Effectiveness of Peer-Support Interventions for Smoking Cessation: A Systematic Review and Meta-analysis.

INTRODUCTION: Peer support has been recommended to promote smoking cessation, but results from prior meta-analyses have not established its efficacy. We conducted a systematic review and meta-analysis to assess current evidence and identify potential modifiers of efficacy. METHODS: Randomized controlled trials of peer-support interventions with a smoking cessation outcome were identified in January 2022 from PubMed and references listed in identified studies. The meta-analysis outcome measure was mean risk ratio (RR, 95% confidence interval [CI]) for abstinence at the longest follow-up timepoint between 3 and 9 months from baseline. Potential modifiers tested were peer smoking status (former, current, or unknown), follow-up timepoint, abstinence measure, and cumulative engagement time between peers and smokers ("dose"). Studies were assessed for risk of bias and certainty of evidence. RESULTS: We identified 16 trials, which varied in abstinence effect size (RR 0.61-3.07), sample size (23-2121), dose (41-207 minutes), and follow-up timepoint (<1-15 months). Across 15 trials with follow-up between 3 and 9 months (N = 8573 participants; 4565 intervention, 4008 control), the pooled Mantel-Haenszel RR was 1.34 (95% CI: 1.11-1.62). Effect sizes were greatest among interventions with formerly smoking peers (RR 1.43, 95% CI 1.17-1.74; five trials). We found positive effects for follow-up timepoints ≥3 months but no effect of intervention dose. The overall quality of evidence was deemed "very low." CONCLUSIONS: Peer-support interventions increased smoking abstinence. There remains a lack of consensus about how to define a peer. Intervention features such as peer smoking status appear to have explanatory power. Additional high-quality and more comparable trials are needed. IMPLICATIONS: This study reviewed the latest evidence from randomized controlled trials and found that peer-support interventions enhance smoking cessation. Efficacy varies with key intervention features such as peer smoking status and follow-up timepoint, which may be used to facilitate development of more effective peer-support interventions. Future trials and reviews would benefit from careful consideration and clear reporting of peer smoking status, length of follow-up, abstinence measures, and intervention dose.

Pilot Randomized Controlled Trial of Feasibility, Acceptability, and Preliminary Efficacy of a Web-Based Physical Activity and Sedentary Time Intervention for Survivors of Physical Inactivity-Related Cancers.

BACKGROUND: This pilot study explored the feasibility, acceptability, and usability of a web-based intervention for survivors of physical inactivity-related cancers through a two-arm, 12-week randomized controlled trial. Secondarily, this study tested the change in physical activity (PA) and sedentary time with intervention exposure. METHODS: Prior to randomization to the intervention (n = 45) or behavior "as usual" wait-listed control (n = 40) groups, participants completed baseline surveys and an accelerometer protocol. The intervention focused on increasing PA and decreasing sedentary time through social cognitive theory techniques. Follow-up acceptability/usability surveys (intervention group only) and accelerometers were sent after the intervention period. Information on intervention completion, adverse events, and user statistics were collected to determine feasibility. Median login time and mean acceptability/usability scores were calculated. RESULTS: Participants (mean age = 60 ± 7 years) included female (n = 80, 94%) and male survivors of breast (82%), colon (6%), endometrial (6%), bladder (4%), and kidney (2%) cancer. Seventy-eight (91.7%) participants returned partially or fully complete post-intervention data. There were no reported injuries or safety concerns. Intervention participants logged into the website for a total of 95 min (Q1, Q3 = 11, 204). System usability scores (72 ± 3) indicated above average usability of the website. Changes in time spent active and sedentary were not statistically significantly different between groups (p = 0.45), but within-group changes suggested intervention group participants spent more time active and less time sedentary after the intervention. CONCLUSION: Results of this pilot study suggest its feasibility and acceptability for survivors of several inactivity-related cancers. Additional research to determine long-term efficacy is warranted. This low-cost online-only intervention has the potential to have a very broad reach. TRIAL REGISTRATION: Clinical Trials Number: NCT03983083. Date registered: June 12th, 2019.

Peer Mentoring and Automated Text Messages for Smoking Cessation: A Randomized Pilot Trial.

