Interventions for smoking cessation in hospitalised patients.

BACKGROUND: In 2020, 32.6% of the world's population used tobacco. Smoking contributes to many illnesses that require hospitalisation. A hospital admission may prompt a quit attempt. Initiating smoking cessation treatment, such as pharmacotherapy and/or counselling, in hospitals may be an effective preventive health strategy. Pharmacotherapies work to reduce withdrawal/craving and counselling provides behavioural skills for quitting smoking. This review updates the evidence on interventions for smoking cessation in hospitalised patients, to understand the most effective smoking cessation treatment methods for hospitalised smokers. OBJECTIVES: To assess the effects of any type of smoking cessation programme for patients admitted to an acute care hospital. SEARCH METHODS: We used standard, extensive Cochrane search methods. The latest search date was 7 September 2022. SELECTION CRITERIA: We included randomised and quasi-randomised studies of behavioural, pharmacological or multicomponent interventions to help patients admitted to hospital quit. Interventions had to start in the hospital (including at discharge), and people had to have smoked within the last month. We excluded studies in psychiatric, substance and rehabilitation centres, as well as studies that did not measure abstinence at six months or longer. DATA COLLECTION AND ANALYSIS: We used standard Cochrane methods. Our primary outcome was abstinence from smoking assessed at least six months after discharge or the start of the intervention. We used the most rigorous definition of abstinence, preferring biochemically-validated rates where reported. We used GRADE to assess the certainty of the evidence. MAIN RESULTS: We included 82 studies (74 RCTs) that included 42,273 participants in the review (71 studies, 37,237 participants included in the meta-analyses); 36 studies are new to this update. We rated 10 studies as being at low risk of bias overall (low risk in all domains assessed), 48 at high risk of bias overall (high risk in at least one domain), and the remaining 24 at unclear risk. Cessation counselling versus no counselling, grouped by intensity of intervention Hospitalised patients who received smoking cessation counselling that began in the hospital and continued for more than a month after discharge had higher quit rates than patients who received no counselling in the hospital or following hospitalisation (risk ratio (RR) 1.36, 95% confidence interval (CI) 1.24 to 1.49; 28 studies, 8234 participants; high-certainty evidence). In absolute terms, this might account for an additional 76 quitters in every 1000 participants (95% CI 51 to 103). The evidence was uncertain (very low-certainty) about the effects of counselling interventions of less intensity or shorter duration (in-hospital only counselling ≤ 15 minutes: RR 1.52, 95% CI 0.80 to 2.89; 2 studies, 1417 participants; and in-hospital contact plus follow-up counselling support for ≤ 1 month: RR 1.04, 95% CI 0.90 to 1.20; 7 studies, 4627 participants) versus no counselling. There was moderate-certainty evidence, limited by imprecision, that smoking cessation counselling for at least 15 minutes in the hospital without post-discharge support led to higher quit rates than no counselling in the hospital (RR 1.27, 95% CI 1.02 to 1.58; 12 studies, 4432 participants). Pharmacotherapy versus placebo or no pharmacotherapy Nicotine replacement therapy helped more patients to quit than placebo or no pharmacotherapy (RR 1.33, 95% CI 1.05 to 1.67; 8 studies, 3838 participants; high-certainty evidence). In absolute terms, this might equate to an additional 62 quitters per 1000 participants (95% CI 9 to 126). There was moderate-certainty evidence, limited by imprecision (as CI encompassed the possibility of no difference), that varenicline helped more hospitalised patients to quit than placebo or no pharmacotherapy (RR 1.29, 95% CI 0.96 to 1.75; 4 studies, 829 participants). Evidence for bupropion was low-certainty; the point estimate indicated a modest benefit at best, but CIs were wide and incorporated clinically significant harm and clinically significant benefit (RR 1.11, 95% CI 0.86 to 1.43, 4 studies, 872 participants). Hospital-only intervention versus intervention that continues after hospital discharge Patients offered both smoking cessation counselling and pharmacotherapy after discharge had higher quit rates than patients offered counselling in hospital but not offered post-discharge support (RR 1.23, 95% CI 1.09 to 1.38; 7 studies, 5610 participants; high-certainty evidence). In absolute terms, this might equate to an additional 34 quitters per 1000 participants (95% CI 13 to 55). Post-discharge interventions offering real-time counselling without pharmacotherapy (RR 1.23, 95% CI 0.95 to 1.60, 8 studies, 2299 participants; low certainty-evidence) and those offering unscheduled counselling without pharmacotherapy (RR 0.97, 95% CI 0.83 to 1.14; 2 studies, 1598 participants; very low-certainty evidence) may have little to no effect on quit rates compared to control. Telephone quitlines versus control To provide post-discharge support, hospitals may refer patients to community-based telephone quitlines. Both comparisons relating to these interventions had wide CIs encompassing both possible harm and possible benefit, and were judged to be of very low certainty due to imprecision, inconsistency, and risk of bias (post-discharge telephone counselling versus quitline referral: RR 1.23, 95% CI 1.00 to 1.51; 3 studies, 3260 participants; quitline referral versus control: RR 1.17, 95% CI 0.70 to 1.96; 2 studies, 1870 participants). AUTHORS' CONCLUSIONS: Offering hospitalised patients smoking cessation counselling beginning in hospital and continuing for over one month after discharge increases quit rates, compared to no hospital intervention. Counselling provided only in hospital, without post-discharge support, may have a modest impact on quit rates, but evidence is less certain. When all patients receive counselling in the hospital, high-certainty evidence indicates that providing both counselling and pharmacotherapy after discharge increases quit rates compared to no post-discharge intervention. Starting nicotine replacement or varenicline in hospitalised patients helps more patients to quit smoking than a placebo or no medication, though evidence for varenicline is only moderate-certainty due to imprecision. There is less evidence of benefit for bupropion in this setting. Some of our evidence was limited by imprecision (bupropion versus placebo and varenicline versus placebo), risk of bias, and inconsistency related to heterogeneity. Future research is needed to identify effective strategies to implement, disseminate, and sustain interventions, and to ensure cessation counselling and pharmacotherapy initiated in the hospital is sustained after discharge.

