Hostname: page-component-cd9895bd7-gbm5v Total loading time: 0 Render date: 2024-12-26T16:59:40.210Z Has data issue: false hasContentIssue false
  • English
  • Français

Brief, Performance-Based Cognitive Screening in Youth Aged 12–25: A Systematic Review

Published online by Cambridge University Press:  19 January 2021

Shayden D. Bryce Open the ORCID record for Shayden D. Bryce [Opens in a new window] ,
Stephen C. Bowden ,
Stephen J. Wood  and
Kelly Allott
Shayden D. Bryce
Affiliation:
Orygen, Parkville, Victoria, Australia Centre for Youth Mental Health, The University of Melbourne, Parkville, Victoria, Australia
Stephen C. Bowden
Affiliation:
Melbourne School of Psychological Sciences, The University of Melbourne, Parkville, Victoria, Australia
Stephen J. Wood
Affiliation:
Orygen, Parkville, Victoria, Australia Centre for Youth Mental Health, The University of Melbourne, Parkville, Victoria, Australia
Kelly Allott*
Affiliation:
Orygen, Parkville, Victoria, Australia Centre for Youth Mental Health, The University of Melbourne, Parkville, Victoria, Australia
*
*Correspondence and reprint requests to: Kelly Allott, 35 Poplar Road, Parkville, VIC3052, Australia. E-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Objective:

Cognitive screening is an efficient method of detecting cognitive impairment in adults and may signal need for comprehensive assessment. Cognitive screening is not, however, routinely used in youth aged 12–25, limiting clinical recommendations. The aims of this review were to describe performance-based cognitive screening tools used in people aged 12–25 and the contexts of use, review screening accuracy in detecting cognitive impairment relative to an objective reference standard, and evaluate the risk of bias of included studies.

Method:

Electronic databases (Scopus, Medline, PsychINFO, and ERIC) were searched for relevant studies according to pre-determined criteria. Risk of bias was rated using the Quality Assessment of Diagnostic Accuracy Studies-2. Dual screening, extraction, and quality ratings occurred at each review phase.

Results:

Twenty studies met the review inclusion criteria. A diverse range of screening tools (length, format) were used in youth aged 12–25 with or without health conditions. Six studies investigating cognitive screening were conducted as primary accuracy studies and reported some relevant psychometric parameters (e.g., sensitivity and specificity). Fourteen studies presented correlational data to investigate the cognitive measure utility. Studies generally presented limited data on classification accuracy, which impacted full screening tool appraisal. Risk of bias was high (or unclear) in most studies with poor adherence to the Standards for Reporting Diagnostic Accuracy Studies (STARD) criteria.

Conclusions:

Few, high quality studies have investigated the utility of cognitive screening in youth aged 12–25, with no screening measure emerging as superior at detecting cognitive impairment in this age group.

Keywords

ScreeningCognitionYouthValidityNeuropsychology
Type
Critical Review
Information
Journal of the International Neuropsychological Society , Volume 27 , Issue 8 , September 2021 , pp. 835 - 854
Copyright
Copyright © INS. Published by Cambridge University Press, 2021

