Online social media poses opportunities and risks in autistic youth: implications for services from a qualitative study.

Background: Autistic people are vulnerable to developing mental health problems due to their difficulties in managing social situations and interpersonal relationships. The popular online social media (OSM) can be a potential solution to these concerns for their social lives as it allows non-face-to-face social interactions, however it remained unclear how this group is using these online platforms. This study explored their experiences of using online social media, and their perceived benefits and risks associated with this use. Method: Qualitative data was collected through in-depth face to face interviews. We recruited 13 autistic young adults who were with normal intelligence from two community centers in Hong Kong. Interviews were conducted in a semi-structured format by experienced clinical psychologist and social workers. Results: Four themes were identified from the data, namely: (1) Paradox of using OSM to supplement social needs; (2) Unpleasant social interactions in the online environment; (3) Restricted and repetitive pattern of interest leading to troubles in OSM use, and; (4) Privacy and personal safety issues. The results suggested that while OSM could be a useful tool for our participants to connect with existing friends and to meet new ones, their limitations, such as difficulties in understanding languages and social interaction as well as restricted patterns of interests could potentially put them at risk, including interpersonal conflicts, cyber-bullying, financial scams, as well as unwanted sexual experiences. These experiences not only paradoxically increased their sense of loneliness and their distance from others, but also resulted in a negative impact on their mood and functioning. Conclusion: This qualitative study provided some insights into the OSM use among autistic young adults. OSM could be a useful tool to overcome potential limitations in social interactions, but at the same time it could potentially bring detrimental consequences. In order to maximize the benefits of online social networking, there is a need for timely guidance and support to use OSM among autists, and for psychoeducation to promote awareness, and enable adequate skills and behaviors attainment associated with safe OSM use.

Psychometric properties of the Persian social media intrusion questionnaire.

In recent years, social media use has dramatically increased worldwide, which has raised many concerns concerning the excessive use of social media. In this regard, Facebook Intrusion Questionnaire (FIQ) was developed to assess the level of addiction to Facebook. In this study, we first modified the FIQ items to cover all social media besides Facebook and labeled it the measure as Social Media Intrusion Questionnaire (SMIQ). Then, we examined its factor structure, reliability, and validity with 374 participants (M age = 25.91; SD = 5.81; 69.80% females) from the Iranian community sample. Confirmatory factor analysis supported the originally proposed uni-factor model, which was also invariant across gender groups. The SMIQ score demonstrated acceptable internal consistency (α = 0.85) and yielded expected associations with external correlates (e.g., cell-phone based addiction to social media, depression, and low self-esteem), supporting the measure's convergent and divergent validity. Overall, our findings indicated that Persian SMIQ enjoys sound psychometric properties.

Using Social Media to Facilitate Communication About Women's Testing: Tool Validation Study.

BACKGROUND: Strong participant recruitment practices are critical to public health research but are difficult to achieve. Traditional recruitment practices are often time consuming, costly, and fail to adequately target difficult-to-reach populations. Social media platforms such as Facebook are well-positioned to address this area of need, enabling researchers to leverage existing social networks and deliver targeted information. The MAGENTA (Making Genetic Testing Accessible) study aimed to improve the availability of genetic testing for hereditary cancer susceptibility in at-risk individuals through the use of a web-based communication system along with social media advertisements to improve reach. OBJECTIVE: This paper is aimed to evaluate the effectiveness of Facebook as an outreach tool for targeting women aged ≥30 years for recruitment in the MAGENTA study. METHODS: We designed and implemented paid and unpaid social media posts with ongoing assessment as a primary means of research participant recruitment in collaboration with patient advocates. Facebook analytics were used to assess the effectiveness of paid and unpaid outreach efforts. RESULTS: Over the course of the reported recruitment period, Facebook materials had a reach of 407,769 people and 57,248 (14.04%) instances of engagement, indicating that approximately 14.04% of people who saw information about the study on Facebook engaged with the content. Paid advertisements had a total reach of 373,682. Among those reached, just <15% (54,117/373,682, 14.48%) engaged with the page content. Unpaid posts published on the MAGENTA Facebook page resulted in a total of 34,087 reach and 3131 instances of engagement, indicating that around 9.19% (3131/34,087) of people who saw unpaid posts engaged. Women aged ≥65 years reported the best response rate, with approximately 43.95% (15,124/34,410) of reaches translating to engagement. Among the participants who completed the eligibility questionnaire, 27.44% (3837/13,983) had heard about the study through social media or another webpage. CONCLUSIONS: Facebook is a useful way of enhancing clinical trial recruitment of women aged ≥30 years who have a potentially increased risk for ovarian cancer by promoting news stories over social media, collaborating with patient advocacy groups, and running paid and unpaid campaigns. TRIAL REGISTRATION: ClinicalTrials.gov NCT02993068; https://clinicaltrials.gov/ct2/show/NCT02993068.

