12 research outputs found

    Web‐based Weight Management Programs in an Integrated Health Care Setting: A Randomized, Controlled Trial

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    Objective : To assess the efficacy of a Web‐based tailored behavioral weight management program compared with Web‐based information‐only weight management materials. Research Methods and Procedures : Participants, 2862 eligible overweight and obese (BMI = 27 to 40 kg/m 2 ) members from four regions of Kaiser Permanente's integrated health care delivery system, were randomized to receive either a tailored expert system or information‐only Web‐based weight management materials. Weight change and program satisfaction were assessed by self‐report through an Internet‐based survey at 3‐ and 6‐month follow‐up periods. Results : Significantly greater weight loss at follow‐up was found among participants assigned to the tailored expert system than among those assigned to the information‐only condition. Subjects in the tailored expert system lost a mean of 3 ± 0.3% of their baseline weight, whereas subjects in the information‐only condition lost a mean of 1.2 ± 0.4% ( p < 0.0004). Participants were also more likely to report that the tailored expert system was personally relevant, helpful, and easy to understand. Notably, 36% of enrollees were African‐American, with enrollment rates higher than the general proportion of African Americans in any of the study regions. Discussion : The results of this large, randomized control trial show the potential benefit of the Web‐based tailored expert system for weight management compared with a Web‐based information‐only weight management program.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/93691/1/oby.2006.34.pd

    Behavioral Informatics and Computational Modeling in Support of Proactive Health Management and Care

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    Health-related behaviors are among the most significant determinants of health and quality of life. Improving health behavior is an effective way to enhance health outcomes and mitigate the escalating challenges arising from an increasingly aging population and the proliferation of chronic diseases. Although it has been difficult to obtain lasting improvements in health behaviors on a wide scale, advances at the intersection of technology and behavioral science may provide the tools to address this challenge. In this paper, we describe a vision and an approach to improve health behavior interventions using the tools of behavioral informatics, an emerging transdisciplinary research domain based on system-theoretic principles in combination with behavioral science and information technology. The field of behavioral informatics has the potential to optimize interventions through monitoring, assessing, and modeling behavior in support of providing tailored and timely interventions. We describe the components of a closed-loop system for health interventions. These components range from fine grain sensor characterizations to individual-based models of behavior change. We provide an example of a research health coaching platform that incorporates a closed-loop intervention based on these multiscale models. Using this early prototype, we illustrate how the optimized and personalized methodology and technology can support self-management and remote care. We note that despite the existing examples of research projects and our platform, significant future research is required to convert this vision to full-scale implementations

    A Multidimensional View of Personal Health Systems for Underserved Populations

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    The advent of electronic personal health records (PHR) provides a major opportunity to encourage positive health management practices, such as chronic disease management. Yet, to date there has been little attention toward the use of PHRs where advanced health information services are perhaps most needed, namely, in underserved communities. Drawing upon research conducted with safety net providers and patients, the authors propose a multi-level analytical framework for guiding actions aimed at fostering PHR adoption and utilization. The authors first outline distinctive user and technical requirements that need to be considered. Next, they assess organizational requirements necessary to implement PHRs within health systems bound by limited resources. Finally, the authors analyze the overriding health care policy context that can facilitate or thwart such efforts. The conclusion notes that heightened national attention toward health information technology and reform provides a significant opportunity for initiatives whose goal is to increase widepread access to PHRs
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