A qualitative study of stakeholders' experiences with and acceptability of a technology-supported health coaching intervention (SHARE-S) delivered in coordination with cancer survivorship care.

PURPOSE: Healthy cancer survivorship involves patients' active engagement with preventative health behaviors and follow-up care. While clinicians and patients have typically held dual responsibility for activating these behaviors, transitioning some clinician effort to technology and health coaches may enhance guideline implementation. This paper reports on the acceptability of the Shared Healthcare Actions & Reflections Electronic systems in survivorship (SHARE-S) program, an entirely virtual multicomponent intervention incorporating e-referrals, remotely-delivered health coaching, and automated text messages to enhance patient self-management and promote healthy survivorship. METHODS: SHARE-S was evaluated in single group hybrid implementation-effectiveness pilot study. Patients were e-referred from the clinical team to health coaches for three health self-management coaching calls and received text messages to enhance coaching. Semi-structured qualitative interviews were conducted with 21 patient participants, 2 referring clinicians, and 2 health coaches to determine intervention acceptability (attitudes, appropriateness, suitability, convenience, and perceived effectiveness) and to identify important elements of the program and potential mechanisms of action to guide future implementation. RESULTS: SHARE-S was described as impactful and convenient. The nondirective, patient-centered health coaching and mindfulness exercises were deemed most acceptable; text messages were less acceptable. Stakeholders suggested increased flexibility in format, frequency, timing, and length of participation, and additional tailored educational materials. Patients reported tangible health behavior changes, improved mood, and increased accountability and self-efficacy. CONCLUSIONS: SHARE-S is overall an acceptable and potentially effective intervention that may enhance survivors' self-management and well-being. Alterations to tailored content, timing, and dose should be tested to determine impact on acceptability and outcomes.

Advancing health equity through implementation science: Identifying and examining measures of the outer setting.

BACKGROUND: Implementation science (IS) could accelerate progress toward achieving health equity goals. However, the lack of attention to the outer setting where interventions are implemented limits applicability and generalizability of findings to different populations, settings, and time periods. We developed a data resource to assess outer setting across seven centers funded by the National Cancer Institute's IS Centers in Cancer Control (ISC3) Network Program. OBJECTIVE: To describe the development of the Outer Setting Data Resource and characterize the county-level outer context across Centers. METHODS: Our Data Resource captures seven key environments, including: (1) food; (2) physical; (3) economic; (4) social; (5) health care; (6) cancer behavioral and screening; and (7) cancer-related policy. Data were obtained from public sources including the US Census and American Community Survey. We present medians and interquartile ranges based on the distribution of all counties in the US, all ISC3 centers, and within each Center for twelve selected measures. Distributions of each factor are compared with the national estimate using single sample sign tests. RESULTS: ISC3 centers' catchment areas include 458 counties and over 126 million people across 28 states. The median percentage of population living within ½ mile of a park is higher in ISC3 counties (38.0%, interquartile range (IQR): 16.0%-59.0%) compared to nationally (18.0%, IQR: 7.0%-38.0%; p < 0.0001). The median percentage of households with no broadband access is significantly lower in ISC3 counties (28.4%, IQR: 21.4%-35.6%) compared the nation overall (32.8%, IQR: 25.8%-41.2%; p < 0.0001). The median unemployment rate was significantly higher in ISC3 counties (5.2%, IQR: 4.1%-6.4%) compared to nationally (4.9%, 3.6%-6.3%, p = 0.0006). CONCLUSIONS: Our results indicate that the outer setting varies across Centers and often differs from the national level. These findings demonstrate the importance of assessing the contextual environment in which interventions are implemented and suggest potential implications for intervention generalizability and scalability.

Monitoring the Implementation of Tobacco Cessation Support Tools: Using Novel Electronic Health Record Activity Metrics.

BACKGROUND: Clinical decision support (CDS) tools in electronic health records (EHRs) are often used as core strategies to support quality improvement programs in the clinical setting. Monitoring the impact (intended and unintended) of these tools is crucial for program evaluation and adaptation. Existing approaches for monitoring typically rely on health care providers' self-reports or direct observation of clinical workflows, which require substantial data collection efforts and are prone to reporting bias. OBJECTIVE: This study aims to develop a novel monitoring method leveraging EHR activity data and demonstrate its use in monitoring the CDS tools implemented by a tobacco cessation program sponsored by the National Cancer Institute's Cancer Center Cessation Initiative (C3I). METHODS: We developed EHR-based metrics to monitor the implementation of two CDS tools: (1) a screening alert reminding clinic staff to complete the smoking assessment and (2) a support alert prompting health care providers to discuss support and treatment options, including referral to a cessation clinic. Using EHR activity data, we measured the completion (encounter-level alert completion rate) and burden (the number of times an alert was fired before completion and time spent handling the alert) of the CDS tools. We report metrics tracked for 12 months post implementation, comparing 7 cancer clinics (2 clinics implemented the screening alert and 5 implemented both alerts) within a C3I center, and identify areas to improve alert design and adoption. RESULTS: The screening alert fired in 5121 encounters during the 12 months post implementation. The encounter-level alert completion rate (clinic staff acknowledged completion of screening in EHR: 0.55; clinic staff completed EHR documentation of screening results: 0.32) remained stable over time but varied considerably across clinics. The support alert fired in 1074 encounters during the 12 months. Providers acted upon (ie, not postponed) the support alert in 87.3% (n=938) of encounters, identified a patient ready to quit in 12% (n=129) of encounters, and ordered a referral to the cessation clinic in 2% (n=22) of encounters. With respect to alert burden, on average, both alerts fired over 2 times (screening alert: 2.7; support alert: 2.1) before completion; time spent postponing the screening alert was similar to completing (52 vs 53 seconds) the alert, and time spent postponing the support alert was more than completing (67 vs 50 seconds) the alert per encounter. These findings inform four areas where the alert design and use can be improved: (1) improving alert adoption and completion through local adaptation, (2) improving support alert efficacy by additional strategies including training in provider-patient communication, (3) improving the accuracy of tracking for alert completion, and (4) balancing alert efficacy with the burden. CONCLUSIONS: EHR activity metrics were able to monitor the success and burden of tobacco cessation alerts, allowing for a more nuanced understanding of potential trade-offs associated with alert implementation. These metrics can be used to guide implementation adaptation and are scalable across diverse settings.

