546
Views
45
CrossRef citations to date
0
Altmetric
Original Articles

Examination of the Mild Brain Injury Atypical Symptom Scale and the Validity-10 Scale to detect symptom exaggeration in US military service members

, &
Pages 325-337 | Received 19 Aug 2014, Accepted 25 Jan 2015, Published online: 07 Apr 2015
 

Abstract

Objective: The purpose of this study was to examine the clinical utility of two validity scales designed for use with the Neurobehavioral Symptom Inventory (NSI) and the PTSD Checklist–Civilian Version (PCL–C); the Mild Brain Injury Atypical Symptoms Scale (mBIAS) and Validity-10 scale. Method: Participants were 63 U.S. military service members (age: M = 31.9 years, SD = 12.5; 90.5% male) who sustained a mild traumatic brain injury (MTBI) and were prospectively enrolled from Walter Reed National Military Medical Center. Participants were divided into two groups based on the validity scales of the Minnesota Multiphasic Personality Inventory–2 Restructured Form (MMPI–2–RF): (a) symptom validity test (SVT)-Fail (n = 24) and (b) SVT-Pass (n = 39). Participants were evaluated on average 19.4 months postinjury (SD = 27.6). Results: Participants in the SVT-Fail group had significantly higher scores (p < .05) on the mBIAS (d = 0.85), Validity-10 (d = 1.89), NSI (d = 2.23), and PCL–C (d = 2.47), and the vast majority of the MMPI–2–RF scales (d = 0.69 to d = 2.47). Sensitivity, specificity, and predictive power values were calculated across the range of mBIAS and Validity-10 scores to determine the optimal cutoff to detect symptom exaggeration. For the mBIAS, a cutoff score of ≥8 was considered optimal, which resulted in low sensitivity (.17), high specificity (1.0), high positive predictive power (1.0), and moderate negative predictive power (.69). For the Validity-10 scale, a cutoff score of ≥13 was considered optimal, which resulted in moderate–high sensitivity (.63), high specificity (.97), and high positive (.93) and negative predictive power (.83). Conclusion: These findings provide strong support for the use of the Validity-10 as a tool to screen for symptom exaggeration when administering the NSI and PCL–C. The mBIAS, however, was not a reliable tool for this purpose and failed to identify the vast majority of people who exaggerated symptoms.

The authors wish to thank current members of the 15YR-TBI Study Group for their contributions to the study: Ashley Graham, Rachel Gartner, Angela Driscoll, Zoe Li, Emma Schmidt, Deanna Pruitt, Megan Wright, Johanna Smith, Brittany Pizzano, Lauren Johnson, Arielle Gajer, Diana Nora, Jessica Kilgore, Anjali Jain, Heidi Mahatan, Mikelle Miles-Mooney, Sydney Appelbaum, Jamie Sullivan, Danielle Thompson, Angelica Dilay, Andrew Ma, Jason Bailie, and Laura Seibert. In addition, we also wish to thank past members of the 15YR-TBI Study Group for their earlier contributions to the study: Sarah Asmussen, Mallory Frazier, Nkenna Chidume-Okoro, Kerri Roberts, Percy Julian, James Foreman, Victoria Merritt, Molly Feliciano, Thomas Woodfill, and Elise Ward. Thank you also to Sandy Camilletti, Chantele Friend, and Patricia Leonard from Defense and Veterans Brain Injury Center (DVBIC) Headquarters for assistance with data entry and quality assurance; and to Angela Perta from the Brain Fitness Center for recent assistance with patient recruitment. The views, opinions, and/or findings contained in this article are those of the authors and should not be construed as an official Department of Defense position, policy, or decision unless so designated by other official documentation.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 53.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 627.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.