A Pilot Study to Test the Feasibility for a Randomized Controlled Trial of E-cigarettes as Harm Reduction Tools Among People Who Smoke and Previously Failed to Quit with Pharmacotherapy.

INTRODUCTION: We conducted a pilot study to test the feasibility of a future randomized controlled trial comparing e-cigarettes to traditional pharmacotherapy among people who smoke daily, were motivated to quit, and failed to quit within the past 5 years using pharmacotherapy. METHODS: Eligible participants were assigned to either: 1) an e-cigarette (n=20) or 2) combination nicotine replacement therapy (patches and lozenges) (n=10). Participants received 5 weeks of product and selected a quit date 1 week later. Assessments were completed weekly, and electronic diaries were completed each day. As a pilot randomized controlled trial, outcomes focus on effects sizes and not statistical significance. RESULTS: Participants in the e-cigarette and NRT groups had a mean age of 51 (SD=13) and 50 (SD=10) years old, were 55% and 60% female, and were 15% and 0% non-white, respectively. At least 90% of participants completed each weekly assessment, and 77% of participants completed at least 80% of daily diaries. Mean cigarettes smoked per day reduced from 18 (SD=6.2) to 2.4 (SD=4.4) per day in the e-cigarette group and 16.5 (SD=8.5) to 4.9 (SD=5.9) per day in the NRT group. Rates of biochemically confirmed 7-day point prevalence abstinence at the end of treatment were numerically, but not statistically, higher in the e-cigarette group than the NRT group (35% vs. 10%, OR=4.8, 95% CI=0.5-46.5). CONCLUSIONS: Among current daily cigarette smokers who have previously tried to quit and failed using standard pharmacotherapies, provision of an e-cigarette is a feasible intervention. A larger adequately powered trial is warranted. IMPLICATIONS: This pilot study suggests that e-cigarettes may serve as an acceptable harm reduction intervention for people who smoke who cannot quit smoking with traditional pharmacotherapy, but adequately powered randomized controlled trials are needed.

Prescription of Nicotine Replacement Therapy for Hospitalized Tobacco Users.

OBJECTIVES: In hospitalized patients, cigarette smoking is linked to increased readmission rates, emergency department visits, and overall mortality. Smoking cessation reduces these risks, but many patients who smoke are unsuccessful in quitting. Nicotine replacement therapy (NRT) is an effective tool that assists patients who smoke with quitting. This study evaluates NRT prescriptions during and after hospitalization at a large health system for patients who smoke. METHODS: A retrospective cohort study was conducted to determine the number of patients who were prescribed NRT during an inpatient admission and at time of discharge from a network of nine hospitals across South Carolina between January 1, 2019 and January 1, 2023. RESULTS: This study included 20,757 patients identified as actively smoking with at least one hospitalization during the study period. Of the cohort, 34.9% were prescribed at least one prescription for NRT during their admission to the hospital. Of the patients identified, 12.6% were prescribed NRT upon discharge from the hospital. CONCLUSIONS: This study identified significantly low rates of NRT prescribed to smokers during hospitalization and at discharge. Although the management of chronic conditions is typically addressed in the outpatient setting, hospitalization may provide an opportunity for patients to initiate health behavior changes. The low rates of prescriptions for NRT present an opportunity to improve tobacco treatment during hospitalization and beyond.

Expectations and Preferences for Digital Cessation Treatment: Multimethods Study Among Older Adults Who Smoke Cigarettes.