Creating research-ready partnerships: the initial development of seven implementation laboratories to advance cancer control.

BACKGROUND: In 2019-2020, with National Cancer Institute funding, seven implementation laboratory (I-Lab) partnerships between scientists and stakeholders in 'real-world' settings working to implement evidence-based interventions were developed within the Implementation Science Centers in Cancer Control (ISC3) consortium. This paper describes and compares approaches to the initial development of seven I-Labs in order to gain an understanding of the development of research partnerships representing various implementation science designs. METHODS: In April-June 2021, members of the ISC3 Implementation Laboratories workgroup interviewed research teams involved in I-Lab development in each center. This cross-sectional study used semi-structured interviews and case-study-based methods to collect and analyze data about I-Lab designs and activities. Interview notes were analyzed to identify a set of comparable domains across sites. These domains served as the framework for seven case descriptions summarizing design decisions and partnership elements across sites. RESULTS: Domains identified from interviews as comparable across sites included engagement of community and clinical I-Lab members in research activities, data sources, engagement methods, dissemination strategies, and health equity. The I-Labs use a variety of research partnership designs to support engagement including participatory research, community-engaged research, and learning health systems of embedded research. Regarding data, I-Labs in which members use common electronic health records (EHRs) leverage these both as a data source and a digital implementation strategy. I-Labs without a shared EHR among partners also leverage other sources for research or surveillance, most commonly qualitative data, surveys, and public health data systems. All seven I-Labs use advisory boards or partnership meetings to engage with members; six use stakeholder interviews and regular communications. Most (70%) tools or methods used to engage I-Lab members such as advisory groups, coalitions, or regular communications, were pre-existing. Think tanks, which two I-Labs developed, represented novel engagement approaches. To disseminate research results, all centers developed web-based products, and most (n = 6) use publications, learning collaboratives, and community forums. Important variations emerged in approaches to health equity, ranging from partnering with members serving historically marginalized populations to the development of novel methods. CONCLUSIONS: The development of the ISC3 implementation laboratories, which represented a variety of research partnership designs, offers the opportunity to advance understanding of how researchers developed and built partnerships to effectively engage stakeholders throughout the cancer control research lifecycle. In future years, we will be able to share lessons learned for the development and sustainment of implementation laboratories.

Effect of a Machine Learning Recommender System and Viral Peer Marketing Intervention on Smoking Cessation: A Randomized Clinical Trial.

Importance: Novel data science and marketing methods of smoking-cessation intervention have not been adequately evaluated. Objective: To compare machine learning recommender (ML recommender) computer tailoring of motivational text messages vs a standard motivational text-based intervention (standard messaging) and a viral peer-recruitment tool kit (viral tool kit) for recruiting friends and family vs no tool kit in a smoking-cessation intervention. Design, Setting, and Participants: This 2 ×2 factorial randomized clinical trial with partial allocation, conducted between July 2017 and September 2019 within an online tobacco intervention, recruited current smokers aged 18 years and older who spoke English from the US via the internet and peer referral. Data were analyzed from March through May 2022. Interventions: Participants registering for the online intervention were randomly assigned to the ML recommender or standard messaging groups followed by partially random allocation to access to viral tool kit or no viral tool kit groups. The ML recommender provided ongoing refinement of message selection based on user feedback and comparison with a growing database of other users, while the standard system selected messages based on participant baseline readiness to quit. Main Outcomes and Measures: Our primary outcome was self-reported 7-day point prevalence smoking cessation at 6 months. Results: Of 1487 participants who smoked (444 aged 19-34 years [29.9%], 508 aged 35-54 years [34.1%], 535 aged ≥55 years [36.0%]; 1101 [74.0%] females; 189 Black [12.7%] and 1101 White [78.5%]; 106 Hispanic [7.1%]), 741 individuals were randomly assigned to the ML recommender group and 746 individuals to the standard messaging group; viral tool kit access was provided to 745 participants, and 742 participants received no such access. There was no significant difference in 6-month smoking cessation between ML recommender (146 of 412 participants [35.4%] with outcome data) and standard messaging (156 of 389 participants [40.1%] with outcome data) groups (adjusted odds ratio, 0.81; 95% CI, 0.61-1.08). Smoking cessation was significantly higher in viral tool kit (177 of 395 participants [44.8%] with outcome data) vs no viral tool kit (125 of 406 participants [30.8%] with outcome data) groups (adjusted odds ratio, 1.48; 95% CI, 1.11-1.98). Conclusions and Relevance: In this study, machine learning-based selection did not improve performance compared with standard message selection, while viral marketing did improve cessation outcomes. These results suggest that in addition to increasing dissemination, viral recruitment may have important implications for improving effectiveness of smoking-cessation interventions. Trial Registration: ClinicalTrials.gov Identifier: NCT03224520.

