Abstract

Objective

Performance-based functional assessment is a critical component of neuropsychological practice. The Texas Functional Living Scale (TFLS) has promise given its brevity, nationally representative norms, and co-norming with Wechsler scales. However, its subscale structure has not been evaluated. The purpose of this study was to evaluate the TFLS in a mixed clinical sample ( n  = 197).

Method

Reliability and convergent and discriminant validity coefficients were calculated with neurocognitive testing and collateral reports and factor analysis was performed.

Results

The Money and Calculation subscale had the best psychometric properties of the subscales. The evidence did not support solitary interpretation of the Time subscale. A three-factor latent structure emerged representing memory and semantic retrieval, performance and visual scanning, and financial calculation.

Conclusions

This study added psychometric support for interpretation of the TFLS total score and some of its subscales. Study limitations included sample characteristics (e.g., gender ratio) and low power for collateral report analyses.

Introduction

The concept of “functioning” can be broadly defined as the performance of everyday activities ( Heinemann & Mallinson, 2010 ). It is often contrasted with “disability,” in which the “International Classification of Functioning, Disability, and Health” (ICF; WHO, 2001 ) operationalizes as body impairments, activity restrictions, and participation limitations that result from an interplay of health conditions and contextual factors ( Heinemann & Mallinson, 2010 ). For example, an individual may experience a stroke (health condition) with subsequent hemiparesis (body impairment), which limits her ability to walk long distances and drive (activity restriction). However, this will not necessarily affect her ability to transport to her place of employment (participation limitation) if her city has a well-implemented public transit system (contextual factor). The “Diagnostic and Statistical Manual of Mental Disorders-Fifth Edition” (DSM-5; APA, 2013 ) emphasizes the ICF model of functioning and its assessment for most disorders. Most notably, the presence of functional impairment is what differentiates mild from major neurocognitive disorders (i.e., mild cognitive impairment vs. dementia).

Self and collateral report measures are typical components of functional assessment, although reporting bias or reduced awareness can limit the validity of such assessment ( Loewenstein & Acevedo, 2010 ). Given these limitations, performance-based functional assessment (PBFA) that requires an individual to perform a standardized functional task is recommended when commenting on everyday functioning. PBFAs have been shown to have greater ecological validity and improved predictive power when used in addition to traditional neuropsychological tests ( Chaytor & Schmitter-Edgecombe, 2003 ; Loewenstein & Acevedo, 2010 ). There is a growing selection of PBFAs available to the neuropsychologist. Measures that frequently appear in the literature include the Independent Living Scales (ILS; Loeb, 1996 ) and the Direct Assessment of Functional Status (DAFS; Loewenstein et al., 1989 ); however, these have some notable limitations, including normative data consisting of only older adults and a significant administration time commitment. More recently, the Texas Functional Living Scale (TFLS; Cullum Weiner, & Saine, 2009 ; formerly called the Test of Everyday Functional Ability [TEFA]) was developed to measure functional abilities in the domains of Time, Money and Calculation, Communication, and Memory, as well as providing a total score (TS).

The TFLS has promising features, including reduced administration burden (i.e., 15–20 min), large nationally representative normative sample (i.e., n  = 800, ages 16–90), and co-norming with the Wechsler Adult Intelligence Scale-Fourth Edition (WAIS-IV) and Wechsler Memory Scale-Fourth Edition (WMS-IV). Adequate reliability and validity have been established for the TS in several populations, with significantly better TS psychometric properties found in impaired versus non-impaired samples ( Cullum et al., 2009 ). Despite promising characteristics, the scale's psychometric performance has not been thoroughly evaluated in clinical practice with mixed referral diagnoses—most notably, research on the TFLS's subscales is lacking. For example, the test manual dichotomized the subscales using criteria of <10th percentile or ≥10th percentile, and stated that test–retest decision consistency (i.e., classification consistency over 23 days) was strong (all coefficients >.90); however, this does not provide information about the internal consistency of each subscale. A study using a research version of the TFLS (i.e., TEFA) reported three of four scales had correlations >.90 with the TS ( Cullum et al., 2001 ), suggesting that the subscales may not represent separate constructs. However, the manual for the final version of the TFLS provides interpretation guidelines for the individual subscales. Also, there are no published TFLS factor analyses to clarify latent structure. Given these limited data, the purpose of this study was to examine the psychometric properties of the TFLS TS and subscales, including internal consistency, convergent, and discriminant validity with neuropsychological tests, and structural validity, in a mixed clinical sample. It was expected that different TFLS subscales would have convergent relationships with neuropsychological abilities that theoretically subsume functional performance (e.g., the Prospective Memory scale should related to memory abilities, the Money and Calculation subscale should relate to working memory, the Communication subscale should relate to language abilities).

