Social features of Web Assisted Tobacco Interventions (WATIS) : case studies

textWeb Assisted Tobacco Interventions (WATIs) are proliferating due to their cost effectiveness and their compatibility with a fast-paced lifestyle that needs to be time and space detached. Following a general trend in web assisted interventions, WATIs are increasingly incorporating social media features. Often though, because they are added post-facto to a solid preexisting foundation that privileges information delivery, the social media and the informational sections are developed independently: the social component has no impact on the informational content. This forms the basis of this study, which proposes to do a detailed analysis of a WATI recommended by a panel of experts in the area of smoking cessation. An emphasis will be given to the visibility of social media features and the degree to which content from the social media component contributed by users impacts the informational component generated by content experts. This analysis will be supported by instruments for data collection especially adapted/designed for this study. This dissertation proposal is at the cusp of disciplinary boundaries as its theoretical underpinnings are in the intersections of three domains: design, health, and social media. This interdisciplinary approach is necessarily reflected in the study's conceptual vii framework, which draws from constructs such as "design with intent", tailored health interventions, and social networks for participatory culture. As a result of the detailed analysis, and the author's own expertise in social media across other fields, a set of recommendations will be proposed for the design of WATIs with social features aiming at a greater impact of these on the evidence-based informational content.Radio-Television-Fil

Combining Users’ Needs With Health Behavior Models in Designing an Internet- and Mobile-Based Intervention for Physical Activity in Cardiac Rehabilitation

Background: Internet-based physical activity interventions have great potential in supporting patients in cardiac rehabilitation. Health behavior change theories and user input are identified as important contributors in the effectiveness of the interventions, but they are rarely combined in a systematic way in the design of the interventions. Objective: The aim of this study is to identify the appropriate theoretical framework, along with the needs of the users of a physical activity intervention for cardiac rehabilitation, and to combine them into an effective Internet- and mobile-based intervention. Methods: We explain the theoretical framework of the intervention in a narrative overview of the existing health behavior change literature as it applies to physical activity. We also conducted a focus group with 11 participants of a cardiac rehabilitation program and used thematic analysis to identify and analyze patterns of meaning in the transcribed data. Results: We chose stage-based approaches, specifically the transtheoretical model and the health action process approach as our main framework for tailoring, supplemented with other theoretical concepts such as regulatory focus within the appropriate stages. From the thematic analysis of the focus group data, we identified seven themes: (1) social, (2) motivation, (3) integration into everyday life, (4) information, (5) planning, (6) monitoring and feedback, and (7) concerns and potential problems. The final design of the intervention was based on both the theoretical review and the user input, and it is explained in detail. Conclusions: We applied a combination of health behavioral theory and user input in designing our intervention. We think this is a promising design approach with the potential to combine the high efficacy of theory-based interventions with the higher perceived usefulness of interventions designed according to user input

The Feasibility of Incentivizing Participation in an Online Social Network Weight Loss Program

Engagement in online social network-delivered weight loss interventions is a predictor of weight loss. Incentivizing engagement in a subset of participants may increase group engagement and subsequent weight loss. In a pilot feasibility trial, 56 adults with obesity were randomized to two Facebook-delivered weight loss interventions, one had 10% users incentivized to engage daily and the other did not. We compared conditions on engagement and weight loss, and then compared incentivized users and natural high engagers on weight loss. Participants were 46.3 (SD: 10.3) years and 89% female. The incentivized user condition had greater total engagement (p=0.0361), but weight loss did not differ (p=0.2096). Three natural superusers emerged in each condition. Natural superusers lost more weight than incentivized users (p=0.0358). Natural superusers’ posts elicited more comments than incentivized superusers (p=0.0107). Incentivized superusers may engage differently than natural superusers. Future studies should explore ways to promote engagement in online interventions

Understanding Individual Differences for Tailored Smoking Cessation Apps

Finding ways to help people quit smoking is a high priority in health behavior change research. Recent HCI studies involving technologies using specific quitting techniques such as social support and SMS messaging to help people quit have reported some success. Early studies using computer generated print material report significant success of tailored versus non-tailored material, however, there is limited understanding on what aspects of digitally delivered quitting assistance should be tailored and how. To address this, we have conducted an empirical investigation with smokers to identify perceived importance of different types of help when quitting and the potential role of technology in providing such help. We found that people are highly individual in their approach to quitting and the kind of help they regard as relevant to their situation. Our contribution is a collection of empirically derived themes for tailoring smoking cessation apps to individual quitting needs. Author Keywords Smoking cessation; tailoring; individual differences; healt

