The Association Between Medication Adherence for Chronic Conditions and Digital Health Activity Tracking: Retrospective Analysis.

BACKGROUND: Chronic diseases have a widespread impact on health outcomes and costs in the United States. Heart disease and diabetes are among the biggest cost burdens on the health care system. Adherence to medication is associated with better health outcomes and lower total health care costs for individuals with these conditions, but the relationship between medication adherence and health activity behavior has not been explored extensively. OBJECTIVE: The aim of this study was to examine the relationship between medication adherence and health behaviors among a large population of insured individuals with hypertension, diabetes, and dyslipidemia. METHODS: We conducted a retrospective analysis of health status, behaviors, and medication adherence from medical and pharmacy claims and health behavior data. Adherence was measured in terms of proportion of days covered (PDC), calculated from pharmacy claims using both a fixed and variable denominator methodology. Individuals were considered adherent if their PDC was at least 0.80. We used step counts, sleep, weight, and food log data that were transmitted through devices that individuals linked. We computed metrics on the frequency of tracking and the extent to which individuals engaged in each tracking activity. Finally, we used logistic regression to model the relationship between adherent status and the activity-tracking metrics, including age and sex as fixed effects. RESULTS: We identified 117,765 cases with diabetes, 317,340 with dyslipidemia, and 673,428 with hypertension between January 1, 2015 and June 1, 2016 in available data sources. Average fixed and variable PDC for all individuals ranged from 0.673 to 0.917 for diabetes, 0.756 to 0.921 for dyslipidemia, and 0.756 to 0.929 for hypertension. A subgroup of 8553 cases also had health behavior data (eg, activity-tracker data). On the basis of these data, individuals who tracked steps, sleep, weight, or diet were significantly more likely to be adherent to medication than those who did not track any activities in both the fixed methodology (odds ratio, OR 1.33, 95% CI 1.29-1.36) and variable methodology (OR 1.37, 95% CI 1.32-1.43), with age and sex as fixed effects. Furthermore, there was a positive association between frequency of activity tracking and medication adherence. In the logistic regression model, increasing the adjusted tracking ratio by 0.5 increased the fixed adherent status OR by a factor of 1.11 (95% CI 1.06-1.16). Finally, we found a positive association between number of steps and adherent status when controlling for age and sex. CONCLUSIONS: Adopters of digital health activity trackers tend to be more adherent to hypertension, diabetes, and dyslipidemia medications, and adherence increases with tracking frequency. This suggests that there may be value in examining new ways to further promote medication adherence through programs that incentivize health tracking and leveraging insights derived from connected devices to improve health outcomes.

Correction: The Association Between Medication Adherence for Chronic Conditions and Digital Health Activity Tracking: Retrospective Analysis.

[This corrects the article DOI: 10.2196/11486.].

Intrapersonal Variation in Goal Setting and Achievement in Health Coaching: Cross-Sectional Retrospective Analysis.

BACKGROUND: Chronic conditions in the United States are among the most costly and preventable of all health problems. Research suggests health coaching is an effective strategy for reducing health risks including decreases in weight, blood pressure, lipids, and blood glucose. Much less is known about how and when coaching works. OBJECTIVE: The aim of this study was to conduct an analysis of intrapersonal variations in participants' progression in health coaching, examining gender and age-related differences. METHODS: This was a cross-sectional, retrospective analysis of 35,333 health coaching participants between 2012 and 2016. Differences in number of goals and activities set and completed, and number of interactions were assessed using negative binomial models. Differences in goal type were assessed using logistic regression for gender and using the Welch test for age to account for unequal variances. RESULTS: Participants choosing online coaching were more likely to be younger and female (P<.001). Gender and age differences were found for the types of goals set by participants. Regarding program activity, women set and completed 12% more action steps than men (P<.001), averaging 21% more interactions than men (P<.001); no gender differences were found in number of goals completed (P=.12), although the percentage of males and females completing goals was significantly different at 60 and 120 days postenrollment (P<.001). Results indicated significant age-related differences in all aspects of program activity: number of interactions, goals set and completed, action steps set and completed (all P values <.01), as well as significant differences in percentage of individuals completing initial goals within 30 days, with older individuals completing more than younger individuals did (all P values <.001). CONCLUSIONS: This study found significant intrapersonal variation in how people participate in and progress through a coaching program. Age-related variations were found in all aspects of coaching activity, from modality preference and initial choice of goal type (eg, weight management, tobacco cessation) to goal completion, whereas gender-related differences were demonstrated for all program activities except number of goals set and completed. These findings indicate that to maximize behavior change, coaches need to personalize the coaching experience to the individual.