Materials and Methods

Participants

Participants included 197 veterans (91.4% men) with an average age of 60.58 years ( SD = 11.96) and average education of 13.04 years ( SD = 2.82) who completed the TFLS. The majority of the sample identified as White, non-Hispanic (51.3%), followed by Hispanic (35%), Black, non-Hispanic (12.7%), and Native American (1%). Twenty-nine percent of the sample were bilingual ( N = 58), speaking both English and Spanish, whereas the remaining 71% were monolingual, speaking English only. All bilingual individuals included in our sample had an English language or equivalent preference, and were tested in English. The most common primary diagnoses were dementia (38%), mild cognitive impairment (29%), major depressive disorder (10%), post-traumatic stress and other anxiety disorders (4%), other psychiatric (5%; e.g., somatic symptom disorder, schizophrenia, substance misuse), neurodevelopmental (3%; i.e., attention-deficit/hyperactivity and specific learning disorder), and no diagnosis (11%). Among those with cognitive impairment, the five most common etiologies were vascular or stroke (32%), Alzheimer (8%), other neurologic condition (8%; multiple sclerosis, epilepsy, Parkinson), remote history of traumatic brain injury (5%), and frontotemporal dementia (4%).

Measures

As part of a larger neuropsychological clinical battery, participants were administered the following commonly used measures of cognition: WAIS-IV indices ( Wechsler, 2008 ), Trail Making Test Parts A and B total time ( Reitan & Wolfson, 1993 ), Stroop Color and Word Test interference trial ( Golden & Freshwater, 2002 ), phonemic verbal fluency (FAS; Gladsjo et al., 1999 ), Animal Naming ( Gladsjo et al., 1999 ), and California Verbal Learning Test-Second Edition (CVLT-II) total learning and long delay free-recall trials (CVLT-II; Delis, Kramer, Kaplan, & Ober, 2000 ). In addition, for evaluation of functional abilities, participants were administered the TFLS ( Cullum, Weiner, & Saine, 2009 ) and the Everyday Cognition scale (ECog; Farias et al., 2008 ). The TFLS is a standardized, ecologically valid measure of instrumental activities of daily living (e.g., bill payment, meal preparation, prospective memory for medication use) appropriate for individuals 16–90 years of age. It consists of 24 performance-based tasks (described in Supplementary material online, Table S1 ) that are scored based on accuracy. The total raw score can range from 0 to 50, which is compared with the entire normative sample to generate a T -score. The manual provides percentile ranges for the four subscales, although the normative sample was later re-analyzed to provide standard scores and percentile ranks for each subscale ( Crawford, Cullum, Garthwaite, Lycett, & Allsopp, 2012 ). The manual does not provide corrections for age or education because functional abilities are conceptualized as having an absolute referent (e.g., the post office will not correctly mail an incorrectly labeled envelope, regardless of the person's age). The ECog is an informant-rated measure of everyday functional abilities categorized by related cognitive demands, such as memory and divided attention. Informants are asked to rate change in task performance over the past 10 years, with ratings ranging from 1 (better or no change) to 4 (consistently much worse). Neuropsychological tests were selected for inclusion in analyses based on expected convergent and discriminant relationships (e.g., TFLS memory would have strong relationships with CVLT-II and not other tests).