Social Media Analytics of Smoking Cessation Intervention: User Behavior Analysis, Classification, and Prediction

Tobacco use causes a large number of diseases and deaths in the United States. Traditional intervention programs are based on face-to-face consulting, and social support is offered to help smoking quitters control stress and achieve better intervention outcomes. However, the scalability of these traditional intervention programs is limited by time and location. With the development of Web 2.0, many intervention programs of smoking cessation are developed online to reach a wider population. QuitNet is a popular website for smoking cessation that provides different services to help users quit smoking. It builds communities on different social media for people to discuss issues of smoking cessation and provide social support for each other. In this dissertation, we develop a comprehensive study to understand user behavior and their discussion interactions in online communities of smoking cessation. We compare user features and behaviors on different social media channels, analyze user interactions from the perspective of social support exchange, and apply data mining techniques to analyze discussion content and recommend threads for users. Health communities are developed on different types of social media. For example, QuitNet has Web forums on its own Web site while it also has its appearance on Facebook. The user participation may vary on different social media platforms. Users may also behave differently depending on the functions and design of the social media platforms. So, as the first step in this dissertation, we carry out a preliminary study to compare smoking cessation communities on different social media channels. We analyze user characteristics and behaviors in QuitNet Forum and QuitNet Facebook with statistical analysis and social network analysis. It is found that most users of QuitNet Forum are early smoking quitters, and they participate in discussions more actively than users of QuitNet Facebook. However, users of QuitNet Facebook have a wider spectrum of quitting statuses and interaction behaviors. Second, we are interested in user behaviors and how they exchange social support in online communities. Social support is "an exchange of resources between two individuals perceived by the provider or the recipient to be intended to enhance the well-being of the recipient". As QuitNet Forum attracts much more active users than QuitNet Facebook, it provides a better platform for our research purpose. So, we focus on QuitNet Forum, developing a classification scheme through qualitative analysis to categorize discussion topics and types of social support on the forum. Patterns of user behaviors are defined and identified. Social networks are built to analyze user interactions of social support exchange. It is found that users at different quit stages have different behaviors to exchange social support, and different types of social support flow between users at different quit stages. Discussion topics, user behaviors and patterns of social support exchanges are thoroughly analyzed. However, due to a huge amount of information on QuitNet Forum, it is difficult for users to find proper topics or peers to discuss or interact with. It would be helpful if we could apply machine learning techniques to understand user generated information in online health communities, and recommend discussion topics to users to participate in. We develop classifiers to categorize posts and comments on QuitNet Forum in terms of user intentions and social support types. User behaviors and patterns are used to help developing various feature sets. Then, we develop recommendation techniques to recommend threads for users to participate in. Based on traditional Collaborative Filtering and content-based approaches, we integrate classification results and user quit stages to develop recommendation systems. The experiments show that integrating classification results or user health statuses can achieve the best recommendation results with different percentages of unknown data. In this dissertation, we implement all-sided studies for online smoking cessation communities, including comprehensive analytics and applications. The proposed frameworks and approaches could be applied to other health communities. In the future, we will apply more analytics and techniques to a larger data set, and develop user-end applications to serve and improve online health intervention programs and communities.Ph.D., Computer Science -- Drexel University, 201

Exploring Facebook as an online support group for smoking cessation

2012 Spring.Includes bibliographical references.This paper employed a quantitative content analysis of the messages posted to a public Facebook page about smoking cessation. The study's population consisted of posts from October and November of 2010, from which a two-week constructed sample was drawn. The sample yielded 118 threads made up of 344 individual posts for analysis. Within the sample, 98 individuals (35 men, 54 women, 9 unidentifiable) served as the unit of analysis. This research explored the types of messages posted on Facebook to see if participants acted in line with gender norms for communicating online and about health. The types of support explored through the posts were informational, esteem and emotional. Results showed that men and women acted differently on the page than traditional gender norms would predict. Specifically, men and women posted to the page at similar rates and both groups used informational support more often than esteem support or emotional support. Smoking status was related to page use; the most active individuals posting to the page were recent quitters and they had a tendency to use informational and esteem support more often than emotional support. Participants also used Facebook's "like" function more often than posting messages containing overt support

