ABSTRACT
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)
Subject(s)
Humans , Male , Female , Adolescent , Online Social Networking , Social Media , Adolescent Health , Psychology, Adolescent , MotivationABSTRACT
Introducción. La pandemia por COVID-19 ha tenido un impacto profundo en la salud de la población joven de todo el mundo y especialmente en personas con trastornos de la conducta alimentaria (TCA) por situaciones de estrés, ansiedad y cambios en el acceso a la atención médica. Objetivo. Explorar las percepciones de adolescentes sobre los cambios en sus vínculos sociales y modalidades de atención en pacientes con TCA. Población y métodos. Se realizó un estudio cualitativo a través de entrevistas en profundidad a adolescentes con TCA en un hospital universitario durante la pandemia por COVID-19. Resultados. Se entrevistó a 15 adolescentes; el 93 % fueron mujeres y la mediana de edad fue 18 años. El 86,6 % tuvo anorexia nerviosa. Los aspectos negativos percibidos más importantes fueron los malestares en la convivencia familiar (80 %) y la disconformidad con los contenidos de las redes sociales sobre la imagen corporal y dietas (73 %). Los aspectos percibidos positivos fueron la ayuda de los pares (66 %) y mejoras en relación con la alimentación (66 %). El principal cambio identificado en comparación con el tratamiento recibido previo a la pandemia por COVID-19 fue el seguimiento virtual por salud mental (73 %). Conclusión. La población adolescente con TCA durante el ASPO manifestó malestar en la convivencia familiar y disconformidad en los contenidos en redes sociales sobre imagen corporal y dietas. Aunque resaltaron como aspectos positivos la ayuda de los pares y mejoras en su alimentación
Introduction. The COVID-19 pandemic has had a profound impact on the health of young people worldwide, especially on people with eating disorders (EDs) due to the stress, anxiety, and changes experienced in access to health care. Objective. To explore adolescents' perceptions on changes in their social ties and the modalities of health care for patients with EDs. Population and methods. Qualitative study using in-depth interviews with adolescents with EDs seen at a teaching hospital during the COVID-19 pandemic. Results. Fifteen adolescents were interviewed; their mean age was 18 years; 93% were girls. Anorexia nervosa was observed in 86.6%. The most relevant negative aspects perceived were discomfort with family life (80%) and dissatisfaction with social media content regarding body image and dieting (73%). The aspects perceived as positive were peer support (66%) and improvements in eating habits (66%). The main change identified regarding the management before the COVID-19 pandemic was online followup by the mental healthcare team (73%). Conclusion. The adolescent population with EDs during the mandatory social isolation period reported discomfort with family life and dissatisfaction with social media content regarding body image and dieting. Notwithstanding this, adolescents highlighted peer support and improvements in their eating habits as positive aspects.
Subject(s)
Humans , Female , Adolescent , Feeding and Eating Disorders/psychology , Feeding and Eating Disorders/therapy , Feeding and Eating Disorders/epidemiology , COVID-19/psychology , COVID-19/epidemiology , Social Isolation/psychology , Social Support , Body Image/psychology , Qualitative Research , Pandemics , Social MediaABSTRACT
Background Prevalence-based, non-comparative studies have been done to assess psychological and physical consequences of social media and gaming addiction. However, similar studies are lacking for binge-watching, especially in India. We compared the physical and psychological health impact between screen addicted and healthy screen users, by minimizing bias due to confounding factors. Methods We did this cross-sectional comparative study among 120 participants (60 cases and 60 matched controls) consisting of gamers, social media users and binge-watchers, who were recruited from schools and colleges of Mumbai based on their scores on the Digital Addiction Scale (DAS). Levels of depression, anxiety and stress; sleep quality; and dry eye disease were assessed using pre-validated scales such as DASS-21, Pittsburgh Sleep Quality Index (PSQI), and Ocular Surface Disease Index (OSDI), respectively, while the other variables were assessed using a self-designed questionnaire with a content validity ratio (CVR) >0.65. Results The mean (SD) age of the participants was 19.3 (3.2) years, one-third were women; 68% were from medical colleges and 16% each from engineering colleges and high schools. The prevalence and scores of depression, anxiety and stress; poor sleep quality; and dry eye disease; and prevalence of loneliness, aggression and musculoskeletal pain in the wrist, thumb, neck and back were significantly higher in the screen addicted group (p<0.05). Conclusions There was a significant difference in the prevalence and levels of physical and psychological health impact between screen addicted and healthy screen users.
