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)

A digital study on predictive factors for Instagram users' engagement with amber necklace-related posts.

AIM: This study aimed to assess the engagement of Instagram users with Brazilian Portuguese posts related to amber necklaces for teething symptoms relief, identifying predictive factors that can increase users' engagement with information and misinformation. METHODS: This digital study analysed Brazilian Portuguese amber necklace-related posts on Instagram. The posts were collected using specific search strategies on CrowdTangleTM. Subsequently, two independent investigators were trained and calibrated to categorise the posts concerning the proposed outcomes. The posts were categorised according to their facticity (information or misinformation), type of media (album/photo or video/Instagram TV), sentiment (positive, neutral, or negative), author's occupation (dentist or non-dentist), and type of profile (commercial or personal). Additionally, investigators compiled information about the time of publication (days) and interaction metrics (total interaction and overperforming score). The statistical analysis assessed the inter-examiner reliability, group comparisons, and the factors associated with interaction and misinformation. P values <0.05 were considered significant. CONCLUSION: Videos and personal profiles were predictive factors for higher user engagement with amber necklace posts on teething symptoms relief on Instagram, even with the warnings of health organisations and the lack of scientific evidence to confirm its efficacy.

Investigating Health and Well-Being Challenges Faced by an Aging Workforce in the Construction and Nursing Industries: Computational Linguistic Analysis of Twitter Data.

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.

Social Media Promotion of Health Tests With Potential for Overdiagnosis or Overuse: Protocol for a Content Analysis.

BACKGROUND: In recent years, social media have emerged as important spaces for commercial marketing of health tests, which can be used for the screening and diagnosis of otherwise generally healthy people. However, little is known about how health tests are promoted on social media, whether the information provided is accurate and balanced, and if there is transparency around conflicts of interest. OBJECTIVE: This study aims to understand and quantify how social media is being used to discuss or promote health tests with the potential for overdiagnosis or overuse to generally healthy people. METHODS: Content analysis of social media posts on the anti-Mullerian hormone test, whole-body magnetic resonance imaging scan, multicancer early detection, testosterone test, and gut microbe test from influential international social media accounts on Instagram and TikTok. The 5 tests have been identified as having the following criteria: (1) there are evidence-based concerns about overdiagnosis or overuse, (2) there is evidence or concerns that the results of tests do not lead to improved health outcomes for generally healthy people and may cause harm or waste, and (3) the tests are being promoted on social media to generally healthy people. English language text-only posts, images, infographics, articles, recorded videos including reels, and audio-only posts are included. Posts from accounts with <1000 followers as well as stories, live videos, and non-English posts are excluded. Using keywords related to the test, the top posts were searched and screened until there were 100 eligible posts from each platform for each test (total of 1000 posts). Data from the caption, video, and on-screen text are being summarized and extracted into a Microsoft Excel (Microsoft Corporation) spreadsheet and included in the analysis. The analysis will take a combined inductive approach when generating key themes and a deductive approach using a prespecified framework. Quantitative data will be analyzed in Stata SE (version 18.0; Stata Corp). RESULTS: Data on Instagram and TikTok have been searched and screened. Analysis has now commenced. The findings will be disseminated via publications in peer-reviewed international medical journals and will also be presented at national and international conferences in late 2024 and 2025. CONCLUSIONS: This study will contribute to the limited evidence base on the nature of the relationship between social media and the problems of overdiagnosis and overuse of health care services. This understanding is essential to develop strategies to mitigate potential harm and plan solutions, with the aim of helping to protect members of the public from being marketed low-value tests, becoming patients unnecessarily, and taking resources away from genuine needs within the health system. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/56899.

Use of multimedia devices in pediatric age: risks or advantages? A survey in an Italian center.