INTRODUCTION: Text-messaging programs for smoking cessation, while efficacious, have high dropout rates. To address this problem, we developed and tested the feasibility and early efficacy of a peer-mentoring intervention for smoking cessation provided by former smokers. METHODS: Adult US smokers were recruited nationally into a randomized pilot trial (N = 200), comparing 6-8 weeks of automated text-messaging support (SmokefreeTXT) and automated text support plus personalized texts from a peer mentor who formerly smoked. The primary outcome was biochemically verified 7-day point-prevalence abstinence at 3 months post-quit date, assessed on an intention-to-treat basis (missing = smoking). Self-reported abstinence, program acceptability, user engagement, and user perceptions were also assessed. RESULTS: Biochemically verified abstinence at 3 months was 7.9% (8/101) in the intervention group and 3.0% (3/99) in the control group (adjusted difference 6.5, 95% CI = 0.7% to 12.3%; p = .03). Self-reported abstinence at 3 months was 23.8% (24/101) in the intervention group versus 13.1% (13/99) in the control group (adjusted difference 12.7, 95% CI = 1.2% to 24.1%; p = .03). The intervention had a positive but insignificant effect on overall satisfaction (78.3% vs. 72.9% control group, p = .55). Having a mentor did not significantly alter duration of interaction with the program nor the proportion unsubscribing, although the intervention group reset their quit date with greater frequency (p < .01) and sent more messages (p < .01). CONCLUSIONS: Peer mentoring combined with automated text messages was feasible and acceptable and increased smoking abstinence compared with automated messages alone. The results highlight the promise of this intervention approach and the need for a full-scale evaluation. IMPLICATIONS: Providing quitting assistance by automated text messaging has been shown to increase smoking abstinence. Yet, dropout rates in text-messaging programs are high. No studies have tested the effectiveness of peer mentors who are former smokers as part of a text-messaging intervention, although they represent a promising way to retain, engage, and support smokers. This randomized pilot trial suggests that peer mentors can complement automated text-messaging programs to promote smoking abstinence.

Investigating relationships among cancer survivors' engagement in an online support community, social support perceptions, well-being, and moderating effects of existing (offline) social support.

PURPOSE: Socially supportive relationships help cancer survivors cope with their diagnosis and may improve quality of life; however, many survivors report unmet support and information needs. Online communities of survivors may address these needs, but research on their benefits have been equivocal. This cross-sectional, self-report study investigated relationships among cancer survivors' level of engagement in an online survivor community (The American Cancer Society Cancer Survivors Network®; CSN), perceptions of emotional/informational support available from online communities ("online social support"), well-being, and moderating effects of "offline social support." METHODS: Participants were 1255 registered users of the CSN who completed surveys between 2013 and 2014. Three types of engagement with the CSN-social/communal, interpersonal communication, and informational/search engagement-were identified through principal components analysis. Regression analyses examined hypotheses. RESULTS: More frequent social/communal and interpersonal communication engagement were associated with increased online social support (p < .0001), and the relationship between interpersonal communication engagement and online social support was strongest for survivors reporting lower offline social support (interaction ß = - .35, p < .001). Greater online social support was associated with increased well-being, but only among survivors reporting low offline social support (interaction ß = - .35, p < .0001). CONCLUSIONS: Engagement in online survivor communities may increase support perceptions that promote well-being, but benefits may accrue more to survivors reporting low offline social support. IMPLICATIONS FOR CANCER SURVIVORS: Newly diagnosed cancer survivors, particularly those with unmet emotional/informational support needs, should be given the opportunity to communicate with other survivors through online survivor support networks.

Trust of Information about Tobacco and E-Cigarettes from Health Professionals versus Tobacco or Electronic Cigarette Companies: Differences by Subgroups and Implications for Tobacco Messaging.

Smoking behavior may be influenced by perceived trust of information from tobacco and e-cigarette companies about their products. The purpose of this study was to identify sociodemographic subgroups with more trust in tobacco product (tobacco and e-cigarette) companies than health professionals and explore associations between this relative trust and tobacco product use.Health Information National Trends Survey (HINTS 4, FDA Cycle) data were analyzed (N = 3,738). Two relative trust measures were developed identifying respondents who trust tobacco companies or e-cigarette companies as much as or more than health professionals for information about the health effects of tobacco products or e-cigarettes versus those who place more trust in health professionals. Dependent variables were smoking status (current, former, never) and e-cigarette use (ever, never). Bivariate analyses and multivariable logistic regressions were conducted in SAS 9.4 using jackknife replicate weights.Respondents who trusted tobacco or e-cigarette companies as much as or more than health professionals were disproportionately from racial/ethnic minority groups or had low levels of income or education (all p < 0.05). Relative trust was not associated with smoking status. After controlling for demographics, respondents who trusted e-cigarette companies as much as or more than health professionals had 87% greater odds (95% CI: 1.16, 3.00) of e-cigarette use, compared to respondents who placed higher trust in health professionals.Findings suggest that population subgroups with greater trust in e-cigarette companies relative to health professionals are more prone to e-cigarette use. Targeted communication strategies may be needed for underserved populations and to counter messaging from e-cigarette companies.

