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. Author manuscript; available in PMC: 2023 Sep 28.
Published in final edited form as: Res Hum Dev. 2017 Aug 10;14(3):219–233. doi: 10.1080/15427609.2017.1340050

Cognitive Performance in Adults’ Daily Lives: Is There a Lab-Life Gap?

Allison AM Bielak 1, Cassandra R Hatt 1, Manfred Diehl 1
PMCID: PMC10538579  NIHMSID: NIHMS1932936  PMID: 37771386

Abstract

This article addresses the “lab-life gap” in cognitive aging research as an important issue of ecological validity in developmental research. Older adults often function competently in complex everyday situations despite age-related deficits on laboratory-based cognitive tasks. Therefore, to what extent do lab-based cognitive tasks predict real-life outcomes in older adults? Our review shows that although they are similar, measures of everyday cognitive competence predict relevant outcomes beyond basic measures. We provide our perspective on critical questions concerning the relevance of everyday cognitive tests in our ever-changing world, new methods of everyday cognitive assessment, and whether everyday cognition can be improved.

The typical cognitive assessment for a research study tends to resemble something akin to the following: The participant visits a university’s psychology department and is invited to sit in a standard office with a chair and a desk. After obtaining informed consent, the researcher administers tests of different cognitive domains one after the other, either on paper or on a computer screen. One test might involve prompting the participant to generate as many synonyms as possible to a particular word or write answers to various facts about the world. The experimenter might read or show lists of words for the participant to later recall or observe and time the participant’s drawing of a figure or completion of a maze. The session might last an hour or two. After scoring the various tests, the researcher would have a glimpse into the participant’s cognitive abilities, or at least how many words the participant can recall from a random word list. This method of testing provides information about lab-based cognition, or essentially how well a person can complete standardized cognitive tests in a controlled environment. This testing technique is recognized for its strict adherence to protocol and high internal validity. Across all participants, testing would be done in the same room, the same tests would be given, and the tests would be administered in the same order with the same instructions. But how well do cognitive results from this typical method of assessment resemble a person’s actual functional cognitive ability in everyday life?

Everyday cognition refers to the ability to solve cognitively complex tasks of daily life (Allaire & Gamaldo, 2017), or those that go beyond simple activities of daily living such as feeding or dressing oneself. Proxies for everyday cognition include psychological tasks asking participants to complete hands-on problems such as understanding a medication label (Marsiske & Willis, 1995). These tasks assess how well a person may complete a task embedded in a real-life context. Objective measures of everyday cognition are therefore considered to have high ecological validity, an aspect of external validity, where the results can be easily generalized to apply to life outside the lab environment. For example, how well people complete a question assessing their financial management skills is likely very similar to how they might fare in completing a similar financial task in their daily life.

Given that the two measurement types of cognition emphasize and highlight different types of validity, tests of lab-based cognition are therefore somewhat at odds with tests of everyday cognition in terms of their intended relevance and applicability. Cognitive aging researchers want to be able to detail how specific aspects of cognition change with age and are linked to other factors such as health, and using standardized tests in controlled lab environments, or “context-free,” allow us to do that. But everyday cognition aims to understand “cognition in context” or functioning in the real world, where we rarely have to do a task that involves only one type of cognitive ability. For example, consider how many cognitive processes might be involved in the decision to buy a new coat (Mason, 2011). Mathematical skills would first be involved as a person calculates the added tax, the true price with the added sale discount, and finally if she can afford it. Problem solving might come into play in deciding whether to buy the coat now or wait until the winter is over and try to get the coat at a discount, risking the chance that the coat might be sold out. A person may use her creativity and sell a few of her current clothing items to get enough money for the coat, or she might make her own coat and have it resemble the coat she saw in the store. The act of buying a new coat involves many different cognitive resources and as such is very different from tasks typically assessed in a lab. Further, the ability to complete tasks of everyday life can rely on the advantages of routine and life-long experience.

How do we reconcile the two sides and seemingly disparate aspects of cognitive assessment? The debate between everyday cognition and lab-based cognitive assessment is not new. The book Everyday Cognition in Adulthood and Late Life included arguments from experts that were at times contradictory to one another regarding the pros and cons for studying cognition outside the laboratory (Rubin, 1989). Further, it becomes more difficult to identify the factors underlying between-person differences in cognitive functioning as cognitive tasks become more complex to reflect everyday life. The present article first reviews the evidence to date on everyday cognition in relation to assessment, performance, and associations with lab-based cognitive tasks. We then provide our perspective on critical questions concerning the relevance of everyday cognitive tests, new methods of how it may be assessed, and whether everyday cognition can be improved via traditional cognitive training. Of note, the entire article is written with the lens of considering ecological validity.

