A New Brief Measure of Executive Function: Adapting the Head-Toes-Knees-Shoulders Task to Older Adults

A New Brief Measure of Executive Function: Adapting the Head-Toes-Knees-Shoulders Task to Older... Abstract Background and Objectives Executive function (EF) abilities are recognized as components of cognition most likely to show age-related declines. Measurement of EF in older adults is often computer-based, takes place in a laboratory setting, and thus lacks ecological validity. We sought to investigate a new way of measuring EF in older adults by adapting a brief, behavioral measure of EF in children, the Head-Toes-Knees-Shoulders task (HTKS). Research Design and Methods A sample of 150 community-dwelling older adults (Mean age = 68.55, SD = 6.34) completed the HTKS, NIH Toolbox: Cognition Battery (NIHTB-CB) and Positive and Negative Affect Schedule. Results The HTKS showed adequate internal consistency, α = .84. Significant associations between HTKS variables and measures of attention and inhibitory control were robust to the influences of age, processing speed, and subjective health ratings. HTKS completion time exhibited the strongest associations to NIHTB-CB measures, suggesting that the time it takes older adults to complete the HTKS may be a better measure of EF than the total score. Nonsignificant associations between HTKS variables and positive and negative affect demonstrated discriminant validity. Discussion and Implications These results provide initial evidence for use of the HTKS as a brief, low-cost, easy to administer measure of EF in older adults. Further research is needed to determine its potential to identify individuals at risk for poor cognitive outcomes. A brief, valid measure may allow for wider screenings aimed at early intervention, when cognitive interventions are most effective. Cognitive function, Executive function, Measurement, Psychometrics Cognitive health is a paramount concern for individuals, as well as society (Alzheimer’s Association, 2016). Higher-level cognitive processes necessary for managing actions, thoughts, and emotions, collectively known as executive function (EF) abilities (e.g., attention, inhibitory control, working memory), are widely recognized as the components of cognition most likely to show age-related declines (Jurado & Rosselli, 2007; Zelazo, Craik, & Booth, 2004). The present study was designed to examine a new way of measuring EF in community-dwelling older adults, through the adaptation of a well-known measure of EF in children, the Head-Toes-Knees-Shoulders task (HTKS; McClelland et al., 2014). The HTKS is a game-like behavioral measure administered between participant and examiner designed to incorporate attention, inhibitory control, and working memory. It has the potential to be utilized in a variety of settings because it is brief, easy to administer, freely available for research purposes, and requires no special equipment (such as a computer). An important first step in assessing whether the HTKS could be widely utilized as a measure of EF is to determine its reliability and validity in a sample of older adults. Current EF Measurement in Older Adults Currently cognitive functioning is often assessed through comprehensive batteries administered via computerized assessment (e.g., the NIH Toolbox for the Assessment of Neurological and Behavioral Function Cognition Battery [NIHTB-CB; Gershon et al., 2013]; Cogstate [Maruff, Collie, Darby, Weaver-Cargin, & McStephen, 2002]) or via response booklets and stimulus materials (e.g., Pearson's Delis-Kaplan EF System [Delis, Kaplan, & Kramer, 2001]). There is variability, however, in the amount of equipment required, financial cost, examiner involvement, adequate validity of tests, and norming data for older adults (see Wild, Howieson, Webbe, Seelye, & Kaye, 2008 for a more comprehensive review). Further, computer-based measurement of EF tends to lack ecological validity, making it difficult to generalize performance to real world scenarios, thoughts, and behaviors (Müller & Kerns, 2015). A new measure that is brief, low-cost, and incorporates multiple components of EF via motoric engagement and social interaction may offer a more efficient way of analyzing EF in older adults. Further, the motoric engagement and social interaction involved in HTKS administration circumvents reliance on materials and computer-based administrations that have little generalizability to real-world scenarios. Prior Research with the HTKS Prior work implementing the HTKS has been restricted to children ages 4–6 (e.g., McClelland et al., 2007; Ponitz, McClelland, Matthews, & Morrison, 2009). McClelland et al. (2014) performed a psychometric evaluation of the HTKS in a longitudinal study and found that among diverse samples of young children, the HTKS demonstrated strong construct validity with measures of attention, inhibitory control, and working memory and also demonstrated high internal consistency reliability. Purpose and Research Question The current study is guided by the life-span theoretical perspective, and its underlying goal of optimizing development by means of maximizing gains and minimizing losses (Baltes, Lindenberger, & Staudinger, 2006). Plasticity, or the ability to adapt to changes in environment and react differently to stimuli throughout development, and culture are driving forces of development under this framework (Baltes, Lindenberger, & Staudinger, 2006). The overarching goal of this study was to determine if the HTKS (McClelland et al., 2014) could be adapted to older adult populations. We addressed the research question, what are the psychometric properties of the HTKS when used in older adults? We hypothesized adequate internal consistency, and strong convergent validity as compared to the “gold standard” measures in the NIHTB-CB (Gershon et al., 2013). We also aimed to explore discriminant validity by examining associations of the HTKS with a measure of a construct not related to EF. For this study, we utilized the construct of affect and used the Positive and Negative Affect Schedule (PANAS; Watson, Clark, & Tellegen, 1988). Specifically, we anticipated strong, significant relationships with measures of attention, inhibitory control, and working memory. Additionally, as an indication of discriminant validity, we anticipated no relationship with a measure of affect. In addition to components of EF, we considered whether processing speed is relevant for the HTKS because speeded performance is a crucial facet to the makeup of cognitive functioning in older adulthood (Kail & Salthouse, 1994). Age-related declines in processing speed are well documented (e.g., Schaie & Willis, 1993; Verhaeghen & Salthouse, 1997) and perhaps due to slower processing of particular mental operations as adults get older (Salthouse, 1996). Given the importance of speeded performance in cognitive aging research, we included timed completion of the HTKS and adjusted for processing speed in analyses. And finally, we include measures of self-reported memory, and physical and mental health to describe our sample. Design and Methods Participants A sample of 150 community-dwelling older adults (60 years of age and older) from Oregon were recruited via e-mail from a previously established participant pool (704 adults 60 years of age and older were eligible to receive the e-mail). Out of 210 adults who expressed interest in the study, 150 adults ultimately scheduled and completed the research protocol. Because this study is the first adaptation of the HTKS in older adults, the sample was limited to community-dwelling older adults with cognitive capacity to consent to research. All participants successfully demonstrated capacity to consent by answering questions regarding information presented in the consent form. Consistent with previous psychometric investigations of EF measures (see Mitchell & Miller, 2008; Weintraub et al., 2014), this study did not include structured screening to exclude participants with chronic medical conditions (e.g., arthritis, diabetes, heart disease) because we aimed to collect a representative sample of community-dwelling older adults. Measures and Procedures After institutional review board approval, participants were scheduled for a 1-hr block of testing in a research office. Participants were given a consent form followed by a brief paper and pencil questionnaire that included questions on demographics, subjective memory loss via a single item from the Cognitive Module of the Behavioral Risk Factor Surveillance System asking, “During the past 12 months, have you experienced confusion or memory loss that is happening more often or is getting worse?” (BRFSS; Alzheimer’s Association and Centers for Disease Control and Prevention, 2013), and self-reported health via the 12-item short form health survey (SF-12; Ware, Kosinksi, & Keller, 1995). A single item reflecting subjective memory loss was chosen due to previous literature demonstrating its efficacy in exhibiting a correlation with objective test performance (e.g., Mol, van Boxtel, Willems, & Jolles, 2006). Next, participants participated in the HTKS protocol (see description, below) to assess EF. Due to the importance of participant engagement in tasks used in cognitive research, participants then answered a question asking, “Would you be interested in playing a game similar to the task you just completed in other studies?” The NIHTB-CB (Gershon et al., 2013) was administered next, with specific measures in this order: computerized demographic form collecting highest level of education (ranging from 12th grade to doctorate degree), Dimensional Change Card Sort Test (DCCS), Flanker Inhibitory Control and Attention Test, List Sort Working Memory Test, and Pattern Comparison Processing Speed Test. A paper format of the PANAS (Watson, Clark, & Tellegen, 1988) followed NIHTB-CB completion. Demographics The sample of 150 participants (M = 68.55 years of age, SD = 6.34, Range = 60–88) completed a brief paper and pencil demographics questionnaire (Table 1). The sample were predominately female (72%), Caucasian (95%), self-identifying as Not Hispanic or Latino/Latina (96%), married (62%), and well educated (81% had at least a Bachelor’s degree). A single item from the BRFSS cognitive module showed 21% of participants reported subjective memory loss in the past year (dichotomized as 0 = no, 1 = yes for analyses). The SF-12 showed the self-reported mental health (M = 53.42, SD = 6.90) and physical health (M = 50.31, SD = 7.53) of the current sample were slightly better and more homogenous than the general U.S. population based on t-score conversions (M = 50, SD = 10; Ware, Kosinski, & Keller, 1995, p. 23). Table 1. Demographics of Sample (N = 150) Variable N % M (SD) Range Age 68.55 (6.34) 60–88  60–69 99 66  70–79 41 27.33  80–88 10 6.67% Gender  Female 108 72  Male 40 26.67  Missing 2 1.33 Race  African American 1 0.67  Asian 2 1.33  Caucasian 143 95.33  Native, Hawaiian, or Other Pacific Islander 1 0.67  Other 2 1.33  Missing 1 0.67 Ethnicity  Hispanic or Latino/ Latina 1 0.67  Not Hispanic or Latino/Latina 144 96  Missing 5 3.33 Marital Status  Married 93 62  Divorced 25 16.67  Single 16 10.67  Widowed 15 10  Missing 1 0.67 Educationa  12th grade – High School graduate 4 2.67  Some college – Associates degree 25 16.67  Bachelor’s Degree 58 38.67  Master’s Degree 44 29.33  Professional Degree – Doctorate Degree 19 12.67 Subjective Memory Lossb 31 20.67 Variable N % M (SD) Range Age 68.55 (6.34) 60–88  60–69 99 66  70–79 41 27.33  80–88 10 6.67% Gender  Female 108 72  Male 40 26.67  Missing 2 1.33 Race  African American 1 0.67  Asian 2 1.33  Caucasian 143 95.33  Native, Hawaiian, or Other Pacific Islander 1 0.67  Other 2 1.33  Missing 1 0.67 Ethnicity  Hispanic or Latino/ Latina 1 0.67  Not Hispanic or Latino/Latina 144 96  Missing 5 3.33 Marital Status  Married 93 62  Divorced 25 16.67  Single 16 10.67  Widowed 15 10  Missing 1 0.67 Educationa  12th grade – High School graduate 4 2.67  Some college – Associates degree 25 16.67  Bachelor’s Degree 58 38.67  Master’s Degree 44 29.33  Professional Degree – Doctorate Degree 19 12.67 Subjective Memory Lossb 31 20.67 Note: aEducation was collapsed into five categories. All education levels include 12th grade, High School graduate, Some college but less than 1 year, One or more years of college no degree, Associate’s degree, Bachelor’s degree, Master’s degree, Professional degree, Doctorate degree. bSubjective Memory Loss denotes the participants that self-reported confusion or memory loss that is happening more often or is getting worse during the past 12 months. View Large Table 1. Demographics of Sample (N = 150) Variable N % M (SD) Range Age 68.55 (6.34) 60–88  60–69 99 66  70–79 41 27.33  80–88 10 6.67% Gender  Female 108 72  Male 40 26.67  Missing 2 1.33 Race  African American 1 0.67  Asian 2 1.33  Caucasian 143 95.33  Native, Hawaiian, or Other Pacific Islander 1 0.67  Other 2 1.33  Missing 1 0.67 Ethnicity  Hispanic or Latino/ Latina 1 0.67  Not Hispanic or Latino/Latina 144 96  Missing 5 3.33 Marital Status  Married 93 62  Divorced 25 16.67  Single 16 10.67  Widowed 15 10  Missing 1 0.67 Educationa  12th grade – High School graduate 4 