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Appearance-related constructs underlying social media are negatively associated with mental health. However, their impact on the Spanish population is still unexplored. The present study aimed to validate the Spanish versions of two appearance-related scales: (1) the appearance-related social media consciousness (ASMC) scale; and (2) the critical thinking about media messages (CTMM) scale. Translation and cultural adaptation of the scales were carried out. The scales’ psychometric properties were assessed using exploratory and confirmatory factor analyses, measurement invariance across gender (boys vs. girls) and age groups (early adolescents vs. middle adolescents), internal consistency, and convergent validity. The sample included 803 Spanish secondary school adolescents aged between 12 and 18 (Mage = 15.1, 47.9% girls, 47.2% boys, 4.9% non-binary gender/others). The exploratory factor analyses replicated original one-factor structures of both scales, which was verified using confirmatory factor analysis. Regarding the ASMC Scale, a re-specified model (allowing for error correlations between Items 1–2) presented an adequate fit. Both models were invariant across gender and age groups. Excellent internal consistency was found. Bivariate correlations between the ASMC and eating disorders related variables (body esteem, disordered eating, self-esteem, sociocultural attitudes towards appearance, and general mental health) supported its convergent validity and proved ASMC to be a potential target for future preventive eating disorder interventions. However, the CTMM scale correlated only with sociocultural pressures, thus, further research is needed to assess the validity of the CTMM in Spanish samples

OBJECTIVE: To assess participant attendance and engagement for an in-person Canadian Ophthalmological Society (COS) annual meeting (2019) compared with a virtual COS annual meeting (2020). DESIGN: Retrospective case-control study of key event metrics of the 2019 and 2020 COS meetings as well as Twitter activity. METHODS: Key annual meeting metrics were collected retrospectively for 2020 virtual meeting and compared with the most recent in-person annual meeting cohort from 2019. Metrics collected included attendance by ophthalmology specialist, geographic distribution of attendees, postevent survey rate, and social media engagement (Twitter). RESULTS: Overall, there was a 7% (n = 60) increase in the number of registrants between 2019 and 2020. The largest change noted was the increase in registrants from British Columbia (n = 78). More ophthalmologists registered for the 2020 meeting than for 2019 meeting (627 versus 592). Of those who registered for the meeting, meeting participation (defined as checking in for the 2019 and logging in for the 2020 meetings) increased from 70% in 2019 to 79% in 2020. There was a 158% (n = 15 000) increase in tweet impressions in 2020 compared with 2019. CONCLUSION: The first COS virtual meeting attracted more participants and was available to a geographically wider audience. Indeed, more professionals from provinces that are geographically further from the traditional COS meeting locations were able to participate in the event. Meeting engagement on a social media platform increased in the virtual meeting in 2020 relative to the in-person meeting in 2019, and possible enablers for increased engagement should be sought and incorporated into future meetings.

A high-frequency approach is used to analyze the effects of President Trump’s tweets that criticize the Federal Reserve on financial markets. Identification exploits a short time window around the precise timestamp for each tweet. The average effect on the expected fed funds rate is negative and statistically significant, with the magnitude growing by horizon. The tweets also lead to an increase in stock prices and to a decrease in long-term U.S. Treasury yields. VAR evidence shows that the tweets had an important impact on actual monetary policy, the stock market, bond premia, and the macroeconomy.

Social media data are transforming sustainability science. However, challenges from restrictions in data accessibility and ethical concerns regarding potential data misuse have threatened this nascent field. Here, we review the literature on the use of social media data in environmental and sustainability research. We find that they can play a novel and irreplaceable role in achieving the UN Sustainable Development Goals by allowing a nuanced understanding of human-nature interactions at scale, observing the dynamics of social-ecological change, and investigating the co-construction of nature values. We reveal threats to data access and highlight scientific responsibility to address trade-offs between research transparency and privacy protection, while promoting inclusivity. This contributes to a wider societal debate of social media data for sustainability science and for the common good.

Residency programs that effectively utilize social media (SoMe) have the potential to distinguish themselves and improve their resident recruitment. These platforms allow programs to connect with applicants they otherwise might have limited ability to reach before the interview season. We sought to evaluate the presence of SoMe across diagnostic radiology residency programs and highlight future trends that programs should account for. A list of diagnostic radiology residency programs within the United States was obtained from the American Medical Association (AMA) FREIDA Residency Database. A search for the presence of Twitter, Facebook, and Instagram was performed for each program. Based on the analysis, the most utilized SoMe platform by diagnostic radiology residency programs was Twitter (61.73%), followed by Instagram (47.45%), and then Facebook (37.76%). Given that Twitter was the most utilized, further analysis was done to evaluate the total number of followers and the year of account creation. The results showed that the average program had 1081 ± 1438 followers and the mean year of creation was 2017 ± 2.6 years. Social media is an effective tool to disseminate information efficiently and effectively to prospective residency candidates. It is important that those involved in radiology medical education stay up to date with current and future social media trends while maintaining an active professional presence on these platforms.

Our aim in this study is to analyze the content and quality of the videos about hallux valgus on YouTube®. The first 50 videos published by typing "hallux valgus" in the search engine on the YouTube® site were analyzed. The number of views of all videos, likes, dislikes, who uploaded the video, video duration, content, watch rate, and how many days it was uploaded were analyzed and recorded. All videos were analyzed with Journal of the American Medical Association (JAMA), DISCERN, GQS, and VPI scores. Six of the videos (12%) were from academic sources, 14 (28%) from commercial product vendors, 13 (26%) by medical animation organizers, 8 (16%) by physicians, 4 (8%) by physiotherapists, 2 (4%) by physical training trainers, 1 (2%) by patients, and last 2 (4%) by trainers. The JAMA mean score of the videos was recorded as 2 (1-4), GQS 3.02 (2-5), DISCERN score 37.56 (26-68), and Video Power Index 41.35 (0-470). The quality of YouTube® videos about hallux valgus is low. The content and quality of health-related information obtained through the Internet are of increasing importance for both healthcare professionals and patients.

