Individual Predictors of Response to A Behavioral Activation-Based Digital Smoking Cessation Intervention: A Machine Learning Approach.

Background: Depression is prevalent among individuals who smoke cigarettes and increases risk for relapse. A previous clinical trial suggests that Goal2Quit, a behavioral activation-based smoking cessation mobile app, effectively increases smoking abstinence and reduces depressive symptoms. Objective: Secondary analyses were conducted on these trial data to identify predictors of success in depression-specific digitalized cessation interventions. Methods: Adult who smoked cigarettes (age = 38.4 ± 10.3, 53% women) were randomized to either use Goal2Quit for 12 weeks (N = 103), paired with a 2-week sample of nicotine replacement therapy (patch and lozenge) or to a Treatment-As-Usual (TAU) control (N = 47). The least absolute shrinkage and selection operator was utilized to identify a subset of baseline variables predicting either smoking or depression intervention outcomes. The retained predictors were then fitted via linear regression models to determine relations to each intervention outcome. Results: Relative to TAU, only individuals who spent significant time using Goal2Quit (56 ± 46 min) were more likely to reduce cigarette use by at least 50% after 12 weeks, whereas those who spent minimal time using Goal2Quit (10 ± 2 min) did not exhibit significant changes. An interaction between educational attainment and treatment group revealed that, as compared to TAU, only app users with an educational degree beyond high school exhibited significant reductions in depression. Conclusions: The findings highlight the importance of tailoring depression-specific digital cessation interventions to individuals' unique engagement needs and educational level. This study provides a potential methodological template for future research aimed at personalizing technology-based treatments for cigarette users with depressive symptoms.

Remote Carbon Monoxide Capture via REDCap: Evaluation of an Integrated Mobile Application.

INTRODUCTION: To improve the feasibility of remote biochemical verification of smoking status, our team developed "COast", a mobile app integrated with REDCap that allows a research participant to complete self-report research assessments and provide a breath sample via the iCOQuit® Smokerlyzer® for the purposes of carbon monoxide (CO) testing. The aims of the present study were to examine: 1) the validity of remote CO data capture using COast as compared to gold standard approaches (salivary cotinine, stand-alone CO monitor) and 2) the feasibility of remote CO data capture using COast as applied to both daily and weekly CO collection schedules. METHODS: Participants (N=143, 59% Female), including recently quit (n=36) and current (n=107) smokers, completed a baseline video session to capture validity data, and then were randomized to daily or weekly CO monitoring for a period of one month. RESULTS: Balancing both sensitivity and specificity, optimal cut-points for defining abstinence using the COast system were < 4 parts per million (ppm) with salivary cotinine as the referent (Sensitivity = 100%, Specificity = 92.8%) and < 8ppm with the stand-alone CO monitor as the referent (Sensitivity = 100%, Specificity = 88.9%). Compliance across groups with CO monitoring was high with average compliance of 74% for the daily group and 84% for the weekly group. Self-reported feasibility and acceptability of using the system were strong. CONCLUSIONS: Pairing the iCOQuit with REDCap via the COast app was both valid and feasible among a sample of adults who smoke cigarettes enrolled remotely. This integration may help to improve the rigor of decentralized smoking cessation trials. IMPLICATIONS: With increasing prevalence of decentralized trial designs, innovative methods are needed to remotely capture biomarkers. Methods that leverage existing widely available research data capture platforms may be particularly useful for promoting adoption. The COast app, which integrates a Bluetooth-enabled carbon monoxide monitor with REDCap, is a fitting, valid, feasible solution to remotely biochemically verify smoking status.

Cannabis use prevalence, patterns, and reasons for use among patients with cancer and survivors in a state without legal cannabis access.

