Skip to main content
eScholarship
Open Access Publications from the University of California

UCLA

UCLA Previously Published Works bannerUCLA

Rationale and Design of the National Neuropsychology Network.

  • Author(s): Loring, David W
  • Bauer, Russell M
  • Cavanagh, Lucia
  • Drane, Daniel L
  • Enriquez, Kristen D
  • Reise, Steven P
  • Shih, KuoChung
  • Umfleet, Laura Glass
  • Wahlstrom, Dustin
  • Whelan, Fiona
  • Widaman, Keith F
  • Bilder, Robert M
  • NNN Study Group
  • et al.
Abstract

Objective.

The National Neuropsychology Network (NNN) is a multicenter clinical research initiative funded by the National Institute of Mental Health (NIMH; R01 MH118514) to facilitate neuropsychology's transition to contemporary psychometric assessment methods with resultant improvement in test validation and assessment efficiency.

Method

The NNN includes four clinical research sites (Emory University; Medical College of Wisconsin; University of California, Los Angeles (UCLA); University of Florida) and Pearson Clinical Assessment. Pearson Q-interactive (Q-i) is used for data capture for Pearson published tests; web-based data capture tools programmed by UCLA, which serves as the Coordinating Center, are employed for remaining measures.

Results

NNN is acquiring item-level data from 500-10,000 patients across 47 widely used Neuropsychology (NP) tests and sharing these data via the NIMH Data Archive. Modern psychometric methods (e.g., item response theory) will specify the constructs measured by different tests and determine their positive/negative predictive power regarding diagnostic outcomes and relationships to other clinical, historical, and demographic factors. The Structured History Protocol for NP (SHiP-NP) helps standardize acquisition of relevant history and self-report data.

Conclusions

NNN is a proof-of-principle collaboration: by addressing logistical challenges, NNN aims to engage other clinics to create a national and ultimately an international network. The mature NNN will provide mechanisms for data aggregation enabling shared analysis and collaborative research. NNN promises ultimately to enable robust diagnostic inferences about neuropsychological test patterns and to promote the validation of novel adaptive assessment strategies that will be more efficient, more precise, and more sensitive to clinical contexts and individual/cultural differences.

Many UC-authored scholarly publications are freely available on this site because of the UC's open access policies. Let us know how this access is important for you.

Main Content
Current View