Exploring the Reasons for Selfie-Taking and Selfie-Posting on Social Media with Its Effect on Psychological and Social Lives:A Study among Indian Youths

‘Selfie’taking was introduced to the common people by smartphones and has become a common practice across the globe in no time.With technological advancement and the popularity of smartphones,selfie-taking has grown rapidly within a short time.In light of the new trend set by the generation,this study aimed to explore reasons for selfie-taking and selfie-posting on social media and their effects on the social and psychological lives of young adults.A purposive sampling method was adopted to select 20 Indian citizens,between 18 and 24 years.The data were collected through semi-structured interviews and analysed using thematic analysis.Selfie-taking and posting on social media give positive feelings,and it acts as a mood modifier dependent mostly on the favourability and feedback about the post which in turn affects emotions and self-satisfaction.

Impact of Social Media Challenges on Pediatric Single-Use Detergent Sacs and Diphenhydramine Ingestions Reported to United States Poison Control Centers

Background: Social media platforms are popular among children and often feature challenges that become viral. Notably, the Tide Pod® and Benadryl® challenges encouraged viewers to ingest these substances for their visual appeal and hallucinogenic effects, respectively. This study aimed to assess the clinical impact and outcomes of single-use detergent sacs (SUDS) and diphenhydramine challenges on pediatric ingestions reported to United States (U.S.) Poison Control Centers (PCCs). Methods: We conducted a retrospective review of pediatric exposures reported to U.S. PCCs using data from the National Poison Data System (NPDS). The study included intentional single-substance ingestions of both brand-name and generic forms of SUDS and diphenhydramine among children ≤ 19 years. We compared the number of calls, clinical effects, disposition, and management strategies for SUDS (pre: 01/01/17 to 12/31/17 vs. post: 01/01/18 to 12/31/18) and diphenhydramine (pre: 08/01/19 to 07/31/20 vs. post: 08/01/20 to 07/31/21) ingestions 12 months before and after the introduction of the respective social media challenges. Differences in proportions were compared using the Chi-square test. Results: During the study period, 469 ingestions of SUDS and 5,702 ingestions of diphenhydramine were reported. Post-challenge periods saw an increase in both SUDS (pre: 82 vs. post: 387;372% increase) and diphenhydramine ingestions (pre: 2,672 vs. post: 3,030;13% increase). While there were no significant changes in moderate or major clinical outcomes, hospitalizations increased post-challenge for both SUDS [pre: 4 (4.9%) vs. post: 33 (8.5%);p = 0.25] and diphenhydramine [pre: n = 904 (33.8%) vs. post: 1,190 (39.3%);p Conclusion: Pediatric ingestions reported to U.S. PCCs and hospitalizations increased coinciding with the introduction of Tide Pod® and Benadryl® challenges. While causality cannot be definitively established, it is essential for pediatricians and parents to be aware of these challenges and educate vulnerable children about the harmful effects of participation in such challenges.

Integrated ribosome and proteome analyses reveal insights into sevoflurane-induced long-term social behavior and cognitive dysfunctions through ADNP inhibition in neonatal mice

A growing number of studies have demonstrated that repeated exposure to sevoflurane during development results in persistent social abnormalities and cognitive impairment.Davunetide,an active fragment of the activity-dependent neuroprotective protein(ADNP),has been implicated in social and cognitive protection.However,the potential of davunetide to attenuate social deficits following sevoflurane exposure and the underlying developmental mechanisms remain poorly understood.In this study,ribosome and proteome profiles were analyzed to investigate the molecular basis of sevoflurane-induced social deficits in neonatal mice.The neuropathological basis was also explored using Golgi staining,morphological analysis,western blotting,electrophysiological analysis,and behavioral analysis.Results indicated that ADNP was significantly down-regulated following developmental exposure to sevoflurane.In adulthood,anterior cingulate cortex(ACC)neurons exposed to sevoflurane exhibited a decrease in dendrite number,total dendrite length,and spine density.Furthermore,the expression levels of Homer,PSD95,synaptophysin,and vglut2 were significantly reduced in the sevoflurane group.Patch-clamp recordings indicated reductions in both the frequency and amplitude of miniature excitatory postsynaptic currents(mEPSCs).Notably,davunetide significantly ameliorated the synaptic defects,social behavior deficits,and cognitive impairments induced by sevoflurane.Mechanistic analysis revealed that loss of ADNP led to dysregulation of Ca^(2+)activity via the Wnt/β-catenin signaling,resulting in decreased expression of synaptic proteins.Suppression of Wnt signaling was restored in the davunetide-treated group.Thus,ADNP was identified as a promising therapeutic target for the prevention and treatment of neurodevelopmental toxicity caused by general anesthetics.This study provides important insights into the mechanisms underlying social and cognitive disturbances caused by sevoflurane exposure in neonatal mice and elucidates the regulatory pathways involved.