2.67  Some college – Associates degree 25 16.67  Bachelor’s Degree 58 38.67  Master’s Degree 44 29.33  Professional Degree – Doctorate Degree 19 12.67 Subjective Memory Lossb 31 20.67 Variable N % M (SD) Range Age 68.55 (6.34) 60–88  60–69 99 66  70–79 41 27.33  80–88 10 6.67% Gender  Female 108 72  Male 40 26.67  Missing 2 1.33 Race  African American 1 0.67  Asian 2 1.33  Caucasian 143 95.33  Native, Hawaiian, or Other Pacific Islander 1 0.67  Other 2 1.33  Missing 1 0.67 Ethnicity  Hispanic or Latino/ Latina 1 0.67  Not Hispanic or Latino/Latina 144 96  Missing 5 3.33 Marital Status  Married 93 62  Divorced 25 16.67  Single 16 10.67  Widowed 15 10  Missing 1 0.67 Educationa  12th grade – High School graduate 4 2.67  Some college – Associates degree 25 16.67  Bachelor’s Degree 58 38.67  Master’s Degree 44 29.33  Professional Degree – Doctorate Degree 19 12.67 Subjective Memory Lossb 31 20.67 Note: aEducation was collapsed into five categories. All education levels include 12th grade, High School graduate, Some college but less than 1 year, One or more years of college no degree, Associate’s degree, Bachelor’s degree, Master’s degree, Professional degree, Doctorate degree. bSubjective Memory Loss denotes the participants that self-reported confusion or memory loss that is happening more often or is getting worse during the past 12 months. View Large HTKS The HTKS is comprised of 30 test items divided equally across three sections with a maximum of four paired behavioral rules applied to the task: “touch your head” and “touch your toes;” “touch your shoulders” and “touch your knees.” Each section begins with the participant responding naturally (e.g., touching head when instructed to touch head), followed by an instruction to change the rules and respond in “opposite” fashion (e.g., touching head when instructed to touch toes). Section 1 includes only two behavioral rules, head goes with toes and toes go with head. Section 2 involves adding the additional two behavioral rules regarding shoulders and knees (e.g., touching their shoulders when instructed to touch their knees). Participants advance to the final section if they are able to respond correctly to all four paired behavioral rules. Section 3 involves switching the paired rules (e.g., touching their head when instructed to touch their knees, and touching their shoulders when instructed to touch their toes). All participants advanced to the third section and completed the 30 test items. Although the measure is designed for the participant to stand up, it is not a requirement of the task. Therefore, if the participant indicated that sitting down was preferable, a seated administration option was offered (Four participants sat down during task administration). The examiner scores the participant’s responses on a three-point scale, including 0(incorrect), 1(self-correct), or 2(correct) for each test item. An incorrect response is scored when the participant does not touch the correct part of their body or touches the part of their body spoken in the instruction (e.g., when asked to touch their head in the first and second sections, a participant touches their head instead of their toes). A self-correct response is scored when the participant makes a discernable motion toward an incorrect response, but then adjusts and makes the correct response (e.g., when asked to touch their head, a participant may initially move toward an incorrect response of touching their head, and then quickly change their mind to touch their toes). A correct response is scored when the participant makes a discernable motion toward the correct part of their body, either immediately or after a pause to think. Participants were allowed to point to body parts in lieu of touching if they preferred. A total score is generated by adding up each of the 30 test items, with a possible range of 0 to 60. Higher scores indicate higher levels of EF. The HTKS is freely available for research purposes only by submitting an online request using the following website address: http://health.oregonstate.edu/labs/kreadiness/resources. Online training is required for those who intend to use the HTKS upon completion of the online request form. In addition to the total score variable, we included a variable for completion time by monitoring how long (in seconds) each participant took to complete the HTKS. Using a digital stopwatch, the test administrator began timing at the start of HTKS task instructions, and ended on the final behavioral response to the task (Item 30). Faster completion times indicate better EF as shorter completion times show more efficient cognitive processing. NIHTB-CB At the time this study was conducted, administration of the NIHTB-CB (Gershon et al., 2013; www.nihtoolbox.org) required a trained examiner administering the tests from a laptop with a dual-monitor function and speakers. For each measure, this battery provides a raw score, computed score, unadjusted scale score, age-adjusted scale score, national percentile rank, and fully adjusted scale score (adjusts for age, gender, race, ethnicity, and education), as well as a total summary score (We have provided these scores in Supplementary Table 1). Among individuals aged 3–85 years, the NIHTB-CB measures have adequate convergent validity as compared to D-KEFS Inhibition (DCCS and Flanker), Wechsler Adult Intelligence Scale – 4th edition (WAIS-IV) Letter-Number Sequencing, Coding, and Symbol Search (Flanker and Pattern Comparison), and WAIS-IV Letter-Number Sequencing and Symbol Search (List Sort), as well as discriminant validity as compared to the Peabody Picture Vocabulary Test – 4th Edition (Weintraub et al., 2014; Zelazo et al., 2014). For the purposes of this study, we used four tests from the battery instead of a composite score to isolate the cognitive dimensions relevant to the HTKS. We utilized age-adjusted scores from these measures because of the wide range of ages sampled (Range: 60–88 years of age). Each of the four measures administered are described below. DCCS This test measures attentional set shifting, or the ability to switch attentional focus among multiple task features. Using left and right arrow keys, the test involves matching a target stimulus to one of two option stimuli depending on “shape” or “color” direction words presented on the previous screen. Participants take 4 min on average to complete 40 total trials; an algorithm combining accuracy and reaction time computed the score (ranging from 0–10). Flanker inhibitory control and attention test This test measures inhibitory control, or the ability to inhibit one’s attention to irrelevant details within the test. Each trial involves an arrow target stimulus in the center of the screen that is flanked by congruent or incongruent arrows on each side. Participants select which direction the central stimulus is pointing via left and right arrow keys. Participants take four minutes on average to complete 40 total trials; an algorithm combining accuracy and reaction time computed the score (ranging from 0–10). List sort working memory test This test measures working memory, or the ability to process, store, and update information. The test involves two sections where a set of stimuli is presented to the participant visually and orally, one at a time. The test requires the participant to report the stimulus items back to the examiner in size order, from smallest to largest. Section 1 presents the same category to the participant. Section 2 presents two different categories of stimulus items with the instruction to report stimuli from one category, then the other category, both from smallest to largest. For example, the stimulus items “corn, egg, dog, cherry, elephant, mouse” would be correctly repeated as “cherry, egg, corn, mouse, dog, elephant.” The number of stimulus items increases each time a successful report occurs up to seven total items. Participants take 7 min on average to complete this test, and the score is derived from the number of items correct across all trials. Pattern comparison processing speed test This test measures processing speed, operationalized as the amount of information processed in 90 s via left and right arrow keys. The test consists of participants determining whether two visual stimuli are the “same” or “not the same”. Participants have 90 s to answer as many items as they can up to 130 items, and the score is derived from the number of items correct across all trials. PANAS The PANAS (Watson et al., 1988) is a 20-item subjective measure of feelings and emotions that includes 10 items assessing positive affect (PA; e.g., “excited,” “inspired,” “proud”) and 10 items assessing negative affect (NA; e.g., “distressed,” “hostile,” “afraid”). Crawford and Henry (2004) reported adequate internal consistency for both the PA (α = .89) and NA (α = .85) scales. Participants are asked to “indicate to what extent you have felt this way today.” Answered on a five-point Likert-type scale, the PANAS ranges from 1 (very slightly or not at all) to 5 (extremely). Scores range from 10 to 50 for the PA scale and the NA scale, with higher scores indicating higher levels of PA and NA. In the current study, the PANAS demonstrated adequate internal consistency for both the PA (α = .84) and NA (α = .81) scales. Analyses We used Cronbach’s α reliability to assess internal consistency. To determine convergent validity, we analyzed initial bivariate correlations between HTKS variables (total score and completion time) and the NIHTB-CB DCCS, Flanker, List Sort, and Pattern Comparison tests (Gershon et al., 2013). Per Cohen (1992), an r of .10 to .30 indicates a small to medium effect size, .30 to .50 indicates a medium to large effect size, and .50 and larger indicates a large effect size. We used multiple regression analyses to determine if significant associations between HTKS variables and the DCCS, Flanker, and List Sort tests were robust to statistical adjustment for age, processing speed, and subjective health ratings (subjective memory loss and self-rated physical and mental health). To assess discriminant validity, we analyzed bivariate correlations between HTKS variables and PA and NA using the PANAS (Watson et al., 1988). Analyses were performed using Stata LC13 statistical software (StataCorp, 2013). Results Descriptive Statistics Table 2 includes all descriptive statistics for primary variables in the analyses. In the present study, we observed a ceiling effect in HTKS total score, with most participants scoring highly on the task (83% of the sample achieved a score between 56 and 60). Compared to the ceiling effect found in the HTKS total score variable, HTKS completion time showed more variability in scores (M = 4 min, 43 s, SD = 29.91 s, Range = 3 min, 56 s – 6 min, 53 s). Due to the ceiling effect in HTKS total score in this relatively healthy older sample, we utilized HTKS completion time as an additional variable of HTKS performance incorporating speed of processing. Table 2. Descriptive Statistics for Analysis Variables Variable M (SD) Range α Inter-item α range HTKSa  HTKS Total Score 57.03 (4.42) 34–60 .84 .82–.84  HTKS Completion Time (seconds) 283.07 (29.91) 236.25–413.10 NIHTB-CBb  DCCS 109.63 (9.62) 78.30–130.83  Flanker 100.47 (9.29) 79.15–124.72  List Sort 112.26 (12.04) 76.17–141.57  Pattern Comparison 105.53 (19.11) 47.05–147.97 PAc 36.68 (5.65) 18–48 .84 .82–.84 NAd 13.27 (3.57) 10–30 .81 .77–.81 SF-12 Health Surveye 51.87 (5.14) 28.14–58.76 .81 .78–.81  Physical Health 50.31 (7.53) 24.82–64.28 .76 .71–.73  Mental Health 53.42 (6.90) 31.42–64.33 .70 .59–.70 Variable M (SD) Range α Inter-item α range HTKSa  HTKS Total Score 57.03 (4.42) 34–60 .84 .82–.84  HTKS Completion Time (seconds) 283.07 (29.91) 236.25–413.10 NIHTB-CBb  DCCS 109.63 (9.62) 78.30–130.83  Flanker 100.47 (9.29) 79.15–124.72  List Sort 112.26 (12.04) 76.17–141.57  Pattern Comparison 105.53 (19.11) 47.05–147.97 PAc 36.68 (5.65) 18–48 .84 .82–.84 NAd 13.27 (3.57) 10–30 .81 .77–.81 SF-12 Health Surveye 51.87 (5.14) 28.14–58.76 .81 .78–.81  Physical Health 50.31 (7.53) 24.82–64.28 .76 .71–.73  Mental Health 53.42 (6.90) 31.42–64.33 .70 .59–.70 Note: aHTKS = Head-Toes-Knees-Shoulders Task (HTKS; McClelland et al., 2014), with Total and Completion Time (in seconds) scores. bNIHTB = National Institutes of Health Toolbox – Cognition Battery (www.nihtoolbox.org). DCCS = Dimensional Change Card Sort = a measure of attentional shifting. Flanker = a measure of inhibitory control. List Sort = a measure of working memory. Pattern Comparison = a measure of processing speed. cPA = Positive Affect. dNA = Negative Affect. Sub-scales derived from the Positive and Negative Affect Schedule (PANAS; Watson, Clark, & Tellegen, 1988). eSF-12 Health Survey = Self-rated health survey with Physical Health and Mental Health subscales comparable to the general U.S. population (M = 50, SD = 10). View Large Table 2. Descriptive Statistics for Analysis Variables Variable M (SD) Range α Inter-item α range HTKSa  HTKS Total Score 57.03 (4.42) 34–60 .84 .82–.84  HTKS Completion Time (seconds) 283.07 (29.91) 236.25–413.10 NIHTB-CBb  DCCS 109.63 (9.62) 78.30–130.83  Flanker 100.47 (9.29) 79.15–124.72  List Sort 112.26 (12.04) 