Cognition assessment using the NIH Toolbox
Open accessAbstract
Cognition is 1 of 4 domains measured by the NIH Toolbox for the Assessment of Neurological and Behavioral Function (NIH-TB), and complements modules testing motor function, sensation, and emotion. On the basis of expert panels, the cognition subdomains identified as most important for health, success in school and work, and independence in daily functioning were Executive Function, Episodic Memory, Language, Processing Speed, Working Memory, and Attention. Seven measures were designed to tap constructs within these subdomains. The instruments were validated in English, in a sample of 476 participants ranging in age from 3 to 85 years, with representation from both sexes, 3 racial/ethnic categories, and 3 levels of education. This report describes the development of the Cognition Battery and presents results on test-retest reliability, age effects on performance, and convergent and discriminant construct validity. The NIH-TB Cognition Battery is intended to serve as a brief, convenient set of measures to supplement other outcome measures in epidemiologic and longitudinal research and clinical trials. With a computerized format and national standardization, this battery will provide a "common currency" among researchers for comparisons across a wide range of studies and populations.
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Written from the paper’s full text.
TL;DR
The NIH Toolbox Cognition Battery is a brief, computerized set of 7 measures covering 6 cognitive subdomains for ages 3–85, validated in 476 participants. It showed good-to-excellent test-retest reliability, expected age associations, and convergent/discriminant validity against gold-standard measures.
Key findings
- Test-retest reliability was strong: intraclass correlations for the entire sample ranged from 0.78 for the Picture Sequence Memory Test to 0.99 for the Oral Reading Recognition Test, with most other values above 0.90.
- Age associations were robust in children (ages 3–15; r = 0.58–0.87) and negative for most nonlanguage measures in adults (ages 20–85; r = −0.46 to −0.65); language measures showed little adult decline (Vocabulary r = 0.15; Reading r = −0.02).
- Convergent validity for ages 8–85 ranged from r = 0.48 to 0.93 (all p < 0.0001), while discriminant validity correlations ranged from r = 0.05 to 0.30.
- In children ages 3–6, all battery measures correlated with a general cognitive ability composite at r = 0.54 to 0.74.
Methods
- Subdomains were selected through expert surveys and panels (N = 102 experts); the battery includes Flanker, Dimensional Change Card Sort, List Sorting Working Memory, Picture Sequence Memory, Oral Reading Recognition, Picture Vocabulary, and Pattern Comparison Processing Speed tests.
- Validation sample: N = 476 community-dwelling participants ages 3–85, stratified by age, education, and race/ethnicity, recruited at Northwestern University and 5 additional sites; not all ages were sampled. One-third was randomly selected for retest 7–21 days later.
- Analyses included Pearson correlations between age and test performance separately for children and adults, intraclass correlations for test-retest reliability, and correlations with gold-standard measures for convergent and discriminant validity; for ages 3–6, only convergent validity with a general cognitive ability composite was assessed.
Limitations
- The paper states the battery was not developed as a clinical measure to screen for cognitive impairment or substitute for a full neuropsychological evaluation; future clinical-population studies are expected to provide additional validation.
- The paper states the validation sample was not population-based and participants tended to be highly educated, especially in the youngest and oldest groups; a more representative sampling strategy was used for the later NIH-TB norming study.
- The paper states gold-standard measures were scarce for ages 3–6, and no well-established measures were identified for attention, episodic memory, EF, and processing speed in that age group, so only convergent validity with general cognitive ability was measured.
- Evident from the text: age effects are cross-sectional correlations, so developmental and aging trajectories are inferred rather than directly observed longitudinally; test-retest reliability was assessed in only one-third of the sample.
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Claims the paper makes
0 of 17 cited sources checked · 0 supported · 0 flagged
- Findingown data§ Age effects.
Nonlanguage subdomain tests peaked in early adulthood and then declined in later adulthood at different rates depending on the measure.
“The nonlanguage subdomain tests in the battery, in contrast, conformed to the pattern expected with cognitive ability measures in that they peaked in early adulthood and then declined in later adulthood at different rates, depending on the measure.”
Quote in the paperSubstantial claim- Rests on an assumption: Cross-sectional age differences in Cognition Battery performance reflect developmental or aging changes rather than cohort effects.
- Findingown data§ Abstract
Many experts (57%) also listed a Global Score as important.
“Many (57%) also listed a “Global Score” as important.”
Quote in the paperNot a substantial claim- Rests on an assumption: The expert panel rankings and self-reported familiarity of experts provide a valid basis for identifying the most important cognitive subdomains for health, school/work success, and independence.
- Findingown data§ Age effects.
In children from 3 to 6 years of age, all NIH-TB Cognition Battery measures were significantly correlated (ranging from r = 0.54 to r = 0.74) with the measure of general cognitive ability (g).
“In children from 3 to 6 years of age, all NIH-TB Cognition Battery measures were significantly correlated (ranging from r 5 0.54 to r 5 0.74) with our measure of general cognitive ability (“g”), indicating that they are sensitive to a range of different cognitive ability levels within this age cohort.”
Quote in the paperSubstantial claim - Findingnone given§ Abstract
Expert panels identified Executive Function, Episodic Memory, Language, Processing Speed, Working Memory, and Attention as the most important cognition subdomains for health, success in school and work, and independence in daily functioning.
“On the basis of expert panels, the cognition subdomains identified as most important for health, success in school and work, and independence in daily functioning were Executive Function, Episodic Memory, Language, Processing Speed, Working Memory, and Attention.”
Quote in the paperSubstantial claim- Rests on an assumption: The expert panel rankings and self-reported familiarity of experts provide a valid basis for identifying the most important cognitive subdomains for health, school/work success, and independence.
- Findingown data§ Age effects.
With the exception of the language measures (Vocabulary and Reading, r = 0.15 and -0.02, respectively), age and test scores (r = -0.46 to -0.65) on the remaining NIH-TB Cognition Battery measures were negatively associated, with lower scores at higher age levels.
“With the exception of the language measures (Vocabulary and Reading, r 5 0.15 and 20.02, respectively), age and test scores (r 5 20.46 to 20.65) on the remaining NIH-TB Cognition Battery measures were negatively associated, with lower scores at higher age levels.”
Quote in the paperSubstantial claim
- Findingown data§ Age effects.
For all NIH-TB CB instruments, correlations for convergent validity measures ranged from r = 0.48 to r = 0.93 (all p < 0.0001).
“For all NIH-TB CB instruments, correlations for convergent validity measures ranged from r 5 0.48 to r 5 0.93 (all p , 0.0001), suggesting that the NIH-TB measures are tapping the desired constructs.”
Quote in the paperSubstantial claim - Findingreasoning§ Age effects.
Reading showed an especially steep improvement from age 3 to the early school years.
“Not surprisingly, Reading showed an especially steep improvement from age 3 to the early school years, when both formal and informal educational experiences ideally promote such development.”
Quote in the paperNot a substantial claim- Rests on an assumption: Cross-sectional age differences in Cognition Battery performance reflect developmental or aging changes rather than cohort effects.
- Findingown data§ Age effects.
Reading and Vocabulary scores showed expected associations with age, growing through adolescence and stabilizing in older adulthood.
“The Reading and Vocabulary scores showed the expected associations with age, growing through adolescence and stabilizing in older adulthood.”
Quote in the paperSubstantial claim- Rests on an assumption: Cross-sectional age differences in Cognition Battery performance reflect developmental or aging changes rather than cohort effects.