Outcomes of a randomized trial evaluating two approaches for promoting pharmacy-based referrals to the tobacco quitline.

OBJECTIVES: To evaluate the long-term impact of 2 promising intervention approaches to engage pharmacy personnel (pharmacists, technicians) in referring patients who want to quit smoking to the tobacco quitline. DESIGN: Randomized trial. SETTING: Community pharmacies in Connecticut (n = 32) and Washington (n = 32). INTERVENTION: Two intervention approaches were evaluated: academic detailing (AD), which involved on-site training for pharmacy staff about the quitline, versus mailed quitline materials (MM). MAIN OUTCOME MEASURES: Changes in the overall percentage of quitline registrants who reported hearing about the quitline from any pharmacy during the 6-month baseline monitoring period versus the 12-month intervention period, and between-group comparisons of a) the number of quitline registrants who reported hearing about the quitline from one of the study pharmacies during the 12-month intervention period, and b) the number of quitline cards and brochures distributed to patients during the first 6 months of the intervention period. RESULTS: The percentage of quitline callers who reported having heard about the quitline from a pharmacy increased significantly, from 2.2% during the baseline monitoring period to 3.8% during the 12-month intervention (P < 0.0001). In addition, comparisons controlled for seasonal effects also revealed significant increases in referrals. Across all 64 pharmacies, 10,013 quitline cards and 4755 brochures were distributed. The number of quitline cards distributed and the number registrants who reported hearing about the quitline from a pharmacy did not differ by intervention approach (AD vs. MM), although AD pharmacies distributed more quitline brochures (P = 0.022). CONCLUSION: Brief cessation interventions are feasible in community pharmacies, and the 2 approaches evaluated for engaging pharmacy personnel were similarly effective and collectively led to meaningful increases in the number and proportion of all patients who called the quitline. Involvement of community pharmacy personnel in tobacco cessation presents a significant opportunity to promote quitline services by connecting patients with an effective publicly available resource.

Utilization of a Web-based vs integrated phone/Web cessation program among 140,000 tobacco users: an evaluation across 10 free state quitlines.

BACKGROUND: Phone-based tobacco cessation program effectiveness has been established and randomized controlled trials have provided some support for Web-based services. Relatively little is known about who selects different treatment modalities and how they engage with treatments in a real-world setting. OBJECTIVE: This paper describes the characteristics, Web utilization patterns, and return rates of tobacco users who self-selected into a Web-based (Web-Only) versus integrated phone/Web (Phone/Web) cessation program. METHODS: We examined the demographics, baseline tobacco use, Web utilization patterns, and return rates of 141,429 adult tobacco users who self-selected into a Web-Only or integrated Phone/Web cessation program through 1 of 10 state quitlines from August 2012 through July 2013. For each state, registrants were only included from the timeframe in which both programs were offered to all enrollees. Utilization data were limited to site interactions occurring within 6 months after registration. RESULTS: Most participants selected the Phone/Web program (113,019/141,429, 79.91%). After enrollment in Web services, Web-Only were more likely to log in compared to Phone/Web (21,832/28,410, 76.85% vs 23,920/56,892, 42.04%; P<.001), but less likely to return after their initial log-in (8766/21,832, 40.15% vs 13,966/23,920, 58.39%; P<.001). In bivariate and multivariable analyses, those who chose Web-Only were younger, healthier, more highly educated, more likely to be uninsured or commercially insured, more likely to be white non-Hispanic and less likely to be black non-Hispanic, less likely to be highly nicotine-addicted, and more likely to have started their program enrollment online (all P<.001). Among both program populations, participants were more likely to return to Web services if they were women, older, more highly educated, or were sent nicotine replacement therapy (NRT) through their quitline (all P<.001). Phone/Web were also more likely to return if they had completed a coaching call, identified as white non-Hispanic or "other" race, or were commercially insured (all P<.001). Web-Only were less likely to return if they started their enrollment online versus via phone. The interactive Tobacco Tracker, Cost Savings Calculator, and Quitting Plan were the most widely used features overall. Web-Only were more likely than Phone/Web to use most key features (all P<.001), most notably the 5 Quitting Plan behaviors. Among quitlines that offered NRT to both Phone/Web and Web-Only, Web-Only were less likely to have received quitline NRT. CONCLUSIONS: This paper adds to our understanding of who selects different cessation treatment modalities and how they engage with the program in a real-world setting. Web-Only were younger, healthier smokers of higher socioeconomic status who interacted more intensely with services in a single session, but were less likely to re-engage or access NRT benefits. Further research should examine the efficacy of different engagement techniques and services with different subpopulations of tobacco users.