What Are the Characteristics of User Texts and Behaviors in Chinese Depression Posts?

Social media platforms provide unique insights into mental health issues, but a large number of related studies have focused on English text information. The purpose of this paper is to identify the posting content and posting behaviors of users with depression on Chinese social media. These clues may suggest signs of depression. We created two data sets consisting of 130 users with diagnosed depression and 320 other users that were randomly selected. By comparing and analyzing the two data sets, we can observe more closely how users reveal their signs of depression on Chinese social platforms. The results show that the distribution of some Chinese speech users with depression is significantly different from that of other users. Emotional sadness, fear and disgust are more common in the depression class. For personal pronouns, negative words and interrogative words, there are also great differences between the two data sets. Using topic modeling, we found that patients mainly discussed seven topics: negative emotion fluctuation, disease treatment and somatic responses, sleep disorders, sense of worthlessness, suicidal extreme behavior, seeking emotional support and interpersonal communication. The depression class post negative polarity posts much more frequently than other users. The frequency and characteristics of posts also reveal certain characteristics, such as sleep problems and reduced self-disclosure. In this study, we used Chinese microblog data to conduct a detailed analysis of the users showing depression signs, which helps to identify more patients with depression. At the same time, the study can provide a further theoretical basis for cross-cultural research of different language groups in the field of psychology.

A Transformer-Based Model for Evaluation of Information Relevance in Online Social-Media: A Case Study of Covid-19 Media Posts.

Online social media has become a major source of information gathering for a huge section of society. As the amount of information flows in online social media is enormous but on the other hand, the fact-checking sources are limited. This shortfall of fact-checking gives birth to the problem of misinformation and disinformation in the case of the truthfulness of facts on online social media which can have serious effects on the wellbeing of society. This problem of misconception becomes more rapid and critical when some events like the recent outbreak of Covid-19 happen when there is no or very little information is available anywhere. In this scenario, the identification of the content available online which is mostly propagated from person to person and not by any governing authority is very needed at the hour. To solve this problem, the information available online should be verified properly before being conceived by any individual. We propose a scheme to classify the online social media posts (Tweets) with the help of the BERT (Bidirectional Encoder Representations from Transformers)-based model. Also, we compared the performance of the proposed approach with the other machine learning techniques and other State of the art techniques available. The proposed model not only classifies the tweets as relevant or irrelevant, but also creates a set of topics by which one can identify a text as relevant or irrelevant to his/her need just by just matching the keywords of the topic. To accomplish this task, after the classification of the tweets, we apply a possible topic modelling approach based on latent semantic analysis and latent Dirichlet allocation methods to identify which of the topics are mostly propagated as false information.

Predictors of e-democracy applicability in Turkish K-12 schools.