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Allen, B. J., & Gfeller, J. D. (2011). The immediate post-concussion assessment and cognitive testing battery and traditional neuropsychological measures: A construct and concurrent validity study. Brain Injury, 25(2), 179-191. doi: 10.3109/02699052.2010.541897 CrossRefGoogle ScholarPubMed
Allott, K., Proffitt, T.-M., McGorry, P. D., Pantelis, C., Wood, S. J., Cumner, M., & Brewer, W. J. (2013). Clinical neuropsychology within adolescent and young-adult psychiatry: Conceptualizing theory and practice. Applied Neuropsychology: Child, 2(1), 47-63. doi: 10.1080/08841233.2012.670566 CrossRefGoogle ScholarPubMed
Allott, K., van-der-EL, K., Bryce, S., Hamilton, M., Adams, S., Burgat, L., & Rickwood, D. (2019). Need for clinical neuropsychological assessment in headspace youth mental health services: A national survey of providers. Australian Journal of Psychology, 71(2), 108–116. doi:https://doi.org/10.1111/ajpy.12225 CrossRefGoogle Scholar
American Psychological Association Practice Organization. (2014). Distinguishing between screening and assessment for mental and behavioral health problems: A statement from an American Psychological Association Practice Organization work group on screening and psychological assessment. Retrieved from: https://www.apaservices.org/practice/reimbursement/billing/assessment-screening Google Scholar
Arain, M., Haque, M., Johal, L., Mathur, P., Nel, W., Rais, A., … Sharma, S. (2013). Maturation of the adolescent brain. Neuropsychiatric Disease and Treatment, 9, 449–460. doi: 10.2147/ndt.s39776 Google ScholarPubMed
Arevalo-Rodriguez, I., Smailagic, N., Roquéi Figuls, M., Ciapponi, A., Sanchez-Perez, E., Giannakou, A., … Cullum, S. (2015). Mini-Mental State Examination (MMSE) for the detection of Alzheimer’s disease and other dementias in people with mild cognitive impairment (MCI). Cochrane Database of Systematic Reviews, 2015(3). doi: 10.1002/14651858.CD010783.pub2 Google Scholar
Arnett, A. B., Peterson, R. L., Kirkwood, M. W., Taylor, H. G., Stancin, T., Brown, T. M., & Wade, S. L. (2013). Behavioral and cognitive predictors of educational outcomes in pediatric traumatic brain injury. Journal of the International Neuropsychological Society, 19(8), 881-889. doi: 10.1017/S1355617713000635 CrossRefGoogle ScholarPubMed
Arrieux, J., Cole, W., & Ahrens, A. (2017). A review of the validity of computerized neurocognitive assessment tools in mild traumatic brain injury assessment. Concussion, 30(2), CNC31. doi: 10.2217/cnc-2016-0021 CrossRefGoogle Scholar
Bauer, R. M., Iverson, G. L., Cernich, A. N., Binder, L. M., Ruff, R. M., & Naugle, R. I. (2012). Computerized neuropsychological assessment devices: Joint position paper of the American academy of clinical neuropsychology and the national academy of neuropsychology. Archives of Clinical Neuropsychology, 27(3), 362-373. doi: 10.1093/arclin/acs027 CrossRefGoogle ScholarPubMed
Bava, S., Thayer, R., Jacobus, J., Ward, M., Jernigan, T., & Tapert, S. (2010). Longitudinal characterisation of white matter maturation during adolescence. Brain Research, 1327, 38–46.CrossRefGoogle Scholar
Blacker, D., Albert, M. S., Bassett, S. S., Rodney, C. P., Harrell, L. E., & Folstein, M. F. (1994). Reliability and Validity of Nincds-Adrda Criteria for Alzheimer’s Disease: The National Institute of Mental Health Genetics Initiative. Archives of Neurology, 51(12), 1198-1204. doi: 10.1001/archneur.1994.00540240042014 CrossRefGoogle ScholarPubMed
