Treatment fidelity refers to the methodological strategies used to monitor and enhance the reliability and validity of behavioral interventions. This article describes a multisite effort by the Treatment Fidelity Workgroup of the National Institutes of Health Behavior Change Consortium (BCC) to identify treatment fidelity concepts and strategies in health behavior intervention research. The work group reviewed treatment fidelity practices in the research literature, identified techniques used within the BCC, and developed recommendations for incorporating these practices more consistently. The recommendations cover study design, provider training, treatment delivery, treatment receipt, and enactment of treatment skills. Funding agencies, reviewers, and journal editors are encouraged to make treatment fidelity a standard part of the conduct and evaluation of health behavior intervention research.

A. Bellg, B. Borrelli, et al. (2004) previously developed a framework that consisted of strategies to enhance treatment fidelity of health behavior interventions. The present study used this framework to (a) develop a measure of treatment fidelity and (b) use the measure to evaluate treatment fidelity in articles published in 5 journals over 10 years. Three hundred forty-two articles met inclusion criteria; 22% reported strategies to maintain provider skills, 27% reported checking adherence to protocol, 35% reported using a treatment manual, 54% reported using none of these strategies, and 12% reported using all 3 strategies. The mean proportion adherence to treatment fidelity strategies was .55; 15.5% of articles achieved greater than or equal to .80. This tool may be useful for researchers, grant reviewers, and editors planning and evaluating trials.

Objective Given the critical role of behavior in preventing and treating chronic diseases, it is important to accelerate the development of behavioral treatments that can improve chronic disease prevention and outcomes. Findings from basic behavioral and social science research hold great promise for addressing behaviorally-based clinical health problems, yet there is currently no established pathway for translating fundamental behavioral science discoveries into health-related treatments ready for Phase III efficacy testing. This article provides a systematic framework for guiding efforts to translate basic behavioral science findings into behavioral treatments for preventing and treating chronic illness. Methods The ORBIT model for behavioral treatment development is described as involving a flexible and progressive process, pre-specified clinically significant milestones for forward movement, and return to earlier stages for refinement and optimization. Results This article presents the background and rationale for the ORBIT model, a summary of key questions for each phase, a selection of study designs and methodologies well-suited to answering these questions, and pre-specified milestones for forward or backward movement across phases. Conclusions The ORBIT model provides a progressive, clinically-relevant approach to increasing the number of evidence-based behavioral treatments available to prevent and treat chronic diseases.

Medication adherence plays an important role in optimizing the outcomes of many treatment and preventive regimens in chronic illness. Self-report is the most common method for assessing adherence behavior in research and clinical care, but there are questions about its validity and precision. The NIH Adherence Network assembled a panel of adherence research experts working across various chronic illnesses to review selfreport medication adherence measures and research on their validity. Self-report medication adherence measures vary substantially in their question phrasing, recall periods, and response items. Self-reports tend to overestimate adherence behavior compared with other assessment methods and generally have high specificity but low sensitivity. Most evidence indicates that self-report adherence measures show moderate correspondence to other adherence measures and can significantly predict clinical outcomes. The quality of self-report adherence measures may be enhanced through efforts to use validated scales, assess the proper construct, improve estimation, facilitate recall, reduce social desirability bias, and employ technologic delivery. Self-report medication adherence measures can provide actionable information despite their limitations. They are preferred when speed, efficiency, and low-cost measures are required, as is often the case in clinical care. KeywordsAdherence, Compliance, Self-management, Medication, Self-report Valid measurement of medication adherence plays a crucial role in healthcare and health research. When a patient is not benefiting from a medication regimen, clinicians need sound adherence information to determine whether the medication is ineffective or not being taken as prescribed. Assessing medication adherence during routine clinical care can further ensure that individuals in need of adherence support interventions receive them, ideally before deleterious outcomes occur. In the context of clinical research, proper interpretation of proof-of-concept trials testing new pharmacologic regimens requires valid adherence data, because any null findings may stem from poor adherence rather than a lack of drug efficacy. Research designed to understand and promote medication adherence also requires precise methods of adherence assessment.Among many approaches to assessing medication adherence, patient self-report measures remain the most common method [1][2][3][4][5][6]. These measures are defined by asking respondents to characterize their medication adherence behavior. Self-report measures of medication adherence range from simple singleitem questions regarding missed doses to complex multi-item assessments that incorporate reasons for nonadherence [7]. The widespread use of self-report adherence measures in clinical care and research reflects their low cost and ease of implementation across a large variety of medication regimens.There are two primary challenges related to selfreport measures of medication adherence. ImplicationsPractice: Routine assessment of medication...

Background-Clinical depression is associated with an increased risk for mortality in patients with a recent myocardial infarction (MI). Reduced heart rate variability (HRV) has been suggested as a possible explanation for this association. The purpose of this study was to determine if depression is associated with reduced HRV in patients with a recent MI. Methods and Results-Three hundred eighty acute MI patients with depression and 424 acute MI patients without depression were recruited. All underwent 24-hour ambulatory electrocardiographic monitoring after hospital discharge. In univariate analyses, 4 indices of HRV were significantly lower in patients with depression than in patients without depression. Variables associated with HRV were then compared between patients with and without depression, and potential confounds were identified. These variables (age, sex, diabetes, and present cigarette smoking) were entered into an analysis of covariance model, followed by depression status. In the final model, all but one HRV index (high-frequency power) remained significantly lower in patients with depression than in patients without depression. Conclusions-We conclude that greater autonomic dysfunction, as reflected by decreased HRV, is a plausible mechanism linking depression to increased cardiac mortality in post-MI patients.

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Writing Committee for the ENRICHD Investigators C ARDIOVASCULAR DISEASE IS THE leading cause of death and a major cause of morbidity and disability in the United States, with an estimated 6 million people having symptomatic coronary heart disease (CHD). 1 Recent studies 2-7 have shown that depression and low perceived social support (LPSS) are associated with increased cardiac morbidity and mortality in CHD patients. In patients with CHD, the prevalence of major depression is nearly 20% and the prevalence of minor depression is approximately 27%. 8-10 After an acute myocardial infarction (MI), depression is a risk factor for mortality independent of cardiac disease severity. 4,6 A recent randomized clinical trial found that the antidepressant sertraline hydrochloride was effective in treating recurrent depression in patients with either an acute MI or an episode of unstable angina. 11 However, no clinical trial has examined whether treating depression with counseling or antidepressants after an acute MI improves survival or reduces cardiac risk. The absence of social support is also a risk factor for cardiac morbidity and mortality in patients with CHD. 2,3,5,7 No clinical trial has tested the effects of increasing social support on clinical end points following acute MI, although

Poor adherence to efficacious cardiovascular related medications has led to considerable morbidity, mortality, and avoidable health care costs. This paper provides results of a recent think tank meeting in which various stakeholder groups representing key experts from consumers, community health providers, the academic community, decision-making government officials (FDA, NIH, etc), and industry scientists met to evaluate the current status of medication adherence and provide recommendations for improving outcomes. Below, we review the magnitude of the problem of medication adherence, prevalence, impact, and cost. We then summarize proven effective approaches and conclude with a discussion of recommendations to address this growing and significant public health issue of medication non adherence.