Online social networks and smoking cessation: a scientific research agenda

Preferences of Iranian smokers regarding smart smoking cessation technologies: a parallel convergent mixed methods study

BACKGROUND

Considering the values and preferences of individuals who attempt to quit smoking is a crucial step in the development of smoking cessation technologies. This study aimed to explore preferences regarding smart smoking cessation technologies.

METHODS

This parallel convergent mixed-methods study was conducted in two phases: quantitative and qualitative. In the quantitative phase, a cross-sectional study was conducted with 360 participants selected through stratified random sampling from technology-based smoking cessation clinics in Tabriz, Tehran, and Karaj cities in Iran. Data on demographic characteristics and preferences for smart smoking cessation technologies were collected using questionnaires and analyzed using descriptive statistics. In the qualitative phase, 25 users of these technologies were selected through purposeful and snowball sampling. The data were gathered through in-depth semistructured interviews and analyzed using qualitative content analysis with a conventional approach. Quantitative and qualitative data were integrated using the merging strategy and convergence model.

RESULTS

The quantitative phase results indicated that the highest preference was related to wearing and using a smartwatch for smoking cessation and using mobile apps. In the qualitative phase, 17 subcategories were extracted and classified into 8 main categories: high effectiveness, better management of the smoking cessation process, personalized technology, safe and uncomplicated technologies, attractiveness and innovative design, scientific basis, mobile applications, and smart monitoring devices.

CONCLUSION

By combining and integrating quantitative and qualitative results, it can be concluded that users are more interested in wearable technologies and interactive mobile applications. The findings of this study can assist smoking cessation technology developers in designing and improving their tools based on user needs and preferences to enhance their effectiveness and acceptability.

A Social Media-Delivered Melanoma Prevention Program for Young Women Engaged in Frequent UV Tanning: Protocol for a Randomized Controlled Trial

BACKGROUND

Rates of melanoma have increased dramatically in the United States over the past 25 years, and it has become among the most prevalent cancers for young adult women. Intentional skin tanning leads to a pattern of intense and intermittent UV radiation exposure that is associated with increased risk of melanoma. Frequent tanning is most common among young women and is linked to a variety of sociocultural pressures that negatively impact body image and drive appearance control behaviors. Unfortunately, there are no established interventions designed for frequent tanners. This intervention addresses this gap with unique content informed by body image and acceptance-based interventions. The intervention is delivered using Facebook secret groups, an approach designed to support behavior change and ensure scalability.

OBJECTIVE

This study aims to describe the rationale and methodology of a randomized controlled trial of a melanoma prevention program targeting young women engaged in frequent indoor or outdoor UV tanning.

METHODS

Participants are women aged 18-25 years who report high-risk tanning (ie, at least 10 indoor tanning sessions in the past 12 months or 10 outdoor sessions in the previous summer). After recruitment and screening, participants completed a baseline survey and were randomly assigned to receive the intervention or an attention-matched control condition. Both conditions were 8-week-long Facebook groups (approximately 25 members each) with daily posting of content. Follow-up surveys are administered at 3, 8, and 18 months after baseline. The primary trial outcome is the combined number of indoor and outdoor tanning sessions reported at the 8-month follow-up. Hypothesized intervention mediators are assessed at the 3-month follow-up.

RESULTS

This project was funded by a National Cancer Institute award (R01 CA218068), and the trial procedures were approved by the University of Kentucky Institutional Review Board in February 2020. Trial recruitment and enrollment occurred in 6 waves of data collection, which started in February 2022 and closed in May 2023. The study is closed to enrollment but remains open for follow-ups, and this protocol report was prepared before data analyses. As of February 2024, all participants have completed the 8-month follow-up assessment, and data collection is scheduled to close by the end of 2024 after the collection of the 18-month follow-up.

CONCLUSIONS

This trial will contribute unique knowledge to the field of skin cancer prevention, as no fully powered trials have examined the efficacy of an intervention designed for frequent indoor or outdoor tanning. The trial may also contribute evidence of the value in translating principles of body image and acceptance-based interventions into the field of skin cancer prevention and beyond. If successful, the use of the Facebook platform is intended to aid in dissemination as it provides a way to embed the intervention into individuals' everyday routines.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03441321; https://clinicaltrials.gov/study/NCT03441321.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/56562.

Sequencing conversational turns in peer interactions: An integrated approach for evidence-based conversational agent for just-in-time nicotine cravings intervention

Background

Risky health behaviors place an enormous toll on public health systems. While relapse prevention support is integrated with most behavior modification programs, the results are suboptimal. Recent advances in artificial intelligence (AI) applications provide us with unique opportunities to develop just-in-time adaptive behavior change solutions.

Methods

In this study, we present an innovative framework, grounded in behavioral theory, and enhanced with social media sequencing and communications scenario builder to architect a conversational agent (CA) specialized in the prevention of relapses in the context of tobacco cessation. We modeled peer interaction data (n = 1000) using the taxonomy of behavior change techniques (BCTs) and speech act (SA) theory to uncover the socio-behavioral and linguistic context embedded within the online social discourse. Further, we uncovered the sequential patterns of BCTs and SAs from social conversations (n = 339,067). We utilized grounded theory-based techniques for extracting the scenarios that best describe individuals' needs and mapped them into the architecture of the virtual CA.

Results

The frequently occurring sequential patterns for BCTs were comparison of behavior and feedback and monitoring; for SAs were directive and assertion. Five cravings-related scenarios describing users' needs as they deal with nicotine cravings were identified along with the kinds of behavior change constructs that are being elicited within those scenarios.

Conclusions

AI-led virtual CAs focusing on behavior change need to employ data-driven and theory-linked approaches to address issues related to engagement, sustainability, and acceptance. The sequential patterns of theory and intent manifestations need to be considered when developing effective behavior change CAs.

Discerning conversational context in online health communities for personalized digital behavior change solutions using Pragmatics to Reveal Intent in Social Media (PRISM) framework

BACKGROUND

Online health communities (OHCs) have emerged as prominent platforms for behavior modification, and the digitization of online peer interactions has afforded researchers with unique opportunities to model multilevel mechanisms that drive behavior change. Existing studies, however, have been limited by a lack of methods that allow the capture of conversational context and socio-behavioral dynamics at scale, as manifested in these digital platforms.

OBJECTIVE

We develop, evaluate, and apply a novel methodological framework, Pragmatics to Reveal Intent in Social Media (PRISM), to facilitate granular characterization of peer interactions by combining multidimensional facets of human communication.

METHODS

We developed and applied PRISM to analyze peer interactions (N = 2.23 million) in QuitNet, an OHC for tobacco cessation. First, we generated a labeled set of peer interactions (n = 2,005) through manual annotation along three dimensions: communication themes (CTs), behavior change techniques (BCTs), and speech acts (SAs). Second, we used deep learning models to apply our qualitative codes at scale. Third, we applied our validated model to perform a retrospective analysis. Finally, using social network analysis (SNA), we portrayed large-scale patterns and relationships among the aforementioned communication dimensions embedded in peer interactions in QuitNet.

RESULTS

Qualitative analysis showed that the themes of social support and behavioral progress were common. The most used BCTs were feedback and monitoring and comparison of behavior, and users most commonly expressed their intentions using SAs-expressive and emotion. With additional in-domain pre-training, bidirectional encoder representations from Transformers (BERT) outperformed other deep learning models on the classification tasks. Content-specific SNA revealed that users' engagement or abstinence status is associated with the prevalence of various categories of BCTs and SAs, which also was evident from the visualization of network structures.

CONCLUSIONS

Our study describes the interplay of multilevel characteristics of online communication and their association with individual health behaviors.

Lessons Learned From Beta-Testing a Facebook Group Prototype to Promote Treatment Use in the "Connecting Alaska Native People to Quit Smoking" (CAN Quit) Study

Social media provides an effective tool to reach, engage, and connect smokers in cessation efforts. Our team developed a Facebook group, CAN Quit (Connecting Alaska Native People to Quit smoking), to promote use of evidence-based smoking cessation resources for Alaska Native people living in Alaska, which are underused despite their effectiveness. Often separated by geography and climate, Alaska Native people prefer group-based approaches for tobacco cessation that support their culture and values. Such preferences make Alaska Native people candidates for social media-based interventions that promote connection. This viewpoint discusses the steps involved and lessons learned in building and beta-testing our Facebook group prototype, which will then be evaluated in a pilot randomized controlled trial. We describe the process of training moderators to facilitate group engagement and foster community, and we describe how we developed and tested our intervention prototype and Facebook group. All parts of the prototype were designed to facilitate use of evidence-based cessation treatments. We include recommendations for best practices with the hope that lessons learned from the CAN Quit prototype could provide a model for others to create similar platforms that benefit Alaska Native and American Indian people in the context of smoking cessation.

