Naturalistic Assessment using a Simulated Environment: Cognitive Correlates and Relationship to Functional Status in Individuals with Neurologic Conditions

Naturalistic Assessment using a Simulated Environment: Cognitive Correlates and Relationship to... Abstract Objective Research has shown that neurologic conditions, such as traumatic brain injury and multiple sclerosis, result in a number of cognitive and functional deficits. However, little is known about the relationship between various cognitive domains and ability to perform everyday activities. The Community Shopping Task (CST), a naturalistic assessment task conducted in a simulated environment, was used to examine functional abilities and cognitive correlates of everyday functioning in individuals with neurologic conditions. Method Thirty-four participants with neurologic conditions and 34 healthy controls completed the CST as well as traditional paper–pencil measures of cognition. In addition, all participants completed a questionnaire assessing instrumental activities of daily living (IADLs). Results The results indicated that participants with neurologic conditions required significantly more cues and time to complete the CST compared to control participants and that immediate memory and executive functioning were important predictors of CST performance. Furthermore, time to complete the CST accounted for a significant amount of variance in IADL performance, over and beyond the traditional measures of cognition. Conclusions These results provide evidence that a naturalistic task completed in an everyday environment can enhance our understanding of how daily functioning is impacted in individuals with neurologic conditions and subsequently inform rehabilitation strategies. Everyday functioning, Assessment, Head injury, Traumatic brain injury, Multiple sclerosis, Cerebrovascular disease/accident and stroke Introduction A report from the World Health Organization suggests that up to 1 billion people worldwide are affected by a neurologic condition (2006), such as traumatic brain injury (TBI), stroke, or multiple sclerosis (MS). Most of these conditions result in a number of cognitive deficits that impact the person’s everyday functioning. As a result, those with neurologic conditions often have poorer life satisfaction and perceived quality of life (Giebel, Sutcliffe, & Challis, 2015; McColl et al., 1999; Resch et al., 2009; Yeaman et al., 2013), higher rates of depression and psychological stress (Brown, Hasson, Thysellius, & Almborg, 2012; Couture, Lariviere, & Lafrancois, 2005), and their caregivers are at a higher risk for health problems (Semlyen, Summers, & Barnes, 1998). Understanding cognitive deficits and the subsequent functional problems that arise from these deficits can inform treatment and clinical decisions to improve the daily lives of those living with neurologic conditions. Everyday activities such as cooking, cleaning, and grocery shopping may seem like relatively simple and easy tasks; however, such tasks require a number of interacting cognitive processes and can be difficult for people with neurologic conditions. For example, grocery shopping requires individuals to scan and process a complex environment, remember what items have been selected and what items still need to be selected, make decisions concerning which type, size, and brand of item to choose, and filter out an enormous amount of extraneous information and environmental distractions. Currently, the relationship between cognitive correlates and everyday functioning remains unclear (Burgess, 1997; Burgess, Alderman, Evans, Emslie, & Wilson, 1998; Chaytor, Schmitter-Edgecombe, & Burr, 2006; Giebel, Challis, & Montaldi, 2014). Several reviews of the literature have found that cognitive predictors account for about 20–25% of total variance in functional status within a variety of patient populations (McAlister, Schmitter-Edgecombe & Lamb, 2016; Royall et al., 2007; Tucker-Drob, 2011) and it has been argued that current neuropsychological tests do not fully capture the breadth of cognitive and functional deficits in individual’s with neurologic insult (Donovan et al., 2011). As such, neuropsychologists have begun developing novel assessment techniques to increase understanding of how everyday functional ability is impacted by cognitive deficits (Marcotte, Scott, Kamat, & Heaton, 2010; Robertson & Schmitter-Edgcombe, 2016). Ecological validity, or the extent to which a task is able to generalize to a real-world setting, is an important topic for neuropsychological assessment. Because traditional paper–pencil assessment tasks tend to lack ecological validity (Chevignard, Soo, Galvin, Catroppa, & Eren, 2012), tasks that more closely resemble everyday activities have been developed. For example, the Naturalistic Action Test requires participants to make toast and coffee, gift-wrap a present, and pack a lunchbox and schoolbag in the laboratory setting (Schwartz, Buxbaum, Ferraro, Veramonti, & Segal, 2003). Some studies have found that, compared to traditional paper–pencil measures, lab-based naturalistic tasks are more sensitive to detecting cognitive deficits and predicting functional status in neurologic populations (Bruce, Ntlholang, Crosby, Cunningham, & Lawlor, 2016; Fortin, Godbout, & Braun, 2003). However, naturalistic tasks administered in lab-based settings often require imagination and abstract thinking to perform the task in an atypical environment, which limits generalizability to real-world environments (Simmons, 1988). To address this limitation, researchers have developed naturalistic tasks that can be performed in realistic environments (Alary Gauvreau, Kairy, Mazer, Guindon, & Le Dorze, 2017; Richardson, Law, Wishart, & Guyatt, 2000; Spooner & Pachana, 2006). As a result, some rehabilitation hospitals have incorporated naturalistic environments into their facilities to improve ecological validity of assessment and treatment. These naturalistic environments are often simulated modules, where facsimiles of grocery stores, restaurants, bus stations, cross walks, and recreational venues can help patients and evaluators make a direct connection to real-world activities. Simulated environments provide high face validity and an opportunity to assess functional status within a realistic environment and to better understand how particular cognitive deficits impact performance on real-world tasks (Hudson, 1995; Simmons, 1988). Moreover, individuals can rely on “automatic responses based on [their] own internal histories and contexts” when performing tasks in more realistic environments (McClusky, 2008; Simmons, 1988, p. 25). This is particularly important because research has shown that implicit processing remains relatively intact compared to more explicit processing abilities in a number of neurologic conditions (Amieva, Rouch-Leroyer, Fabrigoule, & Dartigues, 2000; Collette, Van, & Salmon, 2010; Ford et al., 1997; Glisky & Delaney, 1996; Scarrabelotti & Carroll, 1998; Schmitter-Edgecombe, 1996; Vakil, Biederman, Liran, Groswasser, & Aberbuch, 1994). As a result, if an individual with a neurologic condition is able to capitalize on implicit processing abilities when performing a task in a simulated environment, but continues to have difficulty completing the task, the examiner can better understand and/or anticipate problems that the person may have in the real world. Despite the adoption of simulated environments in rehabilitation settings, little literature evaluating the efficacy of simulated environments is available, and what does exist tends to focus on treatment and intervention, rather than assessment. For example, Hecox and colleagues (1994) retrospectively analyzed Functional Independence Measure (FIM) scores at discharge and found that patients who were admitted to the hospital after the simulated environment was installed had better FIM scores compared to patients who were treated at the hospital before the simulated environment was available. In contrast, a randomized controlled trial that compared use of a gym to use of a simulated environment for rehabilitation of neurologic patients did not find a significant difference between conditions either at discharge or at a 2-month follow-up (Richardson et al., 2000). Outside of the treatment literature, one study created an obstacle course that included components known to increase fall risk in older adults (e.g., different textures of flooring) within a simulated environment, which appeared useful in evaluating fall risk. However, further validation of this task, as well as other assessment tasks that can be used in simulated environments is necessary. Although studies examining simulated environments are few, conclusions drawn from studies evaluating naturalistic tasks conducted in other realistic environments, such as a kitchen, shopping center, or home environment, suggest potential benefits for using simulated environments in assessment. For example, research has demonstrated that performance on cooking (e.g., Rabideau Kitchen Evaluation—Revised), shopping (Multiple Errands Test [MET]) and other household tasks (e.g., Day Out Task [DOT]) in individuals with stroke, brain injury, mild cognitive impairment, and dementia was associated with performance on tasks of executive functioning, verbal memory, retrospective and prospective memory, simple auditory attention, visuospatial skills, and overall cognitive performance (Alderman et al., 2003; Alderman, & Burgess, 2002; Chevignard et al., 2008, 2009, 2010; Cuberos-Urbano et al., 2013; Dawson et al., 2009; Knight et al., 2002; Maeir et al., 2010; Schmitter-Edgecombe & Parsey, 2014b; Schmitter-Edgecombe et al., 2012; Yantz, Johnson-Greene, Higginson, & Emmerson, 2010). Furthermore, performance on shopping and household tasks was found to be predictive of everyday functioning (Alderman et al., 2003; Alderman, & Burgess, 2002; Cuberos-Urbano et al., 2013; Dawson et al., 2009; Knight et al., 2002; Maeir et al., 2010; Sanders & Schmitter-Edgecombe, 2012; Schmitter-Edgecombe & Parsey, 2014a; Schmitter-Edgecombe et al., 2012; Schmitter-Edgecombe & Parsey, 2014b). Therefore, it appears that naturalistic tasks conducted in realistic environments are associated with cognitive processes and can provide useful assessment information about everyday functioning. The purpose of this study was to examine functional status and the cognitive correlates of everyday functioning in individuals with neurologic conditions using a novel naturalistic task conducted in a simulated environment, called the “Community Shopping Task” (CST). Individuals with neurologic conditions (e.g., TBI, MS) and cognitively healthy adults completed the CST, which required them to make a grocery shopping list, go shopping in a simulated grocery store module, pay for the groceries, and board a bus. A hierarchical cueing system was employed if participants were unable to complete an aspect of the task. Correlates of cognitive status were obtained from standardized neurological assessments. Based on research that has evaluated naturalistic tasks in realistic environments, we hypothesized that participants with neurologic conditions would perform more poorly on the CST compared to healthy controls (Chevignard et al., 2008). In regard to the cognitive correlates, we hypothesized that memory and executive functioning would be correlated with the CST performance based on prior research regarding naturalistic tasks and cognition (Chevignard et al., 2010; Schmitter-Edgecombe et al., 2012). As a secondary goal, we assessed whether performance on the CST accounted for additional variance in functional status, as measured by self-report questionnaire, above and beyond what cognitive test performance predicted. Consistent with prior literature (Schmitter-Edgecombe & Parsey, 2014a), we hypothesized that the CST would contribute uniquely to the prediction of everyday functioning. Methods Participants Participants were 34 persons (21 female, 13 male) with a variety of neurologic conditions that can affect cognition. We choose to use a heterogeneous neurologic sample with a range of cognitive and functional impairments so that our study design would be less prone to the spectrum bias (i.e., including participants with too little variability in functional deficits) (Mower, 1999; Mulherin & Miller, 2002; Ransohoff & Feinstein, 1978; Reid, Lachs, & Feinstein, 1995; Sox, 1986; Whitling et al., 2004). About 9 participants had a closed head injury (time since injury: M = 62.71 months, range = 7–192 months), 6 participants had a stroke (time since stroke: M = 8 months, range = 6–10 months), 16 participants had multiple sclerosis (time since diagnosis: M = 224 months, range = 40–507 months), and 3 participants had a spinal cord injury (time since injury: M = 110 months, range = 27–254 months). All participants in the neurologic condition had self-reported ongoing cognitive and functional difficulties. Interview, testing, and collateral medical information were evaluated to substantiate the diagnosis of a neurologic condition. Participants were required to be at least 6 months post-injury or diagnosis. Exclusion criteria included a developmental disorder (e.g., autism), current or recent (within the past year) psychoactive substance abuse, diagnosis of dementia, and psychiatric causes of cognitive dysfunction (e.g., schizophrenia). Thirty-four cognitively healthy controls (24 female, 10 male) were also tested. Control participants were screened for diseases and disorders that may affect cognition during an in-person interview regarding developmental and medical history. Groups were well matched on age; t(66) = 0.05, p = 0.96, education; t(66) = −0.37, p = 0.71, and gender; x2(1, n = 68) = 0.59, p = 0.44 (see Table 1). Participants were recruited through advertisements, community support groups and wellness fairs, physician referrals, and other local agencies working with individuals with neurologic conditions. Table 1. Differences in demographic, cognitive, and Community Shopping Task (CST) variables between the different groups Control Group (n = 34) Neurologic Group (n = 34) TBI (n = 9) Stroke (n = 6) MS (n = 16) SCI (n = 3) M (SD) M (SD) M (SD) M (SD) M (SD) M (SD) Demographics  Age 50.82 51.02 39.22 47.67 57.19 60.33 (15.89) (14.69) (18.36)a (10.31) (9.39)a (14.01)  Education 14.35 14.15 13.44 14.83 14.50 13.00 (2.60) (1.92) (1.42) (2.86) (1.83) (1.00)  Gender 24F/10M 21F/13M 5F/4M 1F/5M 5F/11M 2F/1M General Ability  Estimated premorbid FSIQ 111.62 106.21 106.67 105.80 109.94 85.67 (9.04) (16.81) (15.20) (23.96) (14.63) (10.07) RBANS  Total Score 108.58 91.50** 92.13 85.60 92.94 92.00 (9.33) (17.56) (17.92) (28.24) (16.12) (2.65)  Immediate Memory 107.27 95.73** 94.22 100.60 95.81 91.67 (12.22) (17.12) (20.05) (23.56) (15.41) (9.87)  Visuospatial/Constructional skills 101.70 91.52* 87.33 83.40 92.44 112.67 (15.21) (21.69) (21.80) (26.79) (20.06) (15.95)  Language 108.55 95.03** 94.89 93.20 96.63 90.00 (11.51) (9.43) (13.61) (11.43) (6.46) (6.25)  Attention 106.52 89.59** 89.50 83.20 93.13 81.67 (12.16) (20.52) (24.22) (24.79) (19.72) (5.77)  Delayed Memory 105.82 95.61** 93.44 99.60 95.19 97.67 (8.12) (16.37) (15.80) (20.51) (17.47) (9.50) Executive Functioning  DKEFS Design Fluency 12.36 9.00** 11.00 (4.33)b 5.20 (2.39)b 8.94 (2.21) 9.67 (3.51) (2.51) (3.45) Control Group (n = 34) Neurologic Group (n = 34) TBI (n = 9) Stroke (n = 6) MS (n = 16) SCI (n = 3) M (SD) M (SD) M (SD) M (SD) M (SD) M (SD) Demographics  Age 50.82 51.02 39.22 47.67 57.19 60.33 (15.89) (14.69) (18.36)a (10.31) (9.39)a (14.01)  Education 14.35 14.15 13.44 14.83 14.50 13.00 (2.60) (1.92) (1.42) (2.86) (1.83) (1.00)  Gender 24F/10M 21F/13M 5F/4M 1F/5M 5F/11M 2F/1M General Ability  Estimated premorbid FSIQ 111.62 106.21 106.67 105.80 109.94 85.67 (9.04) (16.81) (15.20) (23.96) (14.63) (10.07) RBANS  Total Score 108.58 91.50** 92.13 85.60 92.94 92.00 (9.33) (17.56) (17.92) (28.24) (16.12) (2.65)  Immediate Memory 107.27 95.73** 94.22 100.60 95.81 91.67 (12.22) (17.12) (20.05) (23.56) (15.41) (9.87)  Visuospatial/Constructional skills 101.70 91.52* 87.33 83.40 92.44 112.67 (15.21) (21.69) (21.80) (26.79) (20.06) (15.95)  Language 108.55 95.03** 94.89 93.20 96.63 90.00 (11.51) (9.43) (13.61) (11.43) (6.46) (6.25)  Attention 106.52 89.59** 89.50 83.20 93.13 81.67 (12.16) (20.52) (24.22) (24.79) (19.72) (5.77)  Delayed Memory 105.82 95.61** 93.44 99.60 95.19 97.67 (8.12) (16.37) (15.80) (20.51) (17.47) (9.50) Executive Functioning  DKEFS Design Fluency 12.36 9.00** 11.00 (4.33)b 5.20 (2.39)b 8.94 (2.21) 9.67 (3.51) (2.51) (3.45) Note: *p < 0.05, **p < 0.01, ap < 0.01, bp < 0.05; FSIQ = Full Scale Intelligence Quotient (predicted by Wechsler Test of Adult Reading scores); RBANS = Repeatable Battery for the Assessment of Neuropsychological Status, DKEFS = Delis-Kaplan Executive Functioning System. Table 1. Differences in demographic, cognitive, and Community Shopping Task (CST) variables between the different groups Control Group (n = 34) Neurologic Group (n = 34) TBI (n = 9) Stroke (n = 6) MS (n = 16) SCI (n = 3) M (SD) M (SD) M (SD) M (SD) M (SD) M (SD) Demographics  Age 50.82 51.02 39.22 47.67 57.19 60.33 (15.89) (14.69) (18.36)a (10.31) (9.39)a (14.01)  Education 14.35 14.15 13.44 14.83 14.50 13.00 (2.60) (1.92) (1.42) (2.86) (1.83) (1.00)  Gender 24F/10M 21F/13M 5F/4M 1F/5M 5F/11M 2F/1M General Ability  Estimated premorbid FSIQ 111.62 106.21 106.67 105.80 109.94 85.67 (9.04) (16.81) (15.20) (23.96) (14.63) (10.07) RBANS  Total Score 108.58 91.50** 92.13 85.60 92.94 92.00 (9.33) (17.56) (17.92) (28.24) (16.12) (2.65)  Immediate Memory 107.27 95.73** 94.22 100.60 95.81 91.67 (12.22) (17.12) (20.05) (23.56) (15.41) (9.87)  Visuospatial/Constructional skills 101.70 91.52* 87.33 83.40 92.44 112.67 (15.21) (21.69) (21.80) (26.79) (20.06) (15.95)  Language 108.55 95.03** 94.89 93.20 96.63 90.00 (11.51) (9.43) (13.61) (11.43) (6.46) (6.25)  Attention 106.52 89.59** 89.50 83.20 93.13 81.67 (12.16) (20.52) (24.22) (24.79) (19.72) (5.77)  Delayed Memory 105.82 95.61** 93.44 99.60 95.19 97.67 (8.12) (16.37) (15.80) (20.51) (17.47) (9.50) Executive Functioning  DKEFS Design Fluency 12.36 9.00** 11.00 (4.33)b 5.20 (2.39)b 8.94 (2.21) 9.67 (3.51) (2.51) (3.45) Control Group (n = 34) Neurologic Group (n = 34) TBI (n = 9) Stroke (n = 6) MS (n = 16) SCI (n = 3) M (SD) M (SD) M (SD) M (SD) M (SD) M (SD) Demographics  Age 50.82 51.02 39.22 47.67 57.19 60.33 (15.89) (14.69) (18.36)a (10.31) (9.39)a (14.01)  Education 14.35 14.15 13.44 14.83 14.50 13.00 (2.60) (1.92) (1.42) (2.86) (1.83) (1.00)  Gender 24F/10M 21F/13M 5F/4M 1F/5M 5F/11M 2F/1M General Ability  Estimated premorbid FSIQ 111.62 106.21 106.67 105.80 109.94 85.67 (9.04) (16.81) (15.20) (23.96) (14.63) (10.07) RBANS  Total Score 108.58 91.50** 92.13 85.60 92.94 92.00 (9.33) (17.56) (17.92) (28.24) (16.12) (2.65)  Immediate Memory 107.27 95.73** 94.22 100.60 95.81 91.67 (12.22) (17.12) (20.05) (23.56) (15.41) (9.87)  Visuospatial/Constructional skills 101.70 91.52* 87.33 83.40 92.44 112.67 (15.21) (21.69) (21.80) (26.79) (20.06) (15.95)  Language 108.55 95.03** 94.89 93.20 96.63 90.00 (11.51) (9.43) (13.61) (11.43) (6.46) (6.25)  Attention 106.52 89.59** 89.50 83.20 93.13 81.67 (12.16) (20.52) (24.22) (24.79) (19.72) (5.77)  Delayed Memory 105.82 95.61** 93.44 99.60 95.19 97.67 (8.12) (16.37) (15.80) (20.51) (17.47) (9.50) Executive Functioning  DKEFS Design Fluency 12.36 9.00** 11.00 (4.33)b 5.20 (2.39)b 8.94 (2.21) 9.67 (3.51) (2.51) (3.45) Note: *p < 0.05, **p < 0.01, ap < 0.01, bp < 0.05; FSIQ = Full Scale Intelligence Quotient (predicted by Wechsler Test of Adult Reading scores); RBANS = Repeatable Battery for the Assessment of Neuropsychological Status, DKEFS = Delis-Kaplan Executive Functioning System. All participants completed a battery of standardized and experimental neuropsychological tests in a clinic-based setting, as well as the CST in a local rehabilitation hospital within a simulated environment. The testing session was approximately three hours. All participants were given a $30 honorarium in return for their time. Participants with a neurologic condition were also given a report documenting their performance on the neuropsychological tests. Measures The Community Shopping Task Participants completed the CST at a local rehabilitation hospital that has multiple simulated modules, including an office area (Fig. 1), grocery store façade (Fig. 2), and bus (Fig. 3). The task is broken into two subsections: recipe and grocery shopping. As seen in Table 2, the recipe, or preparation, section is comprised of 15 unique task steps and the grocery shopping, or execution, section is comprised of 23 unique task steps. Table 2. Task steps of the Community Shopping Task (CST) Recipe Section (Preparation) Begins task Looks up recipe Refers to list of items that they have at home Begins writing down items Writes down paprika Writes down pepper Writes down onions Writes down garlic Writes down 1 can whole tomatoes Writes down noodles Writes down items not needed Writes down chocolate dessert Writes down stamp book Indicates they are ready to move to shopping area Takes wallet and list with them Shopping Section (Execution) Begins task Chooses a shopping instrument Consults grocery list Begins to gather items on the grocery list Gets paprika Gets pepper Gets 3 onions Gets garlic Gets 1 can whole tomatoes Gets noodles Chooses a chocolate dessert Gets children’s ibuprofen Gets items not needed Brings items to cashier Sets items on counter Asks cashier for stamps Retrieves cash from wallet Counts out cash Pays cashier Picks up grocery bag and has wallet Moves towards the bus and leaves cart Uses stop light to cross street Gives the bus driver the bus pass Recipe Section (Preparation) Begins task Looks up recipe Refers to list of items that they have at home Begins writing down items Writes down paprika Writes down pepper Writes down onions Writes down garlic Writes down 1 can whole tomatoes Writes down noodles Writes down items not needed Writes down chocolate dessert Writes down stamp book Indicates they are ready to move to shopping area Takes wallet and list with them Shopping Section (Execution) Begins task Chooses a shopping instrument Consults grocery list Begins to gather items on the grocery list Gets paprika Gets pepper Gets 3 onions Gets garlic Gets 1 can whole tomatoes Gets noodles Chooses a chocolate dessert Gets children’s ibuprofen Gets items not needed Brings items to cashier Sets items on counter Asks cashier for stamps Retrieves cash from wallet Counts out cash Pays cashier Picks up grocery bag and has wallet Moves towards the bus and leaves cart Uses stop light to cross street Gives the bus driver the bus pass Table 2. Task steps of the Community Shopping Task (CST) Recipe Section (Preparation) Begins task Looks up recipe Refers to list of items that they have at home Begins writing down items Writes down paprika Writes down pepper Writes down onions Writes down garlic Writes down 1 can whole tomatoes Writes down noodles Writes down items not needed Writes down chocolate dessert Writes down stamp book Indicates they are ready to move to shopping area Takes wallet and list with them Shopping Section (Execution) Begins task Chooses a shopping instrument Consults grocery list Begins to gather items on the grocery list Gets paprika Gets pepper Gets 3 onions Gets garlic Gets 1 can whole tomatoes Gets noodles Chooses a chocolate dessert Gets children’s ibuprofen Gets items not needed Brings items to cashier Sets items on counter Asks cashier for stamps Retrieves cash from wallet Counts out cash Pays cashier Picks up grocery bag and has wallet Moves towards the bus and leaves cart Uses stop light to cross street Gives the bus driver the bus pass Recipe Section (Preparation) Begins task Looks up recipe Refers to list of items that they have at home Begins writing down items Writes down paprika Writes down pepper Writes down onions Writes down garlic Writes down 1 can whole tomatoes Writes down noodles Writes down items not needed Writes down chocolate dessert Writes down stamp book Indicates they are ready to move to shopping area Takes wallet and list with them Shopping Section (Execution) Begins task Chooses a shopping instrument Consults grocery list Begins to gather items on the grocery list Gets paprika Gets pepper Gets 3 onions Gets garlic Gets 1 can whole tomatoes Gets noodles Chooses a chocolate dessert Gets children’s ibuprofen Gets items not needed Brings items to cashier Sets items on counter Asks cashier for stamps Retrieves cash from wallet Counts out cash Pays cashier Picks up grocery bag and has wallet Moves towards the bus and leaves cart Uses stop light to cross street Gives the bus driver the bus pass Fig. 1. View largeDownload slide Simulated environment: Office area where participants were read Community Shopping Task (CST) instructions and completed the recipe/preparation subsection of the CST. Fig. 1. View largeDownload slide Simulated environment: Office area where participants were read Community Shopping Task (CST) instructions and completed the recipe/preparation subsection of the CST. Fig. 2. View largeDownload slide Simulated environment: The grocery store area where participants completed the shopping portion of the execution subsection of the CST. Fig. 2. View largeDownload slide Simulated environment: The grocery store area where participants completed the shopping portion of the execution subsection of the CST. Fig. 3. View largeDownload slide Simulated environment: The crosswalk and bus where participants completed the latter half of the execution subsection of the Community Shopping Task (CST). Fig. 3. View largeDownload slide Simulated environment: The crosswalk and bus where participants completed the latter half of the execution subsection of the Community Shopping Task (CST). Participants were told to imagine that they were planning to have friends over for dinner and would be making Hungarian Goulash, a recipe contained in a provided recipe book. They were given a list of items that they already had at home and were instructed to make a grocery list of recipe items that they would need to get at the store. In addition to the recipe items, they were told to buy a store-bought chocolate dessert and pick up stamps from the cashier when checking out so that they could mail an important bill. These instructions were read to participants in the office area of the simulated environment, which is also where they prepared their grocery store list. Participants were told that after they completed their shopping list, they were to go into the shopping area to collect the needed items from grocery store shelves. Once they finished shopping, they were to pay for their items and board a bus for the trip home. Participants were provided with a wallet with cash and a bus pass to use. Before beginning the shopping section of the task, participants were shown where the bus was located in the simulated environment, and were instructed to look at a crosswalk light just ahead of the bus before walking in front of the bus. An interruption was also implemented during the course of the shopping task. That is, after the participant collected three items in the grocery store, the examiner told the participant that they just received a call from a neighbor asking them to pick up children’s ibuprofen because the neighbor’s daughter was sick. While completing the CST, an examiner observed the participant’s performance and cued them if necessary. Participants were told that the examiner would not be assisting them with any part of the task unless they got stuck. In cases where the participant could not complete a task step, a hierarchical cueing system was employed as follows: indirect verbal guidance, gestural guidance, direct verbal guidance, physical assistance, and doing the task step for the participant. Each time a cue was given, the examiner recorded which task step had to be cued and the highest level of cue necessary for task step completion. The examiner also coded whether the participant either self-corrected a task step or had a slowed performance. Scoring of the Community Shopping Task Each unique task step was given a 0–6 rating, with a higher rating representing more assistance needed based on the hierarchical cueing system (see Table 3 for a description of the coding rubric). The score for each unique task step was summed to create a preparation score (total score of recipe subsection; range = 0–90), execution score (total score of the shopping subsection; range = 0–138), and CST total score (range = 0–228). The experimenter also recorded the total time it took participants to complete the CST. If a participant was unable to complete a task step due to physical limitations, it was coded separately and did not impact the cueing rubric. Table 3. Coding rubric for each unique task step Type of Cue Description 0: No assistance needed The participant completed the task correctly and in a timely manner without self-correcting. 