A Framework for Integrating Telehealth Equitably across the cancer care continuum.

The COVID-19 pandemic placed a spotlight on the potential to dramatically increase the use of telehealth across the cancer care continuum, but whether and how telehealth can be implemented in practice in ways that reduce, rather than exacerbate, inequities are largely unknown. To help fill this critical gap in research and practice, we developed the Framework for Integrating Telehealth Equitably (FITE), a process and evaluation model designed to help guide equitable integration of telehealth into practice. In this manuscript, we present FITE and showcase how investigators across the National Cancer Institute's Telehealth Research Centers of Excellence are applying the framework in different ways to advance digital and health equity. By highlighting multilevel determinants of digital equity that span further than access alone, FITE highlights the complex and differential ways structural determinants restrict or enable digital equity at the individual and community level. As such, achieving digital equity will require strategies designed to not only support individual behavior but also change the broader context to ensure all patients and communities have the choice, opportunity, and resources to use telehealth across the cancer care continuum.

Scalable Telehealth Cancer Care: integrated healthy lifestyle program to live well after cancer treatment.

Northwestern University's Center for Scalable Telehealth Cancer Care (STELLAR) is 1 of 4 Cancer Moonshot Telehealth Research Centers of Excellence programs funded by the National Cancer Institute to establish an evidence base for telehealth in cancer care. STELLAR is grounded in the Institute of Medicine's vision that quality cancer care includes not only disease treatment but also promotion of long-term health and quality of life (QOL). Cigarette smoking, insufficient physical activity, and overweight and obesity often co-occur and are associated with poorer treatment response, heightened recurrence risk, decreased longevity, diminished QOL, and increased treatment cost for many cancers. These risk behaviors are prevalent in cancer survivors, but their treatment is not routinely integrated into oncology care. STELLAR aims to foster patients' long-term health and QOL by designing, implementing, and sustaining a novel telehealth treatment program for multiple risk behaviors to be integrated into standard cancer care. Telehealth delivery is evidence-based for health behavior change treatment and is well suited to overcome access and workflow barriers that can otherwise impede treatment receipt. This paper describes STELLAR's 2-arm randomized parallel group pragmatic clinical trial comparing telehealth-delivered, coach-facilitated multiple risk behavior treatment vs self-guided usual care for the outcomes of reach, effectiveness, and cost among 3000 cancer survivors who have completed curative intent treatment. This paper also discusses several challenges encountered by the STELLAR investigative team and the adaptations developed to move the research forward.

SMART Family and Friends: Feasibility and outcomes of a video-conference delivered intervention for families impacted by another's methamphetamine use.

INTRODUCTION: Families affected by another's substance use, including methamphetamine, experience harms to their mental and physical health. Yet, research has paid little attention to support and service needs of this population. This pilot study examines the feasibility and outcomes of SMART Family and Friends, a video-conference-delivered mutual-support group targeting families affected by another's methamphetamine use. METHODS: Recruitment for this study occurred between March-October 2021 via the SMART Recovery Australia website. Participants were English-speaking Australian residents, ≥18 years, affected by another's methamphetamine use, interested in participating in a manualised eight-module group delivered via video-conferencing. Feasibility was evaluated by attendance rates, participant satisfaction, fidelity ratings, and semi-structured interviews. Measures of distress, quality of life, and family functioning assessed outcomes at baseline and one-month post-treatment conclusion. RESULTS: Forty-three participants commenced SMART Family and Friends groups. 84 % (n = 36) completed ≥4 modules, 67 % (n = 29) completed ≥6, and 42 % (n = 18) completed all 8 modules. Participant satisfaction (M = 4.32, SD = 0.66, out of 5) and facilitator fidelity (>94 % for all modules) were high. A within-group analysis, without comparison condition demonstrated significant improvements in psychological distress (d = 0.38), family impact (d = 0.64), family strain symptoms (d = 0.48), and total family burden (d = 0.69) post-treatment. Qualitative findings illustrated the benefits and challenges of the video-conference-delivered group, as well as recommendations for improvement. CONCLUSIONS: Results provide initial support for the feasibility and positive outcomes of the SMART Family and Friends program. These findings demonstrate the successful provision of a mutual-support group for affected families delivered via video-conferencing, and merit further sufficiently powered randomised-control-trials to evaluate efficacy.