Bleiberg, J., Kane, R. L., Reeves, D. L., Garmoe, W. S., & Halpern, E. (2000). Factor analysis of computerized and traditional tests used in mild brain injury research. Clinical Neuropsychologist, 14(3), 287-294. doi: 10.1076/1385-4046(200008)14:3;1-P;FT287 CrossRefGoogle ScholarPubMed
Block, C. K., Johnson-Greene, D., Pliskin, N., & Boake, C. (2017). Discriminating cognitive screening and cognitive testing from neuropsychological assessment: implications for professional practice. Clinical Neuropsychologist, 31(3), 487-500. doi: 10.1080/13854046.2016.1267803 CrossRefGoogle ScholarPubMed
Bossuyt, P. M., Reitsma, J. B., Bruns, D. E., Gatsonis, C. A., Glasziou, P. P., Irwig, L., … Cohen, J. F. (2015). STARD 2015: an updated list of essential items for reporting diagnostic accuracy studies. BMJ : British Medical Journal, 351, h5527. doi: 10.1136/bmj.h5527 CrossRefGoogle ScholarPubMed
Bossuyt, P. M., Reitsma, J. B., Bruns, D. E., Gatsonis, C. A., Glasziou, P. P., Irwig, L. M., … Lijmer, J. G. (2003). The STARD statement for reporting studies of diagnostic accuracy: explanation and elaboration. Annals of Internal Medicine, 138(1), W1–12.CrossRefGoogle ScholarPubMed
Boulet-Craig, A., Robaey, P., Laniel, J., Bertout, L., Drouin, S., Krajinovic, M., … Lippé, S. (2018). DIVERGT screening procedure predicts general cognitive functioning in adult long-term survivors of pediatric acute lymphoblastic leukemia: A PETALE study. Pediatric Blood and Cancer, 65(9). doi: 10.1002/pbc.27259 CrossRefGoogle ScholarPubMed
Bryce, S., & Allott, K. (2019). Cognitive screening: A significant unmet need in youth mental health. Australian And New Zealand Journal Of Psychiatry. CrossRefGoogle ScholarPubMed
Bunnage, M. (2017). How do I know when a diagnostic test works? In Bowden, S. (Ed.), Neuropsychological assessment in the age of evidence-based practice: Diagnostic and treatment evaluation (pp. 223–238). Oxford University Press.Google Scholar
Cernich, A., Reeves, D., Sun, W., & Bleiberg, J. (2007). Automated Neuropsychological Assessment Metrics sports medicine battery. Archives of Clinical Neuropsychology, 22(Suppl. 1), 101-114. doi: 10.1016/j.acn.2006.10.008 CrossRefGoogle ScholarPubMed
Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Hillsdale, NJ: Lawrence Earlbaum Associates.Google Scholar
Cohen, J. F., Korevaar, D. A., Altman, D. G., Bruns, D. E., Gatsonis, C. A., Hooft, L., … Bossuyt, P. M. (2016). STARD 2015 guidelines for reporting diagnostic accuracy studies: explanation and elaboration. BMJ Open, 6(11), e012799. doi: 10.1136/bmjopen-2016-012799 CrossRefGoogle ScholarPubMed
Cullen, B., O’Neill, B., Evans, J. J., Coen, R. F., & Lawlor, B. A. (2007). A review of screening tests for cognitive impairment. Journal of Neurology, Neurosurgery and Psychiatry, 78(8), 790-799. doi: 10.1136/jnnp.2006.095414 CrossRefGoogle ScholarPubMed
Davis, D. H. J., Creavin, S. T., Yip, J. L. Y., Noel-Storr, A. H., Brayne, C., & Cullum, S. (2015). Montreal Cognitive Assessment for the diagnosis of Alzheimer’s disease and other dementias. Cochrane Database of Systematic Reviews, 2015(10). doi: 10.1002/14651858.CD010775.pub2 Google Scholar
Delagneau, G., Bowden, S. C., Bryce, S., van-der-El, K., Hamilton, M., Adams, S., … Allott, K. (2020). Thematic analysis of youth mental health providers’ perceptions of neuropsychological assessment services. Early Intervention in Psychiatry, 14(2), 220–227. doi: 10.1111/eip.12876 CrossRefGoogle ScholarPubMed