- Findingown data§ Age effects.
NIH Toolbox Reading and Vocabulary scores show improvement sustained into adulthood.
“(B) Results for NIH Toolbox Reading and Vocabulary scores (reported as a”
Quote in the paperNot a substantial claim- Rests on an assumption: Cross-sectional age differences in Cognition Battery performance reflect developmental or aging changes rather than cohort effects.
- Findingown data§ Age effects.
Correlations between NIH-TB measures and general cognitive ability in young children (ages 3-6 years) were high (0.54-0.74).
“The correlations between the NIH-TB measures and general cognitive ability, our index of convergent validity in young children (ages 3-6 years), were high (0.54-0.74), possibly supporting such a notion.”
Quote in the paperSubstantial claim - Findingown data§ Age effects.
The NIH-TB Picture Vocabulary Test showed gradual, linear improvement with age until the mid 50s and then stabilized.
“In contrast, the NIH-TB Picture Vocabulary Test showed gradual, linear improvement with age until the mid 50s and then stabilized”
Quote in the paperNot a substantial claim - Findingown data§ Age effects.
Correlations for discriminant validity measures ranged from r = 0.05 to r = 0.30.
“Correlations for discriminant validity measures ranged from r 5 0.05 to r 5 0.30, indicating lack of, or relatively weak, relationship with measures that tap different constructs.”
Quote in the paperSubstantial claim - Findingnone given§ Age effects.
Test-retest reliability of all NIH-TB measures is good to excellent across a large age range.
“The results suggest that test-retest reliability of all NIH-TB measures is good to excellent across a large age range.”
Quote in the paperSubstantial claim - Interpretationown data§ Subjects.
Convergent and discriminant validity results provide evidence that the Cognition Battery is measuring the intended constructs.
“Convergent and discriminant validity results provide evidence that the Cognition Battery is measuring the intended constructs.”
Quote in the paperSubstantial claim- Rests on an assumption: The gold standard measures used for convergent and discriminant validity are valid criterion measures of the intended constructs.
- Interpretationown data§ Age effects.
The NIH-TB measures have a lack of, or relatively weak, relationship with measures that tap different constructs.
“Correlations for discriminant validity measures ranged from r 5 0.05 to r 5 0.30, indicating lack of, or relatively weak, relationship with measures that tap different constructs.”
Quote in the paperSubstantial claim - Study design and conductnone given§ Abstract
The rationale for specific cognitive constructs within subdomains and instrument selection was based on a systematic review of the literature, including evidence of the known biological associations of each.
“The rationale for specific cognitive constructs within subdomains and instrument selection was based on a systematic review of the literature, including evidence of the known biological associations of each.”
Quote in the paperSubstantial claim - Study design and conductreasoning§ Subjects.
In the 3- to 6-year-old age group, only convergent validity was measured between the Cognition Battery measures and a measure of general cognitive ability (g) obtained by averaging z scores of the WPPSI-3 Block Design subtest and the PPVT-4.
“Thus, in this age group, only convergent validity was measured between the Cognition Battery measures and a measure of general cognitive ability (i.e., “g”) obtained by averaging z scores of the Wechsler Preschool and Primary Scale of Intelligence-3rd edition Block Design subtest 52 and the Peabody Picture Vocabulary Test-4th edition.53”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites [52]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- cites [53]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Study design and conductcitation§ Age effects.
Evaluating construct validity in young children (ages 3-6 years) was challenging because of the absence of specific gold standard measures of targeted constructs appropriate for these ages.
“Evaluating construct validity in young children (ages 3-6 years) was challenging because of the absence of specific gold standard measures of targeted constructs appropriate for these ages.”
Quote in the paperSubstantial claim - Interpretationown data§ Age effects.
The NIH-TB measures are tapping the desired constructs.
“For all NIH-TB CB instruments, correlations for convergent validity measures ranged from r 5 0.48 to r 5 0.93 (all p , 0.0001), suggesting that the NIH-TB measures are tapping the desired constructs.”
Quote in the paperSubstantial claim
- May combine two claims. 21
- Classified as probably not a substantial claim. 12
May combine two claims.
Findingown data§ Age effects.NIH Toolbox Picture Sequence Memory Test scores show improvement into early adulthood and then decline from the 50s on.
“(A) NIH Toolbox Picture Sequence Memory Test scores show improvement into early adulthood and then decline from the 50s on.”
Quote in the paperNot a substantial claim- Rests on an assumption: Cross-sectional age differences in Cognition Battery performance reflect developmental or aging changes rather than cohort effects.
May combine two claims.
Findingown data§ Age effects.Language subdomain tests peaked somewhat later than measures of other cognitive subdomains and then remained relatively stable into the ninth decade of life.
“The Language subdomain tests, as expected, are experience-based and peaked somewhat later than measures of other cognitive subdomains, and then remained relatively stable even into the ninth decade of life.”
Quote in the paperNot a substantial claim- Rests on an assumption: Cross-sectional age differences in Cognition Battery performance reflect developmental or aging changes rather than cohort effects.
May combine two claims.
Findingown data§ Subjects.Test-retest reliability was strong for the entire sample and separately for children (ages 3-15 years) and adults (ages 20-85 years).
“Test-retest reliability was strong for the entire sample and separately for children (ages 3-15 years) and adults (ages 20-85 years; table 3).”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S1 (asserted), S3 (load-bearing), S4 (based). May combine two claims.
Findingnone given§ Age effects.Gold standard tests related to the Cognition Battery instruments in the expected ways for participants across a wide age band (ages 8-85 years), demonstrating both convergent and discriminant validity.
“The”
Quote in the paperNot a substantial claim- Rests on an assumption: The gold standard tests are valid measures of the intended cognitive constructs.
May combine two claims.
Findingown data§ Age effects.Oral Reading Recognition showed a much sharper increase until early grade-school years (age 7-8) and then followed the same pattern of more gradual improvement and then stability in the older age groups.
“whereas Oral Reading Recognition showed a much sharper increase until early grade-school years (age 7-8) and then followed the same pattern of more gradual improvement and then stability in the older age groups (figure , B).”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown data§ Subjects.Intraclass correlation coefficients for the entire sample on the NIH Toolbox measures ranged from 0.78 for the Picture Sequence Memory Test to 0.99 on the Oral Reading Recognition Test, with most other values falling above 0.90.
“Intraclass correlation coefficients for the entire sample on the NIH Toolbox measures ranged from 0.78 for the Picture Sequence Memory Test to 0.99 on the Oral Reading Recognition Test, with most other values falling above 0.90.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown data§ Age effects.All NIH-TB Cognition Battery measures showed robust associations between test performance and age in the child group (r = 0.58-0.87), where scores improved with age.
“All NIH-TB Cognition Battery measures showed robust associations between test performance and age in the child group (r 5 0.58-0.87),where scores improved with age.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Findingown data§ Age effects.The participants in this study (or their parents, in the case of children) tended to be rather highly educated, particularly in the youngest and oldest groups.
“Thus, the participants in this study (or their parents, in the case of children) tended to be rather highly educated, particularly in the youngest and oldest groups (see table 1).”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown data§ Age effects.Data are presented for 208 normal children (age 3-15 years) and 268 normal adults (age 20-85 years) on 3 important psychometric characteristics: test-retest reliability, sensitivity to cognitive growth during childhood and age-related decline during adulthood, and construct validity.
