JMIR Publications

ABSTRACT

Background:

Increasing evidence promotes the clinical utility of self-reported memory problems for detecting early impairment associated with Alzheimer’s disease (AD). However, past work investigating memory problems often conflated the types of problems (i.e., retrospective and prospective) with their features (i.e., frequency and consequences). This bias limits the specificity of traditional measures of memory problems and minimizes their ability to detect differential trajectories associated with cognitive decline. In the present study, we use a novel measure of self-reported memory problems that uses daily reports of memory lapses to disentangle types from features to analyze the impact of each dimension in two longitudinal datasets. Further, this study explores the individual difference factors of age and gender as potential moderators of the relationships between self-reported memory lapses and objective cognitive decline.

Objective:

This study describes the protocol for a secondary data analysis project that explores the relationship between experiences of daily memory lapses and their associations with cognitive decline in middle-aged and older adults.

Methods:

The present study uses multilevel, coordinated analyses across two measurement burst datasets to examine the links between features and consequences of memory lapses (retrospective and prospective) and their association with objective cognitive decline. The current sample (n = 535; ages 50-85 years; 61% women) is drawn from two ongoing, nationally funded research studies: the Effects of Stress on Cognitive Aging, Physiology, and Emotion Study and the Einstein Aging Study. Both studies assess the daily experience of memory lapses, including the type as well as the emotional and functional outcomes, and objective measures of cognition such as processing speed and episodic memory. We will use multilevel modeling to test our conceptual model that differences in frequency and types of memory lapses show differential trends in their relationships with cognitive decline and that these relationships vary by age and gender of participant.

Results:

This project was funded in August 2019. IRB study approval for secondary data analysis was approved in February 2020. Data analysis for the current project has not yet started.

Conclusions:

The early and accurate identification of individuals most at risk for cognitive decline is of paramount importance. Previous research exploring self-reported memory problems and AD is promising, however limitations in measurement may explain prior reports of inconsistences. The current study addresses these concerns by examining daily reports of memory lapses, how these vary by age and gender, and their relationship with objective cognitive performance. Overall this study aims to identify key features of daily memory lapses and the differential trajectories that best predict cognitive decline to help inform future AD risk screening tools.