Effect of early medication adherence on behavioral treatment utilization and smoking cessation among individuals with current or past major depressive disorder.

SIGNIFICANCE: Little is known about the mechanisms by which medication adherence promotes smoking cessation among adults with MDD. We tested the hypothesis that early adherence promotes abstinence by increasing behavioral treatment (BT) utilization. METHODS: Data for this post-hoc analysis were from a randomized trial of 149 adults with current or past MDD treated with BT and either varenicline (n = 81) or placebo (n = 68). Arms were matched on medication regimen. Early medication adherence was measured by the number of days in which medication was taken at the prescribed dose during the first six of 12 weeks of pharmacological treatment (weeks 2-7). BT consisted of eight 45-minute sessions (weeks 1-12). Bioverified abstinence was assessed at end-of-treatment (week 14). A regression-based approach was used to test whether the effect of early medication adherence on abstinence was mediated by BT utilization. RESULTS: Among 141 participants who initiated the medication regimen, BT utilization mediated the effect of early medication adherence on abstinencea) an interquartile increase in early medication days from 20 to 42 predicted a 4.2 times increase in abstinence (Total Risk Ratio (RR) = 4.24, 95% CI = 2.32-13.37; p <.001); b) increases in BT sessions predicted by such an increase in early medication days were associated with a 2.7 times increase in abstinence (Indirect RR = 2.73, 95% CI = 1.54-7.58; p <.001); and c) early medication adherence effects on abstinence were attenuated, controlling for BT (Direct RR = 1.55, 95% CI = 0.83-4.23, p =.17). CONCLUSIONS: The effect of early medication adherence on abstinence in individuals with current or past MDD is mediated by intensive BT utilization.

Seeing Through the Blind: Belief about Treatment Randomization and Smoking Cessation Outcome among People with Current or Past Major Depressive Disorder who Smoke in a Placebo-Controlled Trial of Varenicline.

INTRODUCTION: Blinding participants to randomization is a cornerstone of science. However, participant beliefs about their allocation can influence outcomes. We examined blind integrity, the association between trial arm belief and cessation, and potential mechanisms linking treatment arm and treatment arm belief among people with major depressive disorder (MDD) who smoke receiving varenicline in a placebo-controlled trial. METHODS: 175 participants were asked at the end of treatment (EOT) if they thought they received placebo, varenicline, or were not sure. We assessed the relationship between treatment arm belief and actual treatment allocation, examined the association between treatment arm belief and EOT cessation, and evaluated changes in craving, withdrawal, side effects, depression symptoms, and smoking reward as mediators through which treatment arm was believed. RESULTS: Treatment arm belief was significantly associated with actual arm assignment (χ2(2)=13.0, p=0.002). Participants in the varenicline arm were >3 times as likely to believe they were taking varenicline, vs. "not sure" (RR=3.05 [1.41-6.60], p=0.005). Participants in the placebo arm were just as likely to believe they were taking placebo vs. "not sure" (χ2[2]=0.75, p=0.69). Controlling for treatment arm, belief that one received varenicline was significantly associated with an increase in cessation rate (OR=5.91 [2.06-16.92], p=0.001). Change in the rewarding experience of smoking may mediate participant ability to discern getting varenicline B=0.077 [0.002-0.192], p <0.05). CONCLUSIONS: Participants receiving varenicline can discern that they received varenicline and this belief is associated with higher cessation rates. Research is needed to continue to examine how participants correctly identify their allocation to varenicline.

Depression Severity Moderates Reward Learning Among Smokers with Current or Past Major Depressive Disorder in a Smoking Cessation Randomized Clinical Trial.