Subject(s)
Depression , Humans , Cross-Sectional Studies , Female , Male , India/epidemiology , Young Adult , Adolescent , Depression/epidemiology , Depression/diagnosis , Prevalence , Dry Eye Syndromes/epidemiology , Dry Eye Syndromes/psychology , Dry Eye Syndromes/diagnosis , Dry Eye Syndromes/etiology , Adult , Anxiety/epidemiology , Anxiety/diagnosis , Video Games/statistics & numerical data , Video Games/adverse effects , Video Games/psychology , Surveys and Questionnaires , Sleep Quality , Internet Addiction Disorder/epidemiology , Internet Addiction Disorder/psychology , Stress, Psychological/epidemiology , Social Media/statistics & numerical data , Behavior, Addictive/epidemiology , Behavior, Addictive/psychologyABSTRACT
From 2020 until 2023, the process of vaccination and progressive control of the SARS-CoV-2 or "Covid-19" virus has allowed for monitored movement to come back. Within this short window of historical reflexion, this chapter aims to bring light to the current context of social media uses and abuses through the lens of the notion of desire for omnipresence. For that, this study articulates this goal through three different layers of analysis: first, by investigating the emergence, management and incitement of what can be described as structurally addictive platforms of online interaction and how they entail a biopolitics of social media dependency; second, by providing in the notion of desire for omnipresence, a framework to understand the driving force for our current wish to subjectively deterritorialize ourselves toward the limitlessness through a zoopolitics where the virtual profile becomes a mode and a model of existence; finally, by pointing out ways "forward" that disrupt the ordinary understanding of linearity and progress to promote modes of un-marketization of life and human affections with the aim of transforming of our current desire for omnipresence into a genuine desire for presence.
Subject(s)
COVID-19 , SARS-CoV-2 , Social Media , Humans , COVID-19/psychology , COVID-19/epidemiology , COVID-19/prevention & control , Behavior, Addictive/psychologyABSTRACT
This study was conducted to evaluate whether smart cell phones detach people from social life, make them lonely, cause depressive symptoms and whether there is a relationship between them. This is a cross-sectional study using face-to-face survey method. The sample was determined as 376 participants, with 95% confidence interval, 50% probability depending on the probability of having a smartphone or not. Participants in the sample were determined by systematic random sampling from adults aged 20 and over in Çiftlik district of Nigde province. The NMP-Q, DASS-42 and UCLA-LS were used. The median age of the 376 participants (192 male, 184 female) was 30 and the mean age was 32.0 (±10.94) years. Participants that had social media accounts were 68.9% of the population. Over 70% of the participants had mild, moderate or severe nomophobia. Nomophobia status of the participants was affected by the mean duration of the first-time smartphone use (Pâ =â .017), the mean daily smartphone usage time of the participants (Pâ <â .001), the mean number of smartphone users in the participants' families (Pâ =â .003), the mean depression and stress scores of the participants (Pâ <â .001), having social media account (Pâ =â .001), and declaration of smart phone dependency (Pâ =â .005). Nomophobia status was not affected by participants' gender, mean age, educational level, employment status, economic status and marital status (Pâ >â .05). The duration of daily smartphone use, the duration of first-time smartphone use, and having multiple smartphone users in family increased nomophobia. Also, having active social media accounts and self-reported smartphone addiction found correlated to nomophobia. Smartphone addiction increases depression, anxiety, and stress scores of the participants.