76.17–141.57  Pattern Comparison 105.53 (19.11) 47.05–147.97 PAc 36.68 (5.65) 18–48 .84 .82–.84 NAd 13.27 (3.57) 10–30 .81 .77–.81 SF-12 Health Surveye 51.87 (5.14) 28.14–58.76 .81 .78–.81  Physical Health 50.31 (7.53) 24.82–64.28 .76 .71–.73  Mental Health 53.42 (6.90) 31.42–64.33 .70 .59–.70 Variable M (SD) Range α Inter-item α range HTKSa  HTKS Total Score 57.03 (4.42) 34–60 .84 .82–.84  HTKS Completion Time (seconds) 283.07 (29.91) 236.25–413.10 NIHTB-CBb  DCCS 109.63 (9.62) 78.30–130.83  Flanker 100.47 (9.29) 79.15–124.72  List Sort 112.26 (12.04) 76.17–141.57  Pattern Comparison 105.53 (19.11) 47.05–147.97 PAc 36.68 (5.65) 18–48 .84 .82–.84 NAd 13.27 (3.57) 10–30 .81 .77–.81 SF-12 Health Surveye 51.87 (5.14) 28.14–58.76 .81 .78–.81  Physical Health 50.31 (7.53) 24.82–64.28 .76 .71–.73  Mental Health 53.42 (6.90) 31.42–64.33 .70 .59–.70 Note: aHTKS = Head-Toes-Knees-Shoulders Task (HTKS; McClelland et al., 2014), with Total and Completion Time (in seconds) scores. bNIHTB = National Institutes of Health Toolbox – Cognition Battery (www.nihtoolbox.org). DCCS = Dimensional Change Card Sort = a measure of attentional shifting. Flanker = a measure of inhibitory control. List Sort = a measure of working memory. Pattern Comparison = a measure of processing speed. cPA = Positive Affect. dNA = Negative Affect. Sub-scales derived from the Positive and Negative Affect Schedule (PANAS; Watson, Clark, & Tellegen, 1988). eSF-12 Health Survey = Self-rated health survey with Physical Health and Mental Health subscales comparable to the general U.S. population (M = 50, SD = 10). View Large Psychometric Assessment of the HTKS Adequate internal consistency was demonstrated by Cronbach’s α of the overall HTKS task (α = .84) and its interitem α range (.82–.84). Initial bivariate correlations supporting convergent validity and discriminant validity of the HTKS are presented in Table 3. Higher HTKS total scores were associated with higher scores on the Pattern Comparison (r = .24, p < .01) and DCCS (r = .17, p < .05), but not the Flanker (r = .07, p > .05) or List Sort (r = −.01, p > .05). Multiple regression analyses revealed higher DCCS scores significantly related to higher HTKS total score after adjusting for the influences of age, processing speed, and subjective health ratings (b = 0.09, SE = 0.04, p < .05; see Table 4), and explained 9% of the variance in HTKS total score (Adj. R2 = .09, F(6, 132) = 3.19, p < .01). Table 3. Bivariate Correlations Demonstrating Convergent and Discriminant Validity of the HTKS Variable 1 2 3 4 5 6 7 8 1. HTKS Total - 2. HTKS Timea −.30*** - 3. DCCSb .17* −.21** - 4. Flankerc .07 −.20* .51*** - 5. List Sortd −.01 −.10 .32*** .08 - 6. Pattern Comparisone .34** −.30*** .28*** .33*** .18* - 7. PAf .01 .01 −.00 −.06 −.01 −.04 - 8. NAg .10 .04 −.10 .01 −.16 −.08 −.02 - Variable 1 2 3 4 5 6 7 8 1. HTKS Total - 2. HTKS Timea −.30*** - 3. DCCSb .17* −.21** - 4. Flankerc .07 −.20* .51*** - 5. List Sortd −.01 −.10 .32*** .08 - 6. Pattern Comparisone .34** −.30*** .28*** .33*** .18* - 7. PAf .01 .01 −.00 −.06 −.01 −.04 - 8. NAg .10 .04 −.10 .01 −.16 −.08 −.02 - Note: *p < .05. **p < .01. ***p < .001. Two-tailed. aHTKS Completion Time = Total time in seconds to complete the HTKS task. bDCCS = NIH Toolbox Dimensional Change Cart Sort Test; a measure of attentional shifting. cFlanker = NIH Toolbox Flanker Inhibitory Control and Attention Test; a measure of inhibitory control. dList Sort = NIH Toolbox List Sort Working Memory Test; a measure of working memory. ePattern Comparison = NIH Toolbox Pattern Comparison Processing Speed Test; a measure of processing speed. fPA = Positive Affect. gNA = Negative Affect. Sub-scales derived from the Positive and Negative Affect Schedule (PANAS; Watson, Clark, & Tellegen, 1988). View Large Table 3. Bivariate Correlations Demonstrating Convergent and Discriminant Validity of the HTKS Variable 1 2 3 4 5 6 7 8 1. HTKS Total - 2. HTKS Timea −.30*** - 3. DCCSb .17* −.21** - 4. Flankerc .07 −.20* .51*** - 5. List Sortd −.01 −.10 .32*** .08 - 6. Pattern Comparisone .34** −.30*** .28*** .33*** .18* - 7. PAf .01 .01 −.00 −.06 −.01 −.04 - 8. NAg .10 .04 −.10 .01 −.16 −.08 −.02 - Variable 1 2 3 4 5 6 7 8 1. HTKS Total - 2. HTKS Timea −.30*** - 3. DCCSb .17* −.21** - 4. Flankerc .07 −.20* .51*** - 5. List Sortd −.01 −.10 .32*** .08 - 6. Pattern Comparisone .34** −.30*** .28*** .33*** .18* - 7. PAf .01 .01 −.00 −.06 −.01 −.04 - 8. NAg .10 .04 −.10 .01 −.16 −.08 −.02 - Note: *p < .05. **p < .01. ***p < .001. Two-tailed. aHTKS Completion Time = Total time in seconds to complete the HTKS task. bDCCS = NIH Toolbox Dimensional Change Cart Sort Test; a measure of attentional shifting. cFlanker = NIH Toolbox Flanker Inhibitory Control and Attention Test; a measure of inhibitory control. dList Sort = NIH Toolbox List Sort Working Memory Test; a measure of working memory. ePattern Comparison = NIH Toolbox Pattern Comparison Processing Speed Test; a measure of processing speed. fPA = Positive Affect. gNA = Negative Affect. Sub-scales derived from the Positive and Negative Affect Schedule (PANAS; Watson, Clark, & Tellegen, 1988). View Large Table 4. Multiple Regression Analyses for DCCS Predicting HTKS Total Score (N = 139) Model 1 Model 2 Variable B SE B β B SE B β Age −0.18** 0.07 −0.23 Pattern Comparisona 0.03 0.02 0.14 Subjective Memory Lossb 0.19 0.95 0.02 SF-12 Physical Healthc 0.01 0.05 0.02 SF-12 Mental Healthd −0.05 0.05 −0.08 DCCSe 0.09* 0.04 0.18 0.09* 0.04 0.20 F 4.72* 3.19** Adj. R2 0.03 0.09 F for change in R2 2.82* Model 1 Model 2 Variable B SE B β B SE B β Age −0.18** 0.07 −0.23 Pattern Comparisona 0.03 0.02 0.14 Subjective Memory Lossb 0.19 0.95 0.02 SF-12 Physical Healthc 0.01 0.05 0.02 SF-12 Mental Healthd −0.05 0.05 −0.08 DCCSe 0.09* 0.04 0.18 0.09* 0.04 0.20 F 4.72* 3.19** Adj. R2 0.03 0.09 F for change in R2 2.82* Note: *p < .05. **p < .01. ***p < .001. Two-tailed. aPattern Comparison = NIH Toolbox Pattern Comparison Processing Speed Test; a measure of processing speed. bSubjective Memory Loss denotes the participants that self-reported confusion or memory loss that is happening more often or is getting worse during the past 12 months. cSelf-rated Physical Health is derived from the SF-12 Health Survey and can be compared to the general U.S. population based on t-score conversions (M = 50, SD = 10). dSelf-rated Mental Health is derived from the SF-12 Health Survey and can be compared to the general U.S. population based on t-score conversions (M = 50, SD = 10). eDCCS = NIH Toolbox Dimensional Change Cart Sort Test; a measure of attentional shifting. View Large Table 4. Multiple Regression Analyses for DCCS Predicting HTKS Total Score (N = 139) Model 1 Model 2 Variable B SE B β B SE B β Age −0.18** 0.07 −0.23 Pattern Comparisona 0.03 0.02 0.14 Subjective Memory Lossb 0.19 0.95 0.02 SF-12 Physical Healthc 0.01 0.05 0.02 SF-12 Mental Healthd −0.05 0.05 −0.08 DCCSe 0.09* 0.04 0.18 0.09* 0.04 0.20 F 4.72* 3.19** Adj. R2 0.03 0.09 F for change in R2 2.82* Model 1 Model 2 Variable B SE B β B SE B β Age −0.18** 0.07 −0.23 Pattern Comparisona 0.03 0.02 0.14 Subjective Memory Lossb 0.19 0.95 0.02 SF-12 Physical Healthc 0.01 0.05 0.02 SF-12 Mental Healthd −0.05 0.05 −0.08 DCCSe 0.09* 0.04 0.18 0.09* 0.04 0.20 F 4.72* 3.19** Adj. R2 0.03 0.09 F for change in R2 2.82* Note: *p < .05. **p < .01. ***p < .001. Two-tailed. aPattern Comparison = NIH Toolbox Pattern Comparison Processing Speed Test; a measure of processing speed. bSubjective Memory Loss denotes the participants that self-reported confusion or memory loss that is happening more often or is getting worse during the past 12 months. cSelf-rated Physical Health is derived from the SF-12 Health Survey and can be compared to the general U.S. population based on t-score conversions (M = 50, SD = 10). dSelf-rated Mental Health is derived from the SF-12 Health Survey and can be compared to the general U.S. population based on t-score conversions (M = 50, SD = 10). eDCCS = NIH Toolbox Dimensional Change Cart Sort Test; a measure of attentional shifting. View Large Taking longer to complete the HTKS was associated with lower scores on the Pattern Comparison (r = −.30, p < .001), DCCS (r = −0.21, p < .01), and Flanker (r = −.20, p < .05), but not the List Sort test (r = −.10, p > .05). After adjusting for age, processing speed and subjective health ratings, higher DCCS scores (b = −0.75, SE = 0.25, p < .01) and higher Flanker scores (b = −0.67, SE = 0.27, p < .05) related to faster HTKS completion time (see Table 5), and explained 18% of the variance (Adj. R2 = .18, F(6, 132) = 5.90, p < .001) and 16% of the variance (Adj. R2 = .16, F(6, 132) = 5.26, p < .001) in HTKS completion time, respectively. Table 5. Multiple Regression Analyses for DCCS and Flanker Predicting HTKS Completion Time (N = 139) Model 1 Model 2 Variable B SE B β B SE B β Age 1.56** 0.45 0.29 Pattern Comparisona −0.28* 0.13 −0.18 Subjective Memory Lossb 6.28 6.03 0.09 SF-12 Physical Healthc 0.17 0.31 0.04 SF-12 Mental Healthd 0.22 0.34 0.05 DCCSe −0.73** 0.26 −0.23 −0.81** 0.26 −0.26 F 7.89** 5.90*** Adj. R2 0.05 0.18 F for change in R2 5.26*** Age 1.41** 0.45 0.27 Pattern Comparisona −0.28* 0.14 −0.18 Subjective Memory Lossb 7.26 6.10 0.10 SF-12 Physical Healthc 0.20 0.31 0.05 SF-12 Mental Healthd 0.30 0.35 0.07 Flankerf −0.70** 0.26 −0.22 −0.67* 0.27 −0.21 F 6.96** 5.26*** Adj. R2 0.04 0.16 F for change in R2 4.73*** Model 1 Model 2 Variable B SE B β B SE B β Age 1.56** 0.45 0.29 Pattern Comparisona −0.28* 0.13 −0.18 Subjective Memory Lossb 6.28 6.03 0.09 SF-12 Physical Healthc 0.17 0.31 0.04 SF-12 Mental Healthd 0.22 0.34 0.05 DCCSe −0.73** 0.26 −0.23 −0.81** 0.26 −0.26 F 7.89** 5.90*** Adj. R2 0.05 0.18 F for change in R2 5.26*** Age 1.41** 0.45 0.27 Pattern Comparisona −0.28* 0.14 −0.18 Subjective Memory Lossb 7.26 6.10 0.10 SF-12 Physical Healthc 0.20 0.31 0.05 SF-12 Mental Healthd 0.30 0.35 0.07 Flankerf −0.70** 0.26 −0.22 −0.67* 0.27 −0.21 F 6.96** 5.26*** Adj. R2 0.04 0.16 F for change in R2 4.73*** Note: *p < .05. **p < .01. ***p < .001. Two-tailed. aPattern Comparison = NIH Toolbox Pattern Comparison Processing Speed Test; a measure of processing speed. bSubjective Memory Loss denotes the participants that self-reported confusion or memory loss that is happening more often or is getting worse during the past 12 months. cSelf-rated Physical Health is derived from the SF-12 Health Survey and can be compared to the general U.S. population based on t-score conversions (M = 50, SD = 10). dSelf-rated Mental Health is derived from the SF-12 Health Survey and can be compared to the general U.S. population based on t-score conversions (M = 50, SD = 10). eDCCS = NIH Toolbox Dimensional Change Cart Sort Test; a measure of attentional shifting. fFlanker = NIH Toolbox Flanker Inhibitory Control and Attention Test; a measure of inhibitory control. View Large Table 5. Multiple Regression Analyses for DCCS and Flanker Predicting HTKS Completion Time (N = 139) Model 1 Model 2 Variable B SE B β B SE B β Age 1.56** 0.45 0.29 Pattern Comparisona −0.28* 0.13 −0.18 Subjective Memory Lossb 6.28 6.03 0.09 SF-12 Physical Healthc 0.17 0.31 0.04 SF-12 Mental Healthd 0.22 0.34 0.05 DCCSe −0.73** 0.26 −0.23 −0.81** 0.26 −0.26 F 7.89** 5.90*** Adj. R2 0.05 0.18 F for change in R2 5.26*** Age 1.41** 0.45 0.27 Pattern Comparisona −0.28* 0.14 −0.18 Subjective Memory Lossb 7.26 6.10 0.10 SF-12 Physical Healthc 0.20 0.31 0.05 SF-12 Mental Healthd 0.30 0.35 0.07 Flankerf −0.70** 0.26 −0.22 −0.67* 0.27 −0.21 F 6.96** 5.26*** Adj. R2 0.04 0.16 F for change in R2 4.73*** Model 1 Model 2 Variable B SE B β B SE B β Age 1.56** 0.45 0.29 Pattern Comparisona −0.28* 0.13 −0.18 Subjective Memory Lossb 6.28 6.03 0.09 SF-12 Physical Healthc 0.17 0.31 0.04 SF-12 Mental Healthd 0.22 0.34 0.05 DCCSe −0.73** 0.26 −0.23 −0.81** 0.26 −0.26 F 7.89** 5.90*** Adj. R2 0.05 0.18 F for change in R2 5.26*** Age 1.41** 0.45 0.27 Pattern Comparisona −0.28* 0.14 −0.18 Subjective Memory Lossb 7.26 6.10 0.10 SF-12 Physical Healthc 0.20 0.31 0.05 SF-12 Mental Healthd 0.30 0.35 0.07 Flankerf −0.70** 0.26 −0.22 −0.67* 0.27 −0.21 F 6.96** 5.26*** Adj. R2 0.04 0.16 F for change in R2 4.73*** Note: *p < .05. **p < .01. ***p < .001. Two-tailed. aPattern Comparison = NIH Toolbox Pattern Comparison Processing Speed Test; a measure of processing speed. bSubjective Memory Loss denotes the participants that self-reported confusion or memory loss that is happening more often or is getting worse during the past 12 months. cSelf-rated Physical Health is derived from the SF-12 Health Survey and can be compared to the general U.S. population based on t-score conversions (M = 50, SD = 10). dSelf-rated Mental Health is derived from the SF-12 Health Survey and can be compared to the general U.S. population based on t-score conversions (M = 50, SD = 10). eDCCS = NIH Toolbox Dimensional Change Cart Sort Test; a measure of attentional shifting. fFlanker = NIH Toolbox Flanker Inhibitory Control and Attention Test; a measure of inhibitory control. View Large As an indicator of discriminant validity, HTKS total score was not associated with PA (r = .01, p > .05) or NA (r = .10, p > .05). HTKS completion time was not associated with PA (r = .01, p > .05) or NA (r = .04, p > .05). These