PURPOSE: Cannabis use among patients with cancer is common, yet data are limited regarding use patterns, reasons for use, and degree of benefit, which represents an unmet need in cancer care delivery. This need is salient in states without legal cannabis programs, where perceptions and behavior among providers and patients may be affected. METHODS: A cross-sectional survey of patients with cancer and survivors at the Hollings Cancer Center at the Medical University of South Carolina (no legal cannabis marketplace in SC) was completed as part of the NCI Cannabis Supplement. Patients (ages 18 +) were recruited using probability sampling from patient lists (N = 7749 sampled; N = 1036 completers). Weight-adjusted Chi-square tests compared demographics and cancer details among patients using cannabis since diagnosis versus those not using cannabis, while weighted descriptives are presented for cannabis use prevalence, consumption, symptom management, and legalization beliefs. RESULTS: Weighted prevalence of cannabis use since diagnosis was 26%, while current cannabis use was 15%. The most common reasons for cannabis use after diagnosis were difficulty sleeping (50%), pain (46%), and mood changes and stress, anxiety, or depression (45%). Symptom improvement was endorsed for pain (57%), stress/anxiety/depression (64%), difficulty sleeping (64%), and loss of appetite (40%). CONCLUSIONS: Among patients with cancer and survivors at a NCI-designated cancer center within SC, a state without legal access to medical cannabis, prevalence rates, and reasons for cannabis use are consistent with emerging literature in oncology populations. These findings have implications for care delivery, and work is needed to inform recommendations for providers and patients.

Mechanism underlying a brief cognitive behavioral treatment for head and neck cancer survivors with body image distress.

PURPOSE: Body image distress (BID) among head and neck cancer (HNC) survivors is a debilitating toxicity associated with depression, anxiety, stigma, and poor quality of life. BRIGHT (Building a Renewed ImaGe after Head & neck cancer Treatment) is a brief cognitive behavioral therapy (CBT) that reduces BID for these patients. This study examines the mechanism underlying BRIGHT. METHODS: In this randomized clinical trial, HNC survivors with clinically significant BID were randomized to receive five weekly psychologist-led video tele-CBT sessions (BRIGHT) or dose-and delivery matched survivorship education (attention control [AC]). Body image coping strategies, the hypothesized mediators, were assessed using the Body Image Coping Skills Inventory (BICSI). HNC-related BID was measured with the Inventory to Measure and Assess imaGe disturbancE-Head and Neck (IMAGE-HN). Causal mediation analyses were used to estimate the mediated effects of changes in BICSI scores on changes in IMAGE-HN scores. RESULTS: Among 44 HNC survivors with BID allocated to BRIGHT (n = 20) or AC (n = 24), mediation analyses showed that BRIGHT decreased avoidant body image coping (mean change in BICSI-Avoidance scale score) from baseline to 1-month post-intervention relative to AC (p = 0.039). Decreases in BICSI-Avoidance scores from baseline to 1-month resulted in decreases in IMAGE-HN scores from baseline to 3 months (p = 0.009). The effect of BRIGHT on IMAGE-HN scores at 3 months was partially mediated by a decrease in BICSI-Avoidance scores (p = 0.039). CONCLUSIONS: This randomized trial provides preliminary evidence that BRIGHT reduces BID among HNC survivors by decreasing avoidant body image coping. Further research is necessary to confirm these results and enhance the development of interventions targeting relevant pathways to reduce BID among HNC survivors. TRIAL REGISTRATION: ClinicalTrials.gov identifier NCT03831100 .

Behavioral Activation-Based Digital Smoking Cessation Intervention for Individuals With Depressive Symptoms: Randomized Clinical Trial.