BACKGROUND: To address enduring age-related tobacco disparities, it is critical to promote cessation treatment among older adults (aged 65+ years). Digital health platforms offer opportunities for wide dissemination of evidence-based behavioral cessation support. However, existing digital cessation treatments are not tailored to unique aging-related needs and preferences, resulting in low uptake. Detailed information is needed about how to best adapt these treatments for this age group. OBJECTIVE: We aimed to collect detailed, hypothesis-generating information about expectations and preferences for cessation digital treatment among older adults who smoke cigarettes. METHODS: Semistructured interviews were conducted with adults aged 65+ years currently smoking or who had quit within the past month. Interviews included open-ended questions regarding prior experiences with digital health platforms and expectations and preferences for cessation treatment via various modalities (app-delivered, texting-based, or videoconferencing counseling). Interviews also elicited questions regarding digital modalities that integrated social components (app-delivered social forums and group videoconferencing counseling). Using an iterative, team-based approach, the thematic analysis identified meaningful themes. Interviews were supplemented with quantitative measures assessing sociodemographics, digital literacy, and physical health symptoms. RESULTS: Participants (12/20, 60% men; 15/20, 75% White; 4/20, 20% Black or African American; 1/20, 5% Asian) were currently smoking (17/20, 85%) or had recently quit (3/20, 15%). Thematic analysis identified 3 meaningful themes across all digital modalities: convenience, accessibility, and personalization. Expected benefits of digital platforms included convenient treatment access, without reliance on transportation. Participants preferred treatments to be personalized and deliver content or strategies beyond standard education. Most (17/20, 85%) were unfamiliar with cessation apps but found them appealing given the potential for offering a novel quitting strategy. App ease of use (eg, easy navigation) was preferred. Half (10/20, 50%) would try a texting-based intervention, with many preferring texting with a counselor rather than automated messaging. Most (17/20, 85%) would use videoconferencing and expected this modality to deliver better quality counseling than via telephone. Expected videoconferencing challenges included looking presentable onscreen, technological difficulties, and privacy or security. Videoconferencing was regarded as the most personalized digital treatment, yet benefits unique to app-delivered and texting-based treatments included anonymity and access to treatment 24/7. Participants expected integrating social components into digital treatment to be useful for quit success and social connection, yet were concerned about possible interpersonal challenges. CONCLUSIONS: Because a long history of quit attempts and familiarity with standard quitting advice is common among older adults who smoke cigarettes, digital platforms might offer appealing and novel strategies for cessation that are accessible and convenient. Overall, this population was open to trying digital cessation treatments and would prefer that these platforms prioritize ease of use and personalized content. These findings challenge the bias that older adults are uninterested or unwilling to engage with digital treatments for behavioral health.

Development of an Electronic Health Record Self-Referral Tool for Lung Cancer Screening: One-Group Posttest Study.

BACKGROUND: Approximately 14 million individuals in the United States are eligible for lung cancer screening (LCS), but only 5.8% completed screening in 2021. Given the low uptake despite the potential great health benefit of LCS, interventions aimed at increasing uptake are warranted. The use of a patient-facing electronic health record (EHR) patient portal direct messaging tool offers a new opportunity to both engage eligible patients in preventative screening and provide a unique referral pathway for tobacco treatment. OBJECTIVE: This study sought to develop and pilot an EHR patient-facing self-referral tool for an established LCS program in an academic medical center. METHODS: Guided by constructs of the Health Belief Model associated with LCS uptake (eg, knowledge and self-efficacy), formative development of an EHR-delivered engagement message, infographic, and self-referring survey was conducted. The survey submits eligible self-reported patient information to a scheduler for the LCS program. The materials were pretested using an interviewer-administered mixed methods survey captured through venue-day-time sampling in 5 network-affiliated pulmonology clinics. Materials were then integrated into the secure patient messaging feature in the EHR system. Next, a one-group posttest quality improvement pilot test was conducted. RESULTS: A total of 17 individuals presenting for lung screening shared-decision visits completed the pretest survey. More than half were newly referred for LCS (n=10, 60%), and the remaining were returning patients. When asked if they would use a self-referring tool through their EHR messaging portal, 94% (n=16) reported yes. In it, 15 participants provided oral feedback that led to refinement in the tool and infographic prior to pilot-testing. When the initial application of the tool was sent to a convenience sample of 150 random patients, 13% (n=20) opened the self-referring survey. Of the 20 who completed the pilot survey, 45% (n=9) were eligible for LCS based on self-reported smoking data. A total of 3 self-referring individuals scheduled an LCS. CONCLUSIONS: Pretest and initial application data suggest this tool is a positive stimulus to trigger the decision-making process to engage in a self-referral process to LCS among eligible patients. This self-referral tool may increase the number of patients engaging in LCS and could also be used to aid in self-referral to other preventative health screenings. This tool has implications for clinical practice. Tobacco treatment clinical services or health care systems should consider using EHR messaging for LCS self-referral. This approach may be cost-effective to improve LCS engagement and uptake. Additional referral pathways could be built into this EHR tool to not only refer patients who currently smoke to LCS but also simultaneously trigger a referral to clinical tobacco treatment.

Implementation of an "opt-out" tobacco treatment program in six hospitals in South Carolina.

