promote research and interventions in health-related decision making, such as how individuals understand the content of health communications as well as manage their own health needs and risks;
expansion of implementation and dissemination activities so as to reduce the gap between research progress and practice;
development of an overall strategy for intervention research that integrates behavioral, psychosocial, and biomedical approaches and that spans multiple levels, from the individual to the societal;
intervention research that capitalizes on new opportunities created by technological innovation.
New measurement techniques and designs for both animal and human studies are necessary to build bridges that will link behavioral, psychological, and social levels of analysis to multiple levels of biology (organ systems, cellular, molecular). This broad purview underscores the need for methodologies that are responsive to the functioning of complex dynamical systems through time. To advance priorities on predisease pathways and positive health it is critically important to conduct longitudinal studies that measure multiple domains (e.g., behavioral, psychological, social, environmental) across time (e.g., early life influences, childhood and adolescence, adulthood, and old age). Parallel longitudinal requirements pertain to the biological mechanisms through which the above factors affect health outcomes. As such, longitudinal studies will increasingly require broad-based forms of data collection—social, behavioral, and biomedical.
Related to this general issue, the concept of cumulative physiological risk, illustrated with allostatic load, requires further refinement to better understand the cascade of internal events from optimal functioning of multiple systems to accumulating risk. Full understanding of predisease pathways will require operationalizations of cumulative multisystem risk that are suitable for infants, young children, and adolescents. The emphasis on pathways in this report also implies a need for statistical methodologies that can specify pathway trajectories, address nonlinearities in diverse indicators, and incorporate narratives as sources of data. Pertinent to the enlarged scope of intervention studies, greater understanding will be required of processes of voluntary self-selection in design and evaluation of complex multiple-component programs.
Specifically, we recommend that NIH support methodological initiatives in four broad areas:
refine the operationalization of cumulative physiological risk that takes explicit account of the internal cascade of events leading to risk across