Social Comparison Orientation Associated with Psychological Well Being:The Mediated Role of Self-efficacy

The paper focused on how social comparison orientation people apply influences their psychological well-being and how self-efficacy plays an important role in buffering some negative influence from upward social comparison compared with someone better in one domain.In Festinger’s(1954)social comparison theory,the social comparison orientation instructed how people process the information they compared for,and related emotion was induced differently.In this paper,2,000 college students in Boston were proposed to participate in two experiments that discuss how different social comparison orientations affect their perception of life satisfaction.For the hypothetical result,we proposed that a high level of engagement in social comparison and ability-based social comparison was associated with less life satisfaction than the participants who had a low level of social comparison and opinion-based social comparison.In terms of coping strategy,we assumed that a high level of self-efficacy,which is the belief in capability to achieve a certain goal,will buffer the negative impact from upward comparison and improve the life satisfaction of those participants who like to engage with social comparison and ability-based comparison orientation.

Interpersonal Perception in Virtual Groups: Examining Homophily, Identification and Individual Attraction Using Social Relations Model in Network

With the penetration of the Internet, virtual groups have become more and more popular. The reliability and accuracy of interpersonal perception in the virtual environment is an intriguing issue. Using the Social relations model (SRM) [1], this paper investigates interpersonal perception in virtual groups from a multilevel perspective. In particular, it examines the following three areas: homophily, identification, and individual attraction, and explores how much of these directional and dyadic relational evaluations can be attributed to the effect of the actor, the partner, and the relationship.

Adolescent suicide risk factors and the integration of socialemotional skills in school-based prevention programs

Adolescents are considered one of the most vulnerable groups affected by suicide.Rapid changes in adolescents’physical and mental states,as well as in their lives,significantly and undeniably increase the risk of suicide.Psychological,social,family,individual,and environmental factors are important risk factors for suicidal behavior among teenagers and may contribute to suicide risk through various direct,indirect,or combined pathways.Social-emotional learning is considered a powerful intervention measure for addressing the crisis of adolescent suicide.When deliberately cultivated,fostered,and enhanced,selfawareness,self-management,social awareness,interpersonal skills,and responsible decision-making,as the five core competencies of social-emotional learning,can be used to effectively target various risk factors for adolescent suicide and provide necessary mental and interpersonal support.Among numerous suicide intervention methods,school-based interventions based on social-emotional competence have shown great potential in preventing and addressing suicide risk factors in adolescents.The characteristics of school-based interventions based on social-emotional competence,including their appropriateness,necessity,cost-effectiveness,comprehensiveness,and effectiveness,make these interventions an important means of addressing the crisis of adolescent suicide.To further determine the potential of school-based interventions based on social-emotional competence and better address the issue of adolescent suicide,additional financial support should be provided,the combination of socialemotional learning and other suicide prevention programs within schools should be fully leveraged,and cooperation between schools and families,society,and other environments should be maximized.These efforts should be considered future research directions.

Tik-Tok Usage During Third Wave of COVID-19 and Its Impacts on Personal,Academic,and Social Life of Teenagers and Youngsters in Turkey

Tik-Tok is a famous entertainment and art creation app that is used all around the world,which enables everyone to make short video clip ranging from 30 seconds to 1 minute and which is published and shared with family,friends,and public.This app is downloaded about 1.5 billion times with 800 million users all around the world,Tik-Tok users from China,India,USA,Russia,and Turkey are at the top.This paper explores the usage of Tik-Tok under the pandemic COVID-19 and how does it impact on personal,academic,and social life of youngsters and teenagers in Turkey.We collected primary data by using questionnaires from four big provinces:Istanbul,Ankara,Izmir,and Antalya(mainly top tourist provinces),500 samples were collected by using convenience sampling method,data collected in between 1 April 2021 to 2 May 2021,data analyzed by Multiple ANOVA,three times simple regression was used to explore the impact of Tik-Tok on personal,academic,and social life separately,furthermore correlation test was also applied to show strength among variables.Results indicate statistical significance(p<0.01)which supports the hypotheses.

