Evaluating short-term and working memory in older adults: French normative data

Abstract

Short-term and working memory (WM) capacities are subject to change with ageing, both in normal older adults and in patients with degenerative or non-degenerative neurological disease. Few normative data are available for comparisons of short-term and WM capacities in the verbal, spatial and visual domains. To provide researchers and clinicians with a set of standardised tasks that assess short-term and WM using verbal and visuospatial materials, and to present normative data for that set of tasks. The present study compiled normative French data for three short-term memory tasks (verbal, visual and spatial simple span tasks) and two WM tasks (verbal and spatial complex span tasks) obtained from 445 healthy older adults aged between 55 and 85 years. Our data reveal main effects of age, education level and gender on older adults' short-term and WM performances. Equation-based normalisation can therefore be used to take these factors into account. The results provide a set of cut-off scores for five standardised tasks that can be used to determine the presence of short-term or WM impairment in older adults.

Working memory in older adults declines with age, but is modulated by sex and education

“…Together with other studies (Cansino et al, 2013;Fournet et al, 2012;Kumar et al, 2017), the evidence suggests that verbal as well as visuospatial WM shows declines within old age, and thus WM may weaken during old age quite generally. Finally, note that the absence of nonlinear effects within old age does not preclude nonlinear declines across the full adult lifespan (as have been found in other cognitive domains; Nyberg et al, 2012), since declines may be quite shallow during early adulthood, and only later show steep declines, which may be captured here.…”

Executive Functions

“…WM declines during aging (e.g., Fiore et al 2012, Fournet et al 2012). Much of that appears to be due to declining inhibitory control making older adults more vulnerable to proactive and retroactive interference (Hedden & Park 2001, Solesio-Jofre et al 2012) and to distraction (Rutman et al 2010, Zanto & Gazzaley 2009).…”

How Health Conditions Translate into Self-Ratings

“…Verbal Fluency tallies the number of different animals the respondent can name in one minute and ranges from 0 to 90 2 (Ardila, Ostrosky-solis, and Bernal 2006). Memory is based on the number of words the respondent can recall from a list of ten words read by the interviewer (Fournet et al 2012) and ranges from 0 to 10. Numeracy (Chapman and Liu 2009) measures mathematical performance and indicates the number of correct responses to a set of four questions testing the ability to calculate and problem solve.…”