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Development of an interactive, Web-delivered system to increase provider-patient engagement in smoking cessation.

ABSTRACT: Patient self-management interventions for smoking cessation are effective but underused. Health care providers do not routinely refer smokers to these interventions.The objective of our study was to uncover barriers and facilitators to the use of an e-referral system that will be evaluated in a community-based randomized trial. The e-referral system will allow providers to refer smokers to an online smoking intervention during routine clinical care.We devised a four-step development and pilot testing process: (1) system conceptualization using Delphi to identify key functionalities that would overcome barriers in provider referrals for smoking cessation, (2) Web system programming using agile software development and best programming practices with usability refinement using think-aloud testing, (3) implementation planning using the nominal group technique for the effective integration of the system into the workflow of practices, and (4) pilot testing to identify practice recruitment and system-use barriers in real-world settings.Our Delphi process (step 1) conceptualized three key e-referral functions: (1) Refer Your Smokers, allowing providers to e-refer patients at the point of care by entering their emails directly into the system, (2) practice reports, providing feedback regarding referrals and impact of smoking-cessation counseling, and (3) secure messaging, facilitating provider-patient communication. Usability testing (step 2) suggested the system was easy to use, but implementation planning (step 3) suggested several important approaches to encourage use (eg, proactive email cues to encourage practices to participate). Pilot testing (step 4) in 5 practices had limited success, with only 2 patients referred; we uncovered important recruitment and system-use barriers (eg, lack of study champion, training, and motivation, registration difficulties, and forgetting to refer).Implementing a system to be used in a clinical setting is complex, as several issues can affect system use. In our ongoing large randomized trial, preliminary analysis with the first 50 practices using the system for 3 months demonstrated that our rigorous preimplementation evaluation helped us successfully identify and overcome these barriers before the main trial.Clinicaltrials.gov NCT00797628; http://clinicaltrials.gov/ct2/show/NCT00797628 (Archived by WebCite at http://www.webcitation.org/61feCfjCy).

SUBMITTER: Sadasivam RS

PROVIDER: S-EPMC3222193 | biostudies-literature | 2011 Oct

REPOSITORIES: biostudies-literature

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Development of an interactive, Web-delivered system to increase provider-patient engagement in smoking cessation.

Sadasivam Rajani S RS Delaughter Kathryn K Crenshaw Katie K Sobko Heather J HJ Williams Jessica H JH Coley Heather L HL Ray Midge N MN Ford Daniel E DE Allison Jeroan J JJ Houston Thomas K TK

Journal of medical Internet research 20111018 4

<h4>Background</h4>Patient self-management interventions for smoking cessation are effective but underused. Health care providers do not routinely refer smokers to these interventions.<h4>Objective</h4>The objective of our study was to uncover barriers and facilitators to the use of an e-referral system that will be evaluated in a community-based randomized trial. The e-referral system will allow providers to refer smokers to an online smoking intervention during routine clinical care.<h4>Method ...[more]

PMID: 22011394

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Project description:ImportanceThe National Lung Screening Trial (NLST) found a reduction in lung cancer mortality among participants screened with low-dose computed tomography vs chest radiography. In February 2015, Medicare announced its decision to cover annual lung screening for patients with a significant smoking history. These guidelines promote smoking cessation treatment as an adjunct to screening, but the frequency and effectiveness of clinician-delivered smoking cessation interventions delivered after lung screening are unknown.ObjectiveTo determine the association between the reported clinician-delivered 5As (ask, advise, assess, assist [talk about quitting or recommend stop-smoking medications or recommend counseling], and arrange follow-up) after lung screening and smoking behavior changes.Design, setting, and participantsA matched case-control study (cases were quitters and controls were continued smokers) of 3336 NLST participants who were smokers at enrollment examined participants' rates and patterns of 5A delivery after a lung screen and reported smoking cessation behaviors.Main outcomes and measuresPrevalence of the clinician-delivered 5As and associated smoking cessation after lung screening.ResultsDelivery of the 5As 1 year after screening were as follows: ask, 77.2%; advise, 75.6%; assess, 63.4%; assist, 56.4%; and arrange follow-up, 10.4%. Receipt of ask, advise, and assess was not significantly associated with quitting in multivariate models that adjusted for sociodemographic characteristics, medical history, screening results, nicotine dependence, and motivation to quit. Assist was associated with a 40% increase in the odds of quitting (odds ratio, 1.40; 95% CI, 1.21-1.63), and arrange was associated with a 46% increase in the odds of quitting (odds ratio, 1.46; 95% CI, 1.19-1.79).Conclusions and relevanceAssist and arrange follow-up delivered by primary care providers to smokers who were participating in the NLST were associated with increased quitting; less intensive interventions (ask, advise, and assess) were not. However, rates of assist and arrange follow-up were relatively low. Our findings confirm the need for and benefit of clinicians taking more active intervention steps in helping patients who undergo screening to quit smoking.