Today, the COVID-19 pandemic has paved the way for a more democratic climate in K-12 schools. Administrators and teachers have had to seek out new ways through which to interact. This raises two questions; "What about the quality of interaction and participation in decision-making?" and "Which factors affect the level of participation in decision-making?" The aim of the current research is to determine the factors that predict the applicability level of e-democracy (i.e., "reporting and declaring opinions" and "decision-making") in K-12 schools. An associational research design was used in order to attain the main goal of the study, with Discriminant Function Analysis (DFA) technique used to analyze the factors predicting the applicability level of e-democracy. Data were collected from a total of 765 inservice K-12 teachers through a questionnaire developed by the researchers. DFA results showed "motivation to participate," "the level of participatory democracy in the country," and higher levels of the "use of Twitter" as the significant determinants of different levels of e-democracy application. Moreover, the results also indicated that those participants with the belief of e-democracy's applicability at the decision-making level found the "motivation level of stakeholders" to be the most critical. Their level of Twitter use was higher. They also believed that the level of participatory democracy in the country was at a higher level. Another result of the DFA pointed to "security and ethical issues," and lower levels of the "use of Twitter" as factors differentiating the group believing that e-democracy can be applicable with reporting and the declaration of opinions to administrators from the other groups. The discussions highlighted the critical role of participation level in e-democracy within K-12 schools.

[Estimating the number of COVID-19 cases using a web-based tool: Results from the first week of the 'Covid-19 Trends' project in the Basque Country]. / Estimando el número de casos de COVID-19 mediante una herramienta web: resultados de la primera semana del proyecto «Covid-19 Trends¼ en Euskadi.

OBJECTIVE: In the Basque Country, two cases of COVID-19 were diagnosed on February 28 2020. On March 14, the Spanish Government established a state of alarm. Only cases confirmed by molecular biology (reverse-transcriptase polymerase chain reaction [RT-PCR]) were known. We launched a web-based surveillance tool to estimate the number of symptomatic cases of COVID-19 to contribute to Public Health decision-making. MATERIAL AND METHODS: We implemented an anonymous web questionnaire and disseminated it through online social media social. We collected epidemiological information about «time¼ (date of onset of symptoms), «place¼ (zip code), and «person¼ (gender, age). We compared cases detected by RT-PCR with the estimated cases, according to the case definition of the Ministry of Health. We calculated the questionnaire response rate and the cumulative incidence at 14days. RESULTS: Between March 19 and 26, 128,009 people answered the questionnaire (5.5% of the Basque population). Of these, 26,375 met the case definition (symptom prevalence of 21.4%). The estimated cases were almost six times more than COVID-19 positive RT-PCR. The estimated 14-day cumulative incidence was 578.3 per 100,000 population compared to RT-PCR positive cases, which was 139.6 per 100,000 population. CONCLUSIONS: This tool was useful in estimating the minimum number of symptomatic cases in the Basque Country, which could support Public Health actions.

Implicações das redes sociais online para a educação da sensibilidade / Implications of online social media to sensitivity education

A violência pode ser identificada na sociedade contemporânea tanto no ambiente virtual quanto no não virtual. Os comportamentos violentos no ambiente não virtual foram analisados por Abib como sendo frutos do conflito entre as sensibilidades primeva e evoluída e propõe, então, o projeto de educação da sensibilidade, que visa restaurar o equilíbrio entre essas sensibilidades. Este trabalho buscou avaliar se as redes sociais online podem contribuir para a educação da sensibilidade cumprindo com seus princípios e estratégias. Para isso, foi realizada uma pesquisa teórico-bibliográfica, cujas fontes foram 34 artigos publicados na revista Computers and Human Behavior; e a análise se pautou nos conceitos fundamentais da educação da sensibilidade. Foram identificados comportamentos favoráveis (pró-sociais) os quais se pautam nos princípios e estratégias da educação da sensibilidade, e comportamentos desfavoráveis (antissociais) que não são condizentes com os princípios e estratégias da educação da sensibilidade. Concluiu-se que as redes sociais online poderiam viabilizar a educação da sensibilidade, mas as possibilidades de anonimato, perfis falsos, e a própria estrutura da Internet pode dificultar o seu desenvolvimento.

Violence can be identified in contemporary society in both virtual and non-virtual environments. Violent behaviors in the non-virtual environment were analyzed by Abib as being the result of the conflict between primeval and evolved sensibilities and propose, therefore, the project of sensitivity education, which aims to restore the balance between these sensitivities. This paper aimed to evaluate if online social media can contribute to the sensitivity education, complying with its principles and strategies. For this, theoretical-bibliographical research was conducted, whose sources were 34 articles published in the journal Computers and Human Behavior; and the analysis was based on the fundamental concepts of sensitivity education. Favorable (prosocial) behaviors which are based on the principles and strategies of sensitivity education were identified, and unfavorable (antisocial) behaviors that are not consistent with the principles and strategies of sensitivity education. It was concluded that online social networks could enable the education of sensitivity, but the possibilities of anonymity, false profiles, and the very structure of the Internet can hinder its development.