1: Self-Corrected or Slowed Performance The participant required no help or reassurance but made mistakes that he/she self-corrected or proceeded at a slow rate with the task. 2: Indirect Verbal Guidance needed The participant was provided with verbal prompting, such as an open-ended question or an affirmation that helped them move on. Indirect verbal guidance generally comes in the form of a question, not a direct instruction, e.g., “Is that the correct/right item?” “What should you do now?”; “Do you have everything you need?”; “Is there something else you may want to do?”. Direct phrases are avoided. 3: Gestural Guidance needed The participant was provided with gestural prompting. The examiner provided a gesticulation that mimics the action that is necessary to complete the subtask, or made a movement that guides the participant, e.g., point to the wallet to remind the participant to take it with them or point to where the participant may find a grocery item, etc. Physical assistance, such as handing the participant an item, is avoided. 4: Direct Verbal Guidance needed The participant was provided a one-step command, so that they took action. For example, the examiner might say, “Write out a list of shopping items”; “Get the children’s Ibuprofen from the shelf”; Pick up the garlic; or “get a shopping bag”. 5: Physical Assistance needed The examiner physically assists the participant with the step, but does not do the task for the participant. For example, the examiner may put the participants hand on a needed grocery item. 6: Did the task for the participant The examiner completed the task for the participant. All other cues have been administered and the participant is still unable to complete the task. Type of Cue Description 0: No assistance needed The participant completed the task correctly and in a timely manner without self-correcting. 1: Self-Corrected or Slowed Performance The participant required no help or reassurance but made mistakes that he/she self-corrected or proceeded at a slow rate with the task. 2: Indirect Verbal Guidance needed The participant was provided with verbal prompting, such as an open-ended question or an affirmation that helped them move on. Indirect verbal guidance generally comes in the form of a question, not a direct instruction, e.g., “Is that the correct/right item?” “What should you do now?”; “Do you have everything you need?”; “Is there something else you may want to do?”. Direct phrases are avoided. 3: Gestural Guidance needed The participant was provided with gestural prompting. The examiner provided a gesticulation that mimics the action that is necessary to complete the subtask, or made a movement that guides the participant, e.g., point to the wallet to remind the participant to take it with them or point to where the participant may find a grocery item, etc. Physical assistance, such as handing the participant an item, is avoided. 4: Direct Verbal Guidance needed The participant was provided a one-step command, so that they took action. For example, the examiner might say, “Write out a list of shopping items”; “Get the children’s Ibuprofen from the shelf”; Pick up the garlic; or “get a shopping bag”. 5: Physical Assistance needed The examiner physically assists the participant with the step, but does not do the task for the participant. For example, the examiner may put the participants hand on a needed grocery item. 6: Did the task for the participant The examiner completed the task for the participant. All other cues have been administered and the participant is still unable to complete the task. Table 3. Coding rubric for each unique task step Type of Cue Description 0: No assistance needed The participant completed the task correctly and in a timely manner without self-correcting. 1: Self-Corrected or Slowed Performance The participant required no help or reassurance but made mistakes that he/she self-corrected or proceeded at a slow rate with the task. 2: Indirect Verbal Guidance needed The participant was provided with verbal prompting, such as an open-ended question or an affirmation that helped them move on. Indirect verbal guidance generally comes in the form of a question, not a direct instruction, e.g., “Is that the correct/right item?” “What should you do now?”; “Do you have everything you need?”; “Is there something else you may want to do?”. Direct phrases are avoided. 3: Gestural Guidance needed The participant was provided with gestural prompting. The examiner provided a gesticulation that mimics the action that is necessary to complete the subtask, or made a movement that guides the participant, e.g., point to the wallet to remind the participant to take it with them or point to where the participant may find a grocery item, etc. Physical assistance, such as handing the participant an item, is avoided. 4: Direct Verbal Guidance needed The participant was provided a one-step command, so that they took action. For example, the examiner might say, “Write out a list of shopping items”; “Get the children’s Ibuprofen from the shelf”; Pick up the garlic; or “get a shopping bag”. 5: Physical Assistance needed The examiner physically assists the participant with the step, but does not do the task for the participant. For example, the examiner may put the participants hand on a needed grocery item. 6: Did the task for the participant The examiner completed the task for the participant. All other cues have been administered and the participant is still unable to complete the task. Type of Cue Description 0: No assistance needed The participant completed the task correctly and in a timely manner without self-correcting. 1: Self-Corrected or Slowed Performance The participant required no help or reassurance but made mistakes that he/she self-corrected or proceeded at a slow rate with the task. 2: Indirect Verbal Guidance needed The participant was provided with verbal prompting, such as an open-ended question or an affirmation that helped them move on. Indirect verbal guidance generally comes in the form of a question, not a direct instruction, e.g., “Is that the correct/right item?” “What should you do now?”; “Do you have everything you need?”; “Is there something else you may want to do?”. Direct phrases are avoided. 3: Gestural Guidance needed The participant was provided with gestural prompting. The examiner provided a gesticulation that mimics the action that is necessary to complete the subtask, or made a movement that guides the participant, e.g., point to the wallet to remind the participant to take it with them or point to where the participant may find a grocery item, etc. Physical assistance, such as handing the participant an item, is avoided. 4: Direct Verbal Guidance needed The participant was provided a one-step command, so that they took action. For example, the examiner might say, “Write out a list of shopping items”; “Get the children’s Ibuprofen from the shelf”; Pick up the garlic; or “get a shopping bag”. 5: Physical Assistance needed The examiner physically assists the participant with the step, but does not do the task for the participant. For example, the examiner may put the participants hand on a needed grocery item. 6: Did the task for the participant The examiner completed the task for the participant. All other cues have been administered and the participant is still unable to complete the task. Cueing and scoring reliability The CST was first piloted with 12 individuals before the experiment began to ensure that the cueing hierarchy could account for a broad possibility of testing scenarios. Next, to substantiate that the cueing hierarchy was being applied appropriately and to evaluate scoring reliability, two examiners were present when 10 (29%) of the study participants were tested. One of the examiners administered the cues to the participant and coded for cue levels administered. The second examiner observed and coded for cue levels administered and additionally recorded whether they agreed or disagreed with the cues being administered by the primary examiner. Total discrepancies in cueing agreement were totaled and there was 99.74% agreement in cues administered by the primary examiner. Total discrepancies in cue coding scores were summed to determine inter-rater reliability and there was 100% agreement in scoring. Internal consistency reliability of the CST total score and CST execution score fell in the acceptable to good ranges (α = 0.82, and α = 0.79, respectively); and the CST preparation score fell within the questionable range (α = 0.64). Cognitive variables Cognitive variables included measures of overall cognition, immediate memory, visuospatial/constructional skills, language, attention, delayed memory, and executive functioning. The standard scores for each test were used in the analyses. “Repeatable Battery for Neuropsychological Status” (RBANS, Randolph, Tierney, Mohr, & Chase, 1998). The RBANS, form A, was administered, which consists of five indices. The total score was used in our analyses as a measure of overall cognitive functioning and each index was used to measure individual cognitive processes. The “Immediate Memory” index includes a list learning and story memory task. The “Visuospatial/Constructional” index is made up of a figure copy and line orientation task. A picture naming and semantic fluency task comprises the “Language” index. The “Attention” index includes a digit span and coding task. List recall, list recognition, story recall, and figure recall tasks make up the “Delayed Memory” index. “Delis-Kaplan Executive Function System (DKEFS) design fluency subtest” (Delis, Kaplan, & Kramer, 2001). The design fluency task was used as a measure of executive functioning given that the RBANS does not include an index of executive functioning, and executive functioning is known to be an important component to everyday performance. The task has three conditions: basic, filter, and switch. For all three conditions, participants were instructed to make as many unique designs as they could in 60 s using only four straight lines and always having each line touch at least one other line at a dot. In the basic condition, the squares contained an array of five filled dots and the participants were asked to draw the designs by connecting the filled dots. In the filter condition, the squares contained five empty dots and five filled dots and the participant was asked to draw designs by connecting only the empty dots. In the switch condition, the squares once again had five empty dots and five filled dots; however, this time the participant was asked to draw the designs by switching back and forth between connecting empty and filled dots. The overall standard score that combines performance on each of the three conditions was used. Everyday functioning The participants also completed the Instrumental Activities of Daily Living-Compensation questionnaire (IADL-C; Schmitter-Edgecombe, Parsey, & Lamb, 2014) prior to their evaluation. The questionnaire consists of 27 questions pertaining to IADLs (e.g., can use a telephone book, address book or other tool to look up unfamiliar numbers). The questionnaire addresses four IADL subdomains: money and self-management, home daily living, travel and event memory, and social skills. Participants answered each question using a Likert scale that ranges from “1” (independent, as well as ever, no aid) to “8” (not able to complete activity anymore). A category for indicating that the participant “does not need to complete the activity” was also included. The total mean score was used in the analyses. A subset of participants with neurologic conditions (n = 15) had knowledgeable informants complete the IADL-C. A correlation analysis between the IADL-C completed by the participants and their respective knowledgeable informants indicated that scores were consistent between the two groups; r = 0.95, p < 0.01. This finding indicates that self-awareness problems did not significantly impact the IADL-C ratings, which is consistent with prior research conducted with similar neurologic groups (Smith & Arnett, 2010; Vanderploeg, Belanger, Duchnick, & Curtiss, 2007). Results Data was analyzed using SPSS statistical software. First, differences between neurologic and control groups on demographic and cognitive variables were examined using independent samples t-tests. Neurologic subgroup data (i.e., TBI, SCI, stroke, and MS) is also presented for reference in Table 1. Independent samples t-tests were used to examine differences on CST performance between the neurologic and control groups. Receiver Operating Characteristic (ROC) curves were also calculated to determine the accuracy of the CST at differentiating between the neurologic and control groups. Neurologic subgroup data for the CST is also presented in Table 4. Correlations between the CST variables were obtained separately for the neurologic and control group to better understand how the CST variables are related to one another. Correlations were also obtained among the cognitive measures and the CST variables. Due to the high number of correlations being conducted, a more conservative p-value of 0.01 was used to indicate correlations that differed significantly from zero. Differences between groups in the amount of cueing administered for each CST task component was examined using Mann–Whitney U tests. A chi-square test of independence was also used to assess for differences in the level of cueing between groups for the CST task. Regression analyses were conducted to further understand the relationship between the CST variables and cognitive measures. Finally, regression analyses were used to evaluate whether CST performance accounted for a significant amount of variance in functional status when controlling for cognition. With the exception of Pearson correlation analyses, all analyses used a Type I error rate of p < 0.05 (All participants with SCI reported ongoing cognitive problems since their injury; however, given the lesser established connection between SCI and cognitive impairment, all analyses involving the neurologic group were also ran without the three participants with SCI. The pattern of data did not differ except where noted.). Table 4. Differences between groups on Community Shopping Task (CST) performance Neurologic Group (n = 34) Control Group (n = 34) Cohen’s d TBI (n = 9) Stroke (n = 6) MS (n = 16) SCI (n = 3) M (SD) M (SD) M (SD) M (SD) M (SD) M (SD) CST Total Score 15.15 5.23 1.03* 14.00 22.00 12.00 21.67 (12.95) (4.29) (14.86) (17.84) (8.52) (16.01) CST Preparation 6.82 2.97 0.84* 7.44 10.50 5.56 4.33 (5.73) (3.00) (7.80) (6.09) (4.34) (0.58) CST Execution 8.32 2.26 0.88* 6.56 11.50 6.44 17.33 (9.30) (2.73) (7.73) (13.97) (5.74) (16.04) CST Total Time (s) 942.06 591.18 1.33* 1037.78 900.00 907.50 923.33 (331.29) (171.71) (327.02) (377.57) (349.77) (229.42) Neurologic Group (n = 34) Control Group (n = 34) Cohen’s d TBI (n = 9) Stroke (n = 6) MS (n = 16) SCI (n = 3) M (SD) M (SD) M (SD) M (SD) M (SD) M (SD) CST Total Score 15.15 5.23 1.03* 14.00 22.00 12.00 21.67 (12.95) (4.29) (14.86) (17.84) (8.52) (16.01) CST Preparation 6.82 2.97 0.84* 7.44 10.50 5.56 4.33 (5.73) (3.00) (7.80) (6.09) (4.34) (0.58) CST Execution 8.32 2.26 0.88* 6.56 11.50 6.44 17.33 (9.30) (2.73) (7.73) (13.97) (5.74) (16.04) CST Total Time (s) 942.06 591.18 1.33* 1037.78 900.00 907.50 923.33 (331.29) (171.71) (327.02) (377.57) (349.77) (229.42) Note: *p < 0.01. Table 4. Differences between groups on Community Shopping Task (CST) performance Neurologic Group (n = 34) Control Group (n = 34) Cohen’s d TBI (n = 9) Stroke (n = 6) MS (n = 16) SCI (n = 3) M (SD) M (SD) M (SD) M (SD) M (SD) M (SD) CST Total Score 15.15 5.23 1.03* 14.00 22.00 12.00 21.67 (12.95) (4.29) (14.86) (17.84) (8.52) (16.01) CST Preparation 6.82 2.97 0.84* 7.44 10.50 5.56 4.33 (5.73) (3.00) (7.80) (6.09) (4.34) (0.58) CST Execution 8.32 2.26 0.88* 6.56 11.50 6.44 17.33 (9.30) (2.73) (7.73) (13.97) (5.74) (16.04) CST Total Time (s) 942.06 591.18 1.33* 1037.78 900.00 907.50 923.33 (331.29) (171.71) (327.02) (377.57) (349.77) (229.42) Neurologic Group (n = 34) Control Group (n = 34) Cohen’s d TBI (n = 9) Stroke (n = 6) MS (n = 16) SCI (n = 3) M (SD) M (SD) M (SD) M (SD) M (SD) M (SD) CST Total Score 15.15 5.23 1.03* 14.00 22.00 12.00 21.67 (12.95) (4.29) (14.86) (17.84) (8.52) (16.01) CST Preparation 6.82 2.97 0.84* 7.44 10.50 5.56 4.33 (5.73) (3.00) (7.80) (6.09) (4.34) (0.58) CST Execution 8.32 2.26 0.88* 6.56 11.50 6.44 17.33 (9.30) (2.73) (7.73) (13.97) (5.74) (16.04) CST Total Time (s) 942.06 591.18 1.33* 1037.78 900.00 907.50 923.33 (331.29) (171.71) (327.02) (377.57) (349.77) (229.42) Note: *p < 0.01. Because the CST is not a standardized measure, correlational analyses were used to examine whether age, gender, or education was associated with performance on the CST for either the neurologic or control group. Results revealed that demographic variables were not significantly related to CST performance (i.e., CST total score, preparation score, execution score, and CST total time; rs < 0.32) for either group; therefore, no demographic variables were controlled for in the analyses. Between and Within Group Performance As can be seen in Table 1, despite being well matched on demographic characteristics (i.e., age, education, gender, premorbid ability) the neurologic group performed significantly more poorly than the control group on all measures of cognition, ts > 2.21, ps < 0.03, Cohen’s d range = 0.54–1.28. Table 1 also presents demographic and cognitive performance data for participants as a function of neurologic condition. With few exceptions the cognitive scores across neurologic subgroups fell within one standard deviation of each other. CST Performance Independent samples t-tests were then used to analyze group differences on the CST (Table 4). Results revealed that participants with neurologic conditions required significantly more cues compared to the control group to complete the CST; t(66) = 4.23, p < 0.01, d = 1.03, and this was true for both the CST preparation t(66) = 3.47, p < 0.01, d = 0.84, and CST execution subsections; t(66) = 3.65, p < 0.01, d = 0.88. Participants with neurologic conditions also took significantly longer to complete the CST compared to the control group; t(66) = 5.48, p < 0.01, d = 1.33. Furthermore, there appeared to be just as much variability within each neurologic condition as across the neurologic conditions on all of the CST variables (Table 4), with the exception that participant’s with SCI (n = 3) appeared to need less assistance on the CST preparation subsection compared to the CST execution subsection. To determine whether the CST could accurately differentiate between the control and neurologic groups, ROC curve analyses were conducted (Tape, n.d.). Results revealed a significant area under the curve for CST total score; 0.81, p < 0.01 (76.5% sensitivity and 76.5% specificity), CST preparation; 0.73, p < 0.01 (59.8% sensitivity and 79.4% specificity), CST execution; 0.75, p < 0.01 (61.8% sensitivity and 76.5% specificity), and CST total time; 0.84 (70.6% sensitivity and 82.4% specificity). The ability to differentiate between groups using the CST total score and CST total time fell in the good range, while using the CST preparation and CST execution scores fell in the fair range. Of note, follow-up exploratory analyses revealed that the cognitive measures were unable to discriminate between groups (ROC curve <0.36), with sensitivity ranging from 18% to 40% and specificity ranging from 34% to 62%. Tables 5 and 6 show the maximum level of cues given to participants in both the neurologic and control groups for each task component of the preparation and execution subsections of the CST. Exploratory Mann–Whitney U tests (no adjustment was made to alpha level) were used to evaluate for significant differences between groups in the total amount of cues given for each individual task component. In general, the neurologic and control groups often needed cueing on similar task components. However, participants with neurologic conditions needed significantly more cues compared to the control group on the following task components of the CST preparation subsection: begins task, looks up the recipe, refers to the list of items at home, begins writing down items, and takes wallet with them. For the CST execution subsection, participants with neurologic conditions needed significantly more cues compared to the control group for the following task components: chooses a shopping instrument, gets noodles, chooses chocolate dessert, sets grocery items on the counter, gets grocery bag and has wallet, uses stop light to cross the street, and gives the bus driver the bus pass. Table 5. Maximum level of cues given for each preparation task component to the neurologic and control participants Cue Level Neurologic Group (n = 34) T Control Group (n = 34) T 1 2 3 4 5 6 1 2 3 4 5 6 Task Components  Begins task* 1 3 0 1 0 0 5 0 0 0 0 0 0 0  Looks up recipe** 6 2 4 1 1 0 14 1 1 1 0 0 0 3  Refers to list of items they have at home* 0 1 2 1 0 0 4 0 0 0 0 0 0 0  Begins writing down items* 2 1 0 2 0 0 5 0 0 0 0 0 0 0  Writes down paprika 0 2 0 0 0 0 2 0 0 2 0 0 0 2  Writes down pepper 1 0 0 0 0 0 1 0 0 0 0 0 0 0  Writes down onions 0 5 3 2 0 0 10 0 2 3 1 0 0 6  Writes down garlic 1 4 0 0 0 0 5 0 1 0 0 0 0 1  Writes down 1 can whole tomatoes 1 2 0 0 0 0 3 0 0 0 0 0 0 0  Writes down noodles 2 0 0 1 0 0 3 0 0 0 0 0 0 0  Writes down items not needed 0 7 3 1 0 0 11 0 10 1 0 0 0 11  Writes down dessert 0 11 1 5 0 0 17 1 12 0 1 0 0 14  Writes down stamp book 0 11 1 2 0 0 14 0 7 0 1 0 0 8  Indicates they are ready to shop 0 0 0 0 0 0 0 0 0 0 0 0 0 0  Takes wallet and list with them* 0 3 1 0 0 0 4 0 0 0 0 0 0 0 Totals 14 52 15 16 1 0 98 2 33 7 3 0 0 45 Cue Level Neurologic Group (n = 34) T Control Group (n = 34) T 1 2 3 4 5 6 1 2 3 4 5 6 Task Components  Begins task* 1 3 0 1 0 0 5 0 0 0 0 0 0 0  Looks up recipe** 6 2 4 1 1 0 14 1 1 1 0 0 0 3  Refers to list of items they have at home* 0 1 2 1 0 0 4 0 0 0 0 0 0 0  Begins writing down items* 2 1 0 2 0 0 5 0 0 0 0 0 0 0  Writes down paprika 0 2 0 0 0 0 2 0 0 2 0 0 0 2  Writes down pepper 1 0 0 0 0 0 1 0 0 0 0 0 0 0  Writes down onions 0 5 3 2 0 0 10 0 2 3 1 0 0 6  Writes down garlic 1 4 0 0 0 0 5 0 1 0 0 0 0 1  Writes down 1 can whole tomatoes 1 2 0 0 0 0 3 0 0 0 0 0 0 0  Writes down noodles 2 0 0 1 0 0 3 0 0 0 0 0 0 0  Writes down items not needed 0 7 3 1 0 0 11 0 10 1 0 0 0 11  Writes down dessert 0 11 1 5 0 0 17 1 12 0 1 0 0 14  Writes down stamp book 0 11 1 2 0 0 14 0 7 0 1 0 0 8  Indicates they are ready to shop 0 0 0 0 0 0 0 0 0 0 0 0 0 0  Takes wallet and list with them* 0 3 1 0 0 0 4 0 0 0 0 0 0 0 Totals 14 52 15 16 1 0 98 2 33 7 3 0 0 45 Note: Cue levels: 1 = Self-Corrected or Slowed Performance, 2 = Indirect Verbal Guidance, 3 = Gestural Guidance, 4 = Direct Verbal Guidance, 5 = Physical Assistance, 6 = Did the task for the participant, T = total. *p < 0.05 difference between groups on total cues of individual task components. **p < 0.01 difference between groups on total cues of individual task components. Table 5. Maximum level of cues given for each preparation task component to the neurologic and control participants Cue Level Neurologic Group (n = 34) T Control Group (n = 34) T 1 2 3 4 5 6 1 2 3 4 5 6 Task Components  Begins task* 1 3 0 1 0 0 5 0 0 0 0 0 0 0  Looks up recipe** 6 2 4 1 1 0 14 1 1 1 0 0 0 3  Refers to list of items they have at home* 0 1 2 1 0 0 4 0 0 0 0 0 0 0  Begins writing down items* 2 1 0 2 0 0 5 0 0 0 0 0 0 0  Writes down paprika 0 2 0 0 0 0 2 0 0 2 0 0 0 2  Writes down pepper 1 0 0 0 0 0 1 0 0 0 0 0 0 0  Writes down onions 0 5 3 2 0 0 10 0 2 3 1 0 0 6  Writes down garlic 1 4 0 0 0 0 5 0 1 0 0 0 0 1  Writes down 1 can whole tomatoes 1 2 0 0 0 0 3 0 0 0 0 0 0 0  Writes down noodles 2 0 0 1 0 0 3 0 0 0 0 0 0 0  Writes down items not needed 0 7 3 1 0 0 11 0 10 1 0 0 0 11  Writes down dessert 0 11 1 5 0 0 17 1 12 0 1 0 0 14  Writes down stamp book 0 11 1 2 0 0 14 0 7 0 1 0 0 8  Indicates they are ready to shop 0 0 0 0 0 0 0 0 0 0 0 0 0 0  Takes wallet and list with them* 0 3 1 0 0 0 4 0 0 0 0 0 0 0 Totals 14 52 15 16 1 0 98 2 33 7 3 0 0 45 Cue Level Neurologic Group (n = 34) T Control Group (n = 34) T 1 2 3 4 5 6 1 2 3 4 5 6 Task Components  Begins task* 1 3 0 1 0 0 5 0 0 0 0 0 0 0  Looks up recipe** 6 2 4 1 1 0 14 1 1 1 0 0 0 3  Refers to list of items they have at home* 0 1 2 1 0 0 4 0 0 0 0 0 0 0  Begins writing down items* 2 1 0 2 0 0 5 0 0 0 0 0 0 0  Writes down paprika 0 2 0 0 0 0 2 0 0 2 0 0 0 2  Writes down pepper 1 0 0 0 0 0 1 0 0 0 0 0 0 0  Writes down onions 0 5 3 2 0 0 10 0 2 3 1 0 0 6  Writes down garlic 1 4 0 0 0 0 5 0 1 0 0 0 0 1  Writes down 1 can whole tomatoes 1 2 0 0 0 0 3 0 0 0 0 0 0 0  Writes down noodles 2 0 0 1 0 0 3 0 0 0 0 