activities on the internet on the development of problematic internet use in adolescents' population.

Background: By using algorithms and Machine Learning - ML techniques, the aim of this research was to determine the impact of the following factors on the development of Problematic Internet Use (PIU): sociodemographic factors, the intensity of using the Internet, different contents accessed on the Internet by adolescents, adolescents' online activities, life habits and different affective temperament types. Methods: Sample included 2,113 adolescents. The following instruments were used: questionnaire about: socio-demographic characteristics, intensity of the Internet use, content categories and online activities on the Internet; Facebook (FB) usage and life habits; The Internet Use Disorder Scale (IUDS). Based on their scores on the scale, subjects were divided into two groups - with or without PIU; Temperament Evaluation of Memphis, Pisa, Paris, and San Diego scale for adolescents (A-TEMPS-A). Results: Various ML classification models on our data set were trained. Binary classification models were created (class-label attribute was PIU value). Models hyperparameters were optimized using grid search method and models were validated using k-fold cross-validation technique. Random forest was the model with the best overall results and the time spent on FB and the cyclothymic temperament were variables of highest importance for these model. We also applied the ML techniques Lasso and ElasticNet. The three most important variables for the development of PIU with both techniques were: cyclothymic temperament, the longer use of the Internet and the desire to use the Internet more than at present time. Group of variables having a protective effect (regarding the prevention of the development of PIU) was found with both techniques. The three most important were: achievement, search for contents related to art and culture and hyperthymic temperament. Next, 34 important variables that explain 0.76% of variance were detected using the genetic algorithms. Finally, the binary classification model (with or without PIU) with the best characteristics was trained using artificial neural network. Conclusion: Variables related to the temporal determinants of Internet usage, cyclothymic temperament, the desire for increased Internet usage, anxious and irritable temperament, on line gaming, pornography, and some variables related to FB usage consistently appear as important variables for the development of PIU.

The 100 Most Impactful Articles on Total Shoulder Arthroplasty: An Altmetric Analysis.

Background: To use the top 100 articles pertaining to total shoulder arthroplasty (TSA) to understand the impact that social media platforms have on the dissemination of shoulder research while highlighting bibliometric factors associated with Altmetric Attention Score (AAS) to offer insight into the impact that social media platforms have on the dissemination, attention, and citation of shoulder research publications. Methods: In June 2023, the Altmetric database was searched using the following PubMed MeSH terms: "total shoulder arthroplasty" or "TSA." Articles with the highest AAS were screened to exclude other topics unrelated to TSA. The top 100 articles that met inclusion criteria were used in the final analysis. Bibliometric factors pertaining to each study were collected for further analysis of article characteristics in accordance with prior studies. Results: The Altmetric Database query yielded 1,283 studies. After applying our inclusion criteria, the top 118 articles with the highest AAS were identified. The mean AAS was 29.14 ± 42.35, with a range of 13 to 402. The included articles represented 27 journals, with 70 articles attributed to 2 journals: Journal of Shoulder and Elbow Surgery (JSES; 43%) and the Journal of Bone and Joint Surgery (JBJS; 16%). There was a significant increase in AAS for the presence of a conflict of interest (p = 0.042) and open access status (p < 0.01), but no association between the score and citation rate (p > 0.05). Conclusions: Top articles on TSA, as defined by high AAS, mostly comprise original clinical research performed in the United States or Europe. The presence of a conflict of interest and open access status is associated with an increase in AAS, but there was no association between AAS score and citation rate.

Trends of fear and anger on YouTube during the initial stage of the COVID-19 outbreak in South Korea.