BACKGROUND: Depression is common among adults who smoke cigarettes. Existing depression-specific cessation interventions have limited reach and are unlikely to improve smoking prevalence rates among this large subgroup of smokers. OBJECTIVE: This study aimed to determine whether a mobile app-based intervention tailored for depression paired with a mailed sample of nicotine replacement therapy (NRT) is efficacious for treating depression and promoting smoking cessation. METHODS: A 2-arm nationwide remote randomized clinical trial was conducted in the United States. Adults (N=150) with elevated depressive symptoms (Patient Health Questionnaire-8≥10) who smoked were enrolled. The mobile app ("Goal2Quit") provided behavioral strategies for treating depression and quitting smoking based on Behavioral Activation Treatment for Depression. Goal2Quit participants also received a 2-week sample of combination NRT. Treatment as usual participants received a self-help booklet for quitting smoking that was not tailored for depression. Primary end points included Goal2Quit usability, change in depression (Beck Depression Inventory-II) across 12 weeks, and smoking cessation including reduction in cigarettes per day, incidence of 24-hour quit attempts, floating abstinence, and 7-day point prevalence abstinence (PPA). RESULTS: In total, 150 participants were enrolled between June 25, 2020, and February 23, 2022, of which 80 were female (53.3%) and the mean age was 38.4 (SD 10.3) years. At baseline, participants on average reported moderate depressive symptoms and smoked a mean of 14.7 (SD 7.5) cigarettes per day. Goal2Quit usability was strong with a mean usability rating on the System Usability Scale of 78.5 (SD 16.9), with 70% scoring above the ≥68 cutoff for above-average usability. Retention data for app use were generally strong immediately following trial enrollment and declined in subsequent weeks. Those who received Goal2Quit and the NRT sample reported lower mean depressive symptoms over the trial duration as compared to treatment as usual (difference of mean 3.72, SE 1.37 points less; P=.01). Across time points, all cessation outcomes favored Goal2Quit. Regarding abstinence, Goal2Quit participants reported significantly higher rates of 7-day PPA at weeks 4 (11% vs 0%; P=.02), 8 (7-day PPA: 12% vs 0%; P=.02), and 12 (16% vs 2%; P=.02). CONCLUSIONS: A mobile app intervention tailored for depression paired with a sample of NRT was effective for depression treatment and smoking cessation. Findings support the utility of this intervention approach for addressing the currently unmet public health treatment need for tailored, scalable depression-specific cessation treatments. TRIAL REGISTRATION: ClinicalTrials.gov NCT03837379; https://clinicaltrials.gov/ct2/show/NCT03837379.

The Cost-Effectiveness of Nicotine Replacement Therapy Sampling in Primary Care: a Markov Cohort Simulation Model.

BACKGROUND: Pharmacotherapies remain a central focus of successful tobacco control, but uptake remains very low. OBJECTIVE: To estimate the cost effectiveness of a primary care nicotine replacement therapy (NRT) sampling intervention. DESIGN: A Markov cohort simulation model was constructed to conduct cost-effectiveness analyses. Clinical trial results were used to initialize the Markov model. All other model parameters were derived from the literature. The study was conducted over a lifetime horizon, from the payers' budgetary perspective. PARTICIPANTS: Smokers with a primary care visit. INTERVENTION: Medication sampling, which provided short, starter packets of NRT (nicotine patch and lozenge) to smokers in the primary care setting. MAIN MEASURES: Lifetime healthcare expenditures, quality-adjusted life years, and life years. KEY RESULTS: Medication sampling was the dominant strategy compared to standard care. Our intervention cost $75, yielding a discounted lifetime savings of $1065 in healthcare expenditures, and increased both discounted quality-adjusted life years and discounted life years by 0.01. One-way sensitivity analyses showed that medication sampling remained dominant in plausible ranges except when it failed to increase cessation relative to standard care. Probabilistic sensitivity analyses confirmed that medication sampling was dominant in 94.1% of the simulated cases, with an implementation cost of $74 (95% CI $73-$76) and discounted lifetime savings in health expenditures of $1061 (- $1106 to - $1,017), increasing quality-adjusted life years by 0.008 (0.0085-0.0093) and life years by 0.008 (0.0081-0.0089). CONCLUSION: Medication sampling, an easily implementable, scalable and low-cost intervention to encourage smoking cessation, is cost saving and improves quality of life.

Proactive Electronic Visits for Smoking Cessation and Chronic Obstructive Pulmonary Disease Screening in Primary Care: Randomized Controlled Trial of Feasibility, Acceptability, and Efficacy.