Doyle, A. E., Vuijk, P. J., Doty, N. D., McGrath, L. M., Willoughby, B. L., O’Donnell, E. H., … Braaten, E. B. (2018). Cross-disorder cognitive impairments in youth referred for neuropsychiatric evaluation. Journal of the International Neuropsychological Society, 24(1), 91–103. doi: 10.1017/S1355617717000601 CrossRefGoogle ScholarPubMed
Folstein, M. F., Folstein, S. E., & McHugh, P. R. (1975). “Mini-mental state”. A practical method for grading the cognitive state of patients for the clinician. Journal of Psychiatric Research, 12(3), 189–198.CrossRefGoogle ScholarPubMed
Foulkes, L., & Blakemore, S-J. (2018). Studying individual differences in human adolescence breain development. Nature Neuroscience, 21, 315–323.CrossRefGoogle ScholarPubMed
Gogtay, N., Giedd, J., Lusk, L., Hayashi, K., Greenstein, D., Vaituzis, C., … Thompson, P. (2004). Dynamic mapping of human cortical development during childhood through early adulthood. Proceedings of the National Academy of Sciences of the United States of America, 101(21), 8174–8179.CrossRefGoogle ScholarPubMed
Gonzalez-Heydrich, J., Hsin, O., Gumlak, S., Kimball, K., Rober, A., Azeem, M. W., … Biederman, J. (2014). Comparing stimulant effects in youth with ADHD symptoms and epilepsy. Epilepsy and Behavior, 36, 102–107. doi: 10.1016/j.yebeh.2014.04.026 CrossRefGoogle ScholarPubMed
Gore, F. M., Bloem, P. J., Patton, G. C., Ferguson, J., Joseph, V., Coffey, C., … Mathers, C. D. (2011). Global burden of disease in young people aged 10–24 years: a systematic analysis. Lancet, 377(9783), 2093–2102. doi: 10.1016/s0140-6736(11)60512-6 CrossRefGoogle ScholarPubMed
Gualtieri, C. T., & Johnson, L. G. (2006). Reliability and validity of a computerized neurocognitive test battery, CNS Vital Signs. Archives of Clinical Neuropsychology, 21(7), 623-643. doi: 10.1016/j.acn.2006.05.007 CrossRefGoogle ScholarPubMed
Heaton, R. K., Akshoomoff, N., Tulsky, D., Mungas, D., Weintraub, S., Dikmen, S., … Gershon, R. (2014). Reliability and validity of composite scores from the NIH toolbox cognition battery in adults. Journal of the International Neuropsychological Society, 20(6), 588–598. doi: 10.1017/S1355617714000241 CrossRefGoogle ScholarPubMed
Hetrick, S. E., Cox, G. R., Fisher, C. A., Bhar, S. S., Rice, S. M., Davey, C. G., & Parker, A. G. (2015). Back to basics: could behavioural therapy be a good treatment option for youth depression? A critical review. Early Intervention in Psychiatry, 9(2), 93-99. doi: 10.1111/eip.12142 CrossRefGoogle ScholarPubMed
Holsinger, T., Deveau, J., Boustani, M., & Williams, J. W. Jr (2007). Does this patient have dementia? Journal of the American Medical Association, 297(21), 2391-2404. doi: 10.1001/jama.297.21.2391 CrossRefGoogle ScholarPubMed
Holzer, L., Chinet, L., Jaugey, L., Plancherel, B., Sofia, C., Halfon, O., & Randolph, C. (2007). Detection of cognitive impairment with the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) in adolescents with psychotic symptomatology. Schizophrenia Research, 95(1-3), 48-53. doi: 10.1016/j.schres.2007.06.013 CrossRefGoogle ScholarPubMed
Hoppe, C., Fliessbach, K., Schlegel, U., Elger, C. E., & Helmstaedter, C. (2009). NeuroCog FX: Computerized screening of cognitive functions in patients with epilepsy. Epilepsy and Behavior, 16(2), 298-310. doi: 10.1016/j.yebeh.2009.07.041 CrossRefGoogle ScholarPubMed
Iverson, G. L., Lovell, M. R., & Collins, M. W. (2005). Validity of ImPACT for measuring processing speed following sports-related concussion. Journal of Clinical and Experimental Neuropsychology, 27(6), 683-689. doi: 10.1081/13803390490918435 CrossRefGoogle ScholarPubMed
