This article summarizes outcomes of the behavioral interventions work group for the Veterans Health Administration (VHA) State of the Art Conference (SOTA) for Weight Management. Sixteen VHA and non-VHA subject matter experts, representing clinical care delivery, research, and policy arenas, participated. The work group reviewed current evidence of efficacy, effectiveness, and implementation of behavioral interventions for weight management, participated in phone- and online-based consensus processes, generated key questions to address gaps, and attended an in-person conference in March 2016. The work group agreed that there is strong evidence for efficacy and effectiveness of core behavioral intervention components and processes, but insufficient evidence to determine the comparative effectiveness of multiple clinician-delivered weight management modalities, as well as technologies that may or may not supplement clinician-delivered treatments. Effective strategies for implementation of weight management services in VHA were identified. The SOTA work group's foremost policy recommendations are to establish a system-wide culture for weight management and to identify a population-level health metric to measure the impact of weight management interventions that can be tracked and clearly communicated throughout VHA. The work group's top research recommendation is to determine how to deploy and scale the most effective behavioral weight management interventions for Veterans.

The article discusses the implications of two health research trends for improving the design, review and reporting of research and evaluation studies in the U.S. The first trend is the gap between research findings and application in practice. The other trend is the increased emphasis on the methodological quality of health research reports.

BACKGROUND: The evidence base regarding what works in practice for helping patients change multiple risk behaviors is less developed than is the more basic literature on behavior change. Still, there is enough consistency of findings to present testable hypotheses for clinicians and administrators to evaluate and guide practice until more definitive evidence is available. METHODS: The behavior change principles known as the 5A's outline a sequence of support activities (assess, advise, agree, assist, arrange) that are effective for helping patients to change various health behaviors. These same principles also apply at the clinic level for designing activities to support behavior change. RESULTS: Successful practices promoting sustainable changes in multiple behaviors are patient centered, tailored, proactive, population based, culturally proficient, multilevel, and ongoing. Often a stepped-care model can be used to provide increasingly intensive (and costly) interventions for patients who are not successful at earlier intervention levels. CONCLUSIONS: Contextual factors are influential in determining success at both the patient and the office practice level. Therefore, greater attention should be paid to creating supportive family, healthcare system, and community resources and policies. We enumerate 15 hypotheses to be tested for improving patient-clinician interactions and for medical office change.

The authors evaluated the efficacy of fluoxetine hydrochloride (Prozac; Eli Lilly and Company, Indianapolis, IN) as an adjunct to behavioral treatment for smoking cessation. Sixteen sites randomized 989 smokers to 3 dose conditions: 10 weeks of placebo, 30 mg, or 60 mg fluoxetine per day. Smokers received 9 sessions of individualized cognitive-behavioral therapy, and biologically verified 7-day self-reported abstinence follow-ups were conducted at 1, 3, and 6 months posttreatment. Analyses assuming missing data counted as smoking observed no treatment difference in outcomes. Pattern-mixture analysis that estimates treatment effects in the presence of missing data observed enhanced quit rates associated with both the 60-mg and 30-mg doses. Results support a modest, short-term effect of fluoxetine on smoking cessation and consideration of alternative models for handling missing data.