INTRODUCTION: Behavioral and pharmacological smoking cessation treatments are hypothesized to increase patients' reward learning to reduce craving. Identifying changes in reward learning processes that support effective tobacco dependence interventions among smokers who experience depression may guide patients towards efficient treatment strategies. The objective was to investigate the extent to which adult daily cigarette smokers with current or past major depressive disorder (MDD) learned to seek reward during 12 weeks of treatment combining behavioral activation and varenicline. We hypothesized that a decline in reward learning would be attenuated (least to most) in the following order: 1) Behavioral activation integrated with ST (BASC) + varenicline, 2) BASC + placebo, 3) Standard behavioral cessation treatment (ST) + varenicline, 4) ST + placebo. METHODS: We ran a Phase 4, placebo-controlled, randomized clinical trial with 300 participants receiving 12 weeks of one of four conditions across two urban medical centers. Depressive symptoms were measured using the Beck Depression Inventory-II (BDI). Reward learning was ascertained at Weeks 1, 7, and 14 using the Probabilistic Reward Task (PRT), a laboratory task that uses an asymmetric reinforcement schedule to assess (a) learning to seek reward (response bias), (b) differentiate between stimuli, and (c) time to react to cues. RESULTS: There was a significant interaction of BDI group x PRT response bias. Response bias declined from Week 7 to 14 among participants with high baseline depression symptoms. The other two BDI groups showed no change in response bias. CONCLUSIONS: Controlling for baseline depression, participants showed a decrease in response bias from Week 1 to 14, and from Weeks 7 to 14. Treatment condition and abstinence status were unassociated with change in reward learning. IMPLICATIONS: Smokers who report greater depression severity show a decline in reward learning despite their participation in smoking cessation treatments, suggesting that depressed populations pose unique challenges with standard smoking cessation approaches.

Rationale and design for Healthy Hearts for Michigan (HH4M): A pragmatic single-arm hybrid effectiveness-implementation study.

Background: The burden of cardiovascular disease (CVD) is particularly high in several US states, which include the state of Michigan. Hypertension and smoking are two major risk factors for mortality due to CVD. Rural Michigan is disproportionally affected by CVD and by primary care shortages. The Healthy Hearts for Michigan (HH4M) study aims to promote hypertension management and smoking cessation through practice facilitation and quality improvement efforts and is part of the multi-state EvidenceNOW: Building State Capacity initiative to provide external support to primary care practices to improve care delivery. Methods: Primary care practices in rural and underserved areas of Michigan were recruited to join HH4M, a pragmatic, single-arm hybrid Type 2 effectiveness-implementation study during which practice facilitation was delivered at the practice level for 12 months, followed by a 3-month maintenance period. Results: Fifty-four practices were enrolled over a 12-month recruitment period. At baseline, the mean proportion (standard deviation) of patients at the practice level meeting the clinical quality measures were: blood pressure, 0.72 (0.12); tobacco screening, 0.80 (0.30); tobacco cessation intervention, 0.57 (0.28); tobacco screening and cessation intervention: 0.78 (0.26). Conclusion: This three-year research program will evaluate the ability of rural and medically underserved primary care practices to implement the quality improvement model by identifying drivers of and barriers to sustainable implementation, and test whether the model improves (a) blood pressure control and (b) tobacco use screening and cessation.

Primary care delivery of behavioral weight loss services for adults with cardiovascular risk factors: development of pragmatic practice components and results of a randomized feasibility trial.