Jewsbury, P. A., Bowden, S. C., & Duff, K. (2017). The Cattell-Horn-Carroll Model of Cognition for Clinical Assessment. Journal of Psychoeducational Assessment, 35(6), 547-567. doi: 10.1177/0734282916651360 CrossRefGoogle Scholar
Jewsbury, P. A., Bowden, S. C., & Strauss, M. E. (2016). Integrating the switching, inhibition, and updating model of executive function with the cattell-horn-carroll model. Journal of Experimental Psychology: General, 145(2), 220-245. doi: 10.1037/xge0000119 CrossRefGoogle ScholarPubMed
Jones, W. P., Loe, S. A., Krach, S. K., Rager, R. Y., & Jones, H. M. (2008). Automated Neuropsychological Assessment Metrics (ANAM) and Woodcock-Johnson III tests of cognitive ability: A concurrent validity study. Clinical Neuropsychologist, 22(2), 305-320. doi: 10.1080/13854040701281483 CrossRefGoogle ScholarPubMed
Kahn, D. A., Asbell, S. J., & Donders, J. (2015). Clinical utility of the LANSE-A in adolescents with traumatic brain injury. Rehabilitation Psychology, 60(2), 187-192. doi: 10.1037/rep0000034 CrossRefGoogle ScholarPubMed
Kassebaum, N., Kyu, H. H., Zoeckler, L., Olsen, H. E., Thomas, K., Pinho, C., … Vos, T. (2017). Child and adolescent health from 1990 to 2015: Findings from the global burden of diseases, injuries, and risk factors 2015 study. JAMA Pediatrics, 171(6), 573–592. doi: 10.1001/jamapediatrics.2017.0250 Google ScholarPubMed
Kavanaugh, B. C., Cancilliere, M. K., & Spirito, A. (2019). Neurocognitive heterogeneity across the spectrum of psychopathology: Need for improved approaches to deficit detection and intervention. CNS Spectrums. doi: 10.1017/S1092852919001081 Google ScholarPubMed
Kelly, M. P., Coldren, R. L., Parish, R. V., Dretsch, M. N., & Russell, M. L. (2012). Assessment of acute concussion in the combat environment. Archives of Clinical Neuropsychology, 27(4), 375-388. doi: 10.1093/arclin/acs036 CrossRefGoogle ScholarPubMed
Kerr, E. N., & Fayed, N. (2017). Cognitive predictors of adaptive functioning in children with symptomatic epilepsy. Epilepsy Research, 136, 67-76. doi: 10.1016/j.eplepsyres.2017.07.015 CrossRefGoogle ScholarPubMed
Krull, K. R., Okcu, M. F., Potter, B., Jain, N., Dreyer, Z., Kamdar, K., & Brouwers, P. (2008). Screening for neurocognitive impairment in pediatric cancer long-term survivors. Journal of Clinical Oncology, 26(25), 4138-4143. doi: 10.1200/JCO.2008.16.8864 CrossRefGoogle ScholarPubMed
Lalkhen, A. G., & McCluskey, A. (2008). Clinical tests: Sensitivity and specificity. Continuing Education in Anaesthesia, Critical Care and Pain, 8(6), 221-223. doi: 10.1093/bjaceaccp/mkn041 CrossRefGoogle Scholar
Lanca, M. (2018). Integration of neuropsychology in primary care. Archives of Clinical Neuropsychology, 33(3), 269–279. doi: 10.1093/arclin/acx135 CrossRefGoogle ScholarPubMed
Larsen, B., & Luna, B. (2018). Adolescence as a neurobiological critical period for the development of higher-order cognition. Neuroscience And Biobehavioral Reviews, 94, 179-195. doi: 10.1016/j.neubiorev.2018.09.005 CrossRefGoogle ScholarPubMed
Laver, K., Cumming, R. G., Dyer, S. M., Agar, M. R., Anstey, K. J., Beattie, E., … Yates, M. W. (2016). Clinical practice guidelines for dementia in Australia. Medical Journal of Australia, 204(5), 1–3.e2. doi: 10.5694/mja15.01339 CrossRefGoogle ScholarPubMed
Lee, R. S. C., Hermens, D. F., Naismith, S. L., Kaur, M., Guastella, A. J., Glozier, N., … Hickie, I. B. (2018). Clinical, neurocognitive and demographic factors associated with functional impairment in the Australian Brain and Mind Youth Cohort Study (2008–2016). BMJ Open, 8(12). doi: 10.1136/bmjopen-2018-022659 CrossRefGoogle Scholar
Maerlender, A., Flashman, L