To clarify, everyday cognition is one of two branches of everyday problem solving (Allaire & Gamaldo, 2017). Everyday problem solving addresses a person’s ability to solve any type of real-life problem, with one branch focusing on socioemotional problem solving (i.e., problems of a social or affective nature), and the other branch of everyday cognition concentrating on the ability to solve problems required for everyday functioning or instrumental tasks of daily life (Allaire, 2012). The present article focuses on everyday cognition and evaluates it as a whole.

REVIEW—WHAT DO WE KNOW?

Evaluation of Everyday Cognition and Their Link With Lab-Based Cognition

Despite well-documented age-related declines in performance on lab-based cognitive tests, there is little corresponding decline in older adults’ ability to manage their daily lives (Bielak, 2017b; Salthouse, 2012). This discrepancy has been addressed by the creation of tests that assess older adults’ ability to solve complex problems in everyday contexts (Diehl, Willis, & Schaie, 1995). The call for measures of everyday cognition arose out of concern of the ecological validity of traditional laboratory measures of cognition (Denney, 1989).

The call for greater ecological validity in cognitive testing resulted in two disparate theoretical approaches, an ill-defined approach, and a well-defined approach (Allaire, 2012; Allaire & Marsiske, 2002). This article focuses on the well-defined approach, or assessments of everyday cognition that require a specific kind and sequence of problem-solving steps to lead to the correct solution. In particular, the tasks of instrumental activities of daily living (IADL) have been analyzed in terms of their cognitive components and demands (Diehl et al., 1995) and have served as tasks with high ecological validity. Although the successful performance of IADL-based tasks of everyday cognition also depends to some extent on noncognitive factors (e.g., motivation, mobility, and manual dexterity), older adults’ performance on these tasks has shown robust and replicable associations with traditional lab-based measures of cognition. We acknowledge however, that other researchers (e.g., Cornelius & Caspi, 1987) have studied adults’ everyday problem solving using the ill-defined approach, where the tasks do not insist on a singular correct solution but rather acknowledge that in practical everyday situations different solutions can be equally efficient and reached in a number of different ways.

There are three reasons for focusing on the well-defined approach. First, this approach is grounded in the psychometric and experimental traditions of cognitive aging research (Allaire & Marsiske, 2002), whereby the measures have adopted similar principles and procedures, allowing for valid comparisons with findings based on laboratory tests. Second, the well-defined approach assumes that many of the everyday problems encountered by older adults are highly structured and have a single, most efficient solution (Willis & Schaie, 1993). Everyday tasks that meet these criteria and are of high practical relevance for older adults’ ability to live independently are the IADLs (Lawton & Brody, 1969). Thus, many of the measures of everyday cognition have incorporated tasks related to activities critical for independent living, such as food preparation. Third, studies that have used this approach often specifically evaluate to what extent and in what ways older adults’ performance on tasks of everyday cognition is related to basic cognitive abilities and age-related changes in those abilities.

Although the number of measures of everyday cognition has increased in recent years, we only describe a select subset of the available tests to illustrate their general approach. The featured measures have several things in common: First, their content focuses on instrumental activities that adults must be able to perform to function independently. Second, the problem to be solved is usually clearly stated and a most effective answer can be scored. Third, all of the tests use real-world stimuli that are similar to those older adults encounter in their everyday lives, such as nutrition labels or the instructions on a medicine bottle. Thus, the ecological validity of these measures rests on their relevance for predicting older adults’ actual ability to perform IADLs effectively without any assistance and over time. For example, Diehl et al. (1995) reported a significant association between performance on the Observed Tasks of Daily Living (OTDL) and self-reported IADL limitations 12 months later.

One of the first everyday cognition measures was the Everyday Problems Test (EPT; Marsiske & Willis, 1995). The EPT is a paper-and-pencil test that uses everyday printed materials (e.g., food labels, bus schedules) to assess adults’ ability to solve problems in seven domains: food preparation, medication and health, telephone use, shopping and consumerism, financial management, housekeeping, and transportation. Another measure similar to the EPT is the Everyday Cognition Battery (ECB; Allaire & Marsiske, 1999). The ECB also uses real-world printed stimuli but only focuses on three specific instrumental activities (i.e., medication use, financial management, food preparation/nutrition) and on the real-world manifestation of three cognitive abilities (i.e., memory, inductive reasoning, and knowledge).

