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.

Neural Correlates of Age-Related Slowing

The influence of increasing the requirements of a later RT task upon the performance of an earlier RT task was investigated in two experiments. The first experiment controlled the probability of the occurrence of the second reaction signal and the second experiment manipulated the complexity of the second task by introducing alternative distractor events to the reaction signal. The results of both experiments were interpreted as supporting a shared processing capacity theory of human performance in which the allocation of ‘preparation’ or ‘concentration’ is distributed in accordance with the demands of the component tasks.

Human Performance as a Function of Future Demands.

Data from a computer‐administered symbol digit substitution task were analyzed to determine the causes and consequences of age‐related differences on this task. Causal variables are assumed to be those that are associated with a reduction in the age‐related variance in symbol digit performance when they are controlled by statistical means. Consequences are inferred by the amount of reduction in the age‐related variance in other variables when symbol digit performance is statistically controlled. Consistent with the results of other studies, perceptual comparison speed was found to share considerable age‐related variance with speeded substitution performance, which in turn was found to share considerable age‐related variance with measures of memory functioning.

Causes and consequences of age-related slowing in speeded substitution performance

Three reaction time (RT) experiments using a modified Sternberg procedure were conducted to determine the number of memory representations maintained for perceptual (dot-pattern) concepts. The difference in RT to test stimuli from memory sets of different sizes was used to infer whether one, or more than one, memory representation was utilized for the perceptual concepts. It was concluded that multiple specific representations are utilized in early stages of experience with stimuli but that a single generic representation serves to represent the concept information after moderate amounts of experience.

/pdf/number-of-memory-representations-in-perceptual-concepts-2g51mybe7e.pdf

Number of Memory Representations in Perceptual Concepts.

The primary goal of Greenwood’s (2007) article is to account for the puzzling paradox that, compared with young adults, older adults have been found to exhibit increased functional neuroim-aging activation in the same brain regions that exhibit the greatest amount of age-related atrophy. In somewhat oversimplified terms, her suggestion is that neurobiological degeneration in specific brain regions results in deficits in cognitive performance, and these trigger changes in strategy that are associated with functional reorganization. She then suggests that one manifestation of this functional reorganization is increased neural activation in the brain region undergoing degeneration. I believe that these speculations are intriguing, and my commentary is primarily composed of questions stimulated by the article.

I will begin with a few general comments and then turn my focus to more specific issues. First, it may be useful to distinguish between a framework and a hypothesis because the former is a set of related assumptions that guide research, whereas the latter is associated with a specific prediction. Hypotheses can therefore be falsified by empirical results, whereas frameworks simply become less useful as inconsistent findings accumulate. Although she refers to her speculations as a hypothesis, I suggest that Greenwood is actually proposing a framework rather than a hypothesis because many critical details necessary for specific predictions are missing.

Second, if the hypothesis (framework) is intended to account for the aging of cognition, then it is important to specify exactly what occurs with age and why. The speculations would still be interesting if the proposed linkages were found to exist at all ages, but in that case they would not necessarily be specific to aging. It is possible that the patterns of relations are qualitatively different at different ages; another possibility is that people of different ages merely differ in the prevalence of the triggering conditions, in which case there might be nothing in the speculations that is intrinsic to aging. A related issue concerns the suggestion that “functional plasticity alters the course of cognitive aging” (p. 659). This statement seems to imply that the relation between age and cognitive functioning would be different if functional plasticity did not occur, but this might not be the case if “functional plasticity” is possible at all ages and is associated with increases in the level of performance without altering the relation between age and performance.

The remainder of this commentary consists of questions about the major relations in the hypothesis (framework). The first postulated relation is a linkage between atrophy and performance deficits. Among the questions related to this linkage are the following:

Does atrophy refer to only a reduction in brain volume, or does it apply to a variety of possible determinants of volumes, including cortical thinning, dendritic regression, and so on? Brain volume, and even regional brain volume, is a very crude variable because there could be many functional changes prior to, or possibly independent of, any volume changes. Furthermore, not all of the factors that affect volume are involved in cognitive functioning, and therefore it is important to know which neurobiological changes are considered critical in triggering the other postulated relations.

Is it the absolute volume that is important in the link with cognitive deficits and plasticity, or is it reduction over time that is critical? If it is absolute volume, then do the other relations in the hypothesis (framework) apply to any case in which brain volumes might differ? If so, could these cases perhaps include contrasts of female with male brains, since the former tend to be smaller?

Does the time course of the atrophy matter? That is, would the consequences be the same with a sudden dramatic decline in regional “brain integrity” such as that associated with a stroke and with slow gradual decline that takes place over a period of decades?

The “apparently weak relationship between regional atrophy and cognitive performance in old age” (p. 667) is interpreted as consistent with the assumption that other factors (such as plasticity) are operative at older ages. However, there is little evidence for this differential relation, and it is not clear how a failure to find a significant difference in volume–cognitive performance relations across age groups with comparisons of adequate power would lead to changes in the hypothesis (framework).

The second postulated relation links performance deficits to strategy changes as well as to functional plasticity in the atrophied region and in the parietal and prefrontal cortices. Some of the questions about this relation are the same as those raised about the first relation. For example, is it merely low performance or also a decrease in performance over time that triggers the new strategy or the functional plasticity? Is the time course important, with the same consequence for a sudden deficit as for one that occurs gradually over decades?

What is it about a low level of performance that instigates these changes—is it a conscious and deliberate attempt to overcome the performance deficit, or is it an automatic and unconscious adaptation?

How can the existence of a strategy be determined? Strategies can be considered optional methods of performing a given task, but if other methods of performing the task are no longer possible because of deterioration of the neurobiological substrate, should the only available mode of performance still be considered a strategy? Is it necessary to establish that other modes of performance are within the capability of the individual before using the term strategy?

Perhaps the most important question in the framework is the following: If the strategy (or functional plasticity) is within the capability of the individual and is beneficial, then why was it not used at earlier periods in life or by anyone who is not performing at the maximum for any reason? One would normally expect that higher functioning individuals would be better able to develop and implement novel strategies, and thus it is surprising that individuals experiencing decline would be capable of formulating and using new strategies. Is it because increased age is associated with better utilization of cognitive or neural resources, and if so, what is the evidence for this?

What if high-density longitudinal assessments of performance and strategy (or plasticity) were available—would a failure to find a lead–lag relation among the constructs, with the presence of a deficit preceding the use of a strategy, be damaging to the hypothesis?

Similar questions can be raised about functional plasticity and its relations to reorganization and activation. More details are desirable about how plasticity (recruitment, task activation) contributes to improved cognitive performance, which is presumably necessary if the deficits are at least partially compensated as a consequence of the plasticity.

In conclusion, I believe that this article contains many intriguing speculations, but as is almost always the case with new ideas, much remains to be done to elaborate the proposed linkages and convert a somewhat vague framework into a set of specific hypotheses with explicit falsifiable predictions. However, the mere fact that the article has stimulated many questions that might not otherwise be asked can be considered evidence that it has made a contribution to scientific progress.

Comment on Greenwood (2007): functional plasticity in cognitive aging.

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