The Development of the Chinese Sentiment Lexicon for Internet.

This paper examines the development of the Chinese Sentiment Lexicon for Internet (CSLI), a sentiment lexicon for capturing the valence and arousal in Chinese online social media texts. We first review the current sentiment lexicons and their building process, including the collection of words, judging the emotionality of words, and testing reliability and validity. In Study 1, we develop CSLI and test its initial reliability and validity. In Study 2, we further test the convergent validity of CSLI by examining its correlations with human judgment in 429 aggregated Weibo comments. In Study 3, the predictive validity of CSLI is examined by linking its results to personality traits among 52 undergraduates. Two replication studies are also conducted to verify the findings in Study 2 and 3. The results have generally supported the reliability and validity of CSLI. Therefore, CSLI can be used as a research tool to capture the degree of valence and arousal in Chinese online social media texts. Its potential to promote human well-being is also discussed.

Critical dynamics in population vaccinating behavior.

Vaccine refusal can lead to renewed outbreaks of previously eliminated diseases and even delay global eradication. Vaccinating decisions exemplify a complex, coupled system where vaccinating behavior and disease dynamics influence one another. Such systems often exhibit critical phenomena-special dynamics close to a tipping point leading to a new dynamical regime. For instance, critical slowing down (declining rate of recovery from small perturbations) may emerge as a tipping point is approached. Here, we collected and geocoded tweets about measles-mumps-rubella vaccine and classified their sentiment using machine-learning algorithms. We also extracted data on measles-related Google searches. We find critical slowing down in the data at the level of California and the United States in the years before and after the 2014-2015 Disneyland, California measles outbreak. Critical slowing down starts growing appreciably several years before the Disneyland outbreak as vaccine uptake declines and the population approaches the tipping point. However, due to the adaptive nature of coupled behavior-disease systems, the population responds to the outbreak by moving away from the tipping point, causing "critical speeding up" whereby resilience to perturbations increases. A mathematical model of measles transmission and vaccine sentiment predicts the same qualitative patterns in the neighborhood of a tipping point to greatly reduced vaccine uptake and large epidemics. These results support the hypothesis that population vaccinating behavior near the disease elimination threshold is a critical phenomenon. Developing new analytical tools to detect these patterns in digital social data might help us identify populations at heightened risk of widespread vaccine refusal.

Integrating sentiment and social structure to determine preference alignments: the Irish Marriage Referendum.

We examine the relationship between social structure and sentiment through the analysis of a large collection of tweets about the Irish Marriage Referendum of 2015. We obtain the sentiment of every tweet with the hashtags #marref and #marriageref that was posted in the days leading to the referendum, and construct networks to aggregate sentiment and use it to study the interactions among users. Our analysis shows that the sentiment of outgoing mention tweets is correlated with the sentiment of incoming mentions, and there are significantly more connections between users with similar sentiment scores than among users with opposite scores in the mention and follower networks. We combine the community structure of the follower and mention networks with the activity level of the users and sentiment scores to find groups that support voting 'yes' or 'no' in the referendum. There were numerous conversations between users on opposing sides of the debate in the absence of follower connections, which suggests that there were efforts by some users to establish dialogue and debate across ideological divisions. Our analysis shows that social structure can be integrated successfully with sentiment to analyse and understand the disposition of social media users around controversial or polarizing issues. These results have potential applications in the integration of data and metadata to study opinion dynamics, public opinion modelling and polling.

Semantic network analysis of vaccine sentiment in online social media.