Impact of baseline weight on smoking cessation and weight gain in quitlines.

BACKGROUND: The use and effectiveness of tobacco quitlines by weight is still unknown. PURPOSE: This study aims to determine if baseline weight is associated with treatment engagement, cessation, or weight gain following quitline treatment. METHODS: Quitline participants (n = 595) were surveyed at baseline, 3 and 6 months. RESULTS: Baseline weight was not associated with treatment engagement. In unadjusted analyses, overweight smokers reported higher quit rates and were more likely to gain weight after quitting than obese or normal weight smokers. At 3 months, 40 % of overweight vs. 25 % of normal weight or obese smokers quit smoking (p = 0.01); 42 % of overweight, 32 % of normal weight, and 33 % of obese quitters gained weight (p = 0.05). After adjusting for covariates, weight was not significantly related to cessation (approaching significance at 6 months, p = 0.06) or weight gain. CONCLUSIONS: In the first quitline study of this kind, we found no consistent patterns of association between baseline weight and treatment engagement, cessation, or weight gain.

Randomized trial of telephone-delivered acceptance and commitment therapy versus cognitive behavioral therapy for smoking cessation: a pilot study.

OBJECTIVE: We conducted a pilot randomized trial of telephone-delivered acceptance and commitment therapy (ACT) versus cognitive behavioral therapy (CBT) for smoking cessation. METHOD: Participants were 121 uninsured South Carolina State Quitline callers who were adult smokers (at least 10 cigarettes/day) and who wanted to quit within the next 30 days. Participants were randomized to 5 sessions of either ACT or CBT telephone counseling and were offered 2 weeks of nicotine replacement therapy (NRT). RESULTS: ACT participants completed more calls than CBT participants (M = 3.25 in ACT vs. 2.23 in CBT; p = .001). Regarding satisfaction, 100% of ACT participants reported their treatment was useful for quitting smoking (vs. 87% for CBT; p = .03), and 97% of ACT participants would recommend their treatment to a friend (vs. 83% for CBT; p = .06). On the primary outcome of intent-to-treat 30-day point prevalence abstinence at 6 months postrandomization, the quit rates were 31% in ACT versus 22% in CBT (odds ratio [OR] = 1.5, 95% confidence interval [CI] = 0.7-3.4). Among participants depressed at baseline (n = 47), the quit rates were 33% in ACT versus 13% in CBT (OR = 1.2, 95% CI = 1.0-1.6). Consistent with ACT's theory, among participants scoring low on acceptance of cravings at baseline (n = 57), the quit rates were 37% in ACT versus 10% in CBT (OR = 5.3, 95% CI = 1.3-22.0). CONCLUSIONS: ACT is feasible to deliver by phone, is highly acceptable to quitline callers, and shows highly promising quit rates compared with standard CBT quitline counseling. As results were limited by the pilot design (e.g., small sample), a full-scale efficacy trial is now needed.