OBJECTIVE: Describe the screening, referral, and treatment delivery associated with an opt-out tobacco treatment program (TTP) implemented in six hospitals varying in size, rurality and patient populations. METHODS: Between March 6, 2021 and December 17, 2021, adult patients (≥ 18 years) admitted to six hospitals affiliated with the Medical University of South Carolina were screened for smoking status. The hospitals ranged in size from 82 to 715 beds. Those currently smoking were automatically referred to one of two tobacco treatment options: 1) Enhanced care (EC) where patients could receive a bedside consult by a trained tobacco treatment specialist plus an automated post-discharge follow-up call designed to connect those smoking to the South Carolina Quitline (SCQL); or 2) Basic care (BC) consisting of the post-discharge follow-up call only. An attempt was made to survey patients at 6-weeks after hospitalization to assess smoking status. RESULTS: Smoking prevalence ranged from 14 to 49% across the six hospitals; 6,000 patients were referred to the TTP.The delivery of the bedside consult varied across the hospitals with the lowest in the Charleston hospitals which had the highest caseload of referred patients per specialist. Among patients who received a consult visit during their hospitalization, 50% accepted the consult, 8% opted out, 3% claimed not to be current smokers, and 38% were unavailable at the time of the consult visit. Most of those enrolled in the TTP were long-term daily smokers.Forty-three percent of patients eligible for the automated post-discharge follow-up call answered the call, of those, 61% reported smoking in the past seven days, and of those, 34% accepted the referral to theSCQL. Among the 986 of patients surveyed at 6-weeks after hospitalization quit rates ranged from 20%-30% based on duration of reported cessation and were similar between hospitals and for patients assigned to EC versus BC intervention groups. CONCLUSION: Findings demonstrate the broad reach of an opt-out TTP. Elements of treatment delivery can be improved by addressing patient-to-staffing ratios, improving systems to prescribe stop smoking medications for patients at discharge and linking patients to stop smoking services after hospital discharge.

Barriers and facilitators to involvement in cancer education opportunities among South Carolina cancer care professionals: A cancer training and diversity, equity, and inclusion training needs assessment.

INTRODUCTION: It is estimated that 1.9 million new cases of cancer will be diagnosed in 2023, with 33,890 occurring in South Carolina. Assessing the needs, barriers, and facilitators of healthcare professionals' (HCP) education in South Carolina is a step towards creating meaningful, equity-promoting cancer-based education/training. METHODS: We developed a mixed-methods REDCap survey instrument to assess HCP needs, which we disseminated via email to HCPs from divisions involved in cancer care in a South Carolina academic medical center health system. We analyzed quantitative data with univariate frequency analysis and employed an inductive content analysis approach for qualitative data. RESULTS: The response rate for the survey was 33.0% (95/284) and 44.2% (42/95) of respondents reported a perceived barrier to attending educational programming, with majority citing time. Most respondents (71.8%) self-identified as non-Hispanic White. HCPs reported having clear interests in trainings, particularly ones focused on additional training in diversity, equity, and inclusion (DEI). Other identified educational needs included cancer treatment updates, nutrition, mental health, and social risk factors. Receiving credits for the trainings was a motivator for both general topics and DEI topics (94.7% and 74.7%, respectively). CONCLUSIONS: There is a need to better align cancer education delivery for HCPs with their training needs and busy schedules as has been a demonstrated want by HCPs in topics that would increase knowledge and practice of DEI. As majority of respondents identified as non-Latine White, it is imperative to diversify the knowledge of the workforce to ensure that HCPs provide optimal care to patients from diverse backgrounds.

Implementation, enrollment, and engagement in an opt-out telehealth pharmacist-assisted tobacco treatment program for patients seen in oncology outpatient clinics.