OBJECTIVE: To examine current vaccine sentiment on social media by constructing and analyzing semantic networks of vaccine information from highly shared websites of Twitter users in the United States; and to assist public health communication of vaccines. BACKGROUND: Vaccine hesitancy continues to contribute to suboptimal vaccination coverage in the United States, posing significant risk of disease outbreaks, yet remains poorly understood. METHODS: We constructed semantic networks of vaccine information from internet articles shared by Twitter users in the United States. We analyzed resulting network topology, compared semantic differences, and identified the most salient concepts within networks expressing positive, negative, and neutral vaccine sentiment. RESULTS: The semantic network of positive vaccine sentiment demonstrated greater cohesiveness in discourse compared to the larger, less-connected network of negative vaccine sentiment. The positive sentiment network centered around parents and focused on communicating health risks and benefits, highlighting medical concepts such as measles, autism, HPV vaccine, vaccine-autism link, meningococcal disease, and MMR vaccine. In contrast, the negative network centered around children and focused on organizational bodies such as CDC, vaccine industry, doctors, mainstream media, pharmaceutical companies, and United States. The prevalence of negative vaccine sentiment was demonstrated through diverse messaging, framed around skepticism and distrust of government organizations that communicate scientific evidence supporting positive vaccine benefits. CONCLUSION: Semantic network analysis of vaccine sentiment in online social media can enhance understanding of the scope and variability of current attitudes and beliefs toward vaccines. Our study synthesizes quantitative and qualitative evidence from an interdisciplinary approach to better understand complex drivers of vaccine hesitancy for public health communication, to improve vaccine confidence and vaccination coverage in the United States.

Factors Associated With Weight Change in Online Weight Management Communities: A Case Study in the LoseIt Reddit Community.

BACKGROUND: Recent research has shown that of the 72% of American Internet users who have looked for health information online, 22% have searched for help to lose or control weight. This demand for information has given rise to many online weight management communities, where users support one another throughout their weight loss process. Whether and how user engagement in online communities relates to weight change is not totally understood. OBJECTIVE: We investigated the activity behavior and analyze the semantic content of the messages of active users in LoseIt (r/loseit), a weight management community of the online social network Reddit. We then explored whether these features are associated with weight loss in this online social network. METHODS: A data collection tool was used to collect English posts, comments, and other public metadata of active users (ie, users with at least one post or comment) on LoseIt from August 2010 to November 2014. Analyses of frequency and intensity of user interaction in the community were performed together with a semantic analysis of the messages, done by a latent Dirichlet allocation method. The association between weight loss and online user activity patterns, the semantics of the messages, and real-world variables was found by a linear regression model using 30-day weight change as the dependent variable. RESULTS: We collected posts and comments of 107,886 unique users. Among these, 101,003 (93.62%) wrote at least one comment and 38,981 (36.13%) wrote at least one post. Median percentage of days online was 3.81 (IQR 9.51). The 10 most-discussed semantic topics on posts were related to healthy food, clothing, calorie counting, workouts, looks, habits, support, and unhealthy food. In the subset of 754 users who had gender, age, and 30-day weight change data available, women were predominant and 92.9% (701/754) lost weight. Female gender, body mass index (BMI) at baseline, high levels of online activity, the number of upvotes received per post, and topics discussed within the community were independently associated with weight change. CONCLUSIONS: Our findings suggest that among active users of a weight management community, self-declaration of higher BMI levels (which may represent greater dissatisfaction with excess weight), high online activity, and engagement in discussions that might provide social support are associated with greater weight loss. These findings have the potential to aid health professionals to assist patients in online interventions by focusing efforts on increasing engagement and/or starting discussions on topics of higher impact on weight change.

In Pursuit of Theoretical Ground in Behavior Change Support Systems: Analysis of Peer-to-Peer Communication in a Health-Related Online Community.