results indicate that the HTKS was associated with constructs hypothesized to be related to it, such as attention and inhibitory control, showing aspects of convergent validity that are robust to age, speed of processing, and subjective health rating influences. Importantly, the HTKS was not related to constructs (e.g., affect) thought to be conceptually unrelated to the HTKS, indicating adequate discriminant validity. Discussion This first study utilizing the HTKS as a measure of EF in community-dwelling older adults has shown it to demonstrate adequate internal consistency, convergent validity with measures of attention and inhibitory control, and discriminant validity as compared to a measure of affect. Our results indicate this brief behavioral measure of EF is low-cost, easy to administer (minimal equipment required) and incorporates motoric engagement in ways that existing EF measures do not. Participants in this study took, on average, less than 5 min. Because administration involves face-to-face interaction between participant and examiner, total administration takes approximately 5–7 min. For our study, implementation of the four NIHTB-CB tests took approximately 20–25 min in total (5–10 total minutes preparing for implementation and reading all task directions, 4-min DCCS, 4-min Flanker, 7-min List Sort, and 90 s Pattern Comparison). Well known measures of EF such as the tests in the NIHTB-CB used in this study require computer-based equipment for administration that adds preparation time and resource allocation to purchase necessary equipment. Since the current study’s data collection, the NIHTB-CB now offers an iPad administration that requires a subscription cost for continued access (yearly subscription of $499.99). Our results demonstrate that the HTKS provides an alternative, freely available measure that takes 5–7 min to assess multiple components of EF together with no computer-based equipment necessary. We examined convergent validity with measures of attention, inhibitory control, and working memory because the HTKS has been found to converge with these components of EF in children (McClelland et al., 2014), and previous factor analytic accounts have examined these three components of EF when identifying distinguishable dimensions of EF among young adults (Miyake et al., 2000) and older adults (Hedden & Yoon, 2006; Hull, Martin, Beier, Lane, & Hamilton, 2008). Use of completion time as a measure of HTKS performance avoided the ceiling effect, and provided a measure with more variability. The significant negative association (r = −.30) between HTKS completion time and HTKS total score (i.e., faster completion time related to higher total scores) suggests faster completion times indicate better EF as shorter completion times show more efficient cognitive processing. The following discussion of the psychometric evaluation includes both total score and completion time as measures of HTKS performance in this sample. Aspects of Internal Consistency, Convergent Validity, and Discriminant Validity The HTKS was an internally consistent measure in our older adult sample (α = .84). Associations between HTKS variables and NIHTB-CB measures of attention and inhibitory control were strongest for completion time (not total score) as the measure of HTKS performance, and regression models adjusting for potential confounds and subjective health ratings explained more variance in completion time (16%–18%) than total score (9%). Faster cognitive processing as measured by HTKS completion time was significantly associated with better attention and inhibitory control, but not working memory. Better EF as measured by HTKS total score was associated with better attention, but not inhibitory control or working memory. As hypothesized, both HTKS completion time and total score were unrelated to PA and NA in this older adult sample, constructs thought to be conceptually unrelated to EF. Associations between HTKS variables and NIHTB-CB tasks of attention and inhibitory control were robust to the influences of age, processing speed, and subjective health ratings. Given the relevance of age-related declines in processing speed, it is important to demonstrate HTKS performance is not simply due to an individual’s speed of processing. Adjusting for these potential confounders, subjective memory loss, and self-rated health strengthens the aspects of convergent validity observed in this study and suggests attention and inhibitory control may be relevant domains of EF for HTKS performance in older adulthood, especially for HTKS completion time. Future work examining associations between the HTKS and self-ratings of EF abilities or complaints would offer an additional aspect of convergent validity linking the behavioral task with subjective ratings of everyday EF. It was surprising that working memory was not related to HTKS completion time or total score. It is possible that a restriction of range in the HTKS task resulted in the inability to detect a correlation with the more variable scores of the List Sort test. In addition, perhaps participants found the List Sort test substantively more challenging than the other three measures in the NIHTB-CB. It is also possible that the HTKS is best aligned with measures of EF that involve a timed component. Age Differences The complexity of EF and how its structure can vary by age group and task is further demonstrated by the differential correlations found between the HTKS and EF domains depending on age group. McClelland et al. (2014) suggested that the HTKS may be specifically incorporating inhibitory control in younger children, attention in children from 4 to 6 years, and working memory in older children. In our sample of older adults, the HTKS may be specifically incorporating attention and inhibitory control, but not working memory. As would be expected, post-hoc correlations showed significant associations between age and HTKS variables such that older age was related to slower HTKS completion time (r = .36, p < .001) and lower HTKS total score (r = −.22, p = .008). Further research can address the variation in relevant EF domains for HTKS performance based on age and task by assessing the factor structure of the HTKS. Implications for Practice By demonstrating aspects of reliability and validity of the HTKS in community-dwelling older adults, this study offers a foundation for future work to examine whether the HTKS may prospectively predict changes in cognitive functioning. Identifying a brief, valid measure of cognitive function may allow for wider screenings at the population level aimed toward intervening early when interventions are most effective (Prince, Bryce, & Ferri, 2011). The HTKS has demonstrated predictive validity with significant prediction of school readiness and academic achievement across diverse child samples (McClelland, Geldhof, Cameron, & Wanless, 2015). Future work should determine whether the HTKS can be utilized to predict cognitive outcomes in adult samples as well. The brief, cost-effective and easy to administer nature of the HTKS has the potential for practical significance in community, medical, and institutionalized care settings. The HTKS task design incorporates motoric engagement, instead of traditional paper and pencil and “spoken word” question and answer formats such as the BRFSS (Alzheimer’s Association and Centers for Disease Control and Prevention, 2013) or the Mini-Mental State Examination (MMSE; Folstein, Folstein, & McHugh, 1975). Further, the HTKS facilitates face-to-face social interaction, instead of administering items over the telephone like the Telephone Interview for Cognitive Status (TICS; Brandt, Spencer, & Folstein, 1988). In this way the HTKS provides a novel means of measuring multiple components of EF together that may augment existing paper and pencil, telephone, or computer-based screening measures, and perhaps provide unique predictive validity through its behavioral, game-like administration incorporating motoric engagement and face-to-face social interaction. Future research should compare the efficacy of the HTKS as a potential screening instrument to those already in the field (e.g., MMSE, Folstein, Folstein, & McHugh, 1975; TICS, Brandt, Spencer, Folstein, 1988). Potential Utility in Cognitive Interventions Applying the HTKS to cognitive interventions for older adult samples may be feasible and may inform the design of cognitive interventions that delay normative age-related declines in EF and cognitive function, in general. Interventions incorporating cognitively engaging activities, such as engagement models like volunteering to support elementary school children’s reading literacy (Carlson et al., 2008), learning digital photography and how to quilt (Park et al., 2014), as well as physical activity models like consistent aerobic exercise (e.g., Guiney & Machado, 2013), may have the greatest benefit for EF ability in late life. It is important to also recognize the value of training-based interventions. Training models are instrumental in preserving and improving certain task specific abilities, but lack transferability to other cognitive domains (e.g., see Simons et al., 2016 for a review of training-based cognitive interventions). Future work is needed to understand potential roles the HTKS may have in an intervention setting. In this study, 93% of the sample indicated interest in future studies that incorporated the HTKS, suggesting older adults may find it enjoyable to engage in the HTKS protocol, an important factor in constructing cognitive interventions that are engaging and maintain motivation to continue involvement in the intervention. Community hubs such as senior centers and fitness clubs may also benefit from HTKS use. Older adults concerned with their recent cognitive functioning may benefit from taking the HTKS at their local senior center or fitness club as a way of self-checking their cognitive health (in similar fashion to having one’s blood pressure taken periodically at a senior center). A freely available measure that is enjoyable for older adults and easy for researchers to administer offers a practical measure of EF that complements existing measures in the field. Limitations and Future Directions Several limitations of this study should be considered. While convergent validity correlation coefficients may seem relatively low, they were statistically significant and remained significant after adjusting for age, processing speed, and subjective health ratings. Further, low to moderate correlations are fairly common among measures of EF in adult samples (e.g., Hull et al., 2008; Miyake et al., 2000), suggesting our results are consistent with previous literature. The decision to only consider cognitively intact adults was intentional in this first study of the HTKS with older adults. However, lack of information about HTKS performance with individuals experiencing mild cognitive impairment or early dementia is a gap that needs to be addressed. Additionally, a convenience sample of community-dwelling older adults resulted in a sample of primarily Caucasian, female, physically and mentally healthy, and highly educated older adults. Future work should examine a more representative sample of older adults with a wide range of health conditions, ranging from chronic conditions that can be controlled (e.g., hypertension) to more severe conditions (e.g., advanced stages of Parkinson’s disease). Although seated administration is possible, a remaining limitation of the HTKS may hold for individuals who understand the directions but are physically unable to make the discernable motions (e.g., stroke survivors). Although the racial characteristics of our sample are similar to Oregon older adults (U.S. Census Bureau, 2015), a more diverse sample would be ideal. Although the sample size was not large, it is comparable to other studies (Hull et al., 2008; Mansbach, MacDougall, Clark, & Mace, 2014; Weintraub et al., 2014). Future studies should examine the predictive validity of the HTKS and explore its potential as a new cognitive screening instrument for those in community (e.g., senior center, fitness club), medical (e.g., doctor’s office), or institutionalized care settings (e.g., nursing home, memory care). More tools in the cognitive assessment arsenal are needed to promote cognitive health awareness among older adults and identify ways of optimizing EF. The HTKS is a novel instrument that is brief, low cost, easy to administer, engaging for older participants, and has the potential to bolster preventive screening efforts at the population level. Supplementary Data Supplementary data are available at The Gerontologist online. Funding This work was supported in part by the National Science Foundation (Grant DGE 0965820). Conflict of Interest None reported. Acknowledgment We would like to acknowledge Sandi Phibbs, PhD, for her insights and assistance in manuscript preparation and proofreading. 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Acta Psychologica , 115 , 167 – 183 . doi: 10.1016/j.actpsy.2003.12.005 Google Scholar CrossRef Search ADS PubMed © The Author(s) 2018. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices) http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png The Gerontologist Oxford University Press