Use of electronic cigarettes among state tobacco cessation quitline callers.

INTRODUCTION: Little is known about the prevalence of electronic cigarette (e-cigarette) use among tobacco users who seek help from state tobacco quitlines, the reasons for its use, and whether e-cigarettes impact a user's ability to successfully quit tobacco. This study investigates these questions and describes differences among state quitline callers who used e-cigarettes for 1 month or more, used e-cigarettes for less than 1 month, or never tried e-cigarettes. METHODS: Data on e-cigarette use were collected from 2,758 callers to 6 state tobacco quitlines 7 months after they received intervention from the quitline program. RESULTS: Nearly one third (30.9%) of respondents reported ever using or trying e-cigarettes; most used for a short period of time (61.7% for less than 1 month). The most frequently reported reasons for use were to help quit other tobacco (51.3%) or to replace other tobacco (15.2%). Both e-cigarette user groups were significantly less likely to be tobacco abstinent at the 7-month survey compared with participants who had never tried e-cigarettes (30-day point prevalence quit rates: 21.7% and 16.6% vs. 31.3%, p < .001). Demographic differences between the 3 groups are discussed. CONCLUSIONS: This study offers a preliminary look at e-cigarette use among state quitline callers and is perhaps the first to describe e-cigarette use in a large group of tobacco users seeking treatment. The notable rates of e-cigarette use and use of e-cigarettes as cessation aids, even though the U.S. Food and Drug Administration has not approved e-cigarettes for this purpose, should inform policy and treatment discussions on this topic.

Enhancing tobacco quitline effectiveness: identifying a superior pharmacotherapy adjuvant.

INTRODUCTION: Telephone tobacco quitlines are effective and are widely used, with more than 500,000 U.S. callers in 2010. This study investigated the clinical effectiveness and cost-effectiveness of 3 different quitline enhancements: combination nicotine replacement therapy (NRT), longer duration of NRT, and counseling to increase NRT adherence. METHODS: In this study, 987 quitline callers were randomized to a combination of quitline treatments in a 2 × 2 × 2 factorial design: NRT duration (2 vs. 6 weeks), NRT type (nicotine patch only vs. patch plus nicotine gum), and standard 4-call counseling (SC) versus SC plus medication adherence counseling (MAC). The primary outcome was 7-day point-prevalence abstinence (PPA) at 6 months postquit in intention-to-treat (ITT) analyses. RESULTS: Combination NRT for 6 weeks yielded the highest 6-month PPA rate (51.6%) compared with 2 weeks of nicotine patch (38.4%), odds ratios [OR] = 1.71 (95% confidence interval [CI]:1.20-2.45). A similar result was found for 2 weeks of combination NRT (48.2%), OR = 1.49 (95% CI: 1.04-2.14) but not for 6 weeks of nicotine patch alone (46.2%), OR = 1.38 (95% CI: 0.96-1.97). The MAC intervention effect was nonsignificant. Cost analyses showed that the 2-week combination NRT group had the lowest cost per quit ($442 vs. $464 for 2-week patch only, $505 for 6-week patch only, and $675 for 6-week combination NRT). CONCLUSIONS: Combination NRT for 2 or 6 weeks increased 6-month abstinence rates by 10% and 13%, respectively, over rates produced by 2 weeks of nicotine patch when offered with quitline counseling. A 10% improvement would potentially yield an additional 50,000 quitters annually, assuming 500,000 callers to U.S. quitlines per year.

Use and effectiveness of quitlines for smokers with diabetes: cessation and weight outcomes, Washington State Tobacco Quit Line, 2008.