BACKGROUND: Most smokers with chronic obstructive pulmonary disease (COPD) have not yet been diagnosed, a statistic that has remained unchanged for over two decades. A dual-focused telehealth intervention that promotes smoking cessation, while also facilitating COPD screening, could help address national priorities to improve the diagnosis, prevention, treatment, and management of COPD. The purpose of this study was to preliminarily evaluate an integrated asynchronous smoking cessation and COPD screening e-visit (electronic visit) that could be delivered proactively to adult smokers at risk for COPD, who are treated within primary care. OBJECTIVE: The aims of this study were (1) to examine e-visit feasibility and acceptability, particularly as compared to in-lab diagnostic pulmonary function testing (PFT), and (2) to examine the efficacy of smoking cessation e-visits relative to treatment as usual (TAU), all within primary care. METHODS: In a randomized clinical trial, 125 primary care patients who smoke were randomized 2:1 to receive either proactive e-visits or TAU. Participants randomized to the e-visit condition were screened for COPD symptoms via the COPD Assessment in Primary Care to Identify Undiagnosed Respiratory Disease and Exacerbation Risk (CAPTURE). Those with scores ≥2 were invited to complete both home spirometry and in-lab PFTs, in addition to two smoking cessation e-visits. Smoking cessation e-visits assessed smoking history and motivation to quit and included completion of an algorithm to determine the best Food and Drug Administration-approved cessation medication to prescribe. Primary outcomes included measures related to (1) e-visit acceptability, feasibility, and treatment metrics; (2) smoking cessation outcomes (cessation medication use, 24-hour quit attempts, smoking reduction ≥50%, self-reported abstinence, and biochemically confirmed abstinence); and (3) COPD screening outcomes. RESULTS: Of 85 participants assigned to the e-visits, 64 (75.3%) were invited to complete home spirometry and in-lab PFTs based on CAPTURE. Among those eligible for spirometry, 76.6% (49/64) completed home spirometry, and 35.9% (23/64) completed in-lab PFTs. At 1 month, all cessation outcomes favored the e-visit, with a significant effect for cessation medication use (odds ratio [OR]=3.22). At 3 months, all cessation outcomes except for 24-hour quit attempts favored the e-visit, with significant effects for cessation medication use (OR=3.96) and smoking reduction (OR=3.09). CONCLUSIONS: A proactive, asynchronous e-visit for smoking cessation and COPD screening may offer a feasible, efficacious approach for broad interventions within primary care. TRIAL REGISTRATION: ClinicalTrials.gov NCT04155073; https://clinicaltrials.gov/ct2/show/NCT04155073.

Mobile, Remote, and Individual Focused: Comparing Breath Carbon Monoxide Readings and Abstinence Between Smartphone-Enabled and Stand-Alone Monitors.

INTRODUCTION: Newly available, smartphone-enabled carbon monoxide (CO) monitors are lower in cost than traditional stand-alone monitors and represent a marked advancement for smoking research. New products are promising, but data are needed to compare breath CO readings between smartphone-enabled and stand-alone monitors. The purpose of this study was to (1) determine the agreement between the mobile iCO (Bedfont Scientific Ltd) with two other monitors from the same manufacturer (Micro+ pro and Micro+ basic) and (2) determine optimal, monitor-specific, cotinine-confirmed abstinence cutoff values. METHODS: Adult (≥18) smokers (n = 26) and nonsmokers (n = 21) provided three breath CO samples (using three different monitors) in each of 10 sessions, and urine cotinine was measured for gold standard determination of abstinence. CO comparisons (N = 437) were analyzed using regression-based Bland-Altman Analysis of Agreement; receiver operating characteristics curves were used to determine optimal abstinence cutoffs. RESULTS: Bland-Altman analyses indicated that the iCO monitor provided higher CO results than both Micro+ monitors. Sensitivity and specificity analyses showed that the optimal CO cutoff for determining abstinence was <3 ppm for the Micro+ pro (88% sensitivity, 93% specificity) and Micro+ basic (83% sensitivity, 98% specificity), but was higher for the iCO (<6 ppm; 73% sensitivity, 100% specificity). CONCLUSIONS: Relative to both Micro+ monitors, the smartphone-enabled iCO provided systematically higher CO values and required a higher cutoff to reliably determine smoking abstinence. This does not indicate that CO values obtained using the iCO are not valid; instead, these results suggest that monitor-specific abstinence cutoffs are needed to ensure accurate bioverification of smoking status. IMPLICATIONS: Results from this study indicate that CO values from the smartphone-enabled iCO should not be used interchangeably with the stand-alone Micro+ pro and Micro+ basic, particularly when lower CO values (<10 ppm) are critical (ie, determination of abstinence vs confirming smoking status for study inclusion). Optimal CO cutoffs recommended for determining abstinence on Micro+ and iCO monitors are at <3 and <6 ppm, respectively.

A Pilot Randomized Clinical Trial of Remote Varenicline Sampling to Promote Treatment Engagement and Smoking Cessation.

