Gordon Parker1, Dusan Hadzi-Pavlovic, Lucy Tully. 1. School of Psychiatry, University of New South Wales, and Black Dog Institute, Prince of Wales Hospital, Randwick 2031, Sydney, Australia. g.parker@unsw.edu.au
Abstract
BACKGROUND: As division between unipolar and bipolar disorders can be problematic, we sought to develop a self-report questionnaire of mood 'highs' that would both distinguish true Bipolar Disorder from any elevated mood states in unipolar depression and sharpen the distinction between Bipolar I and II conditions. METHOD: A 46-item questionnaire was developed and completed by 157 out-patients presenting with a major depressive episode, and clinically diagnosed as having either Bipolar I (BP-I), Bipolar II (BP-II) or Unipolar (UP) depression, although DSM-IV duration criteria for BP-I and BP-II were not imposed. RESULTS: Factor analyses identified four key constructs to mood 'highs', while additional analyses refined the questionnaire to 27 items. The refined measure was highly accurate in distinguishing composite Bipolar (BP-I and BP-II) from UP subjects (AUC = 0.93, sensitivity = 81%; specificity = 98%, positive predictive value = 0.95). Questionnaire scores were similar for BP-I and BP-II subjects, raising the possibility that the core mood state differs little in severity across the two expressions, and that their distinction allows an alternative model that weights the presence or absence of psychotic features. CONCLUSIONS: Our study advances understanding of boundary distinctions between bipolar and unipolar mood disorders, and between BP-I and BP-II conditions, and allows consideration of a model distinguishing BP-I from BP-II by the presence of psychotic features only. The described model is the mirror image of a hierarchical structural model for conceptualizing psychotic and melancholic depression, allowing an 'isomer model' for linking the mood swing states.
BACKGROUND: As division between unipolar and bipolar disorders can be problematic, we sought to develop a self-report questionnaire of mood 'highs' that would both distinguish true Bipolar Disorder from any elevated mood states in unipolar depression and sharpen the distinction between Bipolar I and II conditions. METHOD: A 46-item questionnaire was developed and completed by 157 out-patients presenting with a major depressive episode, and clinically diagnosed as having either Bipolar I (BP-I), Bipolar II (BP-II) or Unipolar (UP) depression, although DSM-IV duration criteria for BP-I and BP-II were not imposed. RESULTS: Factor analyses identified four key constructs to mood 'highs', while additional analyses refined the questionnaire to 27 items. The refined measure was highly accurate in distinguishing composite Bipolar (BP-I and BP-II) from UP subjects (AUC = 0.93, sensitivity = 81%; specificity = 98%, positive predictive value = 0.95). Questionnaire scores were similar for BP-I and BP-II subjects, raising the possibility that the core mood state differs little in severity across the two expressions, and that their distinction allows an alternative model that weights the presence or absence of psychotic features. CONCLUSIONS: Our study advances understanding of boundary distinctions between bipolar and unipolar mood disorders, and between BP-I and BP-II conditions, and allows consideration of a model distinguishing BP-I from BP-II by the presence of psychotic features only. The described model is the mirror image of a hierarchical structural model for conceptualizing psychotic and melancholic depression, allowing an 'isomer model' for linking the mood swing states.
Authors: Adrian A Chrobak; Marcin Siwek; Dominika Dudek; Janusz K Rybakowski Journal: Int J Methods Psychiatr Res Date: 2018-07-30 Impact factor: 4.035
Authors: Judith G Proudfoot; Gordon B Parker; Megan Benoit; Vijaya Manicavasagar; Meg Smith; Aimee Gayed Journal: Health Expect Date: 2009-06 Impact factor: 3.377
Authors: Judith G Proudfoot; Amisha Jayawant; Alexis E Whitton; Gordon Parker; Vijaya Manicavasagar; Meg Smith; Jennifer Nicholas Journal: BMC Psychiatry Date: 2012-11-09 Impact factor: 3.630
Authors: Jennifer Nicholas; Judith Proudfoot; Gordon Parker; Inika Gillis; Rowan Burckhardt; Vijaya Manicavasagar; Meg Smith Journal: J Med Internet Res Date: 2010-12-19 Impact factor: 5.428