AI Article Synopsis

  • Geiger, Carr, and LeBlanc (2010) created a decision-making model aimed at helping professionals choose treatments for escape-maintained problem behaviors.
  • A digital survey tested how useful this model is by having both novice and expert practitioners evaluate hypothetical treatment scenarios, some with the model provided and others relying on their own judgment.
  • Results showed that experts were better at choosing the right treatment without the model compared to novices, and using the model didn’t improve experts' decision-making compared to relying on their experience.

Article Abstract

Geiger, Carr, and LeBlanc (2010) developed a decision-making model for escape-maintained problem behavior that could be used to guide the course of treatment selection. We used a digital survey to evaluate the model's potential usefulness. We presented novice and expert practitioners' written hypothetical scenarios and asked them to determine the optimal treatment in a given situation. Some participants were given the model, whereas others were instructed to use their best clinical judgment. Using logistic regression analyses, the general findings for our scenarios were the following: (a) experts without the aid of a decision model had better odds of selecting the optimal treatment than novices without the decision model, (b) experts with the decision model did not have greater odds of selecting optimal treatment than experts without the model, and

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5622005PMC
http://dx.doi.org/10.1007/s40617-017-0180-1DOI Listing

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