Todd A. Ward, PhD, BCBA-D
In a 2016 study published in The Analysis of Verbal Behavior, Tom Critchfield and Derek Reed sought to untangle and refine how we train members of the public on the early detection of melanoma, or skin cancer.
In their review of existing melanoma detection trainings, they noted a few trends. For example, they found that most trainings describe melanoma symptoms alongside images of clearly developed melanoma. However, the authors noted a relative lack in the variety of cancerous images used, as well as a lack of non-cancerous images. Their review also found a prevalent use of language designed to evoke aversive consequences related to the deadly nature of melanoma if gone undetected, and said that the real-world effects of such trainings on early detection have been unreliable.
Critchfield and Reed sought to tease out the language and image components of melanoma detection trainings to see if they could how the elements influence early detection outcomes.
The team had two groups of participants – a control group and a cancer group. Participants in the control group were shown an image of melanoma in its moderate stages. They were then asked to compare the original image to a variety of sample images and report on which samples were indicative of cancer. Participants in this group weren’t told anything about what the images depicted.
The cancer group performed the same task, with one important difference. Participants in the cancer group were told that the image depicted melanoma, critical symptoms, and were told of the importance of early detection.
The researchers were particularly interested in generalization gradients, or how far the comparison images could vary from the sample while still identifying the comparisons as similar to the original, and thus identifying symptoms of cancer. In short, the researchers found that simply telling the participants about melanoma and its risk factors made participants in the cancer group more likely to identify highly developed melanoma more so than the control group. However, those same participants were less likely to identify more subtle symptoms.
In other words, incorporating cancer language into early detection training may actually decrease the likelihood of early detection.
In offering an explanation for the somewhat counterintuitive findings, the authors suggested that their language around cancer may not have contributed to the shift in and of itself. However, contrasting such language with healthy alternatives may have influenced participants to seek out images that were more clearly opposite of healthy images. The result was an interaction effect whereby participants were less likely to identify subtle symptoms, and thus were less likely to detect early stage melanoma.
For much more on the study, including future research, be sure to check out the full article, and let us know what you think in the comments below! Also be sure to subscribe to bSci21 via email to receive the latest articles directly to your inbox.
Todd A. Ward, PhD, BCBA-D is the President and Founder of bSci21Media, LLC, which owns the top behavior analytic media outlet in the world, bSci21.org. bSci21Media aims to disseminate behavior analysis to the world and to support ABA companies around the globe through the Behavioral Science in the 21st Century blog and its subsidiaries, bSciEntrepreneurial, bSciWebDesign, bSciWriting, and the ABA Outside the Box CEU series. Dr. Ward received his PhD in behavior analysis from the University of Nevada, Reno under Dr. Ramona Houmanfar. He has served as a Guest Associate Editor of the Journal of Organizational Behavior Management, and as an Editorial Board member of Behavior and Social Issues. Dr. Ward has also provided ABA services to children and adults with various developmental disabilities in day centers, in-home, residential, and school settings, and previously served as Faculty Director of Behavior Analysis Online at the University of North Texas. Dr. Ward is passionate about disseminating behavior analysis to the world and growing the field through entrepreneurship. Todd can be reached at email@example.com