BACKGROUND: Nowadays children live in a digital world, exposed to relevant risks for their health and safety. The aim of this study is to investigate the use of multimedia devices in a sample of children and adolescents. METHODS: The study was performed between November 2018 and June 2019 in a third-level University Hospital, recruiting children and adolescents during general or specialistic follow-up visits. Anonymous, age-specific, questionnaires were distributed to 500 children and adolescents and 370 parents. RESULTS: Among children, 25 (17.1%) had their own mobile device, of which 84% Italian. The 54.1% of them uses multimedia devices half an hour/an hour per day and many of them (37.5% of Italian and 40% of foreign) use it without their parents' control. Most of adolescents had a mobile phone since the age of 10-12 years old. WhatsApp (Meta Inc., Cambridge, MA, USA) is the most used social network, followed by Instagram and Facebook. The use of multimedia devices was widespread between teenagers during classroom hours, meals and before sleeping and they are an important mean for cyberbullying. In addition, in the 29.9% of cases there is no correspondence between information given by parents and respective sons/daughters. CONCLUSIONS: This study shows more risks than advantages derived from the use of multimedia devices in children and adolescents. Therefore, it is essential to educate them about their correct and responsible use.

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.

News Coverage of the COVID-19 Pandemic on Social Media and the Public's Negative Emotions: Computational Study.

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.

Long-term impact of digital media on brain development in children.

Digital media (DM) takes an increasingly large part of children's time, yet the long-term effect on brain development remains unclear. We investigated how individual effects of DM use (i.e., using social media, playing video games, or watching television/videos) on the development of the cortex (i.e., global cortical surface area), striatum, and cerebellum in children over 4 years, accounting for both socioeconomic status and genetic predisposition. We used a prospective, multicentre, longitudinal cohort of children from the Adolescent Brain and Cognitive Development Study, aged 9.9 years when entering the study, and who were followed for 4 years. Annually, children reported their DM usage through the Youth Screen Time Survey and underwent brain magnetic resonance imaging scans every 2 years. Quadratic-mixed effect modelling was used to investigate the relationship between individual DM usage and brain development. We found that individual DM usage did not alter the development of cortex or striatum volumes. However, high social media usage was associated with a statistically significant change in the developmental trajectory of cerebellum volumes, and the accumulated effect of high-vs-low social media users on cerebellum volumes over 4 years was only ß = - 0.03, which was considered insignificant. Nevertheless, the developmental trend for heavy social media users was accelerated at later time points. This calls for further studies and longer follow-ups on the impact of social media on brain development.

Facebook addiction and its impact on depression: a cross sectional study.

AIM: Facebook has become a part of daily life for its users and therefore become a very significant factor of mental health. As the number of Facebook users increases exponentially, the problems related to immense use have become more evident and more frequent. Therefore, the study aimed to explore the impact of Facebook addiction on depression among its users. METHODS: An online-based questionnaire was used to collect data from 269 Facebook users of Bangladesh using convenient sampling technique. Bergen Facebook Addiction Scale (BFAS) and Patient Health Questionnaire (PHQ-9) scale was used to assess Facebook addiction and its impact on depression.Ordinal logistic was used to extract the significant variables associated with Facebook addiction and depression. RESULTS: The result categorized the Facebook users into three categories as : normal (17%), problematic user (52%) and addicted (30.5%). Facebook users were suffering from mild (13.4%), minimal (15.6%), moderate (59.5%), and severe (11.5%) level of depression. Both Facebook addiction and depression were moderately correlated (0.701). Ordinal regression showed, gender [Formula: see text] (95% CI) = 0.859 (0.223,1.495)), age (ß (95% CI) = -2.051(-3.789, -0.313)), residential area (ß (95% CI) = -0.858(-1.626, -0.09)), occupation ([Formula: see text]), time length of Facebook use ([Formula: see text]are the significant predictors of Facebook addiction. Wheras, relationship types and occupation are also responsible for depression. CONCLUSION: The study showed large portion of facebook users of Bangladesh are suffering from depression. Authors suggest to arrange mental health campaign to promote bounded and legitimate use of facebook and therefore will accelerate the attaining rate of sustainable development goal related to the Bangladesh's health status.

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.

Examining the Effectiveness of Social Media for the Dissemination of Research Evidence for Health and Social Care Practitioners: Systematic Review and Meta-Analysis.