BACKGROUND: The COVID-19 pandemic has been the most widespread and threatening health crisis experienced by the Korean society. Faced with an unprecedented threat to survival, society has been gripped by social fear and anger, questioning the culpability of this pandemic. This study explored the correlation between social cognitions and negative emotions and their changes in response to the severe events stemming from the COVID-19 pandemic in South Korea. METHODS: The analysis was based on a cognitive-emotional model that links fear and anger to the social causes that trigger them and used discursive content from comments posted on YouTube's COVID-19-related videos. A total of 182,915 comments from 1,200 videos were collected between January and December 2020. We performed data analyses and visualizations using R, Netminer 4.0, and Gephi software and calculated Pearson's correlation coefficients between emotions. RESULTS: YouTube videos were analyzed for keywords indicating cognitive assessments of major events related to COVID-19 and keywords indicating negative emotions. Eight topics were identified through topic modeling: causes and risks, perceptions of China, media and information, infection prevention rules, economic activity, school and infection, political leaders, and religion, politics, and infection. The correlation coefficient between fear and anger was 0.462 (p < .001), indicating a moderate linear relationship between the two emotions. Fear was the highest from January to March in the first year of the COVID-19 outbreak, while anger occurred before and after the outbreak, with fluctuations in both emotions during this period. CONCLUSIONS: This study confirmed that social cognitions and negative emotions are intertwined in response to major events related to the COVID-19 pandemic, with each emotion varying individually rather than being ambiguously mixed. These findings could aid in developing social cognition-emotion-based public health strategies through education and communication during future pandemic outbreaks.

Understanding the determinants of vaccine hesitancy in the United States: A comparison of social surveys and social media.

The COVID-19 pandemic prompted governments worldwide to implement a range of containment measures, including mass gathering restrictions, social distancing, and school closures. Despite these efforts, vaccines continue to be the safest and most effective means of combating such viruses. Yet, vaccine hesitancy persists, posing a significant public health concern, particularly with the emergence of new COVID-19 variants. To effectively address this issue, timely data is crucial for understanding the various factors contributing to vaccine hesitancy. While previous research has largely relied on traditional surveys for this information, recent sources of data, such as social media, have gained attention. However, the potential of social media data as a reliable proxy for information on population hesitancy, especially when compared with survey data, remains underexplored. This paper aims to bridge this gap. Our approach uses social, demographic, and economic data to predict vaccine hesitancy levels in the ten most populous US metropolitan areas. We employ machine learning algorithms to compare a set of baseline models that contain only these variables with models that incorporate survey data and social media data separately. Our results show that XGBoost algorithm consistently outperforms Random Forest and Linear Regression, with marginal differences between Random Forest and XGBoost. This was especially the case with models that incorporate survey or social media data, thus highlighting the promise of the latter data as a complementary information source. Results also reveal variations in influential variables across the five hesitancy classes, such as age, ethnicity, occupation, and political inclination. Further, the application of models to different MSAs yields mixed results, emphasizing the uniqueness of communities and the need for complementary data approaches. In summary, this study underscores social media data's potential for understanding vaccine hesitancy, emphasizes the importance of tailoring interventions to specific communities, and suggests the value of combining different data sources.

A qualitative content analysis of cannabis-related discussions on Reddit during the COVID-19 pandemic.

Social media has become an increasingly important way to seek and share experiences, support, knowledge, and advice during the COVID-19 pandemic. Reddit, a pseudonymous social media platform, was one way that young people interacted during the pandemic. Our study goals were two-fold: (1) to categorize information sought and provided by users of r/saplings, a subreddit devoted to cannabis use and is often used by young people, and (2) to examine if conversations changed during the COVID-19 pandemic. We extracted 213 randomly selected posts and 2,546 related comments across four time periods (before the pandemic, during the first wave, summer, and next fall). We assessed the volume of posts and comments throughout our study period and conducted a qualitative content analysis. Quantitatively, the findings demonstrated an increase in the number of posts and comments throughout the study period. Given the substantial growth in subreddit activity throughout our study period, Reddit may play an increasingly important role in youth socialization related to cannabis. From the content analysis, we identified three major themes: how to acquire cannabis, how to use cannabis, and associated consequences. Reddit-users prioritized certain content in their posts at different stages of the pandemic. 'Places to acquire' and 'future use' were most common at the beginning of the pandemic, while the theme of 'consequences' and the topic of 'tolerance' became more prominent during the summer months. The comments to these posts were generally thorough and responsive to the post. Nearly all the information came from opinions or personal experiences. Firstly, our findings suggest that young people viewed Reddit as a viable outlet for conversations about cannabis. Secondly, due to the nature of the peer comments and lack of verifiable information being exchanged, misinformation may still circulate and inadvertently worsen the efforts to reduce cannabis-related harm. Interventions that provide understandable and accurate cannabis-related information in accessible formats may increase young people's ability to access and practice harm reduction.