INTRODUCTION: Having diabetes and smoking increases the risk of morbidity and mortality. However, cessation-related weight gain, a common side effect during quitting, can further complicate diabetes. Evidence-based telephone quitlines can support quitting but have not been studied adequately in populations with chronic diseases such as diabetes. The purpose of this study was to evaluate the use and effectiveness of a tobacco quitline among tobacco users with diabetes. Cessation-related weight concerns and weight gain were also assessed. METHODS: We administered a telephone-based follow-up survey to tobacco users with and without diabetes 7 months after their enrollment in a quitline. We collected and analyzed data on demographics, tobacco use, dieting, weight concern, quitting success (7- and 30-day point prevalence), and weight gain. We computed summary statistics for descriptive data, χ(2) and t tests for bivariate comparisons, and multivariable analyses to determine correlates of cessation. RESULTS: Tobacco users with diabetes used the quitline in a greater proportion than they were represented in the general population. Quit rates for those with and without diabetes did not differ significantly (24.3% vs 22.5%). No significant differences existed between groups for weight gain at follow-up, regardless of quit status. However, participants with diabetes reported more weight gain in previous quit attempts (34.2% vs 22.4% gained >20 lbs, P = .03). Weight concern was a significant correlate of continued smoking, regardless of diabetes status. CONCLUSIONS: Results suggest that quitlines are effective for participants with diabetes, but tailored interventions that address weight concerns during cessation are needed.

Developing Digital Therapeutics for Chronic Pain in Primary Care: A Qualitative Human-Centered Design Study of Providers' Motivations and Challenges.

BACKGROUND: Digital therapeutics are growing as a solution to manage pain for patients; yet, they are underused in primary care where over half of the patients with chronic pain seek care. Little is known about how to successfully engage primary care providers in recommending digital therapeutics to their patients. Exploring provider motivations in chronic pain management would potentially help to improve their engagement and inform the development of digital therapeutics. OBJECTIVE: This study examined primary care providers' motivations for chronic pain management, including their strategies and challenges, to inform the future development of chronic pain-related digital therapeutics tailored to primary care settings. METHODS: We conducted qualitative semistructured interviews with health care providers recruited from 3 primary care clinics in Washington and 1 clinic in Colorado between July and October 2021. The sample (N=11) included 7 primary care physicians, 2 behavioral health providers, 1 physician assistant, and 1 nurse. Most providers worked in clinics affiliated with urban academic health systems. Guided by the human-centered design approach and Christensen's Job-to-be-Done framework, we asked providers their goals and priorities in chronic pain management, their experiences with challenges and strategies used to care for patients, and their perceptions of applying digital therapeutics in clinical practice. Transcripts were analyzed using a thematic analysis approach. RESULTS: We found that primary care providers were motivated but challenged to strengthen the patient-provider alliance, provide team-based care, track and monitor patients' progress, and address social determinants of health in chronic pain management. Specifically, providers desired additional resources to improve patient-centered communication, pain education and counseling, and goal setting with patients. Providers also requested greater accessibility to multidisciplinary care team consultations and nonpharmacological pain treatments. When managing chronic pain at the population level, providers need infrastructure and systems to systematically track and monitor patients' pain and provide wraparound health and social services for underserved patients. Recommendations on digital therapeutic features that might address provider challenges in achieving these motivations were discussed. CONCLUSIONS: Given the findings, to engage primary care providers, digital therapeutics for chronic pain management need to strengthen the patient-provider alliance, increase access to nonpharmacological treatment options, support population health tracking and management, and provide equitable reach. Leveraging digital therapeutics in a feasible, appropriate, and acceptable way to aid primary care providers in chronic pain management may require multimodal features that address provider motivations at an individual care and clinic or system level.

Trajectories of cigarettes per day during the course of telephone tobacco cessation counseling services: a comparison of missing data models.