Changes in weight among individuals with psychiatric conditions or socioeconomic disadvantage assigned to smoke very low nicotine content cigarettes.

Nicotine abstinence leads to weight gain, which could be an unintended consequence of a nicotine reduction policy. This secondary analysis used weekly assessments of weight and ratings of "increased appetite/hunger/weight gain" collected in three 12-week, randomized controlled trials evaluating the effects of cigarettes differing in nicotine dose (15.8, 2.4, or 0.4 mg/g) among individuals with affective disorders, opioid use disorder (OUD), and socioeconomically disadvantaged women. Linear mixed models tested differences by dose and time. Analyses first collapsed across populations and then separated out individuals with OUD because biomarkers suggested they used substantially more noncombusted nicotine. Across populations, weight increased significantly over time, averaging 1.03 kg (p < .001), but did not vary by dose nor was there any interaction of dose/time. "Increased appetite/hunger/weight gain" ratings increased significantly as a function of dose, with differences between low and high doses (1.95 and 1.73, respectively, p = .01), but not by time nor any interaction. In the combined group of individuals with affective disorders and socioeconomically disadvantaged women, weight and "increased appetite/hunger/weight gain" ratings increased significantly by dose, with differences between low and high doses (1.43 vs. 0.73 kg, p = .003 and 2.00 vs. 1.76, p = .02, respectively). Among individuals with OUD, there were no significant effects of any kind on either outcome. Individuals with affective disorders and socioeconomically disadvantaged women gained weight and reported more subjective appetite/weight gain when given 0.4, but not 2.4 mg/g cigarettes, despite comparable decreases in nicotine exposure. However, neither change was clinically significant, suggesting minimal short-term adverse consequences of a nicotine reduction policy. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Contingency management is associated with positive changes in attitudes and reductions in cannabis use even after discontinuation of incentives among non-treatment seeking youth.

BACKGROUND: It is important to identify interventions that reduce harm in youth not motivated to change their cannabis use. This study evaluated how short-duration contingency management (CM) impacts cannabis use attitudes and behavior after abstinence incentives are discontinued among non-treatment seeking youth. METHODS: Participants (N=220) were randomized to 4 weeks of abstinence-based CM (CB-Abst; n=126) or monitoring (CB-Mon; n=94). Participants completed self-report and provided biochemical measures of cannabis exposure at baseline, end-of-intervention, and 4-week follow-up. Changes in self-reported cannabis use frequency (days/week; times/week) and biochemically verified creatinine-adjusted 11-nor-9-carboxy-tetrahydrocannabinol concentrations (CN-THCCOOH) were analyzed between groups from baseline to follow-up. In CB-Abst, cannabis use goals at end-of-intervention were described and changes in cannabis use at follow-up were explored by goals and cannabis use disorder (CUD) diagnosis. RESULTS: There was a group by visit interaction on cannabis use (days: beta=0.93, p=0.005; times: beta=0.71, p<0.001; CN-THCCOOH: beta=0.26, p=0.004), with reductions at follow-up detected only in CB-Abst. Following 4 weeks of abstinence, 68.4% of CB-Abst participants wanted to reduce or abstain from cannabis use following completion of CM. Those in CB-Abst who set end-of-intervention reduction goals and were without CUD had greater decreases in cannabis use frequency at follow-up (Goals*time on days/week: beta=-2.27, p<0.001; CUD*time on times/week: beta=0.48, SE=0.24, t=2.01, p=0.048). CONCLUSIONS: Findings support the utility of brief incentivized abstinence for generating motivation to reduce cannabis use and behavior change even after incentives end. This study supports CM as a potentially viable harm reduction strategy for those not yet ready to quit.