Developing a Social Media Intervention to Connect Alaska Native People Who Smoke with Resources and Support to Quit Smoking: The Connecting Alaska Native Quit Study

BACKGROUND

Face-to-face tobacco cessation has had limited reach and efficacy in Alaska Native (AN) communities. We describe our two-phased approach to develop content for Connecting Alaska Native People to Quit Smoking, a Facebook group intervention to reduce barriers to evidence-based smoking cessation treatment for AN people in Alaska.

METHODS

Phase 1 included semi-structured telephone interviews with 30 AN people who smoke and ten stakeholders. They provided feedback on existing content from the Centers for Disease Control and Prevention Tips campaign and AN digital stories. Phase 2 included an online survey with a new group of 40 AN smokers who provided feedback on existing content via a measure of perceived effectiveness and cultural relevance.

RESULTS

Phase I results revealed participants evaluated content based upon story strength, relevance to AN culture, emotional appeal, relatability to AN people, and favorite video. No single posting was rated highly across all themes. All perceived effectiveness (PE) and cultural relevance median scores fell between 3.5 and 4.4 (range 1-5). PE scores varied across participant demographic groups.

CONCLUSIONS

Content embodying characteristics perceived to be most appealing, effective, and culturally relevant were selected for the private Facebook group content library with refinements made to incorporate images of AN people engaged in AN activities. PE scores indicate a need for a wide variety of content that moderators could pull from when conducting the intervention.

IMPLICATIONS

Social media content targeting specific population sectors, such as American Indian/AN people for tobacco cessation needs to be culturally tailored. Our approach provides a model others can follow to determine what is appealing, relevant, and effective messaging.

CLINICAL TRIAL REGISTRATION

NCT03645941.

Smoking cessation among disadvantaged young women during and after pregnancy: Exploring the role of social networks

OBJECTIVE

Smoking prevalence during and after pregnancy remains high among socioeconomically disadvantaged, European women. This research aims to gain insight into the role of social networks on smoking cessation among disadvantaged young women during and after pregnancy.

DESIGN

Qualitative interview study.

SETTING

Dutch preventive care program (VoorZorg).

PARTICIPANTS

Disadvantaged young women during and after pregnancy (n = 17) who participated in a Dutch preventive care program, and members in their social networks (n = 4).

METHODS

All qualitative interviews were recorded, transcribed, and analyzed by iterative coding processes.

FINDINGS

Many women were not intrinsically motivated to quit smoking due to, amongst other factors, difficulties in their lives (e.g. domestic violence, psychosocial problems), limited supportive social networks, and a strong dependence on relatives who smoked. Women seemed to be prompted to smoke by smoking cues in their social networks, while distancing from smokers would lead to feelings of social exclusion. When attempting to stop smoking, women experienced little encouragement from their social networks, which instead often undermined their smoking cessation efforts.

KEY CONCLUSIONS AND IMPLICATIONS FOR PRACTICE

The social networks of disadvantaged young women mostly had a negative role on their smoking cessation efforts. Our results emphasize the need to look at interventions that involve women's social networks, and explore novel opportunities, such as eHealth and mHealth applications so that these women can build supportive new social networks.

Exchanges in a Virtual Environment for Diabetes Self-Management Education and Support: Social Network Analysis

BACKGROUND

Diabetes remains a major health problem in the United States, affecting an estimated 10.5% of the population. Diabetes self-management interventions improve diabetes knowledge, self-management behaviors, and clinical outcomes. Widespread internet connectivity facilitates the use of eHealth interventions, which positively impacts knowledge, social support, and clinical and behavioral outcomes. In particular, diabetes interventions based on virtual environments have the potential to improve diabetes self-efficacy and support, while being highly feasible and usable. However, little is known about the patterns of social interactions and support taking place within type 2 diabetes-specific virtual communities.

OBJECTIVE

The objective of this study was to examine social support exchanges from a type 2 diabetes self-management education and support intervention that was delivered via a virtual environment.

METHODS

Data comprised virtual environment-mediated synchronous interactions among participants and between participants and providers from an intervention for type 2 diabetes self-management education and support. Network data derived from such social interactions were used to create networks to analyze patterns of social support exchange with the lens of social network analysis. Additionally, network correlations were used to explore associations between social support networks.

RESULTS

The findings revealed structural differences between support networks, as well as key network characteristics of supportive interactions facilitated by the intervention. Emotional and appraisal support networks are the larger, most centralized, and most active networks, suggesting that virtual communities can be good sources for these types of support. In addition, appraisal and instrumental support networks are more connected, suggesting that members of virtual communities are more likely to engage in larger group interactions where these types of support can be exchanged. Lastly, network correlations suggest that participants who exchange emotional support are likely to exchange appraisal or instrumental support, and participants who exchange appraisal support are likely to exchange instrumental support.

CONCLUSIONS

Social interaction patterns from disease-specific virtual environments can be studied using a social network analysis approach to better understand the exchange of social support. Network data can provide valuable insights into the design of novel and effective eHealth interventions given the unique opportunity virtual environments have facilitating realistic environments that are effective and sustainable, where social interactions can be leveraged to achieve diverse health goals.

Networked collective intelligence improves dissemination of scientific information regarding smoking risks

Despite substantial investments in public health campaigns, misunderstanding of health-related scientific information is pervasive. This is especially true in the case of tobacco use, where smokers have been found to systematically misperceive scientific information about the negative health effects of smoking, in some cases leading smokers to increase their pro-smoking bias. Here, we extend recent work on 'networked collective intelligence' by testing the hypothesis that allowing smokers and nonsmokers to collaboratively evaluate anti-smoking advertisements in online social networks can improve their ability to accurately assess the negative health effects of tobacco use. Using Amazon's Mechanical Turk, we conducted an online experiment where smokers and nonsmokers (N = 1600) were exposed to anti-smoking advertisements and asked to estimate the negative health effects of tobacco use, either on their own or in the presence of peer influence in a social network. Contrary to popular predictions, we find that both smokers and nonsmokers were surprisingly inaccurate at interpreting anti-smoking messages, and their errors persisted if they continued to interpret these messages on their own. However, smokers and nonsmokers significantly improved in their ability to accurately interpret anti-smoking messages by sharing their opinions in structured online social networks. Specifically, subjects in social networks reduced the error of their risk estimates by over 10 times more than subjects who revised solely based on individual reflection (p < 0.001, 10 experimental trials in total). These results suggest that social media networks may be used to activate social learning that improves the public's ability to accurately interpret vital public health information.

Social Media Intervention to Promote Smoking Treatment Utilization and Cessation Among Alaska Native People Who Smoke: Protocol for the Connecting Alaska Native People to Quit Smoking (CAN Quit) Pilot Study

BACKGROUND

Despite the high prevalence of tobacco use among Alaska Native (AN) people, tobacco cessation interventions developed specifically for this group are lacking. Social media hold promise as a scalable intervention strategy to promote smoking treatment utilization and cessation, given the barriers to treatment delivery (ie, geographic remoteness, limited funding, climate, and travel costs) in the state of Alaska (AK). Building on a longstanding tobacco control research partnership with the AK Tribal Health System, in this study, we are developing and pilot-testing a culturally relevant, Facebook (FB)-delivered intervention that incorporates a digital storytelling approach adapted from the effective Centers for Disease Control Tips from Former Smokers campaign.

OBJECTIVE

This study aims to promote evidence-based smoking treatment (eg, state quitline and Tribal cessation programs) uptake and cessation among AN people.

METHODS

This study fulfills the objectives for stage 1 of the National Institute on Drug Abuse behavioral integrative treatment development program. In stage 1a, we will use a mixed method approach to develop the FB intervention. Cultural variance and surface/deep structure frameworks will address the influence of culture in designing health messages. These developmental activities will include qualitative and quantitative assessments, followed by beta testing of proposed intervention content. In stage 1b, we will conduct a randomized pilot trial enrolling 60 AN adults who smoke. We will evaluate the feasibility, uptake, consumer response, and potential efficacy of the FB intervention compared with a control condition (quitline/treatment referral only). Primary outcome measures include feasibility and biochemically verified smoking abstinence at 1-, 3-, and 6-month follow-ups. Secondary outcomes will include self-reported smoking cessation treatment utilization and abstinence from tobacco/nicotine products. We will also explore interdependence (relationship orientation and collaborative efforts in lifestyle change) as a culturally relevant mediator of intervention efficacy.

RESULTS

The study enrolled 40 participants for phase 1, with data saturation being achieved at 30 AN people who smoke and 10 stakeholders. For phase 2, we enrolled 40 participants. Qualitative assessment of proposed intervention content was completed with 30 AN smokers and 10 stakeholders. We are currently analyzing data from the quantitative assessment with 40 participants in preparation for the beta testing, followed by the randomized pilot trial.