“Data are presented for 208 normal children (age 3-15 years) and 268 normal adults (age 20-85 years) on 3 important psychometric characteristics: test-retest reliability, sensitivity to cognitive growth during childhood and age-related decline during adulthood, and construct validity.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown data§ Age effects.On the Picture Sequence Memory Test, performance improved during childhood and early adolescence, with gradual decline in scores across adult age ranges beginning in the 30s.
“Thus, on the Picture Sequence Memory Test, performance improved during childhood and early adolescence, with gradual decline in scores across adult age ranges beginning in the 30s (figure , A).”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown data§ AbstractThe two top-ranked cognitive subdomains by experts were Executive Function (95%) and Episodic Memory (93%), followed by Language (55%), Processing Speed (52%), and Attention (50%).
“The 2 top-ranked subdomains were Executive Function (EF) (95%) and Episodic Memory (93%), followed by Language (55%), Processing Speed (52%), and Attention (50%).”
Quote in the paperSubstantial claim- Rests on an assumption: The expert panel rankings and self-reported familiarity of experts provide a valid basis for identifying the most important cognitive subdomains for health, school/work success, and independence.
Probably not a substantial claim: may not pass S3 (load-bearing).
Premisecitation§ AbstractLanguage scores can predict occupational attainment and performance.
“Language scores can predict occupational attainment and performance.29”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [29]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
May combine two claims.
Study design and conductnone given§ AbstractThe instruments were validated in English, in a sample of 476 participants ranging in age from 3 to 85 years, with representation from both sexes, 3 racial/ethnic categories, and 3 levels of education.
“The instruments were validated in English, in a sample of 476 participants ranging in age from 3 to 85 years, with representation from both sexes, 3 racial/ethnic categories, and 3 levels of education.”
Quote in the paperSubstantial claim- Rests on an assumption: The validation sample of 476 community-dwelling individuals is adequate for drawing conclusions about the Cognition Battery's validity across the 3-85 age range.
Probably not a substantial claim: may not pass S3 (load-bearing).
Interpretationnone given§ Age effects.Language subdomain tests are experience-based.
“The Language subdomain tests, as expected, are experience-based and peaked somewhat later than measures of other cognitive subdomains, and then remained relatively stable even into the ninth decade of life.”
Quote in the paperNot a substantial claim- Rests on an assumption: Cross-sectional age differences in Cognition Battery performance reflect developmental or aging changes rather than cohort effects.
May combine two claims.
Premisenone given§ Age effects.The Cognition Battery has 7 computerized instruments that measure 6 ability subdomains important for cognitive health from the ages of 3 to 85 years.
“The Cognition Battery has 7 computerized instruments that measure 6 ability subdomains important for cognitive health from the ages of 3 to 85 years.”
Quote in the paperNot a substantial claimClassified as probably not a substantial claim.
Study design and conductnone given§ Subjects.One-third of the sample was randomly selected to repeat testing 7 to 21 days later to assess test-retest reliability.
“One-third of the sample was randomly selected to repeat testing 7 to 21 days later to assess test-retest reliability.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Premisecitation§ AbstractProcessing speed measures are among the most sensitive indicators of cerebral dysfunction, and slowed processing speed has been demonstrated in traumatic brain injury, multiple sclerosis, Parkinson disease, symptomatic HIV, chronic fatigue syndrome, dementia, and schizophrenia.
“PS measures are among the most sensitive indicators of cerebral dysfunction, 41 and slowed PS has been demonstrated in traumatic brain injury, multiple sclerosis, Parkinson disease, symptomatic HIV, chronic fatigue syndrome, dementia, and schizophrenia.42”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites [41]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- cites [42]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
May combine two claims.
Study design and conductnone given§ Age effects.The subject sample deliberately emphasized representation of ethnic minorities (almost 50%) and the oldest and youngest groups (3-6 years and 65-85 years; together, 48%) to ensure that the tests would perform as needed in these important segments of the population.
“The subject sample for this study deliberately emphasized representation of ethnic minorities (almost 50%) and the oldest and youngest groups (3-6 years and 65-85 years; together, 48%) to ensure that the tests would perform as needed in these important segments of the population.”
Quote in the paperSubstantial claim- Rests on an assumption: The validation sample of 476 community-dwelling individuals is adequate for drawing conclusions about the Cognition Battery's validity across the 3-85 age range.
May combine two claims.
Premisecitation§ AbstractVocabulary is highly associated with general measures of crystallized intelligence, overall cognitive functioning, and success in school and work.
“Vocabulary represents the lexical component of language and is highly associated with general measures of “crystallized intelligence,” or “g c ,” 33 overall cognitive functioning, and success in school and work.29,34”
Quote in the paperSubstantial claim0 of 3 sources checked- cites [33]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- cites [29]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- cites [34]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Probably not a substantial claim: may not pass S3 (load-bearing).
Premisecitation§ AbstractWorking memory span is thought to double in capacity between the ages of 5 and 10.
“WM improves significantly as children develop and WM span is thought to double in capacity between the ages of 5 and 10. 20”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [20]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
May combine two claims.
Interpretationown data§ Subjects.Age associations reflect the validity of the tests for measuring cognitive development during childhood and age-related cognitive decline during adulthood.
“Age associations reflect the validity of the tests for measuring cognitive development during childhood and age-related cognitive decline during adulthood.”
Quote in the paperSubstantial claim- Rests on an assumption: Cross-sectional age differences in test performance reflect developmental growth during childhood and aging-related decline during adulthood.
May combine two claims.
Premisecitation§ AbstractExecutive function is very vulnerable to aging, and comparisons across the lifespan yield an inverted U-shaped pattern, with early age-related improvement followed by later age-related decline.
“EF is very vulnerable to aging, 4 and comparisons across the lifespan yield an inverted U-shaped pattern, with early age-related improvement followed by later age-related decline.5”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites [4]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- cites [5]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
May combine two claims.
Study design and conductnone given§ Subjects.Gold standard measures were scarce for 3- to 6-year-olds, and the authors were unable to identify well-established measures to test convergent or discriminant validity in this age group for attention, episodic memory, EF, and processing speed.
“Gold standard measures were scarce for 3-to 6-year-olds, and we were unable to identify well-established measures to test convergent or discriminant validity in this age group for the measures of attention, episodic memory, EF, and PS.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Premisecitation§ AbstractEpisodic memory is one of the first cognitive functions to show age-related decline and is the most susceptible to developmental disorders, brain trauma, and neurodegenerative diseases such as Alzheimer disease.
“It is one of the first cognitive functions to show age-related decline and the most susceptible to developmental disorders, 25 brain trauma, and neurodegenerative diseases such as Alzheimer disease.26”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites [25]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- cites [26]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Study design and conductnone given§ Age effects.The NIH-TB Cognition Battery was not developed as a clinical measure to either screen for cognitive impairment or to substitute for a full, competent neuropsychological evaluation.
“The NIH-TB Cognition Battery was not developed as a clinical measure to either screen for cognitive impairment or to substitute for a full, competent neuropsychological evaluation.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Interpretationcitation§ Age effects.The lack of such measures may reflect that different subdomains of cognition become more differentiated with experience and development.
“The lack of such measures may reflect the fact that different subdomains of cognition become more differentiated with experience and development.55”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [55]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Probably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductnone given§ Subjects.The sample (N=476) was based on a stratification plan to include adequate numbers of individuals within age bands, level of education, and racial/ethnic backgrounds.