Background: Intensive lifestyle interventions (ILI) improve weight loss and cardiovascular risk factors, but health systems face challenges implementing them. We engaged stakeholders to cocreate and evaluate feasibility of primary care implementation strategies and of a pragmatic randomization procedure to be used for a future effectiveness trial. Methods: The study setting was a single, urban primary care office. Patients with BMI ≥ 27 and ≥ 1 cardiovascular risk factor were sent a single electronic health record (EHR) message between December 2019 and January 2020 offering services to support an initial weight loss goal of about 10 pounds in 10 weeks. All patients who affirmed weight loss interest were pragmatically enrolled in the trial and offered "Basic Lifestyle Services" (BLS), including a scale that transmits weight data to the EHR using cellular networks, a coupon to enroll in lifestyle coaching resources through a partnering fitness organization, and periodic EHR messages encouraging use of these resources. About half (n = 42) of participants were randomized by an automated EHR algorithm to also receive "Customized Lifestyle Services" (CLS), including weekly email messages adapted to individual weight loss progress and telephonic coaching by a nurse for those facing challenges. Interventions and assessments spanned January to July 2020, with interference by the coronavirus pandemic. Weight measures were collected from administrative sources. Qualitative analysis of stakeholder recommendations and patient interviews assessed acceptability, appropriateness, and sustainability of intervention components. Results: Over 6 weeks, 426 patients were sent the EHR invitation message and 80 (18.8%) affirmed interest in the weight loss goal and were included for analysis. EHR data were available to ascertain a 6-month weight value for 77 (96%) patients. Overall, 62% of participants lost weight; 15.0% exhibited weight loss ≥ 5%, with no statistically significant difference between CLS or BLS arms (p = 0.85). CLS assignment increased participation in daily self-weighing (43% versus 21% of patients through 12 weeks) and enrollment in referral-based lifestyle support resources (52% versus 37%). Conclusions: This preliminary study demonstrates feasibility of implementation strategies for primary care offices to offer and coordinate ILI core components, as well as a pragmatic randomization procedure for use in a future randomized comparative trial.

Primary care delivery of behavioral weight loss services for adults with cardiovascular risk factors: development of pragmatic implementation strategies and results of a randomized feasibility trial.

Background: Intensive lifestyle interventions (ILI) improve weight loss and cardiovascular risk factors, but health systems face challenges implementing them. We engaged stakeholders to cocreate and evaluate feasibility of primary care implementation strategies and of a pragmatic randomization procedure to be used for a future effectiveness trial. Methods: The study setting was a single, urban primary care office. Patients with BMI ≥ 27 and ≥ 1 cardiovascular risk factor were sent a single electronic health record (EHR) message between December 2019 and January 2020 offering services to support an initial weight loss goal of about "10 pounds in 10 weeks." All patients who affirmed weight loss interest were pragmatically enrolled in the trial and offered "Basic Lifestyle Services" (BLS), including a scale that transmits weight data to the EHR using cellular networks, a coupon to enroll in lifestyle coaching resources through a partnering fitness organization, and periodic EHR messages encouraging use of these resources. About half (n = 42) of participants were randomized by an automated EHR algorithm to also receive "Customized Lifestyle Services" (CLS), including weekly email messages adapted to individual weight loss progress and telephonic coaching by a nurse for those facing challenges. Interventions and assessments spanned January to July 2020, with interference by the coronavirus pandemic. Weight measures were collected from administrative sources. Qualitative analysis of stakeholder recommendations and patient interviews assessed acceptability, appropriateness, and sustainability of intervention components. Results: Over 6 weeks, 426 patients were sent the EHR invitation message and 80 (18.8%) affirmed interest in the weight loss goal and were included for analysis. EHR data were available to ascertain a 6-month weight value for 77 (96%) patients. Overall, 62% of participants lost weight; 15.0% exhibited weight loss ≥ 5%, with no statistically significant difference between CLS or BLS arms (p = 0.85). CLS assignment increased participation in daily self-weighing (43% versus 21% of patients through 12 weeks) and enrollment in referral-based lifestyle support resources (52% versus 37%). Conclusions: This preliminary study demonstrates feasibility of implementation strategies for primary care offices to offer and coordinate ILI core components, as well as a pragmatic randomization procedure for use in a future randomized comparative trial.

Data envelopment analysis to evaluate the efficiency of tobacco treatment programs in the NCI Moonshot Cancer Center Cessation Initiative.