Machine learning is the sub field of Artificial Intelligence which is responsible for developing a system that has the capability to learn and improve from past experience. There is an increasing demand for the offensive language detection because there is a large code-mixed text. Sometimes there is a possibility of code-mixed texts which are written using native scripts. If the system is getting trained on the data which is created using single language then it will leads to failure because of complexity. Using online communities and social media platforms has become increasing now. Recently many of the researchers have been investigating different ways of identifying the abusive content and developing systems to detect its different types like aggression identification, cyber bullying detection, hate speech identification, offensive language identification and toxic comments identification. Developing mechanisms to detect this is a challenging task. In the last few years, machine learning techniques and deep learning concept has been playing a significant role in the development of solutions for offensive language detection. So, considerable efforts have also been devoted to the development of machine learning techniques and deep learning models which is used to identify toxic content in recent years. First, this survey provides offensive language taxonomy and detection approaches. Then, the article focuses on the offensive language identification and toxic comments identification approaches. This article reviews various models used, type of learning model, languages for which the developed model is applied, other methods or approaches that were compared against this model, dataset used, offensive language detection type and performance metrics. The findings from the review are as well summarized and they urge that further effort is required to get improvement in the current state-of-the art approaches. This article also focuses on future work to improve the offensive language classification and toxic comments identification.

The Internet is an extensively used source of medical education by the public. In particular, YouTube is a valuable source of information which can be used to improve patient education. However, there is no quality assurance regime for YouTube videos pertaining to medical education. In this study, we aimed to evaluate the quality and accuracy of videos regarding inguinal hernia repair.Two hundred videos were searched for and viewed on YouTube from the phrases: 'inguinal hernia repair,' 'patient information for inguinal hernia repair,' and 'hernia operation.' After the application of predefined exclusion criteria, 23 videos were selected and the following data were collected: number of views, duration since video was posted, and the number of likes, dislikes, and comments. The educational quality was rated using three scoring systems: Health on the Net code, Journal of the American Medical Association, and DISCERN scoring systems. All three scoring systems have been previously used to evaluate online videos; however, they have not been formally validated.The videos were of low quality when using the Health on the Net code, Journal of the American Medical Association, and DISCERN scoring systems. There was no association between video quality as measured by any of the scoring systems and the number of views. The number of days online was independently predictive of the number of views (P = 0.044) and explained 18% of the variance in views. Likewise, there was no significant association between video quality and video length.YouTube videos on inguinal hernia repair are of low quality and accuracy. However, the potential of using YouTube to educate patients cannot be ignored.

Although appearance comparison has emerged as an important mechanism underlying the detrimental effects of exposure to idealized social media images on body image among young women, little is known regarding the role of the direction of these comparisons. In addition, to date, little attention has been paid to the role of self-regulation processes in these effects. A sample of 260 female students (M

The use of social media that facilitates access to surgical training is increasing among general practitioners/surgeons. The present study aimed to evaluate the educational quality of videos on social media and the medical education websites in terms of trabeculectomy surgery.In this cross-sectional and register-based study, the term "trabeculectomy" has been searched on 22 websites containing medical surgery training videos. Demographical features and descriptive statistics of videos are noted. All videos were evaluated independently by two ophthalmologists according to DISCERN, Journal of American Medical Association, and Global Quality scoring system. The main 11 steps of trabeculectomy surgery were taken into consideration in each video and Video Quality Score was determined based on these steps.In total, 731 videos were watched and 634 were excluded and 97 videos were included in the study. The total quality of all videos according to DISCERN, JAMA, GQS, and VQS scores were 31.6 ± 9.1 (poor quality), 1.3 ± 0.4 (poor quality), 2.6 ± 0.9 (fair quality), and 6.9 ± 2.1 (poor quality) respectively. Only 6 of the 97 evaluated videos included all the steps of trabeculectomy surgery. Videos have longer duration, videos with narration or videos with descriptive subtitles were found to be significantly higher quality than those are not.The educational quality of internet videos may be far from the quality it should be and it is indisputable that it is necessary to be able to access surgical educational videos that are peer-viewed and whose quality is not doubted.

OBJECTIVE: To examine the marketing techniques food and beverage brands use on Instagram, as part of their sport sponsorship strategy. METHODS: We conducted a qualitative content analysis of 31 Instagram accounts during the 2021 Australian Open tennis tournament. Branded food and beverage posts with tennis-linked content were coded based on an initial screening and previously published frameworks. RESULTS: Of the 152 included posts, 92% were made by food and beverage companies that were official 'partners' of the Australian Open. Products in posts were mostly discretionary foods and alcohol. The most frequently used strategies were 'Engagement' (89%) and 'Branding' (80%) and nearly half (45%) of alcohol posts invited direct consumption of their product. CONCLUSIONS: The powerful combination of sport and social media are utilised by brands to interact and build relationship with consumers while promoting the consumption of alcohol and discretionary foods - products which impede rather than promote health. The indirect marketing techniques favoured by brands make this form of advertising difficult to identify and control. IMPLICATIONS FOR PUBLIC HEALTH: These results highlight the need for counter-marketing, policy and regulatory actions to remove unhealthy food and alcohol from sport and reorient sponsorship of sporting events towards products that promote health.

Social media use is pervasive among youth and is associated with body image disturbance and self-objectification. The present study investigated whether a 3-day social media fast in a sample for whom social media is especially salient, female adolescent dancers, can mitigate such negative effects. Through an online survey, 65 pre-teen and teen girls, aged 10-19, completed measures of self-objectification (body surveillance and body shame), self-esteem and self-compassion both prior to and following three days of abstaining from all social media. During the fast, girls reflected on their experiences in group messages on the messaging app, WhatsApp. Overall, the fast had positive effects on participants, for whom body surveillance and body shame was significantly reduced after the fast. Self-compassion significantly mediated the change in both body surveillance and body shame, and self-esteem was a significant mediator of improvements in body shame. The content of girls' group messages revealed a number of themes, such as more positive mental states during the fast. Future research should continue to examine the potential of brief social media fasts as a means to alleviate appearance pressures adolescent girls face on these platforms in daily life.

