Hospital-Initiated Smoking Cessation Among Patients Admitted with Behavioral Health Conditions.

BACKGROUND: Smoking rates among people living with behavioral health conditions (BHC) range from 30 to 65% and are 2-4 times higher than rates found in the general population. Starting tobacco treatment during a hospital stay is effective for smoking cessation, but little is known regarding treatment response among inpatients with BHC. OBJECTIVE: This study pooled data across multiple clinical trials to determine the relative success in quitting among participants with BHC compared to other study participants. PARTICIPANTS: Adults who smoke (≥ 18 years old) from five hospital-based smoking cessation randomized clinical trials. DESIGN: A retrospective analysis using data from the electronic health record to identify participants with primary diagnoses related to BHC. Recruitment and data analysis were conducted from 2011 to 2016. We used propensity score matching to pair patients with BHC to those with similar characteristics and logistic regression to determine differences between groups. MEASURES: The main outcome was self-reported 30-day abstinence 6 months post-discharge. RESULTS: Of 6612 participants, 798 patients had a BHC-related primary diagnosis. The matched sample included 642 pairs. Nearly 1 in 3 reported using tobacco medications after hospitalization, with no significant difference between patients with and without BHC (29.3% vs. 31.5%; OR (95% CI) = 0.90 (0.71, 1.14), p = 0.40). Nearly 1 in 5 patients with BHC reported abstinence at 6 months; however, their odds of abstinence were 30% lower than among people without BHC (OR (95% CI) = 0.70 (0.53,0.92), p = 0.01). CONCLUSION: When offered tobacco treatment, hospitalized patients with BHC were as likely as people without BHC to accept and engage in treatment. However, patients with BHC were less likely to report abstinence compared to those without BHC. Hospitals are a feasible and promising venue for tobacco treatment among inpatients with BHC. More studies are needed to identify treatment approaches that help people with BHC achieve long-term abstinence.

Implementation of statistical features of a Bayesian two-armed responsive adaptive randomization trial with post hoc analysis of time trend drift.

Bayesian adaptive designs with response adaptive randomization (RAR) have the potential to benefit more participants in a clinical trial. While there are many papers that describe RAR designs and results, there is a scarcity of works reporting the details of RAR implementation from a statistical point exclusively. In this paper, we introduce the statistical methodology and implementation of the trial Changing the Default (CTD). CTD is a single-center prospective RAR comparative effectiveness trial to compare opt-in to opt-out tobacco treatment approaches for hospitalized patients. The design assumed an uninformative prior, conservative initial allocation ratio, and a higher threshold for stopping for success to protect results from statistical bias. A particular emerging concern of RAR designs is the possibility that time trends will occur during the implementation of a trial. If there is a time trend and the analytic plan does not prespecify an appropriate model, this could lead to a biased trial. Adjustment for time trend was not pre-specified in CTD, but post hoc time-adjusted analysis showed no presence of influential drift. This trial was an example of a successful two-armed confirmatory trial with a Bayesian adaptive design using response adaptive randomization.

Women Physicians and Promotion in Academic Medicine.

BACKGROUND: In 2000, a landmark study showed that women who graduated from U.S. medical schools from 1979 through 1997 were less likely than their male counterparts to be promoted to upper faculty ranks in academic medical centers. It is unclear whether these differences persist. METHODS: We merged data from the Association of American Medical Colleges on all medical school graduates from 1979 through 2013 with faculty data through 2018, and we compared the percentages of women who would be expected to be promoted on the basis of the proportion of women in the graduating class with the actual percentages of women who were promoted. We calculated Kaplan-Meier curves and used adjusted Cox proportional-hazards models to examine the differences between the early cohorts (1979-1997) and the late cohorts (1998-2013). RESULTS: The sample included 559,098 graduates from 134 U.S. medical schools. In most of the cohorts, fewer women than expected were promoted to the rank of associate or full professor or appointed to the post of department chair. Findings were similar across basic science and clinical departments. In analyses that included all the cohorts, after adjustment for graduation year, race or ethnic group, and department type, women assistant professors were less likely than their male counterparts to be promoted to associate professor (hazard ratio, 0.76; 95% confidence interval [CI], 0.74 to 0.78). Similar sex disparities existed in promotions to full professor (hazard ratio, 0.77; 95% CI, 0.74 to 0.81) and appointments to department chair (hazard ratio, 0.46; 95% CI, 0.39 to 0.54). These sex differences in promotions and appointments did not diminish over time and were not smaller in the later cohorts than in the earlier cohorts. The sex differences were even larger in the later cohorts with respect to promotion to full professor. CONCLUSIONS: Over a 35-year period, women physicians in academic medical centers were less likely than men to be promoted to the rank of associate or full professor or to be appointed to department chair, and there was no apparent narrowing in the gap over time. (Funded by the University of Kansas Medical Center Joy McCann Professorship for Women in Medicine and the American Association of University Women.).