Smoking versus quitting and fear of cancer recurrence 9 years after diagnosis in the American Cancer Society's Longitudinal Study of Cancer Survivors-I (SCS-I).

BACKGROUND: Fear of cancer recurrence (FCR) adversely affects quality of life. Cigarette smoking increases the risk of recurrence and may exacerbate FCR among survivors who smoke. FCR also may motivate quitting, but research on whether quitting reduces long-term survivors' FCR is lacking. Among long-term survivors of various cancers, the authors investigated relationships between quitting (vs smoking) and FCR, controlling for sociodemographic, cancer-related, and health-related variables. METHODS: Data from the American Cancer Society's Longitudinal Study of Cancer Survivors-I were used in generalized estimating equations to compare FCR at 3 waves (T1-T3) after diagnosis between 2 groups; survivors who reported current smoking (n = 196) approximately 9 years after diagnosis (at T3) or who, based on T3 recall of quitting age, had quit smoking after diagnosis (n = 97). T3 cross-sectional analyses among current smokers examined associations of FCR with smoking level and intentions of quitting. RESULTS: A significant smoking status × time interaction (P = .003) indicated that only quitters experienced decreases in FCR from T1 to T3 (P = .007). At T3, FCR was significantly lower among quitters than among current smokers (P = .05), and current smokers reported that FCR caused more functioning impairments (eg, disruption of relationships, everyday activities, mood) than quitters (P = .001). Cross-sectional analyses (T3) among smokers found that heavier smoking predicted less attempts to cope with FCR (P = .04) and that reassurance behaviors (eg, self-examination for cancer) predicted stronger quitting intentions (P = .02). CONCLUSIONS: Quitting smoking lowers FCR, and FCR may disrupt functioning among continuing smokers. Interventions for FCR should be multimodal and should treat both psychological distress and health-related behaviors such as smoking.

The impact of psychosocial characteristics in predicting smoking cessation in long-term cancer survivors: A time-to-event analysis.

OBJECTIVE: Smoking poses significant health risks to cancer survivors. Cancer survivorship may heighten psychological distress and reduce social support and health-related quality of life (HRQOL) for years after diagnosis, which could inhibit long-term successful smoking cessation. Understanding longitudinal associations between these psychosocial characteristics and successful cessation could help clinicians tailor cessation interventions for their patients. METHODS: Time-to-event analyses using data from the American Cancer Society Study of Cancer Survivors-I (SCS-I)-a longitudinal nationwide study-examined the relationship of psychosocial characteristics with cessation likelihood and amount of time from diagnosis to quitting in cancer survivors diagnosed 7 to 10 years prior. RESULTS: Cancer survivors with high physical HRQOL were more likely to quit smoking within 10 years from cancer diagnosis than survivors with low physical HRQOL, controlling for cancer type and number of comorbid conditions at baseline (HR = 1.96; 95% CI: 1.10-2.70; P = .02). Survivors with high physical HRQOL also took less time to quit than survivors with low physical HRQOL. Survivors of tobacco-related cancers with low physical HRQOL were the least likely group to quit. No significant relationships between other psychosocial predictors and cessation outcomes were observed. CONCLUSIONS: Smoking cessation programs are needed for all cancer survivors who smoke, but survivors with low physical HRQOL 1 year after diagnosis may need more intensive long-term smoking cessation interventions with multiple check-in points after smoking relapses. Cessation interventions that include strategies to mitigate physical symptoms in those with poor physical HRQOL deserve consideration in research and practice.

Educational attainment & quitting smoking: A structural equation model approach.