Social media use is consistently associated with more negative body image, but much of this literature is cross-sectional and/or lacks ecological validity. To overcome these limitations, we examined associations between everyday social media engagement and appearance satisfaction using an experience sampling method. Fifty participants from Central Europe completed a 14-day experience sampling phase in which they reported their appearance satisfaction at two random time-points each day, as well as following active engagement with social media content, using a wrist-worn wearable and a physical analogue scale (PAS; i.e., angle of a participant's forearm between flat and fully upright as a continuous response scale). Results indicated that engagement with social media content was significantly associated with lower appearance satisfaction. Additionally, we found that engagement with the content of known others was associated with significantly lower appearance satisfaction than engagement with the content of unknown others. These effects were stable even after controlling for participant demographics, active vs. passive daily social media use, and body image-related factors. These results provide evidence that everyday social media engagement is associated with lower appearance satisfaction and additionally provides preliminary support for the use of a PAS in body image research using an experience sampling method.

Suicidal ideation detection from social media is an evolving research with great challenges. Many of the people who have the tendency to suicide share their thoughts and opinions through social media platforms. As part of many researches it is observed that the publicly available posts from social media contain valuable criteria to effectively detect individuals with suicidal thoughts. The most difficult part to prevent suicide is to detect and understand the complex risk factors and warning signs that may lead to suicide. This can be achieved by identifying the sudden changes in a user behavior automatically. Natural language processing techniques can be used to collect behavioral and textual features from social media interactions and these features can be passed to a specially designed framework to detect anomalies in human interactions that are indicators of suicidal intentions. We can achieve fast detection of suicidal ideation using deep learning and/or machine learning based classification approaches. For such a purpose, we can employ the combination of LSTM and CNN models to detect such emotions from posts of the users. In order to improve the accuracy, some approaches like using more data for training, using attention model to improve the efficiency of existing models etc. could be done. This paper proposes a LSTM-Attention-CNN combined model to analyze social media submissions to detect any underlying suicidal intentions. During evaluations, the proposed model demonstrated an accuracy of 90.3 percent and an F1-score of 92.6 percent, which is greater than the baseline models., 12 pages, 12 figures, 4 tables

To examine our website and social media audience data to define the number of African users and review the effects of COVID-19 on our viewership from Africa, and look ahead to potential opportunities.Google Analytics was used to investigate the number of CTisus.com users from Africa across a three-year period: April 2018-March 2019, April 2019-March 2020, and April 2020-March 2021. The percent difference between 18/19 - 19/20 and 19/20 - 20/21 was identified. Each country was categorized into North, South, East, West, or Central Africa, based on the United Nations Statistical Division, and the percent difference was calculated for all five regions. The number of followers of our YouTube, Facebook, and Twitter channels in each African country was also analyzed, again classifying each country into regions.Forty-six of the fifty-four countries in Africa, and all four territories, accessed CTisus.com between April 2018 to March 2021. Northern Africa represented 49.87% of our website visits from all African countries. Southern Africa constituted 18.84% of our traffic and Eastern Africa 18.60%, while Western and Central Africa provided 11.90% and 0.79%, respectively. We found a 27% increase in website traffic from Africa between a non-COVID year and a complete pandemic year. Facebook statistics revealed that 20,782 likes to our page came from Africa, and 20,987 of our followers. Similarly, 15,391 of our YouTube views and 728 of our Twitter followers came from Africa.We have been successful in achieving a 27% increase in website traffic from Africa to our radiology social media offerings. This increase since the onset of the COVID-19 pandemic is encouraging, especially when noting that we do not have any paid advertising. We look forward to reaching a larger African audience to deliver radiology education in the future.

Various online platforms, such as YouTube, are used for surgical education. Esophageal surgery is sophisticated and surgical videos may help reduce the time it takes for surgeons to learn these complicated operations. There is no clear consensus regarding the quality and reliability of esophagectomy videos on YouTube. We aimed to evaluate esophageal surgery videos published on YouTube in terms of quality and reliability.The keywords "esophagectomy" and "surgery" were both searched on YouTube and the first 150 results were evaluated. Eighty two videos were included in the analysis. The quality and reliability of the videos were determined using the esophagectomy scoring system (ESS) developed by the authors, the Journal of the American Medical Association benchmark criteria, and the video power index.A total of 82 videos were reviewed. About two-thirds of the videos demonstrated the Ivor Lewis technique and included surgeries performed using the thoracoscopic/laparoscopic method. The videos were analyzed as per the source of the upload: academic (25.7%), industry-sponsored (9.7%), or individual (64.6%). When the scores were compared by the origin of the videos, industry-sponsored videos scored significantly higher than the videos produced by individuals and academic centers (P = 0.01). While the ESS and Journal of the American Medical Association benchmark criteria scores were significantly correlated (P = 0.00), no correlation was found between video length, video power index score, and ESS score.Conducting a professional evaluation of videos before they are published on YouTube may enhance video quality. Moreover, valuable videos of better quality can be produced by improving the ESS and by assessing more videos.