Using Bayesian hierarchical models for controlled post hoc subgroup analysis of clinical trials: application to smoking cessation treatment in American Indians and Alaska Natives.

Clinical trials powered to detect subgroup effects provide the most reliable data on heterogeneity of treatment effect among different subpopulations. However, pre-specified subgroup analysis is not always practical and post hoc analysis results should be examined cautiously. Bayesian hierarchical modelling provides grounds for defining a controlled post hoc analysis plan that is developed after seeing outcome data for the population but before unblinding the outcome by subgroup. Using simulation based on the results from a tobacco cessation clinical trial conducted among the general population, we defined an analysis plan to assess treatment effect among American Indians and Alaska Natives (AI/AN) enrolled in the study. Patients were randomized into two arms using Bayesian adaptive design. For the opt-in arm, clinicians offered a cessation treatment plan after verifying that a patient was ready to quit. For the opt-out arm, clinicians provided all participants with free cessation medications and referred them to a Quitline. The study was powered to test a hypothesis of significantly higher quit rates for the opt-out arm at one-month post randomization. Overall, one-month abstinence rates were 15.9% and 21.5% (opt-in and opt-out arm, respectively). For AI/AN, one-month abstinence rates were 10.2% and 22.0% (opt-in and opt-out arm, respectively). The posterior probability that the abstinence rate in the treatment arm is higher is 0.96, indicating that AI/AN demonstrate response to treatment at almost the same probability as the whole population.

Leveraging National Data and Regional Innovations to Right-Size Tobacco Treatment Policy for Behavioral Health in a Midwestern State.

BACKGROUND: People with mental health (MH) and substance use disorders (SUD) have high rates of tobacco use and tobacco-related mortality. They want to stop smoking and studies have shown they can quit, but few behavioral health facilities provide tobacco treatment. The purpose of this paper is to describe how a midwestern statewide behavioral health collaboration used regional data to pinpoint strengths and weaknesses in tobacco treatment trends, identified policies in neighboring states that were associated with high rates of tobacco treatment, and worked with state leaders to implement these policies to enhance treatment. METHODS: We used publicly available data from 2 SAMHSA annual national surveys of MH/SUD facilities to describe tobacco treatment services and policies in behavioral health facilities in Kansas and 3 neighboring states (Missouri, Nebraska and Oklahoma). We interviewed neighboring state leaders to identify policies they had implemented to boost tobacco recovery services in behavioral health. We collaborated with our state behavioral health agency to encourage adoption of similar policies. RESULTS: Using 7 years of survey data (2014-2020), rates for screening, counseling, and medications for tobacco dependence were highest in Oklahoma and Missouri facilities. Oklahoma had the highest percentages of facilities reporting smoke-free campuses. In all states, rates of tobacco service provision and smoke-free campuses were lower among SUD facilities than in MH facilities. State leaders associated several policies with high performance, including (a) requiring programs contracting with the state to conduct screening, provide counseling, and adopt smoke-free campuses (Oklahoma and Missouri); (b) state-based collection of tobacco treatment service provision data (Oklahoma); (c) providing facilities with free NRT for clients (Oklahoma); (d) setting benchmarks for service provision (Oklahoma); (e) comprehensive Medicaid coverage of cessation medications (Missouri). Upon review of these findings, Kansas behavioral health officials adopted a 2-year process to implement similar policies and are integrating tobacco treatment requirements into the state Certified Community Behavioral Health Clinic program. CONCLUSIONS: Summarizing and sharing freely-available data across states laid the groundwork for cross-border networking and policy change. State and federal agencies should integrate these policies into contracts and block grants to reduce tobacco-related disparities among individuals with behavioral health conditions.

Vaping, Perceptions of Vaping, and Plans to Quit Among E-cigarette Users in the United States and the United Kingdom.

