Data from the Victoria Longitudinal Study were used to examine the hypothesis that maintaining intellectual engagement through participation in everyday activities buffers individuals against cognitive decline in later life. The sample consisted of 250 middle-aged and older adults tested 3 times over 6 years. Structural equation modeling techniques were used to examine the relationships among changes in lifestyle variables and an array of cognitive variables. There was a relationship between changes in intellectually related activities and changes in cognitive functioning. These results are consistent with the hypothesis that intellectually engaging activities serve to buffer individuals against decline. However, an alternative model suggested the findings were also consistent with the hypothesis that high-ability individuals lead intellectually active lives until cognitive decline in old age limits their activities.

Age differences in three basic types of variability were examined: variability between persons (diversity), variability within persons across tasks (dispersion), and variability within persons across time (inconsistency). Measures of variability were based on latency performance from four measures of reaction time (RT) performed by a total of 99 younger adults (ages 17--36 years) and 763 older adults (ages 54--94 years). Results indicated that all three types of variability were greater in older compared with younger participants even when group differences in speed were statistically controlled. Quantile-quantile plots showed age and task differences in the shape of the inconsistency distributions. Measures of within-person variability (dispersion and inconsistency) were positively correlated. Individual differences in RT inconsistency correlated negatively with level of performance on measures of perceptual speed, working memory, episodic memory, and crystallized abilities. Partial set correlation analyses indicated that inconsistency predicted cognitive performance independent of level of performance. The results indicate that variability of performance is an important indicator of cognitive functioning and aging.

Intraindividual variability in latency and accuracy of cognitive performance across both trials and occasions was examined in 3 groups of older adults: healthy adults, adults with arthritis, and adults diagnosed with mild dementia. Participants completed 2 reaction-time and 2 episodic-memory tasks on 4 occasions. Results indicated that intraindividual variability in latency was greater in individuals diagnosed with mild dementia than in adults who were neurologically intact, regardless of their health status. Individual differences in variability were stable over time and across cognitive domains. Intraindividual variability was also related to level of performance and was uniquely predictive of neurological status, independent of level of performance. Results suggest that intraindividual variability may be a behavioral indicator of compromised neurological mechanisms.

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Two cross-sectional samples of adults were administered the 20-item Center for Epidemiological Studies-Depression Scale (CES-D). Confirmatory item factor analysis showed that RadlofFs (1977) four factor model fit the data well, but that the four factors were highly intercorrelated. A simultaneous second-order factor model fitting a single second-order Depression factor also fit well. Multiple group analyses of the first-order solution yielded invariant unstandardized item factor loadings across samples and age groups. A Cohort (Age) X Sex ANOVA on the total and subscale scores revealed lower total CES-D and subscale (Weil-Being and Depressive Affect) scores for older persons. The Somatic subscale showed no significant age differences. The results support the measurement validity of the CES-D for depression screening in older adult populations.Although it is widely recognized that depression is the most common mental health problem in the elderly, there is some confusion regarding whether there is also an age-related increase in the prevalence of depression. Recent studies have not supported the hypothesis of an age-related increase in either clinically diagnosed depression (Blazer, Hughes, & George, 1987) or depressive symptoms in adulthood (e.g., Radloff & Ten, 1986).A major issue involves the measurement properties of instruments assessing depression (Gallagher, Thompson, & Levy, 1980;Zarit, Eiler, & Hassinger, 1985). For example, several studies suggest that self-report measures of depression that include items measuring somatic manifestations of depression (e.g., fatigue, poor sleep, listlessness) may be artifactually elevated in the elderly because of somatic effects of physical illness, side effects of medications, and the like (Berry,