Abstract
Clinical Question
In adults and adolescents using cigarettes and/or smokeless tobacco, is motivational interviewing (MI) more effective compared to counseling, medical therapies or no intervention for improving tobacco cessation?
Answer
Yes. Evidence is modest but conclusive that using MI alone or in conjunction with other therapies results in greater rates of tobacco cessation compared to interventions that did not include MI.
Level of Evidence of the Answer
A
Search Terms
Motivational interviewing, tobacco cessation, tobacco abuse, intervention
Date Search Was Conducted
September 2015
Limits
Human, English, publication dates 2008 to present, meta-analyses, randomized-control trials, systematic reviews
Inclusion Criteria
Meta-analyses, randomized-control trials, or systematic reviews published during or after 2008 comparing the use of MI to other therapies for tobacco cessation in humans
Exclusion criteria
Studies published before 2008, MI used in other substance use disorders besides tobacco
Summary of the Issues
Among the most common and debilitating diseases ravaging our country, tobacco abuse is associated with directly attributable mortality from cancers, cardiovascular disease, and respiratory disease. Smoking is the primary cause of at least 30% of all cancer deaths, including malignancies of the lung, oropharynx, lip, esophagus, pancreas, larynx, kidney, and bladder. While it is directly associated with early cardiovascular death from ischemic heart disease, stroke, atherosclerosis, abdominal aortic aneurysm, and peripheral vascular disease, smoking is responsible for 80% of deaths from COPD and a large portion of deaths from respiratory infections including influenza, pneumonia, and bronchitis.1
Approximately 443,000 people in the US die annually from tobacco abuse. These trends translate to an alarming 5.1 million years of potential life lost when superimposing smoking-attributable mortality onto life expectancy. Combining productivity losses and health care expenditures, tobacco abuse in the U.S. costs an annual sum of $193 billion.1
Motivational interviewing is a counseling technique focused on eliciting “change talk” in clients by reflective listening and empathically addressing resistance. It has two components: technical, in which clients begin to talk about changing, and relational, which has three key items: a collaborative – rather than authoritarian - spirit between therapist and patient, respect of patient autonomy, and empathy such that motivation blooms implicitly in the patient rather than being imposed by the provider. The relational and technical components are equally vital in inducing change: patients’ vocalization of reasons for change strengthens their commitment to change, and provider empathy and reflective listening to evoke these thoughts leads to their vocalization.2
Since its inception, MI has been used in treatment of diabetes, obesity, illicit substance, alcohol, and tobacco abuse, gambling, mental disorders, and others. This review focuses on current research for using MI for smoking cessation as compared to standard physician counseling or usual care.
Summary of the Evidence
A meta-analysis performed by Hettema et al. included 31 trials in which the intervention was MI alone or combined with other interventions for smoking cessation. The variable tested was abstinence as measured biochemically or through self-reporting after a follow-up period that was either short (less than six months) or long (greater than or equal to six months). Effect size was measured using Cohen’s d value for combined effect sizes, dc. According to these criteria, dc = .20 is a small effect, dc = .50 is a medium effect, and dc = .80 is a large effect. Short-term follow up periods had a mean abstinence rate of 13.8% (SD = 9.10), compared to a mean of 11.2% (SD = 10.01) in comparison conditions, corresponding to an OR of 1.07 [0.96, 1.19] and dc of 0.12 (p < .05). Long-term follow-up periods had a mean abstinence rate of 12.8% (SD = 10.50) compared to 10.5% (SD = 9.10) mean abstinence rate in comparison conditions; OR = 1.35 [1.02, 1.78] and dc =0.17 (p < .05).3
The authors evaluated for several potential moderators in patient characteristics including age (adolescents under age 18 versus adult older than 18), ethnicity, gender, presence of medical comorbidities, level of tobacco dependence, motivation to quit, and whether it was an international study or performed in the US. Of the potential moderators, the international studies had the highest effect size, dc = 0.75 (p < 0.1) at short-term and dc = 0.43 (p < .05) at long-term follow up. Other groups with significant effect size values were those with low level of tobacco dependence, low levels of motivation, adolescents, and those with medical comorbidities.3
A Cochrane review meta-analysis of 28 studies yielded similar results. 16, 803 participants were included. Comparison was to brief advice or usual care; outcome variable was smoking cessation at a minimum of six months follow-up from beginning treatment, as reported by either point prevalence abstinence or sustained abstinence. Risk ratio was 1.26 (95% CI 1.16 to 1.36) overall, although slightly higher in the eight studies that reported sustained abstinence (RR = 1.62; 95% CI 1.32 to 2.00; N = 3111) compared to the twenty studies reporting point prevalence abstinence only at least the six month mark or longer (RR = 1.20; 95% CI 1.09 to 1.31; N = 13,692).4
Inherent in the study design examining an intervention of this nature is a weakness in treatment fidelity. As of now, the exact vital elements and steps of MI are not described, presenting a problem with consistency in execution and limiting our ability to quantitate intervention based on objective criteria. Furthermore, study reports often do not detail the exact methods of MI used, only that MI was included. Hettema et al. had less than half of the included studies report treatment fidelity measures (including recording MI training characteristics, MI competency assessment, and ongoing fidelity checks).3 The Cochrane review attempted to mitigate this problem by excluding studies that did not have some form of fidelity assessment, such as MI training for providers or a measure of treatment fidelity.4
A potential source of bias in meta-analyses is publication bias, or exclusion of studies that showed no effect and thus could compromise overall outcome. To account for this both studies included a funnel plot to estimate the degree of publication bias. On a funnel plot, the standard error of the studies is a function of effect. Symmetrical distribution of plots around the combined effect size indicates no publication bias. Hettema et al. reported a high level of symmetry for both short- and long-term effects, indicating very low level of publication bias, whereas the Cochrane review’s funnel plot indicated some evidence of publication bias based on a less symmetrical distribution.3,4
There was a slightly higher effect in the groups in the Cochrane review, which may be explained by the limitation of included studies to those which had treatment fidelity measures (and thus may suggest greater adherence to true MI), or the fact that the study’s comparison was brief advice or usual care, while Hettema et al. compared more aggressive interventions as well as brief/usual care or placebo - which may obscure the effect of MI in isolation.
Conclusion
The evidence indicates a modest but significant effect of MI for smoking cessation. Younger age, medical comorbidities, lower level of dependence, and lower level of motivation all showed an increased effect. It would be beneficial to study these populations separately to identify which groups derive maximal benefit from MI.
Based on this evidence it is worthwhile to incorporate MI into standard tobacco cessation therapies. I am encouraged to find ways to integrate it more into my practice, either as a focused therapy or in conjunction with others, as another tool to combat the dangerous epidemic of tobacco abuse.
Acknowledgments
This paper was supported in part by Oklahoma Shared Clinical & Translational Resources, grant number NIGMS U54GM104938, NIGMS/NIH.
Footnotes
Conflicts of interest:
There are none to disclose.
References
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