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.

Exploring Online Asynchronous Counseling With Tobacco Treatment Specialists in the QUIT-PRIMO and National Dental PBRN HI-QUIT Studies: Who Uses It and What Do They Say?

PURPOSE: To describe the content of messages sent by smokers through asynchronous counseling within a Web-based smoking cessation intervention. DESIGN: Qualitative. SETTING: National community-based setting of patients who had been engaged by the medical or dental practices at which they attended or via Google advertisements. PARTICIPANTS: Adults older than 19 years who were current smokers and interested in quitting. Participants throughout the United States referred to a Web-based cessation intervention by their medical or dental provider or by clicking on a Google advertisement. METHODS: We conducted a qualitative review of 742 asynchronous counseling messages sent by 270 Web site users. Messages were reviewed, analyzed, and organized into qualitative themes by the investigative team. RESULTS: The asynchronous counseling feature of the intervention was used most frequently by smokers who were white (87%), female (67%), aged 45 to 54 (32%), and who had at least some college-level education (70%). Qualitative analysis yielded 7 basic themes-Talk about the Process of Quitting, Barriers to Quitting, Reasons to Quit, Quit History, Support and Strategies for Quitting, Quitting with Medication, and Quit Progress. The most common theme was Support and Strategies for Quitting with 255 references among all messages. CONCLUSION: We found rich communication across the spectrum of the quit process, from persons preparing to quit to those who had successfully quit. Asynchronous smoking cessation counseling provides a promising means of social support for smokers during the quit process.

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).

Quitters referring smokers: a quitline chain-referral pilot study.

BACKGROUND: Telephone counseling Quitlines can support smoking cessation, but are under-utilized. We explored the use of smoker peer-referrals to increase use of a Quitline in Mississippi and Alabama. FINDINGS: Collaborating with the Alabama and Mississippi Quitline, we piloted peer-referrals to Quitlines. Successful 'quitters' who had used the Quitline were contacted at routine follow-up and recruited to participate as a peer-referrer and refer their friends and family who smoked to the Quitline. Peer-referrers completed a training session, received a manual and a set of Quitline brochures a peer-referral forms. These peer-referral forms were then returned to the Quitline telephone counselors who proactively called the referred smokers. Of the initial potential pool of 96 who quit using the Quitline, 24 peer-referrers (75% Women, 29% African-American, and high school graduates/GED 67%) were recruited and initially agreed to participate as peer-referrers. Eleven of the 24 who initially agreed were trained, and of these 11, 4 (4%) actively referred 23 friends and family over 2 months. From these 23 new referrals, three intakes (100% Women, 66% African-American) were completed. Of the initial pool of 96, 4 (4%) actively participated in referring friends and family. Quitline staff and peer-referrers noted several barriers including: time-point in which potential peer-referrers were asked to participate, an 'overwhelming' referral form to use and limited ways to refer. CONCLUSIONS: Though 'quitters' were willing to agree to peer-refer, we received a minority of referrals. However, we identified several areas to improve this new method for increasing awareness and access to support systems like the Quitline for smokers who want to quit.

Implementing point of care "e-referrals" in 137 clinics to increase access to a quit smoking internet system: the Quit-Primo and National Dental PBRN HI-QUIT Studies.

Integrating electronic referral systems into clinical practices may increase use of web-accessible tobacco interventions. We report on our feasibility evaluation of using theory-driven implementation science techniques to translate an e-referral system (ReferASmoker.org) into the workflow of 137 community-based medical and dental practices, including system use, patient registration, implementation costs, and lessons learned. After 6 months, 2,376 smokers were e-referred (medical, 1,625; dental, 751). Eighty-six percent of the medical practices [75/87, mean referral = 18.7 (SD = 17.9), range 0-105] and dental practices [43/50, mean referral = 15.0 (SD = 10.5), range 0-38] had e-referred. Of those smokers e-referred, 25.3 registered [mean smoker registration rate-medical 4.9 (SD = 7.6, range 0-59), dental 3.6 (SD = 3.0, range 0-10)]. Estimated mean implementation costs are medical practices, US$429.00 (SD = 85.3); and dental practices, US$238.75 (SD = 13.6). High performing practices reported specific strategies to integrate ReferASmoker.org; low performers reported lack of smokers and patient disinterest in the study. Thus, a majority of practices e-referred and 25.3 % of referred smokers registered demonstrating e-referral feasibility. However, further examination of the identified implementation barriers is important as of the estimated 90,000 to 140,000 smokers seen in the 87 medical practices in 6 months, only 1,625 were e-referred.