Threatening language detection from Urdu data with deep sequential model.

The Urdu language is spoken and written on different social media platforms like Twitter, WhatsApp, Facebook, and YouTube. However, due to the lack of Urdu Language Processing (ULP) libraries, it is quite challenging to identify threats from textual and sequential data on the social media provided in Urdu. Therefore, it is required to preprocess the Urdu data as efficiently as English by creating different stemming and data cleaning libraries for Urdu data. Different lexical and machine learning-based techniques are introduced in the literature, but all of these are limited to the unavailability of online Urdu vocabulary. This research has introduced Urdu language vocabulary, including a stop words list and a stemming dictionary to preprocess Urdu data as efficiently as English. This reduced the input size of the Urdu language sentences and removed redundant and noisy information. Finally, a deep sequential model based on Long Short-Term Memory (LSTM) units is trained on the efficiently preprocessed, evaluated, and tested. Our proposed methodology resulted in good prediction performance, i.e., an accuracy of 82%, which is greater than the existing methods.

The relationship between family functioning and social media addiction among university students: a moderated mediation model of depressive symptoms and peer support.

BACKGROUND: Social media addiction (SMA) is an increasing problem, especially among young adults. Little is known about university students' SMA and family functioning. This study aimed to explore the mediating effect of depressive symptoms and the moderating effect of peer support in the relationship between family functioning and SMA among young adults. METHODS: A sample of 1862 Chinese university students completed an online survey including the Bergen Social Media Addiction Scale (BSMAS), Family APGAR, the Patient Health Questionnaire (PHQ-9), peer support, and demographic characteristics. Hierarchical regression and moderated mediation analysis were used to test the effects and pathways among them. RESULTS: Of the 1840 participants, 30.11% experienced SMA, 38.80% had family dysfunction and 15.98% had depressive symptoms. Hierarchical multiple regression showed better family functioning significantly predicted less SMA (ß = -0.26, p < 0.001) and lower depressive symptoms (ß = -0.58, p < 0.001), after adjusting for covariates. Mediation analysis verified that depressive symptoms mediated the effect of family functioning on SMA (indirect effect = -0.22, 95%CI[-0.28, -0.17]). Furthermore, the interaction of family functioning and peer support was negatively related to depressive symptoms (ß= -0.03, 95% CI[-0.05, -0.01]) and the interaction of depressive symptoms and peer support was positively related to SMA (ß = 0.01, 95%CI[0.004, 0.02]). Additional analysis further confirmed that peer support decreased depressive symptoms among young adults from dysfunctional families, and increased SMA behaviors in individuals with depressive symptoms. CONCLUSION: Better family functioning and lower depressive symptoms may contribute to less social media addiction among Chinese university students. Peer support could moderate the mediating role of depressive symptoms on social media addiction in individuals with family dysfunction.

Social media use by patients with hypermobile Ehlers-Danlos syndrome.

BACKGROUND: Patients with uncommon genetic conditions often face limited in-person resources for social and informational support. Hypermobile Ehlers-Danlos syndrome (hEDS) is a rare or underdiagnosed hereditary disorder of the connective tissue, and like those with similar diseases, patients with hEDS have begun to turn to social media in search of care and community. The aims of our study were to understand the usage habits and perceptions of utility of social media use for patients with hEDS in order to formulate suggestions for how clinicians may best engage these and similar patient populations about this topic. METHODS: We conducted both a quantitative survey and qualitative interviews with patients who had received a robust clinical diagnosis of hEDS. RESULTS: Twenty-four individuals completed the initial survey, and a subset of 21 of those participants completed an interview. Through thematic analysis, we identified four primary themes related to their experience with social media: (1) befriending others with their disease, (2) seeking and vetting information, (3) the risks and downsides of social media use, and (4) the desire for clinicians to discuss this topic with them. CONCLUSION: We conclude by proposing five suggestions that emerge empirically from our data. These proposals will help clinicians engage their patients regarding social media use in order to promote its potential benefits and circumvent its potential harms as they pursue support for their hereditary condition.

