Attempts to quit smoking and relapse: Factors associated with success or failure from the ATTEMPT cohort study

Zhou, Xiaolei; Nonnemaker, James; Sherrill, Beth; Gilsenan, Alicia; Coste, F; West, Robert

doi:10.1016/j.addbeh.2008.11.013

Cited by 442 publications

(438 citation statements)

References 12 publications

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“…The reduction in abstinence predicted by depressive symptoms is in line with previous research [12][13][14]17]. There was no evidence of differential effects by gender as found in previous studies [16,17].…”

Section: Discussionsupporting

confidence: 91%

“…A recent review and meta-analysis found that past major depression was associated with a statistically significant, but modest, decrease in both short-and long-term abstinence rates [13]. Having experienced depression and pre-cessation depressed mood have also been found to be associated with increased relapse [14,15]. In older smokers (not all of whom were attempting to quit), level of depression predicted continued smoking [11], and there is evidence across all ages that the negative effect of depression on cessation is stronger for women [16,17].…”

Section: Introductionmentioning

confidence: 99%

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Depression and Smoking Cessation: Evidence from a Smoking Cessation Clinic with 1-Year Follow-Up

et al. 2016

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Background Smoking is more prevalent among people with depression. Depression may make cessation more difficult and cessation may affect depression symptoms. Purpose The aims of this study were to assess the associations between (1) baseline depression and 1-year smoking abstinence and (2) abstinence and change in depression. Methods Observational study using data collected routinely in a smoking cessation clinic in the Czech Republic from 2008 to 2014. Aim 1: N = 3775 patients; 14.3% reported mild and 15.4% moderate/severe baseline depression levels measured using Beck's Depression Inventory (BDI-II). Logistic regressions assessed if depression level predicted 1-year biochemically verified abstinence while adjusting for patient and treatment characteristics. Aim 2: N = 835 patients abstinent at 1 year; change in depression was analysed using Chi-square statistics, t test and mixed method analyses of variance. Results Rate of abstinence was lower for patients with mild (32.5%, OR = 0.68; 95% CI: 0.54 to 0.87, p = 0.002) and moderate/severe depression (25.8%; OR = 0.57, 95% CI: 0.45 to 0.74, p < 0.001) compared with patients without depression (40.5%).Across abstinent patients, the majority with baseline depression reported lower depression levels at follow-up. Overall mean (SD) BDI-II scores improved from 9.2 (8.6) to 5.3 (6.1); t(834) = 14.6, p < 0.001. There were significant main effects of time (F(1832) = 880.8, p < 0.001, partial η 2 = 0.51) and baseline depression level (F(2832) = 666.4, p < 0.001, partial η 2 = 0.62) on follow-up depression and a significant depression * time interaction (F(2832) = 296.5, p < 0.001, partial η 2 = 0.42). Conclusions In this effective smoking cessation clinic, depression at the start of treatment predicted reduced smoking abstinence 1 year later. Patients abstinent from smoking experienced considerable improvement in depression.

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Section: Discussionsupporting

confidence: 91%

Section: Introductionmentioning

confidence: 99%

Depression and Smoking Cessation: Evidence from a Smoking Cessation Clinic with 1-Year Follow-Up

et al. 2016

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“…Evidence suggests that older age and markers of lower cigarette dependence are predictive of success 2, 3, 4, 5, 6, although not all studies show these results 7. There is less consistent, conflicting or negative evidence on the effects of age of smoking onset 2, 3, substance use disorder 8, psychiatric disorder 6, 9, gender 4, 6, 10, geographical location 11, 12, body mass index (BMI) 2, 3, 10, 13, 14 and prior use of smoking cessation treatments 15.…”

Section: Introductionmentioning

confidence: 98%

Factors associated with the efficacy of smoking cessation treatments and predictors of smoking abstinence in EAGLES

