Development of a Twitter-based intervention for smoking cessation that encourages high-quality social media interactions via automessages

Oral Nicotine Gum Discussions on Twitter: Content Analysis

BACKGROUND

Oral nicotine gum such as LUCY, which comes in colorful packaging, mimicking traditional chewing gum, is becoming popular. Many brands of gum have not been approved by the FDA for smoking cessation. This study examined public discourse about, including sentiment toward, oral nicotine gum on Twitter.

METHODS

We used Twitter's Streaming Application Programming Interface to collect data from January 1, 2021, to December 21, 2021, using "nicotine gum" and/or "#nicotinegum" search terms (N = 19 171 unique tweets were collected). We used an inductive approach to become familiar with the data, generated a codebook, and conducted a content analysis on (n = 2152) tweets.

RESULTS

Cessation (n = 716, 33.3%), personal experience (n = 370, 17.2%), and addiction to gum (n = 135, 6.3%) were the most prevalent themes. Cessation tweets primarily discussed cigarette smoking cessation (n = 418, 58.4% of cessation tweets) and successful cessation experiences (n = 155, 21.6%). Other identified themes pertained to using nicotine gum for cognitive enhancement or catching a "buzz" (n = 102, 4.7%), marketing (n = 98, 4.6%), using nicotine gum with other substances (n = 90, 4.2%), and adverse effects (n = 63, 2.9%). Sentiment analysis results revealed that 675 (44.2%) tweets were categorized as neutral, 605 (39.6%) tweets were classified as positive, and 248 tweets (16.2%) were negative.

CONCLUSIONS

About one-third of tweets in our corpus mentioned nicotine gum in the context of smoking cessation. Most nicotine gum-related posts conveyed positive and neutral sentiments. Future studies should consider adding novel nicotine gum-specific search terms as well as exploring other social media platforms to gain more insights about these products.

IMPLICATIONS

Our findings suggest that Twitter has the potential to track and facilitate conversations between those seeking cigarette cessation advice and those who have successfully quit tobacco by using nicotine gum. Monitoring of promotional content from nicotine gum companies is needed to ensure these products are not appealing to youth and nonusers of tobacco.

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.

Associations between Health-Related Use of Social Media and Positive Lifestyle Behaviors: Findings from a Representative Sample of US Adult Smokers

Background: Cigarette smokers have elevated cardiovascular risk factors, which contributes significantly to mortality. Although social media is a potential avenue to deliver smoking interventions, its role in health promotion among smokers remains relatively unexplored.Objective: To examine the uptake and impact of health-related social media use in cigarette smokers.Methods: Using data from the 2017-2020 Health Information National Trends Survey, we evaluated differences in health-related social media use between smokers and nonsmokers. Multivariable logistic regression was performed to examine the association between social media use and positive health behaviors.Results: We included 1863 current smokers and 13,560 nonsmokers; Most participants were women (51.0%), White (64.6%), and 49.2% were aged ≥50 years. Smokers who used ≥1 social media site for health-related purposes in the past year were significantly more likely to meet the guideline recommendations for: (i) weekly physical activity (AOR 2.00, 95% CI 1.23-3.24), (ii) daily vegetable intake (AOR 2.48, 95% CI 1.10-5.59), and (iii) weekly strength training (AOR 1.80, 95% CI 1.10-2.94). However, the odds of reporting intentions to quit smoking (AOR 1.81, 95% CI 0.98-3.34) and attempts at smoking cessation (AOR 1.68, 95% CI 0.90-3.12) did not differ by health-related social media use.Conclusion: Smokers use social media for health-related purposes at comparable rates to nonsmokers. While our findings indicate that these platforms present a novel opportunity for health promotion among smokers, future research exploring the utility of social media in smoking cessation is crucial.

A mixed-methods approach to understanding barriers and facilitators to healthy eating and exercise from five European countries: highlighting the roles of enjoyment, emotion and social engagement

Healthy adults are consistently falling below national and international recommendations for physical activity and dietary intake across Europe. This study took a co-creative approach with adult samples from five European countries to qualitatively and quantitatively establish motivators, barriers and sustaining factors for positive health behaviour change. Stage 1 delivered a newly-designed online programme, creating a community who identified challenges, motivators and solutions to sustaining positive healthy eating and physical activity behaviours. Stage 2 administered an online survey (developed from Stage 1 findings) to a larger sample to quantify the relative importance of these motivators and barriers. Results from both stages indicated enjoyment, positive emotions, and reward as key motivators for both behaviours across all five countries. Barriers included habit-breaking difficulties, temptation and negative affective states. Those with a high BMI placed more importance on social pressure than those with healthy BMI. Participants' reports of motivators and barriers reflected relevant approaches from consumer science, behavioural economics, and psychology. Interventions supporting adults who are not chronically ill but would benefit from improved diet and/or physical activity should not focus exclusively on health as a motivating factor. Emphasis on enjoyable behaviours, social engagement and reward will likely improve engagement and sustained behaviour change.

Investigating #vapingcessation in Twitter

Evidence suggests that an increasing number of e-cigarette users report intentions and attempts to quit vaping. Since exposure to e-cigarette-related content on social media may influence e-cigarette and other tobacco product use, including potentially e-cigarette cessation, we aimed to explore vaping cessation-related posts on Twitter by utilizing a mixed-methods approach. We collected tweets pertaining to vaping cessation for the time period between January 2022 and December 2022 using snscrape. Tweets were scraped for the following hashtags: #vapingcessation, #quitvaping, and #stopJuuling. Data were analysed using Azure Machine Learning and Nvivo 12 software. Sentiment analysis revealed that vaping cessation-related tweets typically embody positive sentiment and are mostly produced in the U.S. and Australia. Our qualitative analysis identified six emerging themes: vaping cessation support, promotion of vaping cessation, barriers and benefits to vaping cessation, personal vaping cessation, and usefulness of peer support for vaping cessation. Our findings imply that improved dissemination of evidence-based vaping cessation strategies to a broad audience through Twitter may promote vaping cessation at the population level.

Understanding Hesitation to Use Nicotine Replacement Therapy: A Content Analysis of Posts in Online Tobacco-Cessation Support Groups

PURPOSE

We aimed to better understand hesitancy to use nicotine replacement therapy (NRT) to quit smoking.

DESIGN

We content coded and analyzed NRT-related posts in online quit smoking support groups to understand NRT-use hesitancy and to examine associations with health outcomes.

SETTING

NRT posts were analyzed in unmoderated social-media support groups with free NRT.

SAMPLE

Adults who smoked daily (n = 438) and posted about NRT were studied, 339 of whom reported on NRT usage and 403 reported on smoking abstinence.

MEASURES

Surveys at 1-month post-quit date assessed NRT usage and smoking abstinence.

ANALYSIS

Relationships among NRT posts, NRT usage and smoking abstinence were analyzed using GEE models accounting for support group and covariates.

RESULTS

Nearly all (96.17%) participants reported using the study-provided NRT once, most (70.21%) used NRT during the past week, but less than half (45.72%) used NRT daily for the full month as recommended. Nearly two-thirds (65.34%) of NRT posts were negative. Posts reflecting dislike or no longer needing NRT were associated with a lower likelihood of using NRT in the past week at least once (B = -.66, P = .005 and B = -.37, P = .045), use occasions (B = -1.86, P = .018 and B = -1.10, P = .016) and used daily for full month (B = -.56, P = .044 and B = -.53, P = .009). Posts related to the effectiveness of NRT related to past-week NRT used at least once (B = .15, P = .023), used daily for full month (B = .25, P = .001), and smoking abstinence (B = .27, P = .002).

CONCLUSION

Strategies are needed to address dislike of NRT and strengthen perceptions of NRT efficacy, especially on social media where posts may be amplified.

A WeChat-based smoking cessation intervention for Chinese smokers: a feasibility study

WeChat is the largest social media platform in China, yet few WeChat-based smoking cessation interventions have been investigated to date. The objective of this study was to develop and test the feasibility of a WeChat-based smoking cessation intervention for smokers in China. Participants were recruited using WeChat and were then randomized into one of three groups: the Standard Group, the Enhanced Group, and the wait-list Control Group. Feasibility indicators including program reach, recruitment rate, recruitment efficiency, cost per person, attrition rate, intervention message exposure, group discussion utilization rate, intervention message engagement, satisfaction, and the likelihood of recommending to others were measured with assessed. Analyses included Chi-square and Fisher exact test, as well as analysis of variance test. A responsive participant is defined as a participant that responded to a certain assessment. A total of 1,132 individuals connected with ("friended") our project on WeChat between July 1 and August 5, 2019. Of these, 403 were eligible to participate, consented, and completed the baseline assessment. As a result, 136, 135, and 132 smokers were randomly assigned to the Standard Group, the Enhanced Group, and the Control Group, respectively. The total program recruitment rate was 35.6% and the attrition rate was 46.4%. The program cost was $0.85 per person. All responsive participants read at least one message during the intervention and engaged with intervention messages 56.8% of the time. Most responsive participants reported being very or somewhat satisfied, highly or somewhat engaged, and were willing to recommend our program to others. This study demonstrated the feasibility of a smoking cessation interventions using WeChat. The program could be expanded to deliver smoking cessation interventions to a large population of smokers.

Effect of a workplace mobile phone-based instant messaging intervention on smoking cessation: a cluster-randomized controlled trial

AIMS

To test the effectiveness of intractive, instant messaging chat-based mobile phone support versus text-based mobile phone support integrated with brief interventions on self-reported smoking abstinence in workplaces.

DESIGN

A two-arm parallel cluster-randomized controlled trial with follow-up to 12 months.

SETTING

Seventy-five companies in Hong Kong, China.

PARTICIPANTS

Daily cigarette adult smokers (92.0% male, 90.9% not ready to quit within the next 30 days) from 75 companies (clusters).