0 0 0  Writes down items not needed 0 7 3 1 0 0 11 0 10 1 0 0 0 11  Writes down dessert 0 11 1 5 0 0 17 1 12 0 1 0 0 14  Writes down stamp book 0 11 1 2 0 0 14 0 7 0 1 0 0 8  Indicates they are ready to shop 0 0 0 0 0 0 0 0 0 0 0 0 0 0  Takes wallet and list with them* 0 3 1 0 0 0 4 0 0 0 0 0 0 0 Totals 14 52 15 16 1 0 98 2 33 7 3 0 0 45 Note: Cue levels: 1 = Self-Corrected or Slowed Performance, 2 = Indirect Verbal Guidance, 3 = Gestural Guidance, 4 = Direct Verbal Guidance, 5 = Physical Assistance, 6 = Did the task for the participant, T = total. *p < 0.05 difference between groups on total cues of individual task components. **p < 0.01 difference between groups on total cues of individual task components. Table 6. Maximum level of cues given for each execution task component to the neurologic and control participants Cue Level Neurologic Group (n = 34) T Control Group (n = 34) T 1 2 3 4 5 6 1 2 3 4 5 6 Task Components  Begins task 0 1 1 1 0 0 3 0 0 0 0 0 0 0  Chooses a shopping instrument* 0 1 0 2 0 1 4 0 0 0 0 0 0 0  Consults grocery list 0 0 1 1 0 0 2 0 0 0 0 0 0 0  Begins to gather items on the grocery list 1 1 0 0 0 0 2 1 0 0 0 0 0 1  Gets paprika 0 2 0 0 0 0 2 0 1 0 0 0 0 1  Gets pepper 0 0 3 0 0 0 3 0 2 0 0 0 0 2  Gets 3 onions 0 2 0 0 0 0 2 0 1 0 0 0 0 1  Gets garlic 0 2 0 0 0 0 2 0 2 0 0 0 0 2  Gets 1 can whole tomatoes 0 1 0 0 0 0 1 0 1 0 0 0 0 1  Gets noodles* 5 0 0 2 0 0 7 1 0 0 0 0 0 1  Chooses a chocolate dessert* 3 5 2 1 0 1 12 2 0 1 1 0 0 4  Gets children’s ibuprofen 5 3 7 2 0 0 17 4 5 3 0 0 0 12  Gets items not needed 0 1 0 1 0 0 2 0 2 1 0 0 0 3  Brings items to cashier 0 1 0 0 0 0 1 0 0 0 0 0 0 0  Sets items on counter* 1 2 0 3 0 2 8 0 1 0 0 0 0 1  Asks cashier for stamps 0 1 1 2 0 0 4 0 2 0 0 0 0 2  Retrieves cash from wallet 1 1 0 0 0 0 2 0 1 0 0 0 0 1  Counts out cash 0 2 0 0 1 0 3 0 0 0 1 0 0 1  Pays cashier 1 1 0 0 0 0 2 0 0 0 0 0 0 0  Picks up grocery bag and has wallet* 0 1 2 0 0 1 4 0 0 0 0 0 0 0  Moves towards the bus and leaves cart 0 1 1 1 0 0 3 0 0 0 0 0 0 0  Uses a stop light to cross street** 2 5 1 0 0 0 8 0 0 0 0 0 0 0  Gives the bus driver the bus pass** 0 11 3 2 0 0 16 0 5 0 0 0 0 5 Totals 19 45 22 18 1 4 109 8 23 5 2 0 0 38 Cue Level Neurologic Group (n = 34) T Control Group (n = 34) T 1 2 3 4 5 6 1 2 3 4 5 6 Task Components  Begins task 0 1 1 1 0 0 3 0 0 0 0 0 0 0  Chooses a shopping instrument* 0 1 0 2 0 1 4 0 0 0 0 0 0 0  Consults grocery list 0 0 1 1 0 0 2 0 0 0 0 0 0 0  Begins to gather items on the grocery list 1 1 0 0 0 0 2 1 0 0 0 0 0 1  Gets paprika 0 2 0 0 0 0 2 0 1 0 0 0 0 1  Gets pepper 0 0 3 0 0 0 3 0 2 0 0 0 0 2  Gets 3 onions 0 2 0 0 0 0 2 0 1 0 0 0 0 1  Gets garlic 0 2 0 0 0 0 2 0 2 0 0 0 0 2  Gets 1 can whole tomatoes 0 1 0 0 0 0 1 0 1 0 0 0 0 1  Gets noodles* 5 0 0 2 0 0 7 1 0 0 0 0 0 1  Chooses a chocolate dessert* 3 5 2 1 0 1 12 2 0 1 1 0 0 4  Gets children’s ibuprofen 5 3 7 2 0 0 17 4 5 3 0 0 0 12  Gets items not needed 0 1 0 1 0 0 2 0 2 1 0 0 0 3  Brings items to cashier 0 1 0 0 0 0 1 0 0 0 0 0 0 0  Sets items on counter* 1 2 0 3 0 2 8 0 1 0 0 0 0 1  Asks cashier for stamps 0 1 1 2 0 0 4 0 2 0 0 0 0 2  Retrieves cash from wallet 1 1 0 0 0 0 2 0 1 0 0 0 0 1  Counts out cash 0 2 0 0 1 0 3 0 0 0 1 0 0 1  Pays cashier 1 1 0 0 0 0 2 0 0 0 0 0 0 0  Picks up grocery bag and has wallet* 0 1 2 0 0 1 4 0 0 0 0 0 0 0  Moves towards the bus and leaves cart 0 1 1 1 0 0 3 0 0 0 0 0 0 0  Uses a stop light to cross street** 2 5 1 0 0 0 8 0 0 0 0 0 0 0  Gives the bus driver the bus pass** 0 11 3 2 0 0 16 0 5 0 0 0 0 5 Totals 19 45 22 18 1 4 109 8 23 5 2 0 0 38 Note: Cue levels: 1 = Self-Corrected or Slowed Performance, 2 = Indirect Verbal Guidance, 3 = Gestural Guidance, 4 = Direct Verbal Guidance, 5 = Physical Assistance, 6 = Did the task for the participant, T = Total. *p < 0.05 difference between groups on total cues of individual task components. **p < 0.01 difference between groups on total cues of individual task components. Table 6. Maximum level of cues given for each execution task component to the neurologic and control participants Cue Level Neurologic Group (n = 34) T Control Group (n = 34) T 1 2 3 4 5 6 1 2 3 4 5 6 Task Components  Begins task 0 1 1 1 0 0 3 0 0 0 0 0 0 0  Chooses a shopping instrument* 0 1 0 2 0 1 4 0 0 0 0 0 0 0  Consults grocery list 0 0 1 1 0 0 2 0 0 0 0 0 0 0  Begins to gather items on the grocery list 1 1 0 0 0 0 2 1 0 0 0 0 0 1  Gets paprika 0 2 0 0 0 0 2 0 1 0 0 0 0 1  Gets pepper 0 0 3 0 0 0 3 0 2 0 0 0 0 2  Gets 3 onions 0 2 0 0 0 0 2 0 1 0 0 0 0 1  Gets garlic 0 2 0 0 0 0 2 0 2 0 0 0 0 2  Gets 1 can whole tomatoes 0 1 0 0 0 0 1 0 1 0 0 0 0 1  Gets noodles* 5 0 0 2 0 0 7 1 0 0 0 0 0 1  Chooses a chocolate dessert* 3 5 2 1 0 1 12 2 0 1 1 0 0 4  Gets children’s ibuprofen 5 3 7 2 0 0 17 4 5 3 0 0 0 12  Gets items not needed 0 1 0 1 0 0 2 0 2 1 0 0 0 3  Brings items to cashier 0 1 0 0 0 0 1 0 0 0 0 0 0 0  Sets items on counter* 1 2 0 3 0 2 8 0 1 0 0 0 0 1  Asks cashier for stamps 0 1 1 2 0 0 4 0 2 0 0 0 0 2  Retrieves cash from wallet 1 1 0 0 0 0 2 0 1 0 0 0 0 1  Counts out cash 0 2 0 0 1 0 3 0 0 0 1 0 0 1  Pays cashier 1 1 0 0 0 0 2 0 0 0 0 0 0 0  Picks up grocery bag and has wallet* 0 1 2 0 0 1 4 0 0 0 0 0 0 0  Moves towards the bus and leaves cart 0 1 1 1 0 0 3 0 0 0 0 0 0 0  Uses a stop light to cross street** 2 5 1 0 0 0 8 0 0 0 0 0 0 0  Gives the bus driver the bus pass** 0 11 3 2 0 0 16 0 5 0 0 0 0 5 Totals 19 45 22 18 1 4 109 8 23 5 2 0 0 38 Cue Level Neurologic Group (n = 34) T Control Group (n = 34) T 1 2 3 4 5 6 1 2 3 4 5 6 Task Components  Begins task 0 1 1 1 0 0 3 0 0 0 0 0 0 0  Chooses a shopping instrument* 0 1 0 2 0 1 4 0 0 0 0 0 0 0  Consults grocery list 0 0 1 1 0 0 2 0 0 0 0 0 0 0  Begins to gather items on the grocery list 1 1 0 0 0 0 2 1 0 0 0 0 0 1  Gets paprika 0 2 0 0 0 0 2 0 1 0 0 0 0 1  Gets pepper 0 0 3 0 0 0 3 0 2 0 0 0 0 2  Gets 3 onions 0 2 0 0 0 0 2 0 1 0 0 0 0 1  Gets garlic 0 2 0 0 0 0 2 0 2 0 0 0 0 2  Gets 1 can whole tomatoes 0 1 0 0 0 0 1 0 1 0 0 0 0 1  Gets noodles* 5 0 0 2 0 0 7 1 0 0 0 0 0 1  Chooses a chocolate dessert* 3 5 2 1 0 1 12 2 0 1 1 0 0 4  Gets children’s ibuprofen 5 3 7 2 0 0 17 4 5 3 0 0 0 12  Gets items not needed 0 1 0 1 0 0 2 0 2 1 0 0 0 3  Brings items to cashier 0 1 0 0 0 0 1 0 0 0 0 0 0 0  Sets items on counter* 1 2 0 3 0 2 8 0 1 0 0 0 0 1  Asks cashier for stamps 0 1 1 2 0 0 4 0 2 0 0 0 0 2  Retrieves cash from wallet 1 1 0 0 0 0 2 0 1 0 0 0 0 1  Counts out cash 0 2 0 0 1 0 3 0 0 0 1 0 0 1  Pays cashier 1 1 0 0 0 0 2 0 0 0 0 0 0 0  Picks up grocery bag and has wallet* 0 1 2 0 0 1 4 0 0 0 0 0 0 0  Moves towards the bus and leaves cart 0 1 1 1 0 0 3 0 0 0 0 0 0 0  Uses a stop light to cross street** 2 5 1 0 0 0 8 0 0 0 0 0 0 0  Gives the bus driver the bus pass** 0 11 3 2 0 0 16 0 5 0 0 0 0 5 Totals 19 45 22 18 1 4 109 8 23 5 2 0 0 38 Note: Cue levels: 1 = Self-Corrected or Slowed Performance, 2 = Indirect Verbal Guidance, 3 = Gestural Guidance, 4 = Direct Verbal Guidance, 5 = Physical Assistance, 6 = Did the task for the participant, T = Total. *p < 0.05 difference between groups on total cues of individual task components. **p < 0.01 difference between groups on total cues of individual task components. A chi-square test of independence also revealed that participants with neurologic conditions required greater levels of cueing to accurately complete the CST compared to the control group, χ2 (5, N = 68) = 12.96, p = .024 (Table 7). To evaluate individual cell contributions to the chi-square results, the adjusted residuals method was employed (MacDonald & Gardner, 2000; Sharpe, 2015). A Bonferroni correction was used to maintain an appropriate Type I error rate (MacDonald & Gardner, 2000). There are 12 cells in the 2 × 6 contingency table; therefore, the alpha was set at approximately 0.004 (0.05/12), which corresponds to a critical value of ±2.8. The findings indicated that the neurologic group received a lower proportion of indirect cues (46.85%) compared to the control participants (67.47%; adjusted residual = 3.18). The difference between the proportions of direct cues given to each group approached significance (adjusted residual = 2.35) with participants in the neurologic group needing more direct cues (16.43%) compared to participants in the control group (6.02%). Furthermore, only participants in the neurologic group required physical assistance or needed to have the task component completed for them. Table 7. Percentage of cue level given out of total cues administered by group Self-Corrected/ Slow Indirect Verbal Guidance Gestural Guidance Direct Verbal Guidance Physical Assistance Did the task for the Participant Neurologic Group (n = 34) 15.94% 46.86% 17.87% 16.43% 2.42% 1.93% Control Group (n = 34) 12.05% 67.47% 14.46% 6.02% 0% 0% Self-Corrected/ Slow Indirect Verbal Guidance Gestural Guidance Direct Verbal Guidance Physical Assistance Did the task for the Participant Neurologic Group (n = 34) 15.94% 46.86% 17.87% 16.43% 2.42% 1.93% Control Group (n = 34) 12.05% 67.47% 14.46% 6.02% 0% 0% Table 7. Percentage of cue level given out of total cues administered by group Self-Corrected/ Slow Indirect Verbal Guidance Gestural Guidance Direct Verbal Guidance Physical Assistance Did the task for the Participant Neurologic Group (n = 34) 15.94% 46.86% 17.87% 16.43% 2.42% 1.93% Control Group (n = 34) 12.05% 67.47% 14.46% 6.02% 0% 0% Self-Corrected/ Slow Indirect Verbal Guidance Gestural Guidance Direct Verbal Guidance Physical Assistance Did the task for the Participant Neurologic Group (n = 34) 15.94% 46.86% 17.87% 16.43% 2.42% 1.93% Control Group (n = 34) 12.05% 67.47% 14.46% 6.02% 0% 0% Cognition and the CST For the control group, the CST total score was significantly correlated with the CST preparation score; r = 0.77, p < 0.01, and the CST execution score; r = 0.72, p < 0.01. The CST execution and CST preparation scores were not significantly correlated with one another (r = 0.12, p = 0.52), indicating that they may be assessing different aspects of performance. CST total time was not significantly correlated with any of the other CST variables for the control group. For the neurologic group, all CST variables were significantly correlated with one another (rs > 0.39). Correlations between the CST variables and predictor variables are presented in Table 8. Table 8. Correlations between cognitive variables and Community Shopping Task (CST) variablesa Neurologic Group (n = 34) Control Group (n = 34) Total CST Prep Score Exec Score CST Time Total CST Prep Score Exec Score CST Time RBANS Total Score −0.64* −0.56* −0.56* −0.53* −0.44* −0.23 −0.43* −0.18 Immediate Memory −0.71* −0.60* −0.62* −0.50* −0.12 −0.06 −0.12 −0.03 Visuospatial/Constructional skills −0.033 −0.37 −0.24 −0.29 −0.35 −0.18 −0.35 −0.06 Language −0.61* −0.47* −0.56* −0.49* −0.20 −0.07 −0.23 −0.38 Attention −0.61* −0.50* −0.55* −0.60* −0.32 −0.24 −0.25 −0.15 Delayed Memory −0.33 −0.29 −0.33 −0.29 −0.07 0.03 −0.14 0.11 DKEFS Design Fluency −0.44* −0.26 −0.46* −0.26 −0.03 0.09 −0.15 −0.21 Neurologic Group (n = 34) Control Group (n = 34) Total CST Prep Score Exec Score CST Time Total CST Prep Score Exec Score CST Time RBANS Total Score −0.64* −0.56* −0.56* −0.53* −0.44* −0.23 −0.43* −0.18 Immediate Memory −0.71* −0.60* −0.62* −0.50* −0.12 −0.06 −0.12 −0.03 Visuospatial/Constructional skills −0.033 −0.37 −0.24 −0.29 −0.35 −0.18 −0.35 −0.06 Language −0.61* −0.47* −0.56* −0.49* −0.20 −0.07 −0.23 −0.38 Attention −0.61* −0.50* −0.55* −0.60* −0.32 −0.24 −0.25 −0.15 Delayed Memory −0.33 −0.29 −0.33 −0.29 −0.07 0.03 −0.14 0.11 DKEFS Design Fluency −0.44* −0.26 −0.46* −0.26 −0.03 0.09 −0.15 −0.21 Note: *p < 0.01 aWhen these analyses were ran excluding participants with SCI from the neurologic group, all significant correlations remained significant. Additional significant correlations were also found between the CST execution score and visuospatial/constructional skills (r = −0.43, p < 0.05) and delayed memory (r = −0.48, p < 0.01), as well as CST total score and visuospatial/constructional skills (r = −0.43, p < 0.05) and delayed memory (r =−0.41, p < 0.05). Table 8. Correlations between cognitive variables and Community Shopping Task (CST) variablesa Neurologic Group (n = 34) Control Group (n = 34) Total CST Prep Score Exec Score CST Time Total CST Prep Score Exec Score CST Time RBANS Total Score −0.64* −0.56* −0.56* −0.53* −0.44* −0.23 −0.43* −0.18 Immediate Memory −0.71* −0.60* −0.62* −0.50* −0.12 −0.06 −0.12 −0.03 Visuospatial/Constructional skills −0.033 −0.37 −0.24 −0.29 −0.35 −0.18 −0.35 −0.06 Language −0.61* −0.47* −0.56* −0.49* −0.20 −0.07 −0.23 −0.38 Attention −0.61* −0.50* −0.55* −0.60* −0.32 −0.24 −0.25 −0.15 Delayed Memory −0.33 −0.29 −0.33 −0.29 −0.07 0.03 −0.14 0.11 DKEFS Design Fluency −0.44* −0.26 −0.46* −0.26 −0.03 0.09 −0.15 −0.21 Neurologic Group (n = 34) Control Group (n = 34) Total CST Prep Score Exec Score CST Time Total CST Prep Score Exec Score CST Time RBANS Total Score −0.64* −0.56* −0.56* −0.53* −0.44* −0.23 −0.43* −0.18 Immediate Memory −0.71* −0.60* −0.62* −0.50* −0.12 −0.06 −0.12 −0.03 Visuospatial/Constructional skills −0.033 −0.37 −0.24 −0.29 −0.35 −0.18 −0.35 −0.06 Language −0.61* −0.47* −0.56* −0.49* −0.20 −0.07 −0.23 −0.38 Attention −0.61* −0.50* −0.55* −0.60* −0.32 −0.24 −0.25 −0.15 Delayed Memory −0.33 −0.29 −0.33 −0.29 −0.07 0.03 −0.14 0.11 DKEFS Design Fluency −0.44* −0.26 −0.46* −0.26 −0.03 0.09 −0.15 −0.21 Note: *p < 0.01 aWhen these analyses were ran excluding participants with SCI from the neurologic group, all significant correlations remained significant. Additional significant correlations were also found between the CST execution score and visuospatial/constructional skills (r = −0.43, p < 0.05) and delayed memory (r = −0.48, p < 0.01), as well as CST total score and visuospatial/constructional skills (r = −0.43, p < 0.05) and delayed memory (r =−0.41, p < 0.05). To understand whether the cognitive variables predicted CST performance, hierarchical regressions were run for the control and neurologic groups separately. Due to limited sample size, regression models used three or less predictor variables so as not to compromise statistical power or lead to possible spurious findings. Thus, we first examined how the RBANS total score and DKEFS design fluency predicted the CST total score. As seen in Table 9, regression results revealed that the RBANS total score and DKEFS design fluency accounted for a significant amount of variance in CST total score for both the control group; F(2, 31) = 3.69, p < 0.05, R2 = 0.20, and the neurologic group, F(2, 31) = 12.82, p < 0.01, R2 = 0.47, with the RBANS total score emerging as a significant predictor in both groups. Table 9. Summary of regression analyses with beta coefficients for the neurologic and control groups, and the cognitive predictors of CST performancea CST Total Score CST Preparation Score CST Execution Score CST Total Time Control Group  Regression Model   RBANS Total Score −0.46** −0.27 −0.42** −0.13   DKEFS Design Fluency 0.09 0.16 −0.04 −0.18    R2 0.20 0.02 0.14 −0.01    F for R2 3.69* 1.26 3.52* 0.96 Neurologic Group  Regression Model   RBANS Total Score −0.53** −0.54** −0.42** −0.50**   DKEFS Design Fluency −0.26 −0.05 −0.33* −0.07    R2 0.47 0.32 0.36 0.24    F for R2 12.82** 6.78** 9.66** 5.77**  Follow-up Regression Model   Immediate Memory −0.46** −0.45* −0.40* −0.21   Language −0.23 −0.10 −0.13 −0.18   Attention −0.27 −0.24 −0.20 −0.41*    R2 0.62 0.45 0.49 0.44    F for R2 17.82** 7.64** 8.33** 7.39** CST Total Score CST Preparation Score CST Execution Score CST Total Time Control Group  Regression Model   RBANS Total Score −0.46** −0.27 −0.42** −0.13   DKEFS Design Fluency 0.09 0.16 −0.04 −0.18    R2 0.20 0.02 0.14 −0.01    F for R2 3.69* 1.26 3.52* 0.96 Neurologic Group  Regression Model   RBANS Total Score −0.53** −0.54** −0.42** −0.50**   DKEFS Design Fluency −0.26 −0.05 −0.33* −0.07    R2 0.47 0.32 0.36 0.24    F for R2 12.82** 6.78** 9.66** 5.77**  Follow-up Regression Model   Immediate Memory −0.46** −0.45* −0.40* −0.21   Language −0.23 −0.10 −0.13 −0.18   Attention −0.27 −0.24 −0.20 −0.41*    R2 0.62 0.45 0.49 0.44    F for R2 17.82** 7.64** 8.33** 7.39** Note: **p < 0.01 *p < 0.05. aWhen analyses were ran excluding participants with SCI from the neurologic group, all results remained the same with the exception that DKEFS Design Fluency was no longer a unique predictor of the CST execution score. Table 9. Summary of regression analyses with beta coefficients for the neurologic and control groups, and the cognitive predictors of CST performancea CST Total Score CST Preparation Score CST Execution Score CST Total Time Control Group  Regression Model   RBANS Total Score −0.46** −0.27 −0.42** −0.13   DKEFS Design Fluency 0.09 0.16 −0.04 −0.18    R2 0.20 0.02 0.14 −0.01    F for R2 3.69* 1.26 3.52* 0.96 Neurologic Group  Regression Model   RBANS Total Score −0.53** −0.54** −0.42** −0.50**   DKEFS Design Fluency −0.26 −0.05 −0.33* −0.07    R2 0.47 0.32 0.36 0.24    F for R2 12.82** 6.78** 9.66** 5.77**  Follow-up Regression Model   Immediate Memory −0.46** −0.45* −0.40* −0.21   Language −0.23 −0.10 −0.13 −0.18   Attention −0.27 −0.24 −0.20 −0.41*    R2 0.62 0.45 0.49 0.44    F for R2 17.82** 7.64** 8.33** 7.39** CST Total Score CST Preparation Score CST Execution Score CST Total Time Control Group  Regression Model   RBANS Total Score −0.46** −0.27 −0.42** −0.13   DKEFS Design Fluency 0.09 0.16 −0.04 −0.18    R2 0.20 0.02 0.14 −0.01    F for R2 3.69* 1.26 3.52* 0.96 Neurologic Group  Regression Model   RBANS Total Score −0.53** −0.54** −0.42** −0.50**   DKEFS Design Fluency −0.26 −0.05 −0.33* −0.07    R2 0.47 0.32 0.36 0.24    F for R2 12.82** 6.78** 9.66** 5.77**  Follow-up Regression Model   Immediate Memory −0.46** −0.45* −0.40* −0.21   Language −0.23 −0.10 −0.13 −0.18   Attention −0.27 −0.24 −0.20 −0.41*    R2 0.62 0.45 0.49 0.44    F for R2 17.82** 7.64** 8.33** 7.39** Note: **p < 0.01 *p < 0.05. aWhen analyses were ran excluding participants with SCI from the neurologic group, all results remained the same with the exception that DKEFS Design Fluency was no longer a unique predictor of the CST execution score. Additional exploratory regressions were then conducted separately for the CST preparation, CST execution, and CST total time scores. As seen in Table 9, RBANS total score and DKEFS design fluency accounted for a significant amount of variance in the CST execution score for the control group; F(2, 31) = 3.52, p < 0.05, R2 = 0.14, with the RBANS total score emerging as a significant predictor. The regression analyses for the CST preparation and CST total time scores were not significant (R2s < 0.02). For the neurologic group, results revealed that the RBANS total score and DKEFS design fluency accounted for a significant amount of variance in the CST preparation score; F(2, 31) = 6.78, p < 0.01, R2 = 0.32, CST execution score; F(2, 31) = 9.66, p < 0.01, R2 = 0.36 (When regression analyses of the cognitive variables predicting CST measures were ran excluding participants with SCI from the neurologic group, all results remained the same with the exception that DKEFS Design Fluency was no longer a unique predictor of the CST execution score.), and CST total time; F(3, 30) = 7.39, p < 0.01, R2 = 0.44. The RBANS total score was a significant predictor for all three CST measures, while DKEFS design fluency emerged as an additional significant predictor only for the CST execution score. In order to understand which RBANS indices were most predictive of CST performance, additional exploratory regression analyses were run using the RBANS scores that were significantly correlated with CST performance for the neurologic group (i.e., immediate memory, language, and attention). As seen in Table 9, results revealed that immediate memory, language, and attention accounted for a significant amount of variance in CST total score; F(3, 30) = 17.82, p < 0.01, R2 = 0.62; CST preparation score; F(3, 30) = 7.63, p < 0.01, R2 = 0.45; CST execution score; F(3, 30) = 8.33, p < 0.01, R2 = 0.49; and CST total time; F(3, 30) = 7.39, p < 0.01, R2 = 0.44. Immediate memory was a significant predictor of CST total score, CST preparation score, and CST execution score. In contrast, attention was a significant predictor of CST total time (Table 9). For the control group, follow-up regression analyses revealed that immediate memory, language and attention did not account for a significant amount of variance in CST total score, CST preparation score, CST execution score, or CST total time (R2s < 0.17). Given that immediate memory was most predictive of CST total score, CST preparation score, and CST execution score for the neurologic group, we wanted to determine whether ability to remember task instructions could be impacting the regression results. Thus we ran correlations between the number of times CST instructions had to be repeated and the CST total score, CST preparation score, and CST execution score. Number of repeated CST instructions was not significantly correlated with any of the aforementioned variables, rs < 0.27. Therefore, it does not appear that ability to remember CST instructions accounted for the results of the regression analyses. Relationship Between Cognitive Variables and CST to Functional Status Finally, we examined whether CST, RBANS total score, and DKEFS design fluency predicted functional status in the neurologic group. Results revealed that the RBANS total score and DKEFS design fluency did not significantly predict functional status; F(2, 31) = 2.55, p = 0.10, R2 = 0.15. In contrast, regression results of the CST total score and CST total time predicting functional status revealed a significant model; F(3, 30) = 5.96, p < 0.01, R2 = 0.30, with both CST total time, t = 3.42, p < 0.01, and CST total score, t = −2.52, p = 0.02, being significant predictors. Because CST total time accounted for the most variance in functional status, a follow-up hierarchical regression analysis was conducted and the first step included the two cognitive variables (RBANS total score and DKEFS design fluency) and the second step included CST total time. Results revealed that the cognitive variables accounted for 15% of the variance in functional status, which was not significant; F(2, 31) = 2.55, p = 0.09. However, the CST total time score accounted for a significant amount of the variance over and above the cognitive measures; F(3, 30) = 4.33, p < 0.01, R2 = 0.33, change in F(1, 30) = 6.84, p < 0.01, R2 change = 0.17. In the final model, significant predictors of functional status were RBANS total score; t = 2.10, p < 0.05, DKEFS design fluency; t = −2.39, p < 0.05, and CST total time; t = 2.61, p < 0.01. Discussion Traditional paper–pencil measures used in neuropsychological assessment are designed to isolate specific cognitive domains in laboratory environments and do not clearly have predictive validity, especially in terms of functional status (Burgess et al., 2006; Goldstein, 1996). However, questions related to functional status have become increasingly important. In this study, we assessed simulated grocery shopping ability in individuals with neurologic conditions using a naturalistic environment. We found that individuals with neurologic conditions performed more poorly than cognitively healthy controls on a naturalistic everyday task. This finding is consistent with research that suggests that individuals with cognitive impairment have more difficulty completing everyday tasks (Chevignard et al., 2010; Cuberos-Urbano et al., 2013; Schmitter-Edgecombe, McAlister, & Weakley, 2012; Yantz et al., 2010). The poorer CST performance of the neurologic group was reflected in the amount of cues needed on both the preparation and execution subsections of the task, as well as the time it took to complete the task. The ability to differentiate between neurologic and control groups using the CST total score and CST total time fell in the good range, while differentiation using the CST preparation and CST execution scores fell in the fair range. In contrast, the cognitive measures failed to accurately differentiate between the neurologic and control groups. Regarding individual CST task components, the neurologic group needed significantly more cues compared to the control group on task components that involved initiation and preparation. For example, participants in the neurologic group needed more cueing to begin writing down recipe items, but once they started the list they were able to complete it with the exception of items that were not part of the recipe (i.e., chocolate dessert, stamps), with which controls demonstrated equivalent difficulty remembering. For the execution subsection, participants in the neurologic group had difficulty when the task component was more vague or a decision had to be made (e.g., choosing a chocolate dessert and/or noodles, setting grocery items on the checkout counter). Participants in the neurologic condition also required significantly more cues on task components that required memory (e.g., using the stop light before crossing the street; using the provided bus pass to board the bus). Level of cueing also distinguished performances between the two groups. Specifically, participants in the control group typically only needed indirect verbal guidance to complete the task, while participants in the neurologic group often required higher cue levels. For example, participants in both the neurologic and control groups often needed prompting to write down grocery items that were not part of the recipe (i.e., stamps and chocolate dessert); however, participants in the neurologic group often had to have a direct cue administered (e.g., “You need to write down chocolate dessert.”), while participants in the control group usually only needed an indirect cue (e.g., “Is there anything else you should write down?”). Due to limited sample sizes, no statistical analyses could be conducted across the neurologic subgroups (i.e., TBI, SCI, MS, and stroke); however, mean time to complete the CST was generally consistent across neurologic subgroups. Participants with TBI and MS appeared to need fewer cues overall compared to the stroke and SCI groups. The stroke group appeared to need slightly more cues for both the CST preparation and CST execution subsections compared to the TBI and MS groups. In contrast, the SCI group appeared to need relatively fewer cues during the CST preparation subsection, but relatively more cues during the CST execution subsection compared to the other groups. Of note, if any participant could not complete the task component due to physical limitations, it did not impact the cueing rubric; therefore, differences in CST preparation and CST execution scores for participants with SCI are not reflective of physical limitations. Due to small samples sizes and significant variability within each neurologic subgroup, it is difficult to draw definitive conclusions as to whether performance on the CST might discriminate between different