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Deconstructing Favorable and Unfavorable Malingering-Attribution Perspectives

  • Gerald Young
Chapter
Part of the International Library of Ethics, Law, and the New Medicine book series (LIME, volume 56)

Abstract

The present chapter examines two works that appear to represent opposite perspectives in the area of psychological injury and law – (a) favorable malingering-attribution and (b) unfavorable malingering-attribution perspectives in forensic and related disability assessments (Larrabee 2012a; Drob et al. 2009, respectively). They are consistent with arguments that might be made in court by plaintiff and defense experts, respectively, although both views are based on scientific perspectives. However, in both cases, there are subtle turns, inconsistencies, and exploitation of the gray zone that help lead to the divergent opinions expressed. Therefore, I conduct an examination and deconstruction of the major points in both sources and conclude that both perspectives are not as consistent and clear as they would like to present to the reader. In analyzing the sources, I present them as making a series of arguments for their preferred points of view, and then comment on each point as they are made. However, note that the arguments were not presented so clearly as successive, enumerated points, as in the manner in which I have presented them. In analyzing Larrabee (2012b), I refer to some of the arguments made in the first part of the present book on confusions and gaps in the literature with respect to both the conceptual and empirical bases for understanding and researching malingering in the forensic disability and related contexts. Adapting a middle-of-the-road, science-first perspective, as presented in the first section of the book, would help in improving research in the field.

Keywords

Minnesota Multiphasic Personality Inventory Psychological Injury Unconscious Process Symptom Validity Factitious Disorder 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  • Gerald Young
    • 1
  1. 1.Glendon CollegeYork UniversityTorontoCanada

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