“The sample (N 5 476) was based on a stratification plan to include adequate numbers of individuals within age bands, level of education, and racial/ethnic backgrounds.”
Quote in the paperNot a substantial claim- Rests on an assumption: The validation sample of 476 community-dwelling individuals is adequate for drawing conclusions about the Cognition Battery's validity across the 3-85 age range.
May combine two claims.
Premisecitation§ AbstractSingle-word reading recognition tasks are strong predictors of health and cognitive outcomes across the lifespan, and performance on these tasks is an estimate of the quality of education, accounting for some of the racial/ethnic differences on neuropsychological test performance seen in older adults.
“Single-word reading recognition tasks are strong predictors of health and cognitive outcomes across the lifespan, and performance on these tasks is also an estimate of the quality of education, accounting for some of the racial/ethnic differences on neuropsychological test performance seen in older adults.31,32”
Quote in the paperSubstantial claim0 of 2 sources checked- cites [31]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- cites [32]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Probably not a substantial claim: may not pass S3 (load-bearing).
Premisecitation§ AbstractExecutive function can be divided into three partially independent subcomponents: set shifting, inhibitory control, and updating/working memory.
“Based on factor-analytic work, there is an emerging consensus that EF can be divided into 3 partially independent subcomponents: set shifting, inhibitory control, and updating/working memory.6”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [6]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
The paper relies on this without support.
The expert panel rankings and self-reported familiarity of experts provide a valid basis for identifying the most important cognitive subdomains for health, school/work success, and independence.
“On the basis of expert panels, the cognition subdomains identified as most important for health, success in school and work, and independence in daily functioning were Executive Function, Episodic Memory, Language, Processing Speed, Working Memory, and Attention.”
“Information was requested from experts (N 5 102) who reported sufficient familiarity with cognition to make recommendations for specific subdomains of importance.”
The paper relies on this without support.
Cross-sectional age differences in test performance reflect developmental growth during childhood and aging-related decline during adulthood.
“Age associations reflect the validity of the tests for measuring cognitive development during childhood and age-related cognitive decline during adulthood.”
The paper relies on this without support.
The gold standard measures used for convergent and discriminant validity are valid criterion measures of the intended constructs.
“Convergent validity was assessed by correlations between each NIH-TB measure and a well-established “gold standard” measure of the same construct; evidence of discriminant validity was assessed by correlations with gold standards of a different cognitive construct.”
The paper relies on this without support.
The validation sample of 476 community-dwelling individuals is adequate for drawing conclusions about the Cognition Battery's validity across the 3-85 age range.
“The sample (N 5 476) was based on a stratification plan to include adequate numbers of individuals within age bands, level of education, and racial/ethnic backgrounds.”
“The subject sample for this study deliberately emphasized representation of ethnic minorities (almost 50%) and the oldest and youngest groups (3-6 years and 65-85 years; together, 48%) to ensure that the tests would perform as needed in these important segments of the population.”
The authors state this as an assumption.
Adequate test-retest reliability is essential for a cognitive battery intended for longitudinal studies.
“Adequate test-retest reliability was considered essential for the NIH-TB Cognition Battery, particularly because of its anticipated use in longitudinal studies.”
The paper relies on this without support.
Cross-sectional age differences in Cognition Battery performance reflect developmental or aging changes rather than cohort effects.
“We presented the relationship of Cognition Battery performance with age in cognitively normal children and adults.”
The paper relies on this without support.
The gold standard tests are valid measures of the intended cognitive constructs.
“The”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The NIHTB-CB measures attention, working memory, language, processing speed, and executive functioning.
“The NIH Toolbox Cognition Battery (NIHTB-CB) measures attention, working memory, language, processing speed, and executive functioning.”
From NIH toolbox cognition tests following traumatic brain injury: Frequency of low scores. (2017) · cites this paper as Weintraub et al., 2013
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
Each contradiction between two passages listed here was confirmed by an independent check.
Conflicting ages for the start of episodic-memory decline
MinorThe results say Picture Sequence Memory scores begin declining in the 30s, whereas the figure caption says they decline from the 50s on.
“Thus, on the Picture Sequence Memory Test, performance improved during childhood and early adolescence, with gradual decline in scores across adult age ranges beginning in the 30s (figure , A).”
“(A) NIH Toolbox Picture Sequence Memory Test scores show improvement into early adulthood and then decline from the 50s on.”
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“52”
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Self-citationPersistent neurologic symptoms and cognitive dysfunction in non-hospitalized COVID-19 “long haulers”
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Targeted enhancement of cortical-hippocampal brain networks and associative memory
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“Test-retest interval range 7 to 21 days, n = 89 [13].”
MethodInfluentialReliability and Validity of Composite Scores from the NIH Toolbox Cognition Battery in Adults
Heaton, R. K., Akshoomoff, N., Tulsky, D., Mungas, D., Weintraub, S., Dikmen, S., Beaumont, J., Casaletto, K. B., Conway, K., Slotkin, J., et al. (2014) · Journal of the International Neuropsychological Society · doi:10.1017/s1355617714000241 · Cited by 437 · see citing works
Self-citationPhysical Activity and Cognitive Vitality
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“For example, the National Institutes of Health Cognitive Toolbox (Weintraub et al. 2013) is one attempt to identify theoretically driven cognitive measures that could be used to facilitate comparisons across studies.”
MethodTrial of the MIND diet for prevention of cognitive decline in older persons
Barnes, L. L., Dhana, K., Liu, X., Carey, V. J., Ventrelle, J., Johnson, K., Hollings, C. S., Bishop, L., Laranjo, N., Stubbs, B. J., et al. (2023) · New England Journal of Medicine · doi:10.1056/nejmoa2302368 · Cited by 366 · see citing works
The ABCD study: understanding the development of risk for mental and physical health outcomes
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“The base of the neurocognitive assessment for ABCD Study is the NIH Toolbox [26, 27], with the complete cognitive Toolbox administered at baseline, and the majority of tasks administered every 2 years.”
MethodNIH Toolbox Cognition Battery (CB): Validation of Executive Function Measures in Adults
Zelazo, P. D., Anderson, J. E., Richler, J., Wallner-Allen, K., Beaumont, J. L., Conway, K. P., Gershon, R., & Weintraub, S. (2014) · Journal of the International Neuropsychological Society · doi:10.1017/s1355617714000472 · Cited by 350 · see citing works
“An initial publication (Weintraub et al., 2013) introduced the Cognition Battery along with the rest of the NIH Toolbox and provided an overview and summary data from the entire validation sample, including both children and adults.”
MethodSelf-citationThe evolution of episodic memory
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Weintraub, S., Dikmen, S. S., Heaton, R. K., Tulsky, D. S., Zelazo, P. D., Slotkin, J., Carlozzi, N. E., Bauer, P. J., Wallner-Allen, K., Fox, N., et al. (2014) · Journal of the International Neuropsychological Society · doi:10.1017/s1355617714000320 · Cited by 342 · see citing works
Self-citationThe Human Connectome Project: A retrospective
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Childhood maltreatment and its effect on neurocognitive functioning: timing and chronicity matter
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“Self-control is a concept encompassing top-down neurocognitive processes involved in explicit, goal-directed processes (Weintraub et al., 2013).”