neurologic conditions and additional research with larger sample sizes is needed. Currently, the relationship between cognition and ability to complete everyday tasks is not fully understood (Burgess, 1997; Burgess, Alderman, Evans, Emslie, & Wilson, 1998). Consistent with models of multitasking (Burgess, 2000), results from the regression analyses suggest that episodic memory is important for completion of a complex, everyday task. The study protocol and follow-up analyses demonstrated that participant’s ability to recall task instructions before starting the task did not significantly impact these results. Therefore, it is more likely that the relationship between memory problems and CST performance is reflective of participant’s difficulty remembering and keeping track of task goals during online performance. Prior research has demonstrated that memory impairment is often one of the more significant cognitive determinants that impact functional status (Farias, Mungas, & Jagust, 2005; Kazui et al., 2005). Moreover, research has shown that executive functioning difficulties may lead to problems with task efficiency, while more significant impairment with everyday tasks occurs once memory is impaired (Schmitter-Edgecombe & Parsey, 2014a, 2014b). Therefore, the CST preparation score appears to be more reflective of problems associated with memory, while the CST execution score captures problems related to both memory and efficiency. However, it is also possible that CST preparation and CST total time are simply related to other aspects of executive functioning outside of cognitive flexibility that were not measured in this study (e.g., organization, planning, problem solving). Furthermore, attention is known to play a significant role in processing speed and ability to complete complex tasks in a timely manner (Levitt, Fugelsang, & Crossley, 2006), which is consistent with findings that attention is related to CST total time. These results also suggest that the different CST components are assessing different aspects of performance. This finding is further supported by the fact that, for the control group, the CST preparation, execution, and time scores were not significantly correlated with one another. We also evaluated whether the CST variables would account for a significant amount of variance in everyday functional status, measured by self-reported IADLs. Several comprehensive reviews of the literature conducted with participants with neurologic conditions have concluded that cognitive predictors account for about 20–25% of the total variance in functional status (McAlister, Schmitter-Edgecombe & Lamb, 2016; Royall et al., 2007; Tucker-Drob, 2011). Results of this study found that cognitive predictors accounted for a nonsignificant proportion of the variance (15%) in functional status. In contrast, CST total time and total score accounted for a significant proportion of the variance in functional status (30%). Furthermore, the time it took to complete the CST continued to be a significant predictor even after controlling for the cognitive predictors in the regression analysis. This is consistent with our hypothesis and prior literature that naturalistic tasks are more predictive of everyday functioning compared to traditional paper–pencil measures of cognition (Fortin, Godbout, & Braun, 2003). Examination of the overall IADL-C scores revealed that most of the participants with neurologic conditions in this study had scores that fell between 1 and 4 (M = 2.10). This means that study participants could complete most of the activities mentioned in the IADL-C, but they either used an assistive device and/or did not complete the task as well as ever. This may help to explain why time to complete the CST was most predictive of functional status compared to level of cues needed. If our sample had more significant impairment and required greater assistance with the IADL-C activities, the number of CST cues may have been even more predictive of functional status. Moreover, using a questionnaire as a proxy for functional status provides limited information and the accuracy of this information is difficult to determine because a trained observer did not complete the questionnaire (although self and informant ratings were highly correlated in a subgroup of our sample). As questions regarding everyday functioning become an increasingly important topic in neuropsychological assessment, it is important to supplement traditional tests of cognition with tests of higher ecological validity (Robertson & Schmitter-Edgecombe, 2016). However, there is currently no clear “gold standard” for assessing functional deficits. Researchers have argued that observation of everyday activities in more realistic environments will likely provide the most information about functional status (Marcotte et al., 2010). This study allowed us to collect direct observation data in a more real-world environment, but it remains unclear how performance might relate to grocery shopping in a real store, especially one with which participants are familiar. We also do not have information on how a similar performance-based task performed in a laboratory setting (e.g., Executive Functioning Performance Test) would compare to the CST. Therefore, comparing functional status questionnaires, performance-based measures administered in the laboratory and realistic environments, and cognitive tests would be beneficial, especially given that many researchers and clinicians do not have access to simulated modules. In regards to study limitations, the sample consisted of primarily Caucasian individuals with an average of 14 years of education, restricting generalizability. Analyses were also restricted in that there were not enough participants to separate out between neurologic conditions to see if any differences within neurologic groups existed. Only the cognitive measures that were used in data collection could be evaluated against the CST, limiting our understanding of other areas of cognition that may be important to everyday functioning. We also recognize that our cognitive battery was brief and the measures used in our study have limited sensitivity and specificity relative to other cognitive tests in existence. Regarding the acuity of the sample, participants were not included in the acute phase of injury and were not currently in the hospital. As a result, the average cognitive scores of our participants in the neurologic group were largely within the average range, but still significantly poorer than the control group. Thus, future research would benefit from evaluating the CST with more acute populations, especially as it relates to community reintegration following hospitalization. Study examiners were not blinded to the neurologic status of participants; therefore, experimenter-bias effects could have potentially impacted results. Furthermore, the CST was evaluated in a single simulated environment for purposes of consistency; however, it is possible to replicate the task in a multitude of clinical and real-world environments and future research examining use of the CST in a broad spectrum of environments would be beneficial. In conclusion, this work empirically investigated the use of a task performed within a simulated environment to better understand everyday functioning. The study provided evidence that individuals with neurologic conditions have more difficulty completing a naturalistic performance-based task compared to cognitively healthy adults. Specifically, individuals with neurologic conditions may require extra time and assistance in completing more complex everyday activities (especially if the task requires initiation, decision-making, or memory). Given that immediate memory was particularly predictive of CST performance, it is important to recognize that individuals with prominent episodic memory problems may be at a higher risk for difficulties completing everyday activities. The results also provide support for the use of simulated environments in assessment to provide a more ecologically valid method for understanding functional deficits. This is imperative given that neuropsychologists are increasingly being asked questions regarding patient’s functional ability and current cognitive tests are not able to reliably address these questions (Robertson, & Schmitter-Edgecombe, 2016). Consequently, by using tasks in more real-world environments, clinicians and researchers can better understand deficits that arise from neurologic conditions and make informed decisions about functional ability. Furthermore, understanding functional ability and the types of problems that preclude an individual from successfully completing everyday tasks can lead to more effective interventions (Giebel & Challis, 2015). Funding This work was supported by a grant from National Science Foundation under grant no. DGE-0900781 and by Edward R. Meyer funds. Conflict of Interest None declared. References Alary Gauvreau , C. , Kairy , D. , Mazer , B. , Guidon , A. , & Le Dorze , G. ( 2017 ). Rehabilitation strategies enhancing participation in shopping malls for persons living with a disability . Disability and Rehabilitation . Alderman , N. , & Burgess , P. W. ( 2002 ). Assessment and rehabilitation of the dysexecutive syndrome. In R. Greenwood , T. M. McMillan , M. P. Barnes , & C. D. Ward (Eds.) , In Handbook of neurological rehabilitation ( 2nd ed ). Hove, East Sussex : Psychology Press . Alderman , N. , Burgess , P. W. , Knight , C. , & Henman , C. ( 2003 ). Ecological validity of a simplified version of the multiple errands shopping test . Journal of the International Neuropsychological Society , 9 , 31 – 44 . Google Scholar CrossRef Search ADS PubMed Amieva , H. , Rouch-Leroyer , I. , Fabrigoule , C. , & Dartigues , J. ( 2000 ). Deterioration of controlled processes in the preclinical phase of dementia: A confirmatory analysis . Dementia and Geriatric Cognitive Disorders , 11 , 46 – 52 . Google Scholar CrossRef Search ADS PubMed Brown , C. , Hasson , H. , Thyselius , V. , & Almborg , A. ( 2012 ). Post‐stroke depression and functional independence: A conundrum . Acta Neurologica Scandinavica , 126 , 45 – 51 . Google Scholar CrossRef Search ADS PubMed Bruce , I. , Ntlholang , O. , Crosby , L. , Cunningham , C. , & Lawlor , B. ( 2016 ). The clinical utility of naturalistic action test in differentiating mild cognitive impairment from early dementia in memory clinic . International Journal of Geriatric Psychology , 31 , 309 – 315 . Google Scholar CrossRef Search ADS Burgess , P. W. ( 1997 ). Theory and methodology in executive function research. In Rabbitt P. (Ed.) , Methodology of fontal and executive function . Hove : Psychology Press . Burgess , P. W. ( 2000 ). Strategy application disorder: The role of the frontal lobes in human multitasking . Psychological Research , 63 , 279 – 288 . Google Scholar CrossRef Search ADS PubMed Burgess , P. W. , Alderman , N. , Evans , J. , Emslie , H. , & Wilson , B. A. ( 1998 ). The ecological validity of tests of executive function . Journal of International Neuropsychological Society , 4 , 547 – 558 . Google Scholar CrossRef Search ADS Burgess , P. W. , Alderman , N. , Forbes , C. , Costello , A. , Coates , L. M. , Dawson , D. R. , et al. . ( 2006 ). The case for the development and use of "ecologically valid" measures of executive function in experimental and clinical psychology . Journal of the International Neuropsychological Society , 12 , 194 – 209 . Google Scholar CrossRef Search ADS PubMed Chaytor , N. , Schmitter-Edgecombe , M. , & Burr , R. ( 2006 ). Improving the ecological validity of executive functioning assessment . Archives of Clinical Neuropsychology , 21 , 217 – 227 . Google Scholar CrossRef Search ADS PubMed Chevignard , M. , Catroppa , C. , Galvin , J. , & Anderson , V. ( 2010 ). Development of an open-ended ecological task to assess executive function in children post TBI: A cooking task . Brain Impairment , 11 , 125 – 143 . Google Scholar CrossRef Search ADS Chevignard , M. , Servant , V. , Mariller , A. , Abada , G. , Pradat-Diehl , P. , & Laurent-Vannier , A. ( 2009 ). Assessment of executive functioning in children after TBI with a naturalistic open-ended task: A pilot study . Developmental Neurorehabilitation , 12 , 76 – 91 . Google Scholar CrossRef Search ADS PubMed Chevignard , M. P. , Soo , C. , Galvin , J. , Catroppa , C. , & Eren , S. ( 2012 ). Ecological assessment of cognitive functions in children with acquired brain injury: A systematic review . Brain Injury , 26 , 1033 – 1057 . Google Scholar CrossRef Search ADS PubMed Chevignard , M. P. , Taillefer , C. , Picq , C. , Poncet , F. , Noulhiane , M. , & Pradat-Diehl , P. ( 2008 ). Ecological assessment of the dysexecutive syndrome using execution of a cooking task . Neuropsychological Rehabilitation , 18 , 461 – 485 . Google Scholar CrossRef Search ADS PubMed Collette , F. , Van der Linden , M. , & Salmon , E. ( 2010 ). Dissociation between controlled and automatic processes in the behavioral variant of frontotemporal dementia . Journal of Alzheimer’s Disease , 22 , 897 – 907 . Google Scholar CrossRef Search ADS PubMed Couture , M. , Larivière , N. , & Lefrançois , R. ( 2005 ). Psychological distress in older adults with low functional independence: A multidimensional perspective . Archives of Gerontology and Geriatrics , 41 , 101 – 111 . Google Scholar CrossRef Search ADS PubMed Cuberos-Urbano , G. , Caracuel , A. , Vilar-Lopez , R. , Valls-Serrano , C. , Bateman , A. , & Verdejo-Garcia , A. ( 2013 ). Ecological validity of the Multiple Errands Test using predictive models of dysexecutive problems in everyday life . Journal of Clinical and Experimental Neuropsychology , 35 , 329 – 336 . Google Scholar CrossRef Search ADS PubMed Dawson , D. R. , Anderson , N. D. , Burgess , P. , Cooper , E. , Krpan , K. M. , & Stuss , D. T. ( 2009 ). Further development of the Multiple Errands Test: Standardized scoring, reliability, and ecological validity for the Baycrest version . Archives of Physical Medicine & Rehabilitation , 90 , S41 – S51 . Google Scholar CrossRef Search ADS Delis , D. C. , Kaplan , E. , & Kramer , J. H. ( 2001 ). Delis-Kaplan Executive Function System (D-KEFS) . San Antonio, TX : The Psychological Corporation . Donovan , N. J. , Heaton , S. C. , Kimberg , C. I. , Wen , P.-S. , Waid-Ebbs , J. K. , Coster , W. , et al. . ( 2011 ). Conceptualizing functional cognition in traumatic brain injury rehabilitation . Brain Injury , 25 , 348 – 364 . Google Scholar CrossRef Search ADS PubMed Farias , S. T. , Mungas , D. , & Jagust , W. ( 2005 ). Degree of discrepancy between self and other-reported everyday functioning by cognitive status: Dementia, mild cognitive impairment, and healthy elders . Int J Geriatr Pscyhiatry , 20 , 827 – 834 . Google Scholar CrossRef Search ADS Ford , J. M. , Roth , W. T. , Isaacks , B. G. , Tinklenberg , J. R. , Yesavage , J. , & Pfefferbaum , A. ( 1997 ). Automatic and effortful processing in aging and dementia: Event-related brain potentials . Neurobiology of Aging , 18 , 169 – 180 . Google Scholar CrossRef Search ADS PubMed Fortin , S. , Godbout , L. , & Braun , C. M. J. ( 2003 ). Cognitive structure of executive deficits in frontally lesioned head trauma patients performing activities of daily living . Cortex; a Journal Devoted to the Study of the Nervous System and Behavior , 39 , 273 – 291 . Google Scholar CrossRef Search ADS PubMed Giebel , C. M. , & Challis , D. ( 2015 ). Translating cognitive and everyday activity deficits into cognitive interventions in mild dementia and mild cognitive impairment . International Journal of Geriatric Psychiatry , 30 , 21 – 31 . Google Scholar CrossRef Search ADS PubMed Giebel , C. M. , Challis , D. , & Montaldi , D. ( 2014 ). Understanding the cognitive underpinnings of functional impairments in early dementia: A review . Aging and Mental Health , 19 , 859 – 875 . Google Scholar CrossRef Search ADS Giebel , C. M. , Shutcliffe , C. , & Challis , D. ( 2015 ). Activities of daily living and quality of life across different stages of dementia: A UK study . Aging and Mental Health , 19 , 63 – 71 . Google Scholar CrossRef Search ADS PubMed Glisky , E. L. , & Delaney , S. M. ( 1996 ). Implicit memory and new semantic learning in posttraumatic amnesia . Journal of Head Trauma Rehabilitation , 11 , 31 – 42 . Google Scholar CrossRef Search ADS Goldstein , G. ( 1996 ). Functional considerations in neuropsychology. In R. J. Sbordone , & C. J. Long (Eds.) , Ecological validity of neuropsychological testing (pp. 75 – 89 ). Delray Beach, FL : GR Press/St Lucie Press . Hecox , R. , Roach , K. E. , DasVerma , J. M. , Giraud , J. E. , Davis , C. M. , & Neulen , K. ( 1994 ). Functional Independence Measurement (FIM) of patients receiving Easy Street—A retrospective study . Physical and Occupational Therapy in Geriatrics , 12 , 17 – 31 . Google Scholar CrossRef Search ADS Hudson , T. ( 1995 ). Learning on Easy Street . Hospitals & Health Networks , 69 , 41 . Google Scholar PubMed Kazui , H. , Matsuda , A. , Hirono , N. , Mori , E. , Miyoshi , N. , Ogino , A. , et al. . ( 2005 ). Everyday memory impairment of patients with mild cognitive impairment . Dementia geriatric Cognitive Disorders , 19 , 331 – 337 . Google Scholar CrossRef Search ADS PubMed Knight , C. , Alderman , N. , & Burgess , P. W. ( 2002 ). Development of a simplified version of the multiple errands test for use in hospital settings . Neuropsychological Rehabilitation , 12 , 231 – 255 . Google Scholar CrossRef Search ADS Levitt , T. , Fugelsang , J. , & Crossley , M. ( 2006 ). Processing speed, attentional capacity, and age-related memory change . Experimental Aging Research , 32 , 263 – 295 . Google Scholar CrossRef Search ADS PubMed MacDonald , P. L. , & Gardner , R. C. ( 2000 ). Type I error rate comparisons of post hoc procedures for Chi-Square tables . Educational and Psychological Measurement , 60 , 735 – 754 . Google Scholar CrossRef Search ADS Maeir , A. , Krauss , S. , & Katz , N. ( 2010 ). Ecological validity of the Multiple Errands Test (MET) on discharge from neurorehabilitation hospital . Occupation, Participation and Health , 31 , S38 – S46 . Google Scholar CrossRef Search ADS Marcotte , T. D. , Scott , J. C. , Kamat , R. , & Heaton , R. K. ( 2010 ). Neuropsychology and the prediction of everyday functioning. In Marcotte T. D. , & Grant I. (Eds.) , Neuropsychology of everyday functioning . New York : The Guildford Press . McAlister , C. , Schmitter-Edgecombe , M. , & Lamb , R. ( 2016 ). Examination of variables that may affect the relationship between cognition and functional status in individuals with mild cognitive impairment: A meta-analysis . Archives of Clinical Neuropsychology , 31 , 123 – 147 . Google Scholar CrossRef Search ADS PubMed McClusky , J. F. ( 2008 ). Creating engaging experiences for rehabilitation . Top Stroke Rehabilitation , 15 , 80 – 86 . Google Scholar CrossRef Search ADS McColl , M. A. , Stirling , P. , Walker , J. , Corey , P. , & Wilkins , R. ( 1999 ). Expectations of independence and life satisfaction among ageing spinal cord injured adults . Disability and Rehabilitation: An International, Multidisciplinary Journal , 21 , 231 – 240 . Google Scholar CrossRef Search ADS Mower , W. R. ( 1999 ). Evaluating bias and variability in diagnostic test reports . Ann Emergency Medicine , 33 , 85 – 91 . Google Scholar CrossRef Search ADS Mulherin , S. A. , & Miller , W. C. ( 2002 ). Spectrum bias or spectrum effect? Subgroup variation in diagnostic test evaluation . Annals of Internal Medicine , 137 , 598 – 602 . Google Scholar CrossRef Search ADS PubMed Randolph , C. , Tierney , M. C. , Mohr , E. , & Chase , T. N. ( 1998 ). The Repeatable Battery for the Assessment of Neuropsychological Status (RBANS): Preliminary clinical validity . Journal for Clinical and Experimental Neuropsychology , 20 , 310 – 319 . Google Scholar CrossRef Search ADS Ransohoff , D. F. , & Feinstein , A. R. ( 1978 ). Problems of spectrum and bias in evaluating the efficacy of diagnostic tests . The New England Journal of Medicine , 299 , 926 – 930 . Google Scholar CrossRef Search ADS PubMed Reid , M. C. , Lachs , M. S. , & Feinstein , A. R. ( 1995 ). Use of methodological standards in diagnostic test research. Getting better but still not good . JAMA: the Journal of the American Medical Association , 274 , 645 – 651 . Google Scholar CrossRef Search ADS Resch , J. A. , Villarreal , V. , Johnson , C. L. , Elliott , T. R. , Kwok , O. , Berry , J. W. , et al. . ( 2009 ). Trajectories of life satisfaction in the first 5 years following traumatic brain injury . Rehabilitation Psychology , 54 , 51 – 59 . Google Scholar CrossRef Search ADS PubMed Richardson , J. , Law , M. , Wishart , L. , & Guyatt , G. ( 2000 ). The use of simulated environment (Easy Street) to retrain independent living skills in elderly persons: A randomized controlled trial . Journal of Gerontology: Medical Sciences , 55 , M578 – M584 . Google Scholar CrossRef Search ADS Robertson , K. , & Schmitter-Edgecombe , M. ( 2016 ). Naturalistic tasks performed in realistic environments: A review with implications for neuropsychological assessment . The Clinical Neuropsychologist , 31 , 16 – 42 . Google Scholar CrossRef Search ADS PubMed Royall , D. R. , Lauterbach , E. C. , Kaufer , D. , Malloy , P. , Coburn , K. L. , & Black , K. J. ( 2007 ). The cognitive correlates of functional status: A review from the committee on research of the American neuropsychiatric association . The Journal of Neuropsychiatry and Clinical Neurosciences , 19 , 249 – 265 . Google Scholar CrossRef Search ADS PubMed Sanders , C. , & Schmitter-Edgecombe , M. ( 2012 ). Identifying the nature of impairment in planning ability with normal aging . Journal of Clinical and Experimental Neuropsychology , 34 , 724 – 737 . Google Scholar CrossRef Search ADS PubMed Scarrabelotti , M. , & Carroll , M. ( 1998 ). Awareness of remembering achieved through automatic and conscious processes in multiple sclerosis . Brain and Cognition , 38 , 183 – 201 . Google Scholar CrossRef Search ADS PubMed Schmitter-Edgcombe , M. , Parsey , C. , & Lamb , R. ( 2014 ). Development and psychometric properties of the Instrumental Activities of Daily Living: Compensation Scale . Archives of Clinical Neuropsychology , 29 , 776 – 792 . Google Scholar CrossRef Search ADS PubMed Schmitter-Edgecombe , M. ( 1996 ). Effects of divided attention on implicit and explicit memory performance following severe closed head injury . Neuropsychology , 10 , 155 – 167 . Google Scholar CrossRef Search ADS Schmitter-Edgecombe , M. , McAlister , C. , & Weakley , A. ( 2012 ). Naturalistic assessment of everyday functioning in individuals with mild cognitive impairment: the day out task . Neuropsychology , 26 , 631 – 641 . Google Scholar CrossRef Search ADS PubMed Schmitter-Edgecombe , M. , & Parsey , C. ( 2014 a). Assessment of functional change and cognitive correlates in the progression from normal aging to dementia . Neuropsychology , 28 , 881 – 893 . Google Scholar CrossRef Search ADS PubMed Schmitter-Edgecombe , M. , & Parsey , C. ( 2014 b). Cognitive correlates of functional abilities in individuals with mild cognitive impairment: Comparison of questionnaire, direct observation and performance-based measures . The Clinical Neuropsychologist , 28 , 726 – 746 . Google Scholar CrossRef Search ADS PubMed Schwartz , M. F. , Buxbaum , L. J. , Ferraro , M. , Veramonti , T. , & Segal , M. ( 2003 ). Naturalistic action test . Suffolk, England : Pearson Assessment . Semlyen , J. K. , Summers , S. J. , & Barnes , M. P. ( 1998 ). Aspects of caregiver distress after severe head injury . Journal of Neurologic Rehabilitation , 12 , 53 – 60 . Sharpe , D. ( 2015 ). Your chi-square test is statistically significant: Now what? Practical Assessment, Research & Evaluation , 20 ( 8–12 ), 1 – 10 . Simmons , N. N. ( 1988 ). A trip down Easy Street. In Clinical aphasiology (pp. 19 – 30 ). Boston, Mass : College-Hill Press . Smith , M. M. , & Arnett , P. A. ( 2010 ). Awareness of executive functioning deficits in multiple sclerosis: Self versus informant ratings of impairment . Journal of Clinical and Experimental Neuropsychology , 32 , 780 – 787 . Google Scholar CrossRef Search ADS PubMed Sox , H. C. ( 1986 ). Probability theory in the use of diagnostic tests. An introduction to critical study of the literature . Ann Internal Medicine , 104 , 60 – 66 . Google Scholar CrossRef Search ADS Spooner , D. M. , & Pachana , N. A. ( 2006 ). Ecological validity in neuropsychological assessment: A case for greater consideration in research with neurologically intact populations . Archives of Clinical Neuropsychology , 21 , 327 – 337 . Google Scholar CrossRef Search ADS PubMed Tape , T. G. (n.d.). The Area Under an AUC Curve. University of Nebraska Medical Center. Retrieved from http://gim.unmc.edu/dxtests/Default.htm. Tucker-Drob , E. M. ( 2011 ). Neurocognitive functions and everyday functions change together in old age . Neuropsychology , 25 , 368 – 377 . Google Scholar CrossRef Search ADS PubMed Vakil , E. , Biederman , Y. , Liran , G. , Grosswasser , Z. , & Aberbuch , S. ( 1994 ). Head injured patients and control group: Implicit vs. explicit measures of frequency judgment . Journal of Clinical Experimental Neuropsychology , 16 , 539 – 546 . Google Scholar CrossRef Search ADS PubMed Vanderploeg , R. D. , Belanger , H. G. , Duchnick , J. D. , & Curtiss , G. ( 2007 ). Awareness problems following moderate to severe traumatic brain injury: Prevalence, assessment methods, and injury correlates . Journal of Rehabilitation Research & Development , 44 , 937 – 950 . Google Scholar CrossRef Search ADS Whitling , P. , Rutjes , A. W. , Reitsma , J. B. , Glas , A. S. , Bossuyt , P. M. , & Klenijnen , J. ( 2004 ). Sources of variation and bias in studies of diagnostic accuracy: A systematic review . Ann Internal Medicine , 140 , 189 – 202 . Google Scholar CrossRef Search ADS World Health Organization . ( 2006 ). Neurological disorders: Public health challenges . Geneva, Switzerland : WHO Press . Yantz , C. L. , Johnson-Greene , D. , Higgins , C. , & Emmerson , L. ( 2010 ). Functional cooking skills and neuropsychological functioning in patients with stroke: An ecological validity study . Neuropsychological Rehabilitation , 20 , 725 – 738 . Google Scholar CrossRef Search ADS PubMed Yeaman , P. A. , Kim , D. , Alexander , J. L. , Ewing , H. , & Kim , K. Y. ( 2013 ). Relationship of physical and functional independence and perceived quality of life of veteran patients with alzheimer disease . American Journal of Hospice & Palliative Medicine , 30 , 462 – 466 . Google Scholar CrossRef Search ADS © The Author(s) 2017. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Archives of Clinical Neuropsychology Oxford University Press

Naturalistic Assessment using a Simulated Environment: Cognitive Correlates and Relationship to Functional Status in Individuals with Neurologic Conditions

