I came across similar arguments while I was writing the recently published Population Reports issue, “Communication for Better Health.” I think there are a lot of people out there who see the so-called “individual behavior change” theories and models and the “social change” theories and models as being “black” and “white”–as belonging to two different spheres. But I think, more and more, we’re seeing a convergence between the two types of theories and models. For example, many of the “individual behavior change” theories have a much greater emphasis on social networks, similar to what Dr. Singhal supports. For example, Everett Rogers’ diffusion of innovations theory has evolved to include more emphasis on social networks, recognizing their importance to behavior change.

I think behavior change communication programming should be based on a broad range of behavioral theories. It shouldn’t be that you subscribe to only one type or another type of theory. Different theories make different contributions to the field, and different situations will require different theories and approaches.

Communication scientists have long recognized that some attitudes, norms and behaviors change slowly, others change rapidly, some are sustained and others aren’t. In every case, however, the change is attributable to MULTIPLE factors, some exerting direct and others exerting indirect influence, some internal to the actor while others are external social or structural factors. The effect of any combination of factors on a behavioral outcome—whether it is a personal decision, a collective decision, a policy decision or a change in norms at the societal level–is not deterministic, but probabilistic. In non-statistical terms, this means that a certain outcome is more likely to happen if certain factors are present (including, perhaps, serendipity, self-organizing and surprise) and less likely to happen if they are absent (or if the combination of factors is different).

Dr Singhal argues that individual behavior change models “subscribe implicitly to questionable assumptions” such as that “…individuals are capable of controlling their context, operate in a level playing field, make decisions of their free will, and mainly through a rational cognitive processing framework.” Some models MIGHT assume such things–although I challenge him to find a commonly used one that actually does—but as a whole, behavior change theories most certainly do NOT make these assumptions. It may be a useful rhetorical strategy to lump a diverse set of models into one category, but to do so grossly oversimplifies them. In fact, behavior change theories range across a wide spectrum from those with a stronger individual cognitive focus to those with a stronger collective and structural focus; few, if any, are purely one or the other. In any event, degree of control over one’s context, equity of opportunity, autonomy and the relative importance of rationality versus emotion and other factors are all VARIABLES, not assumed constants.

No health communication practitioners that I know believe in a “machine” view of social systems or think that a perfectly deterministic approach to communication for health and development is possible. For Dr Singhal to suggest that the “machine” view is the “prevailing mindset of behavior change” is patently wrong. What communication scientists DO seek is to understand how individual and social change occurs and then to take those processes into account when developing communication programs. Inescapably, those processes are complex and communication programs must be similarly complex if they hope to make a difference.

Dr Singhal’s own example of Taru, one could argue, illustrates a perfectly clear multivariate causal effect: exposure to a fictional model of village celebration caused other villages (not all of them, but some of them—probabilistically as a function of multiple contextual and individual variables at play in those villages) to replicate (imperfectly, I’m sure) a similar celebration in their own village. He clearly believes himself that Taru caused the celebration of girls’ birthdays to spread (or at least start to spread) and he hopes that telling the story of Taru (i.e., the use of a narrative communication strategy) will encourage other communities to treat women better in other ways, as well. If he doesn’t believe that Taru contributed to change, why is it offered as an example of an effective approach to development communication?

Douglas Storey
Center for Communication Programs
Johns Hopkins Bloomberg School of Public Health