A New Brief Measure of Executive Function: Adapting the Head-Toes-Knees-Shoulders Task to Older Adults

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Abstract

Abstract Background and Objectives Executive function (EF) abilities are recognized as components of cognition most likely to show age-related declines. Measurement of EF in older adults is often computer-based, takes place in a laboratory setting, and thus lacks ecological validity. We sought to investigate a new way of measuring EF in older adults by adapting a brief, behavioral measure of EF in children, the Head-Toes-Knees-Shoulders task (HTKS). Research Design and Methods A sample of 150 community-dwelling older adults (Mean age = 68.55, SD = 6.34) completed the HTKS, NIH Toolbox: Cognition Battery (NIHTB-CB) and Positive and Negative Affect Schedule. Results The HTKS showed adequate internal consistency, α = .84. Significant associations between HTKS variables and measures of attention and inhibitory control were robust to the influences of age, processing speed, and subjective health ratings. HTKS completion time exhibited the strongest associations to NIHTB-CB measures, suggesting that the time it takes older adults to complete the HTKS may be a better measure of EF than the total score. Nonsignificant associations between HTKS variables and positive and negative affect demonstrated discriminant validity. Discussion and Implications These results provide initial evidence for use of the HTKS as a brief, low-cost, easy to administer measure of EF in older adults. Further research is needed to determine its potential to identify individuals at risk for poor cognitive outcomes. A brief, valid measure may allow for wider screenings aimed at early intervention, when cognitive interventions are most effective. Cognitive function, Executive function, Measurement, Psychometrics Cognitive health is a paramount concern for individuals, as well as society (Alzheimer’s Association, 2016). Higher-level cognitive processes necessary for managing actions, thoughts, and emotions, collectively known as executive function (EF) abilities (e.g., attention, inhibitory control, working memory), are widely recognized as the components of cognition most likely to show age-related declines (Jurado & Rosselli, 2007; Zelazo, Craik, & Booth, 2004). The present study was designed to examine a new way of measuring EF in community-dwelling older adults, through the adaptation of a well-known measure of EF in children, the Head-Toes-Knees-Shoulders task (HTKS; McClelland et al., 2014). The HTKS is a game-like behavioral measure administered between participant and examiner designed to incorporate attention, inhibitory control, and working memory. It has the potential to be utilized in a variety of settings because it is brief, easy to administer, freely available for research purposes, and requires no special equipment (such as a computer). An important first step in assessing whether the HTKS could be widely utilized as a measure of EF is to determine its reliability and validity in a sample of older adults. Current EF Measurement in Older Adults Currently cognitive functioning is often assessed through comprehensive batteries administered via computerized assessment (e.g., the NIH Toolbox for the Assessment of Neurological and Behavioral Function Cognition Battery [NIHTB-CB; Gershon et al., 2013]; Cogstate [Maruff, Collie, Darby, Weaver-Cargin, & McStephen, 2002]) or via response booklets and stimulus materials (e.g., Pearson's Delis-Kaplan EF System [Delis, Kaplan, & Kramer, 2001]). There is variability, however, in the amount of equipment required, financial cost, examiner involvement, adequate validity of tests, and norming data for older adults (see Wild, Howieson, Webbe, Seelye, & Kaye, 2008 for a more comprehensive review). Further, computer-based measurement of EF tends to lack ecological validity, making it difficult to generalize performance to real world scenarios, thoughts, and behaviors (Müller & Kerns, 2015). A new measure that is brief, low-cost, and incorporates multiple components of EF via motoric engagement and social interaction may offer a more efficient way of analyzing EF in older adults. Further, the motoric engagement and social interaction involved in HTKS administration circumvents reliance on materials and computer-based administrations that have little generalizability to real-world scenarios. Prior Research with the HTKS Prior work implementing the HTKS has been restricted to children ages 4–6 (e.g., McClelland et al., 2007; Ponitz, McClelland, Matthews, & Morrison, 2009). McClelland et al. (2014) performed a psychometric evaluation of the HTKS in a longitudinal study and found that among diverse samples of young children, the HTKS demonstrated strong construct validity with measures of attention, inhibitory control, and working memory and also demonstrated high internal consistency reliability. Purpose and Research Question The current study is guided by the life-span theoretical perspective, and its underlying goal of optimizing development by means of maximizing gains and minimizing losses (Baltes, Lindenberger, & Staudinger, 2006). Plasticity, or the ability to adapt to changes in environment and react differently to stimuli throughout development, and culture are driving forces of development under this framework (Baltes, Lindenberger, & Staudinger, 2006). The overarching goal of this study was to determine if the HTKS (McClelland et al., 2014) could be adapted to older adult populations. We addressed the research question, what are the psychometric properties of the HTKS when used in older adults? We hypothesized adequate internal consistency, and strong convergent validity as compared to the “gold standard” measures in the NIHTB-CB (Gershon et al., 2013). We also aimed to explore discriminant validity by examining associations of the HTKS with a measure of a construct not related to EF. For this study, we utilized the construct of affect and used the Positive and Negative Affect Schedule (PANAS; Watson, Clark, & Tellegen, 1988). Specifically, we anticipated strong, significant relationships with measures of attention, inhibitory control, and working memory. Additionally, as an indication of discriminant validity, we anticipated no relationship with a measure of affect. In addition to components of EF, we considered whether processing speed is relevant for the HTKS because speeded performance is a crucial facet to the makeup of cognitive functioning in older adulthood (Kail & Salthouse, 1994). Age-related declines in processing speed are well documented (e.g., Schaie & Willis, 1993; Verhaeghen & Salthouse, 1997) and perhaps due to slower processing of particular mental operations as adults get older (Salthouse, 1996). Given the importance of speeded performance in cognitive aging research, we included timed completion of the HTKS and adjusted for processing speed in analyses. And finally, we include measures of self-reported memory, and physical and mental health to describe our sample. Design and Methods Participants A sample of 150 community-dwelling older adults (60 years of age and older) from Oregon were recruited via e-mail from a previously established participant pool (704 adults 60 years of age and older were eligible to receive the e-mail). Out of 210 adults who expressed interest in the study, 150 adults ultimately scheduled and completed the research protocol. Because this study is the first adaptation of the HTKS in older adults, the sample was limited to community-dwelling older adults with cognitive capacity to consent to research. All participants successfully demonstrated capacity to consent by answering questions regarding information presented in the consent form. Consistent with previous psychometric investigations of EF measures (see Mitchell & Miller, 2008; Weintraub et al., 2014), this study did not include structured screening to exclude participants with chronic medical conditions (e.g., arthritis, diabetes, heart disease) because we aimed to collect a representative sample of community-dwelling older adults. Measures and Procedures After institutional review board approval, participants were scheduled for a 1-hr block of testing in a research office. Participants were given a consent form followed by a brief paper and pencil questionnaire that included questions on demographics, subjective memory loss via a single item from the Cognitive Module of the Behavioral Risk Factor Surveillance System asking, “During the past 12 months, have you experienced confusion or memory loss that is happening more often or is getting worse?” (BRFSS; Alzheimer’s Association and Centers for Disease Control and Prevention, 2013), and self-reported health via the 12-item short form health survey (SF-12; Ware, Kosinksi, & Keller, 1995). A single item reflecting subjective memory loss was chosen due to previous literature demonstrating its efficacy in exhibiting a correlation with objective test performance (e.g., Mol, van Boxtel, Willems, & Jolles, 2006). Next, participants participated in the HTKS protocol (see description, below) to assess EF. Due to the importance of participant engagement in tasks used in cognitive research, participants then answered a question asking, “Would you be interested in playing a game similar to the task you just completed in other studies?” The NIHTB-CB (Gershon et al., 2013) was administered next, with specific measures in this order: computerized demographic form collecting highest level of education (ranging from 12th grade to doctorate degree), Dimensional Change Card Sort Test (DCCS), Flanker Inhibitory Control and Attention Test, List Sort Working Memory Test, and Pattern Comparison Processing Speed Test. A paper format of the PANAS (Watson, Clark, & Tellegen, 1988) followed NIHTB-CB completion. Demographics The sample of 150 participants (M = 68.55 years of age, SD = 6.34, Range = 60–88) completed a brief paper and pencil demographics questionnaire (Table 1). The sample were predominately female (72%), Caucasian (95%), self-identifying as Not Hispanic or Latino/Latina (96%), married (62%), and well educated (81% had at least a Bachelor’s degree). A single item from the BRFSS cognitive module showed 21% of participants reported subjective memory loss in the past year (dichotomized as 0 = no, 1 = yes for analyses). The SF-12 showed the self-reported mental health (M = 53.42, SD = 6.90) and physical health (M = 50.31, SD = 7.53) of the current sample were slightly better and more homogenous than the general U.S. population based on t-score conversions (M = 50, SD = 10; Ware, Kosinski, & Keller, 1995, p. 23). Table 1. Demographics of Sample (N = 150) Variable N % M (SD) Range Age 68.55 (6.34) 60–88  60–69 99 66  70–79 41 27.33  80–88 10 6.67% Gender  Female 108 72  Male 40 26.67  Missing 2 1.33 Race  African American 1 0.67  Asian 2 1.33  Caucasian 143 95.33  Native, Hawaiian, or Other Pacific Islander 1 0.67  Other 2 1.33  Missing 1 0.67 Ethnicity  Hispanic or Latino/ Latina 1 0.67  Not Hispanic or Latino/Latina 144 96  Missing 5 3.33 Marital Status  Married 93 62  Divorced 25 16.67  Single 16 10.67  Widowed 15 10  Missing 1 0.67 Educationa  12th grade – High School graduate 4 2.67  Some college – Associates degree 25 16.67  Bachelor’s Degree 58 38.67  Master’s Degree 44 29.33  Professional Degree – Doctorate Degree 19 12.67 Subjective Memory Lossb 31 20.67 Variable N % M (SD) Range Age 68.55 (6.34) 60–88  60–69 99 66  70–79 41 27.33  80–88 10 6.67% Gender  Female 108 72  Male 40 26.67  Missing 2 1.33 Race  African American 1 0.67  Asian 2 1.33  Caucasian 143 95.33  Native, Hawaiian, or Other Pacific Islander 1 0.67  Other 2 1.33  Missing 1 0.67 Ethnicity  Hispanic or Latino/ Latina 1 0.67  Not Hispanic or Latino/Latina 144 96  Missing 5 3.33 Marital Status  Married 93 62  Divorced 25 16.67  Single 16 10.67  Widowed 15 10  Missing 1 0.67 Educationa  12th grade – High School graduate 4 2.67  Some college – Associates degree 25 16.67  Bachelor’s Degree 58 38.67  Master’s Degree 44 29.33  Professional Degree – Doctorate Degree 19 12.67 Subjective Memory Lossb 31 20.67 Note: aEducation was collapsed into five categories. All education levels include 12th grade, High School graduate, Some college but less than 1 year, One or more years of college no degree, Associate’s degree, Bachelor’s degree, Master’s degree, Professional degree, Doctorate degree. bSubjective Memory Loss denotes the participants that self-reported confusion or memory loss that is happening more often or is getting worse during the past 12 months. View Large Table 1. Demographics of Sample (N = 150) Variable N % M (SD) Range Age 68.55 (6.34) 60–88  60–69 99 66  70–79 41 27.33  80–88 10 6.67% Gender  Female 108 72  Male 40 26.67  Missing 2 1.33 Race  African American 1 0.67  Asian 2 1.33  Caucasian 143 95.33  Native, Hawaiian, or Other Pacific Islander 1 0.67  Other 2 1.33  Missing 1 0.67 Ethnicity  Hispanic or Latino/ Latina 1 0.67  Not Hispanic or Latino/Latina 144 96  Missing 5 3.33 Marital Status  Married 93 62  Divorced 25 16.67  Single 16 10.67  Widowed 