CONCLUSIONS

The project is innovative for its use of social media communication tools that are culturally relevant in a behavioral intervention designed to reach AN people statewide to promote smoking treatment utilization and cessation. The study will further advance tobacco cessation research in an underserved disparity group. If the pilot intervention is successful, we will have a blueprint to conduct a large randomized controlled efficacy trial. Our approach could be considered for other remote AN communities to enhance the reach of evidence-based tobacco cessation treatments.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/15155.

Prevalence and Factors Influencing Use of Internet and Electronic Health Resources by Middle-Aged and Older Adults in a US Health Plan Population: Cross-Sectional Survey Study

Background

Health care organizations are increasingly using electronic health (eHealth) platforms to provide and exchange health information and advice (HIA). There is limited information about how factors beyond internet access affect use of eHealth resources by middle-aged and older adults.

Objective

We aimed to estimate prevalence of use of the internet, health plan patient portal, and Web-based HIA among middle-aged and older adults; investigate whether similar sociodemographic-related disparities in eHealth resource use are found among middle-aged and older adults; and examine how sociodemographic and internet access factors drive disparities in eHealth resource use among adults who use the internet.

Methods

We analyzed cross-sectional survey data for 10,920 Northern California health plan members aged 45 to 85 years who responded to a mailed and Web-based health survey (2014-2015). We used bivariate and multivariable analyses with weighted data to estimate prevalence of and identify factors associated with internet use and self-reported past year use of the health plan’s patient portal and Web-based HIA resources by middle-aged adults (aged 45 to 65 years; n=5520), younger seniors (aged 65 to 75 years; n=3014), and older seniors (aged 76 to 85 years; n=2389).

Results

Although approximately 96% of middle-aged adults, 92% of younger seniors, and 76% of older seniors use the internet to obtain information, about 4%, 9%, and 16%, respectively, require someone’s help to do so. The percentages who used the patient portal and Web-based HIA resources were similar for middle-aged adults and younger seniors but lower among older seniors (59.6%, 61.4%, and 45.0% and 47.9%, 48.4%, and 37.5%, respectively). Disparities in use of the internet, patient portal, and Web-based HIA across levels of education and between low and higher income were observed in all age groups, with wider disparities between low and high levels of education and income among seniors. Multivariable analyses showed that for all 3 age groups, educational attainment, ability to use the internet without help, and having 1 or more chronic condition were significant predictors of patient portal and Web-based HIA use after controlling for gender, race/ethnicity, and internet use.

Conclusions

Internet use, and especially use without help, significantly declines with age, even within a middle-aged group. Educational attainment is significantly associated with internet use, ability to use the internet without help, and use of patient portal and Web-based HIA resources by middle-aged and older adults. Even among middle-aged and older adult internet users, higher educational attainment and ability to use the internet without help are positively associated with patient portal and Web-based HIA use. Organizations serving middle-aged and older adults should take into account target population characteristics when developing and evaluating uptake of eHealth resources and should consider offering instruction and support services to boost patient engagement.

Kick.it: The development of an evidence-based smoking cessation smartphone app

Currently, the evidence for mobile health (mHealth) smoking cessation interventions is limited and heterogeneous, warranting the need for innovative rigorously developed solutions. The aim of this study was to describe the development of a smoking cessation smartphone application (app) developed using evidence-based principles. The app (Kick.it) was designed using the Intervention Mapping framework, incorporating an extensive literature review and qualitative study, in combination with the Behavioural Change Taxonomy v1, the Theoretical Domains Framework, and the Persuasive System Design framework. Kick.it provides quit smoking education, skills training, motivational content and self-regulation functionality for smokers, as well as their social support network. By logging cravings and cigarettes smoked, users will create their own smoking profile, which will be used to provide tailored interventions. It hosts a social network to allow 24/7 social support and provides in-app tools to help with urges to smoke. The app aims to motivate smokers to retry if they slip-up or relapse, allowing them to learn from previous smoking cessation attempts. Rather than basing the app on a singular behavioral change approach, Kick.it will use elements stemming from a variety of behavioral approaches by combining methods of multiple psychological theories. The use of best-practice intervention development frameworks in conjunction with evidence-based behavioral change techniques is expected to result in a smartphone app that has an optimal chance of helping people to quit smoking.

Social media for health promotion and weight management: a critical debate

Background

In 2016 an estimated 1.9 billion adults world-wide were either overweight or obese. The health consequences of obesity are responsible for 2.8 million preventable deaths per year. The WHO now considers obesity as a global epidemic and recommends population-wide health promotion strategies to address this issue. Weight gain is caused by increased energy intake and physical inactivity, so treatment should focus on changes to behaviour regarding diet and physical activity.

Discussion

The WHO has also recognised the importance of social resources as a valuable agent for behaviour change in health promotion. Social resources are translated at the community level as support provided by significant others such as family, partners and peers, in the form of information, material aid and encouragement. Social support has been shown to improve health and well-being, whereas social isolation has been shown to have a negative impact on health outcomes. Social support provided by peers has been shown to be a useful strategy to employ in weight management programmes. The documented increased use of ICT and social media has presented health promoters with a potentially useful medium to increase social support for weight management.

Conclusion

While the use of social media for health promotion is an emerging field of investigation, preliminary research suggests that it increases participant engagement, and may provide a cost-effective tool to provide social support for individuals participating in weight management programmes. With stringent privacy protocols in place, social media may be a useful, cost-effective accompaniment to multifactorial weight management programmes. However more research is needed to identify how to make the best use of social media as health promotion tool.

Investigating Patterns of Participation in an Online Support Group for Problem Drinking: a Social Network Analysis

PURPOSE

This study contributes to emerging literature on online health networks by modeling communication patterns between members of a moderated online support group for problem drinking. Using social network analysis, we described members' patterns of joint participation in threads, parsing out the role of site moderators, and explored differences in member characteristics by network position.

METHODS

Posts made to the online support group of Alcohol Help Centre during 2013 were structured as a two-mode network of members (n = 205) connected via threads (n = 506). Metrics included degree centrality, clique membership, and tie strength.

RESULTS

The network consisted of one component and no cliques of members, although most made few posts and a small number communicated only with the site's moderators. Highly active members were older and tended to have started posting prior to 2013. The distribution of members across threads varied from threads containing posts by one member to others that connected multiple members. Moderators accounted for sizable proportions of the connectivity between both members and threads.

CONCLUSIONS

After 5 years of operation, the AHC online support group appears to be fairly cohesive and stable, in the sense that there were no isolated subnetworks comprised of specific types of members or devoted to specific topics. Participation and connectedness at the member-level was varied, however, and tended to be low on average. The moderators were among the most central in the network, although there were also members who emerged as central and dedicated contributors to the online discussions across topics. Study findings highlight a number of areas for consideration by online support group developers and managers.

Share2Quit: Online Social Network Peer Marketing of Tobacco Cessation Systems

Introduction

Although technology-assisted tobacco interventions (TATIs) are effective, they are underused due to recruitment challenges. We tested whether we could successfully recruit smokers to a TATI using peer marketing through a social network (Facebook).

Methods

We recruited smokers on Facebook using online advertisements. These recruited smokers (seeds) and subsequent waves of smokers (peer recruits) were provided the Share2Quit peer recruitment Facebook app and other tools. Smokers were incentivized for up to seven successful peer recruitments and had 30 days to recruit from date of registration. Successful peer recruitment was defined as a peer recruited smoker completing the registration on the TATI following a referral. Our primary questions were (1) whether smokers would recruit other smokers and (2) whether peer recruitment would extend the reach of the intervention to harder-to-reach groups, including those not ready to quit and minority smokers.

Results

Overall, 759 smokers were recruited (seeds: 190; peer recruits: 569). Fifteen percent (n = 117) of smokers successfully recruited their peers (seeds: 24.7%; peer recruits: 7.7%) leading to four recruitment waves. Compared to seeds, peer recruits were less likely to be ready to quit (peer recruits 74.2% vs. seeds 95.1%), more likely to be male (67.1% vs. 32.9%), and more likely to be African American (23.8% vs. 10.8%) (p < .01 for all comparisons).

Conclusions

Peer marketing quadrupled our engaged smokers and enriched the sample with not-ready-to-quit and African American smokers. Peer recruitment is promising, and our study uncovered several important challenges for future research.

Implications

This study demonstrates the successful recruitment of smokers to a TATI using a Facebook-based peer marketing strategy. Smokers on Facebook were willing and able to recruit other smokers to a TATI, yielding a large and diverse population of smokers.

A prospective examination of online social network dynamics and smoking cessation

Introduction

Use of online social networks for smoking cessation has been associated with abstinence. Little is known about the mechanisms through which the formation of social ties in an online network may influence smoking behavior. Using dynamic social network analysis, we investigated how temporal changes of an individual’s number of social network ties are prospectively related to abstinence in an online social network for cessation. In a network where quitting is normative and is the focus of communications among members, we predicted that an increasing number of ties would be positively associated with abstinence.