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© The Author(s) 2017. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
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Abstract

Abstract Objective Research has shown that neurologic conditions, such as traumatic brain injury and multiple sclerosis, result in a number of cognitive and functional deficits. However, little is known about the relationship between various cognitive domains and ability to perform everyday activities. The Community Shopping Task (CST), a naturalistic assessment task conducted in a simulated environment, was used to examine functional abilities and cognitive correlates of everyday functioning in individuals with neurologic conditions. Method Thirty-four participants with neurologic conditions and 34 healthy controls completed the CST as well as traditional paper–pencil measures of cognition. In addition, all participants completed a questionnaire assessing instrumental activities of daily living (IADLs). Results The results indicated that participants with neurologic conditions required significantly more cues and time to complete the CST compared to control participants and that immediate memory and executive functioning were important predictors of CST performance. Furthermore, time to complete the CST accounted for a significant amount of variance in IADL performance, over and beyond the traditional measures of cognition. Conclusions These results provide evidence that a naturalistic task completed in an everyday environment can enhance our understanding of how daily functioning is impacted in individuals with neurologic conditions and subsequently inform rehabilitation strategies. Everyday functioning, Assessment, Head injury, Traumatic brain injury, Multiple sclerosis, Cerebrovascular disease/accident and stroke Introduction A report from the World Health Organization suggests that up to 1 billion people worldwide are affected by a neurologic condition (2006), such as traumatic brain injury (TBI), stroke, or multiple sclerosis (MS). Most of these conditions result in a number of cognitive deficits that impact the person’s everyday functioning. As a result, those with neurologic conditions often have poorer life satisfaction and perceived quality of life (Giebel, Sutcliffe, & Challis, 2015; McColl et al., 1999; Resch et al., 2009; Yeaman et al., 2013), higher rates of depression and psychological stress (Brown, Hasson, Thysellius, & Almborg, 2012; Couture, Lariviere, & Lafrancois, 2005), and their caregivers are at a higher risk for health problems (Semlyen, Summers, & Barnes, 1998). Understanding cognitive deficits and the subsequent functional problems that arise from these deficits can inform treatment and clinical decisions to improve the daily lives of those living with neurologic conditions. Everyday activities such as cooking, cleaning, and grocery shopping may seem like relatively simple and easy tasks; however, such tasks require a number of interacting cognitive processes and can be difficult for people with neurologic conditions. For example, grocery shopping requires individuals to scan and process a complex environment, remember what items have been selected and what items still need to be selected, make decisions concerning which type, size, and brand of item to choose, and filter out an enormous amount of extraneous information and environmental distractions. Currently, the relationship between cognitive correlates and everyday functioning remains unclear (Burgess, 1997; Burgess, Alderman, Evans, Emslie, & Wilson, 1998; Chaytor, Schmitter-Edgecombe, & Burr, 2006; Giebel, Challis, & Montaldi, 2014). Several reviews of the literature have found that cognitive predictors account for about 20–25% of total variance in functional status within a variety of patient populations (McAlister, Schmitter-Edgecombe & Lamb, 2016; Royall et al., 2007; Tucker-Drob, 2011) and it has been argued that current neuropsychological tests do not fully capture the breadth of cognitive and functional deficits in individual’s with neurologic insult (Donovan et al., 2011). As such, neuropsychologists have begun developing novel assessment techniques to increase understanding of how everyday functional ability is impacted by cognitive deficits (Marcotte, Scott, Kamat, & Heaton, 2010; Robertson & Schmitter-Edgcombe, 2016). Ecological validity, or the extent to which a task is able to generalize to a real-world setting, is an important topic for neuropsychological assessment. Because traditional paper–pencil assessment tasks tend to lack ecological validity (Chevignard, Soo, Galvin, Catroppa, & Eren, 2012), tasks that more closely resemble everyday activities have been developed. For example, the Naturalistic Action Test requires participants to make toast and coffee, gift-wrap a present, and pack a lunchbox and schoolbag in the laboratory setting (Schwartz, Buxbaum, Ferraro, Veramonti, & Segal, 2003). Some studies have found that, compared to traditional paper–pencil measures, lab-based naturalistic tasks are more sensitive to detecting cognitive deficits and predicting functional status in neurologic populations (Bruce, Ntlholang, Crosby, Cunningham, & Lawlor, 2016; Fortin, Godbout, & Braun, 2003). However, naturalistic tasks administered in lab-based settings often require imagination and abstract thinking to perform the task in an atypical environment, which limits generalizability to real-world environments (Simmons, 1988). To address this limitation, researchers have developed naturalistic tasks that can be performed in realistic environments (Alary Gauvreau, Kairy, Mazer, Guindon, & Le Dorze, 2017; Richardson, Law, Wishart, & Guyatt, 2000; Spooner & Pachana, 2006). As a result, some rehabilitation hospitals have incorporated naturalistic environments into their facilities to improve ecological validity of assessment and treatment. These naturalistic environments are often simulated modules, where facsimiles of grocery stores, restaurants, bus stations, cross walks, and recreational venues can help patients and evaluators make a direct connection to real-world activities. Simulated environments provide high face validity and an opportunity to assess functional status within a realistic environment and to better understand how particular cognitive deficits impact performance on real-world tasks (Hudson, 1995; Simmons, 1988). Moreover, individuals can rely on “automatic responses based on [their] own internal histories and contexts” when performing tasks in more realistic environments (McClusky, 2008; Simmons, 1988, p. 25). This is particularly important because research has shown that implicit processing remains relatively intact compared to more explicit processing abilities in a number of neurologic conditions (Amieva, Rouch-Leroyer, Fabrigoule, & Dartigues, 2000; Collette, Van, & Salmon, 2010; Ford et al., 1997; Glisky & Delaney, 1996; Scarrabelotti & Carroll, 1998; Schmitter-Edgecombe, 1996; Vakil, Biederman, Liran, Groswasser, & Aberbuch, 1994). As a result, if an individual with a neurologic condition is able to capitalize on implicit processing abilities when performing a task in a simulated environment, but continues to have difficulty completing the task, the examiner can better understand and/or anticipate problems that the person may have in the real world. Despite the adoption of simulated environments in rehabilitation settings, little literature evaluating the efficacy of simulated environments is available, and what does exist tends to focus on treatment and intervention, rather than assessment. For example, Hecox and colleagues (1994) retrospectively analyzed Functional Independence Measure (FIM) scores at discharge and found that patients who were admitted to the hospital after the simulated environment was installed had better FIM scores compared to patients who were treated at the hospital before the simulated environment was available. In contrast, a randomized controlled trial that compared use of a gym to use of a simulated environment for rehabilitation of neurologic patients did not find a significant difference between conditions either at discharge or at a 2-month follow-up (Richardson et al., 2000). Outside of the treatment literature, one study created an obstacle course that included components known to increase fall risk in older adults (e.g., different textures of flooring) within a simulated environment, which appeared useful in evaluating fall risk. However, further validation of this task, as well as other assessment tasks that can be used in simulated environments is necessary. Although studies examining simulated environments are few, conclusions drawn from studies evaluating naturalistic tasks conducted in other realistic environments, such as a kitchen, shopping center, or home environment, suggest potential benefits for using simulated environments in assessment. For example, research has demonstrated that performance on cooking (e.g., Rabideau Kitchen Evaluation—Revised), shopping (Multiple Errands Test [MET]) and other household tasks (e.g., Day Out Task [DOT]) in individuals with stroke, brain injury, mild cognitive impairment, and dementia was associated with performance on tasks of executive functioning, verbal memory, retrospective and prospective memory, simple auditory attention, visuospatial skills, and overall cognitive performance (Alderman et al., 2003; Alderman, & Burgess, 2002; Chevignard et al., 2008, 2009, 2010; Cuberos-Urbano et al., 2013; Dawson et al., 2009; Knight et al., 2002; Maeir et al., 2010; Schmitter-Edgecombe & Parsey, 2014b; Schmitter-Edgecombe et al., 2012; Yantz, Johnson-Greene, Higginson, & Emmerson, 2010). Furthermore, performance on shopping and household tasks was found to be predictive of everyday functioning (Alderman et al., 2003; Alderman, & Burgess, 2002; Cuberos-Urbano et al., 2013; Dawson et al., 2009; Knight et al., 2002; Maeir et al., 2010; Sanders & Schmitter-Edgecombe, 2012; Schmitter-Edgecombe & Parsey, 2014a; Schmitter-Edgecombe et al., 2012; Schmitter-Edgecombe & Parsey, 2014b). Therefore, it appears that naturalistic tasks conducted in realistic environments are associated with cognitive processes and can provide useful assessment information about everyday functioning. The purpose of this study was to examine functional status and the cognitive correlates of everyday functioning in individuals with neurologic conditions using a novel naturalistic task conducted in a simulated environment, called the “Community Shopping Task” (CST). Individuals with neurologic conditions (e.g., TBI, MS) and cognitively healthy adults completed the CST, which required them to make a grocery shopping list, go shopping in a simulated grocery store module, pay for the groceries, and board a bus. A hierarchical cueing system was employed if participants were unable to complete an aspect of the task. Correlates of cognitive status were obtained from standardized neurological assessments. Based on research that has evaluated naturalistic tasks in realistic environments, we hypothesized that participants with neurologic conditions would perform more poorly on the CST compared to healthy controls (Chevignard et al., 2008). In regard to the cognitive correlates, we hypothesized that memory and executive functioning would be correlated with the CST performance based on prior research regarding naturalistic tasks and cognition (Chevignard et al., 2010; Schmitter-Edgecombe et al., 2012). As a secondary goal, we assessed whether performance on the CST accounted for additional variance in functional status, as measured by self-report questionnaire, above and beyond what cognitive test performance predicted. Consistent with prior literature (Schmitter-Edgecombe & Parsey, 2014a), we hypothesized that the CST would contribute uniquely to the prediction of everyday functioning. Methods Participants Participants were 34 persons (21 female, 13 male) with a variety of neurologic conditions that can affect cognition. We choose to use a heterogeneous neurologic sample with a range of cognitive and functional impairments so that our study design would be less prone to the spectrum bias (i.e., including participants with too little variability in functional deficits) (Mower, 1999; Mulherin & Miller, 2002; Ransohoff & Feinstein, 1978; Reid, Lachs, & Feinstein, 1995; Sox, 1986; Whitling et al., 2004). About 9 participants had a closed head injury (time since injury: M = 62.71 months, range = 7–192 months), 6 participants had a stroke (time since stroke: M = 8 months, range = 6–10 months), 16 participants had multiple sclerosis (time since diagnosis: M = 224 months, range = 40–507 months), and 3 participants had a spinal cord injury (time since injury: M = 110 months, range = 27–254 months). All participants in the neurologic condition had self-reported ongoing cognitive and functional difficulties. Interview, testing, and collateral medical information were evaluated to substantiate the diagnosis of a neurologic condition. Participants were required to be at least 6 months post-injury or diagnosis. Exclusion criteria included a developmental disorder (e.g., autism), current or recent (within the past year) psychoactive substance abuse, diagnosis of dementia, and psychiatric causes of cognitive dysfunction (e.g., schizophrenia). Thirty-four cognitively healthy controls (24 female, 10 male) were also tested. Control participants were screened for diseases and disorders that may affect cognition during an in-person interview regarding developmental and medical history. Groups were well matched on age; t(66) = 0.05, p = 0.96, education; t(66) = −0.37, p = 0.71, and gender; x2(1, n = 68) = 0.59, p = 0.44 (see Table 1). Participants were recruited through advertisements, community support groups and wellness fairs, physician referrals, and other local agencies working with individuals with neurologic conditions. Table 1. Differences in demographic, cognitive, and Community Shopping Task (CST) variables between the different groups Control Group (n = 34) Neurologic Group (n = 34) TBI (n = 9) Stroke (n = 6) MS (n = 16) SCI (n = 3) M (SD) M (SD) M (SD) M (SD) M (SD) M (SD) Demographics  Age 50.82 51.02 39.22 47.67 57.19 60.33 (15.89) (14.69) (18.36)a (10.31) (9.39)a (14.01)  Education 14.35 14.15 13.44 14.83 14.50 13.00 (2.60) (1.92) (1.42) (2.86) (1.83) (1.00)  Gender 24F/10M 21F/13M 5F/4M 1F/5M 5F/11M 2F/1M General Ability  Estimated premorbid FSIQ 111.62 106.21 106.67 105.80 109.94 85.67 (9.04) (16.81) (15.20) (23.96) (14.63) (10.07) RBANS  Total Score 108.58 91.50** 92.13 85.60 92.94 92.00 (9.33) (17.56) (17.92) (28.24) (16.12) (2.65)  Immediate Memory 107.27 95.73** 94.22 100.60 95.81 91.67 (12.22) (17.12) (20.05) (23.56) (15.41) (9.87)  Visuospatial/Constructional skills 101.70 91.52* 87.33 83.40 92.44 112.67 (15.21) (21.69) (21.80) (26.79) (20.06) (15.95)  Language 108.55 95.03** 94.89 93.20 96.63 90.00 (11.51) (9.43) (13.61) (11.43) (6.46) (6.25)  Attention 106.52 89.59** 89.50 83.20 93.13 81.67 (12.16) (20.52) (24.22) (24.79) (19.72) (5.77)  Delayed Memory 105.82 95.61** 93.44 99.60 95.19 97.67 (8.12) (16.37) (15.80) (20.51) (17.47) (9.50) Executive Functioning  DKEFS Design Fluency 12.36 9.00** 11.00 (4.33)b 5.20 (2.39)b 8.94 (2.21) 9.67 (3.51) (2.51) (3.45) Control Group (n = 34) Neurologic Group (n = 34) TBI (n = 9) Stroke (n = 6) MS (n = 16) SCI (n = 3) M (SD) M (SD) M (SD) M (SD) M (SD) M (SD) Demographics  Age 50.82 51.02 39.22 47.67 57.19 60.33 (15.89) (14.69) (18.36)a (10.31) (9.39)a (14.01)  Education 14.35 14.15 13.44 14.83 14.50 13.00 (2.60) (1.92) (1.42) (2.86) (1.83) (1.00)  Gender 24F/10M 21F/13M 5F/4M 1F/5M 5F/11M 2F/1M General Ability  Estimated premorbid FSIQ 111.62 106.21 106.67 105.80 109.94 85.67 (9.04) (16.81) (15.20) (23.96) (14.63) (10.07) RBANS  Total Score 108.58 91.50** 92.13 85.60 92.94 92.00 (9.33) (17.56) (17.92) (28.24) (16.12) (2.65)  Immediate Memory 107.27 95.73** 94.22 100.60 95.81 91.67 (12.22) (17.12) (20.05) (23.56) (15.41) (9.87)  Visuospatial/Constructional skills 101.70 91.52* 87.33 83.40 92.44 112.67 (15.21) (21.69) (21.80) (26.79) (20.06) (15.95)  Language 108.55 95.03** 94.89 93.20 96.63 90.00 (11.51) (9.43) (13.61) (11.43) (6.46) (6.25)  Attention 106.52 89.59** 89.50 83.20 93.13 81.67 (12.16) (20.52) (24.22) (24.79) (19.72) (5.77)  Delayed Memory 105.82 95.61** 93.44 99.60 95.19 97.67 (8.12) (16.37) (15.80) (20.51) (17.47) (9.50) Executive Functioning  DKEFS Design Fluency 12.36 9.00** 11.00 (4.33)b 5.20 (2.39)b 8.94 (2.21) 9.67 (3.51) (2.51) (3.45) Note: *p < 0.05, **p < 0.01, ap < 0.01, bp < 0.05; FSIQ = Full Scale Intelligence Quotient (predicted by Wechsler Test of Adult Reading scores); RBANS = Repeatable Battery for the Assessment of Neuropsychological Status, DKEFS = Delis-Kaplan Executive Functioning System. Table 1. Differences in demographic, cognitive, and Community Shopping Task (CST) variables between the different groups Control Group (n = 34) Neurologic Group (n = 34) TBI (n = 9) Stroke (n = 6) MS (n = 16) SCI (n = 3) M (SD) M (SD) M (SD) M (SD) M (SD) M (SD) Demographics  Age 50.82 51.02 39.22 47.67 57.19 60.33 (15.89) (14.69) (18.36)a (10.31) (9.39)a (14.01)  Education 14.35 14.15 13.44 14.83 14.50 13.00 (2.60) (1.92) (1.42) (2.86) (1.83) (1.00)  Gender 24F/10M 21F/13M 5F/4M 1F/5M 5F/11M 2F/1M General Ability  Estimated premorbid FSIQ 111.62 106.21 106.67 105.80 109.94 85.67 (9.04) (16.81) (15.20) (23.96) (14.63) (10.07) RBANS  Total Score 108.58 91.50** 92.13 85.60 92.94 92.00 (9.33) (17.56) (17.92) (28.24) (16.12) (2.65)  Immediate Memory 107.27 95.73** 94.22 100.60 95.81 91.67 (12.22) (17.12) (20.05) (23.56) (15.41) (9.87)  Visuospatial/Constructional skills 101.70 91.52* 87.33 83.40 92.44 112.67 (15.21) (21.69) (21.80) (26.79) (20.06) (15.95)  Language 108.55 95.03** 94.89 93.20 96.63 90.00 (11.51) (9.43) (13.61) (11.43) (6.46) (6.25)  Attention 106.52 89.59** 89.50 83.20 93.13 81.67 (12.16) (20.52) (24.22) (24.79) (19.72) (5.77)  Delayed Memory 105.82 95.61** 93.44 99.60 95.19 97.67 (8.12) (16.37) (15.80) (20.51) (17.47) (9.50) Executive Functioning  DKEFS Design Fluency 12.36 9.00** 11.00 (4.33)b 5.20 (2.39)b 8.94 (2.21) 9.67 (3.51) (2.51) (3.45) Control Group (n = 34) Neurologic Group (n = 34) TBI (n = 9) Stroke (n = 6) MS (n = 16) SCI (n = 3) M (SD) M (SD) M (SD) M (SD) M (SD) M (SD) Demographics  Age 50.82 51.02 39.22 47.67 57.19 60.33 (15.89) (14.69) (18.36)a (10.31) (9.39)a (14.01)  Education 14.35 14.15 13.44 14.83 14.50 13.00 (2.60) (1.92) (1.42) (2.86) (1.83) (1.00)  Gender 24F/10M 21F/13M 5F/4M 1F/5M 5F/11M 2F/1M General Ability  Estimated premorbid FSIQ 111.62 106.21 106.67 105.80 109.94 85.67 (9.04) (16.81) (15.20) (23.96) (14.63) (10.07) RBANS  Total Score 108.58 91.50** 92.13 85.60 92.94 92.00 (9.33) (17.56) (17.92) (28.24) (16.12) (2.65)  Immediate Memory 107.27 95.73** 94.22 100.60 95.81 91.67 (12.22) (17.12) (20.05) (23.56) (15.41) (9.87)  Visuospatial/Constructional skills 101.70 91.52* 87.33 83.40 92.44 112.67 (15.21) (21.69) (21.80) (26.79) (20.06) (15.95)  Language 108.55 95.03** 94.89 93.20 96.63 90.00 (11.51) (9.43) (13.61) (11.43) (6.46) (6.25)  Attention 106.52 89.59** 89.50 83.20 93.13 81.67 (12.16) (20.52) (24.22) (24.79) (19.72) (5.77)  Delayed Memory 105.82 95.61** 93.44 99.60 95.19 97.67 (8.12) (16.37) (15.80) (20.51) (17.47) (9.50) Executive Functioning  DKEFS Design Fluency 12.36 9.00** 11.00 (4.33)b 5.20 (2.39)b 8.94 (2.21) 9.67 (3.51) (2.51) (3.45) Note: *p < 0.05, **p < 0.01, ap < 0.01, bp < 0.05; FSIQ = Full Scale Intelligence Quotient (predicted by Wechsler Test of Adult Reading scores); RBANS = Repeatable Battery for the Assessment of Neuropsychological Status, DKEFS = Delis-Kaplan Executive Functioning System. All participants completed a battery of standardized and experimental neuropsychological tests in a clinic-based setting, as well as the CST in a local rehabilitation hospital within a simulated environment. The testing session was approximately three hours. All participants were given a $30 honorarium in return for their time. Participants with a neurologic condition were also given a report documenting their performance on the neuropsychological tests. Measures The Community Shopping Task Participants completed the CST at a local rehabilitation hospital that has multiple simulated modules, including an office area (Fig. 1), grocery store façade (Fig. 2), and bus (Fig. 3). The task is broken into two subsections: recipe and grocery shopping. As seen in Table 2, the recipe, or preparation, section is comprised of 15 unique task steps and the grocery shopping, or execution, section is comprised of 23 unique task steps. Table 2. Task steps of the Community Shopping Task (CST) Recipe Section (Preparation) Begins task Looks up recipe Refers to list of items that they have at home Begins writing down items Writes down paprika Writes down pepper Writes down onions Writes down garlic Writes down 1 can whole tomatoes Writes down noodles Writes down items not needed Writes down chocolate dessert Writes down stamp book Indicates they are ready to move to shopping area Takes wallet and list with them Shopping Section (Execution) Begins task Chooses a shopping instrument Consults grocery list Begins to gather items on the grocery list Gets paprika Gets pepper Gets 3 onions Gets garlic Gets 1 can whole tomatoes Gets noodles Chooses a chocolate dessert Gets children’s ibuprofen Gets items not needed Brings items to cashier Sets items on counter Asks cashier for stamps Retrieves cash from wallet Counts out cash Pays cashier Picks up grocery bag and has wallet Moves towards the bus and leaves cart Uses stop light to cross street Gives the bus driver the bus pass Recipe Section (Preparation) Begins task Looks up recipe Refers to list of items that they have at home Begins writing down items Writes down paprika Writes down pepper Writes down onions Writes down garlic Writes down 1 can whole tomatoes Writes down noodles Writes down items not needed Writes down chocolate dessert Writes down stamp book Indicates they are ready to move to shopping area Takes wallet and list with them Shopping Section (Execution) Begins task Chooses a shopping instrument Consults grocery list Begins to gather items on the grocery list Gets paprika Gets pepper Gets 3 onions Gets garlic Gets 1 can whole tomatoes Gets noodles Chooses a chocolate dessert Gets children’s ibuprofen Gets items not needed Brings items to cashier Sets items on counter Asks cashier for stamps Retrieves cash from wallet Counts out cash Pays cashier Picks up grocery bag and has wallet Moves towards the bus and leaves cart Uses stop light to cross street Gives the bus driver the bus pass Table 2. Task steps of the Community Shopping Task (CST) Recipe Section (Preparation) Begins task Looks up recipe Refers to list of items that they have at home Begins writing down items Writes down paprika Writes down pepper Writes down onions Writes down garlic Writes down 1 can whole tomatoes Writes down noodles Writes down items not needed Writes down chocolate dessert Writes down stamp book Indicates they are ready to move to shopping area Takes wallet and list with them Shopping Section (Execution) Begins task Chooses a shopping instrument Consults grocery list Begins to gather items on the grocery list Gets paprika Gets pepper Gets 3 onions Gets garlic Gets 1 can whole tomatoes Gets noodles Chooses a chocolate dessert Gets children’s ibuprofen Gets items not needed Brings items to cashier Sets items on counter Asks cashier for stamps Retrieves cash from wallet Counts out cash Pays cashier Picks up grocery bag and has wallet Moves towards the bus and leaves cart Uses stop light to cross street Gives the bus driver the bus pass Recipe Section (Preparation) Begins task Looks up recipe Refers to list of items that they have at home Begins writing down items Writes down paprika Writes down pepper Writes down onions Writes down garlic Writes down 1 can whole tomatoes Writes down noodles Writes down items not needed Writes down chocolate dessert Writes down stamp book Indicates they are ready to move to shopping area Takes wallet and list with them Shopping Section (Execution) Begins task Chooses a shopping instrument Consults grocery list Begins to gather items on the grocery list Gets paprika Gets pepper Gets 3 onions Gets garlic Gets 1 can whole tomatoes Gets noodles Chooses a chocolate dessert Gets children’s ibuprofen Gets items not needed Brings items to cashier Sets items on counter Asks cashier for stamps Retrieves cash from wallet Counts out cash Pays cashier Picks up grocery bag and has wallet Moves towards the bus and leaves cart Uses stop light to cross street Gives the bus driver the bus pass Fig. 1. View largeDownload slide Simulated environment: Office area where participants were read Community Shopping Task (CST) instructions and completed the recipe/preparation subsection of the CST. Fig. 1. View largeDownload slide Simulated environment: Office area where participants were read Community Shopping Task (CST) instructions and completed the recipe/preparation subsection of the CST. Fig. 2. View largeDownload slide Simulated environment: The grocery store area where participants completed the shopping portion of the execution subsection of the CST. Fig. 2. View largeDownload slide Simulated environment: The grocery store area where participants completed the shopping portion of the execution subsection of the CST. Fig. 3. View largeDownload slide Simulated environment: The crosswalk and bus where participants completed the latter half of the execution subsection of the Community Shopping Task (CST). Fig. 3. View largeDownload slide Simulated environment: The crosswalk and bus where participants completed the latter half of the execution subsection of the Community Shopping Task (CST). Participants were told to imagine that they were planning to have friends over for dinner and would be making Hungarian Goulash, a recipe contained in a provided recipe book. They were given a list of items that they already had at home and were instructed to make a grocery list of recipe items that they would need to get at the store. In addition to the recipe items, they were told to buy a store-bought chocolate dessert and pick up stamps from the cashier when checking out so that they could mail an important bill. These instructions were read to participants in the office area of the simulated environment, which is also where they prepared their grocery store list. Participants were told that after they completed their shopping list, they were to go into the shopping area to collect the needed items from grocery store shelves. Once they finished shopping, they were to pay for their items and board a bus for the trip home. Participants were provided with a wallet with cash and a bus pass to use. Before beginning the shopping section of the task, participants were shown where the bus was located in the simulated environment, and were instructed to look at a crosswalk light just ahead of the bus before walking in front of the bus. An interruption was also implemented during the course of the shopping task. That is, after the participant collected three items in the grocery store, the examiner told the participant that they just received a call from a neighbor asking them to pick up children’s ibuprofen because the neighbor’s daughter was sick. While completing the CST, an examiner observed the participant’s performance and cued them if necessary. Participants were told that the examiner would not be assisting them with any part of the task unless they got stuck. In cases where the participant could not complete a task step, a hierarchical cueing system was employed as follows: indirect verbal guidance, gestural guidance, direct verbal guidance, physical assistance, and doing the task step for the participant. Each time a cue was given, the examiner recorded which task step had to be cued and the highest level of cue necessary for task step completion. The examiner also coded whether the participant either self-corrected a task step or had a slowed performance. Scoring of the Community Shopping Task Each unique task step was given a 0–6 rating, with a higher rating representing more assistance needed based on the hierarchical cueing system (see Table 3 for a description of the coding rubric). The score for each unique task step was summed to create a preparation score (total score of recipe subsection; range = 0–90), execution score (total score of the shopping subsection; range = 0–138), and CST total score (range = 0–228). The experimenter also recorded the total time it took participants to complete the CST. If a participant was unable to complete a task step due to physical limitations, it was coded separately and did not impact the cueing rubric. Table 3. Coding rubric for each unique task step Type of Cue Description 0: No assistance needed The participant completed the task correctly and in a timely manner without self-correcting. 