Although the EPT and ECB represent important measures of everyday problem solving, their administration reveals little about the actual behavior that older adults may use while solving the problems. This critical issue has been addressed by two observational measures of everyday problem solving. The first, the OTDL (Diehl et al., 1995), consists of 31 tasks in the areas of food preparation, medication use, and telephone use. Using real-world objects, the tasks of the OTDL were designed to simulate actual tasks of daily living and have distinct observable elements permitting objective scoring of problem solving behavior. The second observational measure, the Timed Instrumental Activities of Daily Living (TIADL; Owsley, Sloane, McGwin, & Ball, 2002), consists of five timed tasks (i.e., finding a telephone number in a directory, making change, finding and reading the ingredients on a can of food, finding food items on a shelf, and reading instructions on a medicine container). Like the OTDL, the TIADL uses real-world props but is administered under timed conditions. The rapid and efficient completion of the tasks is viewed as an advantage in daily life and was hence emphasized by the test developers.

An important question, both from theoretical and empirical perspectives, is the extent to which the described measures of everyday problem solving are distinct from or similar to measures of basic cognitive abilities. Although some authors (Sternberg & Wagner, 1986) have argued that everyday cognition or practical intelligence should be distinct from and unrelated to traditional psychometric measures of cognition, most of the evidence suggests otherwise. For example, cross-sectional studies reported that large amounts of variance (i.e., as much as 80%) in everyday cognition tasks were accounted for by basic cognitive abilities such as memory and inductive reasoning ability (Allaire & Marsiske, 1999; Diehl et al., 1995). There is also fairly convincing evidence that the associations between these two types of cognition are organized in a hierarchical fashion (Diehl et al., 1995; Willis & Schaie, 1986). That is, cognitive abilities measured in the lab with traditional cognitive tests (e.g., processing speed, reasoning) are the basic abilities on which individuals draw to solve everyday problems. Also, the relevant “mix” of these basic cognitive abilities varies by everyday cognitive task and is usually reflected in the amount of variance that is accounted for by the respective cognitive ability.

Similarly, several longitudinal studies have shown that longitudinal change in measures of everyday cognition shows a very similar shape to change in basic measures of cognition. Tucker-Drob (2011) found moderate to high correlations between individual differences in changes in lab-based cognition and individual differences in changes in everyday cognitive measures. Yam, Gross, Prindle, and Marsiske (2014) reported that level and slope in basic measures of inductive reasoning showed a close association to level and slope of measures of everyday cognition across a 10-year period. These findings suggest that there is considerable overlap between measures of basic cognitive abilities and measures of everyday cognition. At the same time however, the degree of overlap with lab-based cognitive performance is not perfect or complete. For example, though Burton, Strauss, Hultsch, and Hunter (2006) found that traditional cognitive measures significantly predicted EPT performance, over 50% of the variance remained unaccounted for. This underscores that although measures of everyday cognition are certainly capturing related lab-based cognitive skills and abilities, they also assess unique aspects of older adults’ cognition. Such unique aspects may include highly task-specific skills and knowledge, aspects of overlearned behavior, and possibly motivational factors that are relevant for everyday problem-solving tasks but are not activated in the context of traditional cognitive measures.

Adults’ Performance in Real-Life Tasks

In addition to using tests of everyday cognition, researchers have focused on specific tasks of everyday life that easily lend themselves to assessment. Of these tasks, two in particular have received a good deal of attention because of their relevance for independent living and sensitivity to age-related changes: medication-taking behavior and driving competence. These tasks serve as applied examples of how adults apply cognitive functions in the everyday world, and as such have high ecological validity.

Medication-taking behavior

In general, older adults have trouble comprehending and remembering medical information compared to younger individuals (Insel, Morrow, Brewer, & Figueredo, 2006). Multiple cognitive steps and processes are involved in the planning and implementation of medication-taking behavior (Bosworth & Ayotte, 2009) and declines in prospective memory in particular are a key risk factor for medication nonadherence in older adults (Woods et al., 2014).

