...1987). Throughout the 90s, researchers in cognitive and language development used the DS lens to examine real-time performance and profiles of developmental change (e.g., Smith, 1995; van der Maas Molenaar, 1992; van Geert, 1991). More gradually during the 90s, DS approaches to emotional development began to focus on the patterning of facial expressions, emotional behaviors, and emotion regulation (Camras, 1992; Fogel et al., 1992; Lewis, Lamey, & Douglas, 1999). Finally, in the last few years, the study of social development has adopted DS methods sensitive to the fine-grained structure of children's interpersonal interactions (Granic & Hollenstein, 2003; Granic, Hollenstein, Dishion, & Patterson, 2003; Hsu & Fogel, 2003; van Geert & van Dijk, 2002). DS approaches have appeared in other areas of psychology as well, including the study of groups (Arrow, McGrath, & Berdahl, 2000), marital relations (Gottman, Murray, Swanson, Tyson, & Swanson, 2002), and clinical processes (Tschacher & Scheier, 1997). Yet the field of developmental psychopathology, lying at the interface of developmental and clinical investigation, has made little progress in DS-inspired research. Despite long-held assumptions about the systemic nature of individual trajectories, interest in the biological substrates of problem behaviors, and attraction to notions of self-organization and complexity (see Lewis & Granic, 1999), developmental psychopathologists have generally not informed their research practices with DS concepts or methods.

Given this lag, it is exciting to see several articles in this special issue that explicitly draw on DS ideas for conceptualizing and researching developmental processes that lead to problem trajectories. As is typical of research in developmental psychopathology, these studies examine relations between early problem indicators (risk factors), mediating variables, and outcome variables, and/or they assess changes in outcomes measured across several longitudinal waves. In other words, they integrate DS ideas into research focused on prediction. Indeed, much of the practical value of research in developmental psychopathology is in its predictions. How do we know before things go wrong that they will go wrong, or are likely to go wrong, or are likely to go wrong given the presence or absence of certain conditions? Such knowledge is crucial to guide administrators, clinicians, and educators toward preventive practices for children and their families. But is prediction compatible with DS approaches to development? Many researchers understand prediction in terms of linear relations between precursors and outcomes, where increments in one variable are proportional to increments in the other. DS approaches generally highlight nonlinear (complex, indirect, disproportionate) relations among causally connected events, multiple causality, feedback relations, and so forth. Moreover, DS approaches construe time as continuous, and there is little interest in identifying "before" and "after" variables. In fact, the chief contribution of the DS paradigm seems to be in the understanding of process, not outcome. Given these incompatibilities, a marriage between DS principles and the pragmatics of prediction could be rocky.

Several questions come to mind in anticipating such a union. First, predictive relations between precursors and problem outcomes are usually surprisingly weak. Although we get accustomed to correlation coefficients in the 0.2-0.4 range, we should continue to ask where all the rest of the variance (up to 96%) went, and how much cause and effect is captured by these associations. Are the linear assumptions in traditional designs responsible for low coefficients? If life really is complex, multidetermined, and characterized by recursive interactions, then maybe a DS approach to prediction would help capture more of the connection between precursor and outcome events. Both the nature of developmental causation and the shape of developmental trajectories could be revisited from this perspective. Second, in recognizing the complexity of developmental processes, and the indeterminacy of precursors at any age, conventional approaches often look at mediators that contribute to predictions from risk factors to outcomes. However, mediators are usually expressed as values for each individual on one or a few variables (counts, frequencies, scale values, etc.). To what degree can these variables capture complex processes in the real world, including reciprocal interactions among social partners, emotions and behaviors, and expectations and consequences, as they play out over repeated occasions? DS approaches assume a multiplicity of causal factors that interact within developmental periods, as well as the second-order complexity of causal factors interacting across developmental periods. It is worth exploring whether this view of complexity helps provide a more precise and powerful representation of mediating effects. Third and last, critics of DS approaches sometimes ask "what good are they?" To put it bluntly, how much do we care about the fine-grained structure of behavior and the multifaceted web of developmental pathways unless we can make predictions, especially predictions that are falsifiable? Furthermore, DS approaches have remained largely at the level of basic research, so if these predictions can be applied to help people in the real-world,...

NOTE: All illustrations and photos have been removed from this article.



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