A Comprehensive Comparison of Quantifications of Intraindividual Variability in Response Times: A Measurement Burst Approach

Stawski, Robert S.; MacDonald, Stuart W. S.; Brewster, Paul; Muñoz, Elizabeth; Cerino, Eric; Halliday, Drew

doi:10.1093/geronb/gbx115

Cited by 45 publications

(48 citation statements)

References 25 publications

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“…Thus, the RTI metric is in T-score units, with a single point on this scale reflecting 1/10 of an SD. The residualized ISD has numerous advantages over alternative quantifications; beyond being one of the most oft-used indicators of RTI, it also statistically controls for potential confounds including learning, practice effects, and individual differences in average RT (32,42). Further, previous research has shown that the residual ISD from a choice RT task exhibits adequate reliability and predictive validity with as few as 20 trials (25) and is a valid index across adulthood and older age (43).…”

Section: Methodsmentioning

confidence: 99%

“…Although correlated with standardized measures of neuropsychological status and cognitive ability, RTI shows unique sensitivity and clinical utility for predicting cognitive decline, cognitive impairment, and mortality (24). As such, it is potentially more sensitive for detecting subtle variations in processing efficiency, attributable to durable gradations in cognitive status and central nervous system integrity, as well as more transient fluctuations attributable to contextual influences such as daily stress processes (30–32).…”

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confidence: 99%

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Daily Stress Processes as Contributors to and Targets for Promoting Cognitive Health in Later Life

et al. 2019

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Objective: The aim of this study was to test the hypothesis that daily stress processes, including exposure and emotional reactivity to daily stressors, are associated with response time inconsistency (RTI), an indicator of processing efficiency and cognitive health. Furthermore, we considered daily stress-cognitive health associations at the level of individual differences and within-persons over time. Methods: Participants were 111 older adults (Mean=80 years, Range=66–95) enrolled in a measurement burst study where assessments of response-time based cognitive performance, stressful experiences, and affect were administered on each of 6 days over a two-week period. This protocol was repeated every six months for 2.5 years. Multilevel modeling was used to examine frequency of stressor exposure, non-stressor affect, and affect reactivity to daily stressors as individual difference and time-varying predictors of RTI. Results: Between-persons, higher levels of non-stressor negative affect (b=0.41, 95%CI: −0.01, 0.83, p=.055) and negative affect reactivity (b=0.80, 95%CI: 0.18, 1.42, p=.012) were associated with greater RTI. Within-persons over time, higher levels of negative affect (b=0.20, 95%CI: 0.06, 0.34, p=.006) and negative affect reactivity (b=0.13, 95%CI: 0.02, 0.24, p=.018) were associated with increased RTI among the oldest portion of the sample, while higher levels of positive affect (b=−0.11, 95% CI: −0.21, −0.02, p=.019) were associated with reduced RTI. Conclusions: Negative affect reactions to daily stressors are associated with compromised RTI both between- and within-persons. Findings suggest that emotional reactions to daily stressors contribute to compromise older adults’ cognitive health, while increased positive affect may be beneficial.

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Section: Methodsmentioning

confidence: 99%

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confidence: 99%

Daily Stress Processes as Contributors to and Targets for Promoting Cognitive Health in Later Life

et al. 2019

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“…The simplest of these is the intra-individual standard deviation (iSD), which is calculated as the standard deviation across standardized scores of different tasks for a single individual. This measure can be problematic when there are significant systematic group differences in average level of performance, as greater means tend to be associated with bigger variance ( Hale et al, 1988 ; Stawski et al, 2017 ). This can represent a serious confound in the case of comparison of performance between age-groups.…”

Section: Methodsmentioning

confidence: 99%

Intra-Individual Variability Across Fluid Cognition Can Reveal Qualitatively Different Cognitive Styles of the Aging Brain

Felice

Holland

2018

Front. Psychol.

