Dataset Information

Use of an online smoking cessation community promotes abstinence: Results of propensity score weighting.

ABSTRACT: We estimated the causal effects of use of an online smoking cessation community on 30-day point prevalence abstinence at 3 months.Participants (N = 492) were adult current smokers in the enhanced Internet arm of The iQUITT Study, a randomized trial of Internet and telephone treatment for smoking cessation. All participants accessed a Web-based smoking-cessation program that included a large, established online community. Automated tracking metrics of passive (e.g., reading forum posts, viewing member profiles) and active (e.g., writing forum posts, sending private messages) community use were extracted from the site at 3 months. Self-selected community use defines the groups of interest: "None," "Passive," and "Both" (passive + active). Inverse probability of treatment weighting corrected for baseline imbalances on demographic, smoking, psychosocial, and medical history variables. Propensity weights estimated via generalized boosted models were used to calculate Average Treatment Effects (ATE) and Average Treatment effects on the Treated (ATT).Patterns of community use were: None = 198 (40.2%), Passive = 110 (22.4%), and Both = 184 (37.4%). ATE-weighted abstinence rates were: None = 4.2% (95% CI = 1.5-6.9); Passive = 15.1% (95% CI = 8.4-21.9); Both = 20.4% (95% CI = 13.9-26.8). ATT-weighted abstinence rates indicated even greater benefits of community use.Community users were more likely to quit smoking at 3 months than nonusers. The estimated benefit from use of online community resources was even larger among subjects with high propensity to use them. No differences in abstinence emerged between passive and passive/active users. Results suggest that lurking in online communities confers specific abstinence benefits. Implications of these findings for online cessation communities are discussed.

SUBMITTER: Graham AL

PROVIDER: S-EPMC4681311 | biostudies-literature | 2015 Dec

REPOSITORIES: biostudies-literature

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Use of an online smoking cessation community promotes abstinence: Results of propensity score weighting.

Graham Amanda L AL Papandonatos George D GD Erar Bahar B Stanton Cassandra A CA

Health psychology : official journal of the Division of Health Psychology, American Psychological Association 20151201

<h4>Objective</h4>We estimated the causal effects of use of an online smoking cessation community on 30-day point prevalence abstinence at 3 months.<h4>Methods</h4>Participants (N = 492) were adult current smokers in the enhanced Internet arm of The iQUITT Study, a randomized trial of Internet and telephone treatment for smoking cessation. All participants accessed a Web-based smoking-cessation program that included a large, established online community. Automated tracking metrics of passive (e. ...[more]

PMID: 26651470

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Project description:Millions of Americans are forced to quit smoking as they enter tobacco-free prisons and jails, but most return to smoking within days of release. Interventions are needed to sustain tobacco abstinence after release from incarceration.To evaluate the extent to which the WISE intervention (Working Inside for Smoking Elimination), based on motivational interviewing (MI) and cognitive behavioral therapy (CBT), decreases relapse to smoking after release from a smoke-free prison.Participants were recruited approximately 8 weeks prior to their release from a smoke-free prison and randomized to 6 weekly sessions of either education videos (control) or the WISE intervention.A tobacco-free prison in the United States.A total of 262 inmates (35% female).Continued smoking abstinence was defined as 7-day point-prevalence abstinence validated by urine cotinine measurement.At the 3-week follow-up, 25% of participants in the WISE intervention (31 of 122) and 7% of the control participants (9 of 125) continued to be tobacco abstinent (odds ratio [OR], 4.4; 95% CI, 2.0-9.7). In addition to the intervention, Hispanic ethnicity, a plan to remain abstinent, and being incarcerated for more than 6 months were all associated with increased likelihood of remaining abstinent. In the logistic regression analysis, participants randomized to the WISE intervention were 6.6 times more likely to remain tobacco abstinent at the 3-week follow up than those randomized to the control condition (95% CI, 2.5-17.0). Nonsmokers at the 3-week follow-up had an additional follow-up 3 months after release, and overall 12% of the participants in the WISE intervention (14 of 122) and 2% of the control participants (3 of 125) were tobacco free at 3 months, as confirmed by urine cotinine measurement (OR, 5.3; 95% CI, 1.4-23.8).Forced tobacco abstinence alone during incarceration has little impact on postrelease smoking status. A behavioral intervention provided prior to release greatly improves cotinine-confirmed smoking cessation in the community.clinicaltrials.gov Identifier: NCT01122589.

Project description:Introduction:User generated content (UGC) is a valuable but underutilized source of information about individuals who participate in online cessation interventions. This study represents a first effort to passively detect smoking status among members of an online cessation program using UGC. Methods:Secondary data analysis was performed on data from 826 participants in a web-based smoking cessation randomized trial that included an online community. Domain experts from the online community reviewed each post and comment written by participants and attempted to infer the author's smoking status at the time it was written. Inferences from UGC were validated by comparison with self-reported 30-day point prevalence abstinence (PPA). Following validation, the impact of this method was evaluated across all individuals and time points in the study period. Results:Of the 826 participants in the analytic sample, 719 had written at least one post from which content inference was possible. Among participants for whom unambiguous smoking status was inferred during the 30 days preceding their 3-month follow-up survey, concordance with self-report was almost perfect (kappa = 0.94). Posts indicating abstinence tended to be written shortly after enrollment (median = 14 days). Conclusions:Passive inference of smoking status from UGC in online cessation communities is possible and highly reliable for smokers who actively produce content. These results lay the groundwork for further development of observational research tools and intervention innovations. Implications:A proof-of-concept methodology for inferring smoking status from user generated content in online cessation communities is presented and validated. Content inference of smoking status makes a key cessation variable available for use in observational designs. This method provides a powerful tool for researchers interested in online cessation interventions and establishes a foundation for larger scale application via machine learning.