INTERVENTIONS

Participants were cluster-randomized to receive text-based support (TBS, n = 375; 38 clusters) or chat-based support (CBS, n = 304; 37 clusters). TBS participants received automated and fix-scheduled text messages on cessation advice and support. CBS participants received fix-scheduled text messages and additional real-time psychosocial and cessation support via instant messaging services (e.g. WhatsApp) by counsellors. Both groups received a 1-hour health talk at baseline and brief telephone counselling at 1 week and 1, 3, 6 and 12 months.

MEASUREMENTS

The primary outcome was self-reported 7-day point-prevalence abstinence at 6 months post-treatment initiation. Secondary outcomes included 7-day point-prevalence abstinence at 12 months, repeated 7-day point-prevalence abstinence, smoking reduction, quit attempts and intervention engagement, defined as having read text messages and/or engaged in conversation with counsellors.

FINDINGS

By intention-to-treat assuming that dropouts were smoking, self-reported abstinence was not significantly different between the CBS and TBS groups at 6 months [18.8 versus 21.6%, risk ratio (RR) = 0.87, 95% confidence interval (CI) = 0.61, 1.23, retention = 71.3%] and 12 months (21.4 versus 24.0%, RR = 0.90, 95% CI = 0.66, 1.21, retention = 70.8%). The repeated 7-day point-prevalence abstinence, smoking reduction and quit attempts were similar between the groups. The participants who were engaged in the text- and/or chat-based interventions had greater abstinence (adjusted RR = 2.91, 95% CI = 1.87, 4.52) at 6 months compared with unengaged participants.

CONCLUSIONS

Compared with a text messaging mobile phone intervention, a chat-based instant messaging mobile phone intervention did not improve smoking abstinence over 12 months in workplaces. Engagement in text-based or chat-based interventions was associated with higher quit rates compared with non-engagement.

COVID-19 and Tweets About Quitting Cigarette Smoking: Topic Model Analysis of Twitter Posts 2018-2020

Background

The risk of infection and severity of illness by SARS-CoV-2 infection is elevated for people who smoke cigarettes and may motivate quitting. Organic public conversations on Twitter about quitting smoking could provide insight into quitting motivations or behaviors associated with the pandemic.

Objective

This study explored key topics of conversation about quitting cigarette smoking and examined their trajectory during 2018-2020.

Methods

Topic model analysis with latent Dirichlet allocation (LDA) identified themes in US tweets with the term “quit smoking.” The model was trained on posts from 2018 and was then applied to tweets posted in 2019 and 2020. Analysis of variance and follow-up pairwise tests were used to compare the daily frequency of tweets within and across years by quarter.

Results

The mean numbers of daily tweets on quitting smoking in 2018, 2019, and 2020 were 133 (SD 36.2), 145 (SD 69.4), and 127 (SD 32.6), respectively. Six topics were extracted: (1) need to quit, (2) personal experiences, (3) electronic cigarettes (e-cigarettes), (4) advice/success, (5) quitting as a component of general health behavior change, and (6) clinics/services. Overall, the pandemic was not associated with changes in posts about quitting; instead, New Year’s resolutions and the 2019 e-cigarette or vaping use–associated lung injury (EVALI) epidemic were more plausible explanations for observed changes within and across years. Fewer second-quarter posts in 2020 for the topic e-cigarettes may reflect lower pandemic-related quitting interest, whereas fourth-quarter increases in 2020 for other topics pointed to a late-year upswing.

Conclusions

Twitter posts suggest that the pandemic did not generate greater interest in quitting smoking, but possibly a decrease in motivation when the rate of infections was increasing in the second quarter of 2020. Public health authorities may wish to craft messages for specific Twitter audiences (eg, using hashtags) to motivate quitting during pandemics.

Buddies as In-Group Influencers in Online Support Groups: A Social Network Analysis of Processes and Outcomes

Buddies, serving as in-group influencers to aid demographically similar cobuddies, are extensively used in face-to-face support groups to enhance positive social influence. The authors examine the efficacy of buddies in online support groups and investigate underlying mediating processes using social network analysis. They observe what happens when members of support groups for quitting smoking, including members who are relatively active and less active in the group, after a few days are called on to be buddies and assigned to specific cobuddies. The findings indicate that, consistent with normative expectations for buddies, members form especially strong ties with their designated cobuddies. The more active buddies are in the group, the stronger the ties they form with their cobuddies and, in turn, their cobuddies form stronger ties with group members overall, which then relates to cobuddy goal attainment. The findings suggest that interactive marketers should consider using buddies in online support groups but observe activity levels before making buddy assignments, because positive outcomes are contingent on buddies being active in the group. Marketers should also ensure that online support group members post to everyone, not just their buddies, because ties formed among group members as a whole are crucial for goal attainment.

A WeChat-based smoking cessation intervention for Chinese smokers: A pilot study

BACKGROUND

China is the largest tobacco producer and has the highest number of tobacco consumers in the world. Extensive research has demonstrated the utility of social media for smoking cessation. WeChat is the most commonly used social media platform in China, but has not yet been utilized for smoking cessation interventions. The objectives of this study are (1) to evaluate the efficacy of a WeChat-based smoking cessation intervention; and (2) to examine a possible additive effect of integrating oral health and smoking-related information into a tailored, Transtheoretical Model (TTM) guided smoking cessation intervention.

METHODS

Eligible adults were recruited through WeChat from July 1 to August 6, 2019, to participate in a 3-arm, single-blinded, randomized controlled trial. We enrolled and randomized 403 participants into three groups: the Standard Group, Enhanced Group, or a Waitlist-Control Group. Participants in the Standard Group received 20 smoking cessation-related messages for 2 weeks; participants in the Enhanced Group received this same protocol plus 6 oral health-related messages over an additional week. Participants in the Control Group received smoking cessation-related messages, after the post-intervention assessment. The primary outcome was TTM Stage of Change, and the secondary outcomes were 7-day Point Prevalence Abstinence (PPA), 24-h PPA, daily cigarette use, and nicotine dependence at 4 weeks follow-up post intervention, comparing intervention groups with the control group. The overall program attrition rate was 46%. Paired t-tests, McNemar tests, and linear and logistic regression were used to examine differences in smoking cessation outcomes within and between groups.

RESULTS

Participants in the Enhanced Group (β = -1.28, 95%CI: -2.13, -0.44) and the Standard Group (β = -1.13, 95%CI: -1.95, -0.30) reported larger changes in nicotine dependence scores, compared to participants in the Waitlist Group. No statistically significant differences were found between the Enhanced Group and the Standard Group.

DISCUSSION

This WeChat-based intervention was effective for smoking cessation overall. The addition of oral health information did not significantly improve the intervention.

The impact and applications of social media platforms for public health responses before and during COVID-19

Background

 Social media platforms have numerous potential benefits and drawbacks on public health, which have been described in the literature. The COVID-19 pandemic has exposed our limited knowledge regarding the potential health impact of these platforms, which have been detrimental to public health responses in many regions.

Objective

This review aims to highlight a brief history of social media in health care and report its potential negative and positive public health impacts, which have been characterized in the literature.

Methods

 We searched electronic bibliographic databases including PubMed, including Medline and Institute of Electrical and Electronics Engineers Xplore, from December 10, 2015, to December 10, 2020. We screened the title and abstracts and selected relevant reports for review of full text and reference lists. These were analyzed thematically and consolidated into applications of social media platforms for public health.

Results

 The positive and negative impact of social media platforms on public health are catalogued on the basis of recent research in this report. These findings are discussed in the context of improving future public health responses and incorporating other emerging digital technology domains such as artificial intelligence. However, there is a need for more research with pragmatic methodology that evaluates the impact of specific digital interventions to inform future health policy.

Conclusions

 Recent research has highlighted the potential negative impact of social media platforms on population health, as well as potentially useful applications for public health communication, monitoring, and predictions. More research is needed to objectively investigate measures to mitigate against its negative impact while harnessing effective applications for the benefit of public health.

When are alcohol-related blackout Tweets written in the United States?

BACKGROUND

Alcohol use varies throughout the year and often peaks on weekends or during celebrations (e.g., New Year's). There is not a perfect correlation between alcohol use and negative consequences, and the extent to which one particularly risky consequence-an alcohol-related blackout-is more common during certain times of the year is unknown. Identifying when blackouts occur may help identify which periods are associated with more risk and be critical in designing public health campaigns. Thus, we examined Twitter data to ascertain whether alcohol-related blackouts occur more during certain holidays/celebrations than typical weekends and whether they differed in timing from general alcohol-related Tweets.

METHODS

We used a Twitter-sponsored platform to access unique Tweets written in the United States referencing blackouts (e.g., "blackout") and alcohol generally (e.g., "drunk").

RESULTS

The final dataset included 3.5 million blackout Tweets and 591 million alcohol Tweets (written between 2009 and 2020). Both blackout and alcohol Tweets were written in the late evening, on weekends, and during certain holidays (New Years, St. Patrick's). However, relative to typical weekends, only blackout Tweets were more common during Thanksgiving and only general alcohol-related Tweets were more common during Cinco de Mayo.

CONCLUSION

While blackout and alcohol-related Tweets were similar in time of day (peaking in the evening) and day of week (peaking on weekends), they differed during certain celebrations/holidays, suggesting that while alcohol use may be more common during some celebrations, others are more associated with serious harms.