The effect of neighborhood socioeconomic disadvantage on smoking status, quit attempts, and receipt of cessation support among adults with cancer: Results from nine ECOG-ACRIN Cancer Research Group trials.

BACKGROUND: Tobacco use is associated with adverse outcomes among patients diagnosed with cancer. Socioeconomic determinants influence access and utilization of tobacco treatment; little is known about the relationship between neighborhood socioeconomic disadvantage (NSD) and tobacco assessment, assistance, and cessation among patients diagnosed with cancer. METHODS: A modified Cancer Patient Tobacco Use Questionnaire (C-TUQ) was administered to patients enrolled in nine ECOG-ACRIN clinical trials. We examined associations of NSD with (1) smoking status, (2) receiving tobacco cessation assessment and support, and (3) cessation behaviors. NSD was classified by tertiles of the Area Deprivation Index. Associations between NSD and tobacco variables were evaluated using logistic regression. RESULTS: A total of 740 patients completing the C-TUQ were 70% male, 94% White, 3% Hispanic, mean age 58.8 years. Cancer diagnoses included leukemia 263 (36%), lymphoma 141 (19%), prostate 131 (18%), breast 79 (11%), melanoma 69 (9%), myeloma 53 (7%), and head and neck 4 (0.5%). A total of 402 (54%) never smoked, 257 (35%) had formerly smoked, and 81 (11%) were currently smoking. Patients in high disadvantaged neighborhoods were approximately four times more likely to report current smoking (odds ratio [OR], 3.57; 95% CI, 1.69-7.54; p = .0009), and more likely to report being asked about smoking (OR, 4.24; 95% CI, 1.64-10.98; p = .0029), but less likely to report receiving counseling (OR, 0.11; 95% CI, 0.02-0.58; p = .0086) versus those in the least disadvantaged neighborhoods. CONCLUSIONS: Greater neighborhood socioeconomic disadvantage was associated with smoking but less cessation support. Increased cessation support in cancer care is needed, particularly for patients from disadvantaged neighborhoods.

Incidence of opioid misuse by cigarette smoking status in the United States.

BACKGROUND: The combination of opioid misuse and cigarette smoking contributes to increased morbidity and mortality compared to each substance use alone. We estimated the incidence of opioid misuse for persons who currently or formerly smoked versus never smoked. METHODS: Data came from the 2015-2020 National Surveys on Drug Use and Health cross-sectional surveys of US civilians aged 12+ (n = 315,661). Weighted opioid misuse incidence and average time between cigarette use initiation and opioid misuse initiation were calculated annually by smoking status. Logistic regression models tested time trends in incidence by smoking status. RESULTS: Overall, 0.75% of persons initiated opioid misuse per year; opioid misuse incidence was 1.35% for those who currently smoked cigarettes, 0.54% for those who formerly smoked, and 0.67% for those who never smoked. For persons who currently smoked and misused opioids (1.50%), 95.08% smoked prior to opioid use. The average time between smoking followed by opioid misuse was 12.93 years and for opioid misuse followed by smoking was 4.36 years. Persons who currently smoked were more likely to initiate opioid misuse than those who had never smoked (AOR = 1.81, 95% CI: 1.60, 2.06). There was a decrease in the opioid misuse incidence over time (AOR = 0.90; 95% CI: 0.85, 0.92), which did not differ by smoking status. CONCLUSIONS: Persons who currently smoked cigarettes, relative to those who never smoked, were more likely to initiate opioid misuse. As most individuals smoked before opioid misuse, it may be useful for primary prevention efforts to decrease opioid misuse initiation by focusing on smoking status.

Pain catastrophizing is associated with reduced neural response to monetary reward.

Introduction: Pain catastrophizing, a measure of an individual's negative emotional and cognitive appraisals of pain, has been included as a key treatment target in many psychological interventions for pain. However, the neural correlates of pain catastrophizing have been understudied. Prior neuroimaging evidence suggests that adults with pain show altered reward processing throughout the mesocorticolimbic reward circuitry. Methods: In this study, we tested the association between Pain Catastrophizing Scale (PCS) scores and neural activation to the Monetary Incentive Delay (MID) reward neuroimaging task in 94 adults reporting a range of pain, insomnia, and mood symptoms. Results: Results indicated that PCS score but not pain intensity was significantly associated with blunted activation in the caudate and putamen in response to feedback of successful vs. unsuccessful trials on the MID task. Mediation analyses indicated that PCS score fully mediated the relationship between depression symptoms and reward activation. Discussion: These findings provide evidence that pain catastrophizing is independently associated with altered striatal function apart from depression symptoms and pain intensity. Thus, in individuals experiencing pain and/or co- morbid conditions, reward dysfunction is directly related to pain catastrophizing.