INTRODUCTION: Cigarette smoking accounts for approximately 1 in 5 deaths in the United States every year. To combat smoking, a network of telephone-based smoking cessation counseling services or "quitlines" provide smokers in the United States with smoking cessation resources, and several studies have demonstrated the efficacy of quitlines in promoting long-term smoking cessation. Yet, many individuals who enroll in quitlines do not receive all intended calls, and there is a dearth of research on the impact of missing data on the evaluation of quitline outcomes. METHODS: The current study was a secondary analysis of existing data from a commercial telephone smoking cessation counseling service to estimate the trajectories of cigarettes per day among participants (n = 2,041) during the course of the first 5 calls of the quitline program. Numerous missing data models were estimated to assess the degree to which trajectories of cigarettes per day were associated with the propensity for missing data. RESULTS: The results from growth curve models indicated a significant decrease in cigarettes per day during the quitline program, which was predicted from levels of nicotine dependence. The comparison of missing data models indicated that the propensity for missing data was not systematically associated with the trajectories of cigarettes per day after controlling for level of nicotine dependence. CONCLUSIONS: Analyses conducted in the current study provide evidence that the quitline program was effective at reducing cigarettes per day. Researchers are encouraged to examine missing data mechanisms and control for nicotine dependence in studies of smoking cessation treatment outcomes.

Reaching out, inviting back: using Interactive voice response (IVR) technology to recycle relapsed smokers back to Quitline treatment--a randomized controlled trial.

BACKGROUND: Tobacco dependence is a chronic, relapsing condition that typically requires multiple quit attempts and extended treatment. When offered the opportunity, relapsed smokers are interested in recycling back into treatment for a new, assisted quit attempt. This manuscript presents the results of a randomized controlled trial testing the efficacy of interactive voice response (IVR) in recycling low income smokers who had previously used quitline (QL) support back to QL support for a new quit attempt. METHODS: A sample of 2985 previous QL callers were randomized to either receive IVR screening for current smoking (control group) or IVR screening plus an IVR intervention. The IVR intervention consists of automated questions to identify and address barriers to re-cycling in QL support, followed by an offer to be transferred to the QL and reinitiate treatment. Re-enrollment in QL services for both groups was documented. RESULTS: The IVR system successfully reached 715 (23.9%) former QL participants. Of those, 27% (194/715) reported to the IVR system that they had quit smoking and were therefore excluded from the study and analysis. The trial's final sample was composed of 521 current smokers. The re-enrollment rate was 3.3% for the control group and 28.2% for the intervention group (p < .001). Logistic regression results indicated an 11.2 times higher odds for re-enrollment of the intervention group than the control group (p < .001). Results did not vary by gender, race, ethnicity, or level of education, however recycled smokers were older (Mean = 45.2; SD = 11.7) than smokers who declined a new treatment cycle (Mean = 41.8; SD = 13.2); (p = 0.013). The main barriers reported for not engaging in a new treatment cycle were low self-efficacy and lack of interest in quitting. After delivering IVR messages targeting these reported barriers, 32% of the smokers reporting low self-efficacy and 4.8% of those reporting lack of interest in quitting re-engaged in a new QL treatment cycle. CONCLUSION: Proactive IVR outreach is a promising tool to engage low income, relapsed smokers back into a new cycle of treatment. Integration of IVR intervention for recycling smokers with previous QL treatment has the potential to decrease tobacco-related disparities. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT01260597.

State quitlines and cessation patterns among adults with selected chronic diseases in 15 states, 2005-2008.

INTRODUCTION: The death rate of people who have a chronic disease is lower among former smokers than current smokers. State tobacco cessation quitlines are available for free in every state. The objective of our study was to compare demographic characteristics, use of quitline services, and quit rates among a sample of quitline callers. METHODS: We used data from 15 states on tobacco users aged 18 or older who enrolled with a quitline between October 1, 2005, and May 31, 2008; 9 states also provided data from 7-month follow-up surveys. We used descriptive statistics and logistic regression to compare callers by disease status. RESULTS: Among 195,057 callers, 32.3% reported having 1 or more of the following chronic diseases: 17.7%, asthma; 5.9%, coronary artery disease; 11.1%, chronic obstructive pulmonary disease; and 9.3%, diabetes; 9.0% had 2 or more chronic diseases. Callers who had a chronic disease were older and better educated; more likely to be female, have Medicaid or other health insurance, and have used tobacco for 20 years or more; and less likely to quit smoking (22.3%) at 7 months than callers who had none of these chronic diseases (29.7%). CONCLUSION: About one-third of tobacco users who call state quitlines have a chronic disease, and those who have a chronic disease are less likely to quit using tobacco. Continued efforts are needed to ensure cessation treatments are reaching tobacco users who have a chronic disease and to develop and test ways to increase quit rates among them.