Procedure

This retrospective study involved extracting participants’ data from a research database of veterans who underwent neuropsychological evaluation at a large VA medical center. Following completion of neuropsychological evaluation, participants were invited to consider having their clinical data included in a research database. The database study was approved by the local Institutional Review Board (IRB) and all participants provided written consent to be included in the research database. Participants who completed the TFLS and other study measures as part of their clinical evaluation were selected for study inclusion. Four participants were excluded for invalid test performance based on published cut scores on a standalone measure of performance validity (i.e., Test of Memory Malingering [TOMM]; Tombaugh, 1996 ).

Data Analysis

With regard to statistical analyses, assumptions and descriptives were assessed. Absolute value cutoffs were employed for determining significant skewness and kurtosis (>2 and 4, respectively), and Cronbach's alpha (α) and Spearman–Brown (SB) statistics to assess reliability. We used raw scores in our analyses because the age range lent itself to clinicians using different normative studies [e.g., Mayo's Older American Normative Studies (MOANS) or Heaton]. Since age and education may account for variability in raw scores, we partialed out the shared variance from these demographics to help clarify the relationship between cognition and functioning. Partial correlations that excluded shared variance with age and education were calculated to assess convergent validity. Since no factor analysis has been reported in the literature previously, an exploratory approach was selected in accordance with common factor model recommendations ( Brown, 2015 ). Principal factors extraction was used due to its lack of distributional assumptions for indicators. Parallel analysis was used to determine maximum factor extraction ( Raîche,Walls, Magis, Riopel, & Blais, 2013 ). Oblique promax rotation was executed to reflect expected correlations among factors; pattern matrices were used to interpret factor loadings.

Results

Item descriptions and descriptives are listed in the Supplementary material online, Table S1 . See Table 1 for scale descriptives and their correlation coefficients. The TFLS and its subscales were normally distributed, with non-significant negative skew (skewness range = −1.65 to −.99). Age and education were related to all cognitive tests and the TFLS TS, Prospective Memory, and Communication scales. Cronbach's alpha for the TS was 0.83. Some discrepancy across unstandardized and standardized subscales’ Cronbach's alpha was observed and are, respectively: Time (α = .30/.30), Money and Calculation (α = .62/.70), Communication (α = .65/.78), and Prospective Memory (α = .38/.55). Split-half reliability was .76 for the TS and ranged for subscales: Time (SB = .40), Money and Calculation (SB = .69), Communication (SB = .65), and Prospective Memory (SB = .53).

Table 1.

Correlations among scales and subscales

 Time Money Comm. Memory Total Sum M ( SD )  
E-memory −.06 −.09 −.10 −.17 −.13 2.93 (0.86) 
E-language −.05 −.19 −.21 −.17 −.23 2.48 (0.93) 
E-visuo. −.25 −.24 −.23 −.25 .31 2.19 (1.0) 
E-planning −.10 −.24 −.16 −.16 −.22 2.58 (1.1) 
E-organiz. −.14 −.16 −.13 −.10 −.18 2.68 (1.1) 
E-attention −.05 −.05 −.06 −.07 −.08 2.83 (1.0) 
TMT a −.39 −.55 −.39 −.06 −.51 49.77 (23.5) 
TMT b −.41 −.64 −.49 −.03 −.59 163.87 (100.8) 
FAS .34 .43 .39 .04 .46 28.14 (13.4) 
Animals .13 .49 .36 .07 .42 15.19 (5.7) 
CVLT tl .19 .36 .33 .36 .43 38.52 (11.4) 
CVLT ldfr .33 .31 .31 .35 .43 6.82 (3.7) 
ST .35 .48 .37 .04 .46 24.51 (10.0) 
VCI .25 .48 .50 .24 .56 93.82 (13.7) 
PRI .45 .54 .44 .11 .55 89.54 (13.3) 
WMI .39 .56 .51 .13 .60 88.34 (13.8) 
PSI .32 .49 .40 .08 .49 85.83 (12.8) 
M ( SD )  8.11 (1.1) 6.41 (1.7) 23.96 (4.6) 3.93 (1.4) 42.38 (6.8) — 
 Time Money Comm. Memory Total Sum M ( SD )  
E-memory −.06 −.09 −.10 −.17 −.13 2.93 (0.86) 
E-language −.05 −.19 −.21 −.17 −.23 2.48 (0.93) 
E-visuo. −.25 −.24 −.23 −.25 .31 2.19 (1.0) 
E-planning −.10 −.24 −.16 −.16 −.22 2.58 (1.1) 
E-organiz. −.14 −.16 −.13 −.10 −.18 2.68 (1.1) 
E-attention −.05 −.05 −.06 −.07 −.08 2.83 (1.0) 
TMT a −.39 −.55 −.39 −.06 −.51 49.77 (23.5) 
TMT b −.41 −.64 −.49 −.03 −.59 163.87 (100.8) 
FAS .34 .43 .39 .04 .46 28.14 (13.4) 
Animals .13 .49 .36 .07 .42 15.19 (5.7) 
CVLT tl .19 .36 .33 .36 .43 38.52 (11.4) 
CVLT ldfr .33 .31 .31 .35 .43 6.82 (3.7) 
ST .35 .48 .37 .04 .46 24.51 (10.0) 
VCI .25 .48 .50 .24 .56 93.82 (13.7) 
PRI .45 .54 .44 .11 .55 89.54 (13.3) 
WMI .39 .56 .51 .13 .60 88.34 (13.8) 
PSI .32 .49 .40 .08 .49 85.83 (12.8) 
M ( SD )  8.11 (1.1) 6.41 (1.7) 23.96 (4.6) 3.93 (1.4) 42.38 (6.8) — 

