Using a Transdisciplinary Approach to Multiple Health Behavior Change Research
Lori A. J. Scott-Sheldon, PhD, Multiple Health Behavior Change SIG chair; and Jayson J. Spas, PhD, MS, Multiple Health Behavior Change SIG co-chair
The Society of Behavioral Medicine Multiple Health Behavior Change (MHBC) Special Interest Group (SIG) interviewed Christopher M. Warren, recipient of the SIG’s 2016 Outstanding Student/Trainee Abstract Award in MHBC Research. Mr. Warren was honored for an abstract entitled, Childhood Sleep Patterns Predict Future Substance Use Behaviors: A Mediational Pathway through Inhibitory Control Deficits. Mr. Warren is a PhD candidate within the Institute for Health Promotion and Disease Prevention Research in the Department of Preventive Medicine at the University of Southern California’s Keck School of Medicine.
MHBC SIG: Congratulations on your 2016 Outstanding Student/Trainee Abstract Award in MHBC Research. How does your research address an important problem in the MHBC field?
Warren: “This research tested mechanisms through which insufficient sleep increases risk of initiating cigarette and alcohol use during early adolescence. By studying the mediational role of inhibitory control, this research builds upon a growing evidence base arguing for the importance of executive functions in promoting multiple health behaviors like nutrition and physical activity as well as in preventing substance use, sexual risk-taking, and obesogenic behaviors. Since prior work has found executive functions like inhibitory control to be modifiable via multiple intervention modalities, this work can be used to support efforts to develop and implement MBHC interventions that directly improve inhibitory control and/or modify upstream determinants of inhibitory control such as insufficient sleep.”
MHBC SIG: How did you become interested in MHBC research?
Warren: “I was first exposed to MHBC concepts when I spearheaded a school-based participatory asthma intervention on Chicago’s southwest side. The main idea was to partner directly with asthmatic students to systematically identify and address key asthma triggers in their homes, schools, and surrounding communities. Through discussions with these youth, I came to appreciate the complex etiology of their asthma exacerbations and how effective asthma self-management involves a wide variety of behaviors. However, it wasn't until I became a doctoral student working under the mentorship of Mary Ann Pentz, PhD, on the Pathways to Health trial (NICHD R01 HD052107) that I actually heard the term MHBC and began to formally incorporate MHBC theories into my own research.”
MHBC SIG: What prompted you to take a transdisciplinary approach to MHBC research?
Warren: “I was unaware that there was any other approach to MHBC research! I think successful MHBC research must be transdisciplinary to a certain degree since even a single human behavior is typically influenced by myriad biological, psychological, social, and environmental factors. Failure to acknowledge the existence of these multiple determinants of health behavior would unnecessarily hamstring our behavior change efforts. Personally, I am lucky to be a trainee within a large, diverse department where I interact with clinical psychologists, epidemiologists, biostatisticians, neuroscientists, sociologists, hospitalists, and computer scientists on a daily basis.”
MHBC SIG: What are some benefits and challenges for junior investigators interested in MHBC research?
Warren: “The most obvious benefit of MHBC research is that it has the potential to improve human health and alleviate suffering on a broad scale. I believe MHBC research is a particularly useful paradigm for achieving these goals because it is grounded in a set of evidence-based assumptions about human behavior. Perhaps the most important of these assumptions is that patterns of behavior tend to cluster, so we must systematically address multiple health and risk behaviors—not treat single behaviors as if they occur in a vacuum. Of course, the flipside of this is that interventions targeting multiple behaviors are often more complex and challenging to implement. The statistical methods needed to handle data with multiple interrelated exposures and outcomes are also more difficult to apply and interpret than more traditional analytic methods. This can be challenging for junior investigators, who are expected to quickly acquire advanced statistical expertise but sometimes have limited resources when unexpected issues arise while applying these novel modeling frameworks.”