BackgroundAkshoomoff, N., Beaumont, J. L., Bauer, P. J., Dikmen, S. S., Gershon, R. C., Mungas, D., Slotkin, J., Tulsky, D., Weintraub, S., Zelazo, P. D., et al. (2013) · Monographs of the Society for Research in Child Development · doi:10.1111/mono.12038 · Cited by 299 · see citing works
“We expected all three summary scores to increase fairly rapidly with age, in contrast to results obtained during adulthood (Weintraub et al., 2013).”
Self-citationCasaletto, K. B., Umlauf, A., Beaumont, J., Gershon, R., Slotkin, J., Akshoomoff, N., & Heaton, R. K. (2015) · Journal of the International Neuropsychological Society · doi:10.1017/s1355617715000351 · Cited by 271 · see citing works
“Detailed descriptions of the individual Toolbox Cognition measures are provided in Weintraub et al. (2013), and Heaton et al. (2014) describes the validation of the Composite Scores.”
MethodSelf-citationNIH EXAMINER: Conceptualization and Development of an Executive Function Battery
Kramer, J. H., Mungas, D., Possin, K. L., Rankin, K. P., Boxer, A. L., Rosen, H. J., Bostrom, A., Sinha, L., Berhel, A., & Widmeyer, M. (2013) · Journal of the International Neuropsychological Society · doi:10.1017/s1355617713001094 · Cited by 262 · see citing works
Self-citationRelation between Speech-in-Noise Threshold, Hearing Loss and Cognition from 40–69 Years of Age
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Improving Methodological Standards in Behavioral Interventions for Cognitive Enhancement
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Current advances in digital cognitive assessment for preclinical Alzheimer's disease
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The roles of patterning and spatial skills in early mathematics development
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Human Connectomics across the Life Span
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The NIH Toolbox Cognition Battery: Results from a large normative developmental sample (PING).
Akshoomoff, N. A., Newman, E. R., Thompson, W. K., McCabe, C. J., Bloss, C. S., Chang, L., Amaral, D. G., Casey, B. J., Ernst, T. M., Frazier, J. A., et al. (2013) · Neuropsychology · doi:10.1037/neu0000001 · Cited by 203 · see citing works
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“More research is needed to determine whether tasks such as the Flanker Inhibitory Control Test and the Dimensional Change Card Sort Task from the National Institutes of Health Toolbox [78] would be sensitive to changes in executive function in the preclinical stages of AD.”
Brunt, V. E., LaRocca, T. J., Bazzoni, A. E., Sapinsley, Z. J., Miyamoto-Ditmon, J., Gioscia-Ryan, R. A., Neilson, A. P., Link, C. D., & Seals, D. R. (2021) · GeroScience · doi:10.1007/s11357-020-00257-2 · Cited by 197 · see citing works
Language Measures of the NIH Toolbox Cognition Battery
Gershon, R. C., Cook, K. F., Mungas, D., Manly, J. J., Slotkin, J., Beaumont, J. L., & Weintraub, S. (2014) · Journal of the International Neuropsychological Society · doi:10.1017/s1355617714000411 · Cited by 189 · see citing works
“The NIH Toolbox Picture Vocabulary Test and NIH Toolbox Oral Reading Recognition Test were released by the National Institutes of Health for royalty-free use by health and education researchers in late 2012 (see www.nihtoolbox. org for current information).”
BackgroundInfluentialSelf-citationNIH Toolbox Cognition Battery (NIHTB-CB): List Sorting Test to Measure Working Memory
Tulsky, D. S., Carlozzi, N., Chiaravalloti, N. D., Beaumont, J. L., Kisala, P. A., Mungas, D., Conway, K., & Gershon, R. (2014) · Journal of the International Neuropsychological Society · doi:10.1017/s135561771400040x · Cited by 196 · see citing works
“The participants in the validation phase are described in detail in Weintraub et al. (2013).”
BackgroundMethodInfluentialSelf-citationBrain–phenotype models fail for individuals who defy sample stereotypes
Greene, A. S., Shen, X., Noble, S., Horien, C., Hahn, C. A., Arora, J., Tokoglu, F., Spann, M. N., Carrión, C. I., Barron, D. S., et al. (2022) · Nature · doi:10.1038/s41586-022-05118-w · Cited by 167 · see citing works
Digital neuropsychology: challenges and opportunities at the intersection of science and software
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Vitamin C Status and Cognitive Function: A Systematic Review
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Fathers matter: The role of father parenting in preschoolers’ executive function development
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The home math environment: More than numeracy
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Effects of Mindfulness Training and Exercise on Cognitive Function in Older Adults
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“This age range was selected as this is an important time period of neurogenesis related to EF, and EF skills would have typically developed sufficiently to measure by this time period((6)).”
BackgroundAssociation of lead-exposure risk and family income with childhood brain outcomes
Marshall, A. T., Betts, S., Kan, E. C., McConnell, R., Lanphear, B. P., & Sowell, E. R. (2020) · Nature Medicine · doi:10.1038/s41591-019-0713-y · Cited by 164 · see citing works
Romer, A. L., & Pizzagalli, D. (2021) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2021.100994 · Cited by 137 · see citing works
“org) (Weintraub et al., 2013) were administered to children on computer tablets monitored by an experimenter at baseline (Luciana et al.”
MethodMoore, R. C., Swendsen, J. D., & Depp, C. A. (2017) · International Journal of Methods in Psychiatric Research · doi:10.1002/mpr.1562 · Cited by 136 · see citing works
“Studies that used cognitive assessments delivered by research staff on mobile devices (e.g. the NIH Toolbox; Weintraub et al., 2013), regardless of the setting, or administered on a tablet (e.g. iPad) instead of an ambulatory mobile device, were excluded.”
MethodCroarkin, P. E., Elmaadawi, A. Z., Aaronson, S. T., Schrodt, G. R., Holbert, R. C., Verdoliva, S., Heart, K. L., Demitrack, M. A., & Strawn, J. R. (2020) · Neuropsychopharmacology · doi:10.1038/s41386-020-00829-y · Cited by 133 · see citing works
Hessl, D., Sansone, S. M., Berry-Kravis, E., Riley, K., Widaman, K. F., Abbeduto, L., Schneider, A., Coleman, J., Oaklander, D., Rhodes, K. C., et al. (2016) · Journal of Neurodevelopmental Disorders · doi:10.1186/s11689-016-9167-4 · Cited by 126 · see citing works
Self-citationBerry-Kravis, E. M., Harnett, M. D., Reines, S. A., Reese, M. A., Ethridge, L. E., Outterson, A. H., Michalak, C., Furman, J., & Gurney, M. E. (2021) · Nature Medicine · doi:10.1038/s41591-021-01321-w · Cited by 131 · see citing works
Karcher, N. R., O’Brien, K. J., Kandala, S., & Barch, D. M. (2019) · Biological Psychiatry · doi:10.1016/j.biopsych.2019.01.013 · Cited by 125 · see citing works
“(70) for descriptions of individual NIHTB-CB tests] (71).”
BackgroundMeasuring the development of inhibitory control: The challenge of heterotypic continuity
Petersen, I. T., Hoyniak, C. P., McQuillan, M. E., Bates, J. E., & Staples, A. D. (2016) · Developmental Review · doi:10.1016/j.dr.2016.02.001 · Cited by 127 · see citing works
“Future studies might also develop measures that maintain construct validity invariance across lengthy spans of development (for attempts, see Bauer & Zelazo, 2014; Carlson & Zelazo, 2014; Weintraub et al., 2013).”