Note : Time = Texas Functional Living Scales (TFLS) Time subscale; Money = TFLS Money & Calculation subscale; Comm. = TFLS Communication subscale; Memory = TFLS Prospective Memory subscale; Total Sum = TFLS total raw score; T = TFLS total t -score; TFLS n = 197. E-memory, Everyday Cognition Scale (Ecog) Memory subscale ( n = 109); E-language = ECog Language subscale ( n = 109); E-visuo. = ECog Visual-Spatial scale ( n = 103);  E-planning = Ecog Planning subscale ( n = 104);  E-organiz. = ECog Organization subscale ( n = 106);  E-attention = ECog Divided Attention subscale ( n  = 107); TMT a = Trail making Test (TMT) Part A ( n = 196);  TMT b = TMT Part B ( n  = 186);  FAS = Controlled Oral Word Association ( n = 193); Animals = Animal naming ( n = 193); CVLT = California Verbal Learning Test, 2nd Edition, Total Learning ( n = 73), Long Delay Free Recall ( n = 71);  ST = Stroop Color and Word Test, Color-Word Trial ( n =186); FSIQ = Wechsler Adult Intelligence Scale 4th Edition (WAIS-IV); VCI = WAIS-IV Verbal Comprehension Index ( n =156); PRI = WAIS-IV Perceptual Reasoning Index ( n =157); WMI = WAIS-IV Working Memory Index ( n =161); PSI = WAIS-IV Processing Speed Index ( n =162);M = mean; SD  = standard deviation. Emboldened =  p < .05.

Correlations with the TS and collateral report yielded small-to-medium effects with language, visuospatial, and executive-planning abilities. The collateral report of language difficulties correlated with worse Communication performance and collateral report of executive-planning difficulties was associated with poorer Money and Calculation performance. Notably, collateral report of visuospatial problems was related to poorer performance on all TFLS scales. The TS showed medium-to-large relationships with all cognitive tests; in particular, its strongest correlations were with tests of executive functioning and intellectual abilities. The Time subscale showed its strongest relationship with the WAIS perceptual index. The Money and Calculation subscale was also related to all tests, but showed its strongest relationship with WAIS working memory and TMT Part B. The Communication subscale was also related to all cognitive tests, but showed its strongest relationship with WAIS verbal and working memory indices. The Prospective Memory subscale was only related to CVLT memory scores.

Factor analysis indicated that there were eight factors with eigenvalues greater than one; however, parallel analysis indicated that extraction should be limited to a maximum of four factors based on the number of items. Only three factors were interpretable, which included items related to memory and semantic retrieval (Factor 1), performance and visual scanning (Factor 2), and financial calculation (Factor 3). Loadings are reported in Table 2 .

Table 2.