Social networking sites (SNSs) are popular among college-aged adults. The defining characteristic of SNSs is that they are a platform to electronically share content. Most students report posting alcohol-related content (ARC) on SNSs. Little is known concerning these students who consume both alcohol and ARC yet choose not to generate ARC.The purpose of the current study was to compare key characteristics of posters and non-posters and develop a measure assessing reasons for not posting ARC.The researchers recruited a diverse sample of 1063 college students from two universities for an online study.Relative to posters of ARC, non-posters tend to drink less, have fewer alcohol-related problems, and report fewer reasons for drinking. Non-posters also report viewing several positive and negative consequences of drinking on SNSs, but at lower levels than ARC posters. The Reasons Not to Post ARC Scale was correlated with common alcohol measures (drinking motives, drinking problems) and self-monitoring. The scale was not correlated with some other measures (posting and sharing alcohol-related content).Given the dominant echo chamber effects of ARC on SNSs, examining non-posters can provide insight into the cognitions that might prevent others from joining the ARC social media culture.

Background and purposeTwitter presence in academia has been linked to greater research impact which influences career progression. The purpose of this study was to analyse Twitter activity of the radiotherapy community around ESTRO congresses with a focus on gender-related and geographic trends.Materials and methodsTweets, re-tweets and replies, here designated as interactions, around the ESTRO congresses held in 2012–2021 were collected. Twitter activity was analysed temporally and, for the period 2016–2021, the geographical span of the ESTRO Twitter network was studied. Tweets and Twitter users collated during the 10 years analysed were ranked based on number of ‘likes’, ‘re-tweets’ and followers, considered as indicators of leadership/influence. Gender representation was assessed for the top-end percentiles.ResultsTwitter activity around ESTRO congresses was multiplied by 60 in 6 years growing from 150 interactions in 2012 to a peak of 9097 in 2018. In 2020, during the SARS-CoV-2 pandemic, activity dropped by 60 % to reach 2945 interactions and recovered to half the pre-pandemic level in 2021. Europe, North America and Oceania were strongly connected and remained the main contributors. While overall, 58 % of accounts were owned by men, this proportion increased towards top liked/re-tweeted tweets and most-followed profiles to reach up to 84 % in the top-percentiles.ConclusionDuring the SARS-CoV-2 pandemic, Twitter activity around ESTRO congresses substantially decreased. Men were over-represented on the platform and in most popular tweets and influential accounts. Given the increasing importance of social media presence in academia the gender-based biases observed may help in understanding the gender gap in career progression.

There is an increasing interest in the study of detecting psychological stress from the social media like Twitter. However, Twitter has a limitation on the number of characters used per tweet, resulting in data sparsity. Many techniques were proposed to detect stress at the tweet level, but most of them failed to leverage the text content to reduce the impact of data sparsity. In this work, two solutions are proposed to further leverage the text content for the tweet level stress detection. First, a new feature, Sarcasm_Level, is computed to indicate the sarcasm present in the tweet’s content and its influence in detecting stress. Second, a novel neighborhood tweet-based stress detection method is developed, which is a logistic regression-based approach that integrates the content of previous tweets, also known as neighborhood tweets. Experimental results reveal that the proposed model has significantly better performance in detecting stress since it incorporates the information from neighborhood tweets. Also, with the inclusion of the new feature, the proposed model outperformed other well-known machine learning models like support vector machines, random forests and logistic regression with better accuracy and F1-score.

YouTube has been increasingly used as a source of information by patients in the field of health, but many studies revealed poor information quality. This study evaluated the content and quality of YouTube videos on Temporomandibular Joint Arthrocentesis (TMJA) as an information resource for patients.YouTube search with the two keywords "temporomandibular joint arthrocentesis" and "temporomandibular joint lavage" was performed. The first 160 videos were listed for each term according to relevancy. Results were assessed for inclusion and categorized for source, purpose, target, arthrocentesis method described, and the narrator of the videos. An evaluation was performed independently by two oral and maxillofacial surgeons. The quality of videos was analyzed for the content and defined as poor, moderate, and excellent. DISCERN was also performed by scoring between 0 and 5.A total of 43 videos were evaluated. The most upload source was individual users (46.5%) and the most video upload purpose was information for professionals (37.2%). The method with the most information about was the two-needle technic, which had a rate of 44.2 percent. The average usefulness score of the videos was 3.00 and 57.1% of the videos resulted in poor quality. A statistically significant positive high correlation was found between DISCERN and usefulness scoring (r = 0.793; p lt; 0.001).The majority of YouTube videos are of poor quality and this situation affects the patients' decisions about treatment. Health professionals should be aware of the content on YouTube and produce high-quality, accurate, and up-to-date information for patient education.

The aim of this study was to evaluate and compare orthodontic videos uploaded to YouTube and TikTok, the two most popular video sharing platforms, and to determine which of these platforms has more reliable and higher quality videos.YouTube (www.YouTube.com) and Tiktok (www.tiktok.com) was searched for two search-terms: "Orthodontics" and "Orthodontic Treatment". Reliability and quality of the first 120 videos for each search-term was evaluated by social media video content evaluation tools: Global Quality Score (GQS) and Reliability Score (modified DISCERN tool).While YouTube videos were more informative or sharing patient experiences, TikTok videos were almost purely entertainment oriented. Tiktok videos had lower reliability. YouTube videos were rated of higher quality than Tiktok videos. GQS mean values for Youtube and TikTok were 2.90 ± 1.35 and 2.23 ± 1.08 respectively; and reliability (DISCERN) values were 2.42 ± 1.70 and 1.27 ± 1.48 respectively. GQS median values for Youtube and TikTok were 3 and 2 respectively; and reliability (DISCERN) values were 2 and 1 respectively. Most of the uploaders in both platforms were professionals.Neither YouTube videos nor Tiktok videos were found to be reliable or of good quality. Videos on YouTube were higher quality and more reliable than videos on TikTok. However, YouTube videos also contained unreliable information.