15 10  Missing 1 0.67 Educationa  12th grade – High School graduate 4 2.67  Some college – Associates degree 25 16.67  Bachelor’s Degree 58 38.67  Master’s Degree 44 29.33  Professional Degree – Doctorate Degree 19 12.67 Subjective Memory Lossb 31 20.67 Variable N % M (SD) Range Age 68.55 (6.34) 60–88  60–69 99 66  70–79 41 27.33  80–88 10 6.67% Gender  Female 108 72  Male 40 26.67  Missing 2 1.33 Race  African American 1 0.67  Asian 2 1.33  Caucasian 143 95.33  Native, Hawaiian, or Other Pacific Islander 1 0.67  Other 2 1.33  Missing 1 0.67 Ethnicity  Hispanic or Latino/ Latina 1 0.67  Not Hispanic or Latino/Latina 144 96  Missing 5 3.33 Marital Status  Married 93 62  Divorced 25 16.67  Single 16 10.67  Widowed 15 10  Missing 1 0.67 Educationa  12th grade – High School graduate 4 2.67  Some college – Associates degree 25 16.67  Bachelor’s Degree 58 38.67  Master’s Degree 44 29.33  Professional Degree – Doctorate Degree 19 12.67 Subjective Memory Lossb 31 20.67 Note: aEducation was collapsed into five categories. All education levels include 12th grade, High School graduate, Some college but less than 1 year, One or more years of college no degree, Associate’s degree, Bachelor’s degree, Master’s degree, Professional degree, Doctorate degree. bSubjective Memory Loss denotes the participants that self-reported confusion or memory loss that is happening more often or is getting worse during the past 12 months. View Large HTKS The HTKS is comprised of 30 test items divided equally across three sections with a maximum of four paired behavioral rules applied to the task: “touch your head” and “touch your toes;” “touch your shoulders” and “touch your knees.” Each section begins with the participant responding naturally (e.g., touching head when instructed to touch head), followed by an instruction to change the rules and respond in “opposite” fashion (e.g., touching head when instructed to touch toes). Section 1 includes only two behavioral rules, head goes with toes and toes go with head. Section 2 involves adding the additional two behavioral rules regarding shoulders and knees (e.g., touching their shoulders when instructed to touch their knees). Participants advance to the final section if they are able to respond correctly to all four paired behavioral rules. Section 3 involves switching the paired rules (e.g., touching their head when instructed to touch their knees, and touching their shoulders when instructed to touch their toes). All participants advanced to the third section and completed the 30 test items. Although the measure is designed for the participant to stand up, it is not a requirement of the task. Therefore, if the participant indicated that sitting down was preferable, a seated administration option was offered (Four participants sat down during task administration). The examiner scores the participant’s responses on a three-point scale, including 0(incorrect), 1(self-correct), or 2(correct) for each test item. An incorrect response is scored when the participant does not touch the correct part of their body or touches the part of their body spoken in the instruction (e.g., when asked to touch their head in the first and second sections, a participant touches their head instead of their toes). A self-correct response is scored when the participant makes a discernable motion toward an incorrect response, but then adjusts and makes the correct response (e.g., when asked to touch their head, a participant may initially move toward an incorrect response of touching their head, and then quickly change their mind to touch their toes). A correct response is scored when the participant makes a discernable motion toward the correct part of their body, either immediately or after a pause to think. Participants were allowed to point to body parts in lieu of touching if they preferred. A total score is generated by adding up each of the 30 test items, with a possible range of 0 to 60. Higher scores indicate higher levels of EF. The HTKS is freely available for research purposes only by submitting an online request using the following website address: http://health.oregonstate.edu/labs/kreadiness/resources. Online training is required for those who intend to use the HTKS upon completion of the online request form. In addition to the total score variable, we included a variable for completion time by monitoring how long (in seconds) each participant took to complete the HTKS. Using a digital stopwatch, the test administrator began timing at the start of HTKS task instructions, and ended on the final behavioral response to the task (Item 30). Faster completion times indicate better EF as shorter completion times show more efficient cognitive processing. NIHTB-CB At the time this study was conducted, administration of the NIHTB-CB (Gershon et al., 2013; www.nihtoolbox.org) required a trained examiner administering the tests from a laptop with a dual-monitor function and speakers. For each measure, this battery provides a raw score, computed score, unadjusted scale score, age-adjusted scale score, national percentile rank, and fully adjusted scale score (adjusts for age, gender, race, ethnicity, and education), as well as a total summary score (We have provided these scores in Supplementary Table 1). Among individuals aged 3–85 years, the NIHTB-CB measures have adequate convergent validity as compared to D-KEFS Inhibition (DCCS and Flanker), Wechsler Adult Intelligence Scale – 4th edition (WAIS-IV) Letter-Number Sequencing, Coding, and Symbol Search (Flanker and Pattern Comparison), and WAIS-IV Letter-Number Sequencing and Symbol Search (List Sort), as well as discriminant validity as compared to the Peabody Picture Vocabulary Test – 4th Edition (Weintraub et al., 2014; Zelazo et al., 2014). For the purposes of this study, we used four tests from the battery instead of a composite score to isolate the cognitive dimensions relevant to the HTKS. We utilized age-adjusted scores from these measures because of the wide range of ages sampled (Range: 60–88 years of age). Each of the four measures administered are described below. DCCS This test measures attentional set shifting, or the ability to switch attentional focus among multiple task features. Using left and right arrow keys, the test involves matching a target stimulus to one of two option stimuli depending on “shape” or “color” direction words presented on the previous screen. Participants take 4 min on average to complete 40 total trials; an algorithm combining accuracy and reaction time computed the score (ranging from 0–10). Flanker inhibitory control and attention test This test measures inhibitory control, or the ability to inhibit one’s attention to irrelevant details within the test. Each trial involves an arrow target stimulus in the center of the screen that is flanked by congruent or incongruent arrows on each side. Participants select which direction the central stimulus is pointing via left and right arrow keys. Participants take four minutes on average to complete 40 total trials; an algorithm combining accuracy and reaction time computed the score (ranging from 0–10). List sort working memory test This test measures working memory, or the ability to process, store, and update information. The test involves two sections where a set of stimuli is presented to the participant visually and orally, one at a time. The test requires the participant to report the stimulus items back to the examiner in size order, from smallest to largest. Section 1 presents the same category to the participant. Section 2 presents two different categories of stimulus items with the instruction to report stimuli from one category, then the other category, both from smallest to largest. For example, the stimulus items “corn, egg, dog, cherry, elephant, mouse” would be correctly repeated as “cherry, egg, corn, mouse, dog, elephant.” The number of stimulus items increases each time a successful report occurs up to seven total items. Participants take 7 min on average to complete this test, and the score is derived from the number of items correct across all trials. Pattern comparison processing speed test This test measures processing speed, operationalized as the amount of information processed in 90 s via left and right arrow keys. The test consists of participants determining whether two visual stimuli are the “same” or “not the same”. Participants have 90 s to answer as many items as they can up to 130 items, and the score is derived from the number of items correct across all trials. PANAS The PANAS (Watson et al., 1988) is a 20-item subjective measure of feelings and emotions that includes 10 items assessing positive affect (PA; e.g., “excited,” “inspired,” “proud”) and 10 items assessing negative affect (NA; e.g., “distressed,” “hostile,” “afraid”). Crawford and Henry (2004) reported adequate internal consistency for both the PA (α = .89) and NA (α = .85) scales. Participants are asked to “indicate to what extent you have felt this way today.” Answered on a five-point Likert-type scale, the PANAS ranges from 1 (very slightly or not at all) to 5 (extremely). Scores range from 10 to 50 for the PA scale and the NA scale, with higher scores indicating higher levels of PA and NA. In the current study, the PANAS demonstrated adequate internal consistency for both the PA (α = .84) and NA (α = .81) scales. Analyses We used Cronbach’s α reliability to assess internal consistency. To determine convergent validity, we analyzed initial bivariate correlations between HTKS variables (total score and completion time) and the NIHTB-CB DCCS, Flanker, List Sort, and Pattern Comparison tests (Gershon et al., 2013). Per Cohen (1992), an r of .10 to .30 indicates a small to medium effect size, .30 to .50 indicates a medium to large effect size, and .50 and larger indicates a large effect size. We used multiple regression analyses to determine if significant associations between HTKS variables and the DCCS, Flanker, and List Sort tests were robust to statistical adjustment for age, processing speed, and subjective health ratings (subjective memory loss and self-rated physical and mental health). To assess discriminant validity, we analyzed bivariate correlations between HTKS variables and PA and NA using the PANAS (Watson et al., 1988). Analyses were performed using Stata LC13 statistical software (StataCorp, 2013). Results Descriptive Statistics Table 2 includes all descriptive statistics for primary variables in the analyses. In the present study, we observed a ceiling effect in HTKS total score, with most participants scoring highly on the task (83% of the sample achieved a score between 56 and 60). Compared to the ceiling effect found in the HTKS total score variable, HTKS completion time showed more variability in scores (M = 4 min, 43 s, SD = 29.91 s, Range = 3 min, 56 s – 6 min, 53 s). Due to the ceiling effect in HTKS total score in this relatively healthy older sample, we utilized HTKS completion time as an additional variable of HTKS performance incorporating speed of processing. Table 2. Descriptive Statistics for Analysis Variables Variable M (SD) Range α Inter-item α range HTKSa  HTKS Total Score 57.03 (4.42) 34–60 .84 .82–.84  HTKS Completion Time (seconds) 283.07 (29.91) 236.25–413.10 NIHTB-CBb  DCCS 109.63 (9.62) 78.30–130.83  Flanker 100.47 (9.29) 79.15–124.72  List Sort 112.26 (12.04) 76.17–141.57  Pattern Comparison 105.53 (19.11) 47.05–147.97 PAc 36.68 (5.65) 18–48 .84 .82–.84 NAd 13.27 (3.57) 10–30 .81 .77–.81 SF-12 Health Surveye 51.87 (5.14) 28.14–58.76 .81 .78–.81  Physical Health 50.31 (7.53) 24.82–64.28 .76 .71–.73  Mental Health 53.42 (6.90) 31.42–64.33 .70 .59–.70 Variable M (SD) Range α Inter-item α range HTKSa  HTKS Total Score 57.03 (4.42) 34–60 .84 .82–.84  HTKS Completion Time (seconds) 283.07 (29.91) 236.25–413.10 NIHTB-CBb  DCCS 109.63 (9.62) 78.30–130.83  Flanker 100.47 (9.29) 79.15–124.72  List Sort 112.26 (12.04) 76.17–141.57  Pattern Comparison 105.53 (19.11) 47.05–147.97 PAc 36.68 (5.65) 18–48 .84 .82–.84 NAd 13.27 (3.57) 10–30 .81 .77–.81 SF-12 Health Surveye 51.87 (5.14) 28.14–58.76 .81 .78–.81  Physical Health 50.31 (7.53) 24.82–64.28 .76 .71–.73  Mental Health 53.42 (6.90) 31.42–64.33 .70 .59–.70 Note: aHTKS = Head-Toes-Knees-Shoulders Task (HTKS; McClelland et al., 2014), with Total and Completion Time (in seconds) scores. bNIHTB = National Institutes of Health Toolbox – Cognition Battery (www.nihtoolbox.org). DCCS = Dimensional Change Card Sort = a measure of attentional shifting. Flanker = a measure of inhibitory control. List Sort = a measure of working memory. Pattern Comparison = a measure of processing speed. cPA = Positive Affect. dNA = Negative Affect. Sub-scales derived from the Positive and Negative Affect Schedule (PANAS; Watson, Clark, & Tellegen, 1988). eSF-12 Health Survey = Self-rated health survey with Physical Health and Mental Health subscales comparable to the general U.S. population (M = 50, SD = 10). View Large Table 2. Descriptive Statistics for Analysis Variables Variable M (SD) Range α Inter-item α range HTKSa  HTKS Total Score 57.03 (4.42) 34–60 .84 .82–.84  HTKS Completion Time (seconds) 283.07 (29.91) 236.25–413.10 NIHTB-CBb  DCCS 109.63 (9.62) 78.30–130.83  