Cigarette and Alternative Tobacco Product Use among Adult Cancer Survivors Enrolled in 9 ECOG-ACRIN Clinical Trials.

BACKGROUND: While cigarette smoking has declined among the U.S. general population, sale and use of non-cigarette alternative tobacco products (ATP; e.g., e-cigarettes, cigars) and dual use of cigarettes/ATPs are rising. Little is known about ATP use patterns in cancer survivors enrolled in clinical trials. We investigated prevalence of tobacco product use, and factors associated with past 30-day use, among patients with cancer in national trials. METHODS: Cancer survivors (N = 756) enrolled in 9 ECOG-ACRIN clinical trials (2017-2021) completed a modified Cancer Patient Tobacco Use Questionnaire (C-TUQ) which assessed baseline cigarette and ATP use since cancer diagnosis and in the past 30 days. RESULTS: Patients were on average 59 years old, 70% male, and the mean time since cancer diagnosis was 26 months. Since diagnosis, cigarettes (21%) were the most common tobacco product used, followed by smokeless tobacco use (5%), cigars (4%), and e-cigarettes (2%). In the past 30 days, 12% of patients reported smoking cigarettes, 4% cigars, 4% using smokeless tobacco, and 2% e-cigarettes. Since cancer diagnosis, 5.5% of the sample reported multiple tobacco product use, and 3.0% reported multiple product use in the past 30 days. Males (vs. females; OR 4.33; P = 0 < 0.01) and individuals not living with another person who smokes (vs. living with; OR, 8.07; P = 0 < 0.01) were more likely to use ATPs only versus cigarettes only in the past 30 days. CONCLUSIONS: Among patients with cancer, cigarettes were the most prevalent tobacco product reported. IMPACT: Regardless, ATPs and multiple tobacco product use should be routinely assessed in cancer care settings.

Injection of Methamphetamine Has Increased in Boston, Massachusetts: 5 Waves of Centers for Disease Control and Prevention State Surveillance Data.

OBJECTIVES: In the United States, the number of overdose deaths related to opioids in combination with stimulants has increased; however, the Northeast has typically been less impacted by stimulant overdose. Injection drug use (IDU) results in high mortality from overdose and infectious disease and there are racial disparities observed in overdose death rates. We examined trends in stimulant and opioid IDU, including trends stratified by race, using 5 waves of cross-sectional state surveillance data. METHODS: Data came from the Centers for Disease Control and Prevention's National HIV Behavioral Surveillance system Boston, Massachusetts site, which includes 5 waves of data (2005-2018) among adults in the Boston metropolitan area reporting IDU (N = 2550). Outcome measures were type of substance injected in the past 12 months (heroin, prescription opioids, "speedball," cocaine, crack, and/or methamphetamine). RESULTS: Participants were 70% male, 58% non-Hispanic White, and injected a mean of 3 different drugs in the past 12 months. From 2015 to 2018, there was a more than 2-fold increase in injection of methamphetamine (15% vs 38%, P < 0.001), a pattern which held across racial groups. Combination heroin and methamphetamine injection increased from 2015 (15%) to 2018 (35%, P < 0.001). Multiple drug injection (injecting >1 drug) increased significantly across years compared with single drug injection ( P = 0.03). CONCLUSIONS: Findings suggest that increased use of methamphetamine and opioids extends to Boston. There is an urgent need for enhanced screening of methamphetamine use among those using opioids and increased access and payor coverage of efficacious treatments for stimulant and opioid use disorders (eg, contingency management and medication treatment for opioid use disorder).

Preliminary feasibility of integrating tobacco treatment into SUD peer recovery coaching: a mixed-methods study of peer recovery coaches.

BACKGROUND: Individuals with substance use disorder (SUD) have high prevalence of cigarette smoking and difficulty quitting. Peer recovery coaches (PRCs; individuals with lived SUD experience) facilitate SUD behavior change in recoverees but it is unknown if/how they address tobacco treatment in SUD recovery coaching. We assessed PRC's tobacco-related practices and attitudes about tobacco treatment in SUD recovery. METHODS: The Tobacco use In Peer-recovery Study (TIPS) was a cross-sectional mixed-methods pilot survey (January-March 2022) of the 26 PRCs employed by a Massachusetts-based healthcare system's 12 SUD treatment clinics/programs. PRCs completed a quantitative survey (n = 23/26; 88%) and a telephone-based qualitative interview (n = 20/26; 77%). RESULTS: One-third of PRCs reported current smoking, 50% reported former smoking, and 18% never smoked. Among PRCs, 61% reported accompanying recoverees outdoors to smoke, 26% smoked with recoverees, 17% had provided cigarettes to recoverees, 32% used smoking to help build peer-relationships, and 74% rated smoking as socially acceptable in SUD treatment. PRCs reported regularly talking to recoverees about tobacco treatment (65%), believed they should have a role in helping recoverees quit smoking (52%), and were interested in tobacco treatment training (65%). A majority of both nonsmoking and current smoking PRCs (73% vs. 57%) regularly talked to recoverees about quitting smoking. CONCLUSION: PRCs' attitudes about integrating tobacco treatment into SUD recovery coaching were generally positive and PRCs reported they could have a role in helping recoverees with tobacco treatment. Barriers to integrating tobacco treatment into SUD recovery include use of cigarettes as a peer-recovery tool and high prevalence and social acceptability of smoking in SUD recovery.