INTRODUCTION: Medication sampling is a clinically useful tool to engage smokers in the quitting process. Whether varenicline is suitable for sampling purposes is unclear. The purpose of this study was to examine the feasibility, uptake, and preliminary outcomes of varenicline sampling. METHODS: Smokers (N = 99), both motivated to quit and not, were recruited and randomized to varenicline sampling versus not, with 12 week follow-up. The intervention consisted of mailing one-time samples of varenicline (lasting 2-4 wks), with minimally suggestive guidance on use. RESULTS: Uptake of varenicline was strong, at 2 weeks (54% any use, 66% daily use) and 4 weeks (38%, 46%), with 58% of medication users seeking additional medication. Most users followed conventional titration patterns, self-titrating from 0.5 mg to 2 mg. Relative to control, varenicline sampling increased motivation (p = 0.006) and confidence to quit (p = 0.02), and decreased cigarette smoking (p = 0.02). Smokers receiving varenicline samples were significantly more likely to achieve 50% reduction in cigarettes per day (CPD), both immediately following the sampling exercise (Adjusted Odds Ratio [AOR] = 4.12; 95% CI: 1.39 to 12.17) and at final follow-up (AOR = 4.50; 95% CI: 1.56 to 13.01). Though cessation outcomes were not statistically significant, there was a 1.5 to 3-fold increase in quit attempts and abstinence from varenicline sampling throughout follow-up. These outcomes were comparable among smokers motivated to quit and not. CONCLUSIONS: Unguided, user-driven sampling of varenicline sampling is a concrete behavioral exercise that is feasible to do and seems to suggest clinical utility. Sampling is a pragmatic clinical approach to engage more smokers in quitting. IMPLICATIONS: Use of evidence-based pharmacotherapies for smoking cessation is low. Medication sampling is a pragmatic behavioral exercise that allows smokers to experience the benefits of using them, while promoting positive downstream effects towards quitting. While previous studies have shown that nicotine replacement therapy (NRT) sampling is viable and effective, whether this extends to varenicline is unclear. Results from this trial demonstrate that varenicline sampling is feasible, safe, and suggestive of clinically important steps toward quitting, deserving of a larger trial. CLINICAL TRIAL REGISTRATION: NCT #03742154.

Evaluation of a Proactive Smoking Cessation Electronic Visit to Extend the Reach of Evidence-Based Cessation Treatment via Primary Care.

Background:Best practice guidelines for smoking cessation treatment through primary care advise the 5As model. However, compliance with these guidelines is poor, leaving many smokers untreated. The purpose of this study was to develop and preliminarily evaluate an asynchronous smoking cessation electronic visit (e-visit) that could be delivered proactively through the electronic health record (EHR) to adult smokers treated within primary care. The goal of the e-visit is to automate 5As delivery to ensure that all smokers receive evidence-based cessation treatment. As such, the aims of this study were twofold: (1) to examine acceptability, feasibility, and treatment metrics associated with e-visit utilization and (2) to preliminarily examine efficacy relative to treatment as usual (TAU) within primary care.Methods:Participants (n = 51) were recruited from primary care practices between November 2018 and October 2019 and randomized 2:1 to receive either the smoking cessation e-visit or TAU. Participants completed assessments of cessation outcomes 1-month and 3-months postenrollment and e-visit analytics data were gathered from the EHR.Results:Self-report feedback from e-visit participants indicated satisfaction with the intervention and interest in using e-visits again in the future. Nearly all e-visits resulted in prescription of a U.S. Food and Drug Administration (FDA)-approved smoking cessation medication. In general, smoking cessation outcomes favored the e-visit condition at both 1 (odds ratios [ORs]: 2.10-5.39) and 3 months (ORs: 1.31-4.67).Conclusions:These results preliminarily indicate the feasibility, acceptability, and efficacy of this smoking cessation e-visit within primary care. Future studies should focus on larger scale examination of effectiveness and implementation across settings. The clinicaltrials.gov registration number for this trial is NCT04316260.

The differential impact of nicotine replacement therapy sampling on cessation outcomes across established tobacco disparities groups.