BACKGROUND: The Cancer Center Cessation Initiative (C3I) is a National Cancer Institute (NCI) Cancer Moonshot Program that supports NCI-designated cancer centers developing tobacco treatment programs for oncology patients who smoke. C3I-funded centers implement evidence-based programs that offer various smoking cessation treatment components (e.g., counseling, Quitline referrals, access to medications). While evaluation of implementation outcomes in C3I is guided by evaluation of reach and effectiveness (via RE-AIM), little is known about technical efficiency-i.e., how inputs (e.g., program costs, staff time) influence implementation outcomes (e.g., reach, effectiveness). This study demonstrates the application of data envelopment analysis (DEA) as an implementation science tool to evaluate technical efficiency of C3I programs and advance prioritization of implementation resources. METHODS: DEA is a linear programming technique widely used in economics and engineering for assessing relative performance of production units. Using data from 16 C3I-funded centers reported in 2020, we applied input-oriented DEA to model technical efficiency (i.e., proportion of observed outcomes to benchmarked outcomes for given input levels). The primary models used the constant returns-to-scale specification and featured cost-per-participant, total full-time equivalent (FTE) effort, and tobacco treatment specialist effort as model inputs and reach and effectiveness (quit rates) as outcomes. RESULTS: In the DEA model featuring cost-per-participant (input) and reach/effectiveness (outcomes), average constant returns-to-scale technical efficiency was 25.66 (SD = 24.56). When stratified by program characteristics, technical efficiency was higher among programs in cohort 1 (M = 29.15, SD = 28.65, n = 11) vs. cohort 2 (M = 17.99, SD = 10.16, n = 5), with point-of-care (M = 33.90, SD = 28.63, n = 9) vs. no point-of-care services (M = 15.59, SD = 14.31, n = 7), larger (M = 33.63, SD = 30.38, n = 8) vs. smaller center size (M = 17.70, SD = 15.00, n = 8), and higher (M = 29.65, SD = 30.99, n = 8) vs. lower smoking prevalence (M = 21.67, SD = 17.21, n = 8). CONCLUSION: Most C3I programs assessed were technically inefficient relative to the most efficient center benchmark and may be improved by optimizing the use of inputs (e.g., cost-per-participant) relative to program outcomes (e.g., reach, effectiveness). This study demonstrates the appropriateness and feasibility of using DEA to evaluate the relative performance of evidence-based programs.

Development of a targeted behavioral treatment for smoking cessation among individuals with Chronic Obstructive Pulmonary Disease.

OBJECTIVE: Smoking cessation for individuals with Chronic Obstructive Pulmonary Disease (COPD) is medically critical, but smoking for coping motives is a common barrier. METHOD: In this evaluation of three treatment components (Mindfulness, Practice Quitting, and Countering Emotional Behaviors), we conducted two studies guided by the ORBIT model. Study 1 was a single-case design experiment (N = 18); Study 2 was a pilot feasibility study (N = 30). In both studies, participants were randomized to receive one of the three treatment modules. Study 1 examined implementation targets, changes in smoking for coping motives, and changes in smoking rate. Study 2 examined overall feasibility and participant-rated acceptability, and changes in smoking rate. RESULTS: Study 1: Treatment implementation targets were met by 3/5 Mindfulness participants, 2/4 Practice Quitting participants, and 0/6 Countering Emotional Behaviors participants. The Practice Quitting condition led to 100% of participants meeting the clinically significant threshold in smoking for coping motives. Incidence of quit attempts ranged from 0-50%, and smoking rate was reduced by 50% overall. Study 2: Recruitment and retention met feasibility targets, with 97% of participants completing all four treatment sessions. Participants reported high treatment satisfaction by qualitative responses and rating scales (M = 4.8/ 5.0). Incidence of quit attempts ranged from 25-58%, and smoking rate was reduced by 56% overall. CONCLUSIONS: These two small-N studies provide complementary findings on internal validity and implementation of the novel intervention. While Study 1 provided initial support for plausibility of clinically significant change, Study 2 provided data on key feasibility parameters. IMPLICATIONS: Smoking cessation for individuals with COPD is medically critical. We conducted an early-phase evaluation of a novel behavioral treatment focused on reducing smoking for coping motives. Results provided initial support for plausibility of clinically significant change and feasibility of the intervention.