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Dispersion is a measure of intra-individual variability reflecting how much performance across distinct cognitive functions varies within an individual. In cognitive aging studies, results are inconsistent: some studies report an increase in dispersion with increasing age and decline in performance, while others report an increasingly homogenous cognitive profile in older adults. We propose that inconsistencies may reflect qualitative differences in the cognitive functioning of the aging brain: age-groups may differ in how efficiently they engage resources, depending on both executive processing and resources available. This in turn would result in either greater or less dispersion. 21 young (mean 25.14 years, SD ± 2.85), 21 middle-old (65.05 ± 4.19), and 20 old-old (80.65 ± 4.38) healthy adults completed a series of neuropsychological tasks engaging executive processing, including switching, planning, updating, working memory and short-term memory. Individual dispersion profiles were obtained using a regression method which computes individual standard deviation across tasks from standardized test scores. Results revealed associations between performance, dispersion and cognitive reserve (measured as education level). Although differences across groups did not approach significance, there was a general pattern consistent with existing literature showing greater dispersion in the old-old group, and this was negatively associated with performance. In contrast, the middle-old group showed young-equivalent dispersion index, while performance was similar to the young group on some tasks and to the old-old group on others, possibly reflecting differences in cognitive demand. Educational level positively correlated with performance in the middle-old group only. Overall, a distinct pattern emerged for the middle-old adults: they showed young-equivalent performance on a number of measures and similar dispersion index, while uniquely benefitting from cognitive reserve. This may possibly reflect engagement in compensatory mechanisms. This study contributes to clarifying inconsistencies in previous studies and calls for more thoughtful selection of sample cohorts in aging research. The study of dispersion may provide a behavioral index of age-related changes in how cognition functions and recruits resources. Future work could examine whether this also reflects age-related changes in neural recruitment and aim at identifying factors contributing to cognitive reserve, in order to prolong good performance and improve cognition in aging.

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“…Third, while prior TestMyBrain.org sample studies have been replicated compared to traditionally collected and nationally representative US samples (Germine et al, 2011;Hartshorne and Germine, 2015), further validation work is recommended. Finally, our very brief measures of simple and choice RT were sufficient to produce reliable measures of psychomotor response speed, but did not allow us to employ more sophisticated model fitting techniques to trial-by-trial data that have been used in other studies of RT variability, such as estimation of multiple components of variability using an ex-Gaussian distribution (see McAuley et al, 2006;Matzke and Wagenmakers, 2009) or estimation of variability over longer time intervals, such as in a measurement burst design (Stawski et al, 2019).…”

Section: Discussionmentioning

confidence: 99%

“…Here, we focus on variability in RTs within a task, rather than variability across trials within the same session (dispersion) or variability in scores at different timepoints (e.g., longitudinal variability, measurement burst designs, or ecological momentary assessment). While the latter forms of variability are potentially important and informative (e.g., Bielak et al, 2010;Stawski et al, 2019), they are related to fluctuations along longer time scales (hours, days, years) rather than the moment-to-moment variability we focus on for the purposes of this study. Future work might clarify whether within task RT variability that we examined here produces similar findings to measures of variability examined along longer time scales for choice and simple RT data (e.g., in ecological momentary assessment designs).…”

Section: Introductionmentioning

confidence: 99%

Heterogeneous Indicators of Cognitive Performance and Performance Variability Across the Lifespan

Rutter

Vahia

Forester

et al. 2020

Front. Aging Neurosci.

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Reaction time (RT) and RT variability are core components of cognitive performance that can be captured through brief and easy-to-administer tasks of simple RT and choice RT. The current study aims to describe age-related differences in cognitive performance, toward better characterizing normative performance across the lifespan. We examined mean and variability of response times on a simple RT and choice RT tasks in a large and diverse web-based sample (10,060 visitors to TestMyBrain.org). We also examined lifespan-related differences in response time variability using multiple different approaches (raw variability, mean scaled variability, and mean residualized variability). These analyses revealed significant heterogeneity in the patterns of agerelated differences in performance, across metrics and within different estimates of the same metric. Based on segmented regression analysis, age of peak performance differed significantly across metrics, with young adults having the best performance based on measures of median RT, middle age adults at peak on certain measures of RT variability (standard deviation and coefficient of variability), and older adults showing the best performance based on accuracy and mean-corrected RT variability. Our results indicate that no single measure of cognitive performance and performance variability produces the same findings with respect to age related change, with further work needed to establish the validity of particular metrics for different applications.

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A Comprehensive Comparison of Quantifications of Intraindividual Variability in Response Times: A Measurement Burst Approach

Abstract: RTI reflects a novel dimension of performance that is a robust and theoretically informative predictor of BP and WP variation in cognitive function. Among the plenitude of RTI quantifications, not all are interchangeable, nor of comparable predictive utility.

Cited by 45 publications

References 25 publications

Daily Stress Processes as Contributors to and Targets for Promoting Cognitive Health in Later Life

Daily Stress Processes as Contributors to and Targets for Promoting Cognitive Health in Later Life

Intra-Individual Variability Across Fluid Cognition Can Reveal Qualitatively Different Cognitive Styles of the Aging Brain

Heterogeneous Indicators of Cognitive Performance and Performance Variability Across the Lifespan

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