BackgroundMarek, S. A., Tervo‐Clemmens, B., Nielsen, A. N., Wheelock, M. D., Miller, R. L., Laumann, T. O., Earl, E., Foran, W., Cordova, M., Doyle, O. J., et al. (2019) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2019.100706 · Cited by 122 · see citing works
Novel Cognitive Paradigms for the Detection of Memory Impairment in Preclinical Alzheimer’s Disease
Loewenstein, D., Curiel, R. E., Duara, R., & Herman Buschke, L. (2017) · Assessment · doi:10.1177/1073191117691608 · Cited by 126 · see citing works
“This was developed in 2004 to supplement outcome measures in epidemiologic and longitudinal research and clinical trials (Beaumont et al., 2013; Weintraub et al., 2013).”
MethodMahinrad, S., Kurian, S., Garner, C. R., Sedaghat, S., Nemeth, A. J., Moscufo, N., Higgins, J. P., Jacobs, D. R., Hausdorff, J. M., Lloyd‐Jones, D. M., et al. (2019) · Circulation · doi:10.1161/circulationaha.119.042502 · Cited by 125 · see citing works
Measuring cognition and function in the preclinical stage of Alzheimer's disease
Weintraub, S., Carrillo, M., Farias, S., Goldberg, T., Hendrix, J. A., Jaeger, J., Knopman, D., Langbaum, J., Park, D. C., Ropacki, M., et al. (2018) · Alzheimer's & Dementia · doi:10.1016/j.trci.2018.01.003 · Cited by 120 · see citing works
“For example, markers of AD neuropathology were associated with a decline in episodic memory, semantic memory, and working memory [16].”
BackgroundMethodNeville, R. D., McArthur, B. A., Eirich, R., Lakes, K. D., & Madigan, S. (2021) · Journal of Child Psychology and Psychiatry · doi:10.1111/jcpp.13425 · Cited by 109 · see citing works
The NIH Toolbox Pattern Comparison Processing Speed Test: Normative Data
Carlozzi, N. E., Beaumont, J. L., Tulsky, D. S., & Gershon, R. C. (2015) · Archives of Clinical Neuropsychology · doi:10.1093/arclin/acv031 · Cited by 115 · see citing works
Self-citationViterbori, P., Usai, M. C., Traverso, L., & Franchis, V. D. (2015) · Journal of Experimental Child Psychology · doi:10.1016/j.jecp.2015.06.014 · Cited by 118 · see citing works
III. NIH toolbox cognition battery (CB): measuring episodic memory
Bauer, P. J., Dikmen, S. S., Heaton, R. K., Mungas, D., Slotkin, J., & Beaumont, J. L. (2013) · Monographs of the Society for Research in Child Development · doi:10.1111/mono.12033 · Cited by 128 · see citing works
Self-citationClifford, S. A., Davies, S., & Wake, M. A. (2019) · BMJ Open · doi:10.1136/bmjopen-2017-020261 · Cited by 114 · see citing works
Machine learning prediction of cognition from functional connectivity: Are feature weights reliable?
Tian, Y., & Zalesky, A. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.118648 · Cited by 105 · see citing works
Acoustic enhancement of sleep slow oscillations in mild cognitive impairment
Papalambros, N. A., Weıntraub, S., Chen, T. Y., Grimaldi, D., Santostasi, G., Paller, K. A., Zee, P. C., & Malkani, R. G. (2019) · Annals of Clinical and Translational Neurology · doi:10.1002/acn3.796 · Cited by 114 · see citing works
“(NIHTB, Data S1), which includes a brief set of measures of working memory, picture memory, language and executive attention.(37,38) The NIHTB was administered in the morning in both stim and sham conditions.”
MethodSpeech-in-noise representation in the aging midbrain and cortex: Effects of hearing loss
Presacco, A., Simon, J. Z., & Anderson, S. (2019) · PLoS ONE · doi:10.1371/journal.pone.0213899 · Cited by 114 · see citing works
Bidwell, L. C., Ellingson, J. M., Karoly, H. C., YorkWilliams, S. L., Hitchcock, L. N., Tracy, B. L., Klawitter, J., Sempio, C., Bryan, A. D., & Hutchison, K. E. (2020) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2020.0927 · Cited by 112 · see citing works
Genome‐wide association study of shared components of reading disability and language impairment
Eicher, J. D., Powers, N. R., Miller, L. L., Akshoomoff, N. A., Amaral, D. G., Bloss, C. S., Libiger, O., Schork, N. J., Darst, B. F., Casey, B. J., et al. (2013) · Genes Brain & Behavior · doi:10.1111/gbb.12085 · Cited by 108 · see citing works
“Subjects completed the validated study version of the NIH Toolbox Cognition Battery, in which two language- and reading-related tasks were completed: the Oral Reading Recognition Test and Picture Vocabulary Test (Akshoomoff et al. in press; Weintraub et al. 2013).”
MethodAdvances in applications of item response theory to clinical assessment.
Thomas, M. L. (2019) · Psychological Assessment · doi:10.1037/pas0000597 · Cited by 106 · see citing works
“Cognition assessment using the NIH Toolbox.”
MethodInfluentialWalker, W. C., Carne, W. F., Franke, L. M., Nolen, T. L., Dikmen, S. D., Cifu, D. X., Wilson, K. E., Belanger, H. G., & Williams, R. L. (2016) · Brain Injury · doi:10.1080/02699052.2016.1219061 · Cited by 105 · see citing works
“battery takes 30 minutes to administer [32].”
