Background: Frailty is considered highly prevalent in old age and to confer high risk for falls, disability, hospitalization, and mortality. Frailty has been considered synonymous with disability, comorbidity, and other characteristics, but it is recognized that it may have a biologic basis and be a distinct clinical syndrome. A standardized definition has not yet been established. 

Methods: To develop and operationalize a phenotype of frailty in older adults and assess concurrent and predictive validity, the study used data from the Cardiovascular Health Study. Participants were 5,317 men and women 65 years and older (4,735 from an original cohort recruited in 1989-90 and 582 from an African American cohort recruited in 1992-93). Both cohorts received almost identical baseline evaluations and 7 and 4 years of follow-up, respectively, with annual examinations and surveillance for outcomes including incident disease, hospitalization, falls, disability, and mortality. 

Results: Frailty was defined as a clinical syndrome in which three or more of the following criteria were present: unintentional weight loss (10 lbs in past year), self-reported exhaustion, weakness (grip strength), slow walking speed, and low physical activity. The overall prevalence of frailty in this community-dwelling population was 6.9%; it increased with age and was greater in women than men. Four-year incidence was 7.2%. Frailty was associated with being African American, having lower education and income, poorer health, and having higher rates of comorbid chronic diseases and disability. There was overlap, but not concordance, in the cooccurrence of frailty, comorbidity, and disability. This frailty phenotype was independently predictive (over 3 years) of incident falls, worsening mobility or ADL disability, hospitalization, and death, with hazard ratios ranging from 1.82 to 4.46, unadjusted, and 1.29-2.24, adjusted for a number of health, disease, and social characteristics predictive of 5-year mortality. Intermediate frailty status, as indicated by the presence of one or two criteria, showed intermediate risk of these outcomes as well as increased risk of becoming frail over 3-4 years of follow-up (odds ratios for incident frailty = 4.51 unadjusted and 2.63 adjusted for covariates, compared to those with no frailty criteria at baseline). 

Conclusions: This study provides a potential standardized definition for frailty in community-dwelling older adults and offers concurrent and predictive validity for the definition. It also finds that there is an intermediate stage identifying those at high risk of frailty. Finally, it provides evidence that frailty is not synonymous with either comorbidity or disability, but comorbidity is an etiologic risk factor for, and disability is an outcome of, frailty. This provides a potential basis for clinical assessment for those who are frail or at risk, and for future research to develop interventions for frailty based on a standardized ascertainment of frailty.

https://www.sharp.com/services/hospice/upload/phenotype5-13.pdf

Frailty in Older Adults Evidence for a Phenotype

Despite the concern that has been expressed about potential method biases, and the pervasiveness of research settings with the potential to produce them, there is disagreement about whether they really are a problem for researchers in the behavioral sciences. Therefore, the purpose of this review is to explore the current state of knowledge about method biases. First, we explore the meaning of the terms “method” and “method bias” and then we examine whether method biases influence all measures equally. Next, we review the evidence of the effects that method biases have on individual measures and on the covariation between different constructs. Following this, we evaluate the procedural and statistical remedies that have been used to control method biases and provide recommendations for minimizing method bias.

Sources of Method Bias in Social Science Research and Recommendations on How to Control It

because observed behavior is the result of interactions between environmental factors and genes during the extended period of development. Therefore, to better understand expert and exceptional performance, we must require that the account specify the different environmental factors that could selectively promote and facilitate the achievement of such performance. In addition, recent research on expert performance and expertise (Chi, Glaser, & Farr, 1988; Ericsson & Smith, 1991a) has shown that important characteristics of experts' superior performance are acquired through experience and that the effect of practice on performance is larger than earlier believed possible. For this reason, an account of exceptional performance must specify the environmental circumstances, such as the duration and structure of activities, and necessary minimal biological attributes that lead to the acquisition of such characteristics and a corresponding level of performance. An account that explains how a majority of individuals can attain a given level of expert performance might seem inherently unable to explain the exceptional performance of only a small number of individuals. However, if such an empirical account could be empirically supported, then the extreme characteristics of experts could be viewed as having been acquired through learning and adaptation, and studies of expert performance could provide unique insights into the possibilities and limits of change in cognitive capacities and bodily functions. In this article we propose a theoretical framework that explains expert performance in terms of acquired characteristics resulting from extended deliberate practice and that limits the role of innate (inherited) characteristics to general levels of activity and emotionality. We provide empirical support from two new studies and from already published evidence on expert performance in many different domains.

/pdf/the-role-of-deliberate-practice-in-the-acquisition-of-expert-3j9768t5su.pdf

The role of deliberate practice in the acquisition of expert performance.