Flanker 100.47 (9.29) 79.15–124.72  List Sort 112.26 (12.04) 76.17–141.57  Pattern Comparison 105.53 (19.11) 47.05–147.97 PAc 36.68 (5.65) 18–48 .84 .82–.84 NAd 13.27 (3.57) 10–30 .81 .77–.81 SF-12 Health Surveye 51.87 (5.14) 28.14–58.76 .81 .78–.81  Physical Health 50.31 (7.53) 24.82–64.28 .76 .71–.73  Mental Health 53.42 (6.90) 31.42–64.33 .70 .59–.70 Variable M (SD) Range α Inter-item α range HTKSa  HTKS Total Score 57.03 (4.42) 34–60 .84 .82–.84  HTKS Completion Time (seconds) 283.07 (29.91) 236.25–413.10 NIHTB-CBb  DCCS 109.63 (9.62) 78.30–130.83  Flanker 100.47 (9.29) 79.15–124.72  List Sort 112.26 (12.04) 76.17–141.57  Pattern Comparison 105.53 (19.11) 47.05–147.97 PAc 36.68 (5.65) 18–48 .84 .82–.84 NAd 13.27 (3.57) 10–30 .81 .77–.81 SF-12 Health Surveye 51.87 (5.14) 28.14–58.76 .81 .78–.81  Physical Health 50.31 (7.53) 24.82–64.28 .76 .71–.73  Mental Health 53.42 (6.90) 31.42–64.33 .70 .59–.70 Note: aHTKS = Head-Toes-Knees-Shoulders Task (HTKS; McClelland et al., 2014), with Total and Completion Time (in seconds) scores. bNIHTB = National Institutes of Health Toolbox – Cognition Battery (www.nihtoolbox.org). DCCS = Dimensional Change Card Sort = a measure of attentional shifting. Flanker = a measure of inhibitory control. List Sort = a measure of working memory. Pattern Comparison = a measure of processing speed. cPA = Positive Affect. dNA = Negative Affect. Sub-scales derived from the Positive and Negative Affect Schedule (PANAS; Watson, Clark, & Tellegen, 1988). eSF-12 Health Survey = Self-rated health survey with Physical Health and Mental Health subscales comparable to the general U.S. population (M = 50, SD = 10). View Large Psychometric Assessment of the HTKS Adequate internal consistency was demonstrated by Cronbach’s α of the overall HTKS task (α = .84) and its interitem α range (.82–.84). Initial bivariate correlations supporting convergent validity and discriminant validity of the HTKS are presented in Table 3. Higher HTKS total scores were associated with higher scores on the Pattern Comparison (r = .24, p < .01) and DCCS (r = .17, p < .05), but not the Flanker (r = .07, p > .05) or List Sort (r = −.01, p > .05). Multiple regression analyses revealed higher DCCS scores significantly related to higher HTKS total score after adjusting for the influences of age, processing speed, and subjective health ratings (b = 0.09, SE = 0.04, p < .05; see Table 4), and explained 9% of the variance in HTKS total score (Adj. R2 = .09, F(6, 132) = 3.19, p < .01). Table 3. Bivariate Correlations Demonstrating Convergent and Discriminant Validity of the HTKS Variable 1 2 3 4 5 6 7 8 1. HTKS Total - 2. HTKS Timea −.30*** - 3. DCCSb .17* −.21** - 4. Flankerc .07 −.20* .51*** - 5. List Sortd −.01 −.10 .32*** .08 - 6. Pattern Comparisone .34** −.30*** .28*** .33*** .18* - 7. PAf .01 .01 −.00 −.06 −.01 −.04 - 8. NAg .10 .04 −.10 .01 −.16 −.08 −.02 - Variable 1 2 3 4 5 6 7 8 1. HTKS Total - 2. HTKS Timea −.30*** - 3. DCCSb .17* −.21** - 4. Flankerc .07 −.20* .51*** - 5. List Sortd −.01 −.10 .32*** .08 - 6. Pattern Comparisone .34** −.30*** .28*** .33*** .18* - 7. PAf .01 .01 −.00 −.06 −.01 −.04 - 8. NAg .10 .04 −.10 .01 −.16 −.08 −.02 - Note: *p < .05. **p < .01. ***p < .001. Two-tailed. aHTKS Completion Time = Total time in seconds to complete the HTKS task. bDCCS = NIH Toolbox Dimensional Change Cart Sort Test; a measure of attentional shifting. cFlanker = NIH Toolbox Flanker Inhibitory Control and Attention Test; a measure of inhibitory control. dList Sort = NIH Toolbox List Sort Working Memory Test; a measure of working memory. ePattern Comparison = NIH Toolbox Pattern Comparison Processing Speed Test; a measure of processing speed. fPA = Positive Affect. gNA = Negative Affect. Sub-scales derived from the Positive and Negative Affect Schedule (PANAS; Watson, Clark, & Tellegen, 1988). View Large Table 3. Bivariate Correlations Demonstrating Convergent and Discriminant Validity of the HTKS Variable 1 2 3 4 5 6 7 8 1. HTKS Total - 2. HTKS Timea −.30*** - 3. DCCSb .17* −.21** - 4. Flankerc .07 −.20* .51*** - 5. List Sortd −.01 −.10 .32*** .08 - 6. Pattern Comparisone .34** −.30*** .28*** .33*** .18* - 7. PAf .01 .01 −.00 −.06 −.01 −.04 - 8. NAg .10 .04 −.10 .01 −.16 −.08 −.02 - Variable 1 2 3 4 5 6 7 8 1. HTKS Total - 2. HTKS Timea −.30*** - 3. DCCSb .17* −.21** - 4. Flankerc .07 −.20* .51*** - 5. List Sortd −.01 −.10 .32*** .08 - 6. Pattern Comparisone .34** −.30*** .28*** .33*** .18* - 7. PAf .01 .01 −.00 −.06 −.01 −.04 - 8. NAg .10 .04 −.10 .01 −.16 −.08 −.02 - Note: *p < .05. **p < .01. ***p < .001. Two-tailed. aHTKS Completion Time = Total time in seconds to complete the HTKS task. bDCCS = NIH Toolbox Dimensional Change Cart Sort Test; a measure of attentional shifting. cFlanker = NIH Toolbox Flanker Inhibitory Control and Attention Test; a measure of inhibitory control. dList Sort = NIH Toolbox List Sort Working Memory Test; a measure of working memory. ePattern Comparison = NIH Toolbox Pattern Comparison Processing Speed Test; a measure of processing speed. fPA = Positive Affect. gNA = Negative Affect. Sub-scales derived from the Positive and Negative Affect Schedule (PANAS; Watson, Clark, & Tellegen, 1988). View Large Table 4. Multiple Regression Analyses for DCCS Predicting HTKS Total Score (N = 139) Model 1 Model 2 Variable B SE B β B SE B β Age −0.18** 0.07 −0.23 Pattern Comparisona 0.03 0.02 0.14 Subjective Memory Lossb 0.19 0.95 0.02 SF-12 Physical Healthc 0.01 0.05 0.02 SF-12 Mental Healthd −0.05 0.05 −0.08 DCCSe 0.09* 0.04 0.18 0.09* 0.04 0.20 F 4.72* 3.19** Adj. R2 0.03 0.09 F for change in R2 2.82* Model 1 Model 2 Variable B SE B β B SE B β Age −0.18** 0.07 −0.23 Pattern Comparisona 0.03 0.02 0.14 Subjective Memory Lossb 0.19 0.95 0.02 SF-12 Physical Healthc 0.01 0.05 0.02 SF-12 Mental Healthd −0.05 0.05 −0.08 DCCSe 0.09* 0.04 0.18 0.09* 0.04 0.20 F 4.72* 3.19** Adj. R2 0.03 0.09 F for change in R2 2.82* Note: *p < .05. **p < .01. ***p < .001. Two-tailed. aPattern Comparison = NIH Toolbox Pattern Comparison Processing Speed Test; a measure of processing speed. bSubjective Memory Loss denotes the participants that self-reported confusion or memory loss that is happening more often or is getting worse during the past 12 months. cSelf-rated Physical Health is derived from the SF-12 Health Survey and can be compared to the general U.S. population based on t-score conversions (M = 50, SD = 10). dSelf-rated Mental Health is derived from the SF-12 Health Survey and can be compared to the general U.S. population based on t-score conversions (M = 50, SD = 10). eDCCS = NIH Toolbox Dimensional Change Cart Sort Test; a measure of attentional shifting. View Large Table 4. Multiple Regression Analyses for DCCS Predicting HTKS Total Score (N = 139) Model 1 Model 2 Variable B SE B β B SE B β Age −0.18** 0.07 −0.23 Pattern Comparisona 0.03 0.02 0.14 Subjective Memory Lossb 0.19 0.95 0.02 SF-12 Physical Healthc 0.01 0.05 0.02 SF-12 Mental Healthd −0.05 0.05 −0.08 DCCSe 0.09* 0.04 0.18 0.09* 0.04 0.20 F 4.72* 3.19** Adj. R2 0.03 0.09 F for change in R2 2.82* Model 1 Model 2 Variable B SE B β B SE B β Age −0.18** 0.07 −0.23 Pattern Comparisona 0.03 0.02 0.14 Subjective Memory Lossb 0.19 0.95 0.02 SF-12 Physical Healthc 0.01 0.05 0.02 SF-12 Mental Healthd −0.05 0.05 −0.08 DCCSe 0.09* 0.04 0.18 0.09* 0.04 0.20 F 4.72* 3.19** Adj. R2 0.03 0.09 F for change in R2 2.82* Note: *p < .05. **p < .01. ***p < .001. Two-tailed. aPattern Comparison = NIH Toolbox Pattern Comparison Processing Speed Test; a measure of processing speed. bSubjective Memory Loss denotes the participants that self-reported confusion or memory loss that is happening more often or is getting worse during the past 12 months. cSelf-rated Physical Health is derived from the SF-12 Health Survey and can be compared to the general U.S. population based on t-score conversions (M = 50, SD = 10). dSelf-rated Mental Health is derived from the SF-12 Health Survey and can be compared to the general U.S. population based on t-score conversions (M = 50, SD = 10). eDCCS = NIH Toolbox Dimensional Change Cart Sort Test; a measure of attentional shifting. View Large Taking longer to complete the HTKS was associated with lower scores on the Pattern Comparison (r = −.30, p < .001), DCCS (r = −0.21, p < .01), and Flanker (r = −.20, p < .05), but not the List Sort test (r = −.10, p > .05). After adjusting for age, processing speed and subjective health ratings, higher DCCS scores (b = −0.75, SE = 0.25, p < .01) and higher Flanker scores (b = −0.67, SE = 0.27, p < .05) related to faster HTKS completion time (see Table 5), and explained 18% of the variance (Adj. R2 = .18, F(6, 132) = 5.90, p < .001) and 16% of the variance (Adj. R2 = .16, F(6, 132) = 5.26, p < .001) in HTKS completion time, respectively. Table 5. Multiple Regression Analyses for DCCS and Flanker Predicting HTKS Completion Time (N = 139) Model 1 Model 2 Variable B SE B β B SE B β Age 1.56** 0.45 0.29 Pattern Comparisona −0.28* 0.13 −0.18 Subjective Memory Lossb 6.28 6.03 0.09 SF-12 Physical Healthc 0.17 0.31 0.04 SF-12 Mental Healthd 0.22 0.34 0.05 DCCSe −0.73** 0.26 −0.23 −0.81** 0.26 −0.26 F 7.89** 5.90*** Adj. R2 0.05 0.18 F for change in R2 5.26*** Age 1.41** 0.45 0.27 Pattern Comparisona −0.28* 0.14 −0.18 Subjective Memory Lossb 7.26 6.10 0.10 SF-12 Physical Healthc 0.20 0.31 0.05 SF-12 Mental Healthd 0.30 0.35 0.07 Flankerf −0.70** 0.26 −0.22 −0.67* 0.27 −0.21 F 6.96** 5.26*** Adj. R2 0.04 0.16 F for change in R2 4.73*** Model 1 Model 2 Variable B SE B β B SE B β Age 1.56** 0.45 0.29 Pattern Comparisona −0.28* 0.13 −0.18 Subjective Memory Lossb 6.28 6.03 0.09 SF-12 Physical Healthc 0.17 0.31 0.04 SF-12 Mental Healthd 0.22 0.34 0.05 DCCSe −0.73** 0.26 −0.23 −0.81** 0.26 −0.26 F 7.89** 5.90*** Adj. R2 0.05 0.18 F for change in R2 5.26*** Age 1.41** 0.45 0.27 Pattern Comparisona −0.28* 0.14 −0.18 Subjective Memory Lossb 7.26 6.10 0.10 SF-12 Physical Healthc 0.20 0.31 0.05 SF-12 Mental Healthd 0.30 0.35 0.07 Flankerf −0.70** 0.26 −0.22 −0.67* 0.27 −0.21 F 6.96** 5.26*** Adj. R2 0.04 0.16 F for change in R2 4.73*** Note: *p < .05. **p < .01. ***p < .001. Two-tailed. aPattern Comparison = NIH Toolbox Pattern Comparison Processing Speed Test; a measure of processing speed. bSubjective Memory Loss denotes the participants that self-reported confusion or memory loss that is happening more often or is getting worse during the past 12 months. cSelf-rated Physical Health is derived from the SF-12 Health Survey and can be compared to the general U.S. population based on t-score conversions (M = 50, SD = 10). dSelf-rated Mental Health is derived from the SF-12 Health Survey and can be compared to the general U.S. population based on t-score conversions (M = 50, SD = 10). eDCCS = NIH Toolbox Dimensional Change Cart Sort Test; a measure of attentional shifting. fFlanker = NIH Toolbox Flanker Inhibitory Control and Attention Test; a measure of inhibitory control. View Large Table 5. Multiple Regression Analyses for DCCS and Flanker Predicting HTKS Completion Time (N = 139) Model 1 Model 2 Variable B SE B β B SE B β Age 1.56** 0.45 0.29 Pattern Comparisona −0.28* 0.13 −0.18 Subjective Memory Lossb 6.28 6.03 0.09 SF-12 Physical Healthc 0.17 0.31 0.04 SF-12 Mental Healthd 0.22 0.34 0.05 DCCSe −0.73** 0.26 −0.23 −0.81** 0.26 −0.26 F 7.89** 5.90*** Adj. R2 0.05 0.18 F for change in R2 5.26*** Age 1.41** 0.45 0.27 Pattern Comparisona −0.28* 0.14 −0.18 Subjective Memory Lossb 7.26 6.10 0.10 SF-12 Physical Healthc 0.20 0.31 0.05 SF-12 Mental Healthd 0.30 0.35 0.07 Flankerf −0.70** 0.26 −0.22 −0.67* 0.27 −0.21 F 6.96** 5.26*** Adj. R2 0.04 0.16 F for change in R2 4.73*** Model 1 Model 2 Variable B SE B β B SE B β Age 1.56** 0.45 0.29 Pattern Comparisona −0.28* 0.13 −0.18 Subjective Memory Lossb 6.28 6.03 0.09 SF-12 Physical Healthc 0.17 0.31 0.04 SF-12 Mental Healthd 0.22 0.34 0.05 DCCSe −0.73** 0.26 −0.23 −0.81** 0.26 −0.26 F 7.89** 5.90*** Adj. R2 0.05 0.18 F for change in R2 5.26*** Age 1.41** 0.45 0.27 Pattern Comparisona −0.28* 0.14 −0.18 Subjective Memory Lossb 7.26 6.10 0.10 SF-12 Physical Healthc 0.20 0.31 0.05 SF-12 Mental Healthd 0.30 0.35 0.07 Flankerf −0.70** 0.26 −0.22 −0.67* 0.27 −0.21 F 6.96** 5.26*** Adj. R2 0.04 0.16 F for change in R2 4.73*** Note: *p < .05. **p < .01. ***p < .001. Two-tailed. aPattern Comparison = NIH Toolbox Pattern Comparison Processing Speed Test; a measure of processing speed. bSubjective Memory Loss denotes the participants that self-reported confusion or memory loss that is happening more often or is getting worse during the past 12 months. cSelf-rated Physical Health is derived from the SF-12 Health Survey and can be compared to the general U.S. population based on t-score conversions (M = 50, SD = 10). dSelf-rated Mental Health is derived from the SF-12 Health Survey and can be compared to the general U.S. population based on t-score conversions (M = 50, SD = 10). eDCCS = NIH Toolbox Dimensional Change Cart Sort Test; a measure of attentional shifting. fFlanker = NIH Toolbox Flanker Inhibitory Control and Attention Test; a measure of inhibitory control. View Large As an indicator of discriminant validity, HTKS total score was not associated with PA (r = .01, p > .05) or NA (r = .10, p > .05). HTKS completion time was