1: Self-Corrected or Slowed Performance The participant required no help or reassurance but made mistakes that he/she self-corrected or proceeded at a slow rate with the task. 2: Indirect Verbal Guidance needed The participant was provided with verbal prompting, such as an open-ended question or an affirmation that helped them move on. Indirect verbal guidance generally comes in the form of a question, not a direct instruction, e.g., “Is that the correct/right item?” “What should you do now?”; “Do you have everything you need?”; “Is there something else you may want to do?”. Direct phrases are avoided. 3: Gestural Guidance needed The participant was provided with gestural prompting. The examiner provided a gesticulation that mimics the action that is necessary to complete the subtask, or made a movement that guides the participant, e.g., point to the wallet to remind the participant to take it with them or point to where the participant may find a grocery item, etc. Physical assistance, such as handing the participant an item, is avoided. 4: Direct Verbal Guidance needed The participant was provided a one-step command, so that they took action. For example, the examiner might say, “Write out a list of shopping items”; “Get the children’s Ibuprofen from the shelf”; Pick up the garlic; or “get a shopping bag”. 5: Physical Assistance needed The examiner physically assists the participant with the step, but does not do the task for the participant. For example, the examiner may put the participants hand on a needed grocery item. 6: Did the task for the participant The examiner completed the task for the participant. All other cues have been administered and the participant is still unable to complete the task. Type of Cue Description 0: No assistance needed The participant completed the task correctly and in a timely manner without self-correcting. 1: Self-Corrected or Slowed Performance The participant required no help or reassurance but made mistakes that he/she self-corrected or proceeded at a slow rate with the task. 2: Indirect Verbal Guidance needed The participant was provided with verbal prompting, such as an open-ended question or an affirmation that helped them move on. Indirect verbal guidance generally comes in the form of a question, not a direct instruction, e.g., “Is that the correct/right item?” “What should you do now?”; “Do you have everything you need?”; “Is there something else you may want to do?”. Direct phrases are avoided. 3: Gestural Guidance needed The participant was provided with gestural prompting. The examiner provided a gesticulation that mimics the action that is necessary to complete the subtask, or made a movement that guides the participant, e.g., point to the wallet to remind the participant to take it with them or point to where the participant may find a grocery item, etc. Physical assistance, such as handing the participant an item, is avoided. 4: Direct Verbal Guidance needed The participant was provided a one-step command, so that they took action. For example, the examiner might say, “Write out a list of shopping items”; “Get the children’s Ibuprofen from the shelf”; Pick up the garlic; or “get a shopping bag”. 5: Physical Assistance needed The examiner physically assists the participant with the step, but does not do the task for the participant. For example, the examiner may put the participants hand on a needed grocery item. 6: Did the task for the participant The examiner completed the task for the participant. All other cues have been administered and the participant is still unable to complete the task. Table 3. Coding rubric for each unique task step Type of Cue Description 0: No assistance needed The participant completed the task correctly and in a timely manner without self-correcting. 1: Self-Corrected or Slowed Performance The participant required no help or reassurance but made mistakes that he/she self-corrected or proceeded at a slow rate with the task. 2: Indirect Verbal Guidance needed The participant was provided with verbal prompting, such as an open-ended question or an affirmation that helped them move on. Indirect verbal guidance generally comes in the form of a question, not a direct instruction, e.g., “Is that the correct/right item?” “What should you do now?”; “Do you have everything you need?”; “Is there something else you may want to do?”. Direct phrases are avoided. 3: Gestural Guidance needed The participant was provided with gestural prompting. The examiner provided a gesticulation that mimics the action that is necessary to complete the subtask, or made a movement that guides the participant, e.g., point to the wallet to remind the participant to take it with them or point to where the participant may find a grocery item, etc. Physical assistance, such as handing the participant an item, is avoided. 4: Direct Verbal Guidance needed The participant was provided a one-step command, so that they took action. For example, the examiner might say, “Write out a list of shopping items”; “Get the children’s Ibuprofen from the shelf”; Pick up the garlic; or “get a shopping bag”. 5: Physical Assistance needed The examiner physically assists the participant with the step, but does not do the task for the participant. For example, the examiner may put the participants hand on a needed grocery item. 6: Did the task for the participant The examiner completed the task for the participant. All other cues have been administered and the participant is still unable to complete the task. Type of Cue Description 0: No assistance needed The participant completed the task correctly and in a timely manner without self-correcting. 1: Self-Corrected or Slowed Performance The participant required no help or reassurance but made mistakes that he/she self-corrected or proceeded at a slow rate with the task. 2: Indirect Verbal Guidance needed The participant was provided with verbal prompting, such as an open-ended question or an affirmation that helped them move on. Indirect verbal guidance generally comes in the form of a question, not a direct instruction, e.g., “Is that the correct/right item?” “What should you do now?”; “Do you have everything you need?”; “Is there something else you may want to do?”. Direct phrases are avoided. 3: Gestural Guidance needed The participant was provided with gestural prompting. The examiner provided a gesticulation that mimics the action that is necessary to complete the subtask, or made a movement that guides the participant, e.g., point to the wallet to remind the participant to take it with them or point to where the participant may find a grocery item, etc. Physical assistance, such as handing the participant an item, is avoided. 4: Direct Verbal Guidance needed The participant was provided a one-step command, so that they took action. For example, the examiner might say, “Write out a list of shopping items”; “Get the children’s Ibuprofen from the shelf”; Pick up the garlic; or “get a shopping bag”. 5: Physical Assistance needed The examiner physically assists the participant with the step, but does not do the task for the participant. For example, the examiner may put the participants hand on a needed grocery item. 6: Did the task for the participant The examiner completed the task for the participant. All other cues have been administered and the participant is still unable to complete the task. Cueing and scoring reliability The CST was first piloted with 12 individuals before the experiment began to ensure that the cueing hierarchy could account for a broad possibility of testing scenarios. Next, to substantiate that the cueing hierarchy was being applied appropriately and to evaluate scoring reliability, two examiners were present when 10 (29%) of the study participants were tested. One of the examiners administered the cues to the participant and coded for cue levels administered. The second examiner observed and coded for cue levels administered and additionally recorded whether they agreed or disagreed with the cues being administered by the primary examiner. Total discrepancies in cueing agreement were totaled and there was 99.74% agreement in cues administered by the primary examiner. Total discrepancies in cue coding scores were summed to determine inter-rater reliability and there was 100% agreement in scoring. Internal consistency reliability of the CST total score and CST execution score fell in the acceptable to good ranges (α = 0.82, and α = 0.79, respectively); and the CST preparation score fell within the questionable range (α = 0.64). Cognitive variables Cognitive variables included measures of overall cognition, immediate memory, visuospatial/constructional skills, language, attention, delayed memory, and executive functioning. The standard scores for each test were used in the analyses. “Repeatable Battery for Neuropsychological Status” (RBANS, Randolph, Tierney, Mohr, & Chase, 1998). The RBANS, form A, was administered, which consists of five indices. The total score was used in our analyses as a measure of overall cognitive functioning and each index was used to measure individual cognitive processes. The “Immediate Memory” index includes a list learning and story memory task. The “Visuospatial/Constructional” index is made up of a figure copy and line orientation task. A picture naming and semantic fluency task comprises the “Language” index. The “Attention” index includes a digit span and coding task. List recall, list recognition, story recall, and figure recall tasks make up the “Delayed Memory” index. “Delis-Kaplan Executive Function System (DKEFS) design fluency subtest” (Delis, Kaplan, & Kramer, 2001). The design fluency task was used as a measure of executive functioning given that the RBANS does not include an index of executive functioning, and executive functioning is known to be an important component to everyday performance. The task has three conditions: basic, filter, and switch. For all three conditions, participants were instructed to make as many unique designs as they could in 60 s using only four straight lines and always having each line touch at least one other line at a dot. In the basic condition, the squares contained an array of five filled dots and the participants were asked to draw the designs by connecting the filled dots. In the filter condition, the squares contained five empty dots and five filled dots and the participant was asked to draw designs by connecting only the empty dots. In the switch condition, the squares once again had five empty dots and five filled dots; however, this time the participant was asked to draw the designs by switching back and forth between connecting empty and filled dots. The overall standard score that combines performance on each of the three conditions was used. Everyday functioning The participants also completed the Instrumental Activities of Daily Living-Compensation questionnaire (IADL-C; Schmitter-Edgecombe, Parsey, & Lamb, 2014) prior to their evaluation. The questionnaire consists of 27 questions pertaining to IADLs (e.g., can use a telephone book, address book or other tool to look up unfamiliar numbers). The questionnaire addresses four IADL subdomains: money and self-management, home daily living, travel and event memory, and social skills. Participants answered each question using a Likert scale that ranges from “1” (independent, as well as ever, no aid) to “8” (not able to complete activity anymore). A category for indicating that the participant “does not need to complete the activity” was also included. The total mean score was used in the analyses. A subset of participants with neurologic conditions (n = 15) had knowledgeable informants complete the IADL-C. A correlation analysis between the IADL-C completed by the participants and their respective knowledgeable informants indicated that scores were consistent between the two groups; r = 0.95, p < 0.01. This finding indicates that self-awareness problems did not significantly impact the IADL-C ratings, which is consistent with prior research conducted with similar neurologic groups (Smith & Arnett, 2010; Vanderploeg, Belanger, Duchnick, & Curtiss, 2007). Results Data was analyzed using SPSS statistical software. First, differences between neurologic and control groups on demographic and cognitive variables were examined using independent samples t-tests. Neurologic subgroup data (i.e., TBI, SCI, stroke, and MS) is also presented for reference in Table 1. Independent samples t-tests were used to examine differences on CST performance between the neurologic and control groups. Receiver Operating Characteristic (ROC) curves were also calculated to determine the accuracy of the CST at differentiating between the neurologic and control groups. Neurologic subgroup data for the CST is also presented in Table 4. Correlations between the CST variables were obtained separately for the neurologic and control group to better understand how the CST variables are related to one another. Correlations were also obtained among the cognitive measures and the CST variables. Due to the high number of correlations being conducted, a more conservative p-value of 0.01 was used to indicate correlations that differed significantly from zero. Differences between groups in the amount of cueing administered for each CST task component was examined using Mann–Whitney U tests. A chi-square test of independence was also used to assess for differences in the level of cueing between groups for the CST task. Regression analyses were conducted to further understand the relationship between the CST variables and cognitive measures. Finally, regression analyses were used to evaluate whether CST performance accounted for a significant amount of variance in functional status when controlling for cognition. With the exception of Pearson correlation analyses, all analyses used a Type I error rate of p < 0.05 (All participants with SCI reported ongoing cognitive problems since their injury; however, given the lesser established connection between SCI and cognitive impairment, all analyses involving the neurologic group were also ran without the three participants with SCI. The pattern of data did not differ except where noted.). Table 4. Differences between groups on Community Shopping Task (CST) performance Neurologic Group (n = 34) Control Group (n = 34) Cohen’s d TBI (n = 9) Stroke (n = 6) MS (n = 16) SCI (n = 3) M (SD) M (SD) M (SD) M (SD) M (SD) M (SD) CST Total Score 15.15 5.23 1.03* 14.00 22.00 12.00 21.67 (12.95) (4.29) (14.86) (17.84) (8.52) (16.01) CST Preparation 6.82 2.97 0.84* 7.44 10.50 5.56 4.33 (5.73) (3.00) (7.80) (6.09) (4.34) (0.58) CST Execution 8.32 2.26 0.88* 6.56 11.50 6.44 17.33 (9.30) (2.73) (7.73) (13.97) (5.74) (16.04) CST Total Time (s) 942.06 591.18 1.33* 1037.78 900.00 907.50 923.33 (331.29) (171.71) (327.02) (377.57) (349.77) (229.42) Neurologic Group (n = 34) Control Group (n = 34) Cohen’s d TBI (n = 9) Stroke (n = 6) MS (n = 16) SCI (n = 3) M (SD) M (SD) M (SD) M (SD) M (SD) M (SD) CST Total Score 15.15 5.23 1.03* 14.00 22.00 12.00 21.67 (12.95) (4.29) (14.86) (17.84) (8.52) (16.01) CST Preparation 6.82 2.97 0.84* 7.44 10.50 5.56 4.33 (5.73) (3.00) (7.80) (6.09) (4.34) (0.58) CST Execution 8.32 2.26 0.88* 6.56 11.50 6.44 17.33 (9.30) (2.73) (7.73) (13.97) (5.74) (16.04) CST Total Time (s) 942.06 591.18 1.33* 1037.78 900.00 907.50 923.33 (331.29) (171.71) (327.02) (377.57) (349.77) (229.42) Note: *p < 0.01. Table 4. Differences between groups on Community Shopping Task (CST) performance Neurologic Group (n = 34) Control Group (n = 34) Cohen’s d TBI (n = 9) Stroke (n = 6) MS (n = 16) SCI (n = 3) M (SD) M (SD) M (SD) M (SD) M (SD) M (SD) CST Total Score 15.15 5.23 1.03* 14.00 22.00 12.00 21.67 (12.95) (4.29) (14.86) (17.84) (8.52) (16.01) CST Preparation 6.82 2.97 0.84* 7.44 10.50 5.56 4.33 (5.73) (3.00) (7.80) (6.09) (4.34) (0.58) CST Execution 8.32 2.26 0.88* 6.56 11.50 6.44 17.33 (9.30) (2.73) (7.73) (13.97) (5.74) (16.04) CST Total Time (s) 942.06 591.18 1.33* 1037.78 900.00 907.50 923.33 (331.29) (171.71) (327.02) (377.57) (349.77) (229.42) Neurologic Group (n = 34) Control Group (n = 34) Cohen’s d TBI (n = 9) Stroke (n = 6) MS (n = 16) SCI (n = 3) M (SD) M (SD) M (SD) M (SD) M (SD) M (SD) CST Total Score 15.15 5.23 1.03* 14.00 22.00 12.00 21.67 (12.95) (4.29) (14.86) (17.84) (8.52) (16.01) CST Preparation 6.82 2.97 0.84* 7.44 10.50 5.56 4.33 (5.73) (3.00) (7.80) (6.09) (4.34) (0.58) CST Execution 8.32 2.26 0.88* 6.56 11.50 6.44 17.33 (9.30) (2.73) (7.73) (13.97) (5.74) (16.04) CST Total Time (s) 942.06 591.18 1.33* 1037.78 900.00 907.50 923.33 (331.29) (171.71) (327.02) (377.57) (349.77) (229.42) Note: *p < 0.01. Because the CST is not a standardized measure, correlational analyses were used to examine whether age, gender, or education was associated with performance on the CST for either the neurologic or control group. Results revealed that demographic variables were not significantly related to CST performance (i.e., CST total score, preparation score, execution score, and CST total time; rs < 0.32) for either group; therefore, no demographic variables were controlled for in the analyses. Between and Within Group Performance As can be seen in Table 1, despite being well matched on demographic characteristics (i.e., age, education, gender, premorbid ability) the neurologic group performed significantly more poorly than the control group on all measures of cognition, ts > 2.21, ps < 0.03, Cohen’s d range = 0.54–1.28. Table 1 also presents demographic and cognitive performance data for participants as a function of neurologic condition. With few exceptions the cognitive scores across neurologic subgroups fell within one standard deviation of each other. CST Performance Independent samples t-tests were then used to analyze group differences on the CST (Table 4). Results revealed that participants with neurologic conditions required significantly more cues compared to the control group to complete the CST; t(66) = 4.23, p < 0.01, d = 1.03, and this was true for both the CST preparation t(66) = 3.47, p < 0.01, d = 0.84, and CST execution subsections; t(66) = 3.65, p < 0.01, d = 0.88. Participants with neurologic conditions also took significantly longer to complete the CST compared to the control group; t(66) = 5.48, p < 0.01, d = 1.33. Furthermore, there appeared to be just as much variability within each neurologic condition as across the neurologic conditions on all of the CST variables (Table 4), with the exception that participant’s with SCI (n = 3) appeared to need less assistance on the CST preparation subsection compared to the CST execution subsection. To determine whether the CST could accurately differentiate between the control and neurologic groups, ROC curve analyses were conducted (Tape, n.d.). Results revealed a significant area under the curve for CST total score; 0.81, p < 0.01 (76.5% sensitivity and 76.5% specificity), CST preparation; 0.73, p < 0.01 (59.8% sensitivity and 79.4% specificity), CST execution; 0.75, p < 0.01 (61.8% sensitivity and 76.5% specificity), and CST total time; 0.84 (70.6% sensitivity and 82.4% specificity). The ability to differentiate between groups using the CST total score and CST total time fell in the good range, while using the CST preparation and CST execution scores fell in the fair range. Of note, follow-up exploratory analyses revealed that the cognitive measures were unable to discriminate between groups (ROC curve <0.36), with sensitivity ranging from 18% to 40% and specificity ranging from 34% to 62%. Tables 5 and 6 show the maximum level of cues given to participants in both the neurologic and control groups for each task component of the preparation and execution subsections of the CST. Exploratory Mann–Whitney U tests (no adjustment was made to alpha level) were used to evaluate for significant differences between groups in the total amount of cues given for each individual task component. In general, the neurologic and control groups often needed cueing on similar task components. However, participants with neurologic conditions needed significantly more cues compared to the control group on the following task components of the CST preparation subsection: begins task, looks up the recipe, refers to the list of items at home, begins writing down items, and takes wallet with them. For the CST execution subsection, participants with neurologic conditions needed significantly more cues compared to the control group for the following task components: chooses a shopping instrument, gets noodles, chooses chocolate dessert, sets grocery items on the counter, gets grocery bag and has wallet, uses stop light to cross the street, and gives the bus driver the bus pass. Table 5. Maximum level of cues given for each preparation task component to the neurologic and control participants Cue Level Neurologic Group (n = 34) T Control Group (n = 34) T 1 2 3 4 5 6 1 2 3 4 5 6 Task Components  Begins task* 1 3 0 1 0 0 5 0 0 0 0 0 0 0  Looks up recipe** 6 2 4 1 1 0 14 1 1 1 0 0 0 3  Refers to list of items they have at home* 0 1 2 1 0 0 4 0 0 0 0 0 0 0  Begins writing down items* 2 1 0 2 0 0 5 0 0 0 0 0 0 0  Writes down paprika 0 2 0 0 0 0 2 0 0 2 0 0 0 2  Writes down pepper 1 0 0 0 0 0 1 0 0 0 0 0 0 0  Writes down onions 0 5 3 2 0 0 10 0 2 3 1 0 0 6  Writes down garlic 1 4 0 0 0 0 5 0 1 0 0 0 0 1  Writes down 1 can whole tomatoes 1 2 0 0 0 0 3 0 0 0 0 0 0 0  Writes down noodles 2 0 0 1 0 0 3 0 0 0 0 0 0 0  Writes down items not needed 0 7 3 1 0 0 11 0 10 1 0 0 0 11  Writes down dessert 0 11 1 5 0 0 17 1 12 0 1 0 0 14  Writes down stamp book 0 11 1 2 0 0 14 0 7 0 1 0 0 8  Indicates they are ready to shop 0 0 0 0 0 0 0 0 0 0 0 0 0 0  Takes wallet and list with them* 0 3 1 0 0 0 4 0 0 0 0 0 0 0 Totals 14 52 15 16 1 0 98 2 33 7 3 0 0 45 Cue Level Neurologic Group (n = 34) T Control Group (n = 34) T 1 2 3 4 5 6 1 2 3 4 5 6 Task Components  Begins task* 1 3 0 1 0 0 5 0 0 0 0 0 0 0  Looks up recipe** 6 2 4 1 1 0 14 1 1 1 0 0 0 3  Refers to list of items they have at home* 0 1 2 1 0 0 4 0 0 0 0 0 0 0  Begins writing down items* 2 1 0 2 0 0 5 0 0 0 0 0 0 0  Writes down paprika 0 2 0 0 0 0 2 0 0 2 0 0 0 2  Writes down pepper 1 0 0 0 0 0 1 0 0 0 0 0 0 0  Writes down onions 0 5 3 2 0 0 10 0 2 3 1 0 0 6  Writes down garlic 1 4 0 0 0 0 5 0 1 0 0 0 0 1  Writes down 1 can whole tomatoes 1 2 0 0 0 0 3 0 0 0 0 0 0 0  Writes down noodles 2 0 0 1 0 0 3 0 0 0 0 0 0 0  Writes down items not needed 0 7 3 1 0 0 11 0 10 1 0 0 0 11  Writes down dessert 0 11 1 5 0 0 17 1 12 0 1 0 0 14  Writes down stamp book 0 11 1 2 0 0 14 0 7 0 1 0 0 8  Indicates they are ready to shop 0 0 0 0 0 0 0 0 0 0 0 0 0 0  Takes wallet and list with them* 0 3 1 0 0 0 4 0 0 0 0 0 0 0 Totals 14 52 15 16 1 0 98 2 33 7 3 0 0 45 Note: Cue levels: 1 = Self-Corrected or Slowed Performance, 2 = Indirect Verbal Guidance, 3 = Gestural Guidance, 4 = Direct Verbal Guidance, 5 = Physical Assistance, 6 = Did the task for the participant, T = total. *p < 0.05 difference between groups on total cues of individual task components. **p < 0.01 difference between groups on total cues of individual task components. Table 5. Maximum level of cues given for each preparation task component to the neurologic and control participants Cue Level Neurologic Group (n = 34) T Control Group (n = 34) T 1 2 3 4 5 6 1 2 3 4 5 6 Task Components  Begins task* 1 3 0 1 0 0 5 0 0 0 0 0 0 0  Looks up recipe** 6 2 4 1 1 0 14 1 1 1 0 0 0 3  Refers to list of items they have at home* 0 1 2 1 0 0 4 0 0 0 0 0 0 0  Begins writing down items* 2 1 0 2 0 0 5 0 0 0 0 0 0 0  Writes down paprika 0 2 0 0 0 0 2 0 0 2 0 0 0 2  Writes down pepper 1 0 0 0 0 0 1 0 0 0 0 0 0 0  Writes down onions 0 5 3 2 0 0 10 0 2 3 1 0 0 6  Writes down garlic 1 4 0 0 0 0 5 0 1 0 0 0 0 1  Writes down 1 can whole tomatoes 1 2 0 0 0 0 3 0 0 0 0 0 0 0  Writes down noodles 2 0 0 1 0 0 3 0 0 0 0 0 0 0  Writes down items not needed 0 7 3 1 0 0 11 0 10 1 0 0 0 11  Writes down dessert 0 11 1 5 0 0 17 1 12 0 1 0 0 14  Writes down stamp book 0 11 1 2 0 0 14 0 7 0 1 0 0 8  Indicates they are ready to shop 0 0 0 0 0 0 0 0 0 0 0 0 0 0  Takes wallet and list with them* 0 3 1 0 0 0 4 0 0 0 0 0 0 0 Totals 14 52 15 16 1 0 98 2 33 7 3 0 0 45 Cue Level Neurologic Group (n = 34) T Control Group (n = 34) T 1 2 3 4 5 6 1 2 3 4 5 6 Task Components  Begins task* 1 3 0 1 0 0 5 0 0 0 0 0 0 0  Looks up recipe** 6 2 4 1 1 0 14 1 1 1 0 0 0 3  Refers to list of items they have at home* 0 1 2 1 0 0 4 0 0 0 0 0 0 0  Begins writing down items* 2 1 0 2 0 0 5 0 0 0 0 0 0 0  Writes down paprika 0 2 0 0 0 0 2 0 0 2 0 0 0 2  Writes down pepper 1 0 0 0 0 0 1 0 0 0 0 0 0 0  Writes down onions 0 5 3 2 0 0 10 0 2 3 1 0 0 6  Writes down garlic 1 4 0 0 0 0 5 0 1 0 0 0 0 1  Writes down 1 can whole tomatoes 1 2 0 0 0 0 3 0 0 0 0 0 0 0  Writes down noodles 2 0 0 1 0 0 3 0 0 0 0 0 0 0  Writes down