Characterizing Pandemic-Related Changes in Smoking Over Time in a Cohort of Current and Former Smokers.

INTRODUCTION: We used a longitudinal cohort of US adults who were current or former smokers to explore how three participant-reported factors-general stress, coronavirus disease of 2019 (COVID-19) distress, and perceived risk of complications from COVID-19 related to smoking-were associated with changes in smoking status. METHODS: Smoking status was assessed at three time points. Timepoint 1 status was assessed at a prior study completion (2018-2020). Timepoint 2 (start of the pandemic), and Timepoint 3 (early phase of the pandemic) statuses were assessed using an additional survey in 2020. After classifying participants into eight groups per these time points, we compared the means of participant-reported factors and used a linear regression model to adjust for covariates. RESULTS: Participants (n = 392) were mostly female (73.9%) and non-Hispanic White (70.1%). Between Timepoints 2 and 3, abstinence rates decreased by 11%, and 40% of participants reported a smoking status change. Among those reporting a change and the highest general stress levels, newly abstinent participants had higher perceived risk of complications from COVID-19 related to smoking than those who relapsed during pandemic (mean (SD): 14.2 (3.3) vs. 12.6 (3.8)). Compared to participants who sustained smoking, those who sustained abstinence, on average, scored 1.94 less on the general stress scale (ßeta Coefficient (ß): -1.94, p-value < .01) and 1.37 more on the perceived risk of complications from COVID-19 related to smoking scale (ß: 1.37, p-value .02). CONCLUSIONS: Decreased abstinence rates are concerning. Patterns of reported factors were as expected for individuals who sustained their smoking behavior but not for those who changed. IMPLICATIONS: We observed an increase in smoking rates during the COVID-19 pandemic. In exploring how combinations of general stress levels, COVID-19 distress levels, and perceived risk of complications from COVID-19 related to smoking were associated with changes in smoking, we observed expected patterns of these factors among individuals who sustained abstinence or smoking. Among individuals who changed smoking status and reported high stress levels, those who reported a higher perceived risk of complications from COVID-19 related to smoking abstained from smoking. In contrast, those who reported a lower perceived risk of complications from COVID-19 related to smoking, started smoking. An intersectional perspective may be needed to understand smokers' pandemic-related behavior changes.

Effect of Technology-Assisted Brief Abstinence Game on Long-term Smoking Cessation in Individuals Not Yet Ready to Quit: A Randomized Clinical Trial.

IMPORTANCE: Most trials of behavioral or pharmaceutical interventions for people who smoke are limited to individuals reporting they are ready to quit smoking. Engaging individuals who initially report they are not yet ready to quit in brief, precessation, skills-building interventions (eg, practice quit attempts or nicotine replacement therapy [NRT] sampling) is challenging. OBJECTIVE: To test an integrated behavioral plus NRT-sampling intervention using a gamification approach supported by mobile health. DESIGN, SETTING, AND PARTICIPANTS: A multisite randomized clinical trial with site-level 1-to-1 allocation into 2 conditions was conducted in 4 US health care systems. A total of 433 individuals who were currently smoking and reported at enrollment that they were not ready to quit smoking were enrolled. The study was conducted from November 7, 2016, to July 31, 2020. INTERVENTIONS: Take a Break (TAB) was a 3-week game experience and included 5 behavioral components (motivational messaging, challenge quizzes, brief abstinence goal setting, mobile health apps for cravings management, and reward points for participation) integrated with NRT sampling. TAB draws on social cognitive theory and game mechanics concepts to engage participants in health behavior change. The comparison included NRT sampling only. MAIN OUTCOMES AND MEASURES: Time to first quit attempt (duration from TAB experience to primary outcome) and carbon monoxide level-verified smoking cessation at 6-month follow-up. All analyses used an intention-to-treat approach. RESULTS: Of the 433 individuals included in the trial, 223 were women (52%); mean (SD) age was 54 (13) years. More than half (53% [112 of 213]) of the TAB participants completed 100% of the daily challenge quizzes in the first week, 73% (145 of 199) of participants who completed the goal-setting call set a brief abstinence goal (most frequently 1-2 days of abstinence from cigarettes), and 75% (159 of 213) of participants used the mobile health apps to manage nicotine cravings. Time to the first quit attempt was lower for the TAB vs comparison group (hazard ratio, 1.68; 95% CI, 1.09-2.60; P = .02). At the 6-month follow-up, 18% (28 of 160) of TAB participants and 10% (17 of 171) of the comparison (χ2 test, P = .045) participants obtained carbon monoxide level-verified smoking cessation (accounting for clustering of outcomes by site; odds ratio, 1.92; 95% CI, 1.01-3.68; P = .048). CONCLUSIONS AND RELEVANCE: The findings of this randomized clinical trial demonstrate that individuals not yet ready to quit smoking could be engaged in a brief abstinence game. Six months later, the TAB group had nearly double the rate of smoking cessation vs the NRT sampling comparison group. Integrating a skills-building game experience with brief NRT sampling can enhance long-term cessation among those not yet ready to quit smoking. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT02973425.

mHealth Messaging to Motivate Quitline Use and Quitting: Protocol for a Community-Based Randomized Controlled Trial in Rural Vietnam.

