Validation of the Spanish version of the Memory Failures of Everyday questionnaire in older adults using Rasch analysis Articles uri icon


  • Rodriguez Blazquez, Carmen
  • Forjaz, Maria João
  • Garcia Herranz, Sara
  • Venero, Cesar
  • Rodriguez Fernandez, Raquel
  • Diaz Mardomingo, Maria del Carmen

publication date

  • April 2022

start page

  • 332

end page

  • 337


  • 4


  • 22

International Standard Serial Number (ISSN)

  • 1444-1586

Electronic International Standard Serial Number (EISSN)

  • 1447-0594


  • Aim: The Memory Failures of Everyday (MFE) is a widely used instrument for assessing memory failure. The aim of the study was to analyze the MFE items using the Rasch model in a sample of cognitively older adults in Spain.
    Methods: A cross-sectional validation study in a sample of 214 healthy people aged >= 60 years who used centers for older people in Madrid (Spain). The MFE for the assessment of memory complaints was used. The following properties of the Rasch model were assessed: data fit, reliability, unidimensionality, local dependence and lack of differential item functioning by gender, age and marital status
    Results: The MFE showed a good fit to the Rasch model (x2(140) = 160.2; P = 0.116) and high reliability (person separation index = 0.808). The questionnaire was unidimensional (6.54% t-test; IC binomial = 0.036-0.095). The items showed lack of local dependence between them and differential item functioning. The MFE scores were transformed into linear interval scores with a median of 44.31 and an observed range of 17.9-89.2 (theoretical range: 0-100).
    Conclusions: The MFE is a unidimensional, reliable instrument to assess memory complaints in cognitively healthy older adults in Spain, with usefulness in clinical research and practice. The construct validity of the MFE linear score could not be fully confirmed and this deserves further investigation


  • Biology and Biomedicine
  • Medicine
  • Psychology
  • Statistics


  • memory complaints; memory failures; rasch model; validation