Project description:Online health communities (OHCs) provide a convenient and commonly used way for people to connect around shared health experiences, exchange information, and receive social support. Users often interact with peers via multiple communication methods, forming a multirelational social network. Use of OHCs is common among smokers, but to date, there have been no studies on users' online interactions via different means of online communications and how such interactions are related to smoking cessation. Such information can be retrieved in multirelational social networks and could be useful in the design and management of OHCs.To examine the social network structure of an OHC for smoking cessation using a multirelational approach, and to explore links between subnetwork position (ie, centrality) and smoking abstinence.We used NetworkX to construct 4 subnetworks based on users' interactions via blogs, group discussions, message boards, and private messages. We illustrated topological properties of each subnetwork, including its degree distribution, density, and connectedness, and compared similarities among these subnetworks by correlating node centrality and measuring edge overlap. We also investigated coevolution dynamics of this multirelational network by analyzing tie formation sequences across subnetworks. In a subset of users who participated in a randomized, smoking cessation treatment trial, we conducted user profiling based on users' centralities in the 4 subnetworks and identified user groups using clustering techniques. We further examined 30-day smoking abstinence at 3 months postenrollment in relation to users' centralities in the 4 subnetworks.The 4 subnetworks have different topological characteristics, with message board having the most nodes (36,536) and group discussion having the highest network density (4.35×10(-3)). Blog and message board subnetworks had the most similar structures with an in-degree correlation of .45, out-degree correlation of .55, and Jaccard coefficient of .23 for edge overlap. A new tie in the group discussion subnetwork had the lowest probability of triggering subsequent ties among the same two users in other subnetworks: 6.33% (54,142/855,893) for 2-tie sequences and 2.13% (18,207/855,893) for 3-tie sequences. Users' centralities varied across the 4 subnetworks. Among a subset of users enrolled in a randomized trial, those with higher centralities across subnetworks generally had higher abstinence rates, although high centrality in the group discussion subnetwork was not associated with higher abstinence rates.A multirelational approach revealed insights that could not be obtained by analyzing the aggregated network alone, such as the ineffectiveness of group discussions in triggering social ties of other types, the advantage of blogs, message boards, and private messages in leading to subsequent social ties of other types, and the weak connection between one's centrality in the group discussion subnetwork and smoking abstinence. These insights have implications for the design and management of online social networks for smoking cessation.

Project description:ImportancePatients with cancer who smoke after diagnosis risk experiencing reductions in treatment effectiveness, survival rates, and quality of life, and increases in complications, cancer recurrence, and second primary cancers. Smoking cessation can significantly affect these outcomes, but to date comprehensive treatment is not widely implemented in the oncologic setting.ObjectivesTo describe a potential model tobacco treatment program (TTP) implemented in a cancer setting, report on its long-term outcomes, and highlight its importance to quality patient care.Design, setting, and participantsA prospective cohort of smokers was treated in the TTP at a comprehensive cancer center from January 1, 2006, to August 31, 2015. Data analysis was performed from November 2017 to December 2018. Participants included 3245 patients (2343 with current cancer; 309 with previous cancer; 593 with no cancer history) drawn from a population of 5061 smokers referred for treatment in the TTP. Reasons for exclusion included follow-up for a noncancerous disease, no medical consultation, smoked less than 1 cigarette per day; or died before the 9-month follow-up.ExposuresTreatment consisted of an in-person medical consultation, 6 to 8 in-person and telephone follow-up counseling sessions, and 10 to 12 weeks of pharmacotherapy.Main outcomes and measuresPrimary outcome was 9-month 7-day point-prevalence abstinence evaluated using time-specific (3-, 6-, and 9-month follow-ups) and longitudinal covariate-adjusted and unadjusted regression models with multiple imputation, intention-to-treat, and respondent-only approaches to missing data. The Fagerström Test for Cigarette Dependence was used as a measure of dependence (possible range, 0-10; higher numbers indicate greater dependence).ResultsOf the 3245 smokers, 1588 (48.9%) were men, 322 (9.9%) were of black race/ethnicity, 172 (5.3%) were of Hispanic race/ethnicity, and 2498 (76.0%) were of white race/ethnicity. Mean (SD) age was 54 (11.4) years; Fagerström Test for Cigarette Dependence score, 4.41 (2.2), number of cigarettes smoked per day, 17.1 (10.7); years smoked, 33 (13.2); and 1393 patients (42.9%) had at least 1 psychiatric comorbidity. Overall self-reported abstinence was 45.1% at 3 months, 45.8% at 6 months, and 43.7% at 9 months in the multiply imputed sample. Results across all models were consistent, suggesting that, in comparison with smokers with no cancer history, abstinence rates within this TTP program did not differ appreciably whether smokers had current cancer, were a cancer survivor, or had smoking-related cancers, with the exception of patients with head and neck cancer; the rates were higher at 9 months (relative risk, 1.31; 95% CI, 1.11-1.56; P = .001) and in longitudinal models (relative risk, 1.24; 95% CI, 1.08-1.42; P = .002).Conclusions and relevanceIn this study, mean smoking abstinence rates did not differ significantly between patients with cancer and those without cancer. These findings suggest that providing comprehensive tobacco treatment in the oncologic setting can result in sustained high abstinence rates for all patients with cancer and survivors and should be included as standard of care to ensure the best possible cancer treatment outcomes.

Dataset Information

Use of an online smoking cessation community promotes abstinence: Results of propensity score weighting.

Publications

Use of an online smoking cessation community promotes abstinence: Results of propensity score weighting.

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