Subject(s)
Depression , Loneliness , Smartphone , Humans , Male , Female , Adult , Cross-Sectional Studies , Depression/epidemiology , Depression/psychology , Loneliness/psychology , Smartphone/statistics & numerical data , Middle Aged , Young Adult , Social Media/statistics & numerical data , Surveys and QuestionnairesABSTRACT
In response to the data revolution, academic research and media attention have increasingly focused on the technological adaptation and innovation displayed by the far right. The greatest attention is paid to social media and how groups and organizations are utilizing technological advancement and growth in virtual networks to increase recruitment and advance radicalization on a global scale. As with most social and political endeavors, certain technologies are in vogue and thus draw the attention of users and regulators and service providers. This creates a technological blind spot within which extremist groups frequently operate older and less well regarded technologies without the oversight that one might expect. This article examines the less well-studied traditional and official websites of the Ku Klux Klan, the most established and iconic of American far-right organizations. By incorporating non-participant observation of online spaces and thematic analysis, this research analyzes the evolution of 26 websites, from their emergence in the early 1990s to the present day. We examine the ways in which traditional printed communications and other ephemera have progressed with advances in technology, focusing on the following central elements of Klan political activism and community formation: Klan identity, organizational history, aims and objectives; technology and outreach, including online merchandise and event organization; and the constructions of whiteness and racism. The results add value and insight to comparable work by offering a unique historical insight into the ways in which the Klan have developed and made use of Web 1.0, Web 2.0, and Web3 technologies.
Subject(s)
Internet , Humans , Social Media , Political Activism , United States , History, 20th CenturyABSTRACT
Background: As alternative replacement products for tobacco-derived nicotine, synthetic nicotine products have recently emerged and gained increasing popularity. This study analyzes public perception and discussion of synthetic nicotine products on Twitter (now "X"). Methods: Through Twitter streaming API (Application Programming Interface), we have collected 2,764 Twitter posts related to synthetic nicotine from December 12, 2021, to October 17, 2022, using keywords related to synthetic nicotine. By applying an inductive approach, two research assistants manually determined the relevance of tweets to synthetic nicotine products and assessed the attitude of tweets as positive, negative, and neutral of tweets toward synthetic nicotine, and the main topics. Results: Among 1,007 tweets related to synthetic nicotine products, the proportion of negative tweets (383/1007, 38.03%) toward synthetic nicotine products was significantly higher than that of positive tweets (218/1007, 21.65%) with a p-value <0.05. Among negative tweets, major topics include the concern about addiction and health risks of synthetic nicotine products (44.91%) and synthetic nicotine as a policy loophole (31.85%). Among positive tweets, top topics include alternative replacement for nicotine (39.91%) and reduced health risks (31.19%). Conclusion: There are mixed attitudes toward synthetic nicotine products on Twitter, resulting from different perspectives. Future research could incorporate demographic information to understand the attitudes of various population groups.
Subject(s)
Nicotine , Social Media , Humans , Public OpinionABSTRACT
Background: Identifying hate speech (HS) is a central concern within online contexts. Current methods are insufficient for efficient preemptive HS identification. In this study, we present the results of an analysis of automatic HS identification applied to popular alt-right YouTube videos. Methods: This essay describes methodological challenges of automatic HS detection. The case study concerns data on a formative segment of contemporary radical right discourse. Our purpose is twofold. (1) To outline an interdisciplinary mixed-methods approach for using automated identification of HS. This bridges the gap between technical research on the one hand (such as machine learning, deep learning, and natural language processing, NLP) and traditional empirical research on the other. Regarding alt-right discourse and HS, we ask: (2) What are the challenges in identifying HS in popular alt-right YouTube videos? Results: The results indicate that effective and consistent identification of HS communication necessitates qualitative interventions to avoid arbitrary or misleading applications. Binary approaches of hate/non-hate speech tend to force the rationale for designating content as HS. A context-sensitive qualitative approach can remedy this by bringing into focus the indirect character of these communications. The results should interest researchers within social sciences and the humanities adopting automatic sentiment analysis and for those analysing HS and radical right discourse. Conclusions: Automatic identification or moderation of HS cannot account for an evolving context of indirect signification. This study exemplifies a process whereby automatic hate speech identification could be utilised effectively. Several methodological steps are needed for a useful outcome, with both technical quantitative processing and qualitative analysis being vital to achieve meaningful results. With regard to the alt-right YouTube material, the main challenge is indirect framing. Identification demands orientation in the broader discursive context and the adaptation towards indirect expressions renders moderation and suppression ethically and legally precarious.