OBJECTIVE: To describe the workflow, reach, cost, and self-reported quit rates for an opt-out tobacco treatment program (TTP) for patients seen in 43 oncology outpatient clinics. METHODS: Between May 25, 2021, and December 31, 2022, adult patients (≥18 years) visiting clinics affiliated with the Medical University of South Carolina Hollings Cancer Center were screened for smoking status. Those currently smoking were referred to a telehealth pharmacy-assisted TTP. An attempt was made to contact referred patients by phone. Patients reached were offered free smoking cessation counseling and a 2-week starter kit of nicotine replacement medication. A random sample of 420 patients enrolled in the TTP were selected to participate in a telephone survey to assess smoking status 4 to 12 months after enrollment. RESULTS: During the reference period 35,756 patients were screened and 9.3% were identified as currently smoking. Among the 3319 patients referred to the TTP at least once, 2393 (72.1%) were reached by phone, of whom 426 (12.8%) were ineligible for treatment, 458 (13.8%) opted out of treatment, and 1509 (45.5%) received treatment. More than 90% of TTP enrollees smoked daily, with an average of 13.1 cigarettes per day. Follow-up surveys were completed on 167 of 420 patients, of whom 23.4% to 33.5% reported not smoking; if all nonresponders to the survey are counted as smoking, the range of quit rates is 9.3% to 13.3%. CONCLUSION: The findings demonstrate the feasibility of reaching and delivering smoking cessation treatments to patients from a diverse set of geographically dispersed oncology clinics.

Hospitalization as an opportunity to improve lung cancer screening in high-risk patients.

BACKGROUND: Lung cancer screening with annual low-dose computed tomography (LDCT) in high-risk patients with exposure to smoking reduces lung cancer-related mortality, yet the screening rate of eligible adults is low. As hospitalization is an opportune moment to engage patients in their overall health, it may be an opportunity to improve rates of lung cancer screening. Prior to implementing a hospital-based lung cancer screening referral program, this study assesses the association between hospitalization and completion of lung cancer screening. METHODS: A retrospective cohort study of evaluated completion of at least one LDCT from 2014 to 2021 using electronic health record data using hospitalization as the primary exposure. Patients aged 55-80 who received care from a university-based internal medicine clinic and reported cigarette use were included. Univariate analysis and logistic regression evaluated the association of hospitalization and completion of LDCT. Cox proportional hazard model examined the time relationship between hospitalization and LDCT. RESULTS: Of the 1935 current smokers identified, 47% had at least one hospitalization, and 21% completed a LDCT during the study period. While a higher proportion of patients with a hospitalization had a LDCT (24%) compared to patients without a hospitalization (18%, p<0.001), there was no association between hospitalization and completion of a LDCT after adjusting for potentially confounding covariates (95%CI 0.680 - 1.149). There was an association between hospitalization time to event and LDCT completion, with hospitalized patients having a lower probability of competing LDCT compared to non-hospitalized patients (HR 0.747; 95% CI 0.611 - 0.914). CONCLUSIONS: In a cohort of patients at risk for lung cancer and established within a primary care clinic, only 1 in 4 patients who had been hospitalized completed lung cancer screening with LDCT. Hospitalization events were associated with a lower probability of LDCT completion. Hospitalization is a missed opportunity to refer at-risk patients to lung cancer screening.

Smoking Cessation Pharmacotherapy Efficacy in Comorbid Medical Populations: Secondary Analysis of the Evaluating Adverse Events in a Global Smoking Cessation Study (EAGLES) Randomized Clinical Trial.

INTRODUCTION: This study sought to compare medication efficacy in participants with medical comorbidities who smoke in the Evaluating Adverse Events in a Global Smoking Cessation Study (EAGLES) trial, a double-blind, triple-dummy, placebo- and active-controlled randomized controlled trial. AIMS AND METHODS: Participants were from the U.S. cohort of the main trial and randomized (1:1:1:1) to varenicline, bupropion, nicotine replacement therapy (NRT) patch, or placebo for 12 weeks with follow-up through week 24. Medical comorbidity data were derived from the baseline medical screening questionnaire and categorized into four subgroups (cardiac, respiratory, vascular, and diabetes). Within each comorbidity, generalized linear mixed models were used to assess the association between treatment and continuous abstinence rates from weeks 9-12 to 9-24. Similar models were used to test the effect of number of comorbidities on abstinence. RESULTS: Varenicline resulted in the highest week 12 abstinence rates across all pharmacotherapies and compared to placebo in all comorbidity subgroups: Cardiac (40.0% vs. 3.6%; odds ratios [OR] = 23.3 [5.1-107.1]), respiratory (24.7% vs. 12.8%; OR = 2.2 [1.3-3.8]), vascular (29.1% vs. 10.4%; OR = 3.6 [2.3-5.7]), and diabetes (30.9% vs. 8.3%; OR = 6.5 [2.3-19.0]). This was maintained at week 24 for those with cardiac (23.3% vs. 1.8%; OR = 21.7 [2.7-178.2]), vascular (18.9% vs. 7.1%; OR = 3.1 [1.8-5.3]), and diabetes (20.6% vs. 4.2%; OR = 8.4 [2.1-33.7]) comorbidities. Treatment contrasts within some comorbidity subgroups revealed superior efficacy of varenicline over other pharmacotherapies. All pharmacotherapies increased the odds of abstinence regardless of number of comorbidities. CONCLUSIONS: Varenicline is the most efficacious option for patients with manageable cardiac, respiratory, vascular, and diabetes conditions to quit smoking, supporting recent clinical practice guidelines that recommend varenicline as first-line pharmacotherapy. Bupropion and NRT demonstrated efficacy for some comorbidity subgroups. IMPLICATIONS: This secondary analysis of the EAGLES trial demonstrated that varenicline is the most efficacious option for patients with cardiac, respiratory, vascular, and diabetes diagnoses to quit smoking. This demonstration of varenicline efficacy among individuals with comorbid medical conditions supports recent clinical practice guidelines that recommend varenicline as a first-line pharmacotherapy for smoking cessation.