Texas Functional Living Scale: factor loadings

Item Factor 
.17 .02 .01 .51 
−.11 .05 .20 .14 
−.21 .73 −.01 .11 
−.02 .15 .29 −.04 
.29 .10 .01 .15 
.35 .18 .09 .00 
−.02 −.01 .56 .07 
.04 −.06 .53 −.06 
−.14 .04 .53 .11 
10 .10 −.38 .68 −.06 
11 −.27 .25 .59 −.06 
12 .03 .10 .47 .12 
13 .43 .35 .02 −.22 
14 .43 .15 .10 −.12 
15 .36 .11 .09 −.26 
16 .08 .49 −.03 −.08 
17 −.01 .79 −.06 −.10 
18 .10 .64 −.08 .26 
19 .43 −.02 −.17 .02 
20 .15 .16 .25 .31 
21 .27 .27 .21 .16 
22 .56 −.06 −.02 −.04 
23 .71 −.16 −.07 .29 
24 .59 −.08 −.02 .18 
Item Factor 
.17 .02 .01 .51 
−.11 .05 .20 .14 
−.21 .73 −.01 .11 
−.02 .15 .29 −.04 
.29 .10 .01 .15 
.35 .18 .09 .00 
−.02 −.01 .56 .07 
.04 −.06 .53 −.06 
−.14 .04 .53 .11 
10 .10 −.38 .68 −.06 
11 −.27 .25 .59 −.06 
12 .03 .10 .47 .12 
13 .43 .35 .02 −.22 
14 .43 .15 .10 −.12 
15 .36 .11 .09 −.26 
16 .08 .49 −.03 −.08 
17 −.01 .79 −.06 −.10 
18 .10 .64 −.08 .26 
19 .43 −.02 −.17 .02 
20 .15 .16 .25 .31 
21 .27 .27 .21 .16 
22 .56 −.06 −.02 −.04 
23 .71 −.16 −.07 .29 
24 .59 −.08 −.02 .18 

Notes : Loadings >0.32 are emboldened.

Discussion

This study provided support for use of the TFLS TS in a mixed clinical sample given that the TS had adequate internal consistency and convergent validity. In contrast, psychometric support for the TFLS subscales was variable. Reliability coefficients for the Time and Prospective Memory subscales were below .60. Despite this, some differential convergent validity was evidenced with neuropsychological tests (e.g., Prospective Memory correlated with CVLT; Money and Calculation with WMI). The TS, Money and Calculation, and Communication subscales correlated with reports of visuospatial, language, and executive-planning difficulties. Factor analysis did not correspond entirely with the published subscale structure. One factor corresponded with the Money and Calculation subscale; another subsumed the Prospective Memory subscale and items that provided material for incidental retrieval. A third factor did not correspond with any subscale and included items related to performance of overlearned tasks and visual scanning (e.g., finding information in a mock bill and telephone book). These preliminary data suggest that the Money and Calculation subscale is most appropriate for independent interpretation; it has adequate reliability, convergent correlations, and its items appear to reflect a single latent construct. When using a subscale independently, practitioners may want more precise estimates than the percentile range provided in the TFLS manual; standardized scores and confidence intervals for TFLS subscales are provided by Crawford and colleagues (2012) for reference. The Prospective Memory and Communication subscales had conflicting evidence regarding their psychometric properties in this sample. The Prospective Memory subscale evidenced low reliability coefficients, but also evidenced convergent and discriminant relationships with cognitive testing and its items held together within a larger factor. The Communication subscale items did not group together in factor analysis, but it evidenced adequate reliability and convergent relationships with collateral report and cognitive testing. The Time subscale had the lowest reliability coefficients and its items did not clearly correspond with a unique latent construct, although it evidenced convergent relationships with collateral report and cognitive testing of visuoperceptual abilities.

