Applying Decision Research to Improve Clinical Outcomes, Psychological Assessment, and Clinical Prediction

David Faust, PhD is Professor, Department of Psychology and Fellow of the Ryan Institute of Neuroscience, University of Rhode Island; Affiliate Professor, Warren Alpert Medical School of Brown University, Department of Psychiatry and Human BehaviorHal R. Arkes, PhD is Emeritus Professor of Psychology, Ohio State University; Associate, Harding Center for Risk LiteracyCharles E. Gaudet, PhD is Fellow, Department of Physical Medicine and Rehabilitation, Harvard Medical School, Massachusetts General Hospital, Spaulding Rehabilitation Hospital

• Part I: Introduction and Foundations Chapter 1 The Benefits of Decision Research for Clinical Practice: Framing the IssuesChapter 2 Avoiding Unnecessary ErrorPart II: Gathering, Appraising, and Integrating InformationChapter 3 Assessing Whether Clinical Variables Are Related: The Important Task of Covariation EstimationChapter 4 Confirmation BiasChapter 5 Impediments to Accurate Decision MakingChapter 6 Base Rates: One of the Diagnostician's and Prognosticator's Greatest AlliesChapter 7 The Integration of Information: Strengths and Limits Chapter 8 Comparing Clinical Judgment and Statistical Decision Methods Chapter 9 Research on Racial/Ethnic Biases and Professional Judgment: Errors in Cold Cognition, Hot Cognition, and Interconnections with Decision Research Chapter 10 The Use of Artificial Intelligence in Clinical Decision Making: Current Status, Potential Advantages and Limits, Future ProspectsPart III: Corrective Methods and StrategiesChapter 11 Overconfidence and the Limits of ExperienceChapter 12 The Limits of Insight Alone; Need for Active Steps, and Use of Debiasing StrategiesChapter 13 Approaches for Improving Information Gathering, Appraising the Utility of Information, and Combining and Interpreting InformationAppendicesAppendix 1 A sampling of base rate sourcesAppendix 2 Base rate nomogramAppendix 3 Examples of combining base rates with other diagnostic signs, indicators, and test resultsAppendix 4 A sampling of recent publications in five areas of machine learning and artificial intelligence related to applied clinical practiceAppendix 5 Practice Cases and Clinical ScenariosAppendix 6 Checklists/Guidelines