Development and Evaluation of a Data-Driven, Interactive Workshop to Facilitate Communication and Teamwork in Ambulatory Medical Oncology Settings.

Background: While adverse events and toxicities related to cancer drug therapy in the ambulatory oncology setting are common and often rooted in communication challenges, few studies have examined the problems of communication or tested tools to improve communication in this unique, high-risk setting. Objective: To determine the feasibility and acceptability of a virtual interdisciplinary communication Workshop designed to strengthen communication across ambulatory oncology teams members. Methods: Surveys of patients and clinicians in one ambulatory oncology clinic were analyzed and informed the communication intervention: an interdisciplinary virtual Workshop. Workshop evaluation included an implementation survey measure and a structured debrief with Workshop attendees. Results: 87 patients and 56 clinicians participated in pre-workshop surveys that revealed patient satisfaction with timely care and information, yet a range of rating communication experiences with the clinical team, and clinicians perceiving a high amount of organizational safety, yet rated discussion of alternatives to normal work processes low. Survey results guided reflection and discussion within the Workshop. Six clinicians participated in the interactive Workshop. Feasibility and acceptability of the virtual Workshop were supported by formative and summative data, along with suggestions for improvement. Conclusions: The patient and clinician surveys coupled with an interactive virtual Workshop were feasible and acceptable. Implications for Practice: The Workshop identified opportunities for individual- and system-level improvements in clinical team communication. This promising strategy requires replication in larger, diverse practice samples. Foundational: Clinicians accepted an interactive workshop that incorporated clinic-specific data and communication strategies. The program is feasible and acceptable in ambulatory oncology settings.

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.

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.

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.

Provider and clinical setting characteristics associated with tobacco pharmacotherapy dispensed in the Veterans Health Administration.

INTRODUCTION: While initiation rates of tobacco cessation pharmacotherapy have improved both inside and outside the Department of Veteran Affairs (VA), prescribing rates remain low. The objective of this study was to examine correlation of the characteristics of providers, clinics, and facilities with initiation of tobacco cessation pharmacotherapy. METHODS: This retrospective, observational study used VA outpatient electronic medical record data from federal fiscal year 2011. Logistic regression models estimated the adjusted odds ratio associated with provider characteristics for pharmacotherapy initiation. RESULTS: For the 639507 veterans who used tobacco, there were 30388 providers caring for them. Younger (p<0.001) and female (p<0.001) providers were more likely to initiate tobacco cessation pharmacotherapy. Compared to physicians, pharmacists were 74% more likely to initiate pharmacotherapy, while all groups of nurses were 5-8% and physicians' assistants were 12% less likely (p<0.001). Compared to those seen in primary care clinics, patients assessed in substance use treatment clinics were 16% more likely to have pharmacotherapy initiated (p<0.001), while those in psychiatry were 10% less likely (p<0.001), and those in outpatient surgery were 39% less likely to initiate pharmacotherapy (p<0.001). Compared to almost all other classes of VA facilities, patients seen in primary care community-based outpatient clinics (CBOCs) were 7-28% more likely to initiate pharmacotherapy (p<0.0001). CONCLUSIONS: While the VA is at the leading edge of providing tobacco cessation pharmacotherapy, targeting quality improvement efforts towards providers, clinics, and facilities with low prescribing rates will be essential to continue the declining rates of tobacco use among VA patients.

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.

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.

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.

Interest in and barriers to participation in a Facebook-delivered weight loss program among female cancer survivors with overweight or obesity.