BACKGROUND: Research studies involving health-related online communities have focused on examining network structure to understand mechanisms underlying behavior change. Content analysis of the messages exchanged in these communities has been limited to the "social support" perspective. However, existing behavior change theories suggest that message content plays a prominent role reflecting several sociocognitive factors that affect an individual's efforts to make a lifestyle change. An understanding of these factors is imperative to identify and harness the mechanisms of behavior change in the Health 2.0 era. OBJECTIVE: The objective of this work is two-fold: (1) to harness digital communication data to capture essential meaning of communication and factors affecting a desired behavior change, and (2) to understand the applicability of existing behavior change theories to characterize peer-to-peer communication in online platforms. METHODS: In this paper, we describe grounded theory-based qualitative analysis of digital communication in QuitNet, an online community promoting smoking cessation. A database of 16,492 de-identified public messages from 1456 users from March 1-April 30, 2007, was used in our study. We analyzed 795 messages using grounded theory techniques to ensure thematic saturation. This analysis enabled identification of key concepts contained in the messages exchanged by QuitNet members, allowing us to understand the sociobehavioral intricacies underlying an individual's efforts to cease smoking in a group setting. We further ascertained the relevance of the identified themes to theoretical constructs in existing behavior change theories (eg, Health Belief Model) and theoretically linked techniques of behavior change taxonomy. RESULTS: We identified 43 different concepts, which were then grouped under 12 themes based on analysis of 795 messages. Examples of concepts include "sleepiness," "pledge," "patch," "spouse," and "slip." Examples of themes include "traditions," "social support," "obstacles," "relapse," and "cravings." Results indicate that themes consisting of member-generated strategies such as "virtual bonfires" and "pledges" were related to the highest number of theoretical constructs from the existing behavior change theories. In addition, results indicate that the member-generated communication content supports sociocognitive constructs from more than one behavior change model, unlike the majority of the existing theory-driven interventions. CONCLUSIONS: With the onset of mobile phones and ubiquitous Internet connectivity, online social network data reflect the intricacies of human health behavior as experienced by health consumers in real time. This study offers methodological insights for qualitative investigations that examine the various kinds of behavioral constructs prevalent in the messages exchanged among users of online communities. Theoretically, this study establishes the manifestation of existing behavior change theories in QuitNet-like online health communities. Pragmatically, it sets the stage for real-time, data-driven sociobehavioral interventions promoting healthy lifestyle modifications by allowing us to understand the emergent user needs to sustain a desired behavior change.

Visual analysis of online social media to open up the investigation of stance phenomena.

Online social media are a perfect text source for stance analysis. Stance in human communication is concerned with speaker attitudes, beliefs, feelings and opinions. Expressions of stance are associated with the speakers' view of what they are talking about and what is up for discussion and negotiation in the intersubjective exchange. Taking stance is thus crucial for the social construction of meaning. Increased knowledge of stance can be useful for many application fields such as business intelligence, security analytics, or social media monitoring. In order to process large amounts of text data for stance analyses, linguists need interactive tools to explore the textual sources as well as the processed data based on computational linguistics techniques. Both original texts and derived data are important for refining the analyses iteratively. In this work, we present a visual analytics tool for online social media text data that can be used to open up the investigation of stance phenomena. Our approach complements traditional linguistic analysis techniques and is based on the analysis of utterances associated with two stance categories: sentiment and certainty. Our contributions include (1) the description of a novel web-based solution for analyzing the use and patterns of stance meanings and expressions in human communication over time; and (2) specialized techniques used for visualizing analysis provenance and corpus overview/navigation. We demonstrate our approach by means of text media on a highly controversial scandal with regard to expressions of anger and provide an expert review from linguists who have been using our tool.

A Study of the Demographics of Web-Based Health-Related Social Media Users.

BACKGROUND: The rapid spread of Web-based social media in recent years has impacted how patients share health-related information. However, little work has studied the demographics of these users. OBJECTIVE: Our aim was to study the demographics of users who participate in health-related Web-based social outlets to identify possible links to health care disparities. METHODS: We analyze and compare three different types of health-related social outlets: (1) general Web-based social networks, Twitter and Google+, (2) drug review websites, and (3) health Web forums. We focus on the following demographic attributes: age, gender, ethnicity, location, and writing level. We build and evaluate domain-specific classifiers to infer missing data where possible. The estimated demographic statistics are compared against various baselines, such as Internet and social networks usage of the population. RESULTS: We found that (1) drug review websites and health Web forums are dominated by female users, (2) the participants of health-related social outlets are generally older with the exception of the 65+ years bracket, (3) blacks are underrepresented in health-related social networks, (4) users in areas with better access to health care participate more in Web-based health-related social outlets, and (5) the writing level of users in health-related social outlets is significantly lower than the reading level of the population. CONCLUSIONS: We identified interesting and actionable disparities in the participation of various demographic groups to various types of health-related social outlets. These disparities are significantly distinct from the disparities in Internet usage or general social outlets participation.