Spatiotemporal dynamics of the social structure of Indo-Pacific humpback dolphins(Sousa chinensis)in Xiamen waters from 2007 to 2019

As highly social animals,Indo-Pacific humpback dolphins(Sousa chinensis)exhibit community differentiation.Nevertheless,our understanding of the external and internal factors influencing these dynamics,as well as their spatiotemporal variations,is still limited.In the present study,variations in the social structure of an endangered Indo-Pacific humpback dolphin population in Xiamen Bay,China,were monitored over two distinct periods(2007–2010 and 2017–2019)to analyze the effects of habitat utilization and the composition of individuals within the population.In both periods,the population demonstrated a strikingly similar pattern of social differentiation,characterized by the division of individuals into two main clusters and one small cluster.Spatially,the two primary clusters occupied the eastern and western waters,respectively,although the core distribution area of the eastern cluster shifted further eastward between the two periods.Despite this distribution shift,the temporal stability of the social structure and inter-associations within the eastern cluster remained unaffected.A subset of 16individuals observed in both periods,comprising 51.6%and 43.2%of the population in each respective period,emerged as a foundational element of the social structure and may be responsible for sustaining social structure stability,especially during the 2007–2010 period.These observations suggest that the composition of dominant individuals,an internal factor,had a more substantial influence on the formation of the social network than changes in habitat use,an external factor.Consequently,the study proposes distinct conservation measures tailored to each of the two main clusters.

Enhancing Data Forwarding Efficiency in SIoT with Multidimensional Social Relations

Effective data communication is a crucial aspect of the Social Internet of Things(SIoT)and continues to be a significant research focus.This paper proposes a data forwarding algorithm based on Multidimensional Social Relations(MSRR)in SIoT to solve this problem.The proposed algorithm separates message forwarding into intra-and cross-community forwarding by analyzing interest traits and social connections among nodes.Three new metrics are defined:the intensity of node social relationships,node activity,and community connectivity.Within the community,messages are sent by determining which node is most similar to the sender by weighing the strength of social connections and node activity.When a node performs cross-community forwarding,the message is forwarded to the most reasonable relay community by measuring the node activity and the connection between communities.The proposed algorithm was compared to three existing routing algorithms in simulation experiments.Results indicate that the proposed algorithmsubstantially improves message delivery efficiency while lessening network overhead and enhancing connectivity and coordination in the SIoT context.

基于Social Transformer的井下多人轨迹预测方法

目前煤矿井下人员轨迹预测方法中,Transformer与循环神经网络(RNN)、长短期记忆(LSTM)网络相比,在处理数据时不仅计算量小,同时还有效解决了梯度消失导致的长时依赖问题。但当环境中涉及多人同时运动时,Transformer对于场景中所有人员未来轨迹的预测会出现较大偏差。并且目前在井下多人轨迹预测领域尚未出现一种同时采用Transformer并考虑个体之间相互影响的模型。针对上述问题,提出一种基于Social Transformer的井下多人轨迹预测方法。首先对井下每一个人员独立建模,获取人员历史轨迹信息,通过Transformer编码器进行特征提取,接着由全连接层对特征进行表示,然后通过基于图卷积的交互层相互连接,该交互层允许空间上接近的网络彼此共享信息,计算预测对象在受到周围邻居影响时对周围邻居分配的注意力,从而提取其邻居的运动模式,继而更新特征矩阵,最后新的特征矩阵由Transformer解码器进行解码,输出对于未来时刻的人员位置信息预测。实验结果表明,Social Transformer的平均位移误差相较于Transformer降低了45.8%,且与其他主流轨迹预测方法LSTM,S−GAN,Trajectron++和Social−STGCNN相比分别降低了67.1%,35.9%,30.1%和10.9%,有效克服了煤矿井下多人场景中由于人员间互相影响导致预测轨迹失准的问题,提升了预测精度。