An Avatar-Led Digital Smoking Cessation Program for Sexual and Gender Minority Young Adults: Intervention Development and Results of a Single-Arm Pilot Trial

BACKGROUND: Sexual and gender minority young adults have a high prevalence of smoking and unique barriers to accessing tobacco treatment. OBJECTIVE: To address these challenges as well as their preferences for sexual and gender minority-targeted interventions and digital programs, we developed and evaluated the acceptability, preliminary efficacy, and impact on theory-based change processes of an acceptance and commitment therapy-based digital program called Empowered, Queer, Quitting, and Living (EQQUAL). METHODS: Participants (n=22) of a single-arm trial conducted to evaluate the program were young adults, age 18 to 30 years, who self-identified as sexual and gender minority individuals and smoked at least one cigarette per day. All participants received access to the EQQUAL program. Participants completed web-based surveys at baseline and at a follow-up 2 months after enrollment. We verified self-reported smoking abstinence with biochemical testing; missing data were counted as smoking or using tobacco. RESULTS: For young adults who logged in at least once (n=18), the mean number of log-ins was 5.5 (SD 3.6), mean number of sessions completed was 3.1 (SD 2.6), and 39% (7/18) completed all 6 sessions. Overall, 93% of participants (14/15) were satisfied with the EQQUAL program, 100% (15/15) found it easy to use, and 100% (15/15) said it helped them be clearer about how to quit. Abstinence from smoking or using tobacco was confirmed with biochemical testing for 23% of participants (5/22). Both quantitative and qualitative results suggested a positive overall response to the avatar guide, with areas for future improvement largely centered on the avatar\u27s appearance and movements. CONCLUSIONS: Treatment acceptability of EQQUAL was very promising. The rate of abstinence, which was biochemically confirmed, was 3 times higher than that of the only other digital program to date that has targeted sexual and gender minority young adults and 6 to 13 times higher than those of nontargeted digital smoking interventions among sexual and gender minority young adults. Planned improvements for the next iteration of the program include making the avatar\u27s movements more natural; offering multiple avatar guides with different on characteristics such as race, ethnicity, and gender identity from which to choose; and providing a support forum for users to connect anonymously with peers

Marketing to Youth in the Digital Age: The Promotion of Unhealthy Products and Health Promoting Behaviours on Social Media

The near-ubiquitous use of social media among adolescents and young adults creates opportunities for both corporate brands and health promotion agencies to target and engage with young audiences in unprecedented ways. Traditional media is known to have both a positive and negative influence on youth health behaviours, but the impact of social media is less well understood. This paper first summarises current evidence around adolescents’ exposure to the pro-motion and marketing of unhealthy products such as energy dense and nutrient poor food and beverages, alcohol, and tobacco on social media sites such as Facebook, Twitter, Instagram and YouTube. We explore emerging evidence about the extent of exposure to marketing of these harmful products through social media platforms and potential impacts of exposure on adolescent health. Secondly, we present examples of health-promoting social media campaigns aimed at youth, with the purpose of describing innovative campaigns and highlighting lessons learned for creating effective social media interventions. Finally, we suggest implications for policy and practice, and identify knowledge gaps and opportunities for future research

Influences on the Uptake of and Engagement With Health and Well-Being Smartphone Apps: Systematic Review