Subject(s)
Social Media , Video Recording , Humans , Speech , Hate , Natural Language ProcessingABSTRACT
The social and behavioral sciences have been increasingly using automated text analysis to measure psychological constructs in text. We explore whether GPT, the large-language model (LLM) underlying the AI chatbot ChatGPT, can be used as a tool for automated psychological text analysis in several languages. Across 15 datasets (n = 47,925 manually annotated tweets and news headlines), we tested whether different versions of GPT (3.5 Turbo, 4, and 4 Turbo) can accurately detect psychological constructs (sentiment, discrete emotions, offensiveness, and moral foundations) across 12 languages. We found that GPT (r = 0.59 to 0.77) performed much better than English-language dictionary analysis (r = 0.20 to 0.30) at detecting psychological constructs as judged by manual annotators. GPT performed nearly as well as, and sometimes better than, several top-performing fine-tuned machine learning models. Moreover, GPT's performance improved across successive versions of the model, particularly for lesser-spoken languages, and became less expensive. Overall, GPT may be superior to many existing methods of automated text analysis, since it achieves relatively high accuracy across many languages, requires no training data, and is easy to use with simple prompts (e.g., "is this text negative?") and little coding experience. We provide sample code and a video tutorial for analyzing text with the GPT application programming interface. We argue that GPT and other LLMs help democratize automated text analysis by making advanced natural language processing capabilities more accessible, and may help facilitate more cross-linguistic research with understudied languages.
Subject(s)
Multilingualism , Humans , Language , Machine Learning , Natural Language Processing , Emotions , Social MediaABSTRACT
OBJECTIVES: The COVID-19 pandemic has had devastating worldwide impact but most prominent was its effect on marginalised, underserved and equity-deserving populations. Social media arose as an important platform from which health organisations could rapidly disseminate information to equity-deserving populations about COVID-19 risks and events, provide instructions on how to mitigate those risks, motivate compliance with health directives, address false information, provide the opportunity for engagement and immediate feedback. The objective of this scoping review was to synthesise the academic and grey literature on equity-informed social media risk communication strategies developed during the pandemic. DESIGN: The review followed the Arksey and O'Malley framework and focused on the research question: What are the promising principles, processes, and practices for producing equity-informed social media risk communications? DATA SOURCES: CINAHL Complete, MEDLINE (OVID), Business Source Complete, EMBASE database OVID, Scopus and PubMed's curated COVID-19 literature hub: LitCovid, PsycINFO OVID were searched using terms related to access to health services, social media, risk communication, misinformation, community engagement, infectious disease, pandemics and marginalisation, supplemented by grey literature from relevant health organisations. ELIGIBILITY CRITERIA FOR SELECTING STUDIES: Studies were eligible if the population of interest was an equity-deserving population, the concept discussed was COVID-19 risk communication and the article was published in English between January 2019 and December 2022. DATA EXTRACTION AND SYNTHESIS: COVIDENCE facilitated screening and extraction. Charted data were thematically analysed following Braun and Clarke's phased process. Preliminary findings were collaboratively discussed with representatives from health agencies and community organisations focused on serving equity-deserving groups. RESULTS: 12 studies were included. In terms of principles and process, studies emphasised the need to collaboratively create plans for message construction and targeted dissemination using a risk communication framework, capitalise on access to community resources and pre-established communication mediums and be considerate of population-specific needs and concerns. Practice entails careful consideration of communication mediums, language usage, communication frequency and evaluation. CONCLUSION: This scoping review provides valuable insights for health agencies and community organisations in developing principles, processes and practices to equitably communicate risk information through social media. Engagement with stakeholders further refined and confirmed the findings, offering insights for future crisis communication strategies.