In the United States, disparities in smoking prevalence and cessation by socioeconomic status are well documented, but there is limited research on reasons why and none conducted in a national sample assessing multiple potential mechanisms. We identified smoking and cessation-related behavioral and environmental variables associated with both educational attainment and quitting success. We used a structural equation model of cross-sectional data from respondents ≥25 years from the United States 2010-2011 Tobacco Use Supplement-Current Population Survey. Quitting success was defined as former (n = 2607) versus continuing smokers (n = 7636); categories of educational attainment were ≤high school degree, some college/college degree, and advanced degree. Results indicated that using nicotine replacement therapy (NRT) >1 month and having a home smoking restriction were associated with both educational attainment and quitting success. Those with lower educational attainment versus those with an advanced degree were less likely to report using NRT >1 month (≤high school: ß = -0.50, p < 0.001; college: ß = -0.24, p = 0.019). Use of NRT >1 month, in turn, was positively associated with quitting success (ß = 0.25, p < 0.001). Those with lower educational attainment were also less likely to report a home smoking restriction (≤high school: ß = -0.42, p < 0.001; college: ß = -0.21, p = 0.009). Having a home smoking restriction was positively associated with quitting success (ß = 0.50, p < 0.001). Results were similar with income substituted for education. Using NRT >1 month and having a home smoking restriction are two strategies that may explain the association between low education and lower cessation success; these strategies should be further tested for their potential ability to mitigate this association.

Randomised controlled trial of stand-alone tailored emails for smoking cessation.

INTRODUCTION: Digital technology has created opportunities for delivering smoking cessation assistance at the population level. However, the efficacy of sending multiple, automated, tailored emails providing motivation, support and information for quitting is unknown. METHODS: Smokers planning to quit (n=1070) were randomly assigned to (1) 27 tailored cessation emails (deluxe email group (DEG)), (2) 3 to 4 tailored emails with links to downloadable booklets (basic email group (BEG)) or (3) a single non-tailored email (single email group (SEG)). All emails included links to quitting resources. Self-reported 7-day point-prevalence abstinence was assessed at 1 month, 3 months and 6 months postenrolment. RESULTS: Across follow-ups, abstinence was significantly greater for smokers in the DEG (34%) compared with the SEG (25.8%; OR=1.47, 95% CI 1.07 to 2.02, p=0.02) but there was no difference between the BEG (30.8%) and the SEG (p=0.13). Results were independent of baseline cigarettes per day, interest in quitting, smoker in household, use of nicotine replacement therapy (NRT) or varenicline and gender, themselves associated with abstinence (ps<0.05). Missing=smoking and multiple imputation analyses based on 25 data sets corroborated results. Participants in the DEG were also more likely to use non-medication aids (eg, quit smoking website, cessation class/clinic) compared with the SEG (OR=1.34, p=0.02, CI 1.06 to 1.71), but use of these or NRT by the 4-week follow-up (vs no use) increased abstinence across follow-ups primarily for those in the SEG. CONCLUSIONS: Stand-alone tailored, multiple emails providing support, motivation and information during a quit attempt are an easily deployable, inexpensive mode of providing effective cessation assistance to large numbers of smokers planning to quit.

To Text or Not to Text? Technology-based Cessation Communication Preferences among Urban, Socioeconomically Disadvantaged Smokers.

Objective: Effective smoking cessation interventions are needed to reduce tobacco-related disparities. Communication technology-based interventions are increasingly being employed to help smokers quit, with controlled research demonstrating efficacy of text messaging and email in increasing abstinence. Understanding preferences for such strategies among socioeconomically disadvantaged smokers can inform targeted intervention planning. The aims of this study were to: 1) examine socioeconomically disadvantaged smokers' use of and access to communication technology; and 2) elucidate preferences for receiving quitting information and support via email and text message. Design: This cross-sectional, mixed-methods study collected data from a self-administered survey and focus groups in September 2017. Participants: A community-based, sample of 15 predominantly African American, socioeconomically disadvantaged smokers aged 21-64 years. Results: Smartphone ownership was high, although use of communication-based cessation resources such as web sites and smartphone apps was low. Four themes emerged relevant to preferences for receiving quitting information and support via email and text message: access, appropriateness, intended use, and satisfaction. Although initially participants were mixed in their preferences for receiving emails vs texts, 80% preferred emails over texts when presented with sample emails and text messages containing cessation information. Conclusions: In this sample of socioeconomically disadvantaged smokers, emails were preferred over text messages for smoking cessation assistance. Although both email and text message strategies may be acceptable to socioeconomically disadvantaged smokers generally, issues such as access and intended use should be considered to inform specific disparity-reducing intervention approaches.

Topic Modeling of Smoking- and Cessation-Related Posts to the American Cancer Society's Cancer Survivor Network (CSN): Implications for Cessation Treatment for Cancer Survivors Who Smoke.