However, cognitive processes are not the sole predictor of medication-taking behavior. Busyness in daily routines also influences successful medication adherence. Neupert, Patterson, Davis, and Allaire (2011) examined age differences in daily recall to take medication. They found that older adults were more likely to remember to take their medication on days they reported being less busy, whereas younger adults tended to adhere better when they were busier. Busyness may have a negative effect on older adults’ cognitive functions (e.g., it may increase forgetfulness due to greater cognitive load), and this in turn translates into poorer performance in terms of taking the medications as prescribed. Neupert et al. noted that older adults may have less busy routines in general, and a busy day may create a deviation from the contextual norm and increase the likelihood of nonadherence. Park et al. (1999) similarly showed that older adults with high cognitive performance and low levels of busyness had higher rates of medication adherence than middle-age adults who were busy. The research on medication-taking behavior demonstrates the importance of environmental demands in completing these tasks of everyday life, factors that are not taken into consideration in standardized tests of everyday cognition. Specifically, successful medication adherence in an adult’s daily life may be harder to achieve given the cognitive load demands of competing tasks, compared to successful completion of a medication type question on an everyday cognitive test that is completed in an isolated lab context. Therefore, distinct differences remain in the actual ecological validity of tests such as the EPT and OTDL, and tasks performed in real-life.

Driving competence

Driving a motor vehicle is a dynamic, contextual behavior that requires activation of multiple cognitive processes, and depending on the situation, these may vary and change in a very short amount of time. However, for most adults driving is a highly practiced behavior that may not be as influenced by lab-based cognitive declines as other everyday behaviors.

Anstey, Wood, Lord, and Walker (2005) reported that measures of attention, reaction time, memory, and executive and physical function were all associated with driving outcome measures in older adults. One of the notable tools for predicting driving ability in older adults is the Useful Field of View (UFOV) test (Ball et al., 2006). Attention and processing-speed are assessed via the visual UFOV test, conducted in a laboratory setting. UFOV performance has been associated with retrospective and prospective memory and is predictive of crashes and both on- and off-road (e.g., driving simulator) performance (Matas, Nettelbeck, & Burns, 2014).

However, there is evidence that adults adjust their driving behavior to self-perceived cognitive changes. Compared to younger drivers, older drivers maintained lower minimum speeds during hazardous conditions and drove at overall lower speeds in complex and attention-demanding situations (Andrews & Westerman, 2012). Older drivers may slow down and allow more time and space to make decisions on the road, possibly because they know they cannot respond to risky situations as quickly as younger individuals and consequently adopt strategies to give them a greater time window to assess and respond to these circumstances (Andrews & Westerman, 2012). Indeed, compared to younger adults, older adults perceived greater mental demands in all driving situations regardless of the context or difficulty (Bunce, Young, Blane, & Khugputh, 2012). Older adults also employ self-monitoring beliefs that influence their decision to drive in challenging situations (Andrews & Westerman, 2012). That is, they appear to alter their driving behaviors based on their beliefs of their competency in a number of different domains that might affect their ability to drive safely (Pachana & Petriwskyj, 2006). Thus, lack of insight into possible cognitive limitations may serve as a risk factor for poor driving performance and increased rate of crashes (Pachana & Petriwskyj, 2006).

The complexity of the driving experience is another contextual factor for consideration, as complex driving conditions (e.g., highway driving) may elicit greater attentional demands for older drivers and result in poorer performance (Stinchcombe, Gagnon, Zhang, Montembeault, & Bedard, 2011). Indeed, older drivers have been shown to have less spare attentional capacity, putting them at greater risk for accident involvement in unexpected driving situations (Bunce et al., 2012).

The real-life activities of medication adherence and driving not only serve as examples that basic cognitive abilities are significant predictors of performance in daily life, but also illustrate the critical importance of the environment on older adults’ cognitive performance. Therefore, the ability to take into account environmental influences may be a central issue for achieving ecologically valid measures of everyday cognition.

Self-Reports of Everyday Functioning

A third method of assessing everyday functioning is via self-report. Rather than observing performance on test questions that mimic IADLs, self-report relies on participants reporting their subjective difficulty in performing IADLs. Generally speaking, self-report measures are less reliable for assessing everyday cognition, especially among older adults. Older adults may have difficulty accurately evaluating their everyday competence (Diehl et al., 1995) and are specifically more prone to overestimating their competence, possibly due to lower metacognitive skills (Dunning, Heath, & Suls, 2004). Moreover, self-report assessments provide little information about the underlying causes of an older adults’ inability to perform specific daily tasks, limiting their predictive value (Lee, 2000).

