Pragmatic approaches to handling practice effects in longitudinal cognitive aging research

Abstract

INTRODUCTIONThe challenge of accounting for practice effects (PEs) when modeling cognitive change was amplified by the COVID‐19 pandemic, which introduced period and mode effects that may bias the estimation of cognitive trajectory.METHODSIn three Kaiser Permanente Northern California prospective cohorts, we compared predicted cognitive trajectories and the association of grip strength with cognitive decline using three approaches: (1) no acknowledgment of PE, (2) inclusion of a wave indicator, and (3) constraining PE based on a preliminary model (APM) fit using a subset of the data.RESULTSAPM‐based correction for PEs based on balanced, pre‐pandemic data, and with current age as the timescale produced the smallest discrepancy between within‐person and between‐person estimated age effects. Estimated associations between grip strength and cognitive decline were not sensitive to the approach used.DISCUSSIONConstraining PEs based on a preliminary model is a flexible, pragmatic approach allowing for meaningful interpretation of cognitive change.Highlights The magnitude of practice effects (PEs) varied widely by study. When PEs were present, the three PE approaches resulted in divergent estimated age‐related cognitive trajectories. Estimated age‐related cognitive trajectories were sometimes implausible in models that did not account for PEs. The associations between grip strength and cognitive decline did not differ by the PE approach used. Constraining PEs based on estimates from a preliminary model allows for a meaningful interpretation of cognitive change.

Timing and level of educational attainment and late‐life cognition in the KHANDLE study

“…23 This method allows for obtaining parameter estimates, even in the presence of missing data, by using each individual's available data to compute the maximum like- All models allowed for random intercepts and accounted for practice effects using model constraints based on prior analyses in this cohort. 24 An interaction term between the educational attainment change group and time was included to determine whether the rate of cognitive change differed according to the educational attainment change group. We used the fitted models to predict mean cognition over time for each educational attainment change group and plotted the corresponding trajectories averaged across all other baseline covariates.…”

Evaluation of racial and ethnic heterogeneity in the associations of sleep quality and sleep apnea risk with cognitive function and cognitive decline

“…All models restricted the possible range of effect estimates to correct for practice effects based on prior work in KHANDLE. 18 To facilitate the interpretation of findings, we compared associations of sleep apnea risk and sleep quality with cognitive function to the estimated age‐related differences in cognitive function.…”

“…For each sleep quality domain and cognitive outcome, we sequentially adjusted for the two sets of covariates as outlined in the previous section. All models restricted the possible range of effect estimates to correct for practice effects based on prior work in KHANDLE 18. To facilitate the interpretation of findings, we compared associations of sleep apnea risk and sleep quality with cognitive function to the estimated age-related differences in cognitive function.We evaluated heterogeneity in the associations of sleep apnea risk and sleep quality with level and decline in cognitive function, by stratifying the analyses by race and ethnicity.…”

Racial and ethnic differences in the association between depressive symptoms and cognitive outcomes in older adults: Findings from KHANDLE and STAR

“…We further adjusted for a wave indicator and the practice setting to account for practice effects. 34 To assess non‐linear associations of depressive symptoms with cognitive health, we used natural splines with three to four knots based on the Akaike information criterion. Finally, given the age difference between KHANDLE and STAR participants, and given that age is a known risk factor for cognitive function and decline, we further analyzed these associations only among KHANDLE participants.…”