Method

Participants were N = 2,657 adult smokers recruited to a randomized cessation treatment trial following enrollment on BecomeAnEX.org, a longstanding Internet cessation program with a large and mature online social network. At 3-months post-randomization, 30-day point prevalence abstinence was assessed and website engagement metrics were extracted. The social network was constructed with clickstream data to capture the flow of information among members. Two network centrality metrics were calculated at weekly intervals over 3 months: 1) in-degree, defined as the number of members whose posts a participant read; and 2) out-degree-aware, defined as the number of members who read a participant’s post and commented, which was subsequently viewed by the participant. Three groups of users were identified based on social network engagement patterns: non-users (N = 1,362), passive users (N = 812), and active users (N = 483). Logistic regression modeled 3-month abstinence by group as a function of baseline variables, website utilization, and network centrality metrics.

Results

Abstinence rates varied by group (non-users = 7.7%, passive users = 10.7%, active users = 20.7%). Significant baseline predictors of abstinence were age, nicotine dependence, confidence to quit, and smoking temptations in social situations among passive users (ps < .05); age and confidence to quit among active users. Among centrality metrics, positive associations with abstinence were observed for in-degree increases from Week 2 to Week 12 among passive and active users, and for out-degree-aware increases from Week 2 to Week 12 among active users (ps < .05).

Conclusions

This study is the first to demonstrate that increased tie formation among members of an online social network for smoking cessation is prospectively associated with abstinence. It also highlights the value of using individuals’ activities in online social networks to predict their offline health behaviors.

Linking smokers to a quitline: randomized controlled effectiveness trial of a support person intervention that targets non-smokers

Evidence-based treatments (e.g. quitlines) are greatly underutilized by smokers limiting their public health impact. A three-session phone intervention for nonsmoking family members and friends (i.e. support persons) was successful for increasing smoker quitline enrollment. To enhance the intervention's potential translatability, in this study, we delivered treatment for the non-smoker within ongoing quitline services and compared the efficacy of the three-call intervention to a streamlined version (one call). A total of 704 adult non-smokers (85% female, 95% White) wanting to help a smoker quit and recruited statewide in Minnesota participated in this randomized controlled trial with parallel groups. Non-smokers received mailed written materials and were randomly assigned to a control condition (no additional treatment, n = 235), or to a one- (n = 233) or three-call (n = 236) intervention delivered by quitline coaches. The main outcome was smoker quitline enrollment through 7-month follow-up. Smoker quitline enrollment was similar for those linked to non-smokers in the one- and three-call interventions (14.6% [34/233] and 14.8% [35/236]), and higher than for smokers linked to control participants (6.4% [15/235]), P = 0.006. Just one quitline coaching call delivered to non-smokers increased treatment enrollment among smokers. The reach of quitlines could be enhanced by targeting the social support network of smokers.

Online Smoking Cessation Advertising and Young Pacific Smokers in New Zealand

Introduction: Social media advertising could be effective in promoting smoking cessation. However, it's salience to Pacific youth in New Zealand who smoke is unknown.

Aim: To explore the views that 18–25 year old Pacific smokers have towards online smoking cessation advertising.

Methods: Twenty young Pacific smokers, aged 18–25 years, were recruited through indirect snowballing methods interviewed in focus groups by a female Pacific researcher. Questions centred on smoking cessation advice via social media and devices, preferences for advertisements, effective features and implications for internet banner and ad designs, positive versus negative framing, cultural cues and motivations. The general inductive approach was used to analyse the data for common themes.

Results: Smartphones were the most common device and Facebook the social media site most often used by participants. The informants recommended that the advertisements should have the following features: central position, eye-catching, bold imagery using simple language; endorsed by Pacific Island personalities; and positively framed messages to secure and maintain interest. The collective nature of Pacific cultures should be leveraged and testimonies from previous smokers used to strengthen motivation and dispel common myths around smoking.

Conclusion: There are potential opportunities for social media to be used as a platform to promote smoking cessation among Pacific young people.

Social media in epilepsy: A quantitative and qualitative analysis

BACKGROUND

While the social burden of epilepsy has been extensively studied, an evaluation of social media related to epilepsy may provide novel insight into disease perception, patient needs and access to treatments. The objective of this study is to assess patterns in social media and online communication usage related to epilepsy and its associated topics.

METHODS

We searched two major social media platforms (Facebook and Twitter) for public accounts dedicated to epilepsy. Results were analyzed using qualitative and quantitative methodologies. The former involved thematic and word count analysis for online posts and tweets on these platforms, while the latter employed descriptive statistics and non-parametric tests.

RESULTS

Facebook had a higher number of pages (840 accounts) and users (3 million) compared to Twitter (137 accounts and 274,663 users). Foundation and support groups comprised most of the accounts and users on both Facebook and Twitter. The number of accounts increased by 100% from 2012 to 2016. Among the 403 posts and tweets analyzed, "providing information" on medications or correcting common misconceptions in epilepsy was the most common theme (48%). Surgical interventions for epilepsy were only mentioned in 1% of all posts and tweets.

CONCLUSIONS

The current study provides a comprehensive reference on the usage of social media in epilepsy. The number of online users interested in epilepsy is likely the highest among all neurological conditions. Surgery, as a method of treating refractory epilepsy, however, could be underrepresented on social media.

Improving Adherence to Smoking Cessation Treatment: Intervention Effects in a Web-Based Randomized Trial

BACKGROUND

Web-based smoking cessation interventions can deliver evidence-based treatments to a wide swath of the population, but effectiveness is often limited by insufficient adherence to proven treatment components. This study evaluated the impact of a social network (SN) intervention and free nicotine replacement therapy (NRT) on adherence to evidence-based components of smoking cessation treatment in the context of a Web-based intervention.

METHODS

A sample of adult U.S. smokers (N = 5290) was recruited via BecomeAnEX.org, a free smoking cessation Web site. Smokers were randomized to one of four arms: (1) an interactive, evidence-based smoking cessation Web site (WEB) alone; (2) WEB in conjunction with an SN intervention designed to integrate participants into the online community (WEB+SN); (3) WEB plus free NRT (WEB+NRT); and (4) the combination of all treatments (WEB+SN+NRT). Adherence outcomes assessed at 3-month follow-up were as follows: Web site utilization metrics, use of skills training components, intratreatment social support, and pharmacotherapy use.

RESULTS

WEB+SN+NRT outperformed all others on Web site utilization metrics, use of practical counseling tools, intratreatment social support, and NRT use. It was the only intervention to promote the sending of private messages and the viewing of community pages over WEB alone. Both social network arms outperformed WEB on most metrics of online community engagement. Both NRT arms showed higher medication use compared to WEB alone.

CONCLUSIONS

This study demonstrated the effectiveness of two approaches for improving adherence to evidence-based components of smoking cessation treatment. Integrated approaches to medication provision and social network engagement can enhance adherence to components known to improve cessation.

IMPLICATIONS

This study demonstrated that an integrated approach to medication provision and social network integration, when delivered through an online program, can enhance adherence across all three recommended components of an evidence-based smoking cessation program (skills training, social support, and pharmacotherapy use). Nicotine replacement therapy-when provided as part of an integrated program-increases adherence to other program elements, which in turn augment its own therapeutic effects. An explicit focus on approaches to improve treatment adherence is an important first step to identifying leverage points for optimizing intervention effectiveness.

Demographic and Indication-Specific Characteristics Have Limited Association With Social Network Engagement: Evidence From 24,954 Members of Four Health Care Support Groups

Background

Digital health social networks (DHSNs) are widespread, and the consensus is that they contribute to wellness by offering social support and knowledge sharing. The success of a DHSN is based on the number of participants and their consistent creation of externalities through the generation of new content. To promote network growth, it would be helpful to identify characteristics of superusers or actors who create value by generating positive network externalities.

Objective

The aim of the study was to investigate the feasibility of developing predictive models that identify potential superusers in real time. This study examined associations between posting behavior, 4 demographic variables, and 20 indication-specific variables.

Methods

Data were extracted from the custom structured query language (SQL) databases of 4 digital health behavior change interventions with DHSNs. Of these, 2 were designed to assist in the treatment of addictions (problem drinking and smoking cessation), and 2 for mental health (depressive disorder, panic disorder). To analyze posting behavior, 10 models were developed, and negative binomial regressions were conducted to examine associations between number of posts, and demographic and indication-specific variables.

Results

The DHSNs varied in number of days active (3658-5210), number of registrants (5049-52,396), number of actors (1085-8452), and number of posts (16,231-521,997). In the sample, all 10 models had low R² values (.013-.086) with limited statistically significant demographic and indication-specific variables.

Conclusions

Very few variables were associated with social network engagement. Although some variables were statistically significant, they did not appear to be practically significant. Based on the large number of study participants, variation in DHSN theme, and extensive time-period, we did not find strong evidence that demographic characteristics or indication severity sufficiently explain the variability in number of posts per actor. Researchers should investigate alternative models that identify superusers or other individuals who create social network externalities.