Background: The public health impact of health and well-being digital interventions is dependent upon sufficient real-world uptake and engagement. Uptake is currently largely dependent on popularity indicators (eg, ranking and user ratings on app stores), which may not correspond with effectiveness, and rapid disengagement is common. Therefore, there is an urgent need to identify factors that influence uptake and engagement with health and well-being apps to inform new approaches that promote the effective use of such tools. Objective: This review aimed to understand what is known about influences on the uptake of and engagement with health and well-being smartphone apps among adults. Methods: We conducted a systematic review of quantitative, qualitative, and mixed methods studies. Studies conducted on adults were included if they focused on health and well-being smartphone apps reporting on uptake and engagement behavior. Studies identified through a systematic search in Medical Literature Analysis and Retrieval System Online, or MEDLARS Online (MEDLINE), EMBASE, Cumulative Index to Nursing and Allied Health Literature (CINAHL), PsychINFO, Scopus, Cochrane library databases, DataBase systems and Logic Programming (DBLP), and Association for Computing Machinery (ACM) Digital library were screened, with a proportion screened independently by 2 authors. Data synthesis and interpretation were undertaken using a deductive iterative process. External validity checking was undertaken by an independent researcher. A narrative synthesis of the findings was structured around the components of the capability, opportunity, motivation, behavior change model and the theoretical domains framework (TDF). Results: Of the 7640 identified studies, 41 were included in the review. Factors related to uptake (U), engagement (E), or both (B) were identified. Under capability, the main factors identified were app literacy skills (B), app awareness (U), available user guidance (B), health information (E), statistical information on progress (E), well-designed reminders (E), features to reduce cognitive load (E), and self-monitoring features (E). Availability at low cost (U), positive tone, and personalization (E) were identified as physical opportunity factors, whereas recommendations for health and well-being apps (U), embedded health professional support (E), and social networking (E) possibilities were social opportunity factors. Finally, the motivation factors included positive feedback (E), available rewards (E), goal setting (E), and the perceived utility of the app (E). Conclusions: Across a wide range of populations and behaviors, 26 factors relating to capability, opportunity, and motivation appear to influence the uptake of and engagement with health and well-being smartphone apps. Our recommendations may help app developers, health app portal developers, and policy makers in the optimization of health and well-being apps

Evaluation of quitnow men: An online, men-centered smoking cessation intervention

Background: Men continue to smoke cigarettes in greater numbers than women. There is growing evidence for the value of developing targeted, men-centered health promotion programs. However, few smoking cessation interventions have been designed for men. A gender-specific website, QuitNow Men, was developed based on focus group interview findings, stakeholder feedback, and evidence-based cessation strategies. The website was designed to incorporate a masculine look and feel through the use of images, direct language, and interactive content. Usability experts and end-users provided feedback on navigation and functionality of the website prior to pilot testing. Objectives: The objectives of the pilot study were to describe (1) men’s use and evaluations of the interactive resources and information on the QuitNow Men website, and (2) the potential of QuitNow Men to engage men in reducing and quitting smoking. Methods: A one-group, pretest-posttest study design was used. Men who were interested in quitting were recruited and invited to use the website over a 6-month period. Data were collected via online questionnaires at baseline, 3-month, and 6-month follow-up. A total of 117 men completed the baseline survey. Over half of those (67/117, 57.3%) completed both follow-up surveys. Results: At baseline, participants (N=117) had been smoking for an average of 24 years (SD 12.1) and smoked on average 15 cigarettes a day (SD 7.4). The majority had not previously used a quit smoking website (103/117, 88.0%) or websites focused on men’s health (105/117, 89.7%). At the 6-month follow-up, the majority of men used the QuitNow Men website at least once (64/67, 96%). Among the 64 users, 29 (43%) reported using the website more than 6 times. The men using QuitNow Men agreed or strongly agreed that the website was easy to use (51/64, 80%), the design and images were appealing (42/64, 66%), they intended to continue to use the website (42/64, 66%), and that they would recommend QuitNow Men to others who wanted to quit (46/64, 72%). Participants reported using an average of 8.76 (SD 4.08) of the 15 resources available on the website. At 6-month follow-up, 16 of the 67 participants (24%) had quit, 27 (40%) had reduced their smoking and 24 (36%) had not changed their smoking habits. Repeated measures general linear model showed a significant decrease in the number of cigarettes smoked between the 3-month and 6-month follow-up (F1,63=6.41, P=.01, eta squared=0.09). Number of resources used on the website, quit confidence, nicotine dependence and age significantly predicted number of quit attempts by those still smoking at 6 months (F4,45=2.73, P=.04), with number of resources used being the strongest predictor (P=.02). Conclusions: The results of this research support efforts to integrate gender-sensitive approaches in smoking cessation interventions and indicate that this novel Web-based resource has potential in supporting men’s smoking cessation efforts