One of the most significant differences of M5 over previous forecasting competitions is that it was held on Kaggle, an online platform for data scientists and machine learning practitioners. Kaggle provides a gathering place, or virtual community, for web users who are interested in the M5 competition. Users can share code, models, features, and loss functions through online notebooks and discussion forums. Here, we study the social influence of this virtual community on user behavior in the M5 competition. We first research the content of the M5 virtual community by topic modeling and trend analysis. Further, we perform social media analysis to identify the potential relationship network of the virtual community. We study the roles and characteristics of some key participants who promoted the diffusion of information within the M5 virtual community. Overall, this study provides in-depth insights into the mechanism of the virtual community’s influence on the participants and has potential implications for future online competitions.

Against the uncertainty caused by the information overload in the online world, consumers can benefit greatly by reading online product reviews before making their online purchases. However, some of the reviews are written deceptively to manipulate purchasing decisions. The purpose of present study is to determine which feature combination is most effective in fake review detection among the features of sentiment scores, topic distributions, cluster distributions and bag of words. In this study, additional feature combinations to a sentiment analysis are searched to examine the critical problem of fake reviews made to influence the decision-making process using review from amazon.com dataset. Results of the study points that behavior-related features play an important role in fake review classifications when jointly used with text-related features. Verified purchase is the only behavior related feature used comparatively with other text-related features.

There is a need to obtain more information about target audiences in many areas such as law enforcement agencies, institutions, human resources, and advertising agencies. In this context, in addition to the information provided by individuals, their personal characteristics are also important. In particular, the predictability of personality traits of individuals is seen as a major parameter in making decisions about individuals. Textual and media data in social media, where people produce the most data, can provide clues about people's personal lives, characteristics, and personalities. Each social media environment may contain different assets and structures. Therefore, it is important to make a structural analysis according to the social media platform. There is also a need for a labelled dataset to develop a model that can predict personality traits from social media data. In this study, first, a personality dataset was created which was retrieved from Twitter and labelled with IBM Personality Insight. Then the unstructured data were transformed into meaningful and processable data, LSTM-based prediction models were created with the structural analysis, and evaluations were made on both our dataset and PAN-2015-EN.

While recent studies have examined the effects of viewing body-positive social media content on body appreciation and satisfaction in young adult women, research has yet to include older adult women. The current study assessed the effects of viewing body-positive Instagram content on body image in 205 adult women (18-76 years old) who were randomly assigned to view either body-positive, thin-ideal, or appearance-neutral Instagram content. Our findings demonstrated that exposure to body-positive Instagram content resulted in greater levels of body appreciation and body satisfaction compared to exposure to thin-ideal and neutral Instagram content, while no significant differences were found between any of the conditions on self-objectification. Finally, age was only a significant moderator for one variable (self objectification) and condition (thin ideal), indicating that exposure to body-positive social media content may improve levels of body appreciation and satisfaction in adult women, regardless of age.

Over the recent years, the status of luxury has been a fast-growing niche market (Alnawas & Hemsley-Brown, 2019; Chang, Ko, & Leite, 2016; Lo & Yeung, 2020; Yang & Matilla, 2016), contributing to enhancing its status of tourism to a superior commodity, usually labelled as luxuries. This promise of status enhancement has attracted managers to enter the luxury segment, thus conferring to their resorts (Yin Chu, Liang Tang, & Yi Luo, 2016; Walls, Okumus, Wang, & Joon-Wuk Kwun, 2011). The hospitality industry exerts efforts to have high involvement services, rich physical environments and professional services that support the prices (Knutson, Stevens, Patton, & Thompson, 1993; Seyfi, Hall, & Rasoolimanesh, 2020; Titz, 2007). However, tourists in luxury hotels are not expected to have only functional benefits since they also look for value experiential services (Alnawas & Hemsley-Brown, 2019; Cetin & Walls, 2016; Chaney, Lunardo, & Mencarelli, 2018; Walls, Okumus, Wang, & Kwun, 2011). info:eu-repo/semantics/publishedVersion

Research continues to accumulate suggesting that social media use presents a risk to youths' body image, yet the majority of this research has examined late adolescents and emerging adults. This study examined 151 preadolescent girls' (M age = 12.06, SD = 1.22) social media use and associations with both positive and negative body image at two time points separated by approximately five months. Girls completed an online survey that included several body image measures and items that queried girls about the social media platforms they used and the activities they engaged in on these platforms. Findings suggest that girls who use social media do not differ significantly from girls who do not use social media in terms of their body image. However, among girls who use social media, their type of engagement (appearance-focused versus communication-focused use) is important; only girls who engage in appearance-focused social media use seem to experience negative body image concerns.

BACKGROUND: The COVID-19 pandemic has caused isolation, fear, and impacted on maternal healthcare provision. AIM: To explore midwives' experiences about how COVID-19 impacted their ability to provide woman-centred care, and what lessons they have learnt as a result of the mandated government and hospital restrictions (such as social distancing) during the care of the woman and her family. METHODS: A qualitative interpretive descriptive study was conducted. Twenty-six midwives working in all models of care in all states and territories of Australia were recruited through social media, and selected using a maximum variation sampling approach. Data were collected through in-depth interviews between May to August, 2020. The interviews were recorded, transcribed verbatim, and thematically analysed. FINDINGS: Two overarching themes were identified: 'COVID-19 causing chaos' and 'keeping the woman at the centre of care'. The 'COVID-19 causing chaos' theme included three sub-themes: 'quickly evolving situation', 'challenging to provide care', and 'affecting women and families'. The 'Keeping the woman at the centre of care' theme included three sub-themes: 'trying to keep it normal', 'bending the rules and pushing the boundaries', and 'quality time for the woman, baby, and family unit'. CONCLUSION: Findings of this study offer important evidence regarding the impact of the pandemic on the provision of woman-centred care which is key to midwifery philosophy. Recommendations are made for ways to preserve and further enhance woman-centred care during periods of uncertainty such as during a pandemic or other health crises.