Implementation of a WeChat-Based Smoking Cessation Program for Chinese Smokers

Introduction: Although smoking prevalence has recently declined, the smoking prevalence in China remains high. Extensive research has demonstrated ways that social media can assist in quitting smoking. WeChat is the most commonly used social media platform in China but has not been used for smoking cessation. A process evaluation of a novel WeChat-based smoking cessation intervention was conducted to measure its efficacy of content delivery, participant satisfaction, engagement, and likelihood of recommendation to others. Methods: A three-week, three-arm, single-blind randomized control trial was established. WeChat was used to recruit 403 participants and to deliver intervention messages and process evaluation surveys to them. Recruitment advertisements were posted on an official WeChat account and were forwarded to WeChat Moments. Intervention messages were delivered once a day during weekdays, using the WeChat broadcasting messages function, with two messages being sent each time. Process evaluation surveys were organized using Wenjuanwang and were delivered via WeChat. Process assessments were conducted every Friday to assess intervention message receipt, satisfaction level, engagement level, and recommendation to others. The receipt of intervention messages was measured by a self-reported question indicating which messages were read each week. Satisfaction was measured by a five-item Likert scale survey. Engagement was measured by a one-item Likert scale survey. Recommendation to others was measured by one self-reported question. Results: Participants read an average of 4.76 (out of 10), 5.80 (out of 10), and 4.25 (out of 6) messages at week 1, week 2, and week 3, respectively. The second messages were less likely to be read compared to the first messages (52.3% vs. 61.6%, respectively). Moreover, within each single week, the number of participants who read the intervention messages gradually decreases over time. Picture-based intervention messages tended to be less likely to be read than video-based intervention messages. Total program satisfaction scores ranged between 5 and 25, and the overall scores for satisfaction for each week were 21.55, 22.27, and 22.76, respectively. No significant differences were found in all the satisfaction indicators between groups. More than 60% of participants reported being either highly engaged or somewhat engaged each week. In addition, most participants (93.0% at week 1, 95.8% at week 2, and 96.2% at week 3) reported that they were willing to recommend our program to others. Discussion: A WeChat-based smoking cessation intervention for Chinese smokers was implemented and evaluated. For future studies, one should consider sending messages of a higher importance as the first message of a given day. Smokers had a higher rate of reading intervention messages at the beginning part of each week, during which, relatively important messages should be prioritized. One might also consider alternating the topics and formats of the messages for a better engagement of the users in future studies.

Theory-Based Social and Non-Social Engagement Features in Smoking Cessation Mobile Apps: A Content Analysis

Despite the ubiquity of smartphone ownership and the increasing integration of social engagement features in smoking cessation apps to engage users, the social and non-social engagement features that are present in current smoking cessation apps and the effectiveness of these features in engaging users remain understudied. To fill the gap in the literature, a content analysis of free and paid smoking cessation mobile apps was conducted to examine (a) the presence of social features (i.e., social support, social announcement, and social referencing) and non-social engagement features (e.g., personal environmental changes, goal setting, progress tracking, reinforcement tracking, self-monitoring, and personalized recommendations) and (b) their relationships with user engagement scores measured by the Mobile App Rating Scale. In this study, 28.2% of the smoking cessation apps enable social announcement and 8.1% offered the social support feature. Only two apps provided a social referencing feature (1.3%). No app included reinforcement tracking, with the percentage of other non-social engagement features ranging from 9.4% to 49.0%. Social support (β = 0.30, p < 0.001), social announcement (β = 0.21, p < 0.05), and social referencing (β = 0.18, p < 0.05) were significant predictors of user engagement. Regarding the non-social engagement features, personal environment changes (β = 0.38, p < 0.001), progress tracking (β = 0.18, p < 0.05), and personalized recommendations (β = 0.37, p < 0.001) significantly predicted user engagement. The findings not only contribute to the mobile communication literature by applying and extending the theory-based mobile health apps engagement typology, but also inform the future architecture design of smoking cessation mobile apps.

Exploring features of social support in a Chinese online smoking cessation community: A multidimensional content analysis of user interaction data

Due to the rapid development of information technology, an increasing number of smokers choose online smoking cessation communities to interact with other individuals to help themselves quit smoking. Though it is well known that social support plays a key role in the process of smoking cessation, the features of social support that one can get from online smoking cessation communities remain unclear. We collected user interaction data from the largest Chinese online smoking cessation community, the quit smoking forum of Baidu Tieba. We selected 2758 replies from 29 active repliers and 408 correlated posts as our data set. Multidimensional content analysis is carried out from three aspects: posting scenarios, user quitting behavior stages, and types of social support. This article also explores the co-occurrence relationships of different types of social support by social network analysis. Results showed that users receive different compositions of social support in various posting scenarios and behavior stages. In most cases, emotional support is the most typical support the community provides. The community will provide more informational support when needed. Besides, informational support, especially personal experience and perceptual knowledge, has more diverse combination patterns with other types of social support. "Gratitude-Mutual assistance" and "Encouragement-Mutual assistance" are the most frequent co-occurrence relationships. The online smoking cessation community brings people who quit smoking together, and users provide rich types of social support for each other. Users can effectively obtain expected social support in different posting scenarios and smoking cessation stages. Smoking cessation projects should be designed to promote user communication and interaction, which positively affects achieving users' smoking cessation goals.

Feasibility, preliminary efficacy, and accessibility of a twitter-based social support group vs Fitbit only to decrease sedentary behavior in women

BACKGROUND

Health behavior change interventions delivered by social media allow for real-time, dynamic interaction, peer social support, and experimenter-provided content.

AIMS

We tested the feasibility, acceptability, and preliminary efficacy of a novel Twitter-based walking break intervention with daily behavior change strategies and prompts for social support, combined with a Fitbit, vs. Fitbit alone.

METHODS

In a 2-group pilot, 45 sedentary women from a heart clinic were randomized to Twitter + Fitbit activity tracker (Tweet4Wellness, n = 23) or Fitbit-only (control, n = 22). All received a Fitbit and 13 weeks of tailored weekly step goals. Tweet4Wellness consisted of a private Twitter support group, with daily automated behavior change "tweets" informed by behavior change theory, and encouragement to communicate within the group. Feasibility outcomes included recruitment and enrollment numbers, implementation challenges, and number and type of help requests from participants throughout the study period. Preliminary efficacy outcomes provided by Fitbit data were sedentary minutes, number of hours with >250 steps, maximum sitting bout, weighted sedentary median bout length, total steps, intensity minutes (>3.0 METS), and ratio of time spent sitting-to-moving. Acceptability outcomes included level of Twitter participation within Tweet4Wellness, and Likert scale plus open-ended survey questions on enjoyment and perceived effectiveness of intervention components. Survey data on acceptability of the features of the intervention were collected at 13 weeks (end-of-treatment [EOT]) and 22 weeks (follow-up).

RESULTS

The study was feasible, with addressable implementation challenges. Tweet4Wellness participants changed significantly from baseline to EOT relative to control participants on number of active hours p = .018, total steps p = .028, and ratio of sitting-to-moving, p = .014. Only sitting-to-moving was significant at follow-up (p = .047). Among Tweet4Wellness participants, each tweet sent during treatment was associated with a 0.11 increase in active hours per day (p = .04) and a 292-step increase per day (p < .001). Tweet4Wellness participants averaged 54.8 (SD = 35.4) tweets, totaling 1304 tweets, and reported liking the accountability and peer support provided by the intervention.

CONCLUSION

A Twitter-delivered intervention for promoting physical activity among inactive women from a heart clinic was feasible, acceptable, and demonstrated preliminary efficacy in increasing daily active hours, daily total steps, and the ratio of sitting-to-moving from pre to post for the intervention compared with the control. Lessons learned from this pilot suggest that the next study should expand the recruitment pool, refine the intervention to increase group engagement, and select active hours, total steps, and ratio of sitting-to-movement as primary sedentary behavior measures.

Application of Automated Text Analysis to Examine Emotions Expressed in Online Support Groups for Quitting Smoking

Online support groups offer social support and an outlet for expressing emotions when dealing with health-related challenges. This study examines whether automated text analysis of emotional expressions using Linguistic Inquiry and Word Count (LIWC) can identify emotions related to abstinence expressed in online support groups for quitting smoking, suggesting promise for offering targeted mood management to members. The emotional expressions in 1 month of posts by members of 36 online support groups were related to abstinence at month end. Using the available LIWC dictionary, posts were scored for overall positive emotions, overall negative emotions, anxiety, anger, sadness, and an upbeat emotional tone. Greater expressions of negative emotions, and specifically anxiety, related to nonabstinence, while a more upbeat emotional tone related to abstinence. The results indicate that automated text analysis can identify emotions expressed in online support groups for quitting smoking and enable targeted delivery of mood management to group members.

Perceived Costs versus Actual Benefits of Demographic Self-Disclosure in Online Support Groups

Millions of U.S. adults join online support groups to attain health goals, but the social ties they form are often too weak to provide the support they need. What impedes the strengthening of ties in such groups? We explore the role of demographic differences in causing the impediment and demographic self-disclosure in removing it. Using a field study of online quit-smoking groups complemented by three laboratory experiments, we find that members tend to hide demographic differences, concerned about poor social integration that will weaken their ties. However, the self-disclosures of demographic differences that naturally occur during group member discussions actually strengthen their ties, which in turn facilitates attainment of members' health goals. In other words, social ties in online groups are weak not because members are demographically different, but because they are reluctant to self-disclose their differences. If they do self-disclose, this breeds interpersonal connection, trumping any demographic differences among them. Data from both laboratory and field about two types of demographic difference-dyad-level dissimilarity and group-level minority status-provide convergent support for our findings.