Tucker-Drob (2011) examined the relationship between changes in three standardized measures of everyday cognition (i.e., EPT, OTDL, TIADL), changes in lab-based neurocognitive functioning, and self-reported difficulty in completing IADLs. Performance on the everyday function tests did covary with changes in cognitive performance, but rates of change for self-reported IADL difficulty did not significantly correlate with rates of change on the measures of everyday functioning. Tucker-Drob suggested older adults may be unable to accurately appraise everyday competencies and recognize changes in their ability to perform such tasks. Simply put, Tucker-Drob concluded that older adults are “poor judges of their own levels of functioning” (p. 376).

Link between Training of Everyday Cognition and Lab-Based Cognition

Measures of everyday cognition are suggested as key outcome variables in cognitive training studies to examine if observed training gains on basic cognitive abilities also transfer to performance on everyday tasks. However, there are few published reports of this link. The Advanced Cognitive Training for Independent and Vital Elderly (ACTIVE) intervention trial included measures of everyday cognition (i.e., EPT, OTDL, and TIADL) as key outcome variables to address this issue (Ball et al., 2002). Being able to show that training on basic cognitive abilities also transfers to cognitive performance in real-life contexts would provide additional evidence for the interrelatedness of these two types of cognition and, to some extent, for the ecological validity of traditional measures of adult cognition. As everyday cognitive tasks are believed to provide more ecological validity than lab-based tasks, improvements on tests of everyday cognition are perceived as more significant and likely to have an impact on an adults’ daily lives compared to noted improvements on traditional cognitive tests.

To date, the evidence supporting the notion that training-related improvements in basic cognitive abilities should also translate to improvements in everyday cognitive performance is sparse and rather mixed. For example, Ball et al. (2002) reported data from the ACTIVE trial showing that though there had been significant training gains in speed of processing, inductive reasoning, and memory, no training effects were found on measures of everyday function. At that point the investigators reasoned that most of the study participants were perhaps still functioning at too high of a level to see any transfer effects on everyday functioning. If this reasoning was correct, then longer-term follow-up data should be more likely to show training effects on everyday functioning. Willis et al. (2006) reported findings from a 5-year follow-up, whereas Rebok et al. (2014) reported data on the 10-year effects of the ACTIVE training. In both studies, training effects were found for participants’ self-reported IADLs but not for performance-based measures of everyday functioning. Specifically, in the 5-year follow-up study, the reasoning-trained group, but not the speed- or memory-trained groups, reported significantly less difficulty with performing IADLs than the control group. The investigators concluded that reasoning training resulted in less functional decline in self-reported IADL performance (Willis et al., 2006). In the 10-year follow-up study, the same effect was found regardless of specific intervention group as trained participants reported less difficulty with self-reported IADLs (Rebok et al., 2014). Notably, the links with functional ability were subjective reports, and there were no training benefits found for objective measures of everyday cognition. In conclusion, there is limited evidence that training of basic cognitive abilities may indeed translate to improvement, albeit delayed, in everyday cognition.

WHAT WE DO NOT KNOW: QUESTIONS, CONCERNS, AND FUTURE DIRECTIONS

Do We Need to Measure Everyday Cognition or Can We Rely Solely on Lab-Based Cognitive Tests?

There is evidence that measures of everyday cognition provide added value compared to lab-based tests. Impressive findings of the predictive validity of everyday tests includes that everyday cognitive performance is uniquely predictive of IADL performance (Allaire & Marsiske, 2002), the likelihood of death (Weatherbee & Allaire, 2008), medication adherence (Neupert et al., 2011), and cognitive impairment (Allaire & Willis, 2006; Burton, Strauss, Hultsch, & Hunter, 2009), over and above basic cognitive measures. In every noted domain, higher scores on everyday cognitive tests were found to be associated with more positive outcomes, providing evidence that everyday cognition is an important predictor of significant real-life competencies and outcomes beyond traditional lab-based cognition.

However, it is unclear how relevant tests of everyday cognition are in the face of other related and more proximal predictors of such outcomes, such as cardiovascular health. In other words, what is the ultimate predictive goal for using everyday cognitive measures and in what context?

Current measures of everyday cognition show similar decline to reasoning ability over 10 years (Yam et al., 2014), but adults’ ability to complete their jobs, leisure activities, and other demands of daily life generally do not show corresponding significant declines (Bielak, 2017a; Salthouse, 2012). Yam et al. (2014) noted that objective everyday cognitive tasks have face validity but are never precisely the same as what a person might do in his or her everyday life. Rebok et al. (2014) noted “it is probably a mistake to conceive of these performance-based functional measures as something other than cognitive tests” (p. 20). Everyday cognitive measures did in fact evolve from lab-based cognitive tasks, and though distinct in some respects, have not fallen too far from the tree (Burton et al., 2006). Further, everyday cognitive tasks may be more susceptible to interindividual variability due to personality, motivation, and strategies in approaching tasks compared to lab-based tests.