INTRODUCTION: Smoking is a risk factor in at least 18 cancers, and approximately two-thirds of cancer survivors continue smoking following diagnosis. Text mining of survivors' online posts related to smoking and quitting could inform strategies to reduce smoking in this vulnerable population. METHODS: We identified posts containing smoking/cessation-related keywords from the Cancer Survivors Network (CSN), an online cancer survivor community of 166 000 members and over 468 000 posts since inception. Unsupervised topic model analysis of posts since 2000 using Latent Dirichlet Allocation extracted 70 latent topics which two subject experts inspected for themes based on representative terms. Posterior analysis assessed the distribution of topics within posts, and the range of themes discussed across posts. RESULTS: Less than 1% of posts (n = 3998) contained smoking/cessation-related terms, and covered topics related to cancer diagnoses, treatments, and coping. The most frequent smoking-related topics were quit smoking methods (5.4% of posts), and the environment for quitters (2.9% of posts), such as the stigma associated with being a smoker diagnosed with cancer and lack of empathy experienced compared to nonsmokers. Smoking as a risk factor for one's diagnosis was a primary topic in only 1.7% of smoking/cessation-related posts. CONCLUSIONS: The low frequency of smoking/cessation-related posts may be due to expected criticism/stigma for smoking but may also suggests a need for health care providers to address smoking and assist with quitting in the diagnostic and treatment process. Topic model analysis revealed potential barriers that should be addressed in devising clinical or population-level interventions for cancer survivors who smoke. IMPLICATIONS: Although smoking is a major risk factor for cancer, little is known about cancer patients' or survivors' views or concerns about smoking and quitting. This study used text mining of posts to an online community of cancer patients and survivors to investigate contexts in which smoking or quitting is discussed. Results indicated that smoking and quitting discussions were relatively rare, but nevertheless provide insight into barriers that may need to be addressed in cessation interventions for survivors.

Evaluation of a Novel Difficulty of Smoking Cessation Phenotype Based on Number of Quit Attempts.

BACKGROUND: Numerous studies have sought to identify genes that influence the ability to quit smoking, but none found any that are consistently associated with smoking cessation. METHODS: We developed a novel difficulty of quitting smoking phenotype based on the extremes of the number of quit attempts needed to achieve successful abstinence: Easy quitters were defined as having achieved long-term (>1 year) abstinence after their first quit attempt and difficult quitters as having reported 10 or more quit attempts. We conducted a two-stage study to determine if this phenotype could be useful for identifying single nucleotide polymorphisms (SNPs) that influence smoking cessation. In stage 1, 82 SNPs in 26 genes involved in nicotine signaling and metabolism were genotyped in 1357 easy quitters and 1321 difficult quitters from Cancer Prevention Study 3 (CPS-3). In stage 2, the 11 SNPs associated with difficult quitting in stage 1 (p < .1) were genotyped in an independent sample of 1300 easy quitters and 1299 difficult quitters from CPS-3. RESULTS: Three of 11 SNPs (HTR1B rs6298, NR4A2 rs834829, and CYP2A65 rs8192729) were significantly associated with the difficult quitting phenotype in stage 2 (p < .05). In addition, a polygenic risk score based on the 11 SNPs identified in stage 1 was significantly associated with the difficult quitting phenotype in stage 2 (odds ratio = 1.08, 95% confidence interval: 1.03-1.14 per quintile, p trend = 4.5×10-3). CONCLUSIONS: Using a novel difficulty of quitting phenotype, three gene variants and a polygenic risk score based on 11 SNPs were found to be significantly associated with smoking cessation. IMPLICATIONS: Our results provide evidence that a difficulty of quitting smoking phenotype based on the extremes of number of quit attempts could be a useful tool for identifying genetic variants that influence difficulty of smoking cessation. Knowledge of these genetic variants will indicate biological pathways that could be targeted for the development of novel smoking cessation aids and could be used to determine which smokers are most likely to benefit from such smoking cessation aids.

Afraid and tired: A longitudinal study of the relationship between cancer-related fatigue and fear of cancer recurrence in long-term cancer survivors.

OBJECTIVE: Cancer-related fatigue (CRF) and fear of cancer recurrence (FCR) are two common concerns experienced by cancer survivors. However, the relationship between these two concerns is poorly understood, and whether CRF and FCR influence each other over time is unclear. METHODS: Data were from a national, prospective, longitudinal study, the American Cancer Society's Study of Cancer Survivors-I (SCS-I). Surveys were completed by 1395 survivors of 10 different cancer types at three time-points, including assessment 1.3 years (T1), 2.2 years (T2) and 8.8 years (T3) following their cancer diagnosis. CRF was assessed using the fatigue-inertia subscale of the Profile of Mood States, and FCR by the FCR subscale of the Cancer Problems in Living Scale. Multiple group random intercepts cross-lagged panel models investigated prospective associations between CRF and FCR. RESULTS: For younger participants (at or below median age of 55 years, n = 697), CRF at T1 and T2 marginally and significantly predicted FCR at T2 and T3, respectively, but no lagged effects of FCR on subsequent CRF were observed. Cross-lagged effects were not observed for survivors over 55 years of age. CONCLUSION: Both CRF and FCR are debilitating side effects of cancer and its treatments. Given that CRF may be predictive of FCR, it possible that early detection and intervention for CRF could contribute to lowering FCR severity.