Subject(s)
COVID-19 , Communication , SARS-CoV-2 , Social Media , Humans , COVID-19/epidemiology , COVID-19/prevention & control , Pandemics , Health Equity , Information Dissemination/methodsABSTRACT
BACKGROUND: The effectiveness of public health measures (PHMs) depends on population adherence. Social media were suggested as a tool to assess adherence, but representativeness and accuracy issues have been raised. OBJECTIVE: The objectives of this repeated cross-sectional study were to compare self-reported PHM adherence and sociodemographic characteristics between people who used Twitter (subsequently rebranded X) and people who did not use Twitter. METHODS: Repeated Canada-wide web-based surveys were conducted every 14 days from September 2020 to March 2022. Weighted proportions were calculated for descriptive variables. Using Bayesian logistic regression models, we investigated associations between Twitter use, as well as opinions in tweets, and self-reported adherence with mask wearing and vaccination. RESULTS: Data from 40,230 respondents were analyzed. As self-reported, Twitter was used by 20.6% (95% CI 20.1%-21.2%) of Canadians, of whom 29.9% (95% CI 28.6%-31.3%) tweeted about COVID-19. The sociodemographic characteristics differed across categories of Twitter use and opinions. Overall, 11% (95% CI 10.6%-11.3%) of Canadians reported poor adherence to mask-wearing, and 10.8% (95% CI 10.4%-11.2%) to vaccination. Twitter users who tweeted about COVID-19 reported poorer adherence to mask wearing than nonusers, which was modified by the age of the respondents and their geographical region (odds ratio [OR] 0.79, 95% Bayesian credibility interval [BCI] 0.18-1.69 to OR 4.83, 95% BCI 3.13-6.86). The odds of poor adherence to vaccination of Twitter users who tweeted about COVID-19 were greater than those of nonusers (OR 1.76, 95% BCI 1.48-2.07). English- and French-speaking Twitter users who tweeted critically of PHMs were more likely (OR 4.07, 95% BCI 3.38-4.80 and OR 7.31, 95% BCI 4.26-11.03, respectively) to report poor adherence to mask wearing than non-Twitter users, and those who tweeted in support were less likely (OR 0.47, 95% BCI 0.31-0.64 and OR 0.96, 95% BCI 0.18-2.33, respectively) to report poor adherence to mask wearing than non-Twitter users. The OR of poor adherence to vaccination for those tweeting critically about PHMs and for those tweeting in support of PHMs were 4.10 (95% BCI 3.40-4.85) and 0.20 (95% BCI 0.10-0.32), respectively, compared to non-Twitter users. CONCLUSIONS: Opinions shared on Twitter can be useful to public health authorities, as they are associated with adherence to PHMs. However, the sociodemographics of social media users do not represent the general population, calling for caution when using tweets to assess general population-level behaviors.
Subject(s)
COVID-19 , Public Health , Social Media , Humans , COVID-19/prevention & control , Cross-Sectional Studies , Canada , Social Media/statistics & numerical data , Adult , Male , Female , Middle Aged , Bayes Theorem , Young Adult , Masks/statistics & numerical data , Aged , SARS-CoV-2 , Surveys and Questionnaires , Adolescent , Patient Compliance/statistics & numerical data , Self Report , Vaccination/statistics & numerical dataABSTRACT
BACKGROUND: The mpox outbreak resulted in 32,063 cases and 58 deaths in the United States and 95,912 cases worldwide from May 2022 to March 2024 according to the US Centers for Disease Control and Prevention (CDC). Like other disease outbreaks (eg, HIV) with perceived community associations, mpox can create the risk of stigma, exacerbate homophobia, and potentially hinder health care access and social equity. However, the existing literature on mpox has limited representation of the perspective of sexual minority men and gender-diverse (SMMGD) individuals. OBJECTIVE: To fill this gap, this study aimed to synthesize themes of discussions among SMMGD individuals and listen to SMMGD voices for identifying problems in current public health communication surrounding mpox to improve inclusivity, equity, and justice. METHODS: We analyzed mpox-related posts (N=8688) posted between October 2020 and September 2022 by 2326 users who self-identified on Twitter/X as SMMGD and were geolocated in the United States. We applied BERTopic (a topic-modeling technique) on the tweets, validated the machine-generated topics through human labeling and annotations, and conducted content analysis of the tweets in each topic. Geographic analysis was performed on the size of the most prominent topic across US states in relation to the University of California, Los Angeles (UCLA) lesbian, gay, and bisexual (LGB) social climate index. RESULTS: BERTopic identified 11 topics, which annotators labeled as mpox health activism (n=2590, 29.81%), mpox vaccination (n=2242, 25.81%), and adverse events (n=85, 0.98%); sarcasm, jokes, and emotional expressions (n=1220, 14.04%); COVID-19 and mpox (n=636, 7.32%); government or public health response (n=532, 6.12%); mpox symptoms (n=238, 2.74%); case reports (n=192, 2.21%); puns on the naming of the virus (ie, mpox; n=75, 0.86%); media publicity (n=59, 0.68%); and mpox in children (n=58, 0.67%). Spearman rank correlation indicated significant negative correlation (ρ=-0.322, P=.03) between the topic size of health activism and the UCLA LGB social climate index at the US state level. CONCLUSIONS: Discussions among SMMGD individuals on mpox encompass both utilitarian (eg, vaccine access, case reports, and mpox symptoms) and emotionally charged (ie, promoting awareness, advocating against homophobia, misinformation/disinformation, and health stigma) themes. Mpox health activism is more prevalent in US states with lower LGB social acceptance, suggesting a resilient communicative pattern among SMMGD individuals in the face of public health oppression. Our method for social listening could facilitate future public health efforts, providing a cost-effective way to capture the perspective of impacted populations. This study illuminates SMMGD engagement with the mpox discourse, underscoring the need for more inclusive public health programming. Findings also highlight the social impact of mpox: health stigma. Our findings could inform interventions to optimize the delivery of informational and tangible health resources leveraging computational mixed-method analyses (eg, BERTopic) and big data.
Subject(s)
Sexual and Gender Minorities , Social Media , Humans , Male , Sexual and Gender Minorities/psychology , Sexual and Gender Minorities/statistics & numerical data , Social Media/statistics & numerical data , United States/epidemiology , FemaleABSTRACT
Objective: This study aimed to assess the quality of the information in WeChat and TikTok videos related to hypertension and diabetes treatment. Methods: A sample of 120 Chinese videos was collected based on specific inclusion and exclusion criteria. The quality was evaluated using DISCERN, JAMA and the latest edition of Chinese guidelines for hypertension and diabetes prevention and treatment, and two observers independently scored each video using the three assessment tools. Results: Among all 120 videos, only 10 scored above 38 points in DISCERN, with 45 videos rated as "very poor". None of the video met all JAMA criteria simultaneously, and there were gaps in accuracy and completeness compared to the two guidelines. Furthermore, there was no significant correlation between information quality and the number of likes and comments. Conclusion: The current quality of information on the treatment of hypertension and diabetes on WeChat and TikTok was unsatisfactory. Consequently, the government should strengthen oversight of information quality, and social media platforms should actively review health-related content to prevent inaccurate information dissemination. Individuals should enhance their digital and health literacy.
Subject(s)
Diabetes Mellitus , Hypertension , Humans , Hypertension/therapy , Cross-Sectional Studies , Diabetes Mellitus/therapy , Social Media/trends , Social Media/statistics & numerical data , China , Health Literacy/standards , Consumer Health Information/standards , Consumer Health Information/methods , Video RecordingABSTRACT
OBJECTIVES: Older adults are more likely to have poor sleep quality and be socially isolated. The present study examined the potential benefits and disadvantages of social media use (SMU) with respect to sleep quality and perceived social isolation among Iranian late-middle-aged and older adults with focus a on both the mediating and moderating role of psychological distress. METHODS: A population-based cross-sectional study was conducted among 900 older community-dwellers living in Shiraz using a structured questionnaire. Social media use was assessed by estimating the frequency of social networking site visits per week. Data concerning self-rated physical health, chronic medical and mental health conditions, perceived social isolation, sleep quality, and psychological distress were also collected. Multiple linear regression was used to identify independent variables associated with outcomes. Then, mediation and moderation models were used to examine the potential mediating and moderating effects of psychological distress and SMU on their relationships with the study variables. RESULTS: Higher social media use was associated with better sleep quality and less perceived social isolation. Nevertheless, the relationships between SMU and participants' sleep quality and perceived social isolation were largely mediated by their level of psychological distress. Furthermore, SMU had a significant moderating effect in the relationship between the psychological distress and the levels of perceived social isolation, so that participants with higher frequency of SMU per week felt less loneliness. CONCLUSIONS: The study findings suggest that SMU has a positive buffering effect regarding late middle-aged and older adults' mental health mainly through moderation of their perceived social isolation. The mediating role of psychological distress in research examining the relationship between SMU and older adults' mental health outcomes should be considered in future research.
