Mental health professionals often must make judgments or decisions involving vital matters. Is an individual likely to act violently? Has a child been sexually abused? Is a police officer fit to carry a gun? An explosion of research in clinical and cognitive psychology provides practical means for enhancing the accuracy of clinical decision making and prediction and thereby improving outcomes and the quality of care. Unfortunately, this research has not been broadly disseminated in the mental health field. The book is designed to familiarize readers with essential findings from decision science and its practical, immediate applications in the mental health field.

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 Behavior
Hal R. Arkes, PhD is Emeritus Professor of Psychology, Ohio State University; Associate, Harding Center for Risk Literacy
Charles 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 Issues


• Chapter 2 Avoiding Unnecessary Error


• Part II: Gathering, Appraising, and Integrating Information


• Chapter 3 Assessing Whether Clinical Variables Are Related: The Important Task of Covariation Estimation


• Chapter 4 Confirmation Bias


• Chapter 5 Impediments to Accurate Decision Making


• Chapter 6 Base Rates: One of the Diagnostician's and Prognosticator's Greatest Allies


• Chapter 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 Prospects


• Part III: Corrective Methods and Strategies


• Chapter 11 Overconfidence and the Limits of Experience


• Chapter 12 The Limits of Insight Alone; Need for Active Steps, and Use of Debiasing Strategies


• Chapter 13 Approaches for Improving Information Gathering, Appraising the Utility of Information, and Combining and Interpreting Information


• Appendices


• Appendix 1 A sampling of base rate sources


• Appendix 2 Base rate nomogram


• Appendix 3 Examples of combining base rates with other diagnostic signs, indicators, and test results


• Appendix 4 A sampling of recent publications in five areas of machine learning and artificial intelligence related to applied clinical practice


• Appendix 5 Practice Cases and Clinical Scenarios


• Appendix 6 Checklists/Guidelines