Development of two novel treatments to promote smoking cessation: Savor and retrieval-extinction training pilot clinical trial findings.

Despite decades of progress, cigarette smoking remains a significant contributor to disease burden. This effect is especially pronounced for specific priority populations, such as individuals who live in rural communities, in that the burden of tobacco smoking is greater among these groups than in urban areas and the general population. The present study aims to evaluate the feasibility and acceptability of two novel tobacco treatment interventions delivered through remote telehealth procedures to individuals who smoke in the state of South Carolina. Results also include exploratory analyses of smoking cessation outcomes. Study I evaluated savoring, a strategy based on mindfulness practices, alongside nicotine replacement therapy (NRT). Study II evaluated retrieval-extinction training (RET), a memory-modification paradigm alongside NRT. In Study I (savoring), recruitment and retention data showed high interest and engagement in the intervention components, and participants who received this intervention decreased cigarette smoking throughout the course of the treatment (ps < .05). In Study II (RET), results showed high interest and moderate engagement in treatment, although exploratory outcome analyses did not demonstrate significant treatment effects on smoking behaviors. Overall, both studies showed promise in generating interest among individuals who smoke in participating in remotely delivered, telehealth smoking cessation interventions with novel therapeutic targets. A brief savoring intervention appeared to have effects on cigarette smoking throughout treatment, whereas RET did not. Gaining insight from the present pilot study, future studies may improve the efficacy of these procedures and incorporate the treatment components into more robust available treatments. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Shift From Smoking Cigarettes to Vaping Nicotine in Young Adults.

This survey study assesses trends in nicotine use among young adults in the US between 2013 and 2021.

Effect of a Personalized Tobacco Treatment Intervention on Smoking Abstinence in Individuals Eligible for Lung Cancer Screening.

INTRODUCTION: To determine whether personalized gain-framed messaging and biomarker feedback related to tobacco cessation or reduction decrease smoking behavior in patients undergoing or eligible for lung cancer screening. METHODS: Between 2016 and 2020, 188 patients were enrolled in a two-phase, sequential, randomized controlled trial. Phase 1 evaluated whether standard of care (SC) (five in-person counseling sessions and 8 weeks of nicotine patch) plus gain-framed messaging (GFM) versus SC would increase 8-week biochemically verified smoking cessation rates. In 143 participants randomized in phase 2, we tested whether feedback on smoking-related biomarkers would reduce 6-month self-reported number of cigarettes smoked per day compared with a no feedback control. Chi-square test and mixed effects repeated measures analyses were used to evaluate group differences. RESULTS: Participants were 62.5 ± 5.6 (mean ± SD) years of age, had a 50.3 ± 21 pack-year smoking history, and were smoking 16.9 ± 9.9 cigarettes per day. At 8 weeks, there was no difference in quit rates between those randomized to SC plus GFM (n = 15 of 93, 16.1%) and those randomized to SC (n = 16 of 95, 16.8%), with p equals to 0.90. At the 6-month post-randomization follow-up, number of cigarettes smoked per day was similar in the feedback (least-squares mean = 7.5, 95% confidence interval: 6.0-9.1) and no feedback arms (7.7, 95% confidence interval: 6.2-9.3), with p equals to 0.87. CONCLUSIONS: Gain-framed messaging and health feedback did not significantly improve quit rates relative to comprehensive standard of care. Nevertheless, the overall program achieved clinically meaningful smoking quit rates in this older high pack-year cohort, highlighting the importance of intensive tobacco treatment for patients undergoing lung cancer screening. CLINICAL TRIAL REGISTERED WITH CLINICALTRIALS.GOV: NCT02658032.