A mixed-methods study of young adults' receptivity to using Facebook for smoking cessation: if you build it, will they come?

PURPOSE: To determine whether young adults are interested in a Facebook intervention for smoking cessation and to inform the design of such an intervention. DESIGN: Mixed-methods. SETTING: Participants throughout the United States were recruited through Facebook. PARTICIPANTS: Young adults aged 18 to 25 years who had smoked at least once in the past month. METHOD: Participants (N = 570) completed an online survey of tobacco and social media use. A subset of 30 survey completers, stratified by motivation to quit smoking, agreed to participate in a structured interview over online chat. Themes were identified by using grounded theory. RESULTS: Approximately a third of the full sample (31%) reported they would want to get help to quit smoking by using Facebook. Interest in using Facebook to quit was greater among those who were more motivated to quit (χ(2) = 75.2, p < .001), had made a quit attempt in the past year (χ(2) = 16.0, p < .001), and had previously used the Internet for assistance with a quit attempt (χ(2) = 6.2, p = .013). In qualitative interviews, social support and convenience were identified as strengths of a Facebook intervention, while privacy was the main issue of concern. CONCLUSION: Nearly one in three young adult smokers on Facebook expressed interest in using Facebook for quitting smoking. Social media approaches that respect privacy and tailor to readiness to quit are likely to maximize participation.

Using online social media for recruitment of human immunodeficiency virus-positive participants: a cross-sectional survey.

BACKGROUND: There are many challenges in recruiting and engaging participants when conducting research, especially with HIV-positive individuals. Some of these challenges include geographical barriers, insufficient time and financial resources, and perceived HIV-related stigma. OBJECTIVE: This paper describes the methodology of a recruitment approach that capitalized on existing online social media venues and other Internet resources in an attempt to overcome some of these barriers to research recruitment and retention. METHODS: From May through August 2013, a campaign approach using a combination of online social media, non-financial incentives, and Web-based survey software was implemented to advertise, recruit, and retain participants, and collect data for a survey study with a limited budget. RESULTS: Approximately US $5,000 was spent with a research staff designated at 20% of full-time effort, yielding 2034 survey clicks, 1404 of which met the inclusion criteria and initiated the survey, for an average cost of US $3.56 per survey initiation. A total of 1221 individuals completed the survey, yielding 86.97% retention. CONCLUSIONS: These data indicate that online recruitment is a feasible and efficient tool that can be further enhanced by sophisticated online data collection software and the addition of non-financial incentives.

Online support for parents of preterm infants: a qualitative and content analysis of Facebook 'preemie' groups.

OBJECTIVE: To qualitatively evaluate the content of communication in Facebook communities dedicated to preterm infants. DESIGN: The 25 largest public English-language Facebook groups focusing on preterm infants were identified. For each group, the 20 most recent wallposts and a maximum of the 15 first comments to these wallposts, and the 15 most recent discussion topics were analysed according to a thematic coding scheme. The purpose of each group was determined and personal characteristics of administrators and active posters were analysed. RESULTS: 1497 individual Facebook groups focusing on preterm infants were found, wherein the 25 largest had between 391 and 14 986 members. Non-profit fundraising groups comprised 48% of analysed groups and had the greatest number of members (median 1450, IQR 548-5435), followed by general awareness (24% of all groups, members: median 1183, IQR 658-2116) and interpersonal support groups (28% of all groups, members: median 823, IQR 484-1022). 85.0% of administrators and 91.5% of posters were women, and two-thirds of posts had been written by mothers of preterm infants. The analysis of posts, comments and discussion topics (n=1054) showed that 'information sharing' (31%) and 'interpersonal support' (53%) were the most common purposes. CONCLUSIONS: Facebook groups related to preterm birth have become a popular tool for fundraising and awareness-raising. However, most group members use these forums for information sharing and interpersonal support. Given their popularity and reach, further research is warranted to understand the motivations, implications and risks of dynamic online communication among parents of preterm infants.