Self-report screening instruments differentiate bipolar disorder and borderline personality disorder

Brian A. Palmer, Mehak Pahwa, Jennifer R. Geske, Simon Kung, Malik Nassan, Kathryn M. Schak, Renato D. Alarcon, Mark A. Frye, Balwinder Singh*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

14 Scopus citations

Abstract

Background: Bipolar disorder (BD) and borderline personality disorder (BPD) share overlapping phenomenology and are frequently misdiagnosed. This study investigated the diagnostic accuracy of the Mood Disorder Questionnaire (MDQ) and McLean Screening Instrument for Borderline Personality Disorder (MSI) in a clinical inpatient setting and whether individual screening items could differentiate BD from BPD. Methods: 757 sequential inpatients admitted to a Mood Disorder Unit completed both the MDQ and MSI. Screen positive for the MDQ was defined as ≥7/13 symptoms endorsed with concurrence and at least moderate impact. Screen positive for the MSI was defined as a score of ≥7. The clinical discharge summary diagnosis completed by a board-certified psychiatrist was used as the reference standard to identify concordance rates of a positive screen with clinical diagnosis. Individual items predicting one disorder and simultaneously predicting absence of other disorder by odds ratio (OR>and <1) were identified. Results: Both screening instruments were more specific than sensitive (MDQ 83.7%/ 67.8%, MSI 73.2% / 63.3%). MDQ individual items (elevated mood, grandiosity, increased energy, pressured speech, decreased need for sleep, hyperactivity) were significant predictors of BD diagnosis and non-predictors of BPD diagnosis. Whereas MSI subitem, self-harm behaviors/suicidal attempts predicted BPD in the absence of BD; distrust and irritability were additional predictors of BPD. Conclusion: While this study is limited by the lack of structured diagnostic interview, these data provide differential symptoms to discriminate BD and BPD. Further work with larger datasets and more rigorous bioinformatics machine learning methodology is encouraged to continue to identify distinguishing features of these two disorders to guide diagnostic precision and subsequent treatment recommendations.

Original languageEnglish (US)
Article numbere02201
JournalBrain and Behavior
Volume11
Issue number7
DOIs
StatePublished - Jul 2021

Funding

Dr. Frye reports grant support from Assurex Health, Mayo Foundation, and Medibio. Consultant (Mayo) - Actify Neurotherapies, Allergan, Intra-Cellular Therapies, Inc., Janssen, Myriad, Neuralstem Inc., Takeda, Teva Pharmaceuticals. He reports CME/Travel/Honoraria from the American Physician Institute, CME Outfitters, and Global Academy for Medical Education. Dr. Singh received research time support from Medibio. It is unrelated to the current study. Other authors have none to declare Dr. Frye reports grant support from Assurex Health, Mayo Foundation, and Medibio. Consultant (Mayo) ‐ Actify Neurotherapies, Allergan, Intra‐Cellular Therapies, Inc., Janssen, Myriad, Neuralstem Inc., Takeda, Teva Pharmaceuticals. He reports CME/Travel/Honoraria from the American Physician Institute, CME Outfitters, and Global Academy for Medical Education. Dr. Singh received research time support from Medibio. It is unrelated to the current study. Other authors have none to declare

Keywords

  • MDQ
  • MSI
  • bipolar disorder
  • borderline personality disorder

ASJC Scopus subject areas

  • Behavioral Neuroscience

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