Self-citationPatterns of Social Determinants of Health and Child Mental Health, Cognition, and Physical Health
Xiao, Y., Mann, J. J., Chow, J. C., Brown, T. T., Snowden, L. R., Yip, P. S.-F., Tsai, A. C., Hou, Y., Pathak, J., Wang, F., et al. (2023) · Archives of Pediatrics and Adolescent Medicine · doi:10.1001/jamapediatrics.2023.4218 · Cited by 108 · see citing works
European Prevention of Alzheimer’s Dementia Longitudinal Cohort Study (EPAD LCS): study protocol
Solomon, A., Kivipelto, M., Molinuevo, J. L., Tom, B. D. M., & Ritchie, C. W. (2018) · BMJ Open · doi:10.1136/bmjopen-2017-021017 · Cited by 103 · see citing works
The Role of Resting-State Network Functional Connectivity in Cognitive Aging
Hausman, H. K., O’Shea, A. M., Kraft, J. N., Boutzoukas, E. M., Evangelista, N. D., Etten, E. J. V., Bharadwaj, P. K., Smith, S. G., Porges, E. C., Hishaw, G. A., et al. (2020) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2020.00177 · Cited by 101 · see citing works
Guest Editorial: Auditory Processing Disorder
Moore, D. R. (2018) · Ear and Hearing · doi:10.1097/aud.0000000000000582 · Cited by 100 · see citing works
Post-Stroke Cognitive Impairments and Responsiveness to Motor Rehabilitation: A Review
VanGilder, J. L., Hooyman, A., Peterson, D. S., & Schaefer, S. Y. (2020) · Current Physical Medicine and Rehabilitation Reports · doi:10.1007/s40141-020-00283-3 · Cited by 104 · see citing works
Improving high school students' executive functions through digital game play
Homer, B. D., Plass, J. L., Raffaele, C., Ober, T. M., & Ali, A. (2017) · Computers & Education · doi:10.1016/j.compedu.2017.09.011 · Cited by 102 · see citing works
The long-term effects of cocaine use on cognitive functioning: A systematic critical review
Frazer, K. M., Richards, Q., & Keith, D. R. (2018) · Behavioural Brain Research · doi:10.1016/j.bbr.2018.04.005 · Cited by 97 · see citing works
Effect of informational content of noise on speech representation in the aging midbrain and cortex
Presacco, A., Simon, J. Z., & Anderson, S. (2016) · Journal of Neurophysiology · doi:10.1152/jn.00373.2016 · Cited by 95 · see citing works
Pfister, K. M., Zhang, L., Miller, N. C., Ingolfsland, E. C., Demerath, E. W., & Ramel, S. E. (2018) · Pediatric Research · doi:10.1038/s41390-018-0158-x · Cited by 94 · see citing works
“Data Analysis Multiple linear regression was performed to assess the relationship between body composition and anthropometric measurements and SOP (using latency to P100 on the VEP, where shorter (smaller) latency indicates faster processing, and raw score from NTPST, where a higher score means faster processing) in a…”
MethodInfluentialImpacts of dance on cognition, psychological symptoms and quality of life in Parkinson’s disease
Haputhanthirige, N. K. H., Sullivan, K. A., Moyle, G., Brauer, S., Jeffrey, E. R., & Kerr, G. (2019) · Neurorehabilitation · doi:10.3233/nre-192788 · Cited by 93 · see citing works
“Some cognitive functions may be relatively resistant to decline (for example in highly educated groups (Lei-bovici, Ritchie, Ledesert, & Touchon, 1996)), or that – unlike TMT B-A - did not include a correction for reaction time but were dependent on it (i.e., the Flanker inhibitory control test, Dimensional change car…”
InfluentialSmith, M. J., Sherwood, K. L., Ross, B., Smith, J. D., DaWalt, L. S., Bishop, L., Humm, L. B., Elkins, J., & Steacy, C. (2021) · Autism · doi:10.1177/1362361321989928 · Cited by 93 · see citing works
Kindergarten components of executive function and third grade achievement: A national study
Nguyen, T., & Duncan, G. J. (2018) · Early Childhood Research Quarterly · doi:10.1016/j.ecresq.2018.05.006 · Cited by 94 · see citing works
“Though lower than the test-retest reliability of other EF tasks, this measure of cognitive flexibility is widely used in studies predicting achievement in young children and is now a standardized measure in the NIH Toolbox (Weintraub et al., 2013) and has also been used in several studies also examining children’s EF…”
MethodThe developmental relationship between specific cognitive domains and grey matter in the cerebellum
Moore, D. M., D’Mello, A. M., McGrath, L. M., & Stoodley, C. J. (2016) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2016.12.001 · Cited by 90 · see citing works
Soorya, L. V., Leon, J., Trelles, M. P., & Thurm, A. E. (2017) · The Clinical Neuropsychologist · doi:10.1080/13854046.2017.1413211 · Cited by 88 · see citing works
The Dual Mechanisms of Cognitive Control Project
Braver, T. S., Kizhner, A., Tang, R., Freund, M. C., & Etzel, J. A. (2021) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_01768 · Cited by 89 · see citing works
Maschan, M., Caimi, P. F., Reese-Koc, J., Sanchez, G. P., Sharma, A. A., Molostova, O., Shelikhova, L., Pershin, D., Stepanov, A., Muzalevskii, Y., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-27312-6 · Cited by 88 · see citing works
Apple, A. C., Schroeder, M. P., Ryals, A. J., et al. (2018) · NeuroImage Clinical · doi:10.1016/j.nicl.2018.07.010 · Cited by 88 · see citing works
Shalabi, H., Wolters, P. L., Martin, S. C., Toledo‐Tamula, M. A., Roderick, M. C., Struemph, K. L., Kane, E., Yates, B., Delbrook, C., Mackall, C. L., et al. (2018) · Journal of Immunotherapy · doi:10.1097/cji.0000000000000241 · Cited by 87 · see citing works
Casaletto, K. B., Umlauf, A., Marquine, M. J., Beaumont, J. L., Mungas, D., Gershon, R. C., Slotkin, J., Akshoomoff, N. A., & Heaton, R. K. (2016) · Journal of the International Neuropsychological Society · doi:10.1017/s135561771500137x · Cited by 85 · see citing works
“See Weintraub et al. (2013) for more detailed descriptions of each measure and Heaton et al. (2014) for validation of the Composite Scores.”
BackgroundMethodSelf-citationSanborn, V. E., Azcárate-Peril, M. A., Updegraff, J. A., Manderino, L. M., & Gunstad, J. (2020) · Neuropsychiatric Disease and Treatment · doi:10.2147/ndt.s270035 · Cited by 86 · see citing works
Gray matter maturation and cognition in children with different APOE ε genotypes
Chang, L., Douet, V., Bloss, C. S., Lee, K., Pritchett, A., Jernigan, T. L., Akshoomoff, N. A., Murray, S. S., Frazier, J. A., Kennedy, D. N., et al. (2016) · Neurology · doi:10.1212/wnl.0000000000002939 · Cited by 81 · see citing works
Vargas, T., Damme, K. S. F., & Mittal, V. A. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.117086 · Cited by 80 · see citing works
Walhovd, K. B., Fjell, A. M., Wang, Y., Amlien, I. K., Mowinckel, A. M., Lindenberger, U., Düzel, S., David Bartrés-faz, A., Ebmeier, K. P., Drevon, C. A., et al. (2021) · Cerebral Cortex · doi:10.1093/cercor/bhab248 · Cited by 79 · see citing works
“The cognitive measures from the NIH toolbox have shown good short term reliability (Weintraub et al. 2013).”
MethodKarcher, N. R., Loewy, R. L., Savill, M., Avenevoli, S., Huber, R. S., Makowski, C., Sher, K. J., & Barch, D. M. (2021) · Molecular Psychiatry · doi:10.1038/s41380-021-01373-x · Cited by 77 · see citing works
“Neuropsychological test battery The current study utilized uncorrected National Institutes of Health Toolbox Cognitive Battery scores from the 7 individual tests and fluid and crystallized composite scores [46].”