Self-certification: A novel method for increasing sharing discernment on social media.

The proliferation of misinformation on social media platforms has given rise to growing demands for effective intervention strategies that increase sharing discernment (i.e. increase the difference in the probability of sharing true posts relative to the probability of sharing false posts). One suggested method is to encourage users to deliberate on the veracity of the information prior to sharing. However, this strategy is undermined by individuals' propensity to share posts they acknowledge as false. In our study, across three experiments, in a simulated social media environment, participants were shown social media posts and asked whether they wished to share them and, sometimes, whether they believed the posts to be truthful. We observe that requiring users to verify their belief in a news post's truthfulness before sharing it markedly curtails the dissemination of false information. Thus, requiring self-certification increased sharing discernment. Importantly, requiring self-certification didn't hinder users from sharing content they genuinely believed to be true because participants were allowed to share any posts that they indicated were true. We propose self-certification as a method that substantially curbs the spread of misleading content on social media without infringing upon the principle of free speech.

Is YouTube a Useful Source of Information on Pressure Injuries? A Content, Reliability, and Quality Analysis.

OBJECTIVE: To evaluate the comprehensiveness, reliability, and quality of YouTube videos related to pressure injuries. METHODS: The authors searched YouTube for relevant videos using the keywords "pressure injury", "pressure ulcer", "bedsore", "pressure injury etiology", "pressure injury classification", "pressure injury prevention", "pressure injury risk assessment", and "pressure injury management". Of the 1,023 videos screened, 269 met the inclusion criteria and were included in the study. For each video, the authors recorded the number of views, likes, and comments; the length; and the video upload source. The Comprehensiveness Assessment Tool for Pressure Injuries, the Quality Criteria for Consumer Health Information score, and the Global Quality Score were used to evaluate the comprehensiveness, reliability, and quality of the videos. RESULTS: The mean length of the 269 videos was 6.22 ± 4.62 minutes (range, 0.18-19.47 minutes). Only 14.5% of the videos (n = 39) were uploaded by universities or professional organizations. Most videos included information about PI prevention (69.5%), followed by PI management (27.9%). The mean comprehensiveness score was 2.33 ± 1.32 (range, 1-5). Nearly half of the videos (49.1%) were not reliable. However, the quality of 43.9% of the videos was somewhat useful. The Quality Criteria for Consumer Health Information mean scores of universities/professional organizations (P < .001), nonprofit healthcare professionals (P = .015), and independent health information channel videos (P = .026) were higher than the mean score of medical advertising/profit companies channel videos. CONCLUSIONS: This study draws attention to the need for more comprehensive, high-quality, and reliable videos about PIs. It is important that videos on YouTube provide comprehensive and reliable information for patients, caregivers, students, or providers seeking information on PI prevention, assessment, and management.

Social Media Discourse Related to Caregiving for Older Adults Living With Alzheimer Disease and Related Dementias: Computational and Qualitative Study.

BACKGROUND: In the United States, caregivers of people living with Alzheimer disease and Alzheimer disease-related dementias (AD/ADRD) provide >16 billion hours of unpaid care annually. These caregivers experience high levels of stress and burden related to the challenges associated with providing care. Social media is an emerging space for individuals to seek various forms of support. OBJECTIVE: We aimed to explore the primary topics of conversation on the social media site Reddit related to AD/ADRD. We then aimed to explore these topics in depth, specifically examining elements of social support and behavioral symptomology discussed by users. METHODS: We first generated an unsupervised topic model from 6563 posts made to 2 dementia-specific subreddit forums (r/Alzheimers and r/dementia). Then, we conducted a manual qualitative content analysis of a random subset of these data to further explore salient themes in the corpus. RESULTS: The topic model with the highest overall coherence score (0.38) included 10 topics, including caregiver burden, anxiety, support-seeking, and AD/ADRD behavioral symptomology. Qualitative analyses provided added context, wherein users sought emotional and informational support for many aspects of the care experience, including assistance in making key care-related decisions. Users expressed challenging and complex emotions on Reddit, which may be taboo to express in person. CONCLUSIONS: Reddit users seek many different forms of support, including emotional and specific informational support, from others on the internet. Users expressed a variety of concerns, challenges, and behavioral symptoms to manage as part of the care experience. The unique (ie, anonymous and moderated) nature of the forum allowed for a safe space to express emotions free from documented caregiver stigma. Additional support structures are needed to assist caregivers of people living with AD/ADRD.

