Skip to main content Accessibility help

Empirical Derivation and Validation of a Clinical Case Definition for Neuropsychological Impairment in Children and Adolescents

  • Miriam H. Beauchamp (a1) (a2), Brian L. Brooks (a3) (a4) (a5) (a6), Nick Barrowman (a6), Mary Aglipay (a7), Michelle Keightley (a8) (a9) (a10), Peter Anderson (a11) (a12), Keith O. Yeates (a5) (a6) (a13), Martin H. Osmond (a12) (a14) and Roger Zemek (a12) (a14)...


Neuropsychological assessment aims to identify individual performance profiles in multiple domains of cognitive functioning; however, substantial variation exists in how deficits are defined and what cutoffs are used, and there is no universally accepted definition of neuropsychological impairment. The aim of this study was to derive and validate a clinical case definition rule to identify neuropsychological impairment in children and adolescents. An existing normative pediatric sample was used to calculate base rates of abnormal functioning on eight measures covering six domains of neuropsychological functioning. The dataset was analyzed by varying the range of cutoff levels [1, 1.5, and 2 standard deviations (SDs) below the mean] and number of indicators of impairment. The derived rule was evaluated by bootstrap, internal and external clinical validation (orthopedic and traumatic brain injury). Our neuropsychological impairment (NPI) rule was defined as “two or more test scores that fall 1.5 SDs below the mean.” The rule identifies 5.1% of the total sample as impaired in the assessment battery and consistently targets between 3 and 7% of the population as impaired even when age, domains, and number of tests are varied. The NPI rate increases in groups known to exhibit cognitive deficits. The NPI rule provides a psychometrically derived method for interpreting performance across multiple tests and may be used in children 6–18 years. The rule may be useful to clinicians and scientists who wish to establish whether specific individuals or clinical populations present within expected norms versus impaired function across a battery of neuropsychological tests. (JINS, 2015, 21, 596–609)


Corresponding author

Correspondence and reprint requests to: Miriam Beauchamp, Department of Psychology, University of Montreal, C.P. Succursale Centre-Ville, Montréal, Québec, Canada, H3C 3J7. E-mail:


Hide All
Achenbach, T.M. (1991). Integrative guide for the 1991 CBCL/4-18, YSR, and TRF profiles. Burlington, VT: Department of Psychiatry, University of Vermont.
Anderson, V., Spencer-Smith, M., Leventer, R., Coleman, L., Anderson, P., Williams, J., & Jacobs, R. (2009). Childhood brain insult: Can age at insult help us predict outcome? Brain, 132(1), 4556. doi:10.1093/brain/awn293
Babikian, T., & Asarnow, R. (2009). Neurocognitive outcomes and recovery after pediatric TBI: Meta-analytic review of the literature. Neuropsychology, 23(3), 283296. doi:10.1037/a0015268
Babikian, T., Satz, P., Zaucha, K., Light, R., Lewis, R.S., & Asarnow, R.F. (2011). The UCLA longitudinal study of neurocognitive outcomes following mild pediatric traumatic brain injury. Journal of the International Neuropsychological Society, 17(5), 886895. doi:10.1017/s1355617711000907
Beauchamp, M.H., & Anderson, V. (2010). SOCIAL: An integrative framework for the development of social skills. Psychological Bulletin, 136(1), 3964. doi:10.1037/a0017768
Beauchamp, M.H., & Anderson, V. (2013). Cognitive and psychopathological sequelae of pediatric traumatic brain injury. In O. Dulac, S. Di Mauro & M. Lassonde (Eds.), Handbook of clinical pediatric neurology, Vol. 112, (pp. 913920). Amsterdam: Elsevier.
Binder, L.M., Iverson, G.L., & Brooks, B.L. (2009). To err is human: “Abnormal” neuropsychological scores and variability are common in healthy adults. Archives of Clinical Neuropsychology, 24(1), 3146. doi:10.1093/arclin/acn001
Brooks, B.L. (2010). Seeing the forest for the trees: Prevalence of low scores on the Wechsler Intelligence Scale for Children, fourth edition (WISC-IV). Psychological Assessment, 22(3), 650656. doi:10.1037/a0019781
Brooks, B.L., & Iverson, G.L. (2012). Improving accuracy when identifying cognitive impairment in pediatric neuropsychological assessments. In E.M.S. Sherman & B.L. Brooks (Eds.), Pediatric forensic neuropsychology (pp. 6688). New York, NY: Oxford University Press.
Brooks, B.L., Iverson, G.L., Feldman, H.H., & Holdnack, J.A. (2009). Minimizing misdiagnosis: Psychometric criteria for possible or probable memory impairment. Dementia and Geriatric Cognitive Disorders, 27(5), 439450. doi:10.1159/000215390
Brooks, B.L., Iverson, G.L., Koushik, N.S., Mazur-Mosiewicz, A., Horton, A., & Reynolds, C.R. (2013). Prevalence of low scores in children and adolescents on the test of verbal conceptualization and fluency. Applied Neuropsychology; Child, 2(1), 7077. doi:10.1080/21622965.2012.742792
Brooks, B.L., Iverson, G.L., Sherman, E.M., & Holdnack, J.A. (2009). Healthy children and adolescents obtain some low scores across a battery of memory tests. Journal of the International Neuropsychological Society, 15(4), 613617. doi:10.1017/S1355617709090651
Brooks, B.L., Iverson, G.L., Sherman, E.M., & Roberge, M.-C. (2010). Identifying cognitive problems in children and adolescents with depression using computerized neuropsychological testing. Applied Neuropsychology, 17(1), 3743. doi:10.1080/09084280903526083
Brooks, B.L., Sherman, E.M., & Iverson, G.L. (2010). Healthy children get low scores too: Prevalence of low scores on the NEPSY-II in preschoolers, children, and adolescents. Archives of Clinical Neuropsychology, 25(3), 182190. doi:10.1093/arclin/acq005
Carey, C.L., Woods, S.P., Gonzalez, R., Conover, E., Marcotte, T.D., Grant, I., & Heaton, R.K. (2004). Predictive validity of global deficit scores in detecting neuropsychological impairment in HIV infection. Journal of Clinical and Experimental Psychology, 26(3), 307319. doi:10.1080/13803390490510031
Casey, B.J., Jones, R.M., & Hare, T.A. (2008). The adolescent brain. Annals of the New York Academy of Sciences, 1124(1), 111126. doi:10.1196/annals.1440.010
Conklin, H.M., Salorio, C.F., & Slomine, B.S. (2008). Working memory performance following paediatric traumatic brain injury. Brain Injury, 22(11), 847857. doi:10.1080/02699050802403565
Crawford, J.R., Garthwaite, P.H., & Gault, C.B. (2007). Estimating the percentage of the population with abnormally low scores (or abnormally large score differences) on standardized neuropsychological test batteries: A generic method with applications. Neuropsychology, 21(4), 419430. doi:10.1037/0894-4105.21.4.419
Crowe, L.M., Catroppa, C., Babl, F.E., & Anderson, V. (2012). Intellectual, behavioral, and social outcomes of accidental traumatic brain injury in early childhood. Pediatrics, 129(2), e262e268. doi:10.1542/peds.2011-0438
Delis, D.C., Kramer, J.H., Kaplan, E., & Ober, B.A. (1994). CVLT-C: California Verbal Learning Test. San Antonio, TX: The Psychological Corporation.
Diamond, A. (2000). Close interrelation of motor development and cognitive development and of the cerebellum and prefrontal cortex. Child Development, 71(1), 4456.
Evans, A.C., Brain Development Cooperative Group. (2006). The NIH MRI study of normal brain development. Neuroimage, 30(1), 184202.
Ewing-Cobbs, L., Barnes, M.A., & Fletcher, J.M. (2003). Early brain injury in children: Development and reorganization of cognitive function. Developmental Neuropsychology, 24(2-3), 669704. doi:10.1080/87565641.2003.9651915
Fay, T.B., Yeates, K.O., Wade, S.L., Drotar, D., Stancin, T., & Taylor, H.G. (2009). Predicting longitudinal patterns of functional deficits in children with traumatic brain injury. Neuropsychology, 23(3), 271282. doi:10.1037/a0014936
Gathercole, S.E. (1998). The development of memory. Journal of Child Psychology and Psychiatry, 39(1), 327.
Gazzaley, A., & Nobre, A.C. (2012). Top-down modulation: Bridging selective attention and working memory. Trends in Cognitive Science, 16(2), 129135. doi:10.1016/j.tics.2011.11.014
Hackman, D.A., Farah, M.J., & Meaney, M.J. (2014). Socioeconomic status and the brain: Mechanistic insights from human and animal research. Nature Reviews Neuroscience, 11(9), 651659. doi:10.1038/nrn2897