et al. 2018

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AimsTo assess (1) how far the efficacies of front‐line smoking cessation pharmacotherapies vary as a function of smoker characteristics and (2) associations between these characteristics and success of smoking cessation attempts.DesignProspective correlational study in the context of a double‐blind randomized trial. The outcome was regressed individually onto each covariate after adjusting for treatment, and then a forward stepwise model constructed. Treatment moderator effects of covariates were tested by treatment × covariate interactions.SettingHealth service facilities in multiple countries.ParticipantsData came from 8120 smokers willing to make a quit attempt, randomized to varenicline, bupropion, nicotine replacement therapy (NRT) or placebo in Evaluating Adverse Events in a Global Smoking Cessation Study (EAGLES) between 30 November 2011 and 13 January 2015.MeasurementsSmoker characteristics measured at baseline were country, psychiatric history, sex, age, body mass index (BMI), ethnic group, life‐time suicidal ideation/behaviour, anxiety, depression, aggression, psychotropic medication, history of alcohol/substance use disorder, age of starting smoking, cigarette dependence [Fagerström Test for Cigarette Dependence (FTCD)] and prior use of study medicines. Outcome was biochemically confirmed continuous abstinence at weeks 9–24 from start of treatment.FindingsNo statistically significant treatment × covariate interactions were found. Odds of success were associated independently positively with age [odds ratio (OR) = 1.01; 95% confidence interval (CI) = 1.00, 1.01], BMI (1.01; 95% CI = 1.00, 1.02) and age of starting smoking (1.03; 95% CI = 1.02, 1.04). Odds were associated independently negatively with US (versus non‐US) study site (0.53; 95% CI = 0.46, 0.61), black (versus white) ethnic group (0.57; 95% CI = 0.45, 0.72), mood disorder (0.85; 95% CI = 0.73, 0.99), anxiety disorder (0.71; 95% CI = 0.55, 0.90) and psychotic disorder (0.73; 95% CI = 0.50, 1.07), taking psychotropic medication (0.81; 95% CI = 0.68, 0.95), FTCD (0.89; 95% CI = 0.87, 0.92) and previous use of NRT (0.78; 95% CI = 0.67, 0.91).ConclusionsWhile a range of smoker characteristics—including psychiatric history, cigarette dependence and prior use of nicotine replacement therapy (NRT)—are associated with lower cessation rates, they do not substantially influence the efficacy of varenicline, bupropion or NRT.

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“…We also posit that this focus on acceptance may be especially helpful for heavy smokers and those with mental health symptoms because physical, emotional, and cognitive cues to smoke are stronger for these individuals (Cui et al, 2012;Kushnir et al, 2013;Loeber et al, 2011;Weinberger, McKee, & George, 2012). Overall, exploration of comparative treatment effects in these subgroups can aid in the critical effort to improve quit rates for high-risk groups and thereby reduce tobaccorelated health disparities (Baker et al, 2007;Marlatt, Curry, & Gordon, 1988;Wee, West, Bulgiba, & Shahab, 2011;Zhou et al, 2009). …”

Section: Subgroups: Low Acceptance Of Cravings Heavy Smoking and Dementioning

confidence: 99%

Randomized Trial of Telephone-Delivered Acceptance and Commitment Therapy Versus Cognitive Behavioral Therapy for Smoking Cessation: A Pilot Study

Bricker

Bush

Zbikowski

et al. 2014

Nicotine & Tobacco Research

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Objective: We conducted a pilot randomized trial of telephone-delivered acceptance and commitment therapy (ACT) versus cognitive behavioral therapy (CBT) for smoking cessation.Method: Participants were 121 uninsured South Carolina State Quitline callers who were adult smokers (at least 10 cigarettes/ day) and who wanted to quit within the next 30 days. Participants were randomized to 5 sessions of either ACT or CBT telephone counseling and were offered 2 weeks of nicotine replacement therapy (NRT).results: ACT participants completed more calls than CBT participants (M = 3.25 in ACT vs. 2.23 in CBT; p = .001). Regarding satisfaction, 100% of ACT participants reported their treatment was useful for quitting smoking (vs. 87% for CBT; p = .03), and 97% of ACT participants would recommend their treatment to a friend (vs. 83% for CBT; p = .06). On the primary outcome of intent-to-treat 30-day point prevalence abstinence at 6 months postrandomization, the quit rates were 31% in ACT versus 22% in CBT (odds ratio [OR] = 1.5, 95% confidence interval [CI] = 0.7-3.4). Among participants depressed at baseline (n = 47), the quit rates were 33% in ACT versus 13% in CBT (OR = 1.2, 95% CI = 1.0-1.6). Consistent with ACT's theory, among participants scoring low on acceptance of cravings at baseline (n = 57), the quit rates were 37% in ACT versus 10% in CBT (OR = 5.3, 95% CI = 1.3-22.0). Conclusions:ACT is feasible to deliver by phone, is highly acceptable to quitline callers, and shows highly promising quit rates compared with standard CBT quitline counseling. As results were limited by the pilot design (e.g., small sample), a fullscale efficacy trial is now needed.

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Attempts to quit smoking and relapse: Factors associated with success or failure from the ATTEMPT cohort study

Cited by 442 publications

References 12 publications

Depression and Smoking Cessation: Evidence from a Smoking Cessation Clinic with 1-Year Follow-Up

Depression and Smoking Cessation: Evidence from a Smoking Cessation Clinic with 1-Year Follow-Up

Factors associated with the efficacy of smoking cessation treatments and predictors of smoking abstinence in EAGLES

Randomized Trial of Telephone-Delivered Acceptance and Commitment Therapy Versus Cognitive Behavioral Therapy for Smoking Cessation: A Pilot Study

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