Content-specific network analysis of peer-to-peer communication in an online community for smoking cessation

Analysis of user interactions in online communities could improve our understanding of health-related behaviors and inform the design of technological solutions that support behavior change. However, to achieve this we would need methods that provide granular perspective, yet are scalable. In this paper, we present a methodology for high-throughput semantic and network analysis of large social media datasets, combining semi-automated text categorization with social network analytics. We apply this method to derive content-specific network visualizations of 16,492 user interactions in an online community for smoking cessation. Performance of the categorization system was reasonable (average F-measure of 0.74, with system-rater reliability approaching rater-rater reliability). The resulting semantically specific network analysis of user interactions reveals content- and behavior-specific network topologies. Implications for socio-behavioral health and wellness platforms are also discussed.

OPREVENT2: Design of a multi-institutional intervention for obesity control and prevention for American Indian adults

Background

Obesity and other nutrition-related chronic disease rates are high in American Indian (AI) populations, and an urgent need exists to identify evidence-based strategies for prevention and treatment. Multi-level, multi-component (MLMC) interventions are needed, but there are significant knowledge gaps on how to deliver these types of interventions in low-income rural AI communities.

Methods

OPREVENT2 is a MLMC intervention targeting AI adults living in six rural reservations in New Mexico and Wisconsin. Aiming to prevent and reduce obesity in adults by working at multiple levels of the food and physical activity (PA) environments, OPREVENT2 focuses on evidence-based strategies known to increase access to, demand for, and consumption of healthier foods and beverages, and increase worksite and home-based opportunities for PA. OPREVENT2 works to create systems-level change by partnering with tribal stakeholders, multiple levels of the food and PA environment (food stores, worksites, schools), and the social environment (children as change agents, families, social media). Extensive evaluation will be conducted at each level of the intervention to assess effectiveness via process and impact measures.

Discussion

Novel aspects of OPREVENT2 include: active engagement with stakeholders at many levels (policy, institutional, and at multiple levels of the food and PA system); use of community-based strategies to engage policymakers and other key stakeholders (community workshops, action committees); emphasis on both the built environment (intervening with retail food sources) and the social environment. This paper describes the design of the intervention and the evaluation plan of the OPREVENT2.

Trial registration

Clinical Trial Registration: NCT02803853 (June 10, 2016)

Online tobacco websites and online communities-who uses them and do users quit smoking? The quit-primo and national dental practice-based research network Hi-Quit studies

Online tobacco cessation communities are beneficial but underused. Our study examined whether, among smokers participating in a web-assisted tobacco intervention (Decide2quit.org), specific characteristics were associated with navigating to BecomeAnEx.org, an online cessation community, and with subsequent quit rates. Among smokers (N = 759) registered with Decide2quit.org, we identified visitors to BecomeAnEx.org, examining associations between smoker characteristics and likelihood of visiting. We then tested for associations between visits and 6-month cessation (point prevalence). We also tested for an interaction between use of other online support-seeking (Decide2quit.org tobacco cessation coaches), visiting, and 6-month cessation. One quarter (26.0 %; n = 197) of the smokers visited BecomeAnEx.org; less than one tenth (7.5 %; n = 57) registered to participate in the online forum. Visitors were more likely to be female (73.0 vs. 62.6 % of non-visitors, P < 0.01) to have visited a cessation website before (33.0 vs. 17.4 %, P < 0.01) and to report quit attempts in the previous year (62.0 vs. 53.0 %, P = 0.03). In analyses of all participants, BecomeAnEx.org visiting was not associated with 6-month quit completion. Among participants who communicated with a coach, BecomeAnEx.org visiting also lacked a significant association with 6 month quit completion, although a non-significant trend toward quit completion in visitors was noted (OR 2.21, 95 % CI 0.81-3.1). Online cessation communities attract smokers with previous cessation website experience and recent quit attempts. Community visiting was not associated with quit rates in our study, but low use may have limited our power to detect differences. Further research should explore whether an additive effect can be achieved by offering community visitors support via online coaches.

Employing the Gini coefficient to measure participation inequality in treatment-focused Digital Health Social Networks

Digital Health Social Networks (DHSNs) are common; however, there are few metrics that can be used to identify participation inequality. The objective of this study was to investigate whether the Gini coefficient, an economic measure of statistical dispersion traditionally used to measure income inequality, could be employed to measure DHSN inequality. Quarterly Gini coefficients were derived from four long-standing DHSNs. The combined data set included 625,736 posts that were generated from 15,181 actors over 18,671 days. The range of actors (8-2323), posts (29-28,684), and Gini coefficients (0.15-0.37) varied. Pearson correlations indicated statistically significant associations between number of actors and number of posts (0.527-0.835, p < .001), and Gini coefficients and number of posts (0.342-0.725, p < .001). However, the association between Gini coefficient and number of actors was only statistically significant for the addiction networks (0.619 and 0.276, p < .036). Linear regression models had positive but mixed R2 results (0.333-0.527). In all four regression models, the association between Gini coefficient and posts was statistically significant (t = 3.346-7.381, p < .002). However, unlike the Pearson correlations, the association between Gini coefficient and number of actors was only statistically significant in the two mental health networks (t = -4.305 and -5.934, p < .000). The Gini coefficient is helpful in measuring shifts in DHSN inequality. However, as a standalone metric, the Gini coefficient does not indicate optimal numbers or ratios of actors to posts, or effective network engagement. Further, mixed-methods research investigating quantitative performance metrics is required.

Prioritizing the mHealth Design Space: A Mixed-Methods Analysis of Smokers' Perspectives

Background

Smoking remains the leading cause of preventable disease and death in the United States. Therefore, researchers are constantly exploring new ways to promote smoking cessation. Mobile health (mHealth) technologies could be effective cessation tools. Despite the availability of commercial quit-smoking apps, little research to date has examined smokers’ preferred treatment intervention components (ie, design features). Honoring these preferences is important for designing programs that are appealing to smokers and may be more likely to be adopted and used.

Objective

The aim of this study was to understand smokers’ preferred design features of mHealth quit-smoking tools.

Methods

We used a mixed-methods approach consisting of focus groups and written surveys to understand the design preferences of adult smokers who were interested in quitting smoking (N=40). Focus groups were stratified by age to allow differing perspectives to emerge between older (>40 years) and younger (<40 years) participants. Focus group discussion included a “blue-sky” brainstorming exercise followed by participant reactions to contrasting design options for communicating with smokers, providing social support, and incentivizing program use. Participants rated the importance of preselected design features on an exit survey. Qualitative analyses examined emergent discussion themes and quantitative analyses compared feature ratings to determine which were perceived as most important.

Results

Participants preferred a highly personalized and adaptive mHealth experience. Their ideal mHealth quit-smoking tool would allow personalized tracking of their progress, adaptively tailored feedback, and real-time peer support to help manage smoking cravings. Based on qualitative analysis of focus group discussion, participants preferred pull messages (ie, delivered upon request) over push messages (ie, sent automatically) and preferred interaction with other smokers through closed social networks. Preferences for entertaining games or other rewarding incentives to encourage program use differed by age group. Based on quantitative analysis of surveys, participants rated the importance of select design features significantly differently (P<.001). Design features rated as most important included personalized content, the ability to track one’s progress, and features designed to help manage nicotine withdrawal and medication side effects. Design features rated least important were quit-smoking videos and posting on social media. Communicating with stop-smoking experts was rated more important than communicating with family and friends about quitting (P=.03). Perceived importance of various design features varied by age, experience with technology, and frequency of smoking.

Conclusions

Future mHealth cessation aids should be designed with an understanding of smokers’ needs and preferences for these tools. Doing so does not guarantee treatment effectiveness, but balancing user preferences with best-practice treatment considerations could enhance program adoption and improve treatment outcomes. Grounded in the perspectives of smokers, we identify several design considerations, which should be prioritized when designing future mHealth cessation tools and which warrant additional empirical validation.

Behavior change interventions: the potential of ontologies for advancing science and practice

A central goal of behavioral medicine is the creation of evidence-based interventions for promoting behavior change. Scientific knowledge about behavior change could be more effectively accumulated using "ontologies." In information science, an ontology is a systematic method for articulating a "controlled vocabulary" of agreed-upon terms and their inter-relationships. It involves three core elements: (1) a controlled vocabulary specifying and defining existing classes; (2) specification of the inter-relationships between classes; and (3) codification in a computer-readable format to enable knowledge generation, organization, reuse, integration, and analysis. This paper introduces ontologies, provides a review of current efforts to create ontologies related to behavior change interventions and suggests future work. This paper was written by behavioral medicine and information science experts and was developed in partnership between the Society of Behavioral Medicine's Technology Special Interest Group (SIG) and the Theories and Techniques of Behavior Change Interventions SIG. In recent years significant progress has been made in the foundational work needed to develop ontologies of behavior change. Ontologies of behavior change could facilitate a transformation of behavioral science from a field in which data from different experiments are siloed into one in which data across experiments could be compared and/or integrated. This could facilitate new approaches to hypothesis generation and knowledge discovery in behavioral science.