Recent studies of eye movements in reading and other information processing tasks, such as music reading, typing, visual search, and scene perception, are reviewed. The major emphasis of the review is on reading as a specific example of cognitive processing. Basic topics discussed with respect to reading are (a) the characteristics of eye movements, (b) the perceptual span, (c) integration of information across saccades, (d) eye movement control, and (e) individual differences (including dyslexia). Similar topics are discussed with respect to the other tasks examined. The basic theme of the review is that eye movement data reflect moment-to-moment cognitive processes in the various tasks examined. Theoretical and practical considerations concerning the use of eye movement data are also discussed.

/pdf/eye-movements-in-reading-and-information-processing-20-years-3z5ay8hdwc.pdf

Eye movements in reading and information processing: 20 years of research.

A theory is proposed to account for some of the age-related differences reported in measures of Type A or fluid cognition. The central hypothesis in the theory is that increased age in adulthood is associated with a decrease in the speed with which many processing operations can be executed and that this reduction in speed leads to impairments in cognitive functioning because of what are termed the limited time mechanism and the simultaneity mechanism. That is, cognitive performance is degraded when processing is slow because relevant operations cannot be successfully executed (limited time) and because the products of early processing may no longer be available when later processing is complete (simultaneity). Several types of evidence, such as the discovery of considerable shared age-related variance across various measures of speed and large attenuation of the age-related influences on cognitive measures after statistical control of measures of speed, are consistent with this theory.

http://www.anitacrawley.net/Resources/Articles/salthouse%20The%20Processing%20Speed%20Theory%20of%20Adult%20Age%20Differences%20in%20Cognition.pdf

The processing-speed theory of adult age differences in cognition.

Much of the current research in the area of cognitive aging has been focused on investigating specific processes presumed to be responsible for the age differences observed in particular cognitive tasks A central thesis of this article is that age-related effects on cognitive variables seldom occur in isolation, and hence, they are best interpreted in the context of the structural interrelations that exist among variables and the relations of age on that organizational structure Results from analyses of 2 separate data sets suggest that large proportions of the age-related effects across a wide range of cognitive variables are shared and that independent, or unique, age-related effects often contribute relatively little to the age differences observed in many cognitive variables These findings imply that it is important to consider the structure within which a variable occurs when attempting to investigate the processes responsible for age-related differences on that variable

/pdf/structural-constraints-on-process-explanations-in-cognitive-41ok8qyzun.pdf

Structural constraints on process explanations in cognitive aging.

When multiple cognitive abilities are assessed in the same individuals it is possible to compare profiles based on the relative levels of different abilities. For example, Figure 1 portrays the mean levels (expressed in z-score units) of four cognitive abilities for two adults age 44 and 47 years of age. Despite having nearly identical overall means, the two individuals had markedly different ability profiles, with the 44-year-old having a more heterogeneous profile than the 47-year-old. A convenient way to represent differences in profiles is in terms of the standard deviation across the four abilities, and it can be seen that one of these individuals had a standard deviation of .21 whereas the other had a standard deviation of .94. The major questions in this report are whether this measure of within-person across-ability variability is higher at an initial occasion in individuals who subsequently experience large cognitive decline, and whether it is related to age in healthy adults.



Figure 1

Illustration of ability profiles for two participants with nearly the same average level of cognitive performance. The z-score for speed in the 47-year-old was zero, and thus the value is not apparent in the figure.



Because they may reflect different phenomena, and could have different causes and consequences, it is important to distinguish different types of within-person variability. Each type is expressed relative to the individual’s own mean, but they differ in that the variability can be across trials within the same test, across sessions with the same test, or across different tests. The focus in this report is on the latter form of variability, namely, the heterogeneity of different cognitive abilities in the same individual, and not inconsistency of the individual’s performance across repetitions of trials within the same test, or inconsistency of the individual’s performance of the same test across separate sessions.

Interest in ability profiles has a long history in psychological assessment (e.g., Matarazzo et al., 1988; Matarazzo & Prifitera, 1989), but there has been a recent resurgence of interest in this topic for both theoretical and empirical reasons. One theoretical reason is that the multivariate information inherent in across-test variability has been postulated to be a more sensitive indicator of cognitive status than the measures from any single domain (Kliegel & Sliwinski, 2004). Another theoretical speculation is that greater across-domain variability may reflect poor sustained cognitive control, and/or allocation of resources across different types of cognitive tests (Morgan et al., 2012a). Still another proposal is that within-person variability might be an indirect measure of neural connectivity (Reichenberg et al. 2006). That is, if different brain regions are involved in different types of cognitive abilities (e.g., Colom et al., 2009; Jung & Haier, 2007), weaker structural or functional connectivity among regions could diminish the spread of influences across abilities and contribute to greater distinctiveness of ability profiles.