BACKGROUND: Tobacco kills more than 8 million people each year, mostly in low- and middle-income countries. In Vietnam, 1 in every 2 male adults smokes tobacco. Vietnam has set up telephone Quitline counseling that is available to all smokers, but it is underused. We previously developed an automated and effective motivational text messaging system to support smoking cessation among US smokers. OBJECTIVE: The aim of this study is to adapt the aforementioned system for rural Vietnamese smokers to promote cessation of tobacco use, both directly and by increasing the use of telephone Quitline counseling services and nicotine replacement therapy. Moreover, we seek to enhance research and health service capacity in Vietnam. METHODS: We are testing the effectiveness of our culturally adapted motivational text messaging system by using a community-based randomized controlled trial design (N=600). Participants were randomly allocated to the intervention (regular motivational and assessment text messages) or control condition (assessment text messages only) for a period of 6 months. Trial recruitment took place in four communes in the Hung Yen province in the Red River Delta region of Vietnam. Recruitment events were advertised to the local community, facilitated by community health workers, and occurred in the commune health center. We are assessing the impact of the texting system on 6-month self-reported and biochemically verified smoking cessation, as well as smoking self-efficacy, uptake of the Quitline, and use of nicotine replacement therapy. In addition to conducting the trial, the research team also provided ongoing training and consultation with the Quitline during the study period. RESULTS: Site preparation, staff training, intervention adaptation, participant recruitment, and baseline data collection were completed. The study was funded in August 2017; it was reviewed and approved by the University of Massachusetts Medical School Institutional Review Board in 2017. Recruitment began in November 2018. A total of 750 participants were recruited from four communes, and 700 (93.3%) participants completed follow-up by March 2021. An analysis of the trial results is in progress; results are expected to be published in late 2022. CONCLUSIONS: This study examines the effectiveness of mobile health interventions for smoking in rural areas in low- and middle-income countries, which can be implemented nationwide if proven effective. In addition, it also facilitates significant collaboration and capacity building among a variety of international partners, including researchers, policy makers, Quitline counselors, and community health workers. TRIAL REGISTRATION: ClinicalTrials.gov NCT03567993; https://clinicaltrials.gov/ct2/show/NCT03567993. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/30947.

Evaluating the use of a recommender system for selecting optimal messages for smoking cessation: patterns and effects of user-system engagement.

BACKGROUND: Motivational messaging is a frequently used digital intervention to promote positive health behavior changes, including smoking cessation. Typically, motivational messaging systems have not actively sought feedback on each message, preventing a closer examination of the user-system engagement. This study assessed the granular user-system engagement around a recommender system (a new system that actively sought user feedback on each message to improve message selection) for promoting smoking cessation and the impact of engagement on cessation outcome. METHODS: We prospectively followed a cohort of current smokers enrolled to use the recommender system for 6 months. The system sent participants motivational messages to support smoking cessation every 3 days and used machine learning to incorporate user feedback (i.e., user's rating on the perceived influence of each message, collected on a 5-point Likert scale with 1 indicating strong disagreement and 5 indicating strong agreement on perceiving the influence on quitting smoking) to improve the selection of the following message. We assessed user-system engagement by various metrics, including user response rate (i.e., the percent of times a user rated the messages) and the perceived influence of messages. We compared retention rates across different levels of user-system engagement and assessed the association between engagement and the 7-day point prevalence abstinence (missing outcome = smoking) by using multiple logistic regression. RESULTS: We analyzed data from 731 participants (13% Black; 73% women). The user response rate was 0.24 (SD = 0.34) and user-perceived influence was 3.76 (SD = 0.84). The retention rate positively increased with the user response rate (trend test P < 0.001). Compared with non-response, six-month cessation increased with the levels of response rates: low response rate (odds ratio [OR] = 1.86, 95% confidence interval [CI]: 1.07-3.23), moderate response rate (OR = 2.30, 95% CI: 1.36-3.88), high response rate (OR = 2.69, 95% CI: 1.58-4.58). The association between perceived message influence and the outcome showed a similar pattern. CONCLUSIONS: High user-system engagement was positively associated with both high retention rate and smoking cessation, suggesting that investigation of methods to increase engagement may be crucial to increase the impact of the recommender system for smoking cessation. TRIAL REGISTRATION: Registration Identifier: NCT03224520 . Registration date: July 21, 2017.

Written Advice Given by African American Smokers to Their Peers: Qualitative Study of Motivational Messages.