Almomani B, A. Al-Sawalha N. Knowledge and perceptions of synthetic cannabinoids among university students in Jordan

The emergence of blends of synthetic cannabinoids (SC) is an alarming public health concern in Jordan and worldwide. This study aimed to assess the knowledge and perceptions of university students of SC. A cross-sectional study employing a self-administered questionnaire was used to collect data from 1,789 university students in Jordan. The questionnaire measured the knowledge and perceptions of students of SC. Bivariate and multivariate logistic regression were used to investigate the potential predictors of good knowledge of SC. Perceptions of students regarding SC use, prevalence and availability were investigated using principal component analysis. Self-reported familiarity with SC was high (92.5%), while good knowledge was only demonstrated by (33.6%) of students. Predictors of good knowledge included being a smoker (aOR = 1.369, 95% Cl = 11.041–1.871, p = .026), an alcohol user (aOR = 2.134, 95% CI = 1.362–3.346, p = .001), being informed by traditional media (aOR = 1.367, 95% CI = 11.113–1.679, p = .003), social media (aOR = 1.241, 95% CI = 1.161–1.403, p = .021) and self-familiarity with SC (aOR = 2.499, 95% CI = 1.518–4.114, p < .0001). Students perceived SC use to be prevalent and ethically unacceptable, for religious, social, and legal reasons. There were significant differences in the ethical perceptions against the use of SC detected by gender (p < .0001), smoking (p < .0001) or alcohol use (p = .001), and being informed by both traditional media (p-.001) and social media (p = .001), but there were no differences by the level of knowledge (p = .057). Those of good knowledge and those of low knowledge did not differ on their ethical perceptions of using SC. This study showed that there was a low level of knowledge regarding SC among university students in Jordan, which may play a role in the use of SC in the country. Herein, many opportunities exist for public health education to raise awareness against SC use.

Connectedness Based on Shared Engagement Predicts Remote Biochemically Verified Quit Status Within Smoking Cessation Treatment Groups on Facebook

INTRODUCTION

Engagement with online content and online social network integration are associated with smoking behavior change, but less is known about social dynamics of shared engagement between participants in group-based social media interventions.

METHODS

Participants were 251 young adult smokers aged 18 to 25 assigned to one of 29 secret Facebook groups tailored to their readiness to quit smoking ("pre-contemplation," "contemplation," and "preparation"). Groups varied in size and were randomly assigned to receive monetary incentives for engagement. All groups received daily posts for 90 days and were assessed for remote biochemically verified smoking abstinence at the end of the intervention. Across 29 groups, we examined associations between group features (group size, incentive condition, readiness to quit) with how connected members were within the group based on shared engagement with the same content (measured by density). At the individual level, we examined associations between 7-day biochemically verified smoking abstinence and how connected an individual was within the group (measured by degree centrality).

RESULTS

After adjusting for comment volume, being in a contemplation group (vs. pre-contemplation group) was associated with a decrease in comment-based density. Individual degree centrality was significantly associated with biochemically verified smoking abstinence for both comments and likes.

CONCLUSIONS

Future group-based social media interventions for smoking cessation may want to focus on promoting connected engagement between participants, rather than simply quantity of engagement.

IMPLICATIONS

Participants in a smoking cessation intervention delivered through Facebook groups were more likely to have biochemically verified smoking abstinence if they were more connected to the rest of the group via shared engagement. Promoting shared engagement between participants may be more likely to promote behavior change than volume of engagement alone.

EREBOTS: Privacy-Compliant Agent-Based Platform for Multi-Scenario Personalized Health-Assistant Chatbots

Context. Asynchronous messaging is increasingly used to support human–machine interactions, generally implemented through chatbots. Such virtual entities assist the users in activities of different kinds (e.g., work, leisure, and health-related) and are becoming ingrained into humans’ habits due to factors including (i) the availability of mobile devices such as smartphones and tablets, (ii) the increasingly engaging nature of chatbot interactions, (iii) the release of dedicated APIs from messaging platforms, and (iv) increasingly complex AI-based mechanisms to power the bots’ behaviors. Nevertheless, most of the modern chatbots rely on state machines (implementing conversational rules) and one-fits-all approaches, neglecting personalization, data-stream privacy management, multi-topic management/interconnection, and multimodal interactions. Objective. This work addresses the challenges above through an agent-based framework for chatbot development named EREBOTS. Methods. The foundations of the framework are based on the implementation of (i) multi-front-end connectors and interfaces (i.e., Telegram, dedicated App, and web interface), (ii) enabling the configuration of multi-scenario behaviors (i.e., preventive physical conditioning, smoking cessation, and support for breast-cancer survivors), (iii) online learning, (iv) personalized conversations and recommendations (i.e., mood boost, anti-craving persuasion, and balance-preserving physical exercises), and (v) responsive multi-device monitoring interface (i.e., doctor and admin). Results. EREBOTS has been tested in the context of physical balance preservation in social confinement times (due to the ongoing pandemic). Thirteen individuals characterized by diverse age, gender, and country distribution have actively participated in the experimentation, reporting advancements in the physical balance and overall satisfaction of the interaction and exercises’ variety they have been proposed.

"I Still Don't Know What Happened, Complete Blackout": a Content Analysis of Tweets Referencing Alcohol-Induced Amnesia

OBJECTIVE

We qualitatively examined the content of alcohol-related blackouts posts ("Tweets") on Twitter, focusing on reflections post-drinking that involved clear references to memory loss.

METHODS

We examined publically available Tweets that referenced blackouts after an alcohol consumption event (n = 3,574).

RESULTS

Twitter represents a relatively unfiltered glimpse at reflections on alcohol-induced amnesia. As hypothesized, most tweets referencing blackouts did not clearly describe amnesia. In the Tweets that clearly reference amnesia, we identified several themes. Tweeters referenced an 'AlterEgo' who was responsible for all the intoxicated behaviors that were inconsistent with the Tweeter's personality. Additionally, the Tweets discussed ways in which the drinker recovered memories (e.g. from friends, from social media), other events that occurred during the amnesia (e.g. loss of items, help from friends, sexual experiences), and regret about having lost memories. Some Tweeters requested assistance from their followers to reconstruct their drinking event. Tweets have the potential to set norms about acceptable behaviors or scripts following a blackout.

CONCLUSIONS

Since most blackout Tweets are ambiguous with regards to alcohol-induced amnesia, these Tweets might be leading people to believe that blackouts are passing out or just periods of heavy intoxication. In addition, themes from these Tweets can inform future interventions by using the cognitions surrounding this high-risk behavior.

Twitter-Based Social Support Added to Fitbit Self-Monitoring for Decreasing Sedentary Behavior: Protocol for a Randomized Controlled Pilot Trial With Female Patients From a Women's Heart Clinic

Background

Prolonged sitting is an independent risk behavior for the development of chronic disease. With most interventions focusing on physical activity and exercise, there is a separate need for investigation into innovative and accessible interventions to decrease sedentary behavior throughout the day. Twitter is a social media platform with application for health communications and fostering of social support for health behavior change.

Objective

This pilot study aims to test the feasibility, acceptability, and preliminary efficacy of delivering daily behavior change strategies within private Twitter groups to foster peer-to-peer support and decrease sedentary behavior throughout the day in women. The Twitter group was combined with a Fitbit for self-monitoring activity and compared to a Fitbit-only control group.

Methods

In a 2-group design, participants were randomized to a Twitter + Fitbit treatment group or a Fitbit-only control group. Participants were recruited via the Stanford Research Repository System, screened for eligibility, and then invited to an orientation session. After providing informed consent, they were randomized. All participants received 13 weeks of tailored weekly step goals and a Fitbit. The treatment group participants, placed in a private Twitter support group, received daily automated behavior change “tweets” informed by theory and regular automated encouragement via text to communicate with the group. Fitbit data were collected daily throughout the treatment and follow-up period. Web-based surveys and accelerometer data were collected at baseline, treatment end (13 weeks), and at 8.5 weeks after the treatment.

Results

The initial study design funding was obtained from the Women’s Heart Clinic and the Stanford Clayman Institute. Funding to run this pilot study was received from the National Institutes of Health’s National Heart, Lung, and Blood Institute under Award Number K01HL136702. All procedures were approved by Stanford University’s Institutional Review Board, #32127 in 2018, prior to beginning data collection. Recruitment for this study was conducted in May 2019. Of the 858 people screened, 113 met the eligibility criteria, 68 came to an information session, and 45 consented to participate in this pilot study. One participant dropped out of the intervention, and complete follow-up data were obtained from 39 of the 45 participants (87% of the sample). Data were collected over 6 months from June to December 2019. Feasibility, acceptability, and preliminary efficacy results are being analyzed and will be reported in the winter of 2021.

Conclusions

This pilot study is assessing the feasibility, acceptability, and preliminary efficacy of delivering behavior change strategies in a Twitter social support group to decrease sedentary behavior in women. These findings will inform a larger evaluation. With an accessible, tailorable, and flexible platform, Twitter-delivered interventions offer potential for many treatment variations and titrations, thereby testing the effects of different behavior change strategies, peer-group makeups, and health behaviors of interest.

Trial Registration

ClinicalTrials.gov NCT02958189, https://clinicaltrials.gov/ct2/show/NCT02958189

International Registered Report Identifier (IRRID)

DERR1-10.2196/20926

E-Cigarette Advocates on Twitter: Content Analysis of Vaping-Related Tweets

Background

As the majority of Twitter content is publicly available, the platform has become a rich data source for public health surveillance, providing insights into emergent phenomena, such as vaping. Although there is a growing body of literature that has examined the content of vaping-related tweets, less is known about the people who generate and disseminate these messages and the role of e-cigarette advocates in the promotion of these devices.

Objective

This study aimed to identify key conversation trends and patterns over time, and discern the core voices, message frames, and sentiment surrounding e-cigarette discussions on Twitter.

Methods

A random sample of data were collected from Australian Twitter users who referenced at least one of 15 identified e-cigarette related keywords during 2012, 2014, 2016, or 2018. Data collection was facilitated by TrISMA (Tracking Infrastructure for Social Media Analysis) and analyzed by content analysis.

Results

A sample of 4432 vaping-related tweets posted and retweeted by Australian users was analyzed. Positive sentiment (3754/4432, 84.70%) dominated the discourse surrounding e-cigarettes, and vape retailers and manufacturers (1161/4432, 26.20%), the general public (1079/4432, 24.35%), and e-cigarette advocates (1038/4432, 23.42%) were the most prominent posters. Several tactics were used by e-cigarette advocates to communicate their beliefs, including attempts to frame e-cigarettes as safer than traditional cigarettes, imply that federal government agencies lack sufficient competence or evidence for the policies they endorse about vaping, and denounce as propaganda “gateway” claims of youth progressing from e-cigarettes to combustible tobacco. Some of the most common themes presented in tweets were advertising or promoting e-cigarette products (2040/4432, 46.03%), promoting e-cigarette use or intent to use (970/4432, 21.89%), and discussing the potential of e-cigarettes to be used as a smoking cessation aid or tobacco alternative (716/4432, 16.16%), as well as the perceived health and safety benefits and consequences of e-cigarette use (681/4432, 15.37%).