Use of an online smoking cessation community promotes abstinence: Results of propensity score weighting

OBJECTIVE

We estimated the causal effects of use of an online smoking cessation community on 30-day point prevalence abstinence at 3 months.

METHODS

Participants (N = 492) were adult current smokers in the enhanced Internet arm of The iQUITT Study, a randomized trial of Internet and telephone treatment for smoking cessation. All participants accessed a Web-based smoking-cessation program that included a large, established online community. Automated tracking metrics of passive (e.g., reading forum posts, viewing member profiles) and active (e.g., writing forum posts, sending private messages) community use were extracted from the site at 3 months. Self-selected community use defines the groups of interest: "None," "Passive," and "Both" (passive + active). Inverse probability of treatment weighting corrected for baseline imbalances on demographic, smoking, psychosocial, and medical history variables. Propensity weights estimated via generalized boosted models were used to calculate Average Treatment Effects (ATE) and Average Treatment effects on the Treated (ATT).

RESULTS

Patterns of community use were: None = 198 (40.2%), Passive = 110 (22.4%), and Both = 184 (37.4%). ATE-weighted abstinence rates were: None = 4.2% (95% CI = 1.5-6.9); Passive = 15.1% (95% CI = 8.4-21.9); Both = 20.4% (95% CI = 13.9-26.8). ATT-weighted abstinence rates indicated even greater benefits of community use.

CONCLUSIONS

Community users were more likely to quit smoking at 3 months than nonusers. The estimated benefit from use of online community resources was even larger among subjects with high propensity to use them. No differences in abstinence emerged between passive and passive/active users. Results suggest that lurking in online communities confers specific abstinence benefits. Implications of these findings for online cessation communities are discussed.

Mining Twitter to Assess the Public Perception of the "Internet of Things"

Social media analysis has shown tremendous potential to understand public's opinion on a wide variety of topics. In this paper, we have mined Twitter to understand the public's perception of the Internet of Things (IoT). We first generated the discussion trends of the IoT from multiple Twitter data sources and validated these trends with Google Trends. We then performed sentiment analysis to gain insights of the public's attitude towards the IoT. As anticipated, our analysis indicates that the public's perception of the IoT is predominantly positive. Further, through topic modeling, we learned that public tweets discussing the IoT were often focused on business and technology. However, the public has great concerns about privacy and security issues toward the IoT based on the frequent appearance of related terms. Nevertheless, no unexpected perceptions were identified through our analysis. Our analysis was challenged by the limited fraction of tweets relevant to our study. Also, the user demographics of Twitter users may not be strongly representative of the population of the general public.

Smoking Prevention in China: A Content Analysis of an Anti-Smoking Social Media Campaign

The China Tobacco Control Media Campaign on Sina Weibo is novel in the context of smoking prevention and cessation in China and has not to date been evaluated. This study draws on health behavior theories and dialogic theory in public relations to analyze microblog campaign postings and their relationships with the outcome of online audience engagement. Microblog postings from May 2011 to January 2015 were content analyzed, showing that the most common persuasive content characteristic was perceived risk, followed by subjective norms and self-efficacy. Perceived risk and self-efficacy postings positively influenced online audience engagement, whereas subjective norm postings was a nonsignificant predictor. Postings were more likely to share information than aim to interact with audience members. However, both information sharing and audience interaction postings were positive predictors of online audience engagement. There was also evidence of main and interactive effects of message originality on online audience engagement. The current study has, to the best of our knowledge, broken new ground in 2 regards: (a) using health behavior theories as a basis for analyzing the content of an anti-smoking social media campaign and (b) examining the content of an anti-smoking media campaign of any type in China.

Relationship of Autonomy Social Support to Quitting Motivation in Diverse Smokers

BACKGROUND

Research examining relationships between social support and smoking cessation has paid little attention to non-treatment seeking smokers and not considered the role of autonomy support for fostering quitting motivation. This study examined if autonomy support received from family and friends was associated with quitting motivation and making a quit attempt among diverse smokers with varying levels of quitting motivation. Demographic characteristics associated with autonomy support were explored.

METHODS

Participants (N=312) responded to advertisements seeking smokers "not quite ready to quit," and were primarily Black, low-income, and unemployed. Most (255) enrolled in a clinical trial of smoking cessation induction strategies (treatment sample). An additional 57 not meeting the trial eligibility criteria of low quitting motivation enrolled for baseline assessments only. Participants completed baseline measures of autonomy support received from friends and autonomous quitting motivation. In the treatment sample, quit attempts were assessed at 6-months follow-up.

RESULTS

Females reported higher levels than males of autonomy support from friends (p=0.003). Participants with a high school diploma/GED reported higher levels of support from family (p<0.001) and friends (p=0.014) than those with less education or a college/graduate degree. Both family (p=0.007) and friend (p=0.004) autonomy support scores were significantly, albeit weakly, associated with autonomous quitting motivation. Autonomy support was not associated with making a quit attempt.

CONCLUSIONS

Support from family and friends may promote autonomous reasons to quit among diverse smokers. Research is needed to assess the role of social support in the pre-quitting phases among racial and socio-economically diverse populations.

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.

VisOHC: Designing Visual Analytics for Online Health Communities

Through online health communities (OHCs), patients and caregivers exchange their illness experiences and strategies for overcoming the illness, and provide emotional support. To facilitate healthy and lively conversations in these communities, their members should be continuously monitored and nurtured by OHC administrators. The main challenge of OHC administrators' tasks lies in understanding the diverse dimensions of conversation threads that lead to productive discussions in their communities. In this paper, we present a design study in which three domain expert groups participated, an OHC researcher and two OHC administrators of online health communities, which was conducted to find with a visual analytic solution. Through our design study, we characterized the domain goals of OHC administrators and derived tasks to achieve these goals. As a result of this study, we propose a system called VisOHC, which visualizes individual OHC conversation threads as collapsed boxes-a visual metaphor of conversation threads. In addition, we augmented the posters' reply authorship network with marks and/or beams to show conversation dynamics within threads. We also developed unique measures tailored to the characteristics of OHCs, which can be encoded for thread visualizations at the users' requests. Our observation of the two administrators while using VisOHC showed that it supports their tasks and reveals interesting insights into online health communities. Finally, we share our methodological lessons on probing visual designs together with domain experts by allowing them to freely encode measurements into visual variables.

What Online Communities Can Tell Us About Electronic Cigarettes and Hookah Use: A Study Using Text Mining and Visualization Techniques

BACKGROUND

The rise in popularity of electronic cigarettes (e-cigarettes) and hookah over recent years has been accompanied by some confusion and uncertainty regarding the development of an appropriate regulatory response towards these emerging products. Mining online discussion content can lead to insights into people's experiences, which can in turn further our knowledge of how to address potential health implications. In this work, we take a novel approach to understanding the use and appeal of these emerging products by applying text mining techniques to compare consumer experiences across discussion forums.

OBJECTIVE

This study examined content from the websites Vapor Talk, Hookah Forum, and Reddit to understand people's experiences with different tobacco products. Our investigation involves three parts. First, we identified contextual factors that inform our understanding of tobacco use behaviors, such as setting, time, social relationships, and sensory experience, and compared the forums to identify the ones where content on these factors is most common. Second, we compared how the tobacco use experience differs with combustible cigarettes and e-cigarettes. Third, we investigated differences between e-cigarette and hookah use.

METHODS

In the first part of our study, we employed a lexicon-based extraction approach to estimate prevalence of contextual factors, and then we generated a heat map based on these estimates to compare the forums. In the second and third parts of the study, we employed a text mining technique called topic modeling to identify important topics and then developed a visualization, Topic Bars, to compare topic coverage across forums.

RESULTS

In the first part of the study, we identified two forums, Vapor Talk Health & Safety and the Stopsmoking subreddit, where discussion concerning contextual factors was particularly common. The second part showed that the discussion in Vapor Talk Health & Safety focused on symptoms and comparisons of combustible cigarettes and e-cigarettes, and the Stopsmoking subreddit focused on psychological aspects of quitting. Last, we examined the discussion content on Vapor Talk and Hookah Forum. Prominent topics included equipment, technique, experiential elements of use, and the buying and selling of equipment.

CONCLUSIONS

This study has three main contributions. Discussion forums differ in the extent to which their content may help us understand behaviors with potential health implications. Identifying dimensions of interest and using a heat map visualization to compare across forums can be helpful for identifying forums with the greatest density of health information. Additionally, our work has shown that the quitting experience can potentially be very different depending on whether or not e-cigarettes are used. Finally, e-cigarette and hookah forums are similar in that members represent a "hobbyist culture" that actively engages in information exchange. These differences have important implications for both tobacco regulation and smoking cessation intervention design.