The Influence of Watching TV Talent Show on Teenagers Socialization From Marcuse’s Thought of“One Dimensional Person”

Based on Marcuse’s thought of“one-dimensional person”,this paper discusses the influence of TV talent show on teenagers’socialization.By analyzing the characteristics of TV talent shows that emphasize individual competition and success,appearance and image,and instant satisfaction,it is pointed out that these characteristics are easy for teenagers to produce the mentality of pursuing fame and fortune,appearance,and instant satisfaction,ignoring the development of other important values and qualities.Therefore,we need to guide teenagers to maintain a critical attitude toward TV talent shows,and pay attention to cultivating their independent thinking and all-round development.

Establishing the relationship between land use land cover,normalized difference vegetation index and land surface temperature:A case of Lower Son River Basin,India

The study explores the intricate interplay between land use land cover(LULC),normalized difference vegetation index(NDVI),and land surface temperature(LST)within the Lower Son River Basin in India from 1991 to 2020.The region’s ecological balance has been increasingly strained due to rapid urbanization and changing land use patterns.Through a combination of Landsat TM&OLI/TIRS satellite imageries and geospatial analysis techniques,this study unveils the intricate connection between land use and land cover changes,vegetation,and land surface temperature variations.The study area is classified into three altitudinal zones(Zone Ⅰ:39–300 m,Zone Ⅱ:301–600 m and Zone Ⅲ:601–1,247 m)to examine the changes in depth.The area has seen significant changes in LULC,vegetation and LST in all the three altitudinal zones.The findings hold significant implications for sustainable land management and environmental conservation strategies in the Lower Son River Basin.As per the result,103,438 ha of vegetation was converted into agriculture land and 82,572 ha of agricultural land was transformed into settlements from 1991 to 2020.This trend shows human pressure on the land resource in the study area.Minor increase in water body is seen which is attributed to commissioning of Bansagar dam.Zone Ⅰ has seen highest settlement growth while Zone Ⅲ experienced severe deforestation of around 15%.Zone Ⅱ and Ⅲ needs attention for holistic sustenance.Analysis of LST shows that it has increased by 0.82℃ from 1991 to 2020 which is a red flag.The study underscores the critical importance of balanced land use practices to preserve ecological integrity and mitigate the adverse effects of urbanization and climate change.

Exploring Global Demands for Integrating Social Aspects into Community Healthcare: A Literature Review

Aging and crises like pandemics and climate change are global concerns that affect community environments. These social and natural changes influence people’s health worldwide. Aging impacts human health, including physical and mental aspects, and increases the need for care. Recent crises have affected not only the elderly but also younger populations, necessitating further efforts to develop a systematic community strategy. The goal of such a strategy is to maintain or enhance people’s well-being. As we face aging and crises like pandemics and climate change, it becomes essential to consider health holistically and globally, taking into account the community environment and social determinants without boundaries. The present study aimed to explore the necessary aspects of incorporating social determinants into clinical practice, enabling healthcare providers to view health from a holistic and planetary perspective. This approach facilitates the development of integrated community strategies. The study reviewed literature from PubMed, MEDLINE, and CINAHL databases, focusing on medicine, health, and welfare. An electronic search for English-language articles in peer-reviewed journals was conducted up to July 2024, using search terms such as “holistic health,” “planetary health,” and “social determinants.” Eight articles were identified through the search. After excluding three based on their titles, abstracts, and full texts, five articles were selected. The research focused on three areas: perceiving health in ecosystems, considering health-related policy in clinical situations, and addressing health in primary care settings. This study emphasizes the need for further research on innovative, integrated community strategies in the context of a globally aging society, focusing on non-medical aspects like pandemics, climate change, and social determinants to achieve a holistic and planetary understanding of people’s health. It suggests that understanding the social aspects of ecosystems in clinical settings, through interdisciplinary collaboration, is crucial for developing systematic community strategies for people’s well-being life in medical, health, and welfare contexts.