BACKGROUND: Although excess body weight is linked to post-treatment complications for cancer survivors, obesity rates have increased rapidly among adult cancer survivors. Innovative approaches to weight loss programs, such as via social media, are needed to engage female cancer survivors. The purpose of this study is to explore important components of a Facebook-delivered weight loss program for female cancer survivors. METHODS: Female cancer survivors who are overweight or obese and finished active treatment completed a web-based, mixed-methods survey. RESULTS: Participants (N=96) were on average 54.3±9.6 years old, 89% white, 66% obese, and 87% tried to lose weight in the last year. Health concerns were the most important reason (88%) for wanting to lose weight. Barriers to weight loss included other health issues (52%) and perceived sacrifice/burden of weight loss process (35%). Qualitative themes for barriers included inability to make dietary changes (19%), lack of motivation (18%), and physical limitations (13%). Participants were most interested in a weight loss program delivered via Facebook (81%), led by a weight loss counselor (78%), provided healthy recipes (73%) and exercise videos (72%). Qualitative themes included information on cancer treatment effects (25%), calorie tracker (21%), and exercise modifications (17%). Qualitatively, concerns about weight loss included fear of cancer recurrence (20%) and lack of confidence in weight loss efforts (17%). CONCLUSIONS: While female cancer survivors are interested in a Facebook-delivered weight loss program, additional research needs to address customization and delivery to address specific barriers experienced by cancer survivors.

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.

Enhancing behavioral change among lung cancer survivors participating in a lifestyle risk reduction intervention: a qualitative study.

PURPOSE: Early detection and improved treatment have increased lung cancer survival. Lung cancer survivors have more symptom distress and lower function compared with other cancer survivors; however, few interventions are available to improve health-related quality of life (HR-QOL). Lifestyle risk reduction interventions have improved HR-QOL in other cancer survivors. The purpose of this study was to explore lung cancer survivor perspectives on making behavioral changes in the context of a lifestyle risk reduction intervention. METHODS: Twenty-two lung cancer survivors participated in interviews after completing the Healthy Directions (HD) intervention. Interviews were audiotaped, transcribed, and analyzed using inductive content analysis. Demographic and clinical characteristics were gathered through a survey and analyzed using descriptive statistics. RESULTS: Five main themes were identified: (1) the diagnosis was a motivator for behavior change, (2) participants had to deal with disease consequences, (3) the coach provided guidance, (4) strategies for change were initiated, and (5) social support sustained behavioral changes. Other important subthemes were the coach helped interpret symptoms, which supported self-efficacy and goal setting, and survivors employed self-monitoring behaviors. Several participants found the recommended goals for physical activity were difficult and were discouraged if unable to attain the goal. Findings underscore the need for individualized prescriptions of physical activity, especially for sedentary survivors. CONCLUSIONS: Lung cancer survivors described the benefits of coaching to enhance their engagement in behavioral change. Additional research is needed to validate the benefit of the HD intervention to improve HR-QOL among this vulnerable and understudied group of cancer survivors.

SBM recommends policy support to reduce smoking disparities for sexual and gender minorities.

The Society of Behavioral Medicine supports the inclusion of gender and sexual minorities in all local, state, and national tobacco prevention and control activities. These activities include surveillance of tobacco use and cessation activities, targeted outreach and awareness campaigns, increasing access to culturally appropriate tobacco use dependence treatments, and restricting disproportionate marketing to lesbian, gay, bisexual, and transgender communities by the tobacco industry, especially for mentholated tobacco products.

Feasibility and acceptability of "healthy directions" a lifestyle intervention for adults with lung cancer.

OBJECTIVE: The aims of this feasibility study of an adapted lifestyle intervention for adults with lung cancer were to (1) determine rates of enrollment, attrition, and completion of 5 nurse-patient contacts; (2) examine demographic characteristics of those more likely to enroll into the program; (3) determine acceptability of the intervention; and (4) identify patient preferences for the format of supplemental educational intervention materials. METHODS: This study used a single-arm, pretest and posttest design. Feasibility was defined as ≥20% enrollment and a completion rate of 70% for 5 nurse-patient contact sessions. Acceptability was defined as 80% of patients recommending the program to others. Data was collected through electronic data bases and phone interviews. Descriptive statistics, Fisher's exact test and Wilcoxon rank sum test were used for analyses. RESULTS: Of 147 eligible patients, 42 (28.6%) enrolled and of these, 32 (76.2%) started the intervention and 27 (N = 27/32; 84.4%; 95% CI, 67.2%-94.7%) completed the intervention. Patients who were younger were more likely to enroll in the study (P = .04) whereas there were no significant differences by gender (P = .35). Twenty-three of the 24 (95.8%) participants' contacted posttest recommended the intervention for others. Nearly equal numbers of participants chose the website (n = 16, 50%) vs print (n = 14, 44%). CONCLUSION: The intervention was feasible and acceptable in patients with lung cancer. Recruitment rates were higher and completion rates were similar as compared to previous home-based lifestyle interventions for patients with other types of cancer. Strategies to enhance recruitment of older adults are important for future research.

