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:ImportanceMillions 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.ObjectiveTo 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.DesignParticipants 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.SettingA tobacco-free prison in the United States.ParticipantsA total of 262 inmates (35% female).Main outcome measureContinued smoking abstinence was defined as 7-day point-prevalence abstinence validated by urine cotinine measurement.ResultsAt 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).Conclusions and relevanceForced 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.Trial registrationclinicaltrials.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:BackgroundThe diagnostic process is a key element of medicine but it is complex and prone to errors. Infectious diseases are one of the three categories of diseases in which diagnostic errors can be most harmful to patients. In this study we aimed to estimate the effect of initial misdiagnosis of the source of infection in patients with bacteraemia on 14 day mortality using propensity score methods to adjust for confounding.MethodsData from a previously described longitudinal cohort of patients diagnosed with monobacterial bloodstream infection (BSI) at the Leiden University Medical Centre (LUMC) between 2013 and 2015 were used. Propensity score matching and inversed probability of treatment weighting (IPTW) were applied to correct for confounding. The average treatment effect on the treated (ATT), which in this study was the average effect of initial misdiagnosis on the misdiagnosed (AEMM), was estimated. Methodological issues that were encountered when applying propensity score methods were addressed by performing additional sensitivity analyses. Sensitivity analyses consisted of varying caliper in propensity score matching and using different truncated weights in inversed probability of treatment weighting.ResultsData of 887 patients were included in the study. Propensity scores ranged between 0.015 and 0.999 and 80 patients (9.9%) had a propensity score > 0.95. In the matched analyses, 35 of the 171 misdiagnosed patients died within 14 days (20.5%), versus 10 of the 171 correctly diagnosed patients (5.8%), yielding a difference of 14.6% (7.6%; 21.6%). In the total group of patients, the observed percentage of patients with an incorrect initial diagnosis that died within 14 days was 19.8% while propensity score reweighting estimated that their probability of dying would have been 6.5%, if they had been correctly diagnosed (difference 13.3% (95% CI 6.9%;19.6%)). After adjustment for all variables that showed disbalance in the propensity score a difference of 13.7% (7.4%; 19.9%) was estimated. Sensitivity analyses yielded similar results. However, performing weighted analyses without truncation yielded unstable results.ConclusionThus, we observed a substantial increase of 14 day mortality in initially misdiagnosed patients. Furthermore, several patients received propensity scores extremely close to one and were almost sure to be initially misdiagnosed.

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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