Predicting Users’ Latent Suicidal Risk in Social Media: An Ensemble Model Based on Social Network Relationships

Suicide has become a critical concern,necessitating the development of effective preventative strategies.Social media platforms offer a valuable resource for identifying signs of suicidal ideation.Despite progress in detecting suicidal ideation on social media,accurately identifying individuals who express suicidal thoughts less openly or infrequently poses a significant challenge.To tackle this,we have developed a dataset focused on Chinese suicide narratives from Weibo’s Tree Hole feature and introduced an ensemble model named Text Convolutional Neural Network based on Social Network relationships(TCNN-SN).This model enhances predictive performance by leveraging social network relationship features and applying correction factors within a weighted linear fusion framework.It is specifically designed to identify key individuals who can help uncover hidden suicidal users and clusters.Our model,assessed using the bespoke dataset and benchmarked against alternative classification approaches,demonstrates superior accuracy,F1-score and AUC metrics,achieving 88.57%,88.75%and 94.25%,respectively,outperforming traditional TextCNN models by 12.18%,10.84%and 10.85%.We assert that our methodology offers a significant advancement in the predictive identification of individuals at risk,thereby contributing to the prevention and reduction of suicide incidences.

Social prescribing in the metaverse:a new frontier for primary care practice

The advent of immersive technologies such as the metaverse,extended reality,artificial intelligence,and blockchain offers novel possibilities to transform healthcare services.These innovations coincide with clinicians'aspirations to deliver more comprehensive,patient-centered care tailored to individuals singular needs and preferences.Integration of these emerging tools may confer opportunities for providers to engage patients through new modalities and expand their role.However,responsible implementation necessitates deliberation of ethical implications and steadfast adherence to foundational principles of compassion and interpersonal connection underpinning the profession.While the metaverse introduces new channels for social prescribing,this perspective advocates that its ultimate purpose should be strengthening,not supplanting,human relationships.We propose an ethical framework centered on respect for patients'dignity to guide integration of metaverse platforms into medical practice.This framework serves both to harness their potential benefits and mitigate risks of dehumanization or uncompassionate care.Our analysis maps the developing topology of metaverse-enabled care while upholding moral imperatives for medicine to promote healing relationships and human flourishing.

Social Robot Detection Method with Improved Graph Neural Networks

Social robot accounts controlled by artificial intelligence or humans are active in social networks,bringing negative impacts to network security and social life.Existing social robot detection methods based on graph neural networks suffer from the problem of many social network nodes and complex relationships,which makes it difficult to accurately describe the difference between the topological relations of nodes,resulting in low detection accuracy of social robots.This paper proposes a social robot detection method with the use of an improved neural network.First,social relationship subgraphs are constructed by leveraging the user’s social network to disentangle intricate social relationships effectively.Then,a linear modulated graph attention residual network model is devised to extract the node and network topology features of the social relation subgraph,thereby generating comprehensive social relation subgraph features,and the feature-wise linear modulation module of the model can better learn the differences between the nodes.Next,user text content and behavioral gene sequences are extracted to construct social behavioral features combined with the social relationship subgraph features.Finally,social robots can be more accurately identified by combining user behavioral and relationship features.By carrying out experimental studies based on the publicly available datasets TwiBot-20 and Cresci-15,the suggested method’s detection accuracies can achieve 86.73%and 97.86%,respectively.Compared with the existing mainstream approaches,the accuracy of the proposed method is 2.2%and 1.35%higher on the two datasets.The results show that the method proposed in this paper can effectively detect social robots and maintain a healthy ecological environment of social networks.

Brain region-specific roles of brain-derived neurotrophic factor in social stress-induced depressive-like behavior

Brain-derived neurotrophic factor is a key factor in stress adaptation and avoidance of a social stress behavioral response.Recent studies have shown that brain-derived neurotrophic factor expression in stressed mice is brain region–specific,particularly involving the corticolimbic system,including the ventral tegmental area,nucleus accumbens,prefrontal cortex,amygdala,and hippocampus.Determining how brain-derived neurotrophic factor participates in stress processing in different brain regions will deepen our understanding of social stress psychopathology.In this review,we discuss the expression and regulation of brain-derived neurotrophic factor in stress-sensitive brain regions closely related to the pathophysiology of depression.We focused on associated molecular pathways and neural circuits,with special attention to the brain-derived neurotrophic factor–tropomyosin receptor kinase B signaling pathway and the ventral tegmental area–nucleus accumbens dopamine circuit.We determined that stress-induced alterations in brain-derived neurotrophic factor levels are likely related to the nature,severity,and duration of stress,especially in the above-mentioned brain regions of the corticolimbic system.Therefore,BDNF might be a biological indicator regulating stress-related processes in various brain regions.

