Utility of the 20‐Item Noise Pareidolia Task (NPT‐20) for Assessing Visuoperceptual Disturbances Associated with Complex Visual Hallucinations in Parkinson's Disease.

  • Published In: Movement Disorders Clinical Practice, 2023, v. 10, n. 2. P. 269 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Turner, Travis H.; Rodriguez‐Porcel, Federico 3 of 3

Abstract

Background: Complex visual hallucinations (VH) are a common complication of Parkinson's disease (PD). Recent studies have demonstrated relevance of face pareidolia to VH in PD and Lewy body dementia (LBD). Objective: This study examined utility of the 20‐item Noise Pareidolia Task (NPT‐20) in assessing visuoperceptual disturbances associated with VH in PD. Methods: Retrospective chart review included 46 consecutive PD patients who completed NPT‐20 during clinical neuropsychological evaluation. Results: About half the sample (43%) reported VH. PD with VH made significantly more false‐positive pareidolia errors on the NPT‐20 (p < 0.0001). A cut‐off of 2 errors yielded 40% sensitivity, 100% specificity to VH; cut‐off of 1 yielded 75% sensitivity, 81% specificity. NPT‐20 was not associated with any other clinical or demographic factor. Across groups, NPT‐20 evinced moderate correlations with visuospatial functioning and visual memory. Conclusions: Current findings support utility of the NPT‐20 for evaluating visuoperceptual disturbances associated with VH in PD. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Movement Disorders Clinical Practice. 2023/02, Vol. 10, Issue 2, p269
  • Document Type:Article
  • Subject Area:Health and Medicine
  • Publication Date:2023
  • ISSN:2330-1619
  • DOI:10.1002/mdc3.13599
  • Accession Number:162014219
  • Copyright Statement:Copyright of Movement Disorders Clinical Practice is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Looking to go deeper into this topic? Look for more articles on EBSCOhost.