Barriers to helping patients quit smoking: Lack of knowledge about cessation methods, E-cigarettes, and why nurse practitioners and physician assistants can help.

Objectives: Health care settings are ideal for addressing patients' smoking and quitting, but barriers may limit providers' assistance with cessation, including lack of knowledge about newer devices being used by some smokers to quit (e.g., e-cigarettes). Cessation practices among nurse practitioners (NPs) and physician assistants (PAs) are also unknown. Study design: Cross-sectional. Methods: Participants (N = 459) were 151 oncologists, 150 primary care physicians (PCPs), 98 nurse practitioners (NPs), and 60 physician assistants (PAs) recruited from a national online panel who completed an online survey. Results: Four barriers were common across specialties: "patient doesn't want to quit, and it is their decision," "smoking is not reason for patient's visit; must treat the immediate problem first," "patient wants to quit on their own," and "lack of effective methods available." While a majority of oncologists (58%) were aware of free telephone counseling for cessation, only 29% of NPs were aware. Perceived knowledge of e-cigarettes was low. Greater comfort treating patients' smoking predicted greater frequency of engagement in 4 of 5 general cessation practices (ßs = 0.15-0.26, all p ≤ .001). NPs and PAs more frequently asked patients about smoking and e-cigarette use compared to oncologists, but oncologists more frequently referred patients to effective quitting resources (e.g., quitlines). Conclusions: NPs and PAs may be uniquely positioned to provide cessation assistance, but providers need more education on currently available, effective cessation methods, and about e-cigarettes. Addressing patient resistance to offers of cessation services and improving clinical workflows to enhance cessation service provision should be investigated in future research.

Developing a Game (Inner Dragon) Within a Leading Smartphone App for Smoking Cessation: Design and Feasibility Evaluation Study.

BACKGROUND: Several stand-alone smartphone apps have used serious games to provide an engaging approach to quitting smoking. So far, the uptake of these games has been modest, and the evidence base for their efficacy in promoting smoking cessation is still evolving. The feasibility of integrating a game into a popular smoking cessation app is unclear. OBJECTIVE: The aim of this paper was to describe the design and iterative development of the Inner Dragon game within Smoke Free, a smartphone app with proven efficacy, and the results of a single-arm feasibility trial as part of a broad program that seeks to assess the effectiveness of the gamified app for smoking cessation. METHODS: In phase 1, the study team undertook a multistep process to design and develop the game, including web-based focus group discussions with end users (n=15). In phase 2, a single-arm study of Smoke Free users who were trying to quit (n=30) was conducted to assess the feasibility and acceptability of the integrated game and to establish the feasibility of the planned procedures for a randomized pilot trial. RESULTS: Phase 1 led to the final design of Inner Dragon, informed by principles from psychology and behavioral economics and incorporating several game mechanics designed to increase user engagement and retention. Inner Dragon users maintain an evolving pet dragon that serves as a virtual avatar for the users' progress in quitting. The phase-2 study established the feasibility of the study methods. The mean number of app sessions completed per user was 13.8 (SD 13.1; median 8; range 1-46), with a mean duration per session of 5.8 (median 1.1; range 0-81.1) minutes. Overall, three-fourths (18/24, 75%) of the participants entered the Inner Dragon game at least once and had a mean of 2.4 (SD 2.4) sessions of game use. The use of Inner Dragon was positively associated with the total number of app sessions (correlation 0.57). The mean satisfaction score of participants who provided ratings (11/24, 46%) was 4.2 (SD 0.6) on a 5-point scale; however, satisfaction ratings for Inner Dragon were only completed by 13% (3/24) of the participants. CONCLUSIONS: Findings supported further development and evaluation of Inner Dragon as a beneficial feature of Smoke Free. The next step of this study is to conduct a randomized pilot trial to determine whether the gamified version of the app increases user engagement over a standard version of the app.