Efficacy and safety of combination behavioral activation for smoking cessation and varenicline for treating tobacco dependence among individuals with current or past major depressive disorder: A 2 × 2 factorial, randomized, placebo-controlled trial.

BACKGROUND AND AIMS: Treatment of depression-related psychological factors related to smoking behavior may improve rates of cessation among adults with major depressive disorder (MDD). This study measured the efficacy and safety of 12 weeks of behavioral activation for smoking cessation (BASC), varenicline and their combination. DESIGN, SETTING, PARTICIPANTS: This study used a randomized, placebo-controlled, 2 × 2 factorial design comparing BASC versus standard behavioral treatment (ST) and varenicline versus placebo, taking place in research clinics at two urban universities in the United States. Participants comprised 300 hundred adult smokers with current or past MDD. INTERVENTIONS: BASC integrated behavioral activation therapy and ST to increase engagement in rewarding activities by reducing avoidance, withdrawal and inactivity associated with depression. ST was based on the 2008 PHS Clinical Practice Guideline. Both treatments consisted of eight 45-min sessions delivered between weeks 1 and 12. Varenicline and placebo were administered for 12 weeks between weeks 2 and 14. MEASUREMENTS: Primary outcomes were bioverified intent-to-treat (ITT) 7-day point-prevalence abstinence at 27 weeks and adverse events (AEs). FINDINGS: No significant interaction was detected between behavioral treatment and pharmacotherapy at 27 weeks (χ2 (1) = 0.19, P = 0.67). BASC and ST did not differ (χ2 (1) = 0.43, P = 0.51). Significant differences in ITT abstinence rates (χ2 (1) = 4.84, P = 0.03) emerged among pharmacotherapy arms (16.2% for varenicline, 7.5% for placebo), with results favoring varenicline over placebo (rate ratio = 2.16, 95% confidence interval = 1.08, 4.30). All significant differences in AE rates after start of medication were higher for placebo than varenicline. CONCLUSION: A randomized trial in smokers with major depressive disorder found that varenicline improved smoking abstinence versus placebo at 27 weeks without elevating rates of adverse events. Behavioral activation for smoking cessation did not outperform standard behavioral treatment, with or without adjunctive varenicline therapy.

Change in cardiovascular health among adults with current or past major depressive disorder enrolled in intensive smoking cessation treatment.

BACKGROUND: Elevated depressive symptoms and cigarette smoking are independently associated with poorer cardiovascular health (CVH), but it is unknown whether their treatment can synergistically improve CVH. We sought to characterize CVH of adults with comorbid depression and smoking and examine changes in CVH associated with changes in smoking and depression. METHODS: Participants (N = 300, 55 % women) were adult smokers (≥ 1 cigarette/day) with lifetime major depressive disorder enrolled in a 12-week intervention trial targeting depression and smoking. Multiple linear regression examined prospective associations between changes in depression (Beck Depression Inventory-II), smoking (past 24-hour cigarettes or smoking abstinence), and modified CVH score (per American Heart Association, excluding smoking: diet, physical activity, body mass index, blood glucose, cholesterol, blood pressure). RESULTS: Baseline mean CVH score was 5.87/12 points (SD = 2.13). No participants met "ideal" on all CVH components (blood glucose: 48 %, cholesterol: 46 %, physical activity: 38 %, body mass index: 24 %, blood pressure: 22 %, diet: 3 %). CVH scores did not change from baseline to end-of-treatment (M = 0.18 points, SD = 1.36, p = .177), nor did change in depression × smoking predict change in CVH (p = .978). However, greater reductions in depression were significantly associated with greater improvements in CVH (ß = -0.04, SE = 0.01, p = .015). LIMITATIONS: This study was limited by a short follow-up period, missing blood glucose and cholesterol data, and treatment-seeking smokers. CONCLUSIONS: Adults with comorbid depression and smoking had poor CVH. Although integrated treatment for depression and smoking improved both conditions, only reductions in depression were associated with improvements in CVH. These findings have implications for integrating psychosocial treatment into CVH promotion efforts. REGISTRATION: NCT02378714 (clinicaltrials.gov).