Conclusions

Australian Twitter content does not reflect the country’s current regulatory approach to e-cigarettes. Rather, the conversation on Twitter generally encourages e-cigarette use, promotes vaping as a socially acceptable practice, discredits scientific evidence of health risks, and rallies around the idea that e-cigarettes should largely be outside the bounds of health policy. The one-sided nature of the discussion is concerning, as is the lack of disclosure and transparency, especially among vaping enthusiasts who dominate the majority of e-cigarette discussions on Twitter, where it is unclear if comments are endorsed, sanctioned, or even supported by the industry.

Facebook Recruitment Using Zip Codes to Improve Diversity in Health Research: Longitudinal Observational Study

BACKGROUND

Facebook's advertising platform reaches most US households and has been used for health-related research recruitment. The platform allows for advertising segmentation by age, gender, and location; however, it does not explicitly allow for targeting by race or ethnicity to facilitate a diverse participant pool.

OBJECTIVE

This study looked at the efficacy of zip code targeting in Facebook advertising to reach blacks/African Americans and Hispanics/Latinos who smoke daily for a quit-smoking web-based social media study.

METHODS

We ran a general market campaign for 61 weeks using all continental US zip codes as a baseline. Concurrently, we ran 2 campaigns to reach black/African American and Hispanic-/Latino-identified adults, targeting zip codes ranked first by the percentage of households of the racial or ethnic group of interest and then by cigarette expenditure per household. We also ran a Spanish language campaign for 13 weeks, targeting all continental US zip codes but utilizing Facebook's Spanish language targeting. The advertising images and language were common across campaigns. Costs were compared for advertisement clicks, queries, applications, and participants, and yields were compared for the final three outcomes. We examined outcomes before and after the Cambridge Analytica scandal that broke in March 2018. Finally, we examined 2 promoted Facebook features: lookalike audiences and audience network placement.

RESULTS

Zip code targeting campaigns were effective for yielding the racial or ethnic groups of interest. The black-/African American-focused versus general market campaign increased black/African American weekly queries (mean 9.48, SD 5.69 vs general market mean 2.83, SD 2.05; P<.001) and applicants (mean 1.11, SD 1.21 vs general market mean 0.54, SD 0.58; P<.001). The Hispanic-/Latino-focused versus general market campaign increased Hispanic/Latino weekly queries (mean 3.10, SD 2.16 vs general market mean 0.71, SD 0.48; P<.001) and applicants (mean 0.36, SD 0.55 vs general market mean 0.10, SD 0.14; P=.001). Cost metrics did not differ between campaigns at generating participants (overall P=.54). Costs increased post- versus prescandal for the black-/African American-focused campaign for queries (mean US $8.51, SD 3.08 vs US $5.87, SD 1.89; P=.001) and applicants (mean US $59.64, SD 35.63 vs US $38.96, SD 28.31; P=.004) and for the Hispanic-/Latino-focused campaign for queries (mean US $9.24, SD 4.74 vs US $7.04, SD 3.39; P=.005) and applicants (mean US $61.19, SD 40.08 vs US $38.19, SD 21.20; P=.001).

CONCLUSIONS

Zip code targeting in Facebook advertising is an effective way to recruit diverse populations for health-based interventions. Audience network placement should be avoided. The Facebook lookalike audience may not be necessary for recruitment, with drawbacks including an unknown algorithm and unclear use of Facebook user data, and so public concerns around data privacy should be considered.

TRIAL REGISTRATION

ClinicalTrial.gov NCT02823028; https://clinicaltrials.gov/ct2/show/NCT02823028.

Testing the Usability of Digital Educational Games for Encouraging Smoking Cessation

This study, using an observational design, assessed the effect of digital educational games on students' intention to quit smoking. Specifically, a series of digital games were developed to encourage smoking cessation and enhance students' engagement with the material. Three determinants of engagement were tested: perceived ease of use, perceived usefulness, and perceived satisfaction. Usability assessments were performed using a structured questionnaire and usability-testing software (Morae). Most students reported that the games were easy to use (73.3-93.3%), useful (60.0-83.3%) and satisfactory (66.7-70.0%). After using the games, approximately half (46.7-53.3%) reported that they intended to quit smoking. After controlling for gender and age, multiple regression analysis revealed that only perceived usefulness statistically significantly contributed to intention to quit (β = 2.38, p < 0.05). 'Taiko Drumming' showed the highest number of mouse clicks (67.23), and the lowest time between inputs (7.88 s). It also received the most positive feedback (17 marks). These findings show that integrating learners' experiences into the development of learning material can improve learning effectiveness.

Using social media for smoking cessation interventions: a systematic review

Background:

Previous studies have shown that smoking tobacco significantly increases both incidence and mortality rates for many diseases. Social media has become one of the most influential platforms for various smoking cessation interventions. However, results from smoking cessation interventions have differed from study to study. Limited studies have summarised cessation outcomes from social media–based interventions. Therefore, the objective of this review is to explore the effectiveness of using social media for smoking cessation.

Methods:

We searched PubMed, MEDLINE, PsycINFO, and CINAHL for articles between June 2008 and June 2018, and also assessed the references of selected articles. We included studies that used social media as intervention platforms, provided a baseline assessment before the intervention, and provided smoking cessation outcomes after the intervention.

Results:

We identified 13 original studies that enrolled between 16 and 1698 participants; 7-day Point Prevalence Abstinence (PPA) rate was the most frequently used measure of abstinence, with a range of 7%–75%, regardless of the measurement time, study design, and analysis methods. Social media–based smoking cessation interventions were effective, because (1) smokers reported higher 7-day PPA rates after intervention compared to baseline and (2) smokers reported higher 7-day PPA rates in intervention groups than in control groups. Moreover, at each time point, approximately half of all smokers in studies reporting abstinence were found to be biochemically abstinent. There were no significant differences in the effectiveness of smoking cessation outcomes between those that used existing popular social networking platforms (e.g. Pechmann et al’s studies) and those that used individually designed interactive platforms (e.g. MyLastDip, iQuit system, Quitxt system).

Conclusions:

This review highlights the effectiveness of social media–based smoking cessation intervention studies. Due to the widespread use of social media, as well as its low cost, we suggest embedding smoking cessation interventions within existing popular social media platforms.

The Use of Web-Based Support Groups Versus Usual Quit-Smoking Care for Men and Women Aged 21-59 Years: Protocol for a Randomized Controlled Trial

Background

Existing smoking cessation treatments are challenged by low engagement and high relapse rates, suggesting the need for more innovative, accessible, and interactive treatment strategies. Twitter is a Web-based platform that allows people to communicate with each other throughout the day using their phone.

Objective

This study aims to leverage the social media platform of Twitter for fostering peer-to-peer support to decrease relapse with quitting smoking. Furthermore, the study will compare the effects of coed versus women-only groups on women’s success with quitting smoking.

Methods

The study design is a Web-based, three-arm randomized controlled trial with two treatment arms (a coed or women-only Twitter support group) and a control arm. Participants are recruited online and are randomized to one of the conditions. All participants will receive 8 weeks of combination nicotine replacement therapy (patches plus their choice of gum or lozenges), serial emails with links to Smokefree.gov quit guides, and instructions to record their quit date online (and to quit smoking on that date) on a date falling within a week of initiation of the study. Participants randomized to a treatment arm are placed in a fully automated Twitter support group (coed or women-only), paired with a buddy (matched on age, gender, location, and education), and encouraged to communicate with the group and buddy via daily tweeted discussion topics and daily automated feedback texts (a positive tweet if they tweet and an encouraging tweet if they miss tweeting). Recruited online from across the continental United States, the sample consists of 215 male and 745 female current cigarette smokers wanting to quit, aged between 21 and 59 years. Self-assessed follow-up surveys are completed online at 1, 3, and 6 months after the date they selected to quit smoking, with salivary cotinine validation at 3 and 6 months. The primary outcome is sustained biochemically confirmed abstinence at the 6-month follow-up.

Results

From November 2016 to September 2018, 960 participants in 36 groups were recruited for the randomized controlled trial, in addition to 20 participants in an initial pilot group. Data analysis will commence soon for the randomized controlled trial based on data from 896 of the 960 participants (93.3%), with 56 participants lost to follow-up and 8 dropouts.

Conclusions

This study combines the mobile platform of Twitter with a support group for quitting smoking. Findings will inform the efficacy of virtual peer-to-peer support groups for quitting smoking and potentially elucidate gender differences in quit rates found in prior research.

Trial Registration

ClinicalTrials.gov NCT02823028; https://clinicaltrials.gov/ct2/show/NCT02823028

International Registered Report Identifier (IRRID)

DERR1-10.2196/16417

Live counselor contact in a Facebook intervention predicts smoking cessation outcomes

Digital smoking cessation interventions frequently use automated delivery of content. Integrating a counselor may improve participant engagement and facilitate health behavior change. We investigated engagement with live counseling compared to automated content in a Facebook intervention and the impact of engagement on smoking cessation outcomes. The Tobacco Status Project is a 90-day smoking cessation intervention for young adults utilizing automated posts and weekly sessions with a live counselor in Facebook groups tailored to readiness to quit (precontemplation, contemplation, preparation). Data came from the treatment group of a randomized trial. Post-level analyses investigated participant engagement (number of comments) by post type (e.g., counselor posts or automated posts based on transtheoretical model of behavior change, clinical practice guidelines, motivational interviewing), stratified by readiness to quit. Participant-level analyses examined whether extent of participant engagement with counselor posts predicted abstinence at 3 months. We analyzed data of N = 251 participants and N = 2,941 posts, 11% of which were live counselor initiated, and together generated 8,403 comments. Post-level analyses found that compared to the most engaging automated content (motivational content for precontemplation and contemplation, informational content for preparation), live counseling generated more engagement among participants in preparation, similar engagement in precontemplation, and less engagement in contemplation. Extent of live counseling participation predicted 3-month verified abstinence (adjusted OR = 1.10, 95% CI [1.02, 1.20]). In digital interventions, counselor contact may be beneficial in addition to automated posts at yielding engagement and abstinence; however, participants engage differently with counseling according to readiness to quit. (PsycINFO Database Record (c) 2020 APA, all rights reserved).