INTRODUCTION: Government and health organizations in the United States and the United Kingdom have taken different stances on e-cigarettes policy. To explore the potential effects of these policies, we describe e-cigarette user characteristics, intentions to quit, and perceived attitudes toward vaping. METHODS: We used the online crowdsourcing platform Prolific to conduct a cross-sectional survey of current vapers in both countries. Measures were drawn from international surveys. RESULTS: The sample included 1044 vapers (524 United Kingdom; 520 United States) with a mean age of 34. Samples differed by gender (United States: 57% male vs 45% in United Kingdom), race (United States: 79% White vs 90% in United Kingdom) and employment (United States: 73% employed vs 79% in United Kingdom). UK respondents were more likely than US respondents to be ever smokers (89% vs 71%, p < .0001); be daily vapers (69% vs 53%, p < .0001) and to use e-cigarettes to quit smoking (75% vs 65%, p < .0007). Most vapers in the United Kingdom and the United States want to stop vaping (62% vs 61%; p < .9493), but US respondents plan to quit significantly sooner (odds ratio 0.47, p < .0004). Attitudes differed as well. Over half (56%) of UK respondents reported their government-approved e-cigarette use, and 24% felt health care providers had positive views on e-cigarettes versus 29% and 13% from the United States, respectively (p < .0004 for both). CONCLUSIONS: Plans for quitting and perceptions regarding e-cigarettes differ markedly between demographically similar groups of vapers in the two countries. Future research should determine whether e-cigarette cessation for adults should be a public health goal, and if so, identify effective ways to stop. IMPLICATIONS: The contribution of this study is that it describes differences in behaviors and attitudes of vapers recruited through the same research platform and adjusted to account for minor demographic differences across country samples. For clinicians, these findings suggest that most vapers would welcome assistance in quitting. For researchers and policymakers, findings suggest that government policy regarding nicotine devices might influence behaviors and attitudes related to use and also that future research is needed to determine effective ways to quit.

Effectiveness of Recruitment Strategies of Latino Smokers: Secondary Analysis of a Mobile Health Smoking Cessation Randomized Clinical Trial.

BACKGROUND: Latinos remain disproportionately underrepresented in clinical trials, comprising only 2%-3% of research participants. In order to address health disparities, it is critically important to increase enrollment of Latino smokers in smoking cessation trials. There is limited research examining effective recruitment strategies for this population. OBJECTIVE: The purpose of this study was to compare the effectiveness of direct versus mass and high- versus low-effort recruitment strategies on recruitment and retention of Latino smokers to a randomized smoking cessation trial. We also examine how the type of recruitment might have influenced the characteristics of enrolled participants. METHODS: Latino smokers were enrolled into Decídetexto from 4 states-New Jersey, Kansas, Missouri, and New York. Participants were recruited from August 2018 until March 2021. Mass recruitment strategies included English and Spanish advertisements to the Latino community via flyers, Facebook ads, newspapers, television, radio, church bulletins, and our Decídetexto website. Direct, high-effort strategies included referrals from clinics or community-based organizations with whom we partnered, in-person community outreach, and patient registry calls. Direct, low-effort strategies included texting or emailing pre-existing lists of patients who smoked. A team of trained bilingual (English and Spanish) recruiters from 9 different Spanish-speaking countries of origin conducted recruitment, assessed eligibility, and enrolled participants into the trial. RESULTS: Of 1112 individuals who were screened, 895 (80.5%) met eligibility criteria, and 457 (457/895, 51.1%) enrolled in the trial. Within the pool of screened individuals, those recruited by low-effort recruitment strategies (both mass and direct) were significantly more likely to be eligible (odds ratio [OR] 1.67, 95% CI 1.01-2.76 and OR 1.70, 95% CI 0.98-2.96, respectively) and enrolled in the trial (OR 2.60, 95% CI 1.81-3.73 and OR 3.02, 95% CI 2.03-4.51, respectively) compared with those enrolled by direct, high-effort strategies. Among participants enrolled, the retention rates at 3 months and 6 months among participants recruited via low-effort strategies (both mass and direct) were similar to participants recruited via direct, high-effort methods. Compared with enrolled participants recruited via direct (high- and low-effort) strategies, participants recruited via mass strategies were less likely to have health insurance (44.0% vs 71.2% and 71.7%, respectively; P<.001), lived fewer years in the United States (22.4 years vs 32.4 years and 30.3 years, respectively; P<.001), more likely to be 1st generation (92.7% vs 76.5% and 77.5%, respectively; P=.007), more likely to primarily speak Spanish (89.3% vs 65.8% and 66.3%, respectively), and more likely to be at high risk for alcohol abuse (5.8 mean score vs 3.8 mean score and 3.9 mean score, respectively; P<.001). CONCLUSIONS: Although most participants were recruited via direct, high-effort strategies, direct low-effort recruitment strategies yielded a screening pool more likely to be eligible for the trial. Mass recruitment strategies were associated with fewer acculturated enrollees with lower access to health services-groups who might benefit a great deal from the intervention. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT03586596; https://clinicaltrials.gov/ct2/show/NCT03586596. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-DOI: 10.1016/j.cct.2020.106188.

Use of pre-enrollment randomization and delayed consent to maximize participation in a clinical trial of opt-in versus opt-out tobacco treatment.