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

Background: The risk of infection and severity of illness by SARS-CoV-2 infection is elevated for people who smoke cigarettes and may motivate quitting. Organic public conversations on Twitter about quitting smoking could provide insight into quitting motivations or behaviors associated with the pandemic. Objective: This study explored key topics of conversation about quitting cigarette smoking and examined their trajectory during 2018-2020. Methods: Topic model analysis with latent Dirichlet allocation (LDA) identified themes in US tweets with the term "quit smoking." The model was trained on posts from 2018 and was then applied to tweets posted in 2019 and 2020. Analysis of variance and follow-up pairwise tests were used to compare the daily frequency of tweets within and across years by quarter. Results: The mean numbers of daily tweets on quitting smoking in 2018, 2019, and 2020 were 133 (SD 36.2), 145 (SD 69.4), and 127 (SD 32.6), respectively. Six topics were extracted: (1) need to quit, (2) personal experiences, (3) electronic cigarettes (e-cigarettes), (4) advice/success, (5) quitting as a component of general health behavior change, and (6) clinics/services. Overall, the pandemic was not associated with changes in posts about quitting; instead, New Year's resolutions and the 2019 e-cigarette or vaping use-associated lung injury (EVALI) epidemic were more plausible explanations for observed changes within and across years. Fewer second-quarter posts in 2020 for the topic e-cigarettes may reflect lower pandemic-related quitting interest, whereas fourth-quarter increases in 2020 for other topics pointed to a late-year upswing. Conclusions: Twitter posts suggest that the pandemic did not generate greater interest in quitting smoking, but possibly a decrease in motivation when the rate of infections was increasing in the second quarter of 2020. Public health authorities may wish to craft messages for specific Twitter audiences (eg, using hashtags) to motivate quitting during pandemics.

Changes in Smoking Cessation-Related Behaviors Among US Adults During the COVID-19 Pandemic.

Importance: Smoking cessation is an urgent public health priority given that smoking is associated with increased risk of severe COVID-19 outcomes and other diseases. It is unknown how smoking cessation changed nationally during the COVID-19 pandemic. Objective: To investigate changes in smoking cessation-related behaviors in the US during the COVID-19 pandemic. Design, Setting, and Participants: This cross-sectional study was conducted using 2011 to 2020 data on 788 008 individuals who had smoked in the past year from the nationally representative Behavioral Risk Factor Surveillance System (BRFSS) survey. Representative retail scanner sales data between January 2017 and July 2021 for 1004 unique nicotine replacement therapy (NRT) universal product codes in 31 US states from NielsenIQ were also used. Exposures: Calendar year and 4-week sales periods. Main Outcomes and Measures: Changes in annual self-reported prevalence of past-year quit attempts and recent successful cessation before (ie, 2011-2019) and during (ie, 2020) the COVID-19 pandemic and changes in sales volumes in millions of pieces of nicotine gum, lozenge, and patch brands before (1271 four-week sales periods between January 2017 and February 2020) and during (558 four-week sales periods between March 2020 and July 2021) the COVID-19 pandemic were calculated. Results: The 2011 to 2020 pooled BRFSS sample (response rate range, 45.2%-49.9%) included 788 008 respondents (243 061 individuals ages 25-44 years [weighted percentage, 42.5%]; 374 519 men [weighted percentage, 55.7%]). For the first time since 2011, annual past-year quit attempt prevalence decreased between 2019 and 2020, from 65.2% (95% CI, 64.5% to 65.9%) to 63.2% (95% CI, 62.3% to 64.0%), with the largest relative decreases among individuals ages 45 to 64 years (61.4% [95% CI, 60.3% to 62.5%] vs 57.7% [95% CI, 56.3% to 59.2%]), those with 2 or more comorbidities (67.1% [95% CI, 66.0% to 68.2%] to 63.0% [95% CI, 61.6% to 64.4%]), and Black individuals (72.5% [95% CI, 70.3 to 74.6] vs 68.4% [95% CI, 65.3% to 71.3%]). Recent successful cessation remained unchanged during 2019 to 2020. Observed mean (SD) 4-week NRT sales volume in the prepandemic period was 105.6 (66.2) million gum pieces, 51.9 (31.6) million lozenges, and 2.0 (1.1) million patches. Compared with expected sales, observed sales during the COVID-19 pandemic were lower by 13.0% (95% CI, -13.7% to -12.3%) for lozenges, 6.4% (95% CI, -7.3% to -5.5%) for patches, and 1.2% (95% CI, -1.7% to -0.7%) for gum. Conclusions and Relevance: This study found that serious smoking cessation activity among US adults decreased immediately and remained depressed for more than a year during the COVID-19 pandemic. These findings suggest that smokers experiencing disproportionately negative outcomes during the pandemic should be reengaged and assisted in quit attempts.