Is hospitalization a missed opportunity to intervene on tobacco cessation?

BACKGROUND: Although tobacco use is associated with elevated morbidity and mortality, its use remains widespread among adults within the United States. Nicotine Replacement Therapy (NRT) products are effective aids that improve rates of tobacco cessation. Many smokers interact with the medical system, such as during hospitalization, without their tobacco use addressed. Hospitalization is a teachable moment for patients to make health-related changes, including tobacco cessation. METHODS: Retrospective cohort study of adult patients in a university-based patient-centered medical home from 2012 to 2021 evaluating the proportion of adults who smoke who received at least one prescription for NRT. Logistic regression models were used to analyze the association of being hospitalized and receipt of a NRT prescription. RESULTS: Of the 4,072 current smokers identified, 1,182 (29%) received at least one prescription for NRT during the study period. Hospitalization was associated with increased odds of receiving a NRT prescription (OR 1.68). Of 1,844 current smokers with a hospitalization during the study period, 1,078 (58%) never received a prescription for NRT at any point. Only 87 (5%) of the smokers received a prescription for NRT during hospitalization or at the time of hospital discharge. CONCLUSIONS: Despite hospitalization being associated with NRT prescribing, most patients who use tobacco and are hospitalized are not prescribed NRT. Hospitalization is an underutilized opportunity for both hospitalists and primary care physicians to intervene on smoking cessation through education and prescription of tobacco cessation aids.

Implementation of an "Opt-Out" Tobacco Treatment Program in Six Hospitals in South Carolina.

Objective: To describe the implementation an opt-out tobacco treatment program (TTP) in 6 diverse hospitals located in different regions of South Carolina. Methods: Between March 8, 2021 and December 17, 2021, adult patients (≥ 18 years) admitted to 6 hospitals affiliated with the Medical University of South Carolina (MUSC) were screened for their cigarette status. Patients who smoked cigarettes were referred to an TTP offering a brief bedside consult and automated post-discharge follow-up calls with an opportunity to receive a referral to the South Carolina Quitline (SCQL). The hospitals included in this study ranged in size from 82 to 715 beds with diverse patient populations. Herein, we report on the results of screening and referring patients to the TTP, delivery of smoking cessation treatments, and patient smoking status assessed in a sample of patients followed 6-weeks after discharge from the hospital. Results: Smoking prevalence ranged from 14-49% across the 6 hospitals. Among eligible patients reached, 85.6% accepted the bedside consult. Only 3.4% of patients reached were deemed ineligible because they claimed not to be currently smoking cigarettes. The automated post-discharge follow-up calls were answered by 43% of patients, with about a third of those who had relapsed back to smoking accepting the offer of a referral to the SCQL. Overall, about half of the 6,000 patients referred to the TTP received some type of treatment. Self-reported smoking abstinence rates assessed 6-weeks after discharge were similar across the five acute care hospitals ranging from about 20-30%. Conclusion: The findings demonstrate the broad reach of implementing an opt-out TTP for patients in hospitals of varying size, rurality and patient populations.

A Secondary Analysis of a Preliminary Contingency Management Intervention for Presurgical Cancer Patients: Evaluating Individual Participant Data.

INTRODUCTION: Contingency management (CM) interventions deliver monetary reinforcers contingent upon biochemically verified abstinence from smoking. CM has been found to be effective, however, individual participant, analyses are warranted to further elucidate how individual-level behavior patterns vary during the intervention period, both within and across treatment groups. AIMS AND METHODS: This is a secondary analysis of a randomized controlled pilot trial of presurgical cancer patients who smoke (RCT N = 40). All participants were current everyday smokers and were enrolled in cessation counseling, offered nicotine replacement therapy, and submitted breath CO testing 3 times per week for 2-5 weeks. Participants randomized to CM received monetary reinforcers for breath CO ≤6 ppm on an escalating schedule of reinforcement with a reset for positive samples. Sufficient breath CO data exist for 28 participants (CM = 14; monitoring only [MO] = 14). Effect size was calculated for differences in negative CO tests. Time to first negative test was tested using survival analysis. Fisher's exact test was used to assess relapse. RESULTS: The CM group achieved abstinence more quickly (p < .05), had a lower percentage of positive tests (h = 0.80), and experienced fewer lapses following abstinence (p = .00). While 11 of 14 participants in the CM group achieved and sustained abstinence by their third breath test, this was only true for 2 of the 14 MO participants. CONCLUSIONS: Those in CM achieved abstinence quicker and with fewer lapses than those engaged in MO speaking to the efficacy of the schedule of financial reinforcement. This is particularly important within presurgical populations given the potential benefits to postoperative cardiovascular and wound infection risk. IMPLICATIONS: While the efficacy of CM as an intervention is well established, this secondary analysis provides insight into the individual behavior patterns underlying successful abstinence. Those assigned to CM were not only more likely to achieve abstinence, but did so more quickly and with fewer instances of relapse. This is of particular importance to those scheduled for surgery where achieving abstinence as early as possible impacts on the risk of postoperative complications. CM interventions may be particularly well suited for critical windows in which timely and sustained abstinence is advantageous.