Background: Enrollment in smoking cessation trials remain sub-optimal. The aim of this analysis was to determine the effectiveness of a modified Zelen's design in engaging hospitalized patients who smoke in a pragmatic OPT-IN versus OPT-OUT tobacco treatment trial. Methods: At bedside, clinical staff screened smokers for eligibility, randomized eligible into study arms, and delivered the appropriate treatment approach. Study staff called randomized patients at one-month post-discharge, debriefed patients on the study design, and collected consent to participate. We used frequencies and percentages for categorical variables and means and standard deviations for quantitative variables to describe the characteristics of those who consented and were enrolled versus those who did not enroll. We also compared the characteristics of participants who consented and those who were reached and explicitly refused consent at one-month follow-up. We used the Cohen's d measure of effect size to evaluate differences. Results: Of the 1,000 randomized, 741 (74.1%) consented to continue in the study at one-month follow-up. One hundred and twenty-seven (12.7%) refused consent and 132 (13.2%) were unreachable. Cohen's d effect size differences between those who consented/enrolled (n = 741) and those who were not enrolled (n = 259) were negligible (<0.2) for age, gender, race/ethnicity, and most forms of insurance. The effect size was small for Medicaid (0.36), and other public insurance (0.48). After excluding those unreached at 1 month (12.7%), there were medium Cohen's d effect size differences between those who consented to participate (n = 741) and those who explicitly refused (n = 127) with respect to age (0.55) and self-pay or no insurance (0.51). There were small to negligible effect size differences with respect to sex, race/ethnicity, and other forms of health insurance. Conclusions: The modified Zelen's design resulted in successful enrollment of most participants who were initially randomized into the trial, including those not motivated to quit.

Stress, Depression and Quit Attempt Outcomes among Unmotivated Smokers.

INTRODUCTION: Stress and depressive symptoms have been linked to a reduced likelihood of sustaining smoking cessation. Because stress and depressive symptoms may negatively affect motivation to quit, stress and depression may also be important for whether or not smokers make a quit attempt. OBJECTIVE: To examine the relationship between perceived stress and depressive symptoms and initiating a quit attempt in a smoking cessation induction trial. METHODS: We conducted a secondary analysis of existing data from a randomized clinical trial (N = 255) comparing motivational interviewing to health education and brief advice for smoking cessation induction in smokers with low motivation to quit. RESULTS: We observed positive associations between baseline predictors and quit attempts at week 12 (r = 0.192, p < 0.01 for depressive symptoms and r = 0.136, p < 0.05 for perceived stress). Logistic regression models revealed similar significant positive associations between baseline perceived stress and baseline depressive symptoms and making a quit attempt by week 12 (OR = 1.5, CI:1.03, 2.19 and OR = 1.03, 95% CI: 1.01, 1.06; respectively). CONCLUSION: Unexpectedly, this study found generally small but consistently positive associations between baseline depressive symptoms and baseline perceived stress and making a quit attempt by week 12. The results can be viewed as encouraging in that interventions to encourage quit attempts do not appear counter-productive for individuals higher in stress and depressive symptoms, but these patients very likely will need additional supports to sustain abstinence.

Impact of Smoking Cessation Interventions Initiated During Hospitalization Among HIV-Infected Smokers.

INTRODUCTION: Smoking is a key determinant of mortality among people living with HIV (PLWH). METHODS: To better understand the effects of smoking cessation interventions in PLWH, we conducted a pooled analysis of four randomized controlled trials of hospital-initiated smoking interventions conducted through the Consortium of Hospitals Advancing Research on Tobacco (CHART). In each study, cigarette smokers were randomly assigned to usual care or a smoking cessation intervention. The primary outcome was self-reported past 30-day tobacco abstinence at 6-month follow-up. Abstinence rates were compared between PLWH and participants without HIV and by treatment arm, using both complete-case and intention-to-treat analyses. Multivariable logistic regression was used to determine the effect of HIV status on 6-month tobacco abstinence and to determine predictors of smoking cessation within PLWH. RESULTS: Among 5550 hospitalized smokers, there were 202 (3.6%) PLWH. PLWH smoked fewer cigarettes per day and were less likely to be planning to quit than smokers without HIV. At 6 months, cessation rates did not differ between intervention and control groups among PLWH (28.9% vs. 30.5%) or smokers without HIV (36.1% vs. 34.1%). In multivariable regression analysis, HIV status was not significantly associated with smoking cessation at 6 months. Among PLWH, confidence in quitting was the only clinical factor independently associated with smoking cessation (OR 2.0, 95% CI = 1.4 to 2.8, p < .01). CONCLUSIONS: HIV status did not alter likelihood of quitting smoking after hospital discharge, whether or not the smoker was offered a tobacco cessation intervention, but power was limited to identify potentially important differences. IMPLICATIONS: PLWH had similar quit rates to participants without HIV following a hospital-initiated smoking cessation intervention. The findings suggest that factors specific to HIV infection may not influence response to smoking cessation interventions and that all PLWH would benefit from efforts to assist in quitting smoking. TRIAL REGISTRATION: (1) Using "warm handoffs" to link hospitalized smokers with tobacco treatment after discharge: study protocol of a randomized controlled trial: NCT01305928. (2) Web-based smoking cessation intervention that transitions from inpatient to outpatient: NCT01277250. (3) Effectiveness of smoking-cessation interventions for urban hospital patients: NCT01363245. (4) Effectiveness of Post-Discharge Strategies for Hospitalized Smokers (HelpingHAND2): NCT01714323.

