Not only epidemiologists, but also economists, political scientists, and other researchers who are especially concerned with public policy, have been struggling to find new ways to make inferences about people’s behaviors and the choices they make. Instrumental variable analysis—another method of accounting for the unmeasured confounding variable used in econometrics—might also have an application in media research. Another approach is group randomized trials, in which the effects of policies are assessed using random samples of families, schools, neighborhoods, and even towns.
Oakes noted that longitudinal research designs, although they are the prototype for epidemiological research, may not be as helpful in media studies as other approaches. Longitudinal designs, he explained, are very useful for identifying random, unintentional exposures or the natural occurrence and progression of a disease. But when individual choices affect outcomes, the background characteristics and preferences that influence those choices are too difficult to disentangle. Moreover, factors that change over time, such as the nature of media technology or content, and the cumulative effects of ongoing exposure, have changing effects on outcomes, which can affect the findings in a longitudinal study.
The general challenge underlying most epidemiological research, and media research in particular, is that research subjects are not Robinson Crusoe, affected only by the conditions on a small island. Individuals respond to certain stimuli on the basis of their prior experiences as well as current conditions, and they are affected as well by the presence or absence of others. Individuals’ choices and experiences are dependent on an infinite number of choices that others have made, as well as infinite other ways in which they are influenced by the individuals and groups that surround them. The more basic question is the perennial one about how social environment influences biological, psychological, and social processes, and vice versa.
Thus, Oakes argued, the most valuable approach may be to use field experiments to investigate the potential impact of interventions. While models that posit causality are needed to support the choices of interventions to evaluate, conclusively resolving the relative contributions of individual versus social factors (nature versus nurture arguments) may not be necessary to achieve public health objectives.