Prevalence and Frequency of mHealth and eHealth Use Among US and UK Smokers and Differences by Motivation to Quit

BACKGROUND

Both mHealth and eHealth interventions for smoking cessation are rapidly being developed and tested. There are no data on use of mHealth and eHealth technologies by smokers in general or by smokers who are not motivated to quit smoking.

OBJECTIVE

The aims of our study were to (1) assess technology use (eg, texting, social media, Internet) among smokers in the United States and United Kingdom, (2) examine whether technology use differs between smokers who are motivated to quit and smokers who are not motivated to quit, (3) examine previous use of technology to assist with smoking cessation, and (4) examine future intentions to use technology to assist with smoking cessation.

METHODS

Participants were 1000 adult smokers (54.90%, 549/1000 female; mean age 43.9, SD 15.5 years; US: n=500, UK: n=500) who were recruited via online representative sampling strategies. Data were collected online and included demographics, smoking history, and frequency and patterns of technology use.

RESULTS

Among smokers in general, there was a high prevalence of mobile and smartphone ownership, sending and receiving texts, downloading and using apps, using Facebook, and visiting health-related websites. Smokers who were unmotivated to quit were significantly less likely to own a smartphone or handheld device that connects to the Internet than smokers motivated to quit. There was a significantly lower prevalence of sending text messages among US smokers unmotivated to quit (78.2%, 179/229) versus smokers motivated to quit (95.0%, 229/241), but no significant differences between the UK groups (motivated: 96.4%, 239/248; unmotivated: 94.9%, 223/235). Smokers unmotivated to quit in both countries were significantly less likely to use a handheld device to read email, play games, browse the Web, or visit health-related websites versus smokers motivated to quit. US smokers had a high prevalence of app downloads regardless of motivation to quit, but UK smokers who were motivated to quit had greater prevalence of app downloads than smokers unmotivated to quit. US smokers were significantly more likely to have a Facebook account (87.0%, 435/500) than UK smokers (76.4%, 382/500), but smokers unmotivated to quit in both countries used Facebook less frequently than smokers motivated to quit. Smokers who were unmotivated to quit were less likely to have used eHealth or mHealth platforms to help them quit smoking in the past and less likely to say that they would use them for smoking cessation in the future.

CONCLUSIONS

Although smokers unmotivated to quit make less use of technology than smokers motivated to quit, there is sufficient prevalence to make it worthwhile to develop eHealth and mHealth interventions to encourage cessation. Short and low-effort communications, such as text messaging, might be better for smokers who are less motivated to quit. Multiple channels may be required to reach unmotivated smokers.

Effect of a Digital Social Media Campaign on Young Adult Smoking Cessation

INTRODUCTION

Social media (SM) may extend the reach and impact for smoking cessation among young adult smokers. To-date, little research targeting young adults has been done on the use of SM to promote quitting smoking. We assessed the effect of an innovative multicomponent web-based and SM approach known as Break-it-Off (BIO) on young adult smoking cessation.

METHODS

The study employed a quasi-experimental design with baseline and 3-month follow-up data from 19 to 29-year old smokers exposed to BIO (n = 102 at follow-up) and a comparison group of Smokers' Helpline (SHL) users (n = 136 at follow-up). Logistic regression analysis assessed differences between groups on self-reported 7-day and 30-day point prevalence cessation rates, adjusting for ethnicity, education level, and cigarette use (daily or occasional) at baseline.

RESULTS

The campaign reached 37 325 unique visitors with a total of 44 172 visits. BIO users had significantly higher 7-day and 30-day quit rates compared with users of SHL. At 3-month follow-up, BIO participants (32.4%) were more likely than SHL participants (14%) to have quit smoking for 30 days (odds ratio = 2.95, 95% CI = 1.56 to 5.57, P < .001) and BIO participants (91%) were more likely than SHL participants (79%) to have made a quit attempt (odds ratio = 2.69, 95% CI = 1.03 to 6.99, P = .04).

CONCLUSION

The reach of the campaign and findings on quitting success indicate that a digital/SM platform can complement the traditional SHL cessation service for young adult smokers seeking help to quit.

Content-driven analysis of an online community for smoking cessation: integration of qualitative techniques, automated text analysis, and affiliation networks

OBJECTIVES

We identified content-specific patterns of network diffusion underlying smoking cessation in the context of online platforms, with the aim of generating targeted intervention strategies.

METHODS

QuitNet is an online social network for smoking cessation. We analyzed 16 492 de-identified peer-to-peer messages from 1423 members, posted between March 1 and April 30, 2007. Our mixed-methods approach comprised qualitative coding, automated text analysis, and affiliation network analysis to identify, visualize, and analyze content-specific communication patterns underlying smoking behavior.

RESULTS

Themes we identified in QuitNet messages included relapse, QuitNet-specific traditions, and cravings. QuitNet members who were exposed to other abstinent members by exchanging content related to interpersonal themes (e.g., social support, traditions, progress) tended to abstain. Themes found in other types of content did not show significant correlation with abstinence.

CONCLUSIONS

Modeling health-related affiliation networks through content-driven methods can enable the identification of specific content related to higher abstinence rates, which facilitates targeted health promotion.

E-mail to Promote Colorectal Cancer Screening Within Social Networks: Acceptability and Content

Effective techniques to encourage colorectal cancer screening in underscreened populations have included social support interventions and e-mail reminders from physicians. Personalized e-mail messages to promote colorectal cancer screening within social networks could be even more effective but have not been studied. The authors interviewed 387 e-mail users, aged 42-73 years in Georgia, Hawaii, and Massachusetts. Participants were asked to edit a sample message in which the sender shares a recent colonoscopy experience and urges the recipient to discuss colorectal cancer screening with a doctor. For those reporting willingness to send this message, changes to the message and suggested subject lines were recorded. Edited text was analyzed for content and concordance with original message. The majority of participants (74.4%) were willing to e-mail a modifiable message. Of those willing, 63.5% edited the message. Common edits included deletion (17.7%) or modification (17.4%) of a negatively framed sentence on colon cancer risks and addition or modification of personalizing words (15.6%). Few edits changed the meaning of the message (5.6%), and even fewer introduced factual inaccuracies (1.7%). Modifiable e-mail messages offer a way for screened individuals to promote colorectal cancer screening to social network members. The accuracy and effects of such messages should be further studied.

Information seeking regarding tobacco and lung cancer: effects of seasonality

This paper conducted one of the first comprehensive international Internet analyses of seasonal patterns in information seeking concerning tobacco and lung cancer. Search query data for the terms "tobacco" and "lung cancer" from January 2004 to January 2014 was collected from Google Trends. The relevant countries included the USA, Canada, the UK, Australia, and China. Two statistical approaches including periodogram and cross-correlation were applied to analyze seasonal patterns in the collected search trends and their associations. For these countries except China, four out of six cross-correlations of seasonal components of the search trends regarding tobacco were above 0.600. For these English-speaking countries, similar patterns existed in the data concerning lung cancer, and all cross-correlations between seasonal components of the search trends regarding tobacco and that regarding lung cancer were also above 0.700. Seasonal patterns widely exist in information seeking concerning tobacco and lung cancer on an international scale. The findings provide a piece of novel Internet-based evidence for the seasonality and health effects of tobacco use.

Picture Me Smokefree: a qualitative study using social media and digital photography to engage young adults in tobacco reduction and cessation

Background

Young adults have high rates of tobacco use compared to other subpopulations, yet there are relatively few tobacco interventions specifically targeted to this group. Picture Me Smokefree is an online tobacco reduction and cessation intervention for young adults that uses digital photography and social networking.

Objective

The main goal of the project was to determine the feasibility of engaging young adults in participating in user-driven, online forums intended to provide peer support and motivate critical reflection about tobacco use and cessation among this high-use, hard-to-reach population. A related aim was to explore the influence of gender-related factors on participation, in order to determine the need for online interventions to be tailored to the specific gender preferences reflecting young men and women’s participation styles.

Methods

A total of 60 young adults ages 19-24 years who self-identified as current cigarette smokers or who had quit within the last year were recruited from across British Columbia, Canada, and participated in an online photo group on Facebook over a period of 12 consecutive weeks. A variety of data collection methods were used including tracking online activity, a brief online follow-up survey, and qualitative interviews with study participants. Data analysis involved descriptive statistics on recruitment, retention, and participation and qualitative (eg, narrative analysis, synthesis of feedback) feedback about participant engagement.

Results

Findings from this study suggest good potential for Facebook as an accessible, low-cost platform for engaging young adults to reflect on the reasons for their tobacco use, the benefits of quitting or reducing, and the best strategies for tobacco reduction. Young adults’ frequent use of mobile phones and other mobile devices to access social networking permitted ease of access and facilitated real-time peer-to-peer support across a diverse group of participants. However, our experience of conducting the study suggests that working with young tobacco users can be accompanied by considerable recruitment, participation, and retention challenges. Our findings also pointed to differences in how young women and men engaged the photo-group intervention that should be considered, bearing in mind that in follow-up interviews participants indicated their preference for a mixed gender and “gender neutral” group format.