A systematic review and meta-analysis of interventions to induce attempts to quit tobacco among adults not ready to quit.

The prevalence of past-year smoking cessation remains below 10% in the U.S. Most who smoke are not ready to quit in the near future. Cessation requires both (a) initiating a quit attempt (QA) and (b) maintaining abstinence. Most research has focused on abstinence among people already motivated to quit. We systematically reviewed interventions to promote QAs among people not motivated to quit tobacco. We searched PubMed, CENTRAL, PsycINFO, Embase, and our personal libraries for randomized trials of tobacco interventions that reported QAs as an outcome among adults not ready to quit. We screened studies and extracted data in duplicate. We pooled findings of the 25 included studies using Mantel-Haenszel random effects meta-analyses when ≥ 2 studies tested the same intervention. Most (24) trials addressed cigarettes and one addressed smokeless tobacco. Substantial heterogeneity among trials resulted in a series of small meta-analyses. Findings indicate varenicline may increase QAs more than no varenicline, n = 320; RR = 1.4, 95% CI [1.1, 1.7]; I² = 0%, and nicotine replacement therapy (NRT) may increase QAs more than no NRT, n = 2,568; RR = 1.1, 95% CI [1.02, 1.3]; I² = 0%. Pooled effects for motivational counseling, reduction counseling, and very low nicotine content cigarettes showed no clear evidence of benefit or harm. The evidence was judged to be of medium to very low certainty due to imprecision, inconsistency, and risk of bias, suggesting that further research is likely to change interpretation of our results. Findings demonstrate the need for more high-quality research on interventions to induce QAs among adults not ready to quit tobacco. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Patients With Serious Mental Illness Can Engage in Tobacco Treatment Trials and Tobacco Cessation Interventions During Cancer Treatment.

PURPOSE: More than half of individuals with serious mental illness (SMI) smoke, contributing to premature cancer mortality. A cancer diagnosis provides an opportunity to assist with smoking cessation; however, supportive oncology trials frequently exclude patients with SMI. To fill this gap, we examined differences in engagement and tobacco cessation in a pragmatic clinical trial. METHODS: We recruited 303 participants from two National Cancer Institute-designated Comprehensive Cancer Centers, of which 10% had prior diagnoses of SMI (major depressive disorder, bipolar disorder, and schizophrenia spectrum disorders). We compared self-reported smoking behaviors, patient attitudes and beliefs about cessation, and rates of trial completion, engagement, and smoking abstinence among recently diagnosed patients with cancer with and without SMI. Six months after trial completion, we completed qualitative interviews on barriers and facilitators to tobacco cessation in a random sample of participants with SMI. RESULTS: Trial participants with SMI had similar motivation to quit smoking as those without SMI. Additionally, participants with SMI had a similar ability to engage in a tobacco treatment trial (6.5 counseling sessions completed v 7.3 sessions) and benefit from tobacco treatment as those without SMI (32.3% v 27.8% 6-month quit rates). CONCLUSION: Patients with cancer and SMI were able to engage in and benefit from a tobacco cessation trial integrated into cancer care. A cancer diagnosis provides an opportunity to assist patients with SMI with smoking cessation referrals and treatment. Pragmatic supportive oncology trials that include a diverse population of adults with SMI are needed to inform care delivery and improve cancer outcomes for patients with SMI and cancer.

Relating individual differences in the reinforcing value of smoking and dependence severity to nicotine exposure levels in vulnerable populations.

Cigarette smoking is overrepresented in populations with psychiatric conditions and socioeconomic disadvantage. Greater understanding of the role of reinforcement and nicotine dependence in smoking among vulnerable populations may facilitate development of better targeted interventions to reduce smoking. Prior research demonstrated that individual differences in the reinforcing value of smoking and nicotine-dependence severity predicted total nicotine-exposure in vulnerable populations. The present study uses multivariate regression to address two aims: (1) Quantify the degree to which the reinforcing value of smoking, assessed using the Cigarette Purchase Task (CPT), and dependence severity assessed using the Fagerström Test of Nicotine Dependence and Brief Wisconsin Inventory of Smoking Dependence Motives (B-WISDM) each account for individual differences in cotinine-plus-3'-hydroxycotinine (COT+3HC) levels. (2) Explore whether there is overlap in the variance accounted for by the CTP, FTND, and B-WISDM. Participants were 628 adults with co-morbid psychiatric conditions or socioeconomic disadvantage who smoked daily. The CPT, FTND, and B-WISDM models accounted for 23.76%, 32.45%, and 29.61% of the variance in COT+3HC levels, respectively. Adding CPT to the FTND model failed to increase the variance accounted for and adding it to the B-WISDM model did so by only 1.2% demonstrating considerable overlap in the variance in nicotine exposure levels accounted for by these three instruments. These results provide new knowledge on the relationship between individual differences in the reinforcing value of smoking and nicotine-exposure levels and suggest differences in reinforcing value may underpin a considerable portion of the variance in nicotine exposure accounted for by dependence severity.