Effectiveness of Mindfulness-Based Relapse Prevention Program as an Adjunct to the Standard Treatment for Smoking: A Pragmatic Design Pilot Study.

INTRODUCTION: Posttreatment relapse is a major roadblock to stemming the global epidemic of tobacco-related illness. This article presents results from a pilot trial evaluating the feasibility and initial efficacy of Mindfulness-Based Relapse Prevention (MBRP) as an adjunct to standard relapse prevention treatment (ST) for smoking cessation. AIMS AND METHODS: Smokers (n = 86) in the maintenance phase of treatment were randomized to receive either ST plus MBRP (MBRP) (n = 44) or ST alone (ST) (n = 42). Data were collected at baseline and at 4-, 12-, and 24-week follow-up points. We evaluated the feasibility of the protocol with frequency analysis, and the efficacy with both intention to treat and complete case analyses of the effects of MBRP on abstinence. Secondary outcomes included mindfulness, craving, depression, anxiety, and positive/negative affect. RESULTS: High adherence suggested MBRP is acceptable and feasible. Participants in the MBRP group reported increases in mindfulness (M = -7.833, p = .016), and reductions in craving (M = 17.583, p = .01) compared with the ST group. Intention to treat analysis found that, compared with MBRP (36.4%), ST (57.1%) showed trend-level superiority in abstinence at Week 4 (Prevalence Ratio = 0.63, p = .06); however at Week 24, the ST group (14.3%) demonstrated a twofold greater decrease in abstinence, compared with the MBRP group (20.1%) (Prevalence Ratio = 2.25, p = .08). Therefore, the MBRP group maintained a higher abstinence rate for longer. Reported effects were greater in the complete case analysis. CONCLUSIONS: MBRP holds promise for preventing relapse after aided tobacco quit attempts. IMPLICATIONS: Findings suggest that MBRP is acceptable, feasible, and valued by participants. At 24-week follow-up, there was a large effect size and a statistical trend toward fewer MBRP patients relapsing compared with ST patients. MBRP conferred ancillary benefits including reductions in craving and increases in levels of mindfulness. MBRP for tobacco cessation is highly promising and merits further research. TRIAL REGISTRATION: clinicaltrials.gov. IDENTIFIER: NCT02327104.

Insurance coverage and utilization of nicotine patches after receipt of a prescription.

Introduction: Changes in reimbursement policy have made nicotine replacement therapy (NRT) much more available, but little is known about what happens to patients after they receive their prescription. This study describes rates of successfully filling prescriptions for NRT and its association with type of insurance. Methods: We identified 224 patients who received a prescription for NRT during an outpatient visit to an academic medical center between January 1st 2016 and February 10th 2017. We conducted telephone surveys to assess whether they tried to fill their prescriptions and if so, determine the effects of insurance type on the ability to successfully fill the prescription. Results: Of 117 patients completing the survey, 23 (19.6%) did not attempt to fill and 6 (5.1%) had no insurance. Of the 90 patients with insurance who attempted to fill their prescription, 67 (74.4%) were successful and 23 (25.6%) were unsuccessful in obtaining medications. Success varied by insurance with successful fills ranging from 34 (87.2%) of those with commercial insurance, 24 (70.6%) with Medicaid, to 9 (52.9%) with Medicare. Of 37 participants living with another smoker, 31 (83.7%) wanted an NRT prescription specifically for their partner; several volunteered that they had shared patches with their partner. Conclusions: Despite widespread coverage for NRT, many patients may still encounter difficulties in getting their prescriptions filled. Some tobacco users might also benefit from getting NRT prescriptions for their partners that smoke.

Impact of Adding Telephone-Based Care Coordination to Standard Telephone-Based Smoking Cessation Counseling Post-hospital Discharge: a Randomized Controlled Trial.