Virtual Patient Technology: Engaging Primary Care in Quality Improvement Innovations.

BACKGROUND: Engaging health care staff in new quality improvement programs is challenging. OBJECTIVE: We developed 2 virtual patient (VP) avatars in the context of a clinic-level quality improvement program. We sought to determine differences in preferences for VPs and the perceived influence of interacting with the VP on clinical staff engagement with the quality improvement program. METHODS: Using a participatory design approach, we developed an older male smoker VP and a younger female smoker VP. The older male smoker was described as a patient with cardiovascular disease and was ethnically ambiguous. The female patient was younger and was worried about the impact of smoking on her pregnancy. Clinical staff were allowed to choose the VP they preferred, and the more they engaged with the VP, the more likely the VP was to quit smoking and become healthier. We deployed the VP within the context of a quality improvement program designed to encourage clinical staff to refer their patients who smoke to a patient-centered Web-assisted tobacco intervention. To evaluate the VPs, we used quantitative analyses using multivariate models of provider and practice characteristics and VP characteristic preference and analyses of a brief survey of positive deviants (clinical staff in practices with high rates of encouraging patients to use the quit smoking innovation). RESULTS: A total of 146 clinical staff from 76 primary care practices interacted with the VPs. Clinic staff included medical providers (35/146, 24.0%), nurse professionals (19/146, 13.0%), primary care technicians (5/146, 3.4%), managerial staff (67/146, 45.9%), and receptionists (20/146, 13.7%). Medical staff were mostly male, and other roles were mostly female. Medical providers (OR 0.031; CI 0.003-0.281; P=.002) and younger staff (OR 0.411; CI 0.177-0.952; P=.038) were less likely to choose the younger, female VP when controlling for all other characteristics. VP preference did not influence online patient referrals by staff. In high-performing practices that referred 20 or more smokers to the ePortal (13/76), the majority of clinic staff were motivated by or liked the virtual patient (20/26, 77%). CONCLUSIONS: Medical providers are more likely motivated by VPs that are similar to their patient population, while nurses and other staff may prefer avatars that are more similar to them.

Society of Behavioral Medicine supports implementation of high quality lung cancer screening in high-risk populations.

The Society of Behavioral Medicine (SBM) supports the United States Preventive Services Task Force (USPSTF) recommendation of low-dose computed tomography (LDCT) screening of the chest for eligible populations to reduce lung cancer mortality. Consistent with efforts to translate research findings into real-world settings, SBM encourages health-care providers and health-care systems to (1) integrate evidence-based tobacco treatment as an essential component of LDCT-based lung cancer screening, (2) examine the structural barriers that may impact screening uptake, and (3) incorporate shared decision-making as a clinical platform to facilitate consultations and engagement with individuals at high risk for lung cancer about the potential benefits and harms associated with participation in a lung cancer screening program. We advise policy makers and legislators to support screening in high-risk populations by continuing to (1) expand access to high quality LDCT-based screening among underserved high-risk populations, (2) enhance cost-effectiveness by integrating evidence-based tobacco treatments into screening in high-risk populations, and (3) increase funding for research that explores implementation science and increased public awareness and access of diverse populations to participate in clinical and translational research.