Cigarette smoking is increasingly concentrated among marginalized populations with limited access to evidence-based cessation treatment. This includes racial/ethnic minorities, lower income individuals, those with lower educational attainment, and residents of rural areas. To reach Healthy People 2020 objectives, successful cessation interventions must narrow these disparities. Nicotine replacement therapy (NRT) sampling is an easily translatable and scalable intervention that could enhance treatment access and thus narrow disparities. The present study examined individual-level demographic moderators of the impact of NRT sampling on cessation-related behaviors including: 1) use of a cessation medication, 2) making a 24-hour quit attempt, 3) floating abstinence, and 4) 7-day point prevalence abstinence at 6-months. Study participants included N = 1245 adult smokers enrolled in the Tobacco Intervention in Primary Care Treatment Opportunities for Providers (TIP TOP) study, a recently concluded large-scale clinical trial of NRT sampling relative to standard care within 22 primary care clinics across South Carolina. Generalized linear models examined individual-level demographic moderators of treatment effect. Results suggest that NRT sampling may be more effective among some of the most disadvantaged groups of smokers, including smokers with lower income and education, as well those who live in more rural areas. The effects of NRT sampling did not differ by race. In sum, NRT sampling is a low-cost, low-burden intervention that could be disseminated broadly to reach large numbers of smokers and potentially narrow cessation disparities.

Remote Methods for Conducting Tobacco-Focused Clinical Trials.

Most tobacco-focused clinical trials are based on locally conducted studies that face significant challenges to implementation and successful execution. These challenges include the need for large, diverse, yet still representative study samples. This often means a protracted, costly, and inefficient recruitment process. Multisite clinical trials can overcome some of these hurdles but incur their own unique challenges. With recent advances in mobile health and digital technologies, there is now a promising alternative: Remote Trials. These trials are led and coordinated by a local investigative team, but are based remotely, within a given community, state, or even nation. The remote approach affords many of the benefits of multisite trials (more efficient recruitment of larger study samples) without the same barriers (cost, multisite management, and regulatory hurdles). The Coronavirus Disease 2019 (COVID-19) global health pandemic has resulted in rapid requirements to shift ongoing clinical trials to remote delivery and assessment platforms, making methods for the conduct of remote trials even more timely. The purpose of the present review is to provide an overview of available methods for the conduct of remote tobacco-focused clinical trials as well as illustrative examples of how these methods have been implemented across recently completed and ongoing tobacco studies. We focus on key aspects of the clinical trial pipeline including remote: (1) study recruitment and screening, (2) informed consent, (3) assessment, (4) biomarker collection, and (5) medication adherence monitoring. Implications With recent advances in mobile health and digital technologies, remote trials now offer a promising alternative to traditional in-person clinical trials. Remote trials afford expedient recruitment of large, demographically representative study samples, without undo burden to a research team. The present review provides an overview of available methods for the conduct of remote tobacco-focused clinical trials across key aspects of the clinical trial pipeline.

State Tobacco Excise Taxation, Comprehensive Smoke-free Air Laws, and Tobacco Control Appropriations as Predictors of Smoking Cessation Success in the United States.

The purpose of the present study was (1) to examine demographic differences between smokers who successfully quit (n = 1809), who relapsed (n = 6548), and who did not attempt to quit (n = 11 102) within the last year, and (2) to examine state-level tobacco policies/programs as predictors of quit success. Data were utilized from the 2014-2015 Tobacco Use Supplement to the Current Population Survey, which were paired with 2014 data on taxation, appropriations, and smoke-free air laws. As compared with smokers who relapsed, those who successfully quit were more likely to be white, married, more highly educated, of higher income, and heavier smokers. Compared with those who did not attempt to quit, those who attempted to quit, regardless of success, were younger and more likely to be Hispanic. State comprehensive smoke-free air laws and tobacco excise taxation significantly predicted quit success. Thus, expansions of these policies should be considered to promote successful quitting.

Implementation and Utility of an Automated Text Messaging System to Facilitate Symptom Self-Monitoring and Identify Risk for Post-Traumatic Stress Disorder and Depression in Trauma Center Patients.