Results from an outreach program for health systems change in tobacco cessation.

INTRODUCTION: Washington state has experienced a dramatic reduction in adult smoking prevalence (22.4% in 1999 to 14.8% in 2010) because of a comprehensive tobacco control effort that includes a proactive health professional education and an outreach program. The outreach program uses academic detailing and online tools to increase routine identification and treatment of tobacco users. This article summarizes outcomes from the first 2 years of the program. METHOD: Outcome measures include the frequency of contact with providers, changes in the percentage of callers reporting that they had heard about the Quit Line from a health professional, and changes in provider Quit Line fax referrals. Data are compared between Initial, Expanded, and Never Outreach Counties. RESULTS: From 2008 to 2010, a total of 629 unique health care organizations and 3,989 unique health professionals received services. Between 2007 and 2010, the ratio of health professional "How Heard Abouts" to total Quit Line registrations increased by 142.6% and 95.4% in Initial and Expanded Outreach Counties, whereas Never Outreach Counties showed an 11.2% increase. Fax referrals to the Quit Line increased by 132% and 232% in Initial and Expanded Outreach Counties whereas they declined by 39% in Never Outreach Counties. DISCUSSION: Results suggests that health professionals can be an important and reliable source of referrals to a treatment resource such as a tobacco quitline. A field-based outreach program using academic detailing principles can be used to increase treatment referrals and holds application for other chronic disease areas and quality improvement programs.

Analysis of Demographic Characteristics of Users of a Free Tobacco Cessation Smartphone App: Observational Study.

BACKGROUND: Tobacco use continues to be the leading preventable cause of death, disease, and disability in the United States. Since 2000, Washington state has offered free tobacco "quitline" services to help its residents stop using tobacco. In 2015, the state began offering free access to a tobacco cessation smartphone app to absorb excess quitline demand. Since most publicly funded tobacco cessation programs are designed to provide access to populations disproportionately impacted by tobacco use, it is important to consider who these public health interventions reach. OBJECTIVE: The aim of this study is to understand who used a free cessation app and the extent to which users represented populations disproportionately impacted by tobacco use. METHODS: This is an observational study of 1280 adult Washington state residents who registered for and activated the cessation app. Demographic data were collected as part of the sign-up process, examined using standard descriptive measures, and assessed against state-level surveillance data for representativeness. RESULTS: Participants were primarily non-Hispanic White (978/1218, 80.3%), identified as female (780/1236, 63.1%), were between ages 25-54 years (903/1186, 76.1%), had at least some college education (836/1222, 68.4%), and reported a household income under US $50,000 (742/1055, 70.3%). Fewer respondents were from rural counties (359/1220, 29.4%); identified as lesbian, gay, bisexual, pansexual, queer, questioning, or asexual (LGBQA; 153/1222, 12.5%); were uninsured (147/1206, 12.2%); or were currently pregnant, planning pregnancy, or breastfeeding (42/624, 6.7%). However, relative to available state data for tobacco users, there was high representation of women, 35- to 54-year-olds, college graduates, and LGBQA individuals, as well as individuals with low household income, poor mental health, Medicaid insurance, and those residing in rural counties. CONCLUSIONS: A diverse population of tobacco users will use a free cessation app, including some demographic groups disproportionately impacted by tobacco use. With high reach and high efficacy, it is possible to address health disparities associated with tobacco use and dependence treatment among certain underserved and at-risk groups.

Implementing Brief Tobacco Cessation Interventions in Community Pharmacies: An Application of Rogers' Diffusion of Innovations Theory.

