Individual Differences and Features of Self-reported Memory Lapses as Risk Factors for Alzheimer Disease Among Adults Aged 50 Years and Older: Protocol for a Coordinated Analysis Across Two Longitudinal Data Sets

BackgroundIncreasing evidence has promoted the clinical utility of self-reported memory problems for detecting early impairment associated with Alzheimer disease (AD). However, previous studies investigating memory problems often conflated the types of problems (ie, retrospec...

Full description

Bibliographic Details
Main Authors: Mogle, Jacqueline, Hill, Nikki L, Turner, Jennifer R
Format: Article
Language:English
Published: JMIR Publications 2021-05-01
Series:JMIR Research Protocols
Online Access:https://www.researchprotocols.org/2021/5/e25233
id doaj-87dee2dc40644be4bd442b00f3fa651d
record_format Article
spelling doaj-87dee2dc40644be4bd442b00f3fa651d2021-05-14T12:31:45ZengJMIR PublicationsJMIR Research Protocols1929-07482021-05-01105e2523310.2196/25233Individual Differences and Features of Self-reported Memory Lapses as Risk Factors for Alzheimer Disease Among Adults Aged 50 Years and Older: Protocol for a Coordinated Analysis Across Two Longitudinal Data SetsMogle, JacquelineHill, Nikki LTurner, Jennifer R BackgroundIncreasing evidence has promoted the clinical utility of self-reported memory problems for detecting early impairment associated with Alzheimer disease (AD). However, previous studies investigating memory problems often conflated the types of problems (ie, retrospective and prospective) with their features (ie, 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 this study, we use a novel measure of self-reported memory problems that uses daily reports of memory lapses to disentangle types from features for analyzing the impact of each dimension in two longitudinal data sets. Furthermore, 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. ObjectiveThe aim of this study is to describe 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. MethodsThis study uses multilevel, coordinated analyses across two measurement burst data sets to examine the links between features and consequences of memory lapses (retrospective and prospective) and their association with objective cognitive decline. This study’s sample (N=392; aged 50-85 years; n=254, 64.8% 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 demonstrating that differences in frequency and types of memory lapses show differential trends in their relationships with cognitive decline and that these relationships vary by the age and gender of participants. ResultsThis project was funded in August 2019. The approval for secondary data analysis was given by the institutional review board in February 2020. Data analysis for this project has not yet started. ConclusionsThe 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 previous reports of inconsistences. This 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 the key features of daily memory lapses and the differential trajectories that best predict cognitive decline to help inform future AD risk screening tools. International Registered Report Identifier (IRRID)DERR1-10.2196/25233https://www.researchprotocols.org/2021/5/e25233
collection DOAJ
language English
format Article
sources DOAJ
author Mogle, Jacqueline
Hill, Nikki L
Turner, Jennifer R
spellingShingle Mogle, Jacqueline
Hill, Nikki L
Turner, Jennifer R
Individual Differences and Features of Self-reported Memory Lapses as Risk Factors for Alzheimer Disease Among Adults Aged 50 Years and Older: Protocol for a Coordinated Analysis Across Two Longitudinal Data Sets
JMIR Research Protocols
author_facet Mogle, Jacqueline
Hill, Nikki L
Turner, Jennifer R
author_sort Mogle, Jacqueline
title Individual Differences and Features of Self-reported Memory Lapses as Risk Factors for Alzheimer Disease Among Adults Aged 50 Years and Older: Protocol for a Coordinated Analysis Across Two Longitudinal Data Sets
title_short Individual Differences and Features of Self-reported Memory Lapses as Risk Factors for Alzheimer Disease Among Adults Aged 50 Years and Older: Protocol for a Coordinated Analysis Across Two Longitudinal Data Sets
title_full Individual Differences and Features of Self-reported Memory Lapses as Risk Factors for Alzheimer Disease Among Adults Aged 50 Years and Older: Protocol for a Coordinated Analysis Across Two Longitudinal Data Sets
title_fullStr Individual Differences and Features of Self-reported Memory Lapses as Risk Factors for Alzheimer Disease Among Adults Aged 50 Years and Older: Protocol for a Coordinated Analysis Across Two Longitudinal Data Sets
title_full_unstemmed Individual Differences and Features of Self-reported Memory Lapses as Risk Factors for Alzheimer Disease Among Adults Aged 50 Years and Older: Protocol for a Coordinated Analysis Across Two Longitudinal Data Sets
title_sort individual differences and features of self-reported memory lapses as risk factors for alzheimer disease among adults aged 50 years and older: protocol for a coordinated analysis across two longitudinal data sets
publisher JMIR Publications
series JMIR Research Protocols
issn 1929-0748
publishDate 2021-05-01
description BackgroundIncreasing evidence has promoted the clinical utility of self-reported memory problems for detecting early impairment associated with Alzheimer disease (AD). However, previous studies investigating memory problems often conflated the types of problems (ie, retrospective and prospective) with their features (ie, 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 this study, we use a novel measure of self-reported memory problems that uses daily reports of memory lapses to disentangle types from features for analyzing the impact of each dimension in two longitudinal data sets. Furthermore, 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. ObjectiveThe aim of this study is to describe 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. MethodsThis study uses multilevel, coordinated analyses across two measurement burst data sets to examine the links between features and consequences of memory lapses (retrospective and prospective) and their association with objective cognitive decline. This study’s sample (N=392; aged 50-85 years; n=254, 64.8% 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 demonstrating that differences in frequency and types of memory lapses show differential trends in their relationships with cognitive decline and that these relationships vary by the age and gender of participants. ResultsThis project was funded in August 2019. The approval for secondary data analysis was given by the institutional review board in February 2020. Data analysis for this project has not yet started. ConclusionsThe 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 previous reports of inconsistences. This 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 the key features of daily memory lapses and the differential trajectories that best predict cognitive decline to help inform future AD risk screening tools. International Registered Report Identifier (IRRID)DERR1-10.2196/25233
url https://www.researchprotocols.org/2021/5/e25233
work_keys_str_mv AT moglejacqueline individualdifferencesandfeaturesofselfreportedmemorylapsesasriskfactorsforalzheimerdiseaseamongadultsaged50yearsandolderprotocolforacoordinatedanalysisacrosstwolongitudinaldatasets
AT hillnikkil individualdifferencesandfeaturesofselfreportedmemorylapsesasriskfactorsforalzheimerdiseaseamongadultsaged50yearsandolderprotocolforacoordinatedanalysisacrosstwolongitudinaldatasets
AT turnerjenniferr individualdifferencesandfeaturesofselfreportedmemorylapsesasriskfactorsforalzheimerdiseaseamongadultsaged50yearsandolderprotocolforacoordinatedanalysisacrosstwolongitudinaldatasets
_version_ 1721441079755014144