BACKGROUND: Cessation counseling and pharmacotherapy are recommended for hospitalized smokers, but better coordination between cessation counselors and providers might improve utilization of pharmacotherapy and enhance smoking cessation. OBJECTIVE: To compare smoking cessation counseling combined with care coordination post-hospitalization to counseling alone on uptake of pharmacotherapy and smoking cessation. DESIGN: Unblinded, randomized clinical trial PARTICIPANTS: Hospitalized smokers referred from primarily rural hospitals INTERVENTIONS: Counseling only (C) consisted of telephone counseling provided during the hospitalization and post-discharge. Counseling with care coordination (CCC) provided similar counseling supplemented by feedback to the smoker's health care team and help for the smoker in obtaining pharmacotherapy. At 6 months post-hospitalization, persistent smokers were re-engaged with either CCC or C. MAIN MEASURES: Utilization of pharmacotherapy and smoking cessation at 3, 6, and 12 months post-discharge. KEY RESULTS: Among 606 smokers randomized, 429 (70.8%) completed the 12-month assessment and 580 (95.7%) were included in the primary analysis. Use of any cessation pharmacotherapy between 0 and 6 months (55.2%) and between 6 and 12 months (47.1%) post-discharge was similar across treatment arms though use of prescription-only pharmacotherapy between months 6-12 was significantly higher in the CCC group (30.1%) compared with the C group (18.6%) (RR, 1.61 (95% CI, 1.08, 2.41)). Self-reported abstinence rates of 26.2%, 20.3%, and 23.4% at months 3, 6, and 12, respectively, were comparable across the two treatment arms. Of those smoking at month 6, 12.5% reported abstinence at month 12. Validated smoking cessation at 12 months was 19.3% versus 16.9% in the CCC and C groups, respectively (RR, 1.13 (95% CI, 0.80, 1.61)). CONCLUSION: Supplemental care coordination, provided by counselors outside of the health care team, failed to improve smoking cessation beyond that achieved by cessation counseling alone. Re-engagement of smokers 6 months post-discharge can lead to new quitters, at which time care coordination might facilitate use of prescription medications. TRIAL REGISTRATION: NCT01063972.

An Experimental Feasibility Study of a Hybrid Telephone Counseling/Text Messaging Intervention for Post-Discharge Cessation Support Among Hospitalized Smokers in Brazil.

OBJECTIVE: Text messaging interventions are effective. Despite high utilization of smartphones, few studies evaluate text messaging for cessation in middle-/lower-income countries. Initiating tobacco treatment in hospitals is an effective but underutilized approach for reaching smokers. We evaluated a hybrid phone counseling/text messaging intervention for supporting cessation among hospitalized smokers in Brazil. METHODS: We used an experimental design to assess the feasibility and potential effect size of the intervention. Participants (N = 66) were recruited from a university hospital and randomized in a 2:1 ratio into TXT (one session of telephone counseling plus 2 weeks of text messaging; N = 44) or Standard Care control group (N = 22). Participants lost to follow-up were counted as smokers. RESULTS: Counselors sent 1186 texts, of which 924 (77.9%) were received by study participants. Participants rated the TXT content as "helpful" (80.4%) and the phone counseling length to be "just right" (95.1%). Although the study was not powered to evaluate abstinence rates, we did observe a higher prevalence of abstinence in the TXT compared to control group at both 1-month follow-up (25.0% vs. 9.1%) and 3-month follow-up (31.8% vs. 9.1%). Carbon monoxide-verified abstinence at month 3 was also higher in TXT (20.5% vs. 4.5%). CONCLUSIONS: This hybrid telephone/text intervention should progress to full-scale effectiveness testing as it achieved favorable outcomes, was acceptable to participants, and was readily implemented. This type of intervention has strong potential for expanding the reach of hospital-initiated tobacco treatment in middle-/lower-income countries. IMPLICATIONS: This study extends research on hospital-initiated smoking cessation by establishing the feasibility of a novel text-messaging approach for post-discharge follow-up. Text messaging is a low-cost alternative to proactive telephone counseling that could help overcome resource barriers in middle- and lower-income countries. This hybrid texting/counseling intervention identified smokers in hospitals, established rapport through a single telephone follow-up, and expanded acceptability and reach of later support by using text-messaging, which is free of charge in this and other low-income countries. The favorable cessation outcomes achieved by the hybrid intervention provide support for a fully powered effectiveness trial.

Predictors of engagement in post-discharge quitline counseling among hospitalized smokers.

Quitlines provide evidence-based tobacco treatment and multiple calls yield higher quit rates. This study aimed to identify subgroups of smokers with greater quitline engagement following referral during hospitalization. Data were from a randomized clinical trial assessing the effectiveness of fax referral (referral faxed to proactive quitline) versus warm handoff (patient connected to quitline at bedside) (n = 1054). Classification and regression trees analyses evaluated individual and treatment/health system-related variables and their interactions. Among all participants, warm handoff, higher ratings of the tobacco treatment care transition, and being older predicted completing more quitline calls. Among patients enrolled in the quitline, higher transition of care ratings, being older, and use of cessation medication post-discharge predicted completing more calls. Three of the four factors influencing engagement were characteristics of treatment within the hospital (quality of tobacco treatment care transition and referral method) and therapy (use of cessation medications), suggesting potential targets to increase quitline engagement post-discharge.

Critical steps in the path to using cessation pharmacotherapy following hospital-initiated tobacco treatment.