Prevalence of Cannabis Use and Cannabis Route of Administration among Massachusetts Adults in Buprenorphine Treatment for Opioid Use Disorder.

BACKGROUND: Recent prevalence estimates of cannabis use among individuals receiving medication treatment for OUD (MOUD) are lacking, and no study has characterized cannabis route of administration (cROA) in this population. These knowledge gaps are relevant because cannabis' effects and health outcomes vary by cROA and the availability and perceptions of cROA (e.g., vaping devices) are changing. METHODS: The Vaping In Buprenorphine-treated patients Evaluation (VIBE) cross-sectional survey assessed the prevalence and correlates of cannabis use and cROA among adults receiving buprenorphine MOUD from 02/20 to 07/20 at five community health centers in Massachusetts, a state with legal recreational and medical cannabis use. RESULTS: Among the 92/222 (41%) respondents reporting past 30-day cannabis use, smoking was the most common cROA (75%), followed by vaping (38%), and eating (26%). Smoking was more often used as a single cROA vs. in combination others (p = 0.01), whereas vaping, eating, and dabbing were more often used in combination with another cROA (all p < 0.05). Of the 39% of participants reporting multiple cROA, smoking and vaping (61%), and smoking and eating (50%), were the most prevalent combinations. Nonwhite race (vs. white) and current cigarette smoking (vs. no nicotine use) were associated with past 30-day cannabis use in multiple logistic regression. CONCLUSIONS: Prevalence of past 30-day cannabis use among individuals receiving buprenorphine MOUD in Massachusetts in 2020 was nearly double the prevalence of cannabis use in Massachusetts' adult general population in 2019 (21%). Our data are consistent with state and national data showing smoking as the most common cROA.

National Trends in Suicide Thoughts and Behavior among US Adults with Opioid Use Disorder from 2015 to 2020.

INTRODUCTION: Suicide thoughts and behavior (STB) are associated with premature mortality and is disproportionately represented among those with opioid use disorder (OUD). Recent trends in STB among those with OUD are lacking. We investigated trends in STB among US adults with versus without OUD using six waves of cross-sectional, nationally-representative, epidemiological data. METHODS: Data came from the 2015-2020 National Survey on Drug Use and Health (combined n = 241,675). We compared past-year STB outcomes (i.e., thoughts of seriously considering killing self (SI), suicide plan (SP), suicide attempt (SA)) among adults with versus without past-year OUD. Unadjusted and adjusted logistic regression tested the association between survey-year and past-year STB outcomes (i.e., SI, SP/SA) stratified by OUD status. RESULTS: Between 2015 and 2020, 26% versus 4% of those with and without OUD, respectively, reported SI, 10% versus 1% reported a SP, and 6% versus 1% reported SA (all ps < 0.001). In adjusted analyses, across survey years, no changes in the prevalence of SI were observed for adults with or without OUD, and no changes were observed over time for SP/SA in adults with or without OUD. OUD severity and treatment status did not moderate the relationship between OUD and STB outcomes. CONCLUSIONS: Among US adults, OUD was associated with thoughts of suicide and suicide behavior. The heightened prevalence of STB in adults with OUD has not changed in recent years. Screening for SI is needed among those reporting opioid misuse and should be routinely integrated into OUD prevention and treatment.

Corrigendum to "Examining the effects of stress and psychological distress on smoking abstinence in cancer patients" [Prev. Med. Rep. 23 (2021) 101402].

[This corrects the article DOI: 10.1016/j.pmedr.2021.101402.].

Longitudinal Electronic Cigarette Use Among Patients Recently Diagnosed With Cancer Enrolled in a Smoking Cessation Trial.