In recent days, social media, online services, smartphones, and the Internet of Things (IoT) produces large quantities of data every second. The generated data is structured, unstructured, or semi-structured and available in various formats. Therefore, traditional approaches are not sufficient to handle such kind of data effectively. High utility pattern mining is a famous study area of data analytics that incorporates utility measures to consider user-based constraints such as number of units and benefit, in addition to frequency statistics of datasets. It is also essential to make effective decisions, and their demand is increasing in the last decade. Several techniques have been suggested for utility-based frequent pattern extraction. However, these approaches are limited to data size and operate on standalone systems. We have proposed a parallel approach named distributed memory-optimized utility mining (DMOUM) for high utility-based frequent pattern mining to address this issue. A new pruning technique is implemented that greatly reduces processing time and memory use. The proposed approach can handle huge amounts of data, i.e., big data. DMOUM approach is implemented in cluster-node architecture using Spark. The results are validated on various real-time datasets and found proposed approach has better performance than cutting edge approaches in terms of run-time, memory consumption, and scalability measures. The proposed work will provide solutions to real-time issues such as health care, education, e-commerce, and so on.

Deep learning has recently achieved best-in-class performance in several fields, including biomedical domains such as X-ray images. Yet, data scarcity poses a strict limit on training successful deep learning systems in many, if not most, biomedical applications, including those involving brain images. In this study, we translate state-of-the-art transfer learning techniques for single-subject prediction of simpler (sex and age) and more complex phenotypes (number of people in household, household income, fluid intelligence and smoking behavior). We fine-tuned 2D and 3D ResNet-18 convolutional neural networks for target phenotype predictions from brain images of ∼40,000 UK Biobank participants, after pretraining on YouTube videos from the Kinetics dataset and natural images from the ImageNet dataset. Transfer learning was effective on several phenotypes, especially sex and age classification. Additionally, transfer learning in particular outperformed deep learning models trained from scratch especially on smaller sample sizes. The out-of-sample performance using transfer learning from previously learned knowledge based on real-world images and videos could unlock the potential in many areas of imaging neuroscience where deep learning solutions are currently infeasible.

The internet is a primary source of nutrition information in the US. Minorities and non-English speakers face a digital divide when accessing such information. We aimed to report on the reach of social media dissemination of the cultural adaptation of the evidence-based Kid's Healthy Eating Plate to Spanish-speaking Latinos and of previous versions.The adaptation was based on the Framework for Reporting Adaptations and Modifications-Expanded and was disseminated through social media platforms (116 days). Outcomes were impressions, shares, website link clicks, number of viewers, and access country.The kids' culturally adapted version had 288,773 impressions and 1,227 shares on social media; the website was linked 9,763 times, predominantly through Facebook (Meta Platforms, Inc). User engagement and pageviews were mostly from Spain, Latin American countries, and the US.The cultural adaptation of healthy eating guidelines for Spanish-speaking children was accessed in the US and worldwide. Promotion through social media had a significant impact on its reach. Cultural adaptation and paid dissemination of evidence-based materials may help close the digital divide and promote health literacy in diverse populations.

Modern methods of communication and engagement, such as social media, video games, and online shopping, use a variety of behavioral techniques to encourage and reward frequent use, opening the door to addiction. The technological addictions (TAs) are a set of disorders that accompany the technological advances that define the digital age. The TAs are an active source of research in the literature, with promising treatment options already available.There are promising therapeutic and psychopharmacologic treatments for a broad range of TAs. Stimulants, antidepressants, and cognitive therapies may all be effective for internet gaming disorder (IGD). Cognitive therapies may be effective for other TAs, such as social media addiction (SMA), online shopping addiction (OSA), and online porn addiction. Society's dependence on addictive technologies will only increase. Many of the TAs can be addressed with medication and therapy, with more research and literature developing at a rapid pace.

We live in an age of massive global disruption. Technological advancements threaten century-old business models, globalization is reordering supply chains, and people need to work with colleagues and customers who have vastly different backgrounds. On top of that, we have been in the midst of a global pandemic, and customers, employers, and investors are demanding more than just a Black Lives Matter social media post from organizations that purport to take social justice seriously. Organizations with high cultural intelligence (CQ) are able to navigate this volatility and complexity effectively. Over the last two decades, scholars from across the world have published hundreds of articles on CQ, the capability to relate and work effectively in complex, culturally diverse situations. Most of the work has examined CQ at the individual level. But what about organizations? Can organizations be culturally intelligent? The emerging research on CQ at the organizational level offers leaders and organizations critical insights for navigating today's diverse, digital world. Organizational CQ is a firm's capability to function effectively in a complex and unpredictable multicultural world. This article stresses the importance of the culturally intelligent organization and explains how to develop organizational CQ.

To analyze Twitter engagement in response to the urology match during the COVID-19 pandemic.Tweets containing the hashtags "#uromatch" or "#AUAmatch" during the 2021 and 2022 Match Week were reviewed. Date, author type and number of followers, general content, and engagement with each Tweet was collected. Differences in engagement between author type and content were analyzed using the Kruskal-Wallis H test. Tweet characteristics were compared between the 2021 and 2022 Match Cycles using the Chi-Square test.There were 656 Tweets in total, with 272 (43.5%) from 2021 and 353 (56.5%) from 2022. Medical students' and residency programs' posts received significantly more Tweet engagement than those by residents/fellows, attendings, or the AUA (P.05). Tweets focusing on announcing a new residency class and personal announcements of match results received significantly more engagements than other content categories (P.05). In 2022, there was a significantly higher percentage of Tweets about advice for unmatched applicants (2.2 vs 12.5; P.001), match statistics (0.4 vs 2.9; P = .028) and focus on underrepresented groups in urology (0.7 vs 3.4; P = .029).The Twitter response to the urology match between 2021 and 2022 mirrored the increase in competitiveness, with greater participation and an increasing focus on the difficulty of matching. During Match Week, Twitter is a readily available source of information for programs, matched students, and unmatched students alike. As we continue to embrace virtual platforms, we believe that Twitter will remain a major source of match-related information and can be an instrumental tool for broader networking in our field.