items not needed 0 7 3 1 0 0 11 0 10 1 0 0 0 11  Writes down dessert 0 11 1 5 0 0 17 1 12 0 1 0 0 14  Writes down stamp book 0 11 1 2 0 0 14 0 7 0 1 0 0 8  Indicates they are ready to shop 0 0 0 0 0 0 0 0 0 0 0 0 0 0  Takes wallet and list with them* 0 3 1 0 0 0 4 0 0 0 0 0 0 0 Totals 14 52 15 16 1 0 98 2 33 7 3 0 0 45 Note: Cue levels: 1 = Self-Corrected or Slowed Performance, 2 = Indirect Verbal Guidance, 3 = Gestural Guidance, 4 = Direct Verbal Guidance, 5 = Physical Assistance, 6 = Did the task for the participant, T = total. *p < 0.05 difference between groups on total cues of individual task components. **p < 0.01 difference between groups on total cues of individual task components. Table 6. Maximum level of cues given for each execution task component to the neurologic and control participants Cue Level Neurologic Group (n = 34) T Control Group (n = 34) T 1 2 3 4 5 6 1 2 3 4 5 6 Task Components  Begins task 0 1 1 1 0 0 3 0 0 0 0 0 0 0  Chooses a shopping instrument* 0 1 0 2 0 1 4 0 0 0 0 0 0 0  Consults grocery list 0 0 1 1 0 0 2 0 0 0 0 0 0 0  Begins to gather items on the grocery list 1 1 0 0 0 0 2 1 0 0 0 0 0 1  Gets paprika 0 2 0 0 0 0 2 0 1 0 0 0 0 1  Gets pepper 0 0 3 0 0 0 3 0 2 0 0 0 0 2  Gets 3 onions 0 2 0 0 0 0 2 0 1 0 0 0 0 1  Gets garlic 0 2 0 0 0 0 2 0 2 0 0 0 0 2  Gets 1 can whole tomatoes 0 1 0 0 0 0 1 0 1 0 0 0 0 1  Gets noodles* 5 0 0 2 0 0 7 1 0 0 0 0 0 1  Chooses a chocolate dessert* 3 5 2 1 0 1 12 2 0 1 1 0 0 4  Gets children’s ibuprofen 5 3 7 2 0 0 17 4 5 3 0 0 0 12  Gets items not needed 0 1 0 1 0 0 2 0 2 1 0 0 0 3  Brings items to cashier 0 1 0 0 0 0 1 0 0 0 0 0 0 0  Sets items on counter* 1 2 0 3 0 2 8 0 1 0 0 0 0 1  Asks cashier for stamps 0 1 1 2 0 0 4 0 2 0 0 0 0 2  Retrieves cash from wallet 1 1 0 0 0 0 2 0 1 0 0 0 0 1  Counts out cash 0 2 0 0 1 0 3 0 0 0 1 0 0 1  Pays cashier 1 1 0 0 0 0 2 0 0 0 0 0 0 0  Picks up grocery bag and has wallet* 0 1 2 0 0 1 4 0 0 0 0 0 0 0  Moves towards the bus and leaves cart 0 1 1 1 0 0 3 0 0 0 0 0 0 0  Uses a stop light to cross street** 2 5 1 0 0 0 8 0 0 0 0 0 0 0  Gives the bus driver the bus pass** 0 11 3 2 0 0 16 0 5 0 0 0 0 5 Totals 19 45 22 18 1 4 109 8 23 5 2 0 0 38 Cue Level Neurologic Group (n = 34) T Control Group (n = 34) T 1 2 3 4 5 6 1 2 3 4 5 6 Task Components  Begins task 0 1 1 1 0 0 3 0 0 0 0 0 0 0  Chooses a shopping instrument* 0 1 0 2 0 1 4 0 0 0 0 0 0 0  Consults grocery list 0 0 1 1 0 0 2 0 0 0 0 0 0 0  Begins to gather items on the grocery list 1 1 0 0 0 0 2 1 0 0 0 0 0 1  Gets paprika 0 2 0 0 0 0 2 0 1 0 0 0 0 1  Gets pepper 0 0 3 0 0 0 3 0 2 0 0 0 0 2  Gets 3 onions 0 2 0 0 0 0 2 0 1 0 0 0 0 1  Gets garlic 0 2 0 0 0 0 2 0 2 0 0 0 0 2  Gets 1 can whole tomatoes 0 1 0 0 0 0 1 0 1 0 0 0 0 1  Gets noodles* 5 0 0 2 0 0 7 1 0 0 0 0 0 1  Chooses a chocolate dessert* 3 5 2 1 0 1 12 2 0 1 1 0 0 4  Gets children’s ibuprofen 5 3 7 2 0 0 17 4 5 3 0 0 0 12  Gets items not needed 0 1 0 1 0 0 2 0 2 1 0 0 0 3  Brings items to cashier 0 1 0 0 0 0 1 0 0 0 0 0 0 0  Sets items on counter* 1 2 0 3 0 2 8 0 1 0 0 0 0 1  Asks cashier for stamps 0 1 1 2 0 0 4 0 2 0 0 0 0 2  Retrieves cash from wallet 1 1 0 0 0 0 2 0 1 0 0 0 0 1  Counts out cash 0 2 0 0 1 0 3 0 0 0 1 0 0 1  Pays cashier 1 1 0 0 0 0 2 0 0 0 0 0 0 0  Picks up grocery bag and has wallet* 0 1 2 0 0 1 4 0 0 0 0 0 0 0  Moves towards the bus and leaves cart 0 1 1 1 0 0 3 0 0 0 0 0 0 0  Uses a stop light to cross street** 2 5 1 0 0 0 8 0 0 0 0 0 0 0  Gives the bus driver the bus pass** 0 11 3 2 0 0 16 0 5 0 0 0 0 5 Totals 19 45 22 18 1 4 109 8 23 5 2 0 0 38 Note: Cue levels: 1 = Self-Corrected or Slowed Performance, 2 = Indirect Verbal Guidance, 3 = Gestural Guidance, 4 = Direct Verbal Guidance, 5 = Physical Assistance, 6 = Did the task for the participant, T = Total. *p < 0.05 difference between groups on total cues of individual task components. **p < 0.01 difference between groups on total cues of individual task components. Table 6. Maximum level of cues given for each execution task component to the neurologic and control participants Cue Level Neurologic Group (n = 34) T Control Group (n = 34) T 1 2 3 4 5 6 1 2 3 4 5 6 Task Components  Begins task 0 1 1 1 0 0 3 0 0 0 0 0 0 0  Chooses a shopping instrument* 0 1 0 2 0 1 4 0 0 0 0 0 0 0  Consults grocery list 0 0 1 1 0 0 2 0 0 0 0 0 0 0  Begins to gather items on the grocery list 1 1 0 0 0 0 2 1 0 0 0 0 0 1  Gets paprika 0 2 0 0 0 0 2 0 1 0 0 0 0 1  Gets pepper 0 0 3 0 0 0 3 0 2 0 0 0 0 2  Gets 3 onions 0 2 0 0 0 0 2 0 1 0 0 0 0 1  Gets garlic 0 2 0 0 0 0 2 0 2 0 0 0 0 2  Gets 1 can whole tomatoes 0 1 0 0 0 0 1 0 1 0 0 0 0 1  Gets noodles* 5 0 0 2 0 0 7 1 0 0 0 0 0 1  Chooses a chocolate dessert* 3 5 2 1 0 1 12 2 0 1 1 0 0 4  Gets children’s ibuprofen 5 3 7 2 0 0 17 4 5 3 0 0 0 12  Gets items not needed 0 1 0 1 0 0 2 0 2 1 0 0 0 3  Brings items to cashier 0 1 0 0 0 0 1 0 0 0 0 0 0 0  Sets items on counter* 1 2 0 3 0 2 8 0 1 0 0 0 0 1  Asks cashier for stamps 0 1 1 2 0 0 4 0 2 0 0 0 0 2  Retrieves cash from wallet 1 1 0 0 0 0 2 0 1 0 0 0 0 1  Counts out cash 0 2 0 0 1 0 3 0 0 0 1 0 0 1  Pays cashier 1 1 0 0 0 0 2 0 0 0 0 0 0 0  Picks up grocery bag and has wallet* 0 1 2 0 0 1 4 0 0 0 0 0 0 0  Moves towards the bus and leaves cart 0 1 1 1 0 0 3 0 0 0 0 0 0 0  Uses a stop light to cross street** 2 5 1 0 0 0 8 0 0 0 0 0 0 0  Gives the bus driver the bus pass** 0 11 3 2 0 0 16 0 5 0 0 0 0 5 Totals 19 45 22 18 1 4 109 8 23 5 2 0 0 38 Cue Level Neurologic Group (n = 34) T Control Group (n = 34) T 1 2 3 4 5 6 1 2 3 4 5 6 Task Components  Begins task 0 1 1 1 0 0 3 0 0 0 0 0 0 0  Chooses a shopping instrument* 0 1 0 2 0 1 4 0 0 0 0 0 0 0  Consults grocery list 0 0 1 1 0 0 2 0 0 0 0 0 0 0  Begins to gather items on the grocery list 1 1 0 0 0 0 2 1 0 0 0 0 0 1  Gets paprika 0 2 0 0 0 0 2 0 1 0 0 0 0 1  Gets pepper 0 0 3 0 0 0 3 0 2 0 0 0 0 2  Gets 3 onions 0 2 0 0 0 0 2 0 1 0 0 0 0 1  Gets garlic 0 2 0 0 0 0 2 0 2 0 0 0 0 2  Gets 1 can whole tomatoes 0 1 0 0 0 0 1 0 1 0 0 0 0 1  Gets noodles* 5 0 0 2 0 0 7 1 0 0 0 0 0 1  Chooses a chocolate dessert* 3 5 2 1 0 1 12 2 0 1 1 0 0 4  Gets children’s ibuprofen 5 3 7 2 0 0 17 4 5 3 0 0 0 12  Gets items not needed 0 1 0 1 0 0 2 0 2 1 0 0 0 3  Brings items to cashier 0 1 0 0 0 0 1 0 0 0 0 0 0 0  Sets items on counter* 1 2 0 3 0 2 8 0 1 0 0 0 0 1  Asks cashier for stamps 0 1 1 2 0 0 4 0 2 0 0 0 0 2  Retrieves cash from wallet 1 1 0 0 0 0 2 0 1 0 0 0 0 1  Counts out cash 0 2 0 0 1 0 3 0 0 0 1 0 0 1  Pays cashier 1 1 0 0 0 0 2 0 0 0 0 0 0 0  Picks up grocery bag and has wallet* 0 1 2 0 0 1 4 0 0 0 0 0 0 0  Moves towards the bus and leaves cart 0 1 1 1 0 0 3 0 0 0 0 0 0 0  Uses a stop light to cross street** 2 5 1 0 0 0 8 0 0 0 0 0 0 0  Gives the bus driver the bus pass** 0 11 3 2 0 0 16 0 5 0 0 0 0 5 Totals 19 45 22 18 1 4 109 8 23 5 2 0 0 38 Note: Cue levels: 1 = Self-Corrected or Slowed Performance, 2 = Indirect Verbal Guidance, 3 = Gestural Guidance, 4 = Direct Verbal Guidance, 5 = Physical Assistance, 6 = Did the task for the participant, T = Total. *p < 0.05 difference between groups on total cues of individual task components. **p < 0.01 difference between groups on total cues of individual task components. A chi-square test of independence also revealed that participants with neurologic conditions required greater levels of cueing to accurately complete the CST compared to the control group, χ2 (5, N = 68) = 12.96, p = .024 (Table 7). To evaluate individual cell contributions to the chi-square results, the adjusted residuals method was employed (MacDonald & Gardner, 2000; Sharpe, 2015). A Bonferroni correction was used to maintain an appropriate Type I error rate (MacDonald & Gardner, 2000). There are 12 cells in the 2 × 6 contingency table; therefore, the alpha was set at approximately 0.004 (0.05/12), which corresponds to a critical value of ±2.8. The findings indicated that the neurologic group received a lower proportion of indirect cues (46.85%) compared to the control participants (67.47%; adjusted residual = 3.18). The difference between the proportions of direct cues given to each group approached significance (adjusted residual = 2.35) with participants in the neurologic group needing more direct cues (16.43%) compared to participants in the control group (6.02%). Furthermore, only participants in the neurologic group required physical assistance or needed to have the task component completed for them. Table 7. Percentage of cue level given out of total cues administered by group Self-Corrected/ Slow Indirect Verbal Guidance Gestural Guidance Direct Verbal Guidance Physical Assistance Did the task for the Participant Neurologic Group (n = 34) 15.94% 46.86% 17.87% 16.43% 2.42% 1.93% Control Group (n = 34) 12.05% 67.47% 14.46% 6.02% 0% 0% Self-Corrected/ Slow Indirect Verbal Guidance Gestural Guidance Direct Verbal Guidance Physical Assistance Did the task for the Participant Neurologic Group (n = 34) 15.94% 46.86% 17.87% 16.43% 2.42% 1.93% Control Group (n = 34) 12.05% 67.47% 14.46% 6.02% 0% 0% Table 7. Percentage of cue level given out of total cues administered by group Self-Corrected/ Slow Indirect Verbal Guidance Gestural Guidance Direct Verbal Guidance Physical Assistance Did the task for the Participant Neurologic Group (n = 34) 15.94% 46.86% 17.87% 16.43% 2.42% 1.93% Control Group (n = 34) 12.05% 67.47% 14.46% 6.02% 0% 0% Self-Corrected/ Slow Indirect Verbal Guidance Gestural Guidance Direct Verbal Guidance Physical Assistance Did the task for the Participant Neurologic Group (n = 34) 15.94% 46.86% 17.87% 16.43% 2.42% 1.93% Control Group (n = 34) 12.05% 67.47% 14.46% 6.02% 0% 0% Cognition and the CST For the control group, the CST total score was significantly correlated with the CST preparation score; r = 0.77, p < 0.01, and the CST execution score; r = 0.72, p < 0.01. The CST execution and CST preparation scores were not significantly correlated with one another (r = 0.12, p = 0.52), indicating that they may be assessing different aspects of performance. CST total time was not significantly correlated with any of the other CST variables for the control group. For the neurologic group, all CST variables were significantly correlated with one another (rs > 0.39). Correlations between the CST variables and predictor variables are presented in Table 8. Table 8. Correlations between cognitive variables and Community Shopping Task (CST) variablesa Neurologic Group (n = 34) Control Group (n = 34) Total CST Prep Score Exec Score CST Time Total CST Prep Score Exec Score CST Time RBANS Total Score −0.64* −0.56* −0.56* −0.53* −0.44* −0.23 −0.43* −0.18 Immediate Memory −0.71* −0.60* −0.62* −0.50* −0.12 −0.06 −0.12 −0.03 Visuospatial/Constructional skills −0.033 −0.37 −0.24 −0.29 −0.35 −0.18 −0.35 −0.06 Language −0.61* −0.47* −0.56* −0.49* −0.20 −0.07 −0.23 −0.38 Attention −0.61* −0.50* −0.55* −0.60* −0.32 −0.24 −0.25 −0.15 Delayed Memory −0.33 −0.29 −0.33 −0.29 −0.07 0.03 −0.14 0.11 DKEFS Design Fluency −0.44* −0.26 −0.46* −0.26 −0.03 0.09 −0.15 −0.21 Neurologic Group (n = 34) Control Group (n = 34) Total CST Prep Score Exec Score CST Time Total CST Prep Score Exec Score CST Time RBANS Total Score −0.64* −0.56* −0.56* −0.53* −0.44* −0.23 −0.43* −0.18 Immediate Memory −0.71* −0.60* −0.62* −0.50* −0.12 −0.06 −0.12 −0.03 Visuospatial/Constructional skills −0.033 −0.37 −0.24 −0.29 −0.35 −0.18 −0.35 −0.06 Language −0.61* −0.47* −0.56* −0.49* −0.20 −0.07 −0.23 −0.38 Attention −0.61* −0.50* −0.55* −0.60* −0.32 −0.24 −0.25 −0.15 Delayed Memory −0.33 −0.29 −0.33 −0.29 −0.07 0.03 −0.14 0.11 DKEFS Design Fluency −0.44* −0.26 −0.46* −0.26 −0.03 0.09 −0.15 −0.21 Note: *p < 0.01 aWhen these analyses were ran excluding participants with SCI from the neurologic group, all significant correlations remained significant. Additional significant correlations were also found between the CST execution score and visuospatial/constructional skills (r = −0.43, p < 0.05) and delayed memory (r = −0.48, p < 0.01), as well as CST total score and visuospatial/constructional skills (r = −0.43, p < 0.05) and delayed memory (r =−0.41, p < 0.05). Table 8. Correlations between cognitive variables and Community Shopping Task (CST) variablesa Neurologic Group (n = 34) Control Group (n = 34) Total CST Prep Score Exec Score CST Time Total CST Prep Score Exec Score CST Time RBANS Total Score −0.64* −0.56* −0.56* −0.53* −0.44* −0.23 −0.43* −0.18 Immediate Memory −0.71* −0.60* −0.62* −0.50* −0.12 −0.06 −0.12 −0.03 Visuospatial/Constructional skills −0.033 −0.37 −0.24 −0.29 −0.35 −0.18 −0.35 −0.06 Language −0.61* −0.47* −0.56* −0.49* −0.20 −0.07 −0.23 −0.38 Attention −0.61* −0.50* −0.55* −0.60* −0.32 −0.24 −0.25 −0.15 Delayed Memory −0.33 −0.29 −0.33 −0.29 −0.07 0.03 −0.14 0.11 DKEFS Design Fluency −0.44* −0.26 −0.46* −0.26 −0.03 0.09 −0.15 −0.21 Neurologic Group (n = 34) Control Group (n = 34) Total CST Prep Score Exec Score CST Time Total CST Prep Score Exec Score CST Time RBANS Total Score −0.64* −0.56* −0.56* −0.53* −0.44* −0.23 −0.43* −0.18 Immediate Memory −0.71* −0.60* −0.62* −0.50* −0.12 −0.06 −0.12 −0.03 Visuospatial/Constructional skills −0.033 −0.37 −0.24 −0.29 −0.35 −0.18 −0.35 −0.06 Language −0.61* −0.47* −0.56* −0.49* −0.20 −0.07 −0.23 −0.38 Attention −0.61* −0.50* −0.55* −0.60* −0.32 −0.24 −0.25 −0.15 Delayed Memory −0.33 −0.29 −0.33 −0.29 −0.07 0.03 −0.14 0.11 DKEFS Design Fluency −0.44* −0.26 −0.46* −0.26 −0.03 0.09 −0.15 −0.21 Note: *p < 0.01 aWhen these analyses were ran excluding participants with SCI from the neurologic group, all significant correlations remained significant. Additional significant correlations were also found between the CST execution score and visuospatial/constructional skills (r = −0.43, p < 0.05) and delayed memory (r = −0.48, p < 0.01), as well as CST total score and visuospatial/constructional skills (r = −0.43, p < 0.05) and delayed memory (r =−0.41, p < 0.05). To understand whether the cognitive variables predicted CST performance, hierarchical regressions were run for the control and neurologic groups separately. Due to limited sample size, regression models used three or less predictor variables so as not to compromise statistical power or lead to possible spurious findings. Thus, we first examined how the RBANS total score and DKEFS design fluency predicted the CST total score. As seen in Table 9, regression results revealed that the RBANS total score and DKEFS design fluency accounted for a significant amount of variance in CST total score for both the control group; F(2, 31) = 3.69, p < 0.05, R2 = 0.20, and the neurologic group, F(2, 31) = 12.82, p < 0.01, R2 = 0.47, with the RBANS total score emerging as a significant predictor in both groups. Table 9. Summary of regression analyses with beta coefficients for the neurologic and control groups, and the cognitive predictors of CST performancea CST Total Score CST Preparation Score CST Execution Score CST Total Time Control Group  Regression Model   RBANS Total Score −0.46** −0.27 −0.42** −0.13   DKEFS Design Fluency 0.09 0.16 −0.04 −0.18    R2 0.20 0.02 0.14 −0.01    F for R2 3.69* 1.26 3.52* 0.96 Neurologic Group  Regression Model   RBANS Total Score −0.53** −0.54** −0.42** −0.50**   DKEFS Design Fluency −0.26 −0.05 −0.33* −0.07    R2 0.47 0.32 0.36 0.24    F for R2 12.82** 6.78** 9.66** 5.77**  Follow-up Regression Model   Immediate Memory −0.46** −0.45* −0.40* −0.21   Language −0.23 −0.10 −0.13 −0.18   Attention −0.27 −0.24 −0.20 −0.41*    R2 0.62 0.45 0.49 0.44    F for R2 17.82** 7.64** 8.33** 7.39** CST Total Score CST Preparation Score CST Execution Score CST Total Time Control Group  Regression Model   RBANS Total Score −0.46** −0.27 −0.42** −0.13   DKEFS Design Fluency 0.09 0.16 −0.04 −0.18    R2 0.20 0.02 0.14 −0.01    F for R2 3.69* 1.26 3.52* 0.96 Neurologic Group  Regression Model   RBANS Total Score −0.53** −0.54** −0.42** −0.50**   DKEFS Design Fluency −0.26 −0.05 −0.33* −0.07    R2 0.47 0.32 0.36 0.24    F for R2 12.82** 6.78** 9.66** 5.77**  Follow-up Regression Model   Immediate Memory −0.46** −0.45* −0.40* −0.21   Language −0.23 −0.10 −0.13 −0.18   Attention −0.27 −0.24 −0.20 −0.41*    R2 0.62 0.45 0.49 0.44    F for R2 17.82** 7.64** 8.33** 7.39** Note: **p < 0.01 *p < 0.05. aWhen analyses were ran excluding participants with SCI from the neurologic group, all results remained the same with the exception that DKEFS Design Fluency was no longer a unique predictor of the CST execution score. Table 9. Summary of regression analyses with beta coefficients for the neurologic and control groups, and the cognitive predictors of CST performancea CST Total Score CST Preparation Score CST Execution Score CST Total Time Control Group  Regression Model   RBANS Total Score −0.46** −0.27 −0.42** −0.13   DKEFS Design Fluency 0.09 0.16 −0.04 −0.18    R2 0.20 0.02 0.14 −0.01    F for R2 3.69* 1.26 3.52* 0.96 Neurologic Group  Regression Model   RBANS Total Score −0.53** −0.54** −0.42** −0.50**   DKEFS Design Fluency −0.26 −0.05 −0.33* −0.07    R2 0.47 0.32 0.36 0.24    F for R2 12.82** 6.78** 9.66** 5.77**  Follow-up Regression Model   Immediate Memory −0.46** −0.45* −0.40* −0.21   Language −0.23 −0.10 −0.13 −0.18   Attention −0.27 −0.24 −0.20 −0.41*    R2 0.62 0.45 0.49 0.44    F for R2 17.82** 7.64** 8.33** 7.39** CST Total Score CST Preparation Score CST Execution Score CST Total Time Control Group  Regression Model   RBANS Total Score −0.46** −0.27 −0.42** −0.13   DKEFS Design Fluency 0.09 0.16 −0.04 −0.18    R2 0.20 0.02 0.14 −0.01    F for R2 3.69* 1.26 3.52* 0.96 Neurologic Group  Regression Model   RBANS Total Score −0.53** −0.54** −0.42** −0.50**   DKEFS Design Fluency −0.26 −0.05 −0.33* −0.07    R2 0.47 0.32 0.36 0.24    F for R2 12.82** 6.78** 9.66** 5.77**  Follow-up Regression Model   Immediate Memory −0.46** −0.45* −0.40* −0.21   Language −0.23 −0.10 −0.13 −0.18   Attention −0.27 −0.24 −0.20 −0.41*    R2 0.62 0.45 0.49 0.44    F for R2 17.82** 7.64** 8.33** 7.39** Note: **p < 0.01 *p < 0.05. aWhen analyses were ran excluding participants with SCI from the neurologic group, all results remained the same with the exception that DKEFS Design Fluency was no longer a unique predictor of the CST execution score. Additional exploratory regressions were then conducted separately for the CST preparation, CST execution, and CST total time scores. As seen in Table 9, RBANS total score and DKEFS design fluency accounted for a significant amount of variance in the CST execution score for the control group; F(2, 31) = 3.52, p < 0.05, R2 = 0.14, with the RBANS total score emerging as a significant predictor. The regression analyses for the CST preparation and CST total time scores were not significant (R2s < 0.02). For the neurologic group, results revealed that the RBANS total score and DKEFS design fluency accounted for a significant amount of variance in the CST preparation score; F(2, 31) = 6.78, p < 0.01, R2 = 0.32, CST execution score; F(2, 31) = 9.66, p < 0.01, R2 = 0.36 (When regression analyses of the cognitive variables predicting CST measures were ran excluding participants with SCI from the neurologic group, all results remained the same with the exception that DKEFS Design Fluency was no longer a unique predictor of the CST execution score.), and CST total time; F(3, 30) = 7.39, p < 0.01, R2 = 0.44. The RBANS total score was a significant predictor for all three CST measures, while DKEFS design fluency emerged as an additional significant predictor only for the CST execution score. In order to understand which RBANS indices were most predictive of CST performance, additional exploratory regression analyses were run using the RBANS scores that were significantly correlated with CST performance for the neurologic group (i.e., immediate memory, language, and attention). As seen in Table 9, results revealed that immediate memory, language, and attention accounted for a significant amount of variance in CST total score; F(3, 30) = 17.82, p < 0.01, R2 = 0.62; CST preparation score; F(3, 30) = 7.63, p < 0.01, R2 = 0.45; CST execution score; F(3, 30) = 8.33, p < 0.01, R2 = 0.49; and CST total time; F(3, 30) = 7.39, p < 0.01, R2 = 0.44. Immediate memory was a significant predictor of CST total score, CST preparation score, and CST execution score. In contrast, attention was a significant predictor of CST total time (Table 9). For the control group, follow-up regression analyses revealed that immediate memory, language and attention did not account for a significant amount of variance in CST total score, CST preparation score, CST execution score, or CST total time (R2s < 0.17). Given that immediate memory was most predictive of CST total score, CST preparation score, and CST execution score for the neurologic group, we wanted to determine whether ability to remember task instructions could be impacting the regression results. Thus we ran correlations between the number of times CST instructions had to be repeated and the CST total score, CST preparation score, and CST execution score. Number of repeated CST instructions was not significantly correlated with any of the aforementioned variables, rs < 0.27. Therefore, it does not appear that ability to remember CST instructions accounted for the results of the regression analyses. Relationship Between Cognitive Variables and CST to Functional Status Finally, we examined whether CST, RBANS total score, and DKEFS design fluency predicted functional status in the neurologic group. Results revealed that the RBANS total score and DKEFS design fluency did not significantly predict functional status; F(2, 31) = 2.55, p = 0.10, R2 = 0.15. In contrast, regression results of the CST total score and CST total time predicting functional status revealed a significant model; F(3, 30) = 5.96, p < 0.01, R2 = 0.30, with both CST total time, t = 3.42, p < 0.01, and CST total score, t = −2.52, p = 0.02, being significant predictors. Because CST total time accounted for the most variance in functional status, a follow-up hierarchical regression analysis was conducted and the first step included the two cognitive variables (RBANS total score and DKEFS design fluency) and the second step included CST total time. Results revealed that the cognitive variables accounted for 15% of the variance in functional status, which was not significant; F(2, 31) = 2.55, p = 0.09. However, the CST total time score accounted for a significant amount of the variance over and above the cognitive measures; F(3, 30) = 4.33, p < 0.01, R2 = 0.33, change in F(1, 30) = 6.84, p < 0.01, R2 change = 0.17. In the final model, significant predictors of functional status were RBANS total score; t = 2.10, p < 0.05, DKEFS design fluency; t = −2.39, p < 0.05, and CST total time; t = 2.61, p < 0.01. Discussion Traditional paper–pencil measures used in neuropsychological assessment are designed to isolate specific cognitive domains in laboratory environments and do not clearly have predictive validity, especially in terms of functional status (Burgess et al., 2006; Goldstein, 1996). However, questions related to functional status have become increasingly important. In this study, we assessed simulated grocery shopping ability in individuals with neurologic conditions using a naturalistic environment. We found that individuals with neurologic conditions performed more poorly than cognitively healthy controls on a naturalistic everyday task. This finding is consistent with research that suggests that individuals with cognitive impairment have more difficulty completing everyday tasks (Chevignard et al., 2010; Cuberos-Urbano et al., 2013; Schmitter-Edgecombe, McAlister, & Weakley, 2012; Yantz et al., 2010). The poorer CST performance of the neurologic group was reflected in the amount of cues needed on both the preparation and execution subsections of the task, as well as the time it took to complete the task. The ability to differentiate between neurologic and control groups using the CST total score and CST total time fell in the good range, while differentiation using the CST preparation and CST execution scores fell in the fair range. In contrast, the cognitive measures failed to accurately differentiate between the neurologic and control groups. Regarding individual CST task components, the neurologic group needed significantly more cues compared to the control group on task components that involved initiation and preparation. For example, participants in the neurologic group needed more cueing to begin writing down recipe items, but once they started the list they were able to complete it with the exception of items that were not part of the recipe (i.e., chocolate dessert, stamps), with which controls demonstrated equivalent difficulty remembering. For the execution subsection, participants in the neurologic group had difficulty when the task component was more vague or a decision had to be made (e.g., choosing a chocolate dessert and/or noodles, setting grocery items on the checkout counter). Participants in the neurologic condition also required significantly more cues on task components that required memory (e.g., using the stop light before crossing the street; using the provided bus pass to board the bus). Level of cueing also distinguished performances between the two groups. Specifically, participants in the control group typically only needed indirect verbal guidance to complete the task, while participants in the neurologic group often required higher cue levels. For example, participants in both the neurologic and control groups often needed prompting to write down grocery items that were not part of the recipe (i.e., stamps and chocolate dessert); however, participants in the neurologic group often had to have a direct cue administered (e.g., “You need to write down chocolate dessert.”), while participants in the control group usually only needed an indirect cue (e.g., “Is there anything else you should write down?”). Due to limited sample sizes, no statistical analyses could be conducted across the neurologic subgroups (i.e., TBI, SCI, MS, and stroke); however, mean time to complete the CST was generally consistent across neurologic subgroups. Participants with TBI and MS appeared to need fewer cues overall compared to the stroke and SCI groups. The stroke group appeared to need slightly more cues for both the CST preparation and CST execution subsections compared to the TBI and MS groups. In contrast, the SCI group appeared to need relatively fewer cues during the CST preparation subsection, but relatively more cues during the CST execution subsection compared to the other groups. Of note, if any participant could not complete the task component due to physical limitations, it did not impact the cueing rubric; therefore, differences in CST preparation and CST execution scores for participants with SCI are not reflective of physical limitations. Due to small samples sizes and significant variability within each neurologic subgroup, it is difficult to draw definitive conclusions as to whether performance on the CST might discriminate between different neurologic conditions