Literature DB >> 35113616

Incorporating ecological momentary assessment into multimethod investigations of cognitive aging: Promise and practical considerations.

Jennifer L Crawford1, Tammy English1, Todd S Braver1.   

Abstract

Ecological momentary assessment (EMA) represents a promising approach to study cognitive aging. In contrast to laboratory-based studies, EMA involves the repeated sampling of experiences in daily life contexts, enabling investigators to gain access to dynamic processes (e.g., situational contexts, intraindividual variability) that are likely to strongly contribute to aging and age-related change across the adult life-span. As such, EMA approaches complement the prevailing research methods in the field of cognitive aging (e.g., laboratory-based paradigms, neuroimaging), while also providing the opportunity to replicate and extend findings from the laboratory in more naturalistic contexts. Following an overview of the methodological and conceptual strengths of EMA approaches in cognitive aging research, we discuss best practices for researchers interested in implementing EMA studies. A key goal is to highlight the tremendous potential for combining EMA methods with other laboratory-based approaches, in order to increase the robustness, replicability, and real-world implications of research findings in the field of cognitive aging. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

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Year:  2022        PMID: 35113616      PMCID: PMC8860503          DOI: 10.1037/pag0000646

Source DB:  PubMed          Journal:  Psychol Aging        ISSN: 0882-7974


  68 in total

Review 1.  Assessing psychological change in adulthood: an overview of methodological issues.

Authors:  Christopher Hertzog; John R Nesselroade
Journal:  Psychol Aging       Date:  2003-12

2.  Methodological and theoretical implications of intraindividual variability in perceptual-motor performance.

Authors:  John R Nesselroade; Timothy A Salthouse
Journal:  J Gerontol B Psychol Sci Soc Sci       Date:  2004-03       Impact factor: 4.077

3.  The natural frequency of human prospective memory increases with age.

Authors:  Robert S Gardner; Giorgio A Ascoli
Journal:  Psychol Aging       Date:  2015-03-23

4.  Examining the Interplay of Processes Across Multiple Time-Scales: Illustration With the Intraindividual Study of Affect, Health, and Interpersonal Behavior (iSAHIB).

Authors:  Nilam Ram; David E Conroy; Aaron L Pincus; Amy Lorek; Amanda Rebar; Michael J Roche; Michael Coccia; Jennifer Morack; Josh Feldman; Denis Gerstorf
Journal:  Res Hum Dev       Date:  2014-05-14

5.  Age differences in everyday stressor-related negative affect: A coordinated analysis.

Authors:  Robert S Stawski; Stacey B Scott; Matthew J Zawadzki; Martin J Sliwinski; David Marcusson-Clavertz; Jinhyuk Kim; Stephanie T Lanza; Paige A Green; David M Almeida; Joshua M Smyth
Journal:  Psychol Aging       Date:  2018-12-13

Review 6.  Studying Within-Person Variation and Within-Person Couplings in Intensive Longitudinal Data: Lessons Learned and to Be Learned.

Authors:  Andreas B Neubauer; Florian Schmiedek
Journal:  Gerontology       Date:  2020-06-11       Impact factor: 5.140

7.  Eavesdropping on Missing Data: What Are University Students Doing When They Miss Experience Sampling Reports?

Authors:  Jessie Sun; Mijke Rhemtulla; Simine Vazire
Journal:  Pers Soc Psychol Bull       Date:  2020-12-21

8.  Measuring slips and lapses when they occur - ambulatory assessment in application to cognitive failures.

Authors:  Stefanie Lange; Heinz-Martin Süß
Journal:  Conscious Cogn       Date:  2013-12-31

9.  Aging ebbs the flow of thought: adult age differences in mind wandering, executive control, and self-evaluation.

Authors:  Jennifer C McVay; Matthew E Meier; Dayna R Touron; Michael J Kane
Journal:  Acta Psychol (Amst)       Date:  2012-12-20

10.  What is the subjective cost of cognitive effort? Load, trait, and aging effects revealed by economic preference.

Authors:  Andrew Westbrook; Daria Kester; Todd S Braver
Journal:  PLoS One       Date:  2013-07-22       Impact factor: 3.240

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