The present study examined the relationship between posting or viewing fitspiration and clean eating imagery in relation to body image, disordered eating, and compulsive exercise among women. Participants (269 women aged 18-30 years) who posted and/or viewed fitspiration, clean eating or travel imagery on Instagram completed an online cross-sectional questionnaire. Results showed engaging with fitspiration and clean eating material (either posting or viewing) was significantly positively associated with increased levels of compulsive exercise and athletic-ideal internalization. However, only viewing (not posting) fitspiration and clean eating content was significantly related to thin-ideal internalization and disordered eating symptomatology. Athletic-ideal internalization mediated the relationships between posting fitspiration/clean eating and disordered eating symptomatology and compulsive exercise. Both thin-ideal internalization and athletic-ideal internalization mediated the relationship between viewing fitspiration/clean eating material and disordered eating and compulsive exercise. Overall, the findings suggest that viewing fitspiration and clean eating content on Instagram is negatively associated with thin-ideal internalization and disordered eating symptomatology, however the same relationships do not exist for people who frequently post these types of material. The mediational pathways provide a nuanced understanding of how engaging with fitspiration and clean eating material on social media influences female users' body image and health behaviour.

Beauty content on social media has grown exponentially, however research has yet to investigate its association with appearance concerns. This study drew on components of the tripartite influence model to test the associations between young women's engagement with beauty content on social media and cosmetic surgery consideration. A sample of 399 undergraduate women aged 17-25years (M

The use of influencers in marketing is not new. However, the advent of the internet, and more recently various forms of social media have both accelerated the use of influencers in marketing, and also democratized its use considerably. In this paper, we explore the nature of influence and power. We describe a study directed at understanding the promises and perils of influencer marketing from both the firm- and influencer perspectives, with the objective of identifying three key tensions that exist for marketers in the management of influencer relationships. We outline and explain these tensions and the lessons that can be learned from them, and then illustrate the lessons with a series of positive and negative cases. We close by speculating on the further evolution of influencer marketing.

BACKGROUND: Adolescent major depressive disorder (MDD) is highly prevalent and associated with lifelong adversity. Evidence-based treatments exist, but accessible treatment alternatives are needed. We aimed to compare internet-based psychodynamic therapy (IPDT) with an established evidence-based treatment (internet-based cognitive behavioural therapy [ICBT]) for the treatment of adolescents with depression. METHODS: In this randomised, clinical trial, we tested whether IPDT was non-inferior to ICBT in the treatment of adolescent MDD. Eligible participants were 15-19 years old, presenting with a primary diagnosis of MDD according to DSM-5. Participants were recruited nationwide in Sweden through advertisements on social media, as well as contacts with junior and senior high schools, youth associations, social workers, and health-care providers. Adolescents who scored 9 or higher on the Quick Inventory of Depressive Symptomatology for Adolescents (QIDS-A17-SR) in an initial online screening were contacted by telephone for a diagnostic assessment using the Mini International Neuropsychiatric Interview. Participants were randomly assigned to ICBT or IPDT. Both interventions comprised eight self-help modules delivered over 10 weeks on a secure online platform. The primary outcome was change in depression severity measured weekly by the QIDS-A17-SR. Primary analyses were based on an intention-to-treat sample including all participants randomly assigned. A non-inferiority margin of Cohen's d=0·30 was predefined. The study is registered at ISRCTN, ISRCTN12552584. FINDINGS: Between Aug 19, 2019, and Oct 7, 2020, 996 young people completed screening; 516 (52%) were contacted for a diagnostic interview. 272 participants were eligible and randomly assigned to ICBT (n=136) or IPDT (n=136). In the ICBT group, 51 (38%) of 136 participants were classified as remitted, and 54 (40%) of 136 participants were classified as remitted in the IPDT group. Within-group effects were large (ICBT: within-group d=1·75, 95% CI 1·49 to 2·01; IPDT: within-group d=1·93, 1·67 to 2·20; both pFunding: Kavli trust

Cosmetic surgery and other elective noninvasive aesthetic procedures have become significantly more popular throughout the 21st century. As these procedures have grown in popularity, more and more Americans have begun to research potential procedures via social media. However, it is unclear whether plastic surgery practices have done an adequate job advertising these services via social media to men.A systematic search was conducted Google, Facebook, and Instagram in order to examine potential gender disparities in social media plastic surgery marketing in America. Each practice's Facebook and Instagram profile were analyzed in two separate fashions: the presence or absence of advertisement for male services in the last ten posts, and the proportion of specific procedures advertised.. Two Pearson chi-squared analyses comparing the statistical significance of differences in the Facebook and Instagram data were then performed.A total of 242 Facebook and 231 Instagram profiles were selected and subsequently analyzed. The number of both Facebook and Instagram profiles that advertised to male patients varied widely from state to state. Additionally, there was substantial disparity in the procedures most heavily marketed toward men and their actual popularity amongst the male demographic.Plastic surgery practices have not done an effective job in capitalizing upon the increased popularity of cosmetic procedures among men with their social media advertising. Although the industry has improved its presence on Instagram, the marketing efforts of plastic surgery practices geared toward capturing the interest and demand of the male demographic remain lacking.

Advances in artificial intelligence (AI) and brain science are going to have a huge impact on society. While technologies based on those advances can provide enormous social benefits, adoption of new technologies poses various risks. This article first reviews the co-evolution of AI and brain science and the benefits of brain-inspired AI in sustainability, healthcare, and scientific discoveries. We then consider possible risks from those technologies, including intentional abuse, autonomous weapons, cognitive enhancement by brain–computer interfaces, insidious effects of social media, inequity, and enfeeblement. We also discuss practical ways to bring ethical principles into practice. One proposal is to stop giving explicit goals to AI agents and to enable them to keep learning human preferences. Another is to learn from democratic mechanisms that evolved in human society to avoid over-consolidation of power. Finally, we emphasize the importance of open discussions not only by experts, but also including a diverse array of lay opinions.