Pharmacists, as highly accessible members of the healthcare team, have considerable potential to address tobacco use among patients. However, while published data suggest that pharmacists are effective in helping patients quit, barriers exist to routine implementation of cessation services in community pharmacy settings. Within the context of a randomized trial (n = 64 pharmacies), surveys were administered over a period of 6 months to assess pharmacists' perceptions of factors associated with the implementation of "Ask-Advise-Refer", a brief intervention approach that facilitates patient referrals to the tobacco quitline. Study measures, grounded in Rogers' Diffusion of Innovations Theory, assessed pharmacists' perceptions of implementation facilitators and barriers, perceptions of intervention materials provided, and perceived efforts and personal success in implementing Ask-Advise-Refer at 6-months follow-up. Findings indicate that while the brief intervention approach was not difficult to understand or implement, integration into normal workflows presents greater challenges and is associated with overall confidence and implementation success. Lack of time was the most significant barrier to routine implementation. Most (90.6%) believed that community pharmacies should be active in promoting tobacco quitlines. Study results can inform future development of systems-based approaches that lead to broad-scale adoption of brief interventions, including but not limited to tobacco cessation, in pharmacy settings.

Utilization of services in a randomized trial testing phone- and web-based interventions for smoking cessation.

INTRODUCTION: Phone counseling has become standard for behavioral smoking cessation treatment. Newer options include Web and integrated phone-Web treatment. No prior research, to our knowledge, has systematically compared the effectiveness of these three treatment modalities in a randomized trial. Understanding how utilization varies by mode, the impact of utilization on outcomes, and predictors of utilization across each mode could lead to improved treatments. METHODS: One thousand two hundred and two participants were randomized to phone, Web, or combined phone-Web cessation treatment. Services varied by modality and were tracked using automated systems. All participants received 12 weeks of varenicline, printed guides, an orientation call, and access to a phone supportline. Self-report data were collected at baseline and 6-month follow-up. RESULTS: Overall, participants utilized phone services more often than the Web-based services. Among treatment groups with Web access, a significant proportion logged in only once (37% phone-Web, 41% Web), and those in the phone-Web group logged in less often than those in the Web group (mean = 2.4 vs. 3.7, p = .0001). Use of the phone also was correlated with increased use of the Web. In multivariate analyses, greater use of the phone- or Web-based services was associated with higher cessation rates. Finally, older age and the belief that certain treatments could improve success were consistent predictors of greater utilization across groups. Other predictors varied by treatment group. CONCLUSIONS: Opportunities for enhancing treatment utilization exist, particularly for Web-based programs. Increasing utilization more broadly could result in better overall treatment effectiveness for all intervention modalities.

Adherence to varenicline in the COMPASS smoking cessation intervention trial.

INTRODUCTION: Patient adherence to smoking cessation medications can impact their effectiveness. It is important to understand the extent to which prescribed medications are actually taken by smokers, how this influences smoking cessation outcomes, and what factors may influence adherence. METHODS: Smokers recruited from a large health plan were randomized to receive different modes of cessation counseling in combination with varenicline (Swan, G. E., McClure, J. B., Jack, L. M., Zbikowski, S. M., Javitz, H. S., Catz, S. L., et al. 2010.Behavioral counseling and varenicline treatment for smoking cessation. American Journal of Preventive Medicine, 38, 482-490). One thousand one hundred and sixty-one participants were mailed a 28-day varenicline supply when they set a quit date and were able to request up to two refills from the health plan pharmacy at no cost. Pharmacy fill records were obtained and telephone surveys completed at baseline, 21 days, 12 weeks, and 6 months post target quit date. RESULTS: Good adherence to varenicline (≥80% of days taken) was associated with a twofold increase in 6-month quit rates compared with poor adherence (52% vs. 25%). Smokers were more likely than nonsmokers to stop varenicline early. Purposeful nonadherence was associated with smoking at 12 weeks and was predicted in multivariate analyses by age, gender, adherence self-efficacy, and initial medication side effect severity. CONCLUSIONS: Innovative methods for increasing adherence to smoking cessation medications are needed, particularly early in the quit process. Simple metrics of adherence such as number of days cessation medication is taken can and should be routinely incorporated in effectiveness trials and reported to advance future attempts to understand and reduce nonadherence.