Overall, there appears to be not only value in everyday cognitive tests, but also valid reasons to consider alternative novel directions for the assessment of cognition in real life. Landauer (1989) said that “the beast will not change its shape as it lies on the microscope table” (p. 124), underscoring the importance of considering everyday cognition in the laboratory even if the task in the context of daily life may be different. Therefore, in some instances, tasks of everyday cognition may be the best and only approximation possible. It is challenging to observe every possible cognitively-related challenge in people’s daily lives on a continual basis (e.g., their navigation ability not only in driving situations but also when walking outside and indoors) and a lab-based objective measure of their functioning may be the only tool available (but see section entitled “What is the Future of Everyday Cognition Tests?” in the present article).

Are the Tests of Everyday Cognition Becoming Obsolete? How Do We Test the Ability to Navigate and Live in Everyday Contexts that are Constantly Changing?

One of the rather complex issues in terms of the ecological validity of measures of everyday cognition is the fact that adults’ functioning in real life does not exist in a vacuum. Rather, adults’ cognitive performance in real life is embedded into physical and social contexts that are not stationary but dynamic in nature (Diehl & Willis, 2003). The very nature and demand characteristics of the tasks that are used to assess older adults’ cognitive competence and performance in everyday life may change over time and previously valid tasks may become partially invalid or completely obsolete. For example, rapid and pervasive technological changes, such as the computerization of everyday life (e.g., use of touch-screen vending machines) constantly challenge older adults’ established repertoire of everyday problem-solving skills and may also challenge the application of basic cognitive abilities. As such, marker tasks that were used to assess adults’ everyday competence in the past may need to be modified or completely replaced to capture these changes and preserve their ecological validity. Thus, the implication in terms of ecological validity is that, by definition, it is a fluid and dynamic concept in and of itself. This dynamic nature requires that the validity of marker tasks is periodically re-evaluated and re-established.

This issue can be further illustrated with two examples. First, previous versions of the OTDL included a task where the participant had to find the phone number of a pharmacy in a phone book and then dial the number. Given that phone books have literally vanished and most exchanges with pharmacies now happen via automated telephone voice menu systems, it is reasonable to question whether this task is still ecologically valid (Czaja & Sharit, 2003). Further, are the cognitive demands of effectively using an automated telephone voice menu system the same or similar as the demands of the previous OTDL task? Moreover, is an older adult’s performance on both tasks predicted by the same set of basic cognitive abilities? In the absence of studies that compare adults’ performance on such tasks, the answers to these questions remain open.

Our second example addresses the issue of using an electronic personal health record (PHR; Taha, Czaja, Sharit, & Morrow, 2013). One task on the EPT required that the participant fill out a patient record on paper and answer related questions. Such a task is nowadays performed electronically, and adults are increasingly required to access electronic PHRs. However, fairly little is known about the factors and cognitive abilities that predict successful usage of PHRs. One of the few existing studies used a simulated PHR to ask middle-age (40–59 years) and older adults (60–85 years) to perform 15 common health management tasks, including review/interpretation of lab/test results and health maintenance activities (Taha et al., 2013). Results indicated that participants in both age groups experienced significant difficulties in using the PHR to complete these routine health management tasks, but performance was especially low in older adults with lower numeracy skills and lower technology experience.

These two examples illustrate that developers of tests of everyday cognition face a very formidable challenge: Given the constant changes in living context, how can they ensure the ecological validity of the tasks they use to assess adults’ everyday cognition? Clearly, answers to this question require that researchers engage in careful task analyses of relevant everyday problem situations and recalibrate or redesign tasks to reflect the changes in adults’ daily ecology (Czaja & Sharit, 2003; Diehl & Willis, 2003). However, in a world where technology is changing faster than ever before, a recalibration of everyday cognition tests to fit the daily contexts that older adults face may be obsolete soon after they are updated. This issue will be critical to answer as the field moves forward and the environmental demands of life continue to evolve.

What Is the Future for Everyday Cognition Tests? Are There New Alternatives on the Horizon?