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.

Mobile phone text messaging and app-based interventions for smoking cessation

BACKGROUND

Mobile phone-based smoking cessation support (mCessation) offers the opportunity to provide behavioural support to those who cannot or do not want face-to-face support. In addition, mCessation can be automated and therefore provided affordably even in resource-poor settings. This is an update of a Cochrane Review first published in 2006, and previously updated in 2009 and 2012.

OBJECTIVES

To determine whether mobile phone-based smoking cessation interventions increase smoking cessation rates in people who smoke.

SEARCH METHODS

For this update, we searched the Cochrane Tobacco Addiction Group's Specialised Register, along with clinicaltrials.gov and the ICTRP. The date of the most recent searches was 29 October 2018.

SELECTION CRITERIA

Participants were smokers of any age. Eligible interventions were those testing any type of predominantly mobile phone-based programme (such as text messages (or smartphone app) for smoking cessation. We included randomised controlled trials with smoking cessation outcomes reported at at least six-month follow-up.

DATA COLLECTION AND ANALYSIS

We used standard methodological procedures described in the Cochrane Handbook for Systematic Reviews of Interventions. We performed both study eligibility checks and data extraction in duplicate. We performed meta-analyses of the most stringent measures of abstinence at six months' follow-up or longer, using a Mantel-Haenszel random-effects method, pooling studies with similar interventions and similar comparators to calculate risk ratios (RR) and their corresponding 95% confidence intervals (CI). We conducted analyses including all randomised (with dropouts counted as still smoking) and complete cases only.

MAIN RESULTS

This review includes 26 studies (33,849 participants). Overall, we judged 13 studies to be at low risk of bias, three at high risk, and the remainder at unclear risk. Settings and recruitment procedures varied across studies, but most studies were conducted in high-income countries. There was moderate-certainty evidence, limited by inconsistency, that automated text messaging interventions were more effective than minimal smoking cessation support (RR 1.54, 95% CI 1.19 to 2.00; I² = 71%; 13 studies, 14,133 participants). There was also moderate-certainty evidence, limited by imprecision, that text messaging added to other smoking cessation interventions was more effective than the other smoking cessation interventions alone (RR 1.59, 95% CI 1.09 to 2.33; I² = 0%, 4 studies, 997 participants). Two studies comparing text messaging with other smoking cessation interventions, and three studies comparing high- and low-intensity messaging, did not show significant differences between groups (RR 0.92 95% CI 0.61 to 1.40; I² = 27%; 2 studies, 2238 participants; and RR 1.00, 95% CI 0.95 to 1.06; I² = 0%, 3 studies, 12,985 participants, respectively) but confidence intervals were wide in the former comparison. Five studies compared a smoking cessation smartphone app with lower-intensity smoking cessation support (either a lower-intensity app or non-app minimal support). We pooled the evidence and deemed it to be of very low certainty due to inconsistency and serious imprecision. It provided no evidence that smartphone apps improved the likelihood of smoking cessation (RR 1.00, 95% CI 0.66 to 1.52; I² = 59%; 5 studies, 3079 participants). Other smartphone apps tested differed from the apps included in the analysis, as two used contingency management and one combined text messaging with an app, and so we did not pool them. Using complete case data as opposed to using data from all participants randomised did not substantially alter the findings.

AUTHORS' CONCLUSIONS

There is moderate-certainty evidence that automated text message-based smoking cessation interventions result in greater quit rates than minimal smoking cessation support. There is moderate-certainty evidence of the benefit of text messaging interventions in addition to other smoking cessation support in comparison with that smoking cessation support alone. The evidence comparing smartphone apps with less intensive support was of very low certainty, and more randomised controlled trials are needed to test these interventions.

Social media for tobacco smoking cessation intervention: a review of the literature

PURPOSE OF REVIEW

Social media platforms have the potential to reach large audiences and deliver intervention content in an interactive format. Yet, little is known about the efficacy of social media for smoking cessation treatment or which specific features best promote participant engagement and behavior change. This article seeks to evaluate the current literature on the use of social media interventions to support smoking cessation.

RECENT FINDINGS

Findings suggest that social media interventions are feasible and can be utilized effectively for smoking cessation treatment. Greater participant engagement with intervention content appears to be associated with positive changes in smoking behaviors in most, but not all studies reviewed.

SUMMARY

Smoking cessation interventions on social media hold promise to help smokers quit. Future randomized trials with longer follow-up intervals are needed to expand the current evidence base, as are studies that systematically investigate strategies to improve participant engagement with interventions.

Defining Adherence to Mobile Dietary Self-Monitoring and Assessing Tracking Over Time: Tracking at Least Two Eating Occasions per Day Is Best Marker of Adherence within Two Different Mobile Health Randomized Weight Loss Interventions

BACKGROUND

Mobile dietary self-monitoring methods allow for objective assessment of adherence to self-monitoring; however, the best way to define self-monitoring adherence is not known.

OBJECTIVE

The objective was to identify the best criteria for defining adherence to dietary self-monitoring with mobile devices when predicting weight loss.

DESIGN

This was a secondary data analysis from two 6-month randomized trials: Dietary Intervention to Enhance Tracking with Mobile Devices (n=42 calorie tracking app or n=39 wearable Bite Counter device) and Self-Monitoring Assessment in Real Time (n=20 kcal tracking app or n=23 photo meal app).

PARTICIPANTS/SETTING

Adults (n=124; mean body mass index=34.7±5.6) participated in one of two remotely delivered weight-loss interventions at a southeastern university between 2015 and 2017.

INTERVENTION

All participants received the same behavioral weight loss information via twice-weekly podcasts. Participants were randomly assigned to a specific diet tracking method.

MAIN OUTCOME MEASURES

Seven methods of tracking adherence to self-monitoring (eg, number of days tracked, and number of eating occasions tracked) were examined, as was weight loss at 6 months.

STATISTICAL ANALYSES PERFORMED

Linear regression models estimated the strength of association (R²) between each method of tracking adherence and weight loss, adjusting for age and sex.

RESULTS

Among all study completers combined (N=91), adherence defined as the overall number of days participants tracked at least two eating occasions explained the most variance in weight loss at 6 months (R²=0.27; P<0.001). Self-monitoring declined over time; all examined adherence methods had fewer than half the sample still tracking after Week 10.

CONCLUSIONS

Using the total number of days at least two eating occasions are tracked using a mobile self-monitoring method may be the best way to assess self-monitoring adherence during weight loss interventions. This study shows that self-monitoring rates decline quickly and elucidates potential times for early interventions to stop the reductions in self-monitoring.

Automated Identification of Hookahs (Waterpipes) on Instagram: An Application in Feature Extraction Using Convolutional Neural Network and Support Vector Machine Classification

Background

Instagram, with millions of posts per day, can be used to inform public health surveillance targets and policies. However, current research relying on image-based data often relies on hand coding of images, which is time-consuming and costly, ultimately limiting the scope of the study. Current best practices in automated image classification (eg, support vector machine (SVM), backpropagation neural network, and artificial neural network) are limited in their capacity to accurately distinguish between objects within images.

Objective

This study aimed to demonstrate how a convolutional neural network (CNN) can be used to extract unique features within an image and how SVM can then be used to classify the image.

Methods

Images of waterpipes or hookah (an emerging tobacco product possessing similar harms to that of cigarettes) were collected from Instagram and used in the analyses (N=840). A CNN was used to extract unique features from images identified to contain waterpipes. An SVM classifier was built to distinguish between images with and without waterpipes. Methods for image classification were then compared to show how a CNN+SVM classifier could improve accuracy.

Results

As the number of validated training images increased, the total number of extracted features increased. In addition, as the number of features learned by the SVM classifier increased, the average level of accuracy increased. Overall, 99.5% (418/420) of images classified were correctly identified as either hookah or nonhookah images. This level of accuracy was an improvement over earlier methods that used SVM, CNN, or bag-of-features alone.

Conclusions

A CNN extracts more features of images, allowing an SVM classifier to be better informed, resulting in higher accuracy compared with methods that extract fewer features. Future research can use this method to grow the scope of image-based studies. The methods presented here might help detect increases in the popularity of certain tobacco products over time on social media. By taking images of waterpipes from Instagram, we place our methods in a context that can be utilized to inform health researchers analyzing social media to understand user experience with emerging tobacco products and inform public health surveillance targets and policies.

"Okay, We Get It. You Vape": An Analysis of Geocoded Content, Context, and Sentiment regarding E-Cigarettes on Twitter

The current study examined conversations on Twitter related to use and perceptions of e-cigarettes in the United States. We employed the Social Media Analytic and Research Testbed (SMART) dashboard, which was used to identify and download (via a public API) e-cigarette-related geocoded tweets. E-cigarette-related tweets were collected continuously using customized geo-targeted Twitter APIs. A total of 193,051 tweets were collected between October 2015 and February 2016. Of these tweets, a random sample of 973 geocoded tweets were selected and manually coded for information regarding source, context, and message characteristics. Our findings reveal that although over half of tweets were positive, a sizeable portion was negative or neutral. We also found that, among those tweets mentioning a stigma of e-cigarettes, most confirmed that a stigma does exist. Conversely, among tweets mentioning the harmfulness of e-cigarettes, most denied that e-cigarettes were a health hazard. These results suggest that current efforts have left the public with ambiguity regarding the potential dangers of e-cigarettes. Consequently, it is critical to communicate the public health stance on this issue to inform the public and provide counterarguments to the positive sentiments presently dominating conversations about e-cigarettes on social media. The lack of awareness and need to voice a public health position on e-cigarettes represents a vital opportunity to continue winning gains for tobacco control and prevention efforts through health communication interventions targeting e-cigarettes.

