Adaptive intervention design in mobile health: Intervention design and development in the Cell Phone Intervention for You trial.

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.

Impact of Funding Source on Clinical Trial Results Including Cardiovascular Outcome Trials.

Previous authors have suggested a higher likelihood for industry-sponsored (IS) studies to have positive outcomes than non-IS studies, though the influence of publication bias was believed to be a likely confounder. We attempted to control for the latter using a prepublication database to compare the primary outcome of recent trials based on sponsorship. We used the "advanced search" feature in the clinicaltrials.gov website to identify recently completed phase III studies involving the implementation of a pharmaceutical agent or device for which primary data were available. Studies were categorized as either National Institutes of Health (NIH) sponsored or IS. Results were labeled "favorable" if the results favored the intervention under investigation or "unfavorable" if the intervention fared worse than standard medical treatment. We also performed an independent literature search to identify the cardiovascular trials as a case example and again categorized them into IS versus NIH sponsored. A total of 226 studies sponsored by NIH were found. When these were compared with the latest 226 IS studies, it was found that IS studies were almost 4 times more likely to report a positive outcome (odds ratio [OR] 3.90, 95% confidence interval [CI] 2.6087 to 5.9680, p <0.0001). As a case example of a specialty, we also identified 25 NIH-sponsored and 215 IS cardiovascular trials, with most focusing on hypertension therapy (31.6%) and anticoagulation (17.9%). IS studies were 7 times more likely to report favorable outcomes (OR 7.54, 95% CI 2.19 to 25.94, p = 0.0014). They were also considerably less likely to report unfavorable outcomes (OR 0.11, 95% CI 0.04 to 0.26, p <0.0001). In conclusion, the outcomes of large clinical studies especially cardiovascular differ considerably on the basis of their funding source, and publication bias appears to have limited influence on these findings.

Evaluating the Impact of the Positive Choices Intervention on Substance Use, Psychological, and Care Engagement Outcomes Relevant to Current National HIV Prevention Goals

The HIV epidemic in the United States continues to be a significant public health problem, with approximately 50,000 new infections occurring each year. National public health priorities have shifted in recent years towards targeted HIV prevention efforts among people living with HIV/AIDS (PLWHA) that include: increasing engagement in and retention in care, improving HIV treatment adherence, and increasing screening for and treatment of substance use and psychological difficulties. This study evaluated the efficacy of Positive Choices (PC), a brief, care-based, theory-driven, 3-session counseling intervention for newly HIV-diagnosed men who have sex with men (MSM), in the context of current national HIV prevention priorities. The study involved secondary analysis of data from a preliminary efficacy trial of the PC intervention (n=102). Descriptive statistics examined baseline substance use, psychological characteristics and strategies, and care engagement and HIV-related biological outcomes. Generalized Estimating Equations (GEE) examined longitudinal changes in these variables by study condition. Results indicated that PC improved adherence to HIV treatment, but increased use of illicit drugs, specifically amyl nitrates and other stimulant drugs; additionally, moderation analyses indicated differences in patterns of change over time in viral load by baseline depression status. Implications of the findings and suggestions for future research are discussed.