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Demographically-corrected normative data for the HVLT-R, BVMT-R, and Aggregated Learning Ratio values in a sample of older adults.

Dustin B HammersKevin DuffRobert J Spencer
Published in: Journal of clinical and experimental neuropsychology (2021)
Background: The Learning Ratio (LR) is a novel learning slope score that has been developed to reduce the inherent competition between the first trial and subsequent trials in traditional learning slopes. Recent findings suggest that LR is sensitive to AD pathology along the AD continuum - more so than the traditional learning calculations that employ raw changes across trials. However, research is still experimental and not yet directly applicable to clinical settings. Consequently, the objective of the current study was to develop demographically-corrected normative data on these LR learning slopes.Method: The current study examined the influence of age and education on LR scores for the HVLT-R, BVMT-R, and an Aggregated HVLT-R/BVMT-R in 200 cognitively intact adults aged 65 years and older using linear regression.Results: Age negatively correlated with all LR metrics, and education positively correlated with most. No sex differences were identified. LR values were predicted from age and education, which can be compared to observed LR values and converted into demographically-corrected T scores.Conclusions: By comparing observed and predicted LR scores calculated from regression-based prediction equations, interpretations are permitted that aid in clinical decision making and treatment planning. Co-norming of the HVLT-R and BVMT-R also allows for comparisons between verbal and visual learning slope scores in individual patients. We hope normative data for LR enhances its utility as a clinical tool for examining learning slopes in older adults administered the HVLT-R and/or BVMT-R.
Keyphrases
  • healthcare
  • electronic health record
  • decision making
  • clinical trial
  • randomized controlled trial
  • mild cognitive impairment
  • cognitive decline
  • molecular dynamics simulations
  • middle aged
  • patient reported