BACKGROUND: Although African Americans have the lowest rates of smoking onset and progression to daily smoking, they are less likely to achieve long-term cessation. Interventions tailored to promote use of cessation resources in African American individuals who smoke are needed. In our past work, we demonstrated the effectiveness of a technology-assisted peer-written message intervention for increasing smoking cessation in non-Hispanic White smokers. In this formative study, we have adapted this intervention to be specific for African American smokers. OBJECTIVE: We aimed to report on the qualitative analysis of messages written by African American current and former smokers for their peers in response to hypothetical scenarios of smokers facing cessation challenges. METHODS: We recruited African American adult current and former smokers (n=41) via ResearchMatch between April 2017 and November 2017. We asked participants to write motivational messages for their peers in response to smoking-related hypothetical scenarios. We also collected data on sociodemographic factors and smoking characteristics. Thematic analysis was conducted to identify cessation strategies suggested by the study participants. RESULTS: Among the study participants, 60% (25/41) were female. Additionally, more than half (23/41, 56%) were thinking about quitting, 29% (12/41) had set a quit date, and 27% (11/41) had used electronic cigarettes in the past 30 days. Themes derived from the qualitative analysis of peer-written messages were (1) behavioral strategies, (2) seeking help, (3) improvements in quality of life, (4) attitudes and expectations, and (5) mindfulness/religious or spiritual practices. Under the behavioral strategies theme, distraction strategies were the most frequently suggested strategies (referenced 84 times in the 318 messages), followed by use of evidence-based treatments/cessation strategies. Within the seeking help theme, subthemes included seeking help or support from family/friends or close social networks (referenced 56 times) and health care professionals (referenced 22 times). The most frequent subthemes that emerged from improvements in the quality of life theme included improving one's health (referenced 22 times) and quality of life (referenced 21 times). Subthemes that emerged from the attitude and expectations theme included practicing positive self-talk (referenced 27 times), autonomy/independence from the smoking habit (referenced six times), and financial cost of smoking (referenced five times). The two subthemes that emerged from the mindfulness/religious or spiritual practices theme were use of self-awareness techniques (referenced 36 times) and religious or spiritual practices to cope (referenced 13 times). CONCLUSIONS: Our approach to adapt a prior peer-message intervention to African American smokers yielded a set of evidence-based messages that may be suitable for smokers at all phases of motivation to quit (ready to quit or not ready to quit). In future research, we plan to assess the impact of texting these messages to African American smokers in a smoking cessation trial.

Comparing recruitment strategies for a digital smoking cessation intervention: Technology-assisted peer recruitment, social media, ResearchMatch, and smokefree.gov.

BACKGROUND: Choosing the right recruitment strategy has implications for the successful conduct of a trial. Our objective was to compare a novel peer recruitment strategy to four other recruitment strategies for a large randomized trial testing a digital tobacco intervention. METHODS: We compared enrollment rates, demographic and baseline smoking characteristics, and odds of completing the 6-month study by recruitment strategy. Cost of recruitment strategies per retained participant was calculated using staff personnel time and advertisement costs. FINDINGS: We enrolled 1487 participants between August 2017 and March 2019 from: Peer recruitment n = 273 (18.4%), Facebook Ads n = 505 (34%), Google Ads = 200 (13.4%), ResearchMatch n = 356 (23.9%) and Smokefree.govn = 153 (10.3%). Mean enrollment rate per active recruitment month: 1) Peer recruitment, n = 13.9, 2) Facebook ads, n = 25.3, 3) Google ads, n = 10.51, 4) Research Match, n = 59.3, and 5) Smokefree.gov, n = 13.9. Peer recruitment recruited the greatest number of males (n = 110, 40.3%), young adults (n = 41, 14.7%), participants with a high school degree or less (n = 24, 12.5%) and smokers within one's social network. Compared to peer recruitment (retention rate = 57%), participants from Facebook were less likely (OR 0.46, p < 0.01, retention rate = 40%), and those from ResearchMatch were more likely to complete the study (OR 1.90, p < 0.01, retention rate = 70%). Peer recruitment was moderate in cost per retained participant ($47.18) and substantially less costly than Facebook ($173.60). CONCLUSIONS: Though peer recruitment had lower enrollment than other strategies, it may provide greater access to harder to reach populations and possibly others who smoke within one's social network while being moderately cost-effective. ClinicalTrials.gov: NCT03224520.

A longitudinal implementation evaluation of a physical activity program for cancer survivors: LIVESTRONG® at the YMCA.