Conclusions

Tobacco interventions for youth and young adults should be embedded within the existing social networking platforms they access most frequently, rather than designing a stand-alone online prevention or intervention resource. This subpopulation would likely benefit from tobacco reduction interventions that are gender-sensitive rather than gender-specific.

An observational study of social and emotional support in smoking cessation Twitter accounts: content analysis of tweets

Background

Smoking continues to be the number one preventable cause of premature death in the United States. While evidence for the effectiveness of smoking cessation interventions has increased rapidly, questions remain on how to effectively disseminate these findings. Twitter, the second largest online social network, provides a natural way of disseminating information. Health communicators can use Twitter to inform smokers, provide social support, and attract them to other interventions. A key challenge for health researchers is how to frame their communications to maximize the engagement of smokers.

Objective

Our aim was to examine current Twitter activity for smoking cessation.

Methods

Active smoking cessation related Twitter accounts (N=18) were identified. Their 50 most recent tweets were content coded using a schema adapted from the Roter Interaction Analysis System (RIAS), a theory-based, validated coding method. Using negative binomial regression, the association of number of followers and frequency of individual tweet content at baseline was assessed. The difference in followership at 6 months (compared to baseline) to the frequency of tweet content was compared using linear regression. Both analyses were adjusted by account type (organizational or not organizational).

Results

The 18 accounts had 60,609 followers at baseline and 68,167 at 6 months. A total of 24% of tweets were socioemotional support (mean 11.8, SD 9.8), 14% (mean 7, SD 8.4) were encouraging/engagement, and 62% (mean 31.2, SD 15.2) were informational. At baseline, higher frequency of socioemotional support and encouraging/engaging tweets was significantly associated with higher number of followers (socioemotional: incident rate ratio [IRR] 1.09, 95% CI 1.02-1.20; encouraging/engaging: IRR 1.06, 95% CI 1.00-1.12). Conversely, higher frequency of informational tweets was significantly associated with lower number of followers (IRR 0.95, 95% CI 0.92-0.98). At 6 months, for every increase by 1 in socioemotional tweets, the change in followership significantly increased by 43.94 (P=.027); the association was slightly attenuated after adjusting by account type and was not significant (P=.064).

Conclusions

Smoking cessation activity does exist on Twitter. Preliminary findings suggest that certain content strategies can be used to encourage followership, and this needs to be further investigated.

The needs and preferences of pregnant smokers regarding tailored Internet-based smoking cessation interventions: a qualitative interview study

Background

Internet-based Smoking Cessation Interventions (ISCIs) may help pregnant smokers who are unable, or unwilling, to access face-to-face stop smoking support. Targeting ISCIs to specific groups of smokers could increase their uptake and effectiveness. The current study explored the needs and preferences of pregnant women seeking online stop smoking support with an aim to identify features and components of ISCIs that might be most attractive to this population.

Methods

We conducted qualitative interviews with thirteen pregnant women who completed the intervention arm of a pilot randomized controlled trial of a novel ISCI for pregnant smokers (‘MumsQuit’). The interviews explored women’s views towards MumsQuit and online support with quitting smoking in general, as well as their suggestions for how ISCIs could be best targeted to pregnancy. Interview transcripts were analyzed using Framework Analysis.

Results

Participants expressed preferences for an accessible, highly engaging and targeted to pregnancy smoking cessation website, tailored to individuals’ circumstances as well as use of cessation medication, offering comprehensive and novel information on smoking and quitting smoking in pregnancy, ongoing support with cravings management, as well as additional support following relapse to smoking. Participants also viewed as important targeting of the feedback and progress reports to baby’s health and development, offering personal support from experts, and providing a discussion forum allowing for communication with other pregnant women wanting to quit .

Conclusions

The present study has identified a number of potential building blocks for ISCIs targeted to quitting smoking in pregnancy. Pregnant smokers willing to try using ISCI may particularly value an engaging intervention offering a high degree of targeting of comprehensive information to them as a group and tailoring support and advice to their individual needs, as well as one providing post-relapse support, peer-to-peer communication and personal support from experts.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2458-14-1070) contains supplementary material, which is available to authorized users.

Towards Evaluating and Enhancing the Reach of Online Health Forums for Smoking Cessation

Online pro-health social networks facilitating smoking cessation through web-assisted interventions have flourished in the past decade. In order to properly evaluate and increase the impact of this form of treatment on society, one needs to understand and be able to quantify its reach, as defined within the widely-adopted RE-AIM framework. In the online communication context, user engagement is an integral component of reach. This paper quantitatively studies the effect of engagement on the users of the Alt.Support.Stop-Smoking forum that served the needs of an online smoking cessation community for more than ten years. The paper then demonstrates how online service evaluation and planning by social network analysts can be applied towards strategic interventions targeting increased user engagement in online health forums. To this end, the challenges and opportunities are identified in the development of thread recommendation systems using core-users as a strategic resource for effective and efficient spread of healthy behaviors, in particular smoking cessation.

Facebook apps for smoking cessation: a review of content and adherence to evidence-based guidelines

BACKGROUND

Facebook is the most popular social network site, with over 1 billion users globally. There are millions of apps available within Facebook, many of which address health and health behavior change. Facebook may represent a promising channel to reach smokers with cessation interventions via apps. To date, there have been no published reports about Facebook apps for smoking cessation.

OBJECTIVE

The purpose of this study was to review the features and functionality of Facebook apps for smoking cessation and to determine the extent to which they adhere to evidence-based guidelines for tobacco dependence treatment.

METHODS

In August 2013, we searched Facebook and three top Internet search engines using smoking cessation keywords to identify relevant Facebook apps. Resultant apps were screened for eligibility (smoking cessation-related, English language, and functioning). Eligible apps were reviewed by 2 independent coders using a standardized coding scheme. Coding included content features (interactive, informational, and social) and adherence to an established 20-item index (possible score 0-40) derived from the US Public Health Service's Clinical Practice Guidelines for Treating Tobacco Use and Dependence.

RESULTS

We screened 22 apps for eligibility; of these, 12 underwent full coding. Only 9 apps were available on Facebook. Facebook apps fell into three broad categories: public pledge to quit (n=3), quit-date-based calculator/tracker (n=4), or a multicomponent quit smoking program (n=2). All apps incorporated interactive, informational, and social features except for two quit-date-based calculator/trackers apps (lacked informational component). All apps allowed app-related posting within Facebook (ie, on self/other Facebook profile), and four had a within-app "community" feature to enable app users to communicate with each other. Adherence index summary scores among Facebook apps were low overall (mean 15.1, SD 7.8, range 7-30), with multicomponent apps scoring the highest.

CONCLUSIONS

There are few smoking cessation apps available within Facebook. Among those available, adherence to cessation treatment guidelines was low. Smoking cessation interventions provided via the Facebook platform are a unique and as yet untapped treatment strategy that can harness existing social support and social networks for quitting. Research is needed to examine whether apps that adhere to clinical practice guidelines for tobacco dependence treatment are more effective in promoting cessation than those that do not.

Posting behaviour patterns in an online smoking cessation social network: implications for intervention design and development

Objectives

Online Cessation Support Networks (OCSNs) are associated with increased quit success rates, but few studies have examined their use over time. We identified usage patterns in New Zealand's largest OCSN over two years and explored implications for OCSN intervention design and evaluation.

Methods

We analysed metadata relating to 133,096 OCSN interactions during 2011 and 2012. Metrics covered aggregate network activity, user posting activity and longevity, and between-user commenting. Binary logistic regression models were estimated to investigate the feasibility of predicting low user engagement using early interaction data.

Results

Repeating periodic peaks and troughs in aggregate activity related not only to seasonality (e.g., New Year), but also to day of the week. Out of 2,062 unique users, 69 Highly Engaged Users (180+ interactions each) contributed 69% of all OCSN interactions in 2012 compared to 1.3% contributed by 864 Minimally Engaged Users (< = 2 items each). The proportion of Highly Engaged Users increased with network growth between 2011 and 2012 (with marginal significance), but the proportion of Minimally Engaged Users did not decline substantively. First week interaction data enabled identification of Minimally Engaged Users with high specificity and sensitivity (AUROC  = 0.94).

Implications

Results suggest future research should develop and test interventions that promote activity, and hence cessation support, amongst specific user groups or at key time points. For example, early usage information could help identify Minimally Engaged Users for tests of targeted messaging designed to improve their integration into, or re-engagement with, the OCSN. Furthermore, although we observed strong growth over time on varied metrics including posts and comments, this change did not coincide with large gains in first-time user persistence. Researchers assessing intervention effects should therefore examine multiple measures when evaluating changes in network dynamics over time.