INTRODUCTION: Many cancer patients who smoke report concurrent e-cigarette use. Using a mixed-methods approach, we aimed to (1) describe longitudinal e-cigarette use over 6 months after a cancer diagnosis and (2) assess the association between e-cigarette use and smoking cessation, among cancer patients in a smoking cessation trial. AIMS AND METHODS: Data were from a 2-site randomized controlled trial of Standard (brief counseling) versus Intensive treatment (sustained counseling plus smoking cessation medication) in individuals who smoke recently diagnosed with cancer. Participants (n = 303) reported e-cigarette use at baseline, 3 months, and 6 months. Biochemically-verified past 7-day cigarette abstinence was collected at 6 months. Qualitative interviews at 6 months explored factors related to e-cigarette use. RESULTS: E-cigarette use prevalence was highest between baseline and 3 months (16%) and declined over time. Participants using e-cigarettes at follow-up had higher baseline cigarette dependence and smoked more heavily. Multivariable analyses found no significant association between follow-up e-cigarette use and 6-month cigarette abstinence. E-cigarette use at follow-up was higher in the Standard versus Intensive treatment group (p = .003 and .001 at 3 and 6 mo, respectively). Smoking cessation and health concerns were primary reasons for using e-cigarettes. CONCLUSIONS: Among individuals who smoke recently diagnosed with cancer and enrolled in a smoking cessation intervention trial, e-cigarette use during trial participation was not associated with smoking abstinence. Individuals who chose to use e-cigarettes were less likely to be receiving intensive cessation support as part of the trial. Further studies are needed to evaluate the association between e-cigarette use and smoking cessation in cancer patients. IMPLICATIONS: E-cigarette use was not associated with cigarette abstinence at 6 months among adults who smoke recently diagnosed with cancer enrolled in a smoking cessation trial. Individuals with easier access to evidence-based smoking cessation treatment may be less likely to use e-cigarettes.

Investigating documentation of alcohol and non-medical substance use in oncology treatment: an electronic health record review.

PURPOSE: Little is known about non-tobacco substance use (SU) and its treatment in cancer patients. National guidelines address tobacco only, and assessment of SU in cancer patients is not standardized. It is not clear how oncology clinicians assess, document, and follow-up on SU. METHODS: We conducted an electronic health record review of patients enrolled in a smoking cessation trial at one large hospital site (N = 176). Chart review of oncology treatment notes assessed whether SU assessment was documented, the content of the documentation/assessment (e.g., frequency of use), and details about documentation (e.g., where/who documented). RESULTS: Sixty-nine percent (121/176) of cancer patients had SU documented. Many patients (42%, 74/176) had only one substance documented; 66% (116/176) had alcohol use documented. For a substantial minority of patients (43/176; 24%), the provider did not specify the substance assessed (e.g., "drug use," "illicits"). SU was primarily documented by physicians (84%, 102/121), in routine progress notes (56%, 68/121), in the "social history" section of the note (84%, 102/121). Only 4 patients had a documented SU follow-up plan. When examining the subset of patients who reported problematic alcohol use (N = 27), the content of documentation was inconsistent (e.g., number of drinks/day vs. qualitative descriptors of use). CONCLUSIONS: About 1/3 of oncology patients did not have SU assessment documented. SU other than alcohol use was infrequently documented, many clinicians documented SU but did not specify substance type, and few clinicians documented a follow-up plan for problematic SU. Oncology settings should utilize standardized assessment and referral for SU treatment.

Perceptions of E-cigarettes among adults in treatment for opioid use disorder.

Background: Individuals with opioid use disorder (OUD) have a high prevalence of smoking and limited success quitting smoking with existing tools. There is ongoing debate about whether electronic cigarettes (e-cigarettes) may be a viable harm reduction strategy. We sought to determine the potential acceptability of e-cigarettes for cigarette harm reduction among individuals receiving medication treatment for opioid use disorder (MOUD) with buprenorphine. Among individuals receiving MOUD we investigated health harm perceptions of cigarettes, nicotine e-cigarettes, and nicotine replacement therapy (NRT), and perceptions of the helpfulness of e-cigarettes and NRT for quitting cigarettes. Methods: Cross-sectional telephone survey conducted among adults in buprenorphine treatment at five community health centers in the Boston, MA metropolitan area from February to July 2020. Results: 93% and 63% of participants rated cigarettes and e-cigarettes, respectively, as very or extremely harmful to health, and 62% rated NRT as not to slightly harmful to health. Over half (58%) rated cigarettes as more harmful than e-cigarettes; 65% and 83% perceived e-cigarettes and NRT, respectively, to be helpful for reducing/quitting cigarette use. In bivariate analyses, nicotine e-cigarette users, compared to nonusers, perceived e-cigarettes to be less harmful to health and more often rated e-cigarettes as helpful for reducing/quitting cigarette use (both p<0.05). Conclusions: This study suggests that Massachusetts patients receiving MOUD with buprenorphine have concerns about the health harms of e-cigarettes yet rate them as helpful tools for reducing or quitting cigarette smoking. Future research is needed to test the efficacy of e-cigarettes for cigarette harm reduction.

Effects of Reduced Nicotine Content Cigarettes on Fractional Exhaled Nitric Oxide and Self-Reported Respiratory Health Outcomes Among Smokers With Psychiatric Conditions or Socioeconomic Disadvantage.