Background and Introduction: Comprehensive monitoring and follow-up after traumatic injury is important for psychological recovery. However, scalable services to facilitate this are limited. Automated text message-based symptom self-monitoring (SSM) may be a feasible approach. This study examined its implementation and utility in identifying patients at risk for mental health difficulties after traumatic injury.Materials and Methods: Five hundred two patients admitted to a Level I trauma center between June 20, 2016 and July 31, 2017 were offered enrollment in a text message-based SSM service. Patients who enrolled received daily text message prompts over 30 days and most participated in a mental health screening 30 days postbaseline.Results: Approximately 67% of patients enrolled in the service; of these, 58% responded to the text messages, with an average response rate of 53%. Younger patients and those with elevated peritraumatic distress were more likely to enroll. Patients with higher levels of mental health stigma, who were White, or had been in a motor vehicle collision were more likely to enroll and respond to text messages once enrolled. Patients' daily ratings of distress detected clinically elevated 30-day mental health screens with high sensitivity (83%) and specificity (70%).Discussion and Conclusions: Text message-based SSM can be implemented as a clinical service in Level I trauma centers, and patient participation may increase engagement in mental health follow-up. Further, it can inform the use of risk assessments in practice, which can be used to identify patients with poor psychological recovery who require additional screening.

State Tobacco Policies as Predictors of Evidence-Based Cessation Method Usage: Results From a Large, Nationally Representative Dataset.

Introduction: Evidence-based cessation methods including nicotine replacement therapy (NRT), non-NRT medications, quitlines, and behavioral treatments are underutilized by smokers attempting to quit. Although a number of studies have demonstrated a relationship between state-level tobacco policies (eg, taxation, appropriations) and cessation, whether such state-level factors influence likelihood of using an evidence-based treatment is unclear. Accordingly, the aims of the present study were: (1) to describe evidence-based cessation method utilization by state and (2) to examine the effect of state-level factors on cessation method utilization above and beyond individual-level predictors. Methods: Data were utilized from the 2010-2011 Tobacco Use Supplement to the Current Population Survey (TUS-CPS). Participants included 9232 smokers who reported a past-year quit attempt. Data on 11 state-level predictors were collated from national datasets. Analyses were based on: (1) descriptive characterization of quit method usage, (2) logistic regression models to determine state-level factors as predictors of quit method utilization, controlling for individual-level predictors, (3) cluster analyses grouping states with similar state-level factors, and (4) examination of cluster as a predictor of cessation method. Results: Tobacco control appropriations significantly predicted NRT, quitline, and behavioral treatment utilization. Additional state-level factors that demonstrated significant relationships included Medicaid coverage of non-NRT medications and behavioral treatment, tobacco tax rate, smoking prevalence, and percentage of population uninsured. State clustering significantly predicted quit method across all four methods. Conclusions: State-level factors influence the likelihood of residents utilizing evidence-based quit methods. Results are discussed in terms of implications for tobacco policy at the state level. Implications: Results from the present study highlight state tobacco control appropriations as a robust predictor of evidence-based cessation method utilization. Other significant state-level predictors of evidence-based cessation method utilization included Medicaid coverage of non-NRT medications and behavioral treatment, tobacco tax rate, smoking prevalence, and percentage of population uninsured. Moreover, state-level predictors clustered together to significantly predict evidence-based cessation method utilization. Thus, increasing tobacco control appropriations, extending health insurance coverage, maximizing revenue from tobacco taxation and tobacco settlements, and ultimately decreasing smoking prevalence are important targets for individual states to promote utilization of evidence-based cessation methods.

Health Equity and Decentralized Trials.

This Viewpoint discusses the proliferation of decentralized clinical trials during the COVID-19 pandemic and the need for rigorous studies to inform whether decentralized approaches promote or prevent access to clinical trials for people facing health disparities.

Development and Preliminary Feasibility Study of a Brief Behavioral Activation Mobile Application (Behavioral Apptivation) to Be Used in Conjunction With Ongoing Therapy.

Depressive symptoms are the most frequently treated psychiatric condition in the United States. Brief behavioral activation treatment for depression (BATD) is a popular, evidence-based psychotherapy with strong research support for the treatment of depression. In this paper, we describe the development and initial pilot feasibility testing of a BATD mobile application (Behavioral Apptivation) to be used by patients and therapists in conjunction with BATD therapy. We present information regarding the app development process as well as results from a small open-label feasibility trial of the app utilized in conjunction with individual BATD. We include a case series from the open-label trial highlighting how Behavioral Apptivation can be utilized in clinical practice.

The differential impact of state tobacco control policies on cessation treatment utilization across established tobacco disparities groups.

