Abstract

So it appears that the experimental analysis of behavior (EAB) could benefit from intervention aimed at increasing its translational footprint, thus promoting continued recognition and support as a valuable social enterprise. By profession, I analyze behavioral problem spaces and find behavioral solutions. I therefore greatly appreciated Critchfield's (2011) efforts to identify the problem, its controlling variables, and its potential solutions. At least two behavioral problems are identified immediately in Critchfield's abstract. The first can be restated as “Why hasn't basic behavior analysis demonstrated social relevance more often?” I will say little about this first question other than to restate that the perception that basic research frequently demonstrates social relevance is perhaps misguided. Harvey Brooks, a physicist turned Harvard science and public policy analyst, notes that public debate about science and technology has been dominated by a pipeline model (perhaps better known as a linear model; Kline & Rosenberg, 1986) in which new discoveries in science produce new technological ideas, progressing through applied research and terminating in commercialization (Brooks, 1994). This model was exemplified by highly visible successes of World War II (e.g., the atomic bomb, radar), but such a model “corresponded only to the rare and exceptional cases cited above, it became embodied in political rhetoric and took considerable hold on the public imagination and seemed to be confirmed by a sufficient number of dramatic episodes so that it was regarded as typical of the entire process” (Brooks, p. 477). The perception that much basic science leads ultimately to technological innovation is something of a base-rate error. If EAB needs help in this respect, it is not alone among basic sciences. The second question, “What are impediments to translational innovation that may need to be addressed for basic behavior science to increase its translational footprint?” implies a behavioral deficit, and behavior analysts are good at addressing behavioral deficits. Critchfield identifies several important historical antecedents, including carryover (largely through training) of a time when the indirect benefits assumption was strongly supported and the adoption of rules that basic and applied science do not mix well. The second half of Critchfield's article is prescriptive, aimed at promoting translational research behavior on the part of basic researchers. The solutions imply some fundamental changes in operations. Critchfield is not pointing to inadequacies per se, only to changes that are sensitive to the current environment. Change is inevitable. Critchfield is simply recommending how to channel behavior change in ways that are sensitive to that environment. This is good behavior analysis. Towards promoting translational research in basic scientists, Critchfield suggests the following solutions: (a) Basic scientists need to read applied research and interact with practical problems; (b) basic scientists must master the communicative skills necessary to establish the social relevance of their research; (c) basic scientists should collaborate with applied behavior analysts; and (d) basic scientists should consider, and be trained in, experimental methods that are more suitable to use-inspired research. The last solution implies diverting some proportion of basic endeavors towards research questions with practical end points, adopting human subjects as the focus of basic research, determining how to obtain orderly data more efficiently, and considering experimental designs that resonate more strongly with the scientific mainstream. If carried out, I have no doubt that this prescription would succeed in producing more translational research out of our basic laboratories. Although I do not object, I can imagine the resistance or objections of others. They might start with reminders of the very good reasons those practices evolved in the first place. A “drop everything else” approach is not necessarily aligned with pursuing matters of practical import, but translational research is based only on the knowledge at hand. Translational research is perhaps less likely to result in discovery of novel phenomena. I do not entirely disagree with Poling's (2010) characterization of EAB as “esoteric analysis of behavior,” but we should keep in mind that “the cumulative development of a science provides the only final answer as to the importance of any particular data” (Sidman, 1960, p. 41). Group designs and statistical inference are perhaps the norm, but they are only as good as the assumptions on which they are based. Replication trumps p value any day. Nonhuman subjects are far removed from most societal concerns, but many questions of applied relevance are difficult, if not unethical, to answer with humans. History effects and punitive effects readily come to mind. Also, adopting a use-inspired research agenda does not necessarily free the basic researcher from the constraints said to impede more widespread appreciation. The criteria are looser, to be certain, but you find no respite from steady-state requirements in applied and translational research. Many submissions to the Journal of Applied Behavior Analysis (JABA) are still rejected because the authors cannot say with certainty that the same pattern found in Condition A would not have emerged in Condition B if Condition B continued for as long as Condition A.

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