PURPOSE: Increased physical activity (PA) levels in cancer survivors are associated with decreased risk of recurrence and mortality as well as additional positive health outcomes. PA interventions have shown to be efficacious, though many lack translation to and sustainability in community settings. We used dimensions of the RE-AIM framework to evaluate LIVESTRONG® at the YMCA, a nation-wide community-based PA program for cancer survivors delivered at Ys. METHODS: This was a longitudinal study design using national LIVESTRONG at the YMCA data compiled between 2010 and 2018. Data is from all YMCAs who deliver LIVESTRONG at the YMCA, submitted by Program Directors to the YMCA-USA. We assessed reach (number of participants), adoption (associations offering the program), implementation (conducting 3 fidelity checks), and organizational level maintenance (associations recently offering program). We also examined relationships between organizational characteristics (years of program existence and association area household income) and program implementation factors with member conversion rates. RESULTS: As of 2018, LIVESTRONG at the YMCA has reached 62,044 survivors and 245 of the 840 (29.2%) of Y associations have adopted the program. Among the adopters, 91% were aware of fidelity checks; implementation of observational (62.3%), goal setting (49.9%), and functional (64.6%) checklists varied. Most (95.1%) adopters reported offering ≥ 1 LIVESTRONG session per year (organizational-level maintenance) and a facility-level mean membership conversion percentage of 46.9 ± 31.2%. Fewer years implementing the program and higher association area household income were significantly associated with a greater membership conversion rate vs their comparison. In a multiple regression model controlling for organizational characteristics, conducting the fidelity checks independently (observational, ß = 8.41; goal-setting, ß = 9.70; and functional, ß = 9.61) and collectively (ß = 10.82; 95% CI 5.90-16.80) was positively associated with higher membership conversion rates. CONCLUSIONS: LIVESTRONG at the YMCA, in its early years, has shown promise for high reach, while adoption at more associations could be facilitated. Implementing fidelity checks along with organizational characteristics were associated with membership conversion rate. Identification of association-level strategies to increase reach, adoption, implementation, and maintenance may increase the impact of this community-based PA program.

Teamwork for smoking cessation: which smoker was willing to engage their partner? Results from a cross-sectional study.

OBJECTIVE: Smokers are greatly influenced by those living with them, but strategies that increase partner support for smoking cessation are lacking. Using a cross-sectional study design, we explored factors associated with willingness to engage a partner in smoking cessation in smokers registered on a web-assisted tobacco intervention trial. RESULTS: Study participants (n = 983) were recruited between July 2018 and March 2019. About 28% of smokers were willing to engage their partner in cessation efforts. The odds of willingness to engage a partner were more than two-fold for smokers reporting presence of other smokers in the immediate family (adjusted odds ratio (aOR): 2.18; 95% confidence interval (CI) 1.51-3.15 for 1-3 smokers; aOR, 3.12; 95% CI 1.95-4.98 for ≥ 4 smokers) compared to those with no smokers in the immediate family. Women had lower odds of willingness to engage (aOR; 0.82; 95% CI 0.58-1.16) than men, but this was not statistically significant. Use of e-cigarettes and visitation to a smoking cessation website prior to the intervention were both positively associated with willingness to engage partners in cessation. Future research should assess whether interventions tailored to smokers willing to engage partners or spouses could increase effectiveness of partner support during cessation.

Secure Asynchronous Communication Between Smokers and Tobacco Treatment Specialists: Secondary Analysis of a Web-Assisted Tobacco Intervention in the QUIT-PRIMO and National Dental PBRN Networks.

BACKGROUND: Within a web-assisted tobacco intervention, we provided a function for smokers to asynchronously communicate with a trained tobacco treatment specialist (TTS). Previous studies have not attempted to isolate the effect of asynchronous counseling on smoking cessation. OBJECTIVE: This study aimed to conduct a semiquantitative analysis of TTS-smoker communication and evaluate its association with smoking cessation. METHODS: We conducted a secondary analysis of data on secure asynchronous communication between trained TTSs and a cohort of smokers during a 6-month period. Smokers were able to select their preferred TTS and message them using a secure web-based form. To evaluate whether the TTS used evidence-based practices, we coded messages using the Motivational Interviewing Self-Evaluation Checklist and Smoking Cessation Counseling (SCC) Scale. We assessed the content of messages initiated by the smokers by creating topical content codes. At 6 months, we assessed the association between smoking cessation and the amount of TTS use and created a multivariable model adjusting for demographic characteristics and smoking characteristics at baseline. RESULTS: Of the 725 smokers offered asynchronous counseling support, 33.8% (245/725) messaged the TTS at least once. A total of 1082 messages (TTSs: 565; smokers 517) were exchanged between the smokers and TTSs. The majority of motivational interviewing codes were those that supported client strengths (280/517, 54.1%) and promoted engagement (280/517, 54.1%). SCC code analysis showed that the TTS provided assistance to smokers if they were willing to quit (247/517, 47.8%) and helped smokers prepare to quit (206/517, 39.8%) and anticipate barriers (197/517, 38.1%). The majority of smokers' messages discussed motivations to quit (234/565, 41.4%) and current and past treatments (talking about their previous use of nicotine replacement therapy and medications; 201/565, 35.6%). The majority of TTS messages used behavioral strategies (233/517, 45.1%), offered advice on treatments (189/517, 36.5%), and highlighted motivations to quit (171/517, 33.1%). There was no association between the amount of TTS use and cessation. In the multivariable model, after adjusting for gender, age, race, education, readiness at baseline, number of cigarettes smoked per day at baseline, and the selected TTS, smokers messaging the TTS one or two times had a smoking cessation odds ratio (OR) of 0.8 (95% CI 0.4-1.4), and those that messaged the TTS more than two times had a smoking cessation OR of 1.0 (95% CI 0.4-2.3). CONCLUSIONS: Our study demonstrated the feasibility of using asynchronous counseling to deliver evidence-based counseling. Low participant engagement or a lack of power could be potential explanations for the nonassociation with smoking cessation. Future trials should explore approaches to increase participant engagement and test asynchronous counseling in combination with other approaches for improving the rates of smoking cessation.