College student reactions to health warning labels: sociodemographic and psychosocial factors related to perceived effectiveness of different approaches.

OBJECTIVE: To examine factors associated with perceiving different types of pictorial cigarette health warning labels as most effective in motivating smokers to quit or preventing smoking initiation among college students. METHOD: We administered an online survey to 24,055 students attending six Southeast colleges in Fall, 2010. We obtained complete data for the current analyses from 2600. RESULTS: Current smoking prevalence was 23.5%. The largest majority (78.6%) consistently rated gruesome images as most effective, 19.5% rated testimonial images as most effective, and only a small proportion rated either standard (1.6%) or human suffering images (0.3%) as most effective. Subsequent analyses focused on differences between those endorsing gruesome images or testimonials as most effective. Factors related to ranking testimonials versus gruesome images as most effective included being female (p<0.01), White (p<0.01), and nonsmokers (p=0.04), lower perceived smoking prevalence (p<0.01), and greater receptivity to laws/restrictions around smoking (p<0.01) and tobacco marketing (p=0.01). Among smokers, factors related to ranking testimonials as most effective versus gruesome images included being female (p=0.03), being White (p=0.03), higher autonomous motivation (p=0.03), and greater extrinsic self-efficacy (p=0.02). CONCLUSIONS: Understanding factors related to perceived effectiveness of different pictorial warnings among subpopulations should inform health warning labels released by the FDA.

Using the internet to understand smokers' treatment preferences: informing strategies to increase demand.

BACKGROUND: Most smokers attempt to quit on their own even though cessation aids can substantially increase their chances of success. Millions of smokers seek cessation advice on the Internet, so using it to promote cessation products and services is one strategy for increasing demand for treatments. Little is known, however, about what cessation aids these smokers would find most appealing or what predicts their preferences (eg, age, level of dependence, or timing of quit date). OBJECTIVE: The objective of our study was to gain insight into how Internet seekers of cessation information make judgments about their preferences for treatments, and to identify sociodemographic and other predictors of preferences. METHODS: An online survey assessing interest in 9 evidence-based cessation products and services was voluntarily completed by 1196 smokers who visited the American Cancer Society's Great American Smokeout (GASO) webpage. Cluster analysis was conducted on ratings of interest. RESULTS: In total, 48% (572/1196) of respondents were "quite a bit" or "very much" interested in nicotine replacement therapy (NRT), 45% (534/1196) in a website that provides customized quitting advice, and 37% (447/1196) in prescription medications. Only 11.5% (138/1196) indicated similar interest in quitlines, and 17% (208/1196) in receiving customized text messages. Hierarchical agglomerative cluster analysis revealed that interest in treatments formed 3 clusters: interpersonal-supportive methods (eg, telephone counseling, Web-based peer support, and in-person group programs), nonsocial-informational methods (eg, Internet programs, tailored emails, and informational booklets), and pharmacotherapy (NRT, bupropion, and varenicline). Only 5% (60/1196) of smokers were "quite a bit" or "very much" interested in interpersonal-supportive methods compared with 25% (298/1196) for nonsocial-informational methods and 33% (399/1196) for pharmacotherapy. Multivariate analyses and follow-up comparisons indicated that level of interest in pharmacotherapy ("quite a bit or "very much" vs. "not at all") varied as a function of education (n = 575, χ(2) (3) =16.6, P = .001), age (n = 528, χ(2) (3) = 8.2, P = .04), smoking level (n = 514, χ(2) (3) = 9.5, P = .02), and when smokers were planning to quit (n = 607, χ(2) (4) = 34.0, P < .001). Surprisingly, greater age was associated with stronger interest in nonsocial-informational methods (n = 367, χ(2) (3) = 10.8, P = .01). Interest in interpersonal-supportive methods was greater if smokers had used a quitline before (n = 259, χ(2) (1) = 18.3, P < .001), or were planning to quit earlier rather than later (n = 148, χ(2) (1) = 4.9, P = .03). CONCLUSIONS: Smokers accessing the Internet for information on quitting appear to differentiate cessation treatments by how much interpersonal interaction or support the treatment entails. Quitting date, smoking level, and sociodemographic variables can identify smokers with varying levels of interest in the 3 classes of cessation methods identified. These results can potentially be used to more effectively target and increase demand for these treatments among smokers searching the Internet for cessation information.