There are three primary novel pathways that may represent the future of evaluating everyday functioning. The first involves moving everyday cognitive testing further into the “real world.” One alternative to address the issue of the relevancy of everyday cognitive tasks in the ever-changing contexts of daily life is to use technology that allows researchers to observe everyday life close up. For example, participants may wear a small audio or video recorder such as Google Glass, electronically activated recorder (EAR) (Mehl, Pennebaker, Crow, Dabbs, & Price, 2001) or SenseCam (Hodges, Berry, & Wood, 2011) as they go about their day, permitting direct and real-time observations of a person’s functioning. These technologies have already been applied to diverse research questions, for example, as a method of improving memory for patients with dementia (Woodberry et al., 2015). Participants report that they quickly forget the devices are there, addressing the concern that participants would change their behavior if they knew they were being monitored (Lucas-Thompson, 2016). These devices are generally unobtrusive, and the only requirement of the participant is to remember to put them on in the morning. Further, given the endless range of daily tasks the participant may complete over the course of the observation period, such devices include buttons to permit privacy for set amounts of time. Studies often have additional consent considerations built into their design, for example the ability for participants to note retrospectively if they do not want the researchers to view and code certain conversations or portions of the day (Lucas-Thompson, 2016).

Wearable technology methods would allow assessment of the actual ability to complete tasks relevant to a person’s daily life and acknowledge the importance of dynamic environmental influences. The tasks completed, their complexity, and the situational conditions would certainly not be the same for each person, posing potential challenges for analysis and interpretation, but this methodology would provide a better sense of how a person fulfills the tasks necessary in his or her life. One of the tenets of life-span developmental psychology is that development is individualized (Baltes, Lindenberger, & Staudinger, 2006), and expanding everyday cognition assessment to the realm of wearable technology honors this tenet and puts it into action.

Similarly, a second way to represent everyday ecologies in an accurate and realistic way is the use of virtual reality technology or other lifelike simulations in the lab (e.g., simulating driving in different traffic situations, simulating shopping in a virtual supermarket). Such technologies would be able to approximate the real-life demands of driving and shopping complete with contextual complexities such as other cars, shoppers, and having to providing payment. Driving simulators have been successful in assessing everyday cognitive ability in older adults (Lees, Cosman, Lee, Fricke, & Rizzo, 2010), and a virtual supermarket has been used to examine the planning ability of those with Parkinson’s disease (Klinger, Chemin, Lebreton, & Marie, 2004). Thus far, the application of virtual environments has often been to act as a training environment that can then lead to changes in real-life contexts (Casutt, Theill, Martin, Keller, & Jäncke, 2014), or as a contextually diverse way to assess types of cognitive decline (Zygouris et al., 2015). It remains debatable whether these technologies will ever become mainstream and considered a standard part of an everyday cognition battery. Virtual environments can certainly provide greater ecological validity than typical everyday cognitive tasks, but their cost and administration may be prohibitive.

The third possible path of everyday cognition that is ripe for more in-depth exploration is specific attention to the fluctuations in everyday functioning. There is evidence that inconsistency in cognitive performance, specifically moment-to-moment fluctuations on a reaction-time task, provides unique information about cognitive ability and neurological integrity (Bielak & Anstey, 2015). Further, intraindividual variability in other domains such as affect (Kuppens, Van Mechelen, Smits, De Boeck, & Ceulemans, 2007), stress (Diehl & Hay, 2010), and control beliefs (Bielak et al., 2007) have been shown to be reliable indices of functioning and informative beyond single one-time assessments. Using this rationale, Gamaldo and Allaire (2016) investigated the possibility that daily fluctuations in everyday cognition are meaningful. They found significant within-person variability across 8 occasions of an everyday cognitive measure (over 2–3 weeks), the magnitude of which was nearly equal to the differences in performance between individuals on the test. Consequently, there is evidence that there is value in further investigating daily fluctuations in everyday cognition, both to aid understanding of normal cognitive functioning and for its potential use in identifying early cognitive impairment (Gamaldo & Allaire, 2016).

Expanding everyday cognition research into daily variations will also provide insight into the potentially distinct nature between what daily assessments and what traditional single-occasion measures of everyday cognition measure. For example, Bielak (2017b) found that daily reports of activity engagement predicted cognitive ability over and above the conventional one-time activity measure, a verdict that may also hold true for other domains. Daily assessments of everyday cognition may also be a better approximation of actual everyday functioning compared to a one-time measure and provide a better solution to ecological validity concerns as daily tasks can vary in form, context, and level of complexity, just as functional tasks do in real life. Relatedly, expanded longitudinal approaches and repeated assessments (over not only days, but years) have the potential to further highlight changes in everyday functioning at the individual level.