not associated with PA (r = .01, p > .05) or NA (r = .04, p > .05). These results indicate that the HTKS was associated with constructs hypothesized to be related to it, such as attention and inhibitory control, showing aspects of convergent validity that are robust to age, speed of processing, and subjective health rating influences. Importantly, the HTKS was not related to constructs (e.g., affect) thought to be conceptually unrelated to the HTKS, indicating adequate discriminant validity. Discussion This first study utilizing the HTKS as a measure of EF in community-dwelling older adults has shown it to demonstrate adequate internal consistency, convergent validity with measures of attention and inhibitory control, and discriminant validity as compared to a measure of affect. Our results indicate this brief behavioral measure of EF is low-cost, easy to administer (minimal equipment required) and incorporates motoric engagement in ways that existing EF measures do not. Participants in this study took, on average, less than 5 min. Because administration involves face-to-face interaction between participant and examiner, total administration takes approximately 5–7 min. For our study, implementation of the four NIHTB-CB tests took approximately 20–25 min in total (5–10 total minutes preparing for implementation and reading all task directions, 4-min DCCS, 4-min Flanker, 7-min List Sort, and 90 s Pattern Comparison). Well known measures of EF such as the tests in the NIHTB-CB used in this study require computer-based equipment for administration that adds preparation time and resource allocation to purchase necessary equipment. Since the current study’s data collection, the NIHTB-CB now offers an iPad administration that requires a subscription cost for continued access (yearly subscription of $499.99). Our results demonstrate that the HTKS provides an alternative, freely available measure that takes 5–7 min to assess multiple components of EF together with no computer-based equipment necessary. We examined convergent validity with measures of attention, inhibitory control, and working memory because the HTKS has been found to converge with these components of EF in children (McClelland et al., 2014), and previous factor analytic accounts have examined these three components of EF when identifying distinguishable dimensions of EF among young adults (Miyake et al., 2000) and older adults (Hedden & Yoon, 2006; Hull, Martin, Beier, Lane, & Hamilton, 2008). Use of completion time as a measure of HTKS performance avoided the ceiling effect, and provided a measure with more variability. The significant negative association (r = −.30) between HTKS completion time and HTKS total score (i.e., faster completion time related to higher total scores) suggests faster completion times indicate better EF as shorter completion times show more efficient cognitive processing. The following discussion of the psychometric evaluation includes both total score and completion time as measures of HTKS performance in this sample. Aspects of Internal Consistency, Convergent Validity, and Discriminant Validity The HTKS was an internally consistent measure in our older adult sample (α = .84). Associations between HTKS variables and NIHTB-CB measures of attention and inhibitory control were strongest for completion time (not total score) as the measure of HTKS performance, and regression models adjusting for potential confounds and subjective health ratings explained more variance in completion time (16%–18%) than total score (9%). Faster cognitive processing as measured by HTKS completion time was significantly associated with better attention and inhibitory control, but not working memory. Better EF as measured by HTKS total score was associated with better attention, but not inhibitory control or working memory. As hypothesized, both HTKS completion time and total score were unrelated to PA and NA in this older adult sample, constructs thought to be conceptually unrelated to EF. Associations between HTKS variables and NIHTB-CB tasks of attention and inhibitory control were robust to the influences of age, processing speed, and subjective health ratings. Given the relevance of age-related declines in processing speed, it is important to demonstrate HTKS performance is not simply due to an individual’s speed of processing. Adjusting for these potential confounders, subjective memory loss, and self-rated health strengthens the aspects of convergent validity observed in this study and suggests attention and inhibitory control may be relevant domains of EF for HTKS performance in older adulthood, especially for HTKS completion time. Future work examining associations between the HTKS and self-ratings of EF abilities or complaints would offer an additional aspect of convergent validity linking the behavioral task with subjective ratings of everyday EF. It was surprising that working memory was not related to HTKS completion time or total score. It is possible that a restriction of range in the HTKS task resulted in the inability to detect a correlation with the more variable scores of the List Sort test. In addition, perhaps participants found the List Sort test substantively more challenging than the other three measures in the NIHTB-CB. It is also possible that the HTKS is best aligned with measures of EF that involve a timed component. Age Differences The complexity of EF and how its structure can vary by age group and task is further demonstrated by the differential correlations found between the HTKS and EF domains depending on age group. McClelland et al. (2014) suggested that the HTKS may be specifically incorporating inhibitory control in younger children, attention in children from 4 to 6 years, and working memory in older children. In our sample of older adults, the HTKS may be specifically incorporating attention and inhibitory control, but not working memory. As would be expected, post-hoc correlations showed significant associations between age and HTKS variables such that older age was related to slower HTKS completion time (r = .36, p < .001) and lower HTKS total score (r = −.22, p = .008). Further research can address the variation in relevant EF domains for HTKS performance based on age and task by assessing the factor structure of the HTKS. Implications for Practice By demonstrating aspects of reliability and validity of the HTKS in community-dwelling older adults, this study offers a foundation for future work to examine whether the HTKS may prospectively predict changes in cognitive functioning. Identifying a brief, valid measure of cognitive function may allow for wider screenings at the population level aimed toward intervening early when interventions are most effective (Prince, Bryce, & Ferri, 2011). The HTKS has demonstrated predictive validity with significant prediction of school readiness and academic achievement across diverse child samples (McClelland, Geldhof, Cameron, & Wanless, 2015). Future work should determine whether the HTKS can be utilized to predict cognitive outcomes in adult samples as well. The brief, cost-effective and easy to administer nature of the HTKS has the potential for practical significance in community, medical, and institutionalized care settings. The HTKS task design incorporates motoric engagement, instead of traditional paper and pencil and “spoken word” question and answer formats such as the BRFSS (Alzheimer’s Association and Centers for Disease Control and Prevention, 2013) or the Mini-Mental State Examination (MMSE; Folstein, Folstein, & McHugh, 1975). Further, the HTKS facilitates face-to-face social interaction, instead of administering items over the telephone like the Telephone Interview for Cognitive Status (TICS; Brandt, Spencer, & Folstein, 1988). In this way the HTKS provides a novel means of measuring multiple components of EF together that may augment existing paper and pencil, telephone, or computer-based screening measures, and perhaps provide unique predictive validity through its behavioral, game-like administration incorporating motoric engagement and face-to-face social interaction. Future research should compare the efficacy of the HTKS as a potential screening instrument to those already in the field (e.g., MMSE, Folstein, Folstein, & McHugh, 1975; TICS, Brandt, Spencer, Folstein, 1988). Potential Utility in Cognitive Interventions Applying the HTKS to cognitive interventions for older adult samples may be feasible and may inform the design of cognitive interventions that delay normative age-related declines in EF and cognitive function, in general. Interventions incorporating cognitively engaging activities, such as engagement models like volunteering to support elementary school children’s reading literacy (Carlson et al., 2008), learning digital photography and how to quilt (Park et al., 2014), as well as physical activity models like consistent aerobic exercise (e.g., Guiney & Machado, 2013), may have the greatest benefit for EF ability in late life. It is important to also recognize the value of training-based interventions. Training models are instrumental in preserving and improving certain task specific abilities, but lack transferability to other cognitive domains (e.g., see Simons et al., 2016 for a review of training-based cognitive interventions). Future work is needed to understand potential roles the HTKS may have in an intervention setting. In this study, 93% of the sample indicated interest in future studies that incorporated the HTKS, suggesting older adults may find it enjoyable to engage in the HTKS protocol, an important factor in constructing cognitive interventions that are engaging and maintain motivation to continue involvement in the intervention. Community hubs such as senior centers and fitness clubs may also benefit from HTKS use. Older adults concerned with their recent cognitive functioning may benefit from taking the HTKS at their local senior center or fitness club as a way of self-checking their cognitive health (in similar fashion to having one’s blood pressure taken periodically at a senior center). A freely available measure that is enjoyable for older adults and easy for researchers to administer offers a practical measure of EF that complements existing measures in the field. Limitations and Future Directions Several limitations of this study should be considered. While convergent validity correlation coefficients may seem relatively low, they were statistically significant and remained significant after adjusting for age, processing speed, and subjective health ratings. Further, low to moderate correlations are fairly common among measures of EF in adult samples (e.g., Hull et al., 2008; Miyake et al., 2000), suggesting our results are consistent with previous literature. The decision to only consider cognitively intact adults was intentional in this first study of the HTKS with older adults. However, lack of information about HTKS performance with individuals experiencing mild cognitive impairment or early dementia is a gap that needs to be addressed. Additionally, a convenience sample of community-dwelling older adults resulted in a sample of primarily Caucasian, female, physically and mentally healthy, and highly educated older adults. Future work should examine a more representative sample of older adults with a wide range of health conditions, ranging from chronic conditions that can be controlled (e.g., hypertension) to more severe conditions (e.g., advanced stages of Parkinson’s disease). Although seated administration is possible, a remaining limitation of the HTKS may hold for individuals who understand the directions but are physically unable to make the discernable motions (e.g., stroke survivors). Although the racial characteristics of our sample are similar to Oregon older adults (U.S. Census Bureau, 2015), a more diverse sample would be ideal. Although the sample size was not large, it is comparable to other studies (Hull et al., 2008; Mansbach, MacDougall, Clark, & Mace, 2014; Weintraub et al., 2014). Future studies should examine the predictive validity of the HTKS and explore its potential as a new cognitive screening instrument for those in community (e.g., senior center, fitness club), medical (e.g., doctor’s office), or institutionalized care settings (e.g., nursing home, memory care). More tools in the cognitive assessment arsenal are needed to promote cognitive health awareness among older adults and identify ways of optimizing EF. The HTKS is a novel instrument that is brief, low cost, easy to administer, engaging for older participants, and has the potential to bolster preventive screening efforts at the population level. Supplementary Data Supplementary data are available at The Gerontologist online. Funding This work was supported in part by the National Science Foundation (Grant DGE 0965820). Conflict of Interest None reported. Acknowledgment We would like to acknowledge Sandi Phibbs, PhD, for her insights and assistance in manuscript preparation and proofreading. 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The GerontologistOxford University Press

Published: Apr 10, 2018

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