BACKGROUND: Social media use has potential to facilitate the rapid dissemination of research evidence to busy health and social care practitioners. OBJECTIVE: This study aims to quantitatively synthesize evidence of the between- and within-group effectiveness of social media for dissemination of research evidence to health and social care practitioners. It also compared effectiveness between different social media platforms, formats, and strategies. METHODS: We searched electronic databases for articles in English that were published between January 1, 2010, and January 10, 2023, and that evaluated social media interventions for disseminating research evidence to qualified, postregistration health and social care practitioners in measures of reach, engagement, direct dissemination, or impact. Screening, data extraction, and risk of bias assessments were carried out by at least 2 independent reviewers. Meta-analyses of standardized pooled effects were carried out for between- and within-group effectiveness of social media and comparisons between platforms, formats, and strategies. Certainty of evidence for outcomes was assessed using the GRADE (Grading of Recommendations, Assessment, Development, and Evaluations) framework. RESULTS: In total, 50 mixed-quality articles that were heterogeneous in design and outcome were included (n=9, 18% were randomized controlled trials [RCTs]). Reach (measured in number of practitioners, impressions, or post views) was reported in 26 studies. Engagement (measured in likes or post interactions) was evaluated in 21 studies. Direct dissemination (measured in link clicks, article views, downloads, or altmetric attention score) was analyzed in 23 studies (8 RCTs). Impact (measured in citations or measures of thinking and practice) was reported in 13 studies. Included studies almost universally indicated effects in favor of social media interventions, although effect sizes varied. Cumulative evidence indicated moderate certainty of large and moderate between-group effects of social media interventions on direct dissemination (standardized mean difference [SMD] 0.88; P=.02) and impact (SMD 0.76; P<.001). After social media interventions, cumulative evidence showed moderate certainty of large within-group effects on reach (SMD 1.99; P<.001), engagement (SMD 3.74; P<.001), and direct dissemination (SMD 0.82; P=.004) and low certainty of a small within-group effect on impacting thinking or practice (SMD 0.45; P=.02). There was also evidence for the effectiveness of using multiple social media platforms (including Twitter, subsequently rebranded X; and Facebook), images (particularly infographics), and intensive social media strategies with frequent, daily posts and involving influential others. No included studies tested the dissemination of research evidence to social care practitioners. CONCLUSIONS: Social media was effective for disseminating research evidence to health care practitioners. More intense social media campaigns using specific platforms, formats, and strategies may be more effective than less intense interventions. Implications include recommendations for effective dissemination of research evidence to health care practitioners and further RCTs in this field, particularly investigating the dissemination of social care research. TRIAL REGISTRATION: PROSPERO International Prospective Register of Systematic Reviews CRD42022378793; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=378793. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/45684.

Misunderstanding the harms of online misinformation.

The controversy over online misinformation and social media has opened a gap between public discourse and scientific research. Public intellectuals and journalists frequently make sweeping claims about the effects of exposure to false content online that are inconsistent with much of the current empirical evidence. Here we identify three common misperceptions: that average exposure to problematic content is high, that algorithms are largely responsible for this exposure and that social media is a primary cause of broader social problems such as polarization. In our review of behavioural science research on online misinformation, we document a pattern of low exposure to false and inflammatory content that is concentrated among a narrow fringe with strong motivations to seek out such information. In response, we recommend holding platforms accountable for facilitating exposure to false and extreme content in the tails of the distribution, where consumption is highest and the risk of real-world harm is greatest. We also call for increased platform transparency, including collaborations with outside researchers, to better evaluate the effects of online misinformation and the most effective responses to it. Taking these steps is especially important outside the USA and Western Europe, where research and data are scant and harms may be more severe.

Post-January 6th deplatforming reduced the reach of misinformation on Twitter.