Subject(s)
Psychological Distress , Sleep Quality , Social Isolation , Social Media , Humans , Social Isolation/psychology , Male , Female , Aged , Cross-Sectional Studies , Middle Aged , Surveys and Questionnaires , Iran/epidemiology , Aged, 80 and over , Stress, Psychological/psychology , Stress, Psychological/epidemiologyABSTRACT
Youth screen media activity is a growing concern, though few studies include objective usage data. Through the longitudinal, U.S.-based Adolescent Brain Cognitive Development (ABCD) Study, youth (mage = 14; n = 1415) self-reported their typical smartphone use and passively recorded three weeks of smartphone use via the ABCD-specific Effortless Assessment Research System (EARS) application. Here we describe and validate passively-sensed smartphone keyboard and app use measures, provide code to harmonize measures across operating systems, and describe trends in adolescent smartphone use. Keyboard and app-use measures were reliable and positively correlated with one another (r = 0.33) and with self-reported use (rs = 0.21-0.35). Participants recorded a mean of 5 h of daily smartphone use, which is two more hours than they self-reported. Further, females logged more smartphone use than males. Smartphone use was recorded at all hours, peaking on average from 8 to 10 PM and lowest from 3 to 5 AM. Social media and texting apps comprised nearly half of all use. Data are openly available to approved investigators ( https://nda.nih.gov/abcd/ ). Information herein can inform use of the ABCD dataset to longitudinally study health and neurodevelopmental correlates of adolescent smartphone use.
Subject(s)
Smartphone , Humans , Adolescent , Female , Male , Mobile Applications , Self Report , Adolescent Behavior , Longitudinal Studies , Social Media , Sex FactorsABSTRACT
The COVID-19 pandemic has disrupted people's lives and caused significant economic damage around the world, but its impact on people's mental health has not been paid due attention by the research community. According to anecdotal data, the pandemic has raised serious concerns related to mental health among the masses. However, no systematic investigations have been conducted previously on mental health monitoring and, in particular, detection of post-traumatic stress disorder (PTSD). The goal of this study is to use classical machine learning approaches to classify tweets into COVID-PTSD positive or negative categories. To this end, we employed various Machine Learning (ML) classifiers, to segregate the psychotic difficulties with the user's PTSD in the context of COVID-19, including Random Forest Support Vector Machine, Naïve Bayes, and K-Nearest Neighbor. ML models are trained and tested using various combinations of feature selection strategies to get the best possible combination. Based on our experimentation on real-world dataset, we demonstrate our model's effectiveness to perform classification with an accuracy of 83.29% using Support Vector Machine as classifier and unigram as a feature pattern.
Subject(s)
COVID-19 , Machine Learning , Social Media , Stress Disorders, Post-Traumatic , Support Vector Machine , Survivors , Humans , Stress Disorders, Post-Traumatic/psychology , Stress Disorders, Post-Traumatic/diagnosis , Stress Disorders, Post-Traumatic/epidemiology , COVID-19/psychology , COVID-19/epidemiology , Survivors/psychology , SARS-CoV-2/isolation & purification , Bayes Theorem , Mental HealthABSTRACT
Data annotation in NLP is a costly and time-consuming task, traditionally handled by human experts who require extensive training to enhance the task-related background knowledge. Besides, labeling social media texts is particularly challenging due to their brevity, informality, creativity, and varying human perceptions regarding the sociocultural context of the world. With the emergence of GPT models and their proficiency in various NLP tasks, this study aims to establish a performance baseline for GPT-4 as a social media text annotator. To achieve this, we employ our own dataset of tweets, expertly labeled for stance detection with full inter-rater agreement among three annotators. We experiment with three techniques: Zero-shot, Few-shot, and Zero-shot with Chain-of-Thoughts to create prompts for the labeling task. We utilize four training sets constructed with different label sets, including human labels, to fine-tune transformer-based large language models and various combinations of traditional machine learning models with embeddings for stance classification. Finally, all fine-tuned models undergo evaluation using a common testing set with human-generated labels. We use the results from models trained on human labels as the benchmark to assess GPT-4's potential as an annotator across the three prompting techniques. Based on the experimental findings, GPT-4 achieves comparable results through the Few-shot and Zero-shot Chain-of-Thoughts prompting methods. However, none of these labeling techniques surpass the top three models fine-tuned on human labels. Moreover, we introduce the Zero-shot Chain-of-Thoughts as an effective strategy for aspect-based social media text labeling, which performs better than the standard Zero-shot and yields results similar to the high-performing yet expensive Few-shot approach.