Tobacco use and cancer-related symptom burden: Analysis of the US Population Assessment of Tobacco and Health Study.

BACKGROUND: Understanding the relationship between tobacco use and symptom burden may inform tobacco treatment interventions tailored to the needs of individuals with cancer. METHODS: The study included 1409 adult cancer survivors from Wave 5 of the US Food and Drug Administration Population Assessment of Tobacco and Health (PATH) Study. A multivariate analysis of variance controlling for age, sex, and race/ethnicity assessed the association of cigarette smoking and vaping on cancer-related symptom burden (fatigue, pain, emotional problems) and quality of life (QoL). Generalized linear mixed models controlling for the same factors were used to assess associations among symptom burden, QoL, and quit-smoking intentions, quit-smoking likelihood, and past 12-month smoking quit attempts. RESULTS: Weighted rates of current cigarette smoking and vaping were 14.21% and 2.88%, respectively. Current smoking was associated with greater fatigue (p < .0001; partial η 2  = .02), pain (p < .0001; partial η 2  = .08), emotional problems (p < .0001; partial η 2  = .02), and worse QoL (p < .0001; partial η 2  = .08). Current vaping was associated with greater fatigue (p = .001; partial η 2  = .008), pain (p = .009; partial η 2  = .005), and emotional problems (p = .04; partial η 2  = .003), but not worse QoL (p = .17). Higher cancer symptom burden was not associated with reduced interest in quitting, likelihood of quitting, or odds of past year quit attempts (p > .05 for each). CONCLUSIONS: Among adults with cancer, current smoking and vaping were associated with greater symptom burden. Survivors' interest in and intentions to quit smoking were not related to symptom burden. Future research should examine the role of tobacco cessation in improving symptom burden and QoL.

E-Cigarette Screening in Primary Care.

INTRODUCTION: Primary care visits present an opportune time to assess behaviors that contribute to patient health. Smoking, alcohol use, and illicit drugs are routinely documented in electronic health records, but less is known about screening for E-cigarette use and the prevalence of E-cigarette use in primary care settings. METHODS: Data include 134,931 adult patients who visited 1 of 41 primary care clinics within a 12-month period (June 1, 2021-June 1, 2022). Data on demographics, combustible tobacco, alcohol, illicit drug, and E-cigarette use were extracted from electronic medical records. Logistic regression was utilized to examine the variables associated with differential odds of being screened for E-cigarette use. RESULTS: Rates of E-cigarette screening (n=46,997; 34.8%) were significantly lower than that of tobacco (n=134,196; 99.5%), alcohol (n=129,766; 96.2%), and illicit drug (n=129,766; 92.6%) use. Of those assessed for E-cigarette use, 3.6% (n=1,669) reported current use. Of those with documented nicotine use (n=7,032), 17.2% (n=1,207) used mono E-cigarettes exclusively, 76.3% (n=5,364) used combustible tobacco exclusively, and 6.6% (n=461) reported dual use (both E-cigarette use and combustible tobacco use). Those who used combustible tobacco or illicit substances as well as younger patients were more likely to have been screened for E-cigarette use. CONCLUSIONS: Overall rates of E-cigarette screening were significantly lower than those of other substances. The use of combustible tobacco or illicit substances was associated with an increased likelihood of being screened. This finding may be because of the relatively recent proliferation of E-cigarettes, the recent addition of E-cigarette documentation to the electronic health record, or a lack of training on screening for E-cigarette use.