Project description:Although screening for tobacco use is increasing with electronic health records and standard protocols, other tobacco-control activities, such as referral of patients to cessation resources, is quite low. In the QUIT-PRIMO study, an online referral portal will allow providers to enter smokers' email addresses into the system. Upon returning home, the smokers will receive automated emails providing education about tobacco cessation and encouragement to use the patient smoking cessation website (with interactive tools, educational resources, motivational email messages, secure messaging with a tobacco treatment specialist, and online support group).The informatics system will be evaluated in a comparative effectiveness trial of 160 community-based primary care practices, cluster-randomized at the practice level. In the QUIT-PRIMO intervention, patients will be provided a paper information-prescription referral and then "e-referred" to the system. In the comparison group, patients will receive only the paper-based information-prescription referral with the website address. Once patients go to the website, they are subsequently randomized within practices to either a standard patient smoking cessation website or an augmented version with access to a tobacco treatment specialist online, motivational emails, and an online support group. We will compare intervention and control practice participation (referral rates) and patient participation (proportion referred who go to the website). We will then compare the effectiveness of the standard and augmented patient websites.Our goal is to evaluate an integrated informatics solution to increase access to web-delivered smoking cessation support. We will analyze the impact of this integrated system in terms of process (provider e-referral and patient login) and patient outcomes (six-month smoking cessation).Web-delivered Provider Intervention for Tobacco Control (QUIT-PRIMO) - a randomized controlled trial: NCT00797628.

Project description:BACKGROUND AND AIMS:Millions of people world-wide use websites to help them quit smoking, but effectiveness trials have an average 34% follow-up data retention rate and an average 9% quit rate. We compared the quit rates of a website using a new behavioral approach called Acceptance and Commitment Therapy (ACT; WebQuit.org) with the current standard of the National Cancer Institute's (NCI) Smokefree.gov website. DESIGN:A two-arm stratified double-blind individually randomized trial (n = 1319 for WebQuit; n = 1318 for Smokefree.gov) with 12-month follow-up. SETTING:United States. PARTICIPANTS:Adults (n = 2637) who currently smoked at least five cigarettes per day were recruited from March 2014 to August 2015. At baseline, participants were mean [standard deviation (SD)] age 46.2 years (13.4), 79% women and 73% white. INTERVENTIONS:WebQuit.org website (experimental) provided ACT for smoking cessation; Smokefree.gov website (comparison) followed US Clinical Practice Guidelines for smoking cessation. MEASUREMENTS:The primary outcome was self-reported 30-day point prevalence abstinence at 12 months. FINDINGS:The 12-month follow-up data retention rate was 88% (2309 of 2637). The 30-day point prevalence abstinence rates at the 12-month follow-up were 24% (278 of 1141) for WebQuit.org and 26% (305 of 1168) for Smokefree.gov [odds ratio (OR) = 0.91; 95% confidence interval (CI) = 0.76, 1.10; P = 0.334] in the a priori complete case analysis. Abstinence rates were 21% (278 of 1319) for WebQuit.org and 23% (305 of 1318) for Smokefree.gov (OR = 0.89 (0.74, 1.07; P = 0.200) when missing cases were imputed as smokers. The Bayes factor comparing the primary abstinence outcome was 0.17, indicating 'substantial' evidence of no difference between groups. CONCLUSIONS:WebQuit.org and Smokefree.gov had similar 30-day point prevalence abstinence rates at 12 months that were descriptively higher than those of prior published website-delivered interventions and telephone counselor-delivered interventions.

Project description:IntroductionAddressing tobacco use is an important issue in general health care. In order to improve smoking cessation advice, spirometry values can be displayed to the smoker to demonstrate possible lung function impairment. The estimate of so-called lung age may show a decrease in lung function associated with smoking. It has been suggested that performing spirometry on patients who smoke but are asymptomatic can be a useful way to show the adverse effects of smoking. The aim of this systematic review was to determine if providing spirometry results in combination with smoking cessation counselling can increase smoking cessation rates compared to what is achieved through counselling alone.MethodsIn this systematic review, we included randomized controlled trials (RCTs) evaluating smoking cessation interventions for adult smokers. The systematic search was performed in PubMed, Medline, Cochrane Library, Cinahl, Embase, Amed and PsycInfo.ResultsThe literature search resulted in 946 studies, which, after reading by two independent reviewers, were reduced to seven trials that matched the inclusion criteria. Two RCTs showed significant improvement in smoking cessation when giving patients feedback on spirometry results in combination with smoking cessation counselling, compared to patients who received only smoking cessation counselling. In both studies, the spirometry results were expressed as lung age. In the other five studies no difference was found. Five further published study protocols for ongoing RCT studies in the field have been found, and therefore this systematic overview will likely need to be updated within a few years.ConclusionsFew studies have been undertaken to examine the efficacy of spirometry in increasing smoking quit rates. Studies conducted to date have shown mixed results, and there is currently limited evidence in the literature that smoking cessation counselling that includes feedback from spirometry and a demonstration of lung age promotes quit rates.