Subject(s)
Social Media , Humans , Natural Language Processing , Machine LearningABSTRACT
Reward-based crowdfunding is a typical two-sided platform (fundraiser side and backer side) with high information asymmetry. While existing research indicates that signals from fundraisers and backers can impact crowdfunding performance, the interplay among these signals warrants further investigation. Drawing on signaling theory, this study adopts a configurational perspective and utilizes the fsQCA method and linear regression to investigate the combined effects of fundraiser engagement (update and fundraiser comment), third-party endorsement (backer comment and Facebook sharing), and project preparedness (video, image, and description) on crowdfunding performance. Drawing data from the reward-based crowdfunding platform Indiegogo, this research pointed out that these signals cannot generate better crowdfunding performance alone and examined substitution and complementary effects among different signals. Based on the linear regression and fsQCA results, configurations that lead to high crowdfunding performance are identified. We found that project preparedness must work with other signals to produce high crowdfunding performance. Besides, we summarized these configurations into two patterns that may lead to high crowdfunding performance: a fundraiser engagement-driven pattern and a third-party endorsement-driven pattern. This study contributes a configurational perspective and valuable insights into how signals can work together to mitigate information asymmetry in crowdfunding.
Subject(s)
Fund Raising , Humans , Crowdsourcing/economics , Linear Models , Reward , Social MediaABSTRACT
BACKGROUND: The proliferation of misinformation on social media is a significant concern due to its frequent occurrence and subsequent adverse social consequences. Effective interventions for and corrections of misinformation have become a focal point of scholarly inquiry. However, exploration of the underlying causes that affect the public acceptance of misinformation correction is still important and not yet sufficient. OBJECTIVE: This study aims to identify the critical attributions that influence public acceptance of misinformation correction by using attribution analysis of aspects of public sentiment, as well as investigate the differences and similarities in public sentiment attributions in different types of misinformation correction. METHODS: A theoretical framework was developed for analysis based on attribution theory, and public sentiment attributions were divided into 6 aspects and 11 dimensions. The correction posts for the 31 screened misinformation events comprised 33,422 Weibo posts, and the corresponding Weibo comments amounted to 370,218. A pretraining model was used to assess public acceptance of misinformation correction from these comments, and the aspect-based sentiment analysis method was used to identify the attributions of public sentiment response. Ultimately, this study revealed the causality between public sentiment attributions and public acceptance of misinformation correction through logistic regression analysis. RESULTS: The findings were as follows: First, public sentiments attributed to external attribution had a greater impact on public acceptance than those attributed to internal attribution. The public associated different aspects with correction depending on the type of misinformation. The accuracy of the correction and the entity responsible for carrying it out had a significant impact on public acceptance of misinformation correction. Second, negative sentiments toward the media significantly increased, and public trust in the media significantly decreased. The collapse of media credibility had a detrimental effect on the actual effectiveness of misinformation correction. Third, there was a significant difference in public attitudes toward the official government and local governments. Public negative sentiments toward local governments were more pronounced. CONCLUSIONS: Our findings imply that public acceptance of misinformation correction requires flexible communication tailored to public sentiment attribution. The media need to rebuild their image and regain public trust. Moreover, the government plays a central role in public acceptance of misinformation correction. Some local governments need to repair trust with the public. Overall, this study offered insights into practical experience and a theoretical foundation for controlling various types of misinformation based on attribution analysis of public sentiment.