One theoretical implication of this study is that collateral report of executive functioning, visuospatial, and language difficulties had the strongest relationship—a small-to-medium effect—with functional impairment. Furthermore, neuropsychological tests of executive functioning had the strongest relationship with the TFLS compared with other cognitive domains. These findings correspond with other literature that has reported the impact of executive functioning on everyday functional decline (e.g., Yam, Gross, Prindle, & Marsiske, 2014 ) and clinicians may wish to place more weight on executive difficulties when determining functional decline. An unexpected finding was the consistent effect of collateral report of visuospatial problems on functioning despite visuospatial problems being the most infrequently reported domain. One hypothesis is that visuospatial abilities disproportionately impact performance on many of the visually mediated TFLS tasks. Another hypothesis is that visuospatial problems occur in later stages of neurodegenerative diseases (e.g., Alzheimer), which are also associated with more functional impairment. Despite the partial significance of collateral report, neuropsychological assessment of intellectual functions and other cognitive domains was a more robust predictor of everyday functioning, which corroborates the previous literature demonstrating limited relationships of collateral report with observed performance (e.g., Davis, Martin-Cook, Hynan, & Weiner, 2006 ).

This study has several limitations. First, the naturalistic clinical selection of the sample (i.e., only those referred for evaluation because of cognitive concerns) means that findings may not generalize to the general population. Furthermore, other sample characteristics, such as being 91% men and veteran, may limit generalization. For example, the observed relationships among functional and cognitive scales may differ among women or civilians with differing developmental trajectories. Moreover, non-normality of TFLS items may have attenuated reliability coefficients. However, non-normality is likely inherent to the construct of functioning and not an idiosyncrasy of our sample. As such, our reported coefficients provide useful information when considering the TFLS's psychometric properties. Another limitation is that not all neuropsychological measures were given to all participants due to the clinical nature of the evaluation (see Table 1 for exact numbers). Furthermore, not all participants had collateral sources complete rating forms, such that observed power for this subset was 0.33 for a small effect and 0.89 for a medium effect; other correlations were adequately powered.

One strength of the study is that it is the first published study to report latent structure and reliability information for the TFLS subscales. Another strength is the use of a mixed clinical sample that may reflect the varied diagnoses present in practice. Future studies may consider exploring the latent structure in different samples or using confirmatory techniques. The limited relationship with collateral report may be further explored to better understand what complaints are best predictive of performance-based functional decline.

In sum, the TFLS TS and Money and Calculation subscale are helpful tools as a part of functional assessment that may provide a brief assessment of functional information to inform diagnosis, recommendations, and interventions to improve the quality of life for individuals and their family members.

Supplementary Material

Supplementary material is available at Archives of Clinical Neuropsychology online .

Conflict of Interest

The authors have no financial interest with the subject matter discussed in the manuscript. The views expressed herein are those of the authors and do not necessarily reflect the views or the official policy of the Department of Veterans Affairs or U.S. Government.

