Pao-Hwa Lin1, Stephen Intille2, Gary Bennett3, Hayden B Bosworth4, Leonor Corsino5, Corrine Voils6, Steven Grambow7, Tony Lazenka2, Bryan C Batch5, Crystal Tyson8, Laura P Svetkey8. 1. Department of Medicine, Division of Nephrology, Duke University Medical Center, Durham, NC, USA Sarah W. Stedman Nutrition and Metabolism Center, Duke University Medical Center, Durham, NC, USA pao.hwa.lin@dm.duke.edu. 2. College of Computer and Information Science and Bouvé College of Health Sciences, Northeastern University, Boston, MA, USA. 3. Department of Psychology & Neuroscience, Duke University Medical Center, Durham, NC, USA Duke Obesity Prevention Program, Duke University Medical Center, Durham, NC, USA Duke Global Health Institute, Duke University Medical Center, Durham, NC, USA. 4. Center for Health Services Research in Primary Care, Durham Veterans Affairs Medical Center, Durham, NC, USA Department of Medicine, Division of General Internal Medicine, Duke University Medical Center, Durham, NC, USA Department of Psychiatry, Duke University Medical Center, Durham, NC, USA School of Nursing, Duke University, Durham, NC, USA. 5. Sarah W. Stedman Nutrition and Metabolism Center, Duke University Medical Center, Durham, NC, USA Department of Medicine, Division of Endocrinology, Duke University Medical Center, Durham, NC, USA. 6. Center for Health Services Research in Primary Care, Durham Veterans Affairs Medical Center, Durham, NC, USA Department of Medicine, Division of General Internal Medicine, Duke University Medical Center, Durham, NC, USA. 7. Center for Health Services Research in Primary Care, Durham Veterans Affairs Medical Center, Durham, NC, USA Department of Biostatistics and Bioinformatics, Duke University Medical Center, Durham, NC, USA. 8. Department of Medicine, Division of Nephrology, Duke University Medical Center, Durham, NC, USA Sarah W. Stedman Nutrition and Metabolism Center, Duke University Medical Center, Durham, NC, USA.
Abstract
BACKGROUND/AIMS: The obesity epidemic has spread to young adults, and obesity is a significant risk factor for cardiovascular disease. The prominence and increasing functionality of mobile phones may provide an opportunity to deliver longitudinal and scalable weight management interventions in young adults. The aim of this article is to describe the design and development of the intervention tested in the Cell Phone Intervention for You study and to highlight the importance of adaptive intervention design that made it possible. The Cell Phone Intervention for You study was a National Heart, Lung, and Blood Institute-sponsored, controlled, 24-month randomized clinical trial comparing two active interventions to a usual-care control group. Participants were 365 overweight or obese (body mass index≥25 kg/m2) young adults. METHODS: Both active interventions were designed based on social cognitive theory and incorporated techniques for behavioral self-management and motivational enhancement. Initial intervention development occurred during a 1-year formative phase utilizing focus groups and iterative, participatory design. During the intervention testing, adaptive intervention design, where an intervention is updated or extended throughout a trial while assuring the delivery of exactly the same intervention to each cohort, was employed. The adaptive intervention design strategy distributed technical work and allowed introduction of novel components in phases intended to help promote and sustain participant engagement. Adaptive intervention design was made possible by exploiting the mobile phone's remote data capabilities so that adoption of particular application components could be continuously monitored and components subsequently added or updated remotely. RESULTS: The cell phone intervention was delivered almost entirely via cell phone and was always-present, proactive, and interactive-providing passive and active reminders, frequent opportunities for knowledge dissemination, and multiple tools for self-tracking and receiving tailored feedback. The intervention changed over 2 years to promote and sustain engagement. The personal coaching intervention, alternatively, was primarily personal coaching with trained coaches based on a proven intervention, enhanced with a mobile application, but where all interactions with the technology were participant-initiated. CONCLUSION: The complexity and length of the technology-based randomized clinical trial created challenges in engagement and technology adaptation, which were generally discovered using novel remote monitoring technology and addressed using the adaptive intervention design. Investigators should plan to develop tools and procedures that explicitly support continuous remote monitoring of interventions to support adaptive intervention design in long-term, technology-based studies, as well as developing the interventions themselves.
RCT Entities:
BACKGROUND/AIMS: The obesity epidemic has spread to young adults, and obesity is a significant risk factor for cardiovascular disease. The prominence and increasing functionality of mobile phones may provide an opportunity to deliver longitudinal and scalable weight management interventions in young adults. The aim of this article is to describe the design and development of the intervention tested in the Cell Phone Intervention for You study and to highlight the importance of adaptive intervention design that made it possible. The Cell Phone Intervention for You study was a National Heart, Lung, and Blood Institute-sponsored, controlled, 24-month randomized clinical trial comparing two active interventions to a usual-care control group. Participants were 365 overweight or obese (body mass index≥25 kg/m2) young adults. METHODS: Both active interventions were designed based on social cognitive theory and incorporated techniques for behavioral self-management and motivational enhancement. Initial intervention development occurred during a 1-year formative phase utilizing focus groups and iterative, participatory design. During the intervention testing, adaptive intervention design, where an intervention is updated or extended throughout a trial while assuring the delivery of exactly the same intervention to each cohort, was employed. The adaptive intervention design strategy distributed technical work and allowed introduction of novel components in phases intended to help promote and sustain participant engagement. Adaptive intervention design was made possible by exploiting the mobile phone's remote data capabilities so that adoption of particular application components could be continuously monitored and components subsequently added or updated remotely. RESULTS: The cell phone intervention was delivered almost entirely via cell phone and was always-present, proactive, and interactive-providing passive and active reminders, frequent opportunities for knowledge dissemination, and multiple tools for self-tracking and receiving tailored feedback. The intervention changed over 2 years to promote and sustain engagement. The personal coaching intervention, alternatively, was primarily personal coaching with trained coaches based on a proven intervention, enhanced with a mobile application, but where all interactions with the technology were participant-initiated. CONCLUSION: The complexity and length of the technology-based randomized clinical trial created challenges in engagement and technology adaptation, which were generally discovered using novel remote monitoring technology and addressed using the adaptive intervention design. Investigators should plan to develop tools and procedures that explicitly support continuous remote monitoring of interventions to support adaptive intervention design in long-term, technology-based studies, as well as developing the interventions themselves.
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