How Can We Improve Everyday Cognition?

Cognitive aging researchers tend to approach cognitive improvement and training from the perspective of training specific abilities. For example, the ACTIVE trial focused on improving performance in speed of processing, memory, and reasoning (Ball et al., 2002). The training benefits extended to real-life tasks, such as driving (Ball, Edwards, Ross, & McGwin, 2010) and self-reported subjective IADL performance (Rebok et al., 2014), but did not relate to improved performance on standard tests of everyday functioning such as the EPT and OTDL. Overall, there is little research that has found supportive evidence that training of specific cognitive abilities extends to improvements in everyday cognition. As noted earlier, the higher ecological validity of everyday cognitive tasks compared to lab-based tasks has translated into the perception that improvement on everyday cognitive tasks has a higher likelihood of translating to corresponding improvement in daily life compared to when improvement on traditional tasks is observed.

However distant and future based, the goal of cognitive training research is ultimately to improve quality of life, everyday functioning, and delay or prevent the onset of dementia for older adults. In the face of this goal, Marsiske (2015) pointed out the inherent backward nature of the predominant method of training a specific cognitive ability and expecting it to change functioning in everyday life. Rather, a more valuable approach to cognitive training would be to flip the direction of the expected generalization. Marsiske suggested it would be a better use of time and money to focus on an everyday cognitive ability that we want to improve amongst older adults, such as medication-taking behavior, and train individuals in ways that improve functioning for that particular everyday task. For example, this approach is often used to improve driving ability via driving simulators (Casutt et al., 2014). We could still evaluate transfer of training, but in the opposite direction of whether the everyday task training had an impact on ability-specific cognitive performance such as memory or reasoning. This approach would ensure that older adults leave the study with an improved capacity to conduct an everyday task, and generalization to specific cognitive abilities would be a bonus. The focus on the everyday behavior would also be more likely to result in improvements in subjective and objective tests of everyday functioning. In the traditional training approach, significant improvement in the trained cognitive ability is rarely a sufficient outcome for success. It is well known that individuals who are trained on cognitive tasks improve their performance on those cognitive tasks (Ball et al., 2002), but because the specific task often has little relevance to everyday life (e.g., memorize a paragraph), the training technique is not considered a success unless there are corresponding improvements in real-world abilities. Therefore, a key defining feature and difference of the suggested training scheme by Marsiske is that improvement in the trained domain of everyday life would be enough to consider the training a success.

The practicality and ecological validity of instituting this novel training approach would require a clear taxonomy of the cognitive demands and functions that are necessary for the trained everyday task, and thus which additional lab-based cognitive tasks the participant would need to complete to evaluate the generalization of training. In general, such a taxonomy would rest on careful task analyses (Crandall, Klein, & Hoffman, 2006) of the to-be-trained everyday tasks and would provide a detailed description of the manual steps and cognitive functions (e.g., sensory processes, attention, memory, reasoning abilities) required for task completion. Such a task analysis would also permit the ordering of the to-be-trained tasks along a continuum of difficulty and complexity. For example, simply retrieving a text message on a smartphone would be considered a cognitively less complex task than actively writing and sending a new text message. Without such a taxonomy, researchers would be “shooting into the dark” regarding likely generalization to specific cognitive tasks. Further, given that the skills and strategies used to complete everyday cognitive tasks are themselves task specific, there is the possibility that transfer to fundamental cognitive abilities will also be limited. However, this limitation and the additional taxonomy requirement are small compared to the possible benefits of implementing this new approach to cognitive training.

CONCLUSION

The current article reviewed what we know about everyday cognition and its similarities and differences compared to lab-based cognition and also discussed critical questions regarding the two concepts. We conclude by directly answering the question raised in the title of this article: Is there a lab-life gap? Our evaluation showed that everyday cognitive tests add to our understanding of the daily life and functioning of older adults beyond what we can learn via lab-based cognitive tests. Everyday cognitive tests however were created from lab-based tests and by lab-based researchers, so they do have substantial overlap. However, both types of tests have their place in learning about how cognition operates and changes in adulthood. Overall, there is value in both, and there is sufficient value in understanding how older adults function in their daily lives for these tests to continue to be of relevance and evolve.

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