The social media platforms of the twenty-first century have an enormous role in regulating speech in the USA and worldwide1. However, there has been little research on platform-wide interventions on speech2,3. Here we evaluate the effect of the decision by Twitter to suddenly deplatform 70,000 misinformation traffickers in response to the violence at the US Capitol on 6 January 2021 (a series of events commonly known as and referred to here as 'January 6th'). Using a panel of more than 500,000 active Twitter users4,5 and natural experimental designs6,7, we evaluate the effects of this intervention on the circulation of misinformation on Twitter. We show that the intervention reduced circulation of misinformation by the deplatformed users as well as by those who followed the deplatformed users, though we cannot identify the magnitude of the causal estimates owing to the co-occurrence of the deplatforming intervention with the events surrounding January 6th. We also find that many of the misinformation traffickers who were not deplatformed left Twitter following the intervention. The results inform the historical record surrounding the insurrection, a momentous event in US history, and indicate the capacity of social media platforms to control the circulation of misinformation, and more generally to regulate public discourse.

Integrating the ESM usage and work engagement for employee agility performance: based on regulatory focus theory.

This present research aims to clarify the intricate conjunction of enterprise social media (ESM) utilization and employee agility with a main focus on uncovering the underlying mechanisms that work through the mediating influence of work engagement and the moderating influence of regulatory focus. Drawing upon regularity focus theory, 353 Chinese samples of ESM users in organizational contexts are analyzed using SPSS 23.0. The empirical findings substantiate a robust and significant positive linkage between ESM usage and worker agility. Further reinforcing the model, the mediating role of work engagement is established as it channels the impact of ESM usage on worker agility. Turning to the moderating effects, the study unveils the differential impact of prevention focus and promotion focus, wherein individuals with a lower prevention focus exhibit a more pronounced positive linkage between ESM usage and worker agility. Similarly, individuals with a higher promotion focus demonstrate a heightened positive association between ESM usage and worker agility. By comprehensively inspecting the intricate dynamics of ESM usage, work engagement, and regulatory focus, this study enhances our theoretical understanding of how these factors synergistically shape employee agility, ultimately furnishing organizations with invaluable insights to foster and cultivate an agile workforce.

Assessment of patterns and related factors in using social media platforms to access health and oral health information among Sri Lankan adults, with special emphasis on promoting oral health awareness.

BACKGROUND: Social media has evolved beyond its conventional purpose of communication and information sharing to become a potent tool for disseminating health and oral health awareness. This study seeks to assess the patterns and related factors of using social media platforms to access health and oral health information among Sri Lankan adults, with special emphasis to promotion of oral health awareness. METHODS: In March 2023, individuals aged ≥ 18 years residing in Sri Lanka, who are users of social media participated in this electronic questionnaire-based survey. Statistical analyses of the collected data were done using the SPSS version 21 software, with a p-value of < 0.05 set to determine the level of statistical significance. RESULTS: A total of 421 persons participated in this survey. Majority (68.4%) belonged to the age category of 18 to 30 years, and 55.5% were females. WhatsApp (96.8%) was the most frequently used social media platform across all age groups and both genders. Statistically significant differences were identified between genders in the usage of Telegram, Twitter, and Viber within the 18-30 years age category, with a higher percentage of males using these platforms (p ≤ 0.05). Similar significant differences were observed in the 31-40 years age group for WhatsApp and Telegram (p ≤ 0.05). Among 95.4% of online health information seekers, YouTube (74.9%) was the most popular platform. One-quarter of the respondents preferred social media platforms, and 22.3% preferred websites for obtaining oral health information. Furthermore, 74.9% had positive opinions on obtaining oral health information via social media, while only 17% reported pleasant experiences with social media platforms for oral health promotion. In assessing the reliability of oral health information on social media, 48% relied on the quality of the information. The most preferred source of oral health information was short videos from professionals (43.1%). Additionally, 69.5% reported changes in their oral health behaviours after accessing information through social media. CONCLUSION: Social media is a viable platform for promoting public oral health awareness in Sri Lankan; hence, workable strategies need to be employed, to further ensure its effective and wider use in a culturally and socioeconomically diverse country like Sri Lanka.

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.