Comparison of a Collective Intelligence Tailored Messaging System on Smoking Cessation Between African American and White People Who Smoke: Quasi-Experimental Design.

BACKGROUND: The Patient Experience Recommender System for Persuasive Communication Tailoring (PERSPeCT) is a machine learning recommender system with a database of messages to motivate smoking cessation. PERSPeCT uses the collective intelligence of users (ie, preferences and feedback) and demographic and smoking profiles to select motivating messages. PERSPeCT may be more beneficial for tailoring content to minority groups influenced by complex, personally relevant factors. OBJECTIVE: The objective of this study was to describe and evaluate the use of PERSPeCT in African American people who smoke compared with white people who smoke. METHODS: Using a quasi-experimental design, we compared African American people who smoke with a historical cohort of white people who smoke, who both received up to 30 emailed tailored messages over 65 days. People who smoke rated the daily message in terms of perceived influence on quitting smoking for 30 days. Our primary analysis compared daily message ratings between the two groups using a t test. We used a logistic model to compare 30-day cessation between the two groups and adjusted for covariates. RESULTS: The study included 119 people who smoke (African Americans, 55/119; whites, 64/119). At baseline, African American people who smoke were significantly more likely to report allowing smoking in the home (P=.002); all other characteristics were not significantly different between groups. Daily mean ratings were higher for African American than white people who smoke on 26 of the 30 days (P<.001). Odds of quitting as measured by 30-day cessation were significantly higher for African Americans (odds ratio 2.3, 95% CI 1.04-5.53; P=.03) and did not change after adjusting for allowing smoking at home. CONCLUSIONS: Our study highlighted the potential of using a recommender system to personalize for African American people who smoke. TRIAL REGISTRATION: ClinicalTrials.gov NCT02200432; https://clinicaltrials.gov/ct2/show/NCT02200432. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/jmir.6465.

The 'Take a Break' game: Randomized trial protocol for a technology-assisted brief abstinence experience designed to engage lower-motivated smokers.

BACKGROUND: While smoking continues to be the most preventable cause of mortality in the United States, most current smokers remain not ready to quit at any given time. Engaging these 'motivation phase' smokers with brief experiences to build confidence and practice skills related to cessation could lead to sooner and more successful quit attempts. Increasingly available mobile technology and gamification can be used to provide smokers with accessible and engaging support. METHODS: We describe our protocol for conducting a randomized controlled trial evaluating Take a Break, an mHealth-based smoking pre-cessation challenge designed for smokers not ready to quit. Participants in the intervention receive 1) Motivational Messages, 2) text message Challenge Quizzes, 3) Goal-setting with tobacco treatment specialist, 4) Coping Mini-Games apps, and 5) Recognition and Rewards for participation during a 3-week challenge. Access to coping mini-games and motivational messaging continues for 6-months. Both intervention and comparison group participants receive brief Nicotine Replacement Therapy (NRT) sampling and daily smoking assessment text messages for three weeks. Primary outcomes include number of days abstinent during the challenge, change in patient-reported self-efficacy after the challenge, time to first quit attempt following the challenge, and 7-day point prevalent smoking cessation at six months. CONCLUSION: Take a Break is an innovative approach to engage those not prepared for a quit attempt. Take a Break provides motivation phase smokers with tools and a brief experience to prepare them for a quit attempt, filling a gap in tobacco cessation support and current research.

Nurse-Driven mHealth Implementation Using the Technology Inpatient Program for Smokers (TIPS): Mixed Methods Study.

BACKGROUND: Smoking is the leading cause of preventable death and disease, yet implementation of smoking cessation in inpatient settings is inconsistent. The Technology Inpatient Program for Smokers (TIPS) is an implementation program designed to reach smokers with a mobile health (mHealth) intervention using stakeholder-supported strategies. OBJECTIVE: The purpose of this study was to determine the impact of the TIPS implementation strategies on smoker-level engagement of the mHealth intervention during care transition. METHODS: We examined varying intensities (passive motivational posters only and posters + active nurse-led facilitation) of TIPS strategies on four hospital units located in two sites. Unit-level and smoker-level adoption was monitored during active implementation (30 weeks) and sustainability follow-up (30 weeks). Process measures reflecting the reach, effectiveness, adoption, implementation, maintenance (RE-AIM) framework, stakeholder reported adaptations of strategies, and formative evaluation data were collected and analyzed. RESULTS: For our smoker-level reach, 103 smokers signed up for the mHealth intervention in-hospital, with minimal decline during sustainability follow-up. While posters + nurse facilitation did not lead to higher reach than posters alone during active implementation (27 vs 30 signed up), it did lead to higher engagement of smokers (85.2% vs 73.3% completion of the full 2-week intervention). TIPS strategy adoption and fidelity varied by unit, including adoption of motivational posters (range: weeks 1 and 5), fidelity of posters (0.4% to 16.2% of posters missing per unit weekly) and internal facilitation of nurse training sessions (average of 2 vs 7.5 by site). Variable maintenance costs of the program totaled US $6.63 (US $683.28/103) per smoker reached. Reported family-member facilitation of mHealth sign-up was an observation of unintended behavior. CONCLUSIONS: TIPS is a feasible and low-cost implementation program that successfully engages smokers in an mHealth intervention and sustains engagement after discharge. Further testing of nurse facilitation and expanding reach to patient family and friends as an implementation strategy is needed.