and additional research with larger sample sizes is needed. Currently, the relationship between cognition and ability to complete everyday tasks is not fully understood (Burgess, 1997; Burgess, Alderman, Evans, Emslie, & Wilson, 1998). Consistent with models of multitasking (Burgess, 2000), results from the regression analyses suggest that episodic memory is important for completion of a complex, everyday task. The study protocol and follow-up analyses demonstrated that participant’s ability to recall task instructions before starting the task did not significantly impact these results. Therefore, it is more likely that the relationship between memory problems and CST performance is reflective of participant’s difficulty remembering and keeping track of task goals during online performance. Prior research has demonstrated that memory impairment is often one of the more significant cognitive determinants that impact functional status (Farias, Mungas, & Jagust, 2005; Kazui et al., 2005). Moreover, research has shown that executive functioning difficulties may lead to problems with task efficiency, while more significant impairment with everyday tasks occurs once memory is impaired (Schmitter-Edgecombe & Parsey, 2014a, 2014b). Therefore, the CST preparation score appears to be more reflective of problems associated with memory, while the CST execution score captures problems related to both memory and efficiency. However, it is also possible that CST preparation and CST total time are simply related to other aspects of executive functioning outside of cognitive flexibility that were not measured in this study (e.g., organization, planning, problem solving). Furthermore, attention is known to play a significant role in processing speed and ability to complete complex tasks in a timely manner (Levitt, Fugelsang, & Crossley, 2006), which is consistent with findings that attention is related to CST total time. These results also suggest that the different CST components are assessing different aspects of performance. This finding is further supported by the fact that, for the control group, the CST preparation, execution, and time scores were not significantly correlated with one another. We also evaluated whether the CST variables would account for a significant amount of variance in everyday functional status, measured by self-reported IADLs. Several comprehensive reviews of the literature conducted with participants with neurologic conditions have concluded that cognitive predictors account for about 20–25% of the total variance in functional status (McAlister, Schmitter-Edgecombe & Lamb, 2016; Royall et al., 2007; Tucker-Drob, 2011). Results of this study found that cognitive predictors accounted for a nonsignificant proportion of the variance (15%) in functional status. In contrast, CST total time and total score accounted for a significant proportion of the variance in functional status (30%). Furthermore, the time it took to complete the CST continued to be a significant predictor even after controlling for the cognitive predictors in the regression analysis. This is consistent with our hypothesis and prior literature that naturalistic tasks are more predictive of everyday functioning compared to traditional paper–pencil measures of cognition (Fortin, Godbout, & Braun, 2003). Examination of the overall IADL-C scores revealed that most of the participants with neurologic conditions in this study had scores that fell between 1 and 4 (M = 2.10). This means that study participants could complete most of the activities mentioned in the IADL-C, but they either used an assistive device and/or did not complete the task as well as ever. This may help to explain why time to complete the CST was most predictive of functional status compared to level of cues needed. If our sample had more significant impairment and required greater assistance with the IADL-C activities, the number of CST cues may have been even more predictive of functional status. Moreover, using a questionnaire as a proxy for functional status provides limited information and the accuracy of this information is difficult to determine because a trained observer did not complete the questionnaire (although self and informant ratings were highly correlated in a subgroup of our sample). As questions regarding everyday functioning become an increasingly important topic in neuropsychological assessment, it is important to supplement traditional tests of cognition with tests of higher ecological validity (Robertson & Schmitter-Edgecombe, 2016). However, there is currently no clear “gold standard” for assessing functional deficits. Researchers have argued that observation of everyday activities in more realistic environments will likely provide the most information about functional status (Marcotte et al., 2010). This study allowed us to collect direct observation data in a more real-world environment, but it remains unclear how performance might relate to grocery shopping in a real store, especially one with which participants are familiar. We also do not have information on how a similar performance-based task performed in a laboratory setting (e.g., Executive Functioning Performance Test) would compare to the CST. Therefore, comparing functional status questionnaires, performance-based measures administered in the laboratory and realistic environments, and cognitive tests would be beneficial, especially given that many researchers and clinicians do not have access to simulated modules. In regards to study limitations, the sample consisted of primarily Caucasian individuals with an average of 14 years of education, restricting generalizability. Analyses were also restricted in that there were not enough participants to separate out between neurologic conditions to see if any differences within neurologic groups existed. Only the cognitive measures that were used in data collection could be evaluated against the CST, limiting our understanding of other areas of cognition that may be important to everyday functioning. We also recognize that our cognitive battery was brief and the measures used in our study have limited sensitivity and specificity relative to other cognitive tests in existence. Regarding the acuity of the sample, participants were not included in the acute phase of injury and were not currently in the hospital. As a result, the average cognitive scores of our participants in the neurologic group were largely within the average range, but still significantly poorer than the control group. Thus, future research would benefit from evaluating the CST with more acute populations, especially as it relates to community reintegration following hospitalization. Study examiners were not blinded to the neurologic status of participants; therefore, experimenter-bias effects could have potentially impacted results. Furthermore, the CST was evaluated in a single simulated environment for purposes of consistency; however, it is possible to replicate the task in a multitude of clinical and real-world environments and future research examining use of the CST in a broad spectrum of environments would be beneficial. In conclusion, this work empirically investigated the use of a task performed within a simulated environment to better understand everyday functioning. The study provided evidence that individuals with neurologic conditions have more difficulty completing a naturalistic performance-based task compared to cognitively healthy adults. Specifically, individuals with neurologic conditions may require extra time and assistance in completing more complex everyday activities (especially if the task requires initiation, decision-making, or memory). Given that immediate memory was particularly predictive of CST performance, it is important to recognize that individuals with prominent episodic memory problems may be at a higher risk for difficulties completing everyday activities. The results also provide support for the use of simulated environments in assessment to provide a more ecologically valid method for understanding functional deficits. This is imperative given that neuropsychologists are increasingly being asked questions regarding patient’s functional ability and current cognitive tests are not able to reliably address these questions (Robertson, & Schmitter-Edgecombe, 2016). Consequently, by using tasks in more real-world environments, clinicians and researchers can better understand deficits that arise from neurologic conditions and make informed decisions about functional ability. Furthermore, understanding functional ability and the types of problems that preclude an individual from successfully completing everyday tasks can lead to more effective interventions (Giebel & Challis, 2015). Funding This work was supported by a grant from National Science Foundation under grant no. DGE-0900781 and by Edward R. Meyer funds. Conflict of Interest None declared. References Alary Gauvreau , C. , Kairy , D. , Mazer , B. , Guidon , A. , & Le Dorze , G. ( 2017 ). Rehabilitation strategies enhancing participation in shopping malls for persons living with a disability . Disability and Rehabilitation . Alderman , N. , & Burgess , P. W. ( 2002 ). Assessment and rehabilitation of the dysexecutive syndrome. In R. Greenwood , T. M. McMillan , M. P. Barnes , & C. D. Ward (Eds.) , In Handbook of neurological rehabilitation ( 2nd ed ). Hove, East Sussex : Psychology Press . Alderman , N. , Burgess , P. W. , Knight , C. , & Henman , C. ( 2003 ). Ecological validity of a simplified version of the multiple errands shopping test . Journal of the International Neuropsychological Society , 9 , 31 – 44 . Google Scholar CrossRef Search ADS PubMed Amieva , H. , Rouch-Leroyer , I. , Fabrigoule , C. , & Dartigues , J. ( 2000 ). Deterioration of controlled processes in the preclinical phase of dementia: A confirmatory analysis . Dementia and Geriatric Cognitive Disorders , 11 , 46 – 52 . Google Scholar CrossRef Search ADS PubMed Brown , C. , Hasson , H. , Thyselius , V. , & Almborg , A. ( 2012 ). Post‐stroke depression and functional independence: A conundrum . Acta Neurologica Scandinavica , 126 , 45 – 51 . Google Scholar CrossRef Search ADS PubMed Bruce , I. , Ntlholang , O. , Crosby , L. , Cunningham , C. , & Lawlor , B. ( 2016 ). The clinical utility of naturalistic action test in differentiating mild cognitive impairment from early dementia in memory clinic . International Journal of Geriatric Psychology , 31 , 309 – 315 . Google Scholar CrossRef Search ADS Burgess , P. W. ( 1997 ). Theory and methodology in executive function research. In Rabbitt P. (Ed.) , Methodology of fontal and executive function . Hove : Psychology Press . Burgess , P. W. ( 2000 ). Strategy application disorder: The role of the frontal lobes in human multitasking . Psychological Research , 63 , 279 – 288 . Google Scholar CrossRef Search ADS PubMed Burgess , P. W. , Alderman , N. , Evans , J. , Emslie , H. , & Wilson , B. A. ( 1998 ). The ecological validity of tests of executive function . Journal of International Neuropsychological Society , 4 , 547 – 558 . Google Scholar CrossRef Search ADS Burgess , P. W. , Alderman , N. , Forbes , C. , Costello , A. , Coates , L. M. , Dawson , D. R. , et al. . ( 2006 ). The case for the development and use of "ecologically valid" measures of executive function in experimental and clinical psychology . Journal of the International Neuropsychological Society , 12 , 194 – 209 . Google Scholar CrossRef Search ADS PubMed Chaytor , N. , Schmitter-Edgecombe , M. , & Burr , R. ( 2006 ). Improving the ecological validity of executive functioning assessment . Archives of Clinical Neuropsychology , 21 , 217 – 227 . Google Scholar CrossRef Search ADS PubMed Chevignard , M. , Catroppa , C. , Galvin , J. , & Anderson , V. ( 2010 ). Development of an open-ended ecological task to assess executive function in children post TBI: A cooking task . Brain Impairment , 11 , 125 – 143 . Google Scholar CrossRef Search ADS Chevignard , M. , Servant , V. , Mariller , A. , Abada , G. , Pradat-Diehl , P. , & Laurent-Vannier , A. ( 2009 ). Assessment of executive functioning in children after TBI with a naturalistic open-ended task: A pilot study . Developmental Neurorehabilitation , 12 , 76 – 91 . Google Scholar CrossRef Search ADS PubMed Chevignard , M. P. , Soo , C. , Galvin , J. , Catroppa , C. , & Eren , S. ( 2012 ). Ecological assessment of cognitive functions in children with acquired brain injury: A systematic review . Brain Injury , 26 , 1033 – 1057 . Google Scholar CrossRef Search ADS PubMed Chevignard , M. P. , Taillefer , C. , Picq , C. , Poncet , F. , Noulhiane , M. , & Pradat-Diehl , P. ( 2008 ). Ecological assessment of the dysexecutive syndrome using execution of a cooking task . Neuropsychological Rehabilitation , 18 , 461 – 485 . Google Scholar CrossRef Search ADS PubMed Collette , F. , Van der Linden , M. , & Salmon , E. ( 2010 ). Dissociation between controlled and automatic processes in the behavioral variant of frontotemporal dementia . Journal of Alzheimer’s Disease , 22 , 897 – 907 . Google Scholar CrossRef Search ADS PubMed Couture , M. , Larivière , N. , & Lefrançois , R. ( 2005 ). Psychological distress in older adults with low functional independence: A multidimensional perspective . Archives of Gerontology and Geriatrics , 41 , 101 – 111 . Google Scholar CrossRef Search ADS PubMed Cuberos-Urbano , G. , Caracuel , A. , Vilar-Lopez , R. , Valls-Serrano , C. , Bateman , A. , & Verdejo-Garcia , A. ( 2013 ). Ecological validity of the Multiple Errands Test using predictive models of dysexecutive problems in everyday life . Journal of Clinical and Experimental Neuropsychology , 35 , 329 – 336 . Google Scholar CrossRef Search ADS PubMed Dawson , D. R. , Anderson , N. D. , Burgess , P. , Cooper , E. , Krpan , K. M. , & Stuss , D. T. ( 2009 ). Further development of the Multiple Errands Test: Standardized scoring, reliability, and ecological validity for the Baycrest version . Archives of Physical Medicine & Rehabilitation , 90 , S41 – S51 . Google Scholar CrossRef Search ADS Delis , D. C. , Kaplan , E. , & Kramer , J. H. ( 2001 ). Delis-Kaplan Executive Function System (D-KEFS) . San Antonio, TX : The Psychological Corporation . Donovan , N. J. , Heaton , S. C. , Kimberg , C. I. , Wen , P.-S. , Waid-Ebbs , J. K. , Coster , W. , et al. . ( 2011 ). Conceptualizing functional cognition in traumatic brain injury rehabilitation . Brain Injury , 25 , 348 – 364 . Google Scholar CrossRef Search ADS PubMed Farias , S. T. , Mungas , D. , & Jagust , W. ( 2005 ). Degree of discrepancy between self and other-reported everyday functioning by cognitive status: Dementia, mild cognitive impairment, and healthy elders . Int J Geriatr Pscyhiatry , 20 , 827 – 834 . Google Scholar CrossRef Search ADS Ford , J. M. , Roth , W. T. , Isaacks , B. G. , Tinklenberg , J. R. , Yesavage , J. , & Pfefferbaum , A. ( 1997 ). Automatic and effortful processing in aging and dementia: Event-related brain potentials . Neurobiology of Aging , 18 , 169 – 180 . Google Scholar CrossRef Search ADS PubMed Fortin , S. , Godbout , L. , & Braun , C. M. J. ( 2003 ). Cognitive structure of executive deficits in frontally lesioned head trauma patients performing activities of daily living . Cortex; a Journal Devoted to the Study of the Nervous System and Behavior , 39 , 273 – 291 . Google Scholar CrossRef Search ADS PubMed Giebel , C. M. , & Challis , D. ( 2015 ). Translating cognitive and everyday activity deficits into cognitive interventions in mild dementia and mild cognitive impairment . International Journal of Geriatric Psychiatry , 30 , 21 – 31 . Google Scholar CrossRef Search ADS PubMed Giebel , C. M. , Challis , D. , & Montaldi , D. ( 2014 ). Understanding the cognitive underpinnings of functional impairments in early dementia: A review . Aging and Mental Health , 19 , 859 – 875 . Google Scholar CrossRef Search ADS Giebel , C. M. , Shutcliffe , C. , & Challis , D. ( 2015 ). Activities of daily living and quality of life across different stages of dementia: A UK study . Aging and Mental Health , 19 , 63 – 71 . Google Scholar CrossRef Search ADS PubMed Glisky , E. L. , & Delaney , S. M. ( 1996 ). Implicit memory and new semantic learning in posttraumatic amnesia . Journal of Head Trauma Rehabilitation , 11 , 31 – 42 . Google Scholar CrossRef Search ADS Goldstein , G. ( 1996 ). Functional considerations in neuropsychology. In R. J. Sbordone , & C. J. Long (Eds.) , Ecological validity of neuropsychological testing (pp. 75 – 89 ). Delray Beach, FL : GR Press/St Lucie Press . Hecox , R. , Roach , K. E. , DasVerma , J. M. , Giraud , J. E. , Davis , C. M. , & Neulen , K. ( 1994 ). Functional Independence Measurement (FIM) of patients receiving Easy Street—A retrospective study . Physical and Occupational Therapy in Geriatrics , 12 , 17 – 31 . Google Scholar CrossRef Search ADS Hudson , T. ( 1995 ). Learning on Easy Street . Hospitals & Health Networks , 69 , 41 . Google Scholar PubMed Kazui , H. , Matsuda , A. , Hirono , N. , Mori , E. , Miyoshi , N. , Ogino , A. , et al. . ( 2005 ). Everyday memory impairment of patients with mild cognitive impairment . Dementia geriatric Cognitive Disorders , 19 , 331 – 337 . Google Scholar CrossRef Search ADS PubMed Knight , C. , Alderman , N. , & Burgess , P. W. ( 2002 ). Development of a simplified version of the multiple errands test for use in hospital settings . Neuropsychological Rehabilitation , 12 , 231 – 255 . Google Scholar CrossRef Search ADS Levitt , T. , Fugelsang , J. , & Crossley , M. ( 2006 ). Processing speed, attentional capacity, and age-related memory change . Experimental Aging Research , 32 , 263 – 295 . Google Scholar CrossRef Search ADS PubMed MacDonald , P. L. , & Gardner , R. C. ( 2000 ). Type I error rate comparisons of post hoc procedures for Chi-Square tables . Educational and Psychological Measurement , 60 , 735 – 754 . Google Scholar CrossRef Search ADS Maeir , A. , Krauss , S. , & Katz , N. ( 2010 ). Ecological validity of the Multiple Errands Test (MET) on discharge from neurorehabilitation hospital . Occupation, Participation and Health , 31 , S38 – S46 . Google Scholar CrossRef Search ADS Marcotte , T. D. , Scott , J. C. , Kamat , R. , & Heaton , R. K. ( 2010 ). Neuropsychology and the prediction of everyday functioning. In Marcotte T. D. , & Grant I. (Eds.) , Neuropsychology of everyday functioning . New York : The Guildford Press . McAlister , C. , Schmitter-Edgecombe , M. , & Lamb , R. ( 2016 ). Examination of variables that may affect the relationship between cognition and functional status in individuals with mild cognitive impairment: A meta-analysis . Archives of Clinical Neuropsychology , 31 , 123 – 147 . Google Scholar CrossRef Search ADS PubMed McClusky , J. F. ( 2008 ). Creating engaging experiences for rehabilitation . Top Stroke Rehabilitation , 15 , 80 – 86 . Google Scholar CrossRef Search ADS McColl , M. A. , Stirling , P. , Walker , J. , Corey , P. , & Wilkins , R. ( 1999 ). Expectations of independence and life satisfaction among ageing spinal cord injured adults . Disability and Rehabilitation: An International, Multidisciplinary Journal , 21 , 231 – 240 . Google Scholar CrossRef Search ADS Mower , W. R. ( 1999 ). Evaluating bias and variability in diagnostic test reports . Ann Emergency Medicine , 33 , 85 – 91 . Google Scholar CrossRef Search ADS Mulherin , S. A. , & Miller , W. C. ( 2002 ). Spectrum bias or spectrum effect? Subgroup variation in diagnostic test evaluation . Annals of Internal Medicine , 137 , 598 – 602 . Google Scholar CrossRef Search ADS PubMed Randolph , C. , Tierney , M. C. , Mohr , E. , & Chase , T. N. ( 1998 ). The Repeatable Battery for the Assessment of Neuropsychological Status (RBANS): Preliminary clinical validity . Journal for Clinical and Experimental Neuropsychology , 20 , 310 – 319 . Google Scholar CrossRef Search ADS Ransohoff , D. F. , & Feinstein , A. R. ( 1978 ). Problems of spectrum and bias in evaluating the efficacy of diagnostic tests . The New England Journal of Medicine , 299 , 926 – 930 . Google Scholar CrossRef Search ADS PubMed Reid , M. C. , Lachs , M. S. , & Feinstein , A. R. ( 1995 ). Use of methodological standards in diagnostic test research. Getting better but still not good . JAMA: the Journal of the American Medical Association , 274 , 645 – 651 . Google Scholar CrossRef Search ADS Resch , J. A. , Villarreal , V. , Johnson , C. L. , Elliott , T. R. , Kwok , O. , Berry , J. W. , et al. . ( 2009 ). Trajectories of life satisfaction in the first 5 years following traumatic brain injury . Rehabilitation Psychology , 54 , 51 – 59 . Google Scholar CrossRef Search ADS PubMed Richardson , J. , Law , M. , Wishart , L. , & Guyatt , G. ( 2000 ). The use of simulated environment (Easy Street) to retrain independent living skills in elderly persons: A randomized controlled trial . Journal of Gerontology: Medical Sciences , 55 , M578 – M584 . Google Scholar CrossRef Search ADS Robertson , K. , & Schmitter-Edgecombe , M. ( 2016 ). Naturalistic tasks performed in realistic environments: A review with implications for neuropsychological assessment . The Clinical Neuropsychologist , 31 , 16 – 42 . Google Scholar CrossRef Search ADS PubMed Royall , D. R. , Lauterbach , E. C. , Kaufer , D. , Malloy , P. , Coburn , K. L. , & Black , K. J. ( 2007 ). The cognitive correlates of functional status: A review from the committee on research of the American neuropsychiatric association . The Journal of Neuropsychiatry and Clinical Neurosciences , 19 , 249 – 265 . Google Scholar CrossRef Search ADS PubMed Sanders , C. , & Schmitter-Edgecombe , M. ( 2012 ). Identifying the nature of impairment in planning ability with normal aging . Journal of Clinical and Experimental Neuropsychology , 34 , 724 – 737 . Google Scholar CrossRef Search ADS PubMed Scarrabelotti , M. , & Carroll , M. ( 1998 ). Awareness of remembering achieved through automatic and conscious processes in multiple sclerosis . Brain and Cognition , 38 , 183 – 201 . Google Scholar CrossRef Search ADS PubMed Schmitter-Edgcombe , M. , Parsey , C. , & Lamb , R. ( 2014 ). Development and psychometric properties of the Instrumental Activities of Daily Living: Compensation Scale . Archives of Clinical Neuropsychology , 29 , 776 – 792 . Google Scholar CrossRef Search ADS PubMed Schmitter-Edgecombe , M. ( 1996 ). Effects of divided attention on implicit and explicit memory performance following severe closed head injury . Neuropsychology , 10 , 155 – 167 . Google Scholar CrossRef Search ADS Schmitter-Edgecombe , M. , McAlister , C. , & Weakley , A. ( 2012 ). Naturalistic assessment of everyday functioning in individuals with mild cognitive impairment: the day out task . Neuropsychology , 26 , 631 – 641 . Google Scholar CrossRef Search ADS PubMed Schmitter-Edgecombe , M. , & Parsey , C. ( 2014 a). Assessment of functional change and cognitive correlates in the progression from normal aging to dementia . Neuropsychology , 28 , 881 – 893 . Google Scholar CrossRef Search ADS PubMed Schmitter-Edgecombe , M. , & Parsey , C. ( 2014 b). Cognitive correlates of functional abilities in individuals with mild cognitive impairment: Comparison of questionnaire, direct observation and performance-based measures . The Clinical Neuropsychologist , 28 , 726 – 746 . Google Scholar CrossRef Search ADS PubMed Schwartz , M. F. , Buxbaum , L. J. , Ferraro , M. , Veramonti , T. , & Segal , M. ( 2003 ). Naturalistic action test . Suffolk, England : Pearson Assessment . Semlyen , J. K. , Summers , S. J. , & Barnes , M. P. ( 1998 ). Aspects of caregiver distress after severe head injury . Journal of Neurologic Rehabilitation , 12 , 53 – 60 . Sharpe , D. ( 2015 ). Your chi-square test is statistically significant: Now what? Practical Assessment, Research & Evaluation , 20 ( 8–12 ), 1 – 10 . Simmons , N. N. ( 1988 ). A trip down Easy Street. In Clinical aphasiology (pp. 19 – 30 ). Boston, Mass : College-Hill Press . Smith , M. M. , & Arnett , P. A. ( 2010 ). Awareness of executive functioning deficits in multiple sclerosis: Self versus informant ratings of impairment . Journal of Clinical and Experimental Neuropsychology , 32 , 780 – 787 . Google Scholar CrossRef Search ADS PubMed Sox , H. C. ( 1986 ). Probability theory in the use of diagnostic tests. An introduction to critical study of the literature . Ann Internal Medicine , 104 , 60 – 66 . Google Scholar CrossRef Search ADS Spooner , D. M. , & Pachana , N. A. ( 2006 ). Ecological validity in neuropsychological assessment: A case for greater consideration in research with neurologically intact populations . Archives of Clinical Neuropsychology , 21 , 327 – 337 . Google Scholar CrossRef Search ADS PubMed Tape , T. G. (n.d.). The Area Under an AUC Curve. University of Nebraska Medical Center. Retrieved from http://gim.unmc.edu/dxtests/Default.htm. Tucker-Drob , E. M. ( 2011 ). Neurocognitive functions and everyday functions change together in old age . Neuropsychology , 25 , 368 – 377 . Google Scholar CrossRef Search ADS PubMed Vakil , E. , Biederman , Y. , Liran , G. , Grosswasser , Z. , & Aberbuch , S. ( 1994 ). Head injured patients and control group: Implicit vs. explicit measures of frequency judgment . Journal of Clinical Experimental Neuropsychology , 16 , 539 – 546 . Google Scholar CrossRef Search ADS PubMed Vanderploeg , R. D. , Belanger , H. G. , Duchnick , J. D. , & Curtiss , G. ( 2007 ). Awareness problems following moderate to severe traumatic brain injury: Prevalence, assessment methods, and injury correlates . Journal of Rehabilitation Research & Development , 44 , 937 – 950 . Google Scholar CrossRef Search ADS Whitling , P. , Rutjes , A. W. , Reitsma , J. B. , Glas , A. S. , Bossuyt , P. M. , & Klenijnen , J. ( 2004 ). Sources of variation and bias in studies of diagnostic accuracy: A systematic review . Ann Internal Medicine , 140 , 189 – 202 . Google Scholar CrossRef Search ADS World Health Organization . ( 2006 ). Neurological disorders: Public health challenges . Geneva, Switzerland : WHO Press . Yantz , C. L. , Johnson-Greene , D. , Higgins , C. , & Emmerson , L. ( 2010 ). Functional cooking skills and neuropsychological functioning in patients with stroke: An ecological validity study . Neuropsychological Rehabilitation , 20 , 725 – 738 . Google Scholar CrossRef Search ADS PubMed Yeaman , P. A. , Kim , D. , Alexander , J. L. , Ewing , H. , & Kim , K. Y. ( 2013 ). Relationship of physical and functional independence and perceived quality of life of veteran patients with alzheimer disease . American Journal of Hospice & Palliative Medicine , 30 , 462 – 466 . Google Scholar CrossRef Search ADS © The Author(s) 2017. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

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Archives of Clinical NeuropsychologyOxford University Press

Published: Dec 28, 2017

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