Smoking Cessation, Version 3.2022, NCCN Clinical Practice Guidelines in Oncology.

Although the harmful effects of smoking after a cancer diagnosis have been clearly demonstrated, many patients continue to smoke cigarettes during treatment and beyond. The NCCN Guidelines for Smoking Cessation emphasize the importance of smoking cessation in all patients with cancer and seek to establish evidence-based recommendations tailored to the unique needs and concerns of patients with cancer. The recommendations contained herein describe interventions for cessation of all combustible tobacco products (eg, cigarettes, cigars, hookah), including smokeless tobacco products. However, recommendations are based on studies of cigarette smoking. The NCCN Smoking Cessation Panel recommends that treatment plans for all patients with cancer who smoke include the following 3 tenets that should be done concurrently: (1) evidence-based motivational strategies and behavior therapy (counseling), which can be brief; (2) evidence-based pharmacotherapy; and (3) close follow-up with retreatment as needed.

Treatment adherence in a smoking cessation clinical trial for individuals with current or past major depressive disorder: Predictors and association with cessation.

INTRODUCTION: Individuals with major depressive disorder (MDD) exhibit high rates of tobacco use and lower responsiveness to tobacco cessation treatments. Treatment adherence is a strong predictor of treatment outcomes in the general population but has not been evaluated in this under-served community of smokers with MDD. METHODS: We used data from a randomized clinical trial on smoking cessation treatment among 300 smokers with MDD to examine the rate of adherence (medication and counseling), the association of adherence with cessation outcomes, and factors associated with adherence, including demographic and smoking characteristics, psychiatric characteristics, smoking cessation processes (e.g., withdrawal, reinforcers), and treatment-related side effects (e.g., nausea). RESULTS: Overall, 43.7% of participants were adherent with medication and 63.0% were adherent with counseling. Medication adherence was significantly associated with cessation, with 32.1% of adherent vs. 13.0% of non-adherent participants quitting smoking at EOT. Counseling adherence was also significantly associated with cessation, with 32.3% of adherent vs. 2.7% of non-adherent participants quitting smoking. Multivariate regression models showed that medication adherence was associated with higher engagement in complementary reinforcers and higher baseline smoking reward, while counseling adherence was associated with identifying as female, lower alcohol use and nicotine dependence, higher baseline smoking reward, and higher engagement in substitute and complementary reinforcers within the first weeks of medication use. CONCLUSIONS: As with the general population of smokers, non-adherence to treatment in smokers experiencing depression is widespread and a significant barrier to cessation. Interventions that target reinforcers may improve rates of treatment adherence.

The Impact of the COVID-19 Pandemic on Stress, Isolation, Smoking Behaviors, and Motivation to Quit in People with HIV Who Smoke.

People with HIV (PWH) smoke at higher rates compared with the general population and have lower cessation rates. The primary aim of this study was to examine the impact of the COVID-19 pandemic on smoking in PWH. A survey was administered to participants in two smoking cessation trials in the United States. Mean cigarettes per day was 13.9 (SD 8.6), and participants reported they had smoked on average for 30.93 years (SD 10.4). More than half (55.7%) of participants (N = 140) reported not changing their smoking during the pandemic, while 15% reported decreasing, and 25% reported increasing their smoking. In bivariate analyses, worrying about food due to lack of money (χ2 = 9.13, df 2, p = 0.01) and greater Covid-related worry (rs = 0.19, p = 0.02) were significantly associated with increased smoking. Qualitative research may be needed to more clearly elucidate factors related to smoking behaviors among PWH.

An EHR-automated and theory-based population health management intervention for smoking cessation in diverse low-income patients of safety-net health centers: a pilot randomized controlled trial.