Dissemination and Effectiveness of the Peer Marketing and Messaging of a Web-Assisted Tobacco Intervention: Protocol for a Hybrid Effectiveness Trial.

BACKGROUND: Smoking continues to be the leading preventable cause of death. Digital Interventions for Smoking Cessation (DISCs) are health communication programs accessible via the internet and smartphones and allow for greater reach and effectiveness of tobacco cessation programs. DISCs have led to increased 6-month cessation rates while also reaching vulnerable populations. Despite this, the impact of DISCs has been limited and new ways to increase access and effectiveness are needed. OBJECTIVE: We are conducting a hybrid effectiveness-dissemination study. We aim to evaluate the effectiveness of a machine learning-based approach (recommender system) for computer-tailored health communication (CTHC) over a standard CTHC system based on quit rates and risk reduction. In addition, this study will assess the dissemination of providing access to a peer recruitment toolset on recruitment rate and variability of the sample. METHODS: The Smoker-to-Smoker (S2S) study is a 6-month hybrid effectiveness dissemination trial conducted nationally among English-speaking, current smokers aged ≥18 years. All eligible participants will register for the DISC (Decide2quit) and be randomized to the recommender system CTHC or the standard CTHC, followed by allocation to a peer recruitment toolset group or control group. Primary outcomes will be 7-day point prevalence and risk reduction at the 6-month follow-up. Secondary outcomes include recruitment rate, website engagement, and patient-reported outcomes collected via the 6-month follow-up questionnaire. All primary analyses will be conducted on an intent-to-treat basis. RESULTS: The project is funded from 2017 to 2020 by the Patient Centered Outcomes Research Institute. Enrollment was completed in early 2019, and 6-month follow-ups will be completed by late 2019. Preliminary data analysis is currently underway. CONCLUSIONS: Conducting a hybrid study with both effectiveness and dissemination hypotheses raises some unique challenges in the study design and analysis. Our study addresses these challenges to test new innovations and increase the effectiveness and reach of DISCs. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/14814.

Gamification to Motivate the Unmotivated Smoker: The "Take a Break" Digital Health Intervention.

Objective: Digital health technologies most often reach only those more motivated to engage, particularly when preventive health is targeted. To test whether gamification could be used to engage low-motivation smokers, we conceptualized "Take a Break"-a 3-week technology-assisted challenge for smokers to compete in setting and achieving brief abstinence goals. Materials and Methods: In the feasibility study of the multi-technology Take a Break challenge, low-motivation smokers were given (1) daily motivational messages, (2) brief "challenge quizzes" related to smoking behaviors, (3) a telehealth call to personalize their abstinence goal for the challenge, (4) "coping minigames" to help manage cravings while attempting to achieve their brief abstinence goals, and (5) a leaderboard "webApp," providing comparative feedback on smokers' participation, and allowing for competition. Heterogeneity of engagement was tracked. Results: All 41 smokers initially reported that they were not actively quitting. Over half were employed less than full time (51%), completed less than a 4-year college education (76%), and experienced financial stress (54%). No smokers opted out of the motivational messages, and mean proportion of response to the challenge quizzes was 0.88 (SD = 0.19). Half of the smokers reported using the "coping minigames." Almost all set abstinence goals (78%), with over half lasting 1-2 days (51%); median = 1 day (IQR 1-7). Leaderboard points ranged widely. Conclusions: Rates of smoking in the developed world have declined, and those who remain smokers are complex and have lower motivation to quit. Using a game-inspired challenge, we achieved high levels of engagement from low-motivation smokers.

Exploring Online Asynchronous Counseling With Tobacco Treatment Specialists in the QUIT-PRIMO and National Dental PBRN HI-QUIT Studies: Who Uses It and What Do They Say?

PURPOSE: To describe the content of messages sent by smokers through asynchronous counseling within a Web-based smoking cessation intervention. DESIGN: Qualitative. SETTING: National community-based setting of patients who had been engaged by the medical or dental practices at which they attended or via Google advertisements. PARTICIPANTS: Adults older than 19 years who were current smokers and interested in quitting. Participants throughout the United States referred to a Web-based cessation intervention by their medical or dental provider or by clicking on a Google advertisement. METHODS: We conducted a qualitative review of 742 asynchronous counseling messages sent by 270 Web site users. Messages were reviewed, analyzed, and organized into qualitative themes by the investigative team. RESULTS: The asynchronous counseling feature of the intervention was used most frequently by smokers who were white (87%), female (67%), aged 45 to 54 (32%), and who had at least some college-level education (70%). Qualitative analysis yielded 7 basic themes-Talk about the Process of Quitting, Barriers to Quitting, Reasons to Quit, Quit History, Support and Strategies for Quitting, Quitting with Medication, and Quit Progress. The most common theme was Support and Strategies for Quitting with 255 references among all messages. CONCLUSION: We found rich communication across the spectrum of the quit process, from persons preparing to quit to those who had successfully quit. Asynchronous smoking cessation counseling provides a promising means of social support for smokers during the quit process.