BACKGROUND: Hospital-initiated smoking cessation interventions utilizing pharmacotherapy increase post-discharge quit rates. Use of smoking cessation medications following discharge may further increase quit rates. This study aims to identify individual, smoking-related and hospitalization-related predictors of engagement in three different steps in the smoking cessation pharmacotherapy utilization process: 1) receiving medications as inpatient, 2) being discharged with a prescription and 3) using medications at 1-month post-hospitalization, while accounting for associations between these steps. METHODS: Study data come from a clinical trial (N = 1054) of hospitalized smokers interested in quitting who were randomized to recieve referral to a quitline via either warm handoff or fax. Variables were from the electronic health record, the state tobacco quitline, and participant self-report. Relationships among the predictors and the steps in cessation medication utilization were assessed using bivariate analyses and multivariable path analysis. RESULTS: Twenty-eight percent of patients reported using medication at 1-month post-discharge. Receipt of smoking cessation medications while hospitalized (OR = 2.09, 95%CI [1.39, 3.15], p < .001) and discharge with a script (OR = 4.88, 95%CI [3.34, 7.13], p < .001) were independently associated with medication use at 1-month post-hospitalization. The path analysis also revealed that the likelihood of being discharged with a script was strongly influenced by receipt of medication as an inpatient (OR = 6.61, 95%CI [4.66, 9.38], p < .001). A number of other treatment- and individual-level factors were associated with medication use in the hospital, receipt of a script, and use post-discharge. CONCLUSIONS: To encourage post-discharge smoking cessation medication use, concerted effort should be made to engage smokers in tobacco treatment while in hospital. The individual and hospital-level factors associated with each step in the medication utilization process provide good potential targets for future implementation research to optimize treatment delivery and outcomes. TRIAL REGISTRATION: Number: NCT01305928 . Date registered: February 24, 2011.

Which hospitalized smokers receive a prescription for quit-smoking medication at discharge? A secondary analysis of a smoking cessation randomized clinical trial.

OBJECTIVE: To determine the prevalence and predictors of receiving a smoking cessation medication prescription at discharge. METHODS: Retrospective analysis of ongoing Human Studies Committee-approved clinical trial data at large tertiary care center, The University of Kansas Medical Center. Patients included were smokers over 18, either Spanish or English speaking, those admitted between October 1, 2016 through May 31, 2018. Other eligibility criteria include access to a telephone or mobile phone, not currently be pregnant or breastfeeding, have no significant co-morbidity that precludes participation (acute, life-threatening illness, and communication barriers such as tracheal tube or altered mental status). Those included in this analysis were those randomized into the trial who expressed interest in receiving a smoking cessation medication prescription at discharge. RESULTS: Two hundred fourteen patients were recommended a prescription by their smoking cessation counselor, 88 patients (41.12%) were approved a prescription at discharge. Out of those approved, 50.70 (14.05 SD) was the average age, 12.84 (8.47 SD) was the average number of cigarettes used per day, 47 patients (53.41%) were White, 49 patients (55.68%) were admitted through the emergency department, 55 patients (62.50%) had used smoking cessation medication in the past, 49 patients (55.68%) had used inpatient smoking cessation, 36 patients (40.91%) had Medicaid. A binary logistic regression determined to show insurance status (P = 0.042) and use of inpatient smoking cessation medication use (P < 0.001) as statistically significant predictors of receiving a prescription at discharge. CONCLUSION: It was determined that among the population recommended for medication, 41.12% actually received a prescription at discharge. The variables of "health insurance status" and "use of inpatient smoking cessation medication" demonstrated to be predictors of receiving a prescription. It is important to further study this as many patients rely on a prescription to afford these medications that are useful in a quit attempt.

Pilot Study of a Tailored Smoking Cessation Intervention for Individuals in Treatment for Opioid Dependence.

Introduction: Over 85% of opioid-dependent individuals in methadone treatment smoke cigarettes; however, smoking cessation interventions are minimally effective in this population. To better help opioid-dependent individuals quit smoking, we developed and pilot-tested an intervention, based in the Information-Motivation-Behavioral Skills (IMB) model of behavior change, which could be tailored to address individual barriers to smoking cessation in this population. Methods: We randomized participants (n = 83) in methadone treatment to the eight-session, IMB model-based, intervention plus nicotine replacement therapy (intervention, n = 41) or a facilitated referral to the state Quitline (control, n = 42). All participants completed assessments at baseline, 3 months, and 6 months. Results: Intervention participants completed a median of five sessions (interquartile range [IQR] 3-8) and had significantly higher intervention satisfaction than control participants. Intervention participants reported smoking significantly fewer cigarettes per day at 3 months (median [IQR] = 6 [4-15]) and 6 months (median [IQR] = 8 [4-14]) as compared control participants at 3 months (median [IQR] = 10 [5-20]) and 6 months (median [IQR] = 10 [6-20]). Fifty-six percent of the intervention group and 41% of the control group a made a quit attempt during the study (p = .16). At 3 months, 7% (n = 3) of intervention participants and none of the control participants were abstinent from smoking (p = .23). At 6 months, 2% of participants in both groups were abstinent. Twenty-four percent and 10% of the intervention and control group participants, respectively, reported 20 or more smoke-free days (p = .43). Conclusions: An IMB model-based smoking cessation intervention for opioid-dependent smokers is feasible and acceptable in methadone treatment and may help methadone maintained smokers cut down on their smoking. Implications: This is the first study of a tailored, IMB Model-based, smoking cessation intervention for opioid dependent smokers. Results showed that opioid dependent smokers are willing and able to participate in an IMB model-based smoking cessation intervention, and this intervention may help this population cut down on their smoking. Also, the Quitline seems less feasible and acceptable for this population than a face-to-face intervention. Further research is needed to determine how to integrate smoking cessation treatment into methadone programs and how to improve interventions so that treatment gains can lead to long-term abstinence in this population.