MethodGettens, K. M., & Gorin, A. A. (2017) · Journal of Behavioral Medicine · doi:10.1007/s10865-017-9831-5 · Cited by 75 · see citing works
Jonklaas, J., Bianco, A. C., Cappola, A. R., Celi, F. S., Fliers, E., Heuer, H., McAninch, E. A., Moeller, L. C., Nygaard, B., Sawka, A. M., et al. (2021) · European Thyroid Journal · doi:10.1159/000512970 · Cited by 78 · see citing works
Long-Term Treatment of Niemann-Pick Type C1 Disease With Intrathecal 2-Hydroxypropyl-β-Cyclodextrin
Berry‐Kravis, E., Chin, J. A., Hoffmann, A., Winston, A., Stoner, R., LaGorio, L. A., Friedmann, K., Hernández, M., Ory, D. S., Porter, F. D., et al. (2018) · Pediatric Neurology · doi:10.1016/j.pediatrneurol.2017.12.014 · Cited by 76 · see citing works
Sekiyama, M., Yamazaki, S., Michikawa, T., et al. (2020) · Journal of Epidemiology · doi:10.2188/jea.je20200448 · Cited by 75 · see citing works
Harris, C., Tang, Y., Birnbaum, E., Cherian, C., Mendhe, D., & Chen, M. H. (2024) · Archives of Clinical Neuropsychology · doi:10.1093/arclin/acae016 · Cited by 81 · see citing works
Preschoolers' Executive Function: Importance, Contributors, Research Needs and Assessment Options
Ackerman, D. J., & Friedman‐Krauss, A. H. (2017) · ETS Research Report Series · doi:10.1002/ets2.12148 · Cited by 80 · see citing works
Pindus, D. M., Drollette, E. S., Scudder, M. R., Khan, N. A., Raine, L. B., Sherar, L. B., Esliger, D., Kramer, A. F., & Hillman, C. H. (2016) · The Journal of Pediatrics · doi:10.1016/j.jpeds.2016.02.045 · Cited by 74 · see citing works
Exercise Intensity Influences Prefrontal Cortex Oxygenation during Cognitive Testing
Moriarty, T. A., Bourbeau, K., Bellovary, B. N., & Zuhl, M. (2019) · Behavioral Sciences · doi:10.3390/bs9080083 · Cited by 74 · see citing works
Validation of the NIH Toolbox Cognitive Battery in intellectual disability
Shields, R. H., Kaat, A. J., McKenzie, F. J., Drayton, A., Sansone, S. M., Coleman, J., Michalak, C., Riley, K., Berry-Kravis, E., Gershon, R. C., et al. (2020) · Neurology · doi:10.1212/wnl.0000000000009131 · Cited by 73 · see citing works
Self-citationValidation of the NIH Toolbox in Individuals with Neurologic Disorders
Carlozzi, N. E., Goodnight, S. M., Casaletto, K. B., Goldsmith, A., Heaton, R. K., Wong, A., Baum, C. M., Gershon, R. C., Heinemann, A. W., & Tulsky, D. S. (2017) · Archives of Clinical Neuropsychology · doi:10.1093/arclin/acx020 · Cited by 73 · see citing works
Self-citationHome-based Cognitive Prehabilitation in Older Surgical Patients: A Feasibility Study
Vlisides, P. E., Das, A. R., Thompson, A. M., Kunkler, B. S., Zierau, M., Cantley, M. J., McKinney, A., & Giordani, B. (2018) · Journal of Neurosurgical Anesthesiology · doi:10.1097/ana.0000000000000569 · Cited by 72 · see citing works
Keller, A. S., Pines, A. R., Shanmugan, S., Sydnor, V. J., Cui, Z., Bertolero, M. A., Barzilay, R., Alexander‐Bloch, A. F., Byington, N., Chen, A. A., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-44087-0 · Cited by 71 · see citing works
- Authors
- Weintraub, S., Dikmen, S. S., Heaton, R. K., Tulsky, D. S., Zelazo, P. D., Bauer, P. J., Carlozzi, N. E., Slotkin, J., Blitz, D., Wallner-Allen, K., Fox, N. A., Beaumont, J. L., Mungas, D., Nowinski, C. J., Richler, J., Deocampo, J. A., Anderson, J. E., Manly, J. J., Borosh, B., Havlik, R., Conway, K., Edwards, E., Freund, L., King, J. W., Moy, C., Witt, E., & Gershon, R. C.
- Affiliations
- From the Cognitive Neurology and Alzheimer's Disease Center (S.W., B.B.), Northwestern Feinberg School of Medicine, Chicago, IL; Department of Rehabilitation Medicine (S.S.D.), University of Washington, Seattle, WA; Department of Psychiatry (R.K.H.), University of California, San Diego, CA; Department of Physical Medicine and Rehabilitation (D.S.T., N.E.C.), University of Michigan, Ann Arbor, MI; Institute of Child Development (P.D.Z., J.E.A.), University of Minnesota, Minneapolis, MN; Department of...
- University of Minnesota (US)
- ORCID
- Venue
- Neurology
- Published
- 2013-03-12
- Volume
- 80
- Issue
- 11_supplement_3
- Pages
- S54-64
- ISSN
- 0028-3878 (ISSN-L)
- 1526-632X
- PMC
- PMC3662346
- OpenAlex
- W4296295377
- Semantic Scholar
- ad1bf29d236b7efc7939f4798eb18300052b81c2
- Cited by
- 1,287
- References
- 53
- Citations by year
- 2026: 106 · 2025: 140 · 2024: 162 · 2023: 143 · 2022: 157 · 2021: 163 · 2020: 130 · 2019: 88 · 2018: 71 · 2017: 50 · 2016: 23 · 2015: 21 · 2014: 20 · 2013: 11
- FWCI
- 33.79
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Neurology (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Kessler Foundation
- Brown University
- Ohio State University
- Northwestern University
- University of Washington
- Temple University
- National Institutes of Health (5ul1rr025761-04)
- Centers for Disease Control and Prevention (HHSN260200600007C)
- U.S. Public Health Service (NIDRR H133G090022, NIDRR H133A080035, H133A070037-08A, H133B090024, H133G070138, HHSN260200600007, H133A980023, H133N060022, B6237R)
- University of California, San Diego
- University of California, San Francisco
- Canadian Institutes of Health Research (201963)
- National Institute on Aging (R01AG028786, R01 AG016206, U01 AG14282, R01AG037212, RC2AG036498, U01AG014260, N01-AG-6-0007, U01AG14260, 1RC2AG036498-01, U01AG014263, U01AG014276, R01AG010220, U01AG014289, P30AG013854, AG-260-06-01, U01AG014282)
- National Heart, Lung, and Blood Institute (K23HL085766 NIA, K23HL085766)
- National Institute of Mental Health (MH074454, U01MH083506, R01MH058076, R01MH078748, R01 MH060720, R01MH081861, U01MH074454, P50MH078105, R01 MH073433, R01MH083552, U01MH080759, R01MH078737, R01MH080759, R01MH091363, R01MH074454, P30MH062512)
- National Institute on Drug Abuse (P50DA026306, P01DA012065)
- National Institute on Deafness and Other Communication Disorders (R01DC008552)
- National Institute of Diabetes and Digestive and Kidney Diseases (U01DK082342, 1U01DK082342-01)
- National Institute of Neurological Disorders and Stroke (HHSN 2652004236-01C, R03NS065194, U01 NS 056 975 02, R01 NS058302, NIH R01 NS058302)
- National Institute of Arthritis and Musculoskeletal and Skin Diseases (U01 AR057929, U54AR057943, 1U5AR057943-01)
- National Center for Research Resources (UL1-RR025761)
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (R37 HD017899, P01HD064653, R01HD061400, HHSN267200700027C, HD05469, R01HD054659, R01HD067359)
- Topics
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Cognitive Abilities and Testing
- Social Sciences › Psychology › Clinical Psychology › Historical and Modern Theater Studies
- Social Sciences › Psychology › Applied Psychology › Psychological Testing and Assessment
- Keywords
- NIH Toolbox, cognitive assessment, executive function, episodic memory, language, processing speed, working memory, attention, test-retest reliability, construct validity, age effects, computerized cognitive assessment, cognitive outcome measures
- MeSH terms
- Adolescent, Adult, Aged, Aged, 80 and over, Attention, Child, Child, Preschool, Cognition, Cognition Disorders, Humans, Language, Middle Aged, National Institutes of Health (U.S.), Neuropsychological Tests, United States, Reproducibility of Results, Young Adult
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