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.

Use of a Rapid Qualitative Method to Inform the Development of a Text Messaging Intervention for People With Serious Mental Illness Who Smoke: Formative Research Study.

BACKGROUND: People with serious mental illness are disproportionately affected by smoking and face barriers to accessing smoking cessation treatments in mental health treatment settings. Text-based interventions are cost-effective and represent a widely accessible approach to providing smoking cessation support. OBJECTIVE: We aimed to identify key factors for adapting text-based cessation interventions for people with serious mental illness who smoke. METHODS: We recruited 24 adults from mental health programs who had a serious mental illness and currently smoked cigarettes or had quit smoking within the past 5 years. We then conducted virtual qualitative interviews between November 2020 and August 2021. Data were analyzed using the rapid thematic analytic approach. RESULTS: We identified the following 3 major themes: (1) interplay between smoking and having a serious mental illness, (2) social contextual factors of smoking in adults with serious mental illness, and (3) smoking and quitting behaviors similar to the general population. Participants reported barriers and facilitators to quitting across the 3 themes. Within the "interplay between smoking and having a serious mental illness" theme, barriers included smoking to manage stress and mental health symptoms, and facilitators to quitting included the awareness of the harm of smoking on mental health and patient-provider discussions on smoking and mental health. In the "social contextual factors of smoking in adults with serious mental illness" theme, barriers included high social acceptability of smoking among peers. Positive support and the combined social stigma of smoking and having a mental health condition outside of peer groups motivated individuals to quit. Some participants indicated that low exposure to other smokers during the COVID-19 pandemic helped them to engage in cessation efforts. In the "smoking and quitting behaviors similar to the general population" theme, barriers included smoking after eating, having coffee, drinking alcohol, and experiencing negative social support, and facilitators included health concerns, improvement in the general quality of life, and use of evidence-based tobacco treatments when available. CONCLUSIONS: People with serious mental illness often smoke to cope with intense emotional states, manage mental health symptoms, or maintain social bonds. Text message content emphasizing equally effective and less harmful ways for stress reduction and mental health symptom management may improve quit rates in individuals with serious mental illness.

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.

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.

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.

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.

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

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

Crave-Out: A Distraction/Motivation Mobile Game to Assist in Smoking Cessation.

BACKGROUND: Smoking is still the number one preventable cause of death. Cravings-an intense desire or longing for a cigarette-are a major contributor to quit attempt failure. New tools to help smokers' manage their cravings are needed. OBJECTIVE: To present a case study of the development process and testing of a distraction/motivation game (Crave-Out) to help manage cravings. METHODS: We used a phased approach: in Phase 1 (alpha testing), we tested and refined the game concept, using a Web-based prototype. In Phase 2 (beta testing), we evaluated the distraction/motivation potential of the mobile game prototype, using a prepost design. After varying duration of abstinence, smokers completed the Questionnaire of Smoking Urge-Brief (QSU-Brief) measurement before and after playing Crave-Out. Paired t tests were used to compare pregame and postgame QSU-Brief levels. To test dissemination potential, we released the game on the Apple iTunes App Store and tracked downloads between December 22, 2011, and May 5, 2014. RESULTS: Our concept refinement resulted in a multilevel, pattern memory challenge game, with each level increasing in difficulty. Smokers could play the game as long as they wanted. At the end of each level, smokers were provided clear goals for the next level and rewards (positive reinforcement using motivational tokens that represented a benefit of quitting smoking). Negative reinforcement was removed in alpha testing as smokers felt it reminded them of smoking. Measurement of QSU-Brief (N=30) resulted in a pregame mean of 3.24 (SD 1.65) and postgame mean of 2.99 (SD 1.40) with an overall decrease of 0.25 in cravings (not statistically significant). In a subset analysis, the QSU-Brief decrease was significant for smokers abstinent for more than 48 hours (N=5) with a pregame mean of 2.84 (SD 1.16) and a postgame mean of 2.0 (SD 0.94; change=0.84; P =.03). Between December 22, 2011, and May 29, 2014, the game was downloaded 3372 times from the App-Store, with 1526 smokers visiting the online resource www.decide2quit.org linked to the game. CONCLUSIONS: Overall, playing the game resulted in small, but nonsignificant decreases in cravings, with changes greater for those had already quit for more than 48 hours. Lessons learned can inform further development. Future research could incorporate mHealth games in multicomponent cessation interventions. TRIAL REGISTRATION: Clinicaltrials.gov NCT00797628; https://clinicaltrials.gov/ct2/show/NCT00797628 (Archived by WebCite at http://www.webcitation.org/6hbJr6LWG).

Identification of Relationships Between Patients Through Elements in a Data Warehouse Using the Familial, Associational, and Incidental Relationship (FAIR) Initiative: A Pilot Study.

BACKGROUND: Over the last several years there has been widespread development of medical data warehouses. Current data warehouses focus on individual cases, but lack the ability to identify family members that could be used for dyadic or familial research. Currently, the patient's family history in the medical record is the only documentation we have to understand the health status and social habits of their family members. Identifying familial linkages in a phenotypic data warehouse can be valuable in cohort identification and in beginning to understand the interactions of diseases among families. OBJECTIVE: The goal of the Familial, Associational, & Incidental Relationships (FAIR) initiative is to identify an index set of patients' relationships through elements in a data warehouse. METHODS: Using a test set of 500 children, we measured the sensitivity and specificity of available linkage algorithm identifiers (eg, insurance identification numbers and phone numbers) and validated this tool/algorithm through a manual chart audit. RESULTS: Of all the children, 52.4% (262/500) were male, and the mean age of the cohort was 8 years old (SD 5). Of the children, 51.6% (258/500) were identified as white in race. The identifiers used for FAIR were available for the majority of patients: insurance number (483/500, 96.6%), phone number (500/500, 100%), and address (497/500, 99.4%). When utilizing the FAIR tool and various combinations of identifiers, sensitivity ranged from 15.5% (62/401) to 83.8% (336/401), and specificity from 72% (71/99) to 100% (99/99). The preferred method was matching patients using insurance or phone number, which had a sensitivity of 72.1% (289/401) and a specificity of 94% (93/99). Using the Informatics for Integrating Biology and the Bedside (i2b2) warehouse infrastructure, we have now developed a Web app that facilitates FAIR for any index population. CONCLUSIONS: FAIR is a valuable research and clinical resource that extends the capabilities of existing data warehouses and lays the groundwork for family-based research. FAIR will expedite studies that would otherwise require registry or manual chart abstraction data sources.