Enhancing partner support to improve smoking cessation.

BACKGROUND: While many cessation programmes are available to assist smokers in quitting, research suggests that support from individual partners, family members, or 'buddies' may encourage abstinence. OBJECTIVES: To determine if an intervention to enhance one-to-one partner support for smokers attempting to quit improves smoking cessation outcomes, compared with cessation interventions lacking a partner-support component. SEARCH METHODS: We limited the search to the Cochrane Tobacco Addiction Group Specialised Register, which was updated in April 2018. This includes the results of searches of the Cochrane Central Register of Controlled Trials (CENTRAL); MEDLINE (via OVID); Embase (via OVID); and PsycINFO (via OVID). The search terms used were smoking (prevention, control, therapy), smoking cessation and support (family, marriage, spouse, partner, sexual partner, buddy, friend, cohabitant and co-worker). We also reviewed the bibliographies of all included articles for additional trials. SELECTION CRITERIA: We included randomised controlled trials recruiting people who smoked. Trials were eligible if they had at least one treatment arm that included a smoking cessation intervention with a partner-support component, compared to a control condition providing behavioural support of similar intensity, without a partner-support component. Trials were also required to report smoking cessation at six months follow-up or more. DATA COLLECTION AND ANALYSIS: Two review authors independently identified the included studies from the search results, and extracted data using a structured form. A third review author helped resolve discrepancies, in line with standard methodological procedures expected by Cochrane. Smoking abstinence, biochemically verified where possible, was the primary outcome measure and was extracted at two post-treatment intervals where possible: at six to nine months and at 12 months or longer. We used a random-effects model to pool risk ratios from each study and estimate a summary effect. MAIN RESULTS: Our update search identified 465 citations, which we assessed for eligibility. Three new studies met the criteria for inclusion, giving a total of 14 included studies (n = 3370). The definition of partner varied among the studies. We compared partner support versus control interventions at six- to nine-month follow-up and at 12 or more months follow-up. We also examined outcomes among three subgroups: interventions targeting relatives, friends or coworkers; interventions targeting spouses or cohabiting partners; and interventions targeting fellow cessation programme participants. All studies gave self-reported smoking cessation rates, with limited biochemical verification of abstinence. The pooled risk ratio (RR) for abstinence was 0.97 (95% confidence interval (CI) 0.83 to 1.14; 12 studies; 2818 participants) at six to nine months, and 1.04 (95% CI 0.88 to 1.22; 7 studies; 2573 participants) at 12 months or more post-treatment. Of the 11 studies that measured partner support at follow-up, only two reported a significant increase in partner support in the intervention groups. One of these studies reported a significant increase in partner support in the intervention group, but smokers' reports of partner support received did not differ significantly. We judged one of the included studies to be at high risk of selection bias, but a sensitivity analysis suggests that this did not have an impact on the results. There were also potential issues with detection bias due to a lack of validation of abstinence in five of the 14 studies; however, this is not apparent in the statistically homogeneous results across studies. Using the GRADE system we rated the overall quality of the evidence for the two primary outcomes as low. We downgraded due to the risk of bias, as we judged studies with a high weighting in analyses to be at a high risk of detection bias. In addition, a study in both analyses was insufficiently randomised. We also downgraded the quality of the evidence for indirectness, as very few studies provided any evidence that the interventions tested actually increased the amount of partner support received by participants in the relevant intervention group. AUTHORS' CONCLUSIONS: Interventions that aim to enhance partner support appear to have no impact on increasing long-term abstinence from smoking. However, most interventions that assessed partner support showed no evidence that the interventions actually achieved their aim and increased support from partners for smoking cessation. Future research should therefore focus on developing behavioural interventions that actually increase partner support, and test this in small-scale studies, before large trials assessing the impact on smoking cessation can be justified.