This study tested the preliminary effectiveness of an electronic health record (EHR)-automated population health management (PHM) intervention for smoking cessation among adult patients of a federally qualified health center in Chicago. Participants (N = 190; 64.7% women, 82.1% African American/Black, 8.4% Hispanic/Latino) were self-identified as smokers, as documented in the EHR, who completed the baseline survey of a longitudinal "needs assessment of health behaviors to strengthen health programs and services." Four weeks later, participants were randomly assigned to the PHM intervention (N = 97) or enhanced usual care (EUC; N = 93). PHM participants were mailed a single-page self-determination theory (SDT)-informed letter that encouraged smoking cessation or reduction as an initial step. The letter also addressed low health literacy and low income. PHM participants also received automated text messages on days 1, 5, 8, 11, and 20 after the mailed letter. Two weeks after mailing, participants were called by the Illinois Tobacco Quitline. EUC participants were e-referred following a usual practice. Participants reached by the quitline were offered behavioral counseling and nicotine replacement therapy. Outcome assessments were conducted at weeks 6, 14, and 28 after the mailed letter. Primary outcomes were treatment engagement, utilization, and self-reported smoking cessation. In the PHM arm, 25.8% of participants engaged in treatment, 21.6% used treatment, and 16.3% were abstinent at 28 weeks. This contrasts with no quitline engagement among EUC participants, and a 6.4% abstinence rate. A PHM approach that can reach all patients who smoke and address unique barriers for low-income individuals may be a critical supplement to clinic-based care.

History and Correlates of Smoking Cessation Behaviors Among Individuals With Current or Past Major Depressive Disorder Enrolled in a Smoking Cessation Trial.

INTRODUCTION: Smoking among adults with major depressive disorder (MDD) is at least double that of the general US population. More effective smoking cessation interventions for depressed smokers may be facilitated through a better understanding of the smoking and depression-related characteristics of this population. METHODS: We used baseline data from 300 participants enrolled in randomized clinical trial for smokers with current or past MDD. We described history of smoking cessation behaviors (ie, quit attempts, quit motivation, and cessation treatment utilization) and used multivariate regression to identify demographic and depression-related correlates of these behaviors. RESULTS: Sixty-eight percent of participants reported at least one quit attempt in the past year, nearly 51% reported motivation to quit in the subsequent 30 days, and 83% reported prior use of a nicotine replacement therapy. A greater readiness to quit smoking was associated with increased age (p = .04) and lower cigarettes per day (p = .01). Greater use of smoking cessation medication was associated with greater education and nicotine dependence, minority race, and greater use of complementary reinforcers (eg, activities associated with increased reinforcing value of smoking; p's < .05). CONCLUSIONS: These data indicate that smokers with current or past MDD are highly motivated to quit smoking and have a history of engaging in efforts to quit. Interventions to promote smoking cessation behaviors should address younger and lighter smokers, who may perceive less risk from tobacco use, and efforts to promote smoking cessation medications and counseling should address minority smokers who are engaging in complementary reinforcers. IMPLICATIONS: These data are inconsistent with the assumption that smokers with serious mental illness are not willing to quit smoking and suggest the need for studies that test behavioral interventions that address complementary reinforcers to treat tobacco use in this community.

Electronic nicotine delivery systems: use, knowledge, and attitudes among diverse college students.

ObjectiveThe purpose of this study was to examine Electronic Nicotine Delivery Systems (ENDS) use among nonusers in diverse college students. Participants: Participants were college students enrolled at a Hispanic-Serving University in Chicago, IL, USA in December 2017. Methods: An online survey was administered using questions about ENDS-use behaviors, device characteristics, and knowledge of their own device, and ENDS attitudes. ENDS attitudes included questions about health, susceptibility, and quit characteristics. Results: The prevalence rate of ENDS use was 7%, and 39% of ENDS users identified all device characteristics. Nonusers categorize ENDS as a healthier alternative to cigarettes and as quit devices. Finally, cigarette use, age, health factor, and social proximity are correlated with ENDS susceptibility. Conclusions: These ENDS users lack awareness of their devices and tobacco use plays a key role in ENDS susceptibility. Future studies should continue to study the role ENDS has in dependence and cigarette use.