Identifying Sentiment of Hookah-Related Posts on Twitter

BACKGROUND

The increasing popularity of hookah (or waterpipe) use in the United States and elsewhere has consequences for public health because it has similar health risks to that of combustible cigarettes. While hookah use rapidly increases in popularity, social media data (Twitter, Instagram) can be used to capture and describe the social and environmental contexts in which individuals use, perceive, discuss, and are marketed this tobacco product. These data may allow people to organically report on their sentiment toward tobacco products like hookah unprimed by a researcher, without instrument bias, and at low costs.

OBJECTIVE

This study describes the sentiment of hookah-related posts on Twitter and describes the importance of debiasing Twitter data when attempting to understand attitudes.

METHODS

Hookah-related posts on Twitter (N=986,320) were collected from March 24, 2015, to December 2, 2016. Machine learning models were used to describe sentiment on 20 different emotions and to debias the data so that Twitter posts reflected sentiment of legitimate human users and not of social bots or marketing-oriented accounts that would possibly provide overly positive or overly negative sentiment of hookah.

RESULTS

From the analytical sample, 352,116 tweets (59.50%) were classified as positive while 177,537 (30.00%) were classified as negative, and 62,139 (10.50%) neutral. Among all positive tweets, 218,312 (62.00%) were classified as highly positive emotions (eg, active, alert, excited, elated, happy, and pleasant), while 133,804 (38.00%) positive tweets were classified as passive positive emotions (eg, contented, serene, calm, relaxed, and subdued). Among all negative tweets, 95,870 (54.00%) were classified as subdued negative emotions (eg, sad, unhappy, depressed, and bored) while the remaining 81,667 (46.00%) negative tweets were classified as highly negative emotions (eg, tense, nervous, stressed, upset, and unpleasant). Sentiment changed drastically when comparing a corpus of tweets with social bots to one without. For example, the probability of any one tweet reflecting joy was 61.30% from the debiased (or bot free) corpus of tweets. In contrast, the probability of any one tweet reflecting joy was 16.40% from the biased corpus.

CONCLUSIONS

Social media data provide researchers the ability to understand public sentiment and attitudes by listening to what people are saying in their own words. Tobacco control programmers in charge of risk communication may consider targeting individuals posting positive messages about hookah on Twitter or designing messages that amplify the negative sentiments. Posts on Twitter communicating positive sentiment toward hookah could add to the normalization of hookah use and is an area of future research. Findings from this study demonstrated the importance of debiasing data when attempting to understand attitudes from Twitter data.

Systematic review of social media interventions for smoking cessation

BACKGROUND

Popular social media could extend the reach of smoking cessation efforts. In this systematic review, our objectives were: 1) to determine whether social media interventions for smoking cessation are feasible, acceptable, and potentially effective; 2) to identify approaches for recruiting subjects; and 3) to examine the specific intervention design components and strategies employed to promote user engagement and retention.

METHODS

We searched Scopus, Medline, EMBASE, Cochrane Central, PsychINFO, CINAHL, and Web of Science through July 2016 and reference lists of relevant articles. Included studies described social media interventions for smoking cessation and must have reported outcomes related to feasibility, acceptability, usability, or smoking-related outcomes.

RESULTS

We identified 7 studies (all were published since 2014) that enrolled 9755 participants (median=136 [range 40 to 9042]). Studies mainly used Facebook (n=4) or Twitter (n=2), and emerged as feasible and acceptable. Five studies reported smoking-related outcomes such as greater abstinence, reduction in relapse, and an increase in quit attempts. Most studies (n=6) recruited participants using online or Facebook advertisements. Tailored content, targeted reminders, and moderated discussions were used to promote participant engagement. Three studies found that active participation through posting comments or liking content may be associated with improved outcomes. Retention ranged from 35% to 84% (median=70%) across the included studies.

CONCLUSIONS

Our review highlights the feasibility, acceptability and preliminary effectiveness of social media interventions for smoking cessation. Future research should continue to explore approaches for promoting user engagement and retention, and whether sustained engagement translates to clinically meaningful smoking cessation outcomes.

Internet-based interventions for smoking cessation

BACKGROUND

Tobacco use is estimated to kill 7 million people a year. Nicotine is highly addictive, but surveys indicate that almost 70% of US and UK smokers would like to stop smoking. Although many smokers attempt to give up on their own, advice from a health professional increases the chances of quitting. As of 2016 there were 3.5 billion Internet users worldwide, making the Internet a potential platform to help people quit smoking.

OBJECTIVES

To determine the effectiveness of Internet-based interventions for smoking cessation, whether intervention effectiveness is altered by tailoring or interactive features, and if there is a difference in effectiveness between adolescents, young adults, and adults.

SEARCH METHODS

We searched the Cochrane Tobacco Addiction Group Specialised Register, which included searches of MEDLINE, Embase and PsycINFO (through OVID). There were no restrictions placed on language, publication status or publication date. The most recent search was conducted in August 2016.

SELECTION CRITERIA

We included randomised controlled trials (RCTs). Participants were people who smoked, with no exclusions based on age, gender, ethnicity, language or health status. Any type of Internet intervention was eligible. The comparison condition could be a no-intervention control, a different Internet intervention, or a non-Internet intervention. To be included, studies must have measured smoking cessation at four weeks or longer.

DATA COLLECTION AND ANALYSIS

Two review authors independently assessed and extracted data. We extracted and, where appropriate, pooled smoking cessation outcomes of six-month follow-up or more, reporting short-term outcomes narratively where longer-term outcomes were not available. We reported study effects as a risk ratio (RR) with a 95% confidence interval (CI).We grouped studies according to whether they (1) compared an Internet intervention with a non-active control arm (e.g. printed self-help guides), (2) compared an Internet intervention with an active control arm (e.g. face-to-face counselling), (3) evaluated the addition of behavioural support to an Internet programme, or (4) compared one Internet intervention with another. Where appropriate we grouped studies by age.

MAIN RESULTS

We identified 67 RCTs, including data from over 110,000 participants. We pooled data from 35,969 participants.There were only four RCTs conducted in adolescence or young adults that were eligible for meta-analysis.Results for trials in adults: Eight trials compared a tailored and interactive Internet intervention to a non-active control. Pooled results demonstrated an effect in favour of the intervention (RR 1.15, 95% CI 1.01 to 1.30, n = 6786). However, statistical heterogeneity was high (I² = 58%) and was unexplained, and the overall quality of evidence was low according to GRADE. Five trials compared an Internet intervention to an active control. The pooled effect estimate favoured the control group, but crossed the null (RR 0.92, 95% CI 0.78 to 1.09, n = 3806, I² = 0%); GRADE quality rating was moderate. Five studies evaluated an Internet programme plus behavioural support compared to a non-active control (n = 2334). Pooled, these studies indicated a positive effect of the intervention (RR 1.69, 95% CI 1.30 to 2.18). Although statistical heterogeneity was substantial (I² = 60%) and was unexplained, the GRADE rating was moderate. Four studies evaluated the Internet plus behavioural support compared to active control. None of the studies detected a difference between trial arms (RR 1.00, 95% CI 0.84 to 1.18, n = 2769, I² = 0%); GRADE rating was moderate. Seven studies compared an interactive or tailored Internet intervention, or both, to an Internet intervention that was not tailored/interactive. Pooled results favoured the interactive or tailored programme, but the estimate crossed the null (RR 1.10, 95% CI 0.99 to 1.22, n = 14,623, I² = 0%); GRADE rating was moderate. Three studies compared tailored with non-tailored Internet-based messages, compared to non-tailored messages. The tailored messages produced higher cessation rates compared to control, but the estimate was not precise (RR 1.17, 95% CI 0.97 to 1.41, n = 4040), and there was evidence of unexplained substantial statistical heterogeneity (I² = 57%); GRADE rating was low.Results should be interpreted with caution as we judged some of the included studies to be at high risk of bias.

AUTHORS' CONCLUSIONS

The evidence from trials in adults suggests that interactive and tailored Internet-based interventions with or without additional behavioural support are moderately more effective than non-active controls at six months or longer, but there was no evidence that these interventions were better than other active smoking treatments. However some of the studies were at high risk of bias, and there was evidence of substantial statistical heterogeneity. Treatment effectiveness in younger people is unknown.

Cancer Risk-Promoting Information: The Communication Environment of Young Adults

Young adulthood represents a time of myriad transitions, which leave young adults (YAs) more susceptible to the influences of cancer risk-promoting information. The tobacco, alcohol, indoor tanning, and food and beverage industries engage in aggressive marketing strategies through both traditional and social media to target this age group to consume their products, which have known links to cancer. Despite this barrage of messaging, detailed data are lacking on the communication behaviors of subgroups of this diverse age group, particularly those from low SES. This paper explores the available data on media usage among YAs and describes the cancer risk-promoting information environment, with a focus on communication inequalities and their implications for cancer research and control. Nationally representative data on media consumption patterns indicate that the majority of YAs access a diverse range of traditional and social media platforms, but these data do not fully describe differences at the intersection of age and important factors such as SES, gender, race/ethnicity, or urban/rural residence. Meanwhile, risk-promoting information is heavily marketed to YAs across media, with an increasing focus on using social media sites to normalize products and evade marketing restrictions. Gaps in the available data on YAs' media consumption behaviors, coupled with aggressive risk-promoting marketing strategies toward YAs, may impede cancer control efforts. Relationships between exposure to various cancer risk-promoting information, concurrent risk behaviors, SES disparities, and communication inequalities should be investigated to develop innovative and effective control programs and policies to promote cancer control in this important group.