Hung, R., Carroll, L.J., Cancelliere, C., Cote, P., Rumney, P., Keightley, M., & Cassidy, J.D. (2014). Systematic review of the clinical course, natural history, and prognosis for pediatric mild traumatic brain injury: Results of the International Collaboration on Mild Traumatic Brain Injury Prognosis. Archives of Physical Medicine and Rehabilitation, 95(3 Suppl.), S174S191. doi:10.1016/j.apmr.2013.08.301
Hurks, P., Hendriksen, J., Dek, J., & Kooij, A. (2013). Normal variability of children’s scaled scores on subtests of the Dutch Wechsler Preschool and Primary Scale of Intelligence-Third Edition. The Clinical Neuropsychologist, 27(6), 9881003. doi:10.1080/13854046.2013.797502
Huttenlocher, P.R. (1979). Synaptic density in human frontal cortex - Developmental changes and effects of aging. Brain Research, 163(2), 195205.
Huttenlocher, P.R., & Dabholkar, A. (1997). Developmental anatomy of the prefrontal cortex. In N. Krasnegor, G. Reid, & P. Goldman-Rakic (Eds.), Development of the prefrontal cortex: Evolution, neurobiology and behaviour (pp. 6983). Baltimore: Paul H. Brookes Publishing Company.
Isquith, P.K., Crawford, J.S., Espy, K.A., & Gioia, G.A. (2005). Assessment of executive function in preschool-aged children. Mental Retardation and Developmental Disabilities Research Reviews, 11(3), 209215. doi:10.1002/mrdd.20075
Kolb, B., Pellis, S., & Robinson, T.E. (2004). Plasticity and functions of the orbital frontal cortex. Brain and Cognition, 55(1), 104115. doi:10.1016/S0278-2626(03)00278-1
Korkman, M., Kirk, U., & Kemp, S. (1998). NEPSY: A developmental neuropsychological assessment. San Antonio, TX: The Psychological Corporation.
Levin, H.S., Li, X., McCauley, S.R., Hanten, G., Wilde, E.A., & Swank, P. (2013). Neuropsychological outcome of mTBI: A principal component analysis approach. Journal of Neurotrauma, 30(8), 625632. doi:10.1089/neu.2012.2627
Lezak, M.D. (1995). Neuropsychological assessment. New York: Oxford University Press.
Mather, N., & Woodcock, R.W. (2001). Woodcock-Johnson III Tests of Achievement: Examiner’s manual. Rolling Meadows, IL: Riverside Publishing.
Rieger, B.P., Lewandowski, L.J., Callahan, J.M., Spenceley, L., Truckenmiller, A., Gathje, R., & Miller, L.A. (2013). A prospective study of symptoms and neurocognitive outcomes in youth with concussion vs orthopaedic injuries. Brain Injury, 27(2), 169178. doi:10.3109/02699052.2012.729290
Sady, M.D., Vaughan, C.G., & Gioia, G.A. (2014). Psychometric characteristics of the postconcussion symptom inventory in children and adolescents. Archives of Clinical Neuropsychology, 29(4), 348363. doi:10.1093/arclin/acu014
Sahakian, B.J., Morris, R.G., Evenden, J.L., Heald, A., Levy, R., Philpot, M., & Robbins, T.W. (1988). A comparative study of visuospatial memory and learning in Alzheimer-type dementia and Parkinson’s disease. Brain, 111(3), 695718.
Sahakian, B.J., & Owen, A.M. (1992). Computerized assessment in neuropsychiatry using CANTAB: Discussion paper. Journal of the Royal Society of Medicine, 85(7), 399402.
Schoenberg, M.R., Lange, R.T., Brickell, T.A., & Saklofske, D.H. (2007). Estimating premorbid general cognitive functioning for children and adolescents using the American Wechsler Intelligence Scale for Children-Fourth Edition: Demographic and current performance approaches. Child Neurology, 22(4), 379388.
Tiffin, J. (1968). Purdue pegboard: Examiner manual. Chicago: Science Research Associates.
Tiffin, J., & Asher, E.J. (1948). The Purdue Pegboard: Norms and studies of reliability and validity. Journal of Applied Psychology, 32(3), 234247.
Tsujimoto, S. (2008). The prefrontal cortex: Functional neural development during early childhood. Neuroscientist, 14(4), 345358. doi:10.1177/1073858408316002
van der Sluis, S., Willemsen, G., de Geus, E.J., Boomsma, D.I., & Posthuma, D. (2008). Gene-environment interaction in adults’ IQ scores: Measures of past and present environment. Behavioral Genetics, 38(4), 348360. doi:10.1007/s10519-008-9212-5
Waber, D.P., De Moor, C., Forbes, P.W., Almli, C.R., Botteron, K.N., Leonard, G., & Group, B.D.C. (2007). The NIH MRI study of normal brain development: Performance of a population based sample of healthy children aged 6 to 18 years on a neuropsychological battery. Journal of the International Neuropsychological Society, 13(5), 729746. doi:10.1017/S1355617707070841
Wechsler, D. (1999). Wechsler Abbreviated Scale of Intelligence. New York, NY: The Psychological Corporation.
Yeates, K.O. (2010). Mild traumatic brain injury and postconcussive symptoms in children and adolescents. Journal of the International Neuropsychological Society, 16(6), 953960. doi:10.1017/s1355617710000986
Yeates, K.O., Taylor, H.G., Wade, S., Drotar, D., Stancin, T., & Minich, N. (2002). A prospective study of short- and long-term neuropsychological outcomes after traumatic brain injury in children. Neuropsychology, 16(4), 514523.
Zemek, R., Osmond, M.H., & Barrowman, N., Pediatric Emergency Research Canada Concussion Team. (2013). Predicting and preventing postconcussive problems in paediatrics (5P) study: Protocol for a prospective multicentre clinical prediction rule derivation study in children with concussion. British Medical Journal Open, 3(8), 110. doi:10.1136/bmjopen-2013-003550
Zimmerman, I.L., Steiner, V.G., & Pond, R.E. (2002). Preschool language scale (3rd ed.). San Antonio, TX: The Psychological Corporation.



Altmetric attention score

Full text views

Total number of HTML views: 0
Total number of PDF views: 0 *
Loading metrics...

Abstract views

Total abstract views: 0 *
Loading metrics...

* Views captured on Cambridge Core between <date>. This data will be updated every 24 hours.

Usage data cannot currently be displayed