Project description:BackgroundMotivational messaging is a frequently used digital intervention to promote positive health behavior changes, including smoking cessation. Typically, motivational messaging systems have not actively sought feedback on each message, preventing a closer examination of the user-system engagement. This study assessed the granular user-system engagement around a recommender system (a new system that actively sought user feedback on each message to improve message selection) for promoting smoking cessation and the impact of engagement on cessation outcome.MethodsWe prospectively followed a cohort of current smokers enrolled to use the recommender system for 6 months. The system sent participants motivational messages to support smoking cessation every 3 days and used machine learning to incorporate user feedback (i.e., user's rating on the perceived influence of each message, collected on a 5-point Likert scale with 1 indicating strong disagreement and 5 indicating strong agreement on perceiving the influence on quitting smoking) to improve the selection of the following message. We assessed user-system engagement by various metrics, including user response rate (i.e., the percent of times a user rated the messages) and the perceived influence of messages. We compared retention rates across different levels of user-system engagement and assessed the association between engagement and the 7-day point prevalence abstinence (missing outcome = smoking) by using multiple logistic regression.ResultsWe analyzed data from 731 participants (13% Black; 73% women). The user response rate was 0.24 (SD = 0.34) and user-perceived influence was 3.76 (SD = 0.84). The retention rate positively increased with the user response rate (trend test P < 0.001). Compared with non-response, six-month cessation increased with the levels of response rates: low response rate (odds ratio [OR] = 1.86, 95% confidence interval [CI]: 1.07-3.23), moderate response rate (OR = 2.30, 95% CI: 1.36-3.88), high response rate (OR = 2.69, 95% CI: 1.58-4.58). The association between perceived message influence and the outcome showed a similar pattern.ConclusionsHigh user-system engagement was positively associated with both high retention rate and smoking cessation, suggesting that investigation of methods to increase engagement may be crucial to increase the impact of the recommender system for smoking cessation.Trial registrationRegistration Identifier: NCT03224520 . Registration date: July 21, 2017.

Project description:BackgroundSocial media offer a great opportunity to deliver smoking cessation treatment to young adults, but previous online and social media interventions targeting health behavior change have struggled with low participant engagement. We examined engagement generated by content based on the Transtheoretical Model of Behavior Change (TTM) in a motivationally tailored smoking cessation intervention on Facebook.ObjectiveThis study aimed to identify which intervention content based on the TTM (Decisional Balance and 10 processes of change) generated the highest engagement among participants in pre-action stages of change (Precontemplation, Contemplation, and Preparation).MethodsParticipants (N=79, 20% female, mean age 20.8) were assessed for readiness to quit smoking and assigned to one of 7 secret Facebook groups tailored to their stage of change. Daily postings to the groups based on TTM Decisional Balance and the 10 processes of change were made by research staff over 3 months. Engagement was operationalized as the number of participant comments to each post. TTM content-based predictors of number of comments were analyzed and stratified by baseline stage of change, using negative binomial regression analyses with and without zero inflation.ResultsA total of 512 TTM-based posts generated 630 individual comments. In Precontemplation and Contemplation groups, Decisional Balance posts generated above average engagement (P=.01 and P<.001). In Contemplation groups, posts based on the TTM processes Dramatic Relief and Self-Liberation resulted in below average engagement (P=.01 and P=.005). In Preparation groups, posts based on Consciousness Raising generated above average engagement (P=.009). Participant engagement decreased over time and differed between groups within Precontemplation and Contemplation stages, but was independent of day of the week and time of day the content was posted to the groups. No participant baseline characteristics significantly predicted engagement.ConclusionsParticipants not ready to quit in the next 30 days (in Precontemplation or Contemplation) engaged most when prompted to think about the pros and cons of behavior change, while those in the Preparation stage engaged most when posts increased awareness about smoking and smoking cessation. Findings support tailoring intervention content to readiness to quit and suggest intervention components that may be most effective in generating high participant engagement on social media.

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Development of an interactive, Web-delivered system to increase provider-patient engagement in smoking cessation.

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Development of an interactive, Web-delivered system to increase provider-patient engagement in smoking cessation.

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