References

American Psychiatric Association
. (
2013
).
Diagnostic and statistical manual of mental disorders
  (
5th ed.
).
Arlington, VA
:
American Psychiatric Association
.
Brown
,
T. A.
(
2015
).
Confirmatory factor analysis for applied research
  (
2nd ed.
).
New York
:
Guilford Press
.
Chaytor
,
N.
, &
Schmitter-Edgecombe
,
M.
(
2003
).
The ecological validity of neuropsychological tests: a review of the literature on everyday cognitive skills
.
Neuropsychology Review
  ,
13
,
181
197
.
Crawford
,
J. R.
,
Cullum
,
C. M.
,
Garthwaite
,
P. H.
,
Lycett
,
E.
, &
Allsopp
,
K. J.
(
2012
).
Point and interval estimates of percentile ranks for scores on The Texas Functional Living Scale
.
The Clinical Neuropsychologist
  ,
26
,
1154
1165
.
Cullum
,
C. M.
,
Saine
,
K.
,
Chan
,
L. D.
,
Martin-Cook
,
K.
,
Gray
,
K. F.
, &
Weiner
,
M. F.
(
2001
).
Performance-based instrument to assess functional capacity in dementia: The Texas Functional Living Scale
.
Neuropsychiatry, Neuropsychology, and Behavioral Neurology
  ,
14
,
103
108
.
Cullum
,
C. M.
,
Weiner
,
M. F.
, &
Saine
,
K. C.
(
2009
).
Texas Functional Living Scale: examiner's manual
  .
San Antonio, TX
:
Pearson
.
Davis
,
B. A.
,
Martin-Cook
,
K.
,
Hynan
,
L. S.
, &
Weiner
,
M. F.
(
2006
).
Caregivers’ perceptions of dementia patients’ functional abilities
.
American Journal of Alzheimer's Disease and Other Dementia
  ,
21
,
85
91
.
Delis
,
D. C.
,
Kramer
,
J. H.
,
Kaplan
,
E.
, &
Ober
,
B. A.
(
2000
).
California verbal learning test-second edition
  .
San Antonio, TX
:
The Psychological Corporation
.
Farias
,
S. T.
,
Mungas
,
D.
,
Reed
,
B. R.
,
Cahn-Weiner
,
D.
,
Jaqust
,
W.
,
Baynes
,
K.
, et al
. (
2008
).
The measurement of everyday cognition (ECog): scale development and psychometric properties
.
Neuropsychology
  ,
22
,
531
544
.
Gladsjo
,
J. A.
,
Schuman
,
C. C.
,
Evans
,
J. D.
,
Peavey
,
G. M.
,
Miller
,
S. W.
, &
Heaton
,
R. K.
(
1999
).
Norms for letter and category fluency: demographic corrections for age, education, and ethnicity
.
Assessment
  ,
6
,
147
178
.
Golden
,
C. J.
, &
Freshwater
,
S. M.
(
2002
).
Stroop color and word test: revised examiner's manual
  .
Wood Dale, IL
:
Stoelting Co
.
Heinemann
,
A. W.
, &
Mallinson
,
T.
(
2010
). Functional status and quality-of-life measures . In
R. G.
Frank
,
M.
Rosenthal
, &
B.
Caplan
(Eds.),
Handbook of rehabilitation psychology
  (
2nd ed.
). (pp.
147
164
).
Washington, D.C.
:
American Psychological Association
.
Loeb
,
P. A.
(
1996
).
ILS: Independent Living Scales manual
  .
San Antonio, TX
:
Psychological Corp: Harcourt Brace Jovanovich
.
Loewenstein
,
D.
, &
Acevedo
,
A.
(
2010
). The relationship between instrumental activities of daily living and neuropsychological performance . In
T. D.
Marcotte
, &
I.
Grant
(Eds.),
Neuropsychology of everyday functioning
  . (pp.
93
112
).
New York
:
Guilford Press
.
Loewenstein
,
D. A.
,
Amigo
,
E.
,
Duara
,
R.
,
Guterman
,
A.
,
Hurwitz
,
D.
,
Berkowitz
,
N.
, et al
. (
1989
).
A new scale for the assessment of functional status in Alzheimer's disease and related disorders
.
Journal of Gerontology
  ,
44
,
114
121
.
Raîche
,
G.
,
Walls
,
T. A.
,
Magis
,
D.
,
Riopel
,
M.
, &
Blais
,
J-G.
(
2013
).
Non-graphical solutions for Cattell's scree test
.
Methodology
  ,
9
,
23
29
.
Reitan
,
R. M.
, &
Wolfson
,
D.
(
1993
).
The Halstead-Reitan Neuropsychological Test Battery: theory and clinical interpretation
  (
2nd ed.
).
Tucson, AZ
:
Neuropsychology Press
.
Tombaugh
,
T. N.
(
1996
).
Test of Memory Malingering (TOMM)
  .
North Tonawanda, NY
:
MHS
.
Wechsler
,
D.
(
2008
).
Wechsler Adult Intelligence Scale-Fourth Edition (WAIS-IV) manual
  .
San Antonio, TX
:
Pearson
.
World Health Organization
. (
2001
).
International Classification of Functioning, Disability and Health: ICF
  .
Geneva, Switzerland
:
World Health Organization
.
Yam
,
A.
,
Gross
,
A. L.
,
Prindle
,
J. J.
, &
Marsiske
,
M.
(
2014
).
Ten-year longitudinal trajectories of older adults’ basic and everyday cognitive abilities
.
Neuropsychology
  ,
28
,
819
828
.

Supplementary data