Effects of individual heterogeneity on social contagions

Despite having significant effects on social contagions,individual heterogeneity has frequently been overlooked in earlier studies.To better understand the complexity of social contagions,a non-Markovian model incorporating heterogeneous social influence and adoption thresholds is introduced.For theoretical analysis,a generalized edge-based compartmental theory which considers the heterogeneities of social influence and adoption thresholds is developed.Focusing on the final adoption size,the critical propagation probability,and the phase transition type,social contagions for adoption thresholds that follow normal distributions with various standard deviations,follow various distributions,and correlate with degrees are investigated.When thresholds follow normal distributions,a larger standard deviation results in a larger final adoption size when the information propagation probability is relatively low.However,when the information propagation probability is relatively high,a larger standard deviation results in a smaller final adoption size.When thresholds follow various distributions,crossover phenomena in phase transition are observed when investigating the relationship of the final adoption size versus the average adoption threshold for some threshold distributions.When thresholds are correlated with degrees,similar crossover phenomena occur when investigating the relationship of the final adoption size versus the degree correlation index.Additionally,we find that increasing the heterogeneity of social influence suppresses the effects of adoption threshold heterogeneity on social contagions in three cases.Our theory predictions agree well with the simulation results.

Potential use of large language models for mitigating students’problematic social media use:ChatGPT as an example

The problematic use of social media has numerous negative impacts on individuals'daily lives,interpersonal relationships,physical and mental health,and more.Currently,there are few methods and tools to alleviate problematic social media,and their potential is yet to be fully realized.Emerging large language models(LLMs)are becoming increasingly popular for providing information and assistance to people and are being applied in many aspects of life.In mitigating problematic social media use,LLMs such as ChatGPT can play a positive role by serving as conversational partners and outlets for users,providing personalized information and resources,monitoring and intervening in problematic social media use,and more.In this process,we should recognize both the enormous potential and endless possibilities of LLMs such as ChatGPT,leveraging their advantages to better address problematic social media use,while also acknowledging the limitations and potential pitfalls of ChatGPT technology,such as errors,limitations in issue resolution,privacy and security concerns,and potential overreliance.When we leverage the advantages of LLMs to address issues in social media usage,we must adopt a cautious and ethical approach,being vigilant of the potential adverse effects that LLMs may have in addressing problematic social media use to better harness technology to serve individuals and society.

The Impact of Social Media on Dietary Behaviors and Body Image of College Students: A Qualitative Approach

Background: The use of social media platforms for health and nutrition information has become popular among college students. Although social media made information readily accessible in different formats, nutritional misinformation promoted by influencers and non-experts caused negative impact on diet behavior and perception of body image. Previous research indicated that extensive use of social media was positively linked to disordered eating behaviors. Social media platforms like Facebook and Instagram that allow users to follow celebrities intensified exposure to influencers’ messages and images and resulted in negative moods and body dissatisfaction. Objective: This paper aims to explore the impact of social media on college students’ dietary behaviors and body image. Participants: 18 undergraduate students from a public university in the Southern United States were recruited through a mass email. Methods: A cross-sectional qualitative study of three focus groups was conducted. The focus groups were based on guiding open-ended questions. Atlas.ti was used to code and analyze the data using inductive and deductive codes. Results: Three main themes were identified. The conditions theme included elements that explain why and how social media influences the participants’ actions. The actions theme included eating behavior, physical activity, and dietary supplement intake. The consequences theme describes anticipated or actual outcomes of actions such as body image and ideal weight. Conclusions: Social media has had a negative influence on diet behaviors and a positive influence on physical activity. Evidence-based nutrition and weight management information is needed to thwart potential misinformation.