Tobacco control policies are effective in promoting quit attempts and increase the likelihood that smokers use evidence-based cessation treatments (e.g., nicotine replacement therapies (NRT), non-NRT medications, behavioral treatment, and/or quitlines). However, what is less clear is how these policies might differentially impact different groups of smokers, perhaps in some cases even widening disparities in the use of evidence-based tobacco dependence treatments. This paper examined how different state-level tobacco control policies impact the use of evidence-based cessation treatments by race/ethnicity, gender, socio-economic status (SES), age, and smoking history. Participants included 9110 adult smokers reporting a past-year quit attempt within the 2010-2011 Tobacco Use Supplement to the Current Population Survey. Lasso regression modeling was used to identify a subset of interactions between tobacco policies and individual smoker characteristics that predicted use of evidence-based cessation treatment. Significant interactions were fitted via participant-weighted generalized linear models to determine effect sizes and relations to each cessation treatment outcome. Results highlighted that various state level tobacco control policies differentially impacted the reported use of both prescription and non-prescription stop smoking medications by race/ethnicity, age, and SES. The relationship between state level tobacco control policies and the use of behavioral treatments and quitlines did not differ by smoker characteristics. In sum, tobacco control policies differentially impact the use of FDA approved stop smoking medications across different race/ethnicity, age, and SES groups. Understanding such effects can help to target interventions to ensure equal access to evidence-based tobacco dependence treatments.

Depressive Symptoms and Cigarette Demand as a Function of Induced Stress.

INTRODUCTION: Depressed smokers may disproportionately value cigarettes as compared to other reinforcers in the context of increases in negative affect (NA). Thus, cigarette demand may be an important construct for understanding the relationship between depression, NA change, and tobacco use. The aim of the current study was to examine the interaction between depressive symptoms and change in NA as a function of induced mood as a predictor of cigarette demand. METHODS: Participants included 73 young adult daily smokers (41.70% female, 73.60% White, age M (SD) = 19.70 (1.15)) who attended two experimental sessions: one stress and one neutral. During each session, participants completed ratings of depressive symptoms, NA, and cigarette demand. RESULTS: We examined the predictive utility of depressive symptoms, change in NA as a result of a stressor, and the interaction between depressive symptoms and NA change on demand indices. Separate models were constructed by session. Results indicated significant interactive effects between depressive symptoms and change in NA for predicting intensity, breakpoint, and P max during the stress session. Specifically, change in NA moderated the relationship between depression and demand indices such that among individuals high in NA change, depressive symptoms were positively related to P max and breakpoint, whereas among individuals low in NA change, depressive symptoms were positively related to intensity. CONCLUSIONS: When exposed to stress, cigarettes may become more valuable for individuals with depressive symptoms. IMPLICATIONS: This study contributes to the literature attempting to understand the complex relationships between depression, stress-related changes in NA, and tobacco use. This study suggests that one mechanism that may be important to the relationship between depression and tobacco use is cigarette demand. Specifically, for individuals with elevated depressive symptoms, certain aspects of cigarette demand may be higher (intensity, breakpoint, and P max) when exposed to stress, which may contribute to tobacco use being maintained over time.

Moodivate: A self-help behavioral activation mobile app for utilization in primary care-Development and clinical considerations.

Depressive symptoms are highly prevalent and are associated with considerable functional impairment, significant public health costs, and heightened mortality risk. Individuals experiencing impairment due to depressive symptomatology are most likely to report their symptoms to a primary care provider. As such, national guidelines highlight the need to assess and effectively treat depression via primary care. Despite these guidelines, the dissemination of evidence-based psychotherapy via primary care is limited, likely due to both provider- and patient-level treatment barriers. Mobile health (mHealth) technologies are promising for addressing these barriers and for promoting uptake of evidence-based depression treatment. Among evidence-based psychotherapies for depression, brief Behavioral Activation Treatment for Depression (BATD) has shown great promise and is particularly amenable to mHealth delivery. Herein, we discuss the development of a BATD mobile application, Moodivate, that was developed in order to disseminate BATD via primary care. This paper focuses on description of (1) rationale for Moodivate treatment development, (2) Moodivate treatment components, (3) ongoing clinical trial evaluation of Moodivate, and (4) clinical considerations for incorporating Moodivate into clinical practice.