We study the effects of social media on the informativeness of retail trading. Our identification strategy exploits the editorial delay between report submission and publication on Seeking Alpha, a popular crowdsourced investment research platform. We find the ability of retail order imbalances to predict the cross-section of stock returns and cash-flow news increases sharply in the intraday post-publication window relative to the pre-publication window. The findings are robust to controlling for report tone and stronger for reports authored by more capable contributors. The evidence suggests that recent technology-enabled innovations in how individuals share information help retail investors become better informed.

To determine how medical students' Twitter engagement impacted the urology residency match and overall student perception of Twitter.We utilized a mixed methods approach with (1) Twitter metrics data, (2) online student surveys, and (3) qualitative semi-structured interviews. Interviews were evaluated with iterative thematic content analysis, while quantitative data were analyzed with descriptive statistics, and univariate analyses.We identified 245 Twitter accounts of Urology residency applicants from the 2021 cycle. Matched students were more likely to have a Twitter account (59% matched vs 28% unmatched, P = .002) and account creation increased following the COVID-19 pandemic announcement. Matched students' profiles were associated with more followers, bios mentioning Urology, home Urology residency programs, and no international flags and/or references. The online survey had a 16% response rate. A majority reported utilizing Twitter for residency information (95%), wanting to continue Twitter throughout residency (67%), and feeling uncomfortable tweeting about racial, political, or diversity issues (64%). Nine interviews revealed 4 themes: Twitter's opportunities for networking, Twitter's role in the application process, the burden of social media use, and professionalism.Students applying to Urology residency increasingly utilized Twitter during the COVID-19 pandemic and having a Twitter account was associated with matching. While Twitter may not be necessary to succeed in the match and can pose an additional time burden, applicants view it as an opportunity for learning, networking, and personal branding.

Nurses comprise the largest portion of healthcare workers and are integral to the COVID-19 response. Twitter has become a popular platform for the public, including nurses, to engage in pandemic-related discourse.We sought to analyze the representation of the nursing profession and characterize nurses' experiences during the pandemic from tweets published in April 2020.We analyzed tweets using natural language processing, Word Adjacency Graph (WAG) Modeling, and thematic analysis. Authors independently reviewed 10% of raw tweets in each WAG-generated topic, qualitatively analyzed tweets, and identified emerging themes.Six themes emerged: Support and Recognition of Nurses, Military Metaphors, Superhuman/Spiritual Metaphors, Advocacy, Personal Experiences with Nurses, and Social/Political Commentary. Public perception of nurses was positive, but nurses conveyed harsh realities of their work.Findings highlight discrepancies in nursing experiences and public perceptions of nursing. Further research should accurately identify and convey the complexities of the nursing profession.

Since 2013 there have been at least 421 recorded incidents of gunfire on school grounds METHOD: This study used a critical review of national and local media news reports of 25 American male school shooter cases from 2013 to 2019.Approximately 88% of school shooters had at least one social media account, and 76% posted disturbing content of guns and threatening messages. Over 72% of shooters had at least one reported adverse childhood experience, and 60% reported being bullied in-person or online DISCUSSION: Professionals who work with adolescents are front-line providers who routinely assess student safety. Social media use is often underassessed, demonstrating a knowledge gap that may reveal insights into the perspective and well-being of adolescents. Inclusion of questions on social media, adverse childhood experiences, and experiences of bullying by pediatric nurses and others may be proactive measures that can help identify, protect, and intervene with at-risk students.

Because of the recent surge in the number of unicorns and their role in spurring entrepreneurship and social impacts, venture capitalists, entrepreneurs, and regulators are concerned about how startup firms are valued. This is due to a lack of financial and historical information about startups as well as the need to understand their disruptive technological aspects. The length of observations is 2008–2018. The study uses the average value of variables for cross-sectional estimations. Our study investigates whether the types of recent technologies adopted by startups could serve as key factors to be used in startup valuations. Using a sample of 4903 startup in 13 subregions, we find that financial information (revenues) and nonfinancial information (social media) as well as sectoral and technological differences influence startup equity valuation. Technologies that involve big data, clean tech, mobile and augmented reality are prominent equity valuation premiums, regardless of the subsectors in which the startups originate. In addition, we find that e-commerce and mobile and big data are effective technologies for startup firms to employ for accumulating short-term capital.

Social media has become increasingly important for patients when deciding whether they should undergo rhinoplasty. The purpose of this study is to analyze patient satisfaction of rhinoplasty procedures through RealSelf social media reviews.We collected data from 583 rhinoplasty reviews published on the RealSelf portal. In posts dated between 2016 and 2020, we included those which were labeled as "Worth It" and "Not Worth It." Posts that were labeled as "Unsure" or were left unlabeled were excluded from the study. In addition, posts not including the cost of their rhinoplasty were excluded. Taking into account patient demographics and cost of the procedure, we analyzed reasons for choosing to undergo surgery, reasons for choosing surgeons, and reasons for liking or disliking their procedure.Of the 583 reviews analyzed, most (45.4%) were categorized from the 18-24 years age group and there was an overall 93.8% satisfaction rate. While there was no statistically significant difference in the cost of rhinoplasty surgeries between "Worth It" and "Not Worth It" groups, the average cost of recorded rhinoplasties was US$ 8043 with a standard deviation ± $3296. According to our analysis, younger patients aged 18-24 years relied more on social media to choose their surgeons and desired a more natural appearance to their nose while older ones preferred compatible physician personalities and increased self-esteem for rhinoplasty.This study offers a unique perspective into the distinguishing characteristics of different age groups and the values they place in pursuing rhinoplasty, choosing their surgeons, and why they like/dislike their surgical outcomes.