Are Social Networking Sites Making Health Behavior Change Interventions More Effective? A Meta-Analytic Review

The increasing popularity of social networking sites (SNSs) has drawn scholarly attention in recent years, and a large amount of efforts have been made in applying SNSs to health behavior change interventions. However, these interventions showed mixed results, with a large variance of effect sizes in Cohen's d ranging from -1.17 to 1.28. To provide a better understanding of SNS-based interventions' effectiveness, a meta-analysis of 21 studies examining the effects of health interventions using SNS was conducted. Results indicated that health behavior change interventions using SNS are effective in general, but the effects were moderated by health topic, methodological features, and participant features. Theoretical and practical implications of findings are discussed.

Randomised controlled trial evaluation of Tweet2Quit: a social network quit-smoking intervention

BACKGROUND

We evaluated a novel Twitter-delivered intervention for smoking cessation, Tweet2Quit, which sends daily, automated communications to small, private, self-help groups to encourage high-quality, online, peer-to-peer discussions.

DESIGN

A 2-group randomised controlled trial assessed the net benefit of adding a Tweet2Quit support group to a usual care control condition of nicotine patches and a cessation website.

PARTICIPANTS

Participants were 160 smokers (4 cohorts of 40/cohort), aged 18-59 years, who intended to quit smoking, used Facebook daily, texted weekly, and had mobile phones with unlimited texting.

INTERVENTION

All participants received 56 days of nicotine patches, emails with links to the smokefree.gov cessation website, and instructions to set a quit date within 7 days. Additionally, Tweet2Quit participants were enrolled in 20-person, 100-day Twitter groups, and received daily discussion topics via Twitter, and daily engagement feedback via text.

MEASURES

The primary outcome was sustained abstinence at 7, 30 and 60 days post-quit date.

RESULTS

Participants (mean age 35.7 years, 26.3% male, 31.2% college degree, 88.7% Caucasian) averaged 18.0 (SD=8.2) cigarettes per day and 16.8 (SD=9.8) years of smoking. Participants randomised to Tweet2Quit averaged 58.8 tweets/participant and the average tweeting duration was 47.4 days/participant. Tweet2Quit doubled sustained abstinence out to 60 days follow-up (40.0%, 26/65) versus control (20.0%, 14/70), OR=2.67, CI 1.19 to 5.99, p=0.017. Tweeting via phone predicted tweet volume, and tweet volume predicted sustained abstinence (p<0.001). The daily autocommunications caused tweeting spikes accounting for 24.0% of tweets.

CONCLUSIONS

Tweet2Quit was engaging and doubled sustained abstinence. Its low cost and scalability makes it viable as a global cessation treatment.

TRIAL REGISTRATION NUMBER

NCT01602536.

Variations in Facebook Posting Patterns Across Validated Patient Health Conditions: A Prospective Cohort Study

Background

Social media is emerging as an insightful platform for studying health. To develop targeted health interventions involving social media, we sought to identify the patient demographic and disease predictors of frequency of posting on Facebook.

Objective

The aims were to explore the language topics correlated with frequency of social media use across a cohort of social media users within a health care setting, evaluate the differences in the quantity of social media postings across individuals with different disease diagnoses, and determine if patients could accurately predict their own levels of social media engagement.

Methods

Patients seeking care at a single, academic, urban, tertiary care emergency department from March to October 2014 were queried on their willingness to share data from their Facebook accounts and electronic medical records (EMRs). For each participant, the total content of Facebook posts was extracted. Using the latent Dirichlet allocation natural language processing technique, Facebook language topics were correlated with frequency of Facebook use. The mean number of Facebook posts over 6 months prior to enrollment was then compared across validated health outcomes in the sample.

Results

A total of 695 patients consented to provide access to their EMR and social media data. Significantly correlated language topics among participants with the highest quartile of posts contained health terms, such as “cough,” “headaches,” and “insomnia.” When adjusted for demographics, individuals with a history of depression had significantly higher posts (mean 38, 95% CI 28-50) than individuals without a history of depression (mean 22, 95% CI 19-26, P=.001). Except for depression, across prevalent health outcomes in the sample (hypertension, diabetes, asthma), there were no significant posting differences between individuals with or without each condition.

Conclusions

High-frequency posters in our sample were more likely to post about health and to have a diagnosis of depression. The direction of causality between depression and social media use requires further evaluation. Our findings suggest that patients with depression may be appropriate targets for health-related interventions on social media.

Social media and your practice: navigating the surgeon-patient relationship

Utilization of social media both in the private and professional arenas has grown rapidly in the last decade. The rise of social media use within health care can be viewed as the Internet-based corollary of the patient-centered care movement, in which patient perspectives and values are central to the delivery of quality care. For orthopedic surgeons and their practices, general-purpose online social networks, such as Facebook and Twitter, are convenient platforms for marketing, providing patient education and generating referrals. Virtual health communities are used less frequently by orthopedic surgeons but provide forums for patient engagement and active surgeon-to-patient communication via blogs and ask-the-doctor platforms. This commentary reviews the current state of social media use in orthopedic practice, with particular emphasis on managing the extension of the surgeon-patient relationship online, including the unique practice risks social media poses, such as privacy concerns, potential liability, and time consumption.

Use of Web 2.0 Social Media Platforms to Promote Community-Engaged Research Dialogs: A Preliminary Program Evaluation

Background

Community-engaged research is defined by the Institute of Medicine as the process of working collaboratively with groups of people affiliated by geographic proximity, special interests, or similar situations with respect to issues affecting their well-being. Traditional face-to-face community-engaged research is limited by geographic location, limited in resources, and/or uses one-way communications. Web 2.0 technologies including social media are novel communication channels for community-engaged research because these tools can reach a broader audience while promoting bidirectional dialogs.

Objective

This paper reports on a preliminary program evaluation of the use of social media platforms for promoting engagement of researchers and community representatives in dialogs about community-engaged research.

Methods

For this pilot program evaluation, the Clinical and Translational Science Office for Community Engagement in Research partnered with the Social Media Network at our institution to create a WordPress blog and Twitter account. Both social media platforms were facilitated by a social media manager. We used descriptive analytics for measuring engagement with WordPress and Twitter over an 18-month implementation period during 2014-2016. For the blog, we examined type of user (researcher, community representative, other) and used content analysis to generate the major themes from blog postings. For use of Twitter, we examined selected demographics and impressions among followers.

Results

There were 76 blog postings observed from researchers (48/76, 64%), community representatives (23/76, 32%) and funders (5/76, 8%). The predominant themes of the blog content were research awareness and dissemination of community-engaged research (35/76, 46%) and best practices (23/76, 30%). For Twitter, we obtained 411 followers at the end of the 18-month evaluation period, with an increase of 42% (from 280 to 411) over the final 6 months. Followers reported varied geographic location (321/411, 78%, resided in the United States); 99% (407/411) spoke English; and about half (218/411, 53%) were female. Followers produced 132,000 Twitter impressions.

Conclusions

Researchers and community stakeholders use social medial platforms for dialogs related to community-engaged research. This preliminary work is novel because we used Web 2.0 social media platforms to engage these stakeholders whereas prior work used face-to-face formats. Future research is needed to explore additional social media platforms; expanded reach to other diverse stakeholders including patients, providers, and payers; and additional outcomes related to engagement.

Online Health Information-Seeking Behavior and Confidence in Filling Out Online Forms Among Latinos: A Cross-Sectional Analysis of the California Health Interview Survey, 2011-2012

BACKGROUND

Health information is increasingly being disseminated online, but there is a knowledge gap between Latinos and non-Hispanic whites, particularly those whose English language proficiency is poor, in terms both of online health information-seeking behavior and computer literacy skills. This knowledge gap may also exist between US- and foreign-born Latinos.

OBJECTIVE

The specific aim of this study was to examine Internet use, online health information-seeking behavior, and confidence in filling out online forms among Latinos, particularly as it relates to health-risk behaviors. We then stratified our sample by nativity.

METHODS

We used the adult population file of the 2011-2012 California Health Interview Survey, analyzing Internet use, online health information-seeking behavior, and confidence in filling out online forms using binary logistic regression among Latinos and whites (N=27,289), Latinos (n=9506), and Latinos who use the Internet (n=6037).

RESULTS

Foreign-born Latinos (OR 0.71, 95% CI 0.58-0.88, P=.002) have lower odds of engaging in online health information-seeking behavior, and higher odds (OR 2.90, 95% CI 2.07-4.06, P<.001) of reporting a lack of confidence in filling out online forms compared to US-born Latinos. Correlates of online health information-seeking behavior and form confidence varied by nativity.

CONCLUSIONS

Latinos, particularly foreign-born individuals, are at an increased risk of being left behind as the move to increase online content delivery and care expands. As online health information dissemination and online health portals become more popular, the impact of these sites on Latino gaps in coverage and care should be considered.

Mobile health solutions for the aging population: A systematic narrative analysis

Introduction The ubiquitous nature of mobile technology coupled with the acceptance of mobile health (mHealth) among the elderly offers an opportunity to augment the existing medical workforce in long-term care. The objective of this review and narrative analysis is to identify and analyse facilitators and barriers to adoption of mHealth for the elderly. Methods Studies over the last year were identified in multiple database indices, and three reviewers examined abstracts ( k = 0.82) and analysed articles for themes which were tallied in affinity diagrams to identify frequency of occurrence in the literature (n = 36). Results The three facilitators mentioned most often were independence (18%), understanding (13%), and visibility (13%). The three barriers mentioned most often were complexity (21%), limited by users (12%) and ineffective (12%). Discussion and conclusions The reviewers concluded that the work done so far illustrates that mHealth enables a perception of independence. Future research should focus on the barriers of complexity of technology and improving existing medical literacy in order to facilitate further adoption.