INTRODUCTION: This study examined whether exposure to reduced-nicotine-content cigarettes (RNCCs) for 12 weeks alters respiratory health using Fractional Exhaled Nitric Oxide (FeNO), a validated biomarker of respiratory epithelial health, and the Respiratory Health Questionnaire (RHQ), a subject-rated questionnaire on respiratory symptoms. Participants were 747 adult daily smokers enrolled in three double-blind, randomized clinical trials evaluating effects of cigarette nicotine content (0.4, 2.4, 15.8 mg nicotine/g tobacco) in people with affective disorders, opioid use disorder (OUD), or socioeconomic disadvantage. AIMS AND METHODS: FeNO levels and RHQ ratings were collected at baseline and Weeks 6 and 12 following randomization. Multiple regression was used to assess associations of FeNO and RHQ with smoking characteristics. Mixed-model repeated-measures ANOVA was used to evaluate the effects of nicotine content on FeNO and RHQ outcomes over the 12-week study period. RESULTS: FeNO levels but not RHQ ratings varied inversely with smoking characteristics at baseline (Ps < 0.0001) in smokers with affective disorders and socioeconomic disadvantage but less so in those with OUD. Participants with affective disorders and socioeconomic disadvantage, but not those with OUD, who were assigned to RNCCs had higher FeNO levels at Week 12 than those assigned to the 15.8 mg/g dose [F(2,423) = 4.51, p = .01, Cohen's d = 0.21]. No significant dose-related changes in RHQ scores were identified. CONCLUSIONS: Use of RNCCs across a 12-week period attenuates smoking-related reductions in FeNO levels in smokers with affective disorders and socioeconomic disadvantage although not those with OUD. FeNO changes were not accompanied by changes in respiratory-health ratings. TRIAL REGISTRATION: Inclusion and exclusion criteria for the sample and experimental manipulation of the nicotine content of assigned cigarettes are registered: NCT02232737, NCT02250664, NCT02250534. The FeNO measure reported in this manuscript is an exploratory outcome that was not registered. IMPLICATIONS: Should a reduced nicotine content standard be implemented; these results suggest that reduced nicotine content in cigarettes will not exacerbate and instead may attenuate smoking-related decreases in FeNO. This is significant as NO is an important component in maintaining a healthy respiratory system and necessary to defend against infection. Furthermore, the results of the current study demonstrate that the adoption of the reduced nicotine content standard may result in beneficial impacts on respiratory epithelial health among vulnerable populations that are disproportionally affected by the adverse health outcomes precipitated by combustible tobacco use.

Interest in Electronic Cigarettes for Smoking Cessation Among Adults With Opioid Use Disorder in Buprenorphine Treatment: A Mixed-Methods Investigation.

INTRODUCTION: Individuals in treatment for opioid use disorder (OUD) have high smoking rates and limited success with Food and Drug Administration (FDA)-approved cessation aids, suggesting need for novel approaches. Electronic cigarettes (e-cigarettes) might benefit this population, but e-cigarettes' acceptability for tobacco reduction or cessation among smokers in OUD treatment is not known. METHODS: A cross-sectional mixed-methods study of 222 adults in OUD treatment with buprenorphine in the Boston, Massachusetts metropolitan area was conducted in 2020. We used quantitative and qualitative data to investigate individuals' experience with and interest in e-cigarettes and other methods for smoking cessation and assessed factors associated with interest in e-cigarette use. RESULTS: One hundred sixty (72%) of the 222 participants were past 30-day cigarette smokers. They most frequently reported having ever used nicotine replacement therapy (NRT; 83%) and e-cigarettes (71%) for smoking cessation and most often indicated interest in using NRT (71%) and e-cigarettes (44%) for future smoking cessation. In multiple logistic regression analysis, interest in using e-cigarettes for future smoking cessation was independently associated with having ever used e-cigarettes for smoking cessation, current e-cigarette use, and perceiving e-cigarettes to be less harmful than cigarettes (ps < .05). In qualitative data, many current vapers/former smokers reported that e-cigarettes had been helpful for quitting cigarettes. For current smokers who currently or formerly vaped, frequently reported challenges in switching to e-cigarettes were concerns about replacing one addiction with another and e-cigarettes not adequately substituting for cigarettes. CONCLUSIONS: E-cigarettes had a moderate level of acceptability for smoking cessation among cigarette smokers in OUD treatment. More research is warranted to test the efficacy of this approach. IMPLICATIONS: Individuals in treatment for opioid use disorder (OUD) have high smoking rates and limited success with existing smoking cessation tools, suggesting a need for novel cessation treatment approaches. In this mixed-methods study of individuals receiving medication treatment for OUD with buprenorphine in Massachusetts in 2020, we found a moderate level of acceptability of e-cigarettes for smoking cessation.