Who participates in Web-assisted tobacco interventions? The QUIT-PRIMO and National Dental Practice-Based Research Network Hi-Quit studies.

INTRODUCTION: Smoking is the most preventable cause of death. Although effective, Web-assisted tobacco interventions are underutilized and recruitment is challenging. Understanding who participates in Web-assisted tobacco interventions may help in improving recruitment. OBJECTIVES: To understand characteristics of smokers participating in a Web-assisted tobacco intervention (Decide2Quit.org). METHODS: In addition to the typical Google advertisements, we expanded Decide2Quit.org recruitment to include referrals from medical and dental providers. We assessed how the expanded recruitment of smokers changed the users' characteristics, including comparison with a population-based sample of smokers from the national Behavioral Risk Factors Surveillance Survey (BRFSS). Using a negative binomial regression, we compared demographic and smoking characteristics by recruitment source, in particular readiness to quit and association with subsequent Decide2Quit.org use. RESULTS: The Decide2Quit.org cohort included 605 smokers; the 2010 BRFSS dataset included 69,992. Compared to BRFSS smokers, a higher proportion of Decide2Quit.org smokers were female (65.2% vs 45.7%, P=.001), over age 35 (80.8% vs 67.0%, P=.001), and had some college or were college graduates (65.7% vs 45.9%, P=.001). Demographic and smoking characteristics varied by recruitment; for example, a lower proportion of medical- (22.1%) and dental-referred (18.9%) smokers had set a quit date or had already quit than Google smokers (40.1%, P<.001). Medical- and dental-referred smokers were less likely to use Decide2Quit.org functions; in adjusted analysis, Google smokers (predicted count 17.04, 95% CI 14.97-19.11) had higher predicted counts of Web page visits than medical-referred (predicted count 12.73, 95% CI 11.42-14.04) and dental-referred (predicted count 11.97, 95% CI 10.13-13.82) smokers, and were more likely to contact tobacco treatment specialists. CONCLUSIONS: Recruitment from clinical practices complimented Google recruitment attracting smokers less motivated to quit and less experienced with Web-assisted tobacco interventions.

Cluster-randomized trial of a web-assisted tobacco quality improvement intervention of subsequent patient tobacco product use: a National Dental PBRN study.

BACKGROUND: Brief clinician delivered advice helps in tobacco cessation efforts. This study assessed the impact of our intervention on instances of advice given to dental patients during visits on tobacco use quit rates 6 months after the intervention. METHODS: The intervention was cluster randomized trial at the dental practice level. Intervention dental practices were provided a longitudinal technology-assisted intervention, oralcancerprevention.org that included a series of interactive educational cases and motivational email cues to remind dental provides to complete guideline-concordant brief behavioral counseling at the point of care. In all dental practices, exit cards were given to the first 100 consecutive patients, in which tobacco users provided contact information for a six month follow-up telephone survey. RESULTS: A total of 564 tobacco using dental patients completed a six month follow-up survey. Among intervention patients, 55% reported receiving advice to quit tobacco, and 39% of control practice patients reported receiving advice to quit tobacco (p < 0.01). Six-month tobacco use quit rates were not significantly between the Intervention (9%) and Control (13%) groups, (p = 0.088). CONCLUSION: Although we increased rates of cessation advice delivered in dental practices, this study shows no evidence that brief advice by dentist's increases long-term abstinence in smokers. TRIAL REGISTRATION: ClinicalTrials.gov NCT00627185.

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

BACKGROUND: Patient self-management interventions for smoking cessation are effective but underused. Health care providers do not routinely refer smokers to these interventions. OBJECTIVE: 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. METHODS: 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. RESULTS: 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). CONCLUSIONS: 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. TRIAL: Clinicaltrials.gov NCT00797628; http://clinicaltrials.gov/ct2/show/NCT00797628 (Archived by WebCite at http://www.webcitation.org/61feCfjCy).