The major empirical reason for the interest in across-ability variability is that several reports have found greater variability in clinical groups, such as schizophrenics (Reichenberg et al. 2006), patients positive for HIV (Morgan et al., 2011, 2012b), patients with hepatitis C (Morgan et al., 2012a), patients with dementia (Reckess et al., 2013), athletes after a sports-related concussion (Rabinowitz & Arnett, 2013), and individuals with low functional status (Rapp et al., 2005). There are also reports of higher within-person variability for individuals who subsequently develop cognitive pathologies (Holtzer et al., 2008; Kliegel & Sliwinski, 2004). Taken together, these findings suggest that the distinctiveness or heterogeneity of cognitive ability profiles may convey important information about an individual’s cognitive status.

Results of two studies are described in the current report. The first study examined the predictive power of across-domain variability at the initial occasion on subsequent cognitive change in older adults. The second study examined properties of within-person variability among healthy adults across a wide age range in both cross-sectional and longitudinal comparisons.

Several issues need to be considered when examining group differences in within-person variability. First, although it is desirable that the variability reflect a number of different domains of cognitive functioning, it may be misleading to include tests of acquired knowledge in the computations because tests of knowledge reflect the products of processing carried out earlier in life rather than efficiency or effectiveness of processing at the time of assessment. Furthermore, the existence of different age trends in product and process measures may introduce artifactual decreases followed by increases in relations of age to within-person variability as ability levels first converge and then diverge with increased age. Vocabulary or other measures of knowledge have sometimes been used as a reference to compare with other cognitive measures because they have been postulated to reflect early-life intelligence (Christensen et al., 1999; Rabbitt, 1993), but their inclusion in the computation of across-ability variability should either be avoided, or implemented with caution.

Second, because variability will likely be lowest near the floors and ceilings of measurement, there may be an inverted-U function relating variability to mean performance. It is therefore important to control for the mean when analyzing group differences in variability if the groups differ in average level of performance.

And third, although variability could be computed across scores on individual tests, the resulting variability measure will include measurement error and influences of characteristics of specific tests in addition to those of relevant abilities. However, influences of the relevant ability can be emphasized, and reliability increased, by conducting analyses on composite scores instead of scores of individual tests.

/pdf/heterogeneous-ability-profiles-may-be-a-unique-indicator-of-5303t0ym06.pdf

Heterogeneous ability profiles may be a unique indicator of impending cognitive decline.

Two experiments were conducted to determine whether young and old adults differ in the rate of a hypothetical internal clock. Clock rate was measured as the slope of the function relating actual duration to perceived duration. No age differences were apparent when subjects were asked to judge the duration of a flash of light in Exp. I, or to judge the duration of a dark interval between two light flashes in Exp. II. It was concluded that there is no evidence to support the hypothesis that perceptual and motor speed differences associated with increased age can be attributable to a slower rate of internal time.

Adult Age and the Rate of an Internal Clock

Although cross-sectional (between-person) comparisons consistently reveal age-related cognitive declines beginning in early adulthood, significant declines in longitudinal (within-person) comparisons are often not apparent until age 60 or later. The latter results have led to inferences that cognitive change does not begin until late middle age. However, because mean change reflects a mixture of maturational and experiential influences whose contributions could vary with age, it is important to examine other properties of change before reaching conclusions about the relation of age to cognitive change. The present study was designed to examine measures of the stability, variability, and reliability of change, as well as correlations of changes in memory with changes in speed in 2,330 adults between 18 and 80 years of age. Despite substantial power to detect small effects, the absence of significant age differences in these properties suggests that cognitive change represents a qualitatively similar phenomenon across a large range of adulthood.

/pdf/continuity-of-cognitive-change-across-adulthood-41c1fhcdq2.pdf

Continuity of cognitive change across adulthood.

Adult age differences in Wisconsin Card Sorting Test (WCST) measures were examined before and after statistical control of age-related differences in measures of feedback usage, working memory, and perceptual-comparison speed. The proportion of age-related variance associated with a summary measure of WCST performance was greatly reduced after controlling for measures of feedback usage, working memory, and perceptual-comparison speed. Furthermore, the age-related variance associated with the feedback-usage measure was reduced after controlling for working memory and perceptual-comparison speed measures. These results are consistent with the idea that age-related performance differences in the WCST are partially mediated by adult age differences in feedback usage and that age differences in feedback usage are mediated by age differences in working memory, which are in turn-mediated by age-related reductions in processing speed, indexed by measures of perceptual-comparison speed.

Examination of age-related deficits on the Wisconsin card sorting test

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