Looking Outside Our Field highlights areas of science outside of behavior analysis that are of relevance for advancing behavior analytic research and improving clinical practice. In a previous post, I discussed neuroscience as an area for behavior analysts to explore with the aim of enriching our research endeavors and clinical practice.
Today, I turn to medicine and the predictive markers used for determining the best course of treatment for a patient. In recent years, cancer treatment has been revolutionized by the discovery of cancer subtypes, which do not all respond equally well to treatment. For instance, one subtype of lung cancer might require more aggressive chemotherapy than another. Precision medicine refers to tailoring treatments to the individual characteristics of the patient, considering their genes, lifestyle, and environment. By delivering treatment tailored to the subtype of the cancer, healthcare providers can ensure the best outcomes for patients. Best outcomes, in addition to remission of the cancer, include avoiding high cost of care associated with trying various treatments before finding one that works for the specific cancer, as well as avoiding side effects and invasiveness of treatments not deemed as effective for that cancer subtype.
In behavior analysis, we conduct behavioral assessments and functional analyses to identify behavioral goals to address during treatment and determine the function of target behaviors. A recent paper by Hagopian and colleagues borrowed from the precision medicine approach to tackle the issue of finding the most suitable behavioral treatment for individual clients. The authors write, “applying the methods and concepts from the precision medicine paradigm to behavior analysis could lead to the identification of variables (in addition to the function of behavior) to guide selection of the best treatment for a given case” (p. 3).
These researchers utilized predictive behavioral markers, behavioral measures that predict response to treatment, for self-injurious behavior maintained by automatic reinforcement. A predictive behavioral marker refers to a conditional probability that a given treatment will be effective at producing the desired behavior change given certain characteristics of the behavior being treated (e.g., occurring at high rates during all conditions of a functional analysis, high rates only during the alone/ignore condition). I will not go into the details of the analysis conducted by Hagopian and colleagues. For that I encourage you to read their paper published in JABA. I will, however, say their findings suggest incorporating predictive behavioral markers may be useful for identifying relations between the level of differentiation in a functional analysis of self-injurious behavior and the response to a particular treatment package. As important as is finding behavioral variables associated with treatment success, identifying variables associated with treatment failure also can be informative for elucidating behavioral mechanisms and designing effective treatments.
We know the behavioral profile of each individual with ASD is unique. Some exhibit high rates of problem behavior accompanied by limited language and social skills, whereas others have age-appropriate language and also exhibit high rates of problem behavior. Further, and perhaps most importantly for the present discussion, not all problem behavior maintained by the same function will respond equally well to the same treatment. The BACB ethical code discusses individualized behavior-change programs (4.03). Would the use of predictive behavioral markers enhance our ability to comply with this section of the code and provide better service to our clients? How could we advance our science and practice by looking outside our field?
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