Oral cancer: analysis of the clarity of publications in Instagram profiles of official health agencies in Brazil.

This article aims to analyze the clarity and engagement measures of publications on oral cancer in the Instagram profiles of official health agencies in Brazil. An infodemiological study was conducted with 81 profiles. Data collected concerned content classification, account and media, manner of addressing the topic, number of posts, likes, comments, views and hashtags. The clarity of the educational publications was assessed with the Brazilian version of the Clear Communication Index (BR-CDC-CCI). Data analysis involved Spearman's correlation and the Mann-Whitney test (α = 5%). A total of 775 publications on oral cancer were found. The average BR-CDC-CCI score was 69.8 (SD = 15.5). The clarity of the information was adequate in 9.5% of the educational publications. Positive correlations were found between the number of likes and engagement (comments [r = 0.49], views [r = 0.96]), number of hashtags (r = 0.13) and year of publication (r = 0.21). Publications from the Health Ministry had a significantly higher BR-CDC-CCI score compared to the other profiles. Publications on oral cancer were correlated with engagement, year of publication and number of hashtags. Public agencies increased publications to reach the population, but the clarity of the content was low.

Sentiment analysis of the Hamas-Israel war on YouTube comments using deep learning.

Sentiment analysis aims to classify text based on the opinion or mentality expressed in a situation, which can be positive, negative, or neutral. Therefore, in the world, a lot of opinions are available on various social media sites, which must be gathered and analyzed to assess the general public's opinion. Finding and monitoring comments, as well as manually extracting the information contained in them, is a difficult task due to the vast diversity of ideas on YouTube. Identifying public opinion on war topics is crucial for offering insights to opposing sides based on popular opinion and emotions about the ongoing war. To address the gap, we build a model on YouTube comment sentiment analysis of the Hamas-Israel war to determine public opinion. In this study, we address the gaps by developing a deep learning-based approach for sentiment analysis. We have collected 24,360 comments from popular YouTube News Channels including BBC, WION, Aljazeera, and others about the Hamas-Israel War using YouTube API and Google spreadsheet and labeled them by linguistic experts into three classes: positive, negative, and neutral. Then, textual comments were preprocessed using natural language processing (NLP) techniques, and features were extracted using Word2vec, FastText, and GloVe. Moreover, we have used the SMOTE data balancing technique and used different data splits, but the 80/20 train-test split ratio has the highest accuracy. For classification model building, commonly used classification algorithms LSTM, Bi-LSTM, GRU, and Hybrid of CNN and Bi-LSTM were applied, and their performance is compared. As a result, the Hybrid of CNN and Bi-LSTM with Word2vec achieved the highest performance with 95.73% accuracy for comments classifications.

Applying deep learning on social media to investigate cultural ecosystem services in protected areas worldwide.

Protected areas (PAs) are the cornerstone of conservation efforts. Although they provide many benefits to humanity, the variability in the provision of cultural ecosystem services (CES) among global PAs remains unknown. To investigate this, we combined Convolutional Neural Networks with hierarchical clustering to categorize photos from Flickr taken in PAs worldwide. A final sample of 87,090 photos in 2813 PAs within 207 countries was obtained. Distinct global patterns of CES activities emerged. Such activities had three main interaction types: human-nature (abiotic), human-nature (biotic) and human-human. Human-nature (abiotic) interactions dominated in mountain ranges. Human-nature (biotic) photos were more common in equatorial countries, and human-human photos occurred mainly in Europe. To determine the extent of the influence of biome type of PAs on CES, mixed-effects models were subsequently run. These models additionally included the country of PAs as a random effect. Despite differences in physical environments, PAs within each country generally shared similar CES types. Moreover, the effect of biome differences was marginal, thereby demonstrating that country-level management of PAs likely has a more important role in influencing CES activities in PAs. To conclude, we suggest that our results demonstrate the utility of social media data for understanding visitor activities in PAs.

Monitoring Adverse Drug Events in Web Forums: Evaluation of a Pipeline and Use Case Study.

BACKGROUND: To mitigate safety concerns, regulatory agencies must make informed decisions regarding drug usage and adverse drug events (ADEs). The primary pharmacovigilance data stem from spontaneous reports by health care professionals. However, underreporting poses a notable challenge within the current system. Explorations into alternative sources, including electronic patient records and social media, have been undertaken. Nevertheless, social media's potential remains largely untapped in real-world scenarios. OBJECTIVE: The challenge faced by regulatory agencies in using social media is primarily attributed to the absence of suitable tools to support decision makers. An effective tool should enable access to information via a graphical user interface, presenting data in a user-friendly manner rather than in their raw form. This interface should offer various visualization options, empowering users to choose representations that best convey the data and facilitate informed decision-making. Thus, this study aims to assess the potential of integrating social media into pharmacovigilance and enhancing decision-making with this novel data source. To achieve this, our objective was to develop and assess a pipeline that processes data from the extraction of web forum posts to the generation of indicators and alerts within a visual and interactive environment. The goal was to create a user-friendly tool that enables regulatory authorities to make better-informed decisions effectively. METHODS: To enhance pharmacovigilance efforts, we have devised a pipeline comprising 4 distinct modules, each independently editable, aimed at efficiently analyzing health-related French web forums. These modules were (1) web forums' posts extraction, (2) web forums' posts annotation, (3) statistics and signal detection algorithm, and (4) a graphical user interface (GUI). We showcase the efficacy of the GUI through an illustrative case study involving the introduction of the new formula of Levothyrox in France. This event led to a surge in reports to the French regulatory authority. RESULTS: Between January 1, 2017, and February 28, 2021, a total of 2,081,296 posts were extracted from 23 French web forums. These posts contained 437,192 normalized drug-ADE couples, annotated with the Anatomical Therapeutic Chemical (ATC) Classification and Medical Dictionary for Regulatory Activities (MedDRA). The analysis of the Levothyrox new formula revealed a notable pattern. In August 2017, there was a sharp increase in posts related to this medication on social media platforms, which coincided with a substantial uptick in reports submitted by patients to the national regulatory authority during the same period. CONCLUSIONS: We demonstrated that conducting quantitative analysis using the GUI is straightforward and requires no coding. The results aligned with prior research and also offered potential insights into drug-related matters. Our hypothesis received partial confirmation because the final users were not involved in the evaluation process. Further studies, concentrating on ergonomics and the impact on professionals within regulatory agencies, are imperative for future research endeavors. We emphasized the versatility of our approach and the seamless interoperability between different modules over the performance of individual modules. Specifically, the annotation module was integrated early in the development process and could undergo substantial enhancement by leveraging contemporary techniques rooted in the Transformers architecture. Our pipeline holds potential applications in health surveillance by regulatory agencies or pharmaceutical companies, aiding in the identification of safety concerns. Moreover, it could be used by research teams for retrospective analysis of events.

[The mediating role of social media addiction and sleep quality in the association between social media usage and depressive symptoms in university students]. / O papel mediador da dependência de mídia social e da qualidade do sono na associação entre tempo de uso de mídia social e sintomas depressivos em universitários.

Increase in time spent on social media and its association with depressive symptoms, especially among young adults, has generated the need to understand how this association occurs in order to support the development of policies to reduce harm and complications. In view of this fact, this study aimed to assess the mediating effect of social media addiction and sleep quality on the association between time spent on social media and depressive symptoms in Brazilian university students. This is a cross-sectional study conducted with 2,823 university students, who provided information regarding time spent on social media, social media addiction, depressive symptoms and sleep quality. The mediation analysis, adjusted for confounding factors, was performed using the PROCESS macro for SPSS to obtain the total (c), direct (c'), and indirect effects (EI1, EI2, and EI3). The results identified an association between time spent on social media and depressive symptoms, mediated by social media addiction (EI1 = 20%) and sleep quality (EI1 = 40%). These findings help expand knowledge about the mechanisms that mutually influence the relationship between time spent on social media and depressive symptoms, supporting the adoption of strategies to reduce harm resulting from excessive social media use.

O aumento do uso de mídias sociais e sua associação com sintomas depressivos, especialmente em jovens adultos, tem gerado a necessidade do entendimento de como ocorre tal associação para subsidiar políticas de redução de danos e agravos. Nesse sentido, este estudo objetivou verificar o efeito mediador da dependência de mídias sociais e da qualidade do sono na associação entre o tempo de uso de mídias sociais e sintomas depressivos em universitários brasileiros. Trata-se de um estudo transversal, realizado com 2.823 universitários, que forneceram informações referentes ao tempo de uso de mídias sociais, à dependência de mídias sociais, aos sintomas depressivos e à qualidade do sono. A análise de mediação, ajustada por fatores de confusão, foi realizada por meio do software PROCESS para SPSS, para obtenção do efeito total (c), direto (c') e indiretos (EI1, EI2 e EI3). Os resultados identificaram associação entre o tempo de uso de mídias sociais e os sintomas depressivos, mediada pela dependência de mídias sociais (EI1 = 20%) e pela qualidade do sono (EI1 = 40%). Os resultados permitem ampliar o conhecimento acerca dos mecanismos que influenciam mutuamente a relação entre o tempo de uso de mídias sociais e os sintomas depressivos, auxiliando na adoção de estratégias de redução de danos decorrentes do uso excessivo de mídias sociais.

El aumento del uso de las redes sociales y su asociación con síntomas depresivos, especialmente en adultos jóvenes, ha generado la necesidad de comprender cómo se produce esta asociación como una forma de apoyar las políticas de reducción de daños y afecciones. En ese sentido, el presente estudio tuvo como objetivo verificar el efecto mediador de la adicción a las redes sociales y de la calidad del sueño en la asociación entre el tiempo de uso de las redes sociales y los síntomas depresivos en estudiantes universitarios brasileños. Se trata de un estudio transversal, realizado con 2.823 estudiantes universitarios, quienes brindaron información respecto al tiempo de uso de las redes sociales, adicción a las redes sociales, síntomas depresivos y calidad del sueño. El análisis de mediación, ajustado por factores de confusión, se realizó por medio del software PROCESS para SPSS, para obtener el efecto total (c), directo (c') e indirectos (EI1, EI2 y EI3). Los resultados identificaron una asociación entre el tiempo de uso de las redes sociales y los síntomas depresivos, mediada por adicción a las redes sociales (EI1 = 20%) y la calidad del sueño (EI1 = 40%). Los resultados permiten ampliar el conocimiento acerca de los mecanismos que influyen mutuamente en la relación entre tiempo de uso de las redes sociales y los síntomas depresivos, ayudando a adoptar estrategias para reducir los daños resultantes del uso excesivo de las redes sociales.

Bubble reachers and uncivil discourse in polarized online public sphere.

Early optimism saw possibilities for social media to renew democratic discourse, marked by hopes for individuals from diverse backgrounds to find opportunities to learn from and interact with others different from themselves. This optimism quickly waned as social media seemed to breed ideological homophily marked by "filter bubbles" or "echo chambers." A typical response to the sense of fragmentation has been to encourage exposure to more cross-partisan sources of information. But do outlets that reach across partisan lines in fact generate more civil discourse? And does the civility of discourse hosted by such outlets vary depending on the political context in which they operate? To answer these questions, we identified bubble reachers, users who distribute content that reaches other users with diverse political opinions in recent presidential elections in Brazil, where populism has deep roots in the political culture, and Canada, where the political culture is comparatively moderate. Given that background, this research studies unexplored properties of content shared by bubble reachers, specifically the quality of conversations and comments it generates. We examine how ideologically neutral bubble reachers differ from ideologically partisan accounts in the level of uncivil discourse they provoke, and explore how this varies in the context of the two countries considered. Our results suggest that while ideologically neutral bubble reachers support less uncivil discourse in Canada, the opposite relationship holds in Brazil. Even non-political content by ideologically neutral bubble reachers elicits a considerable amount of uncivil discourse in Brazil. This indicates that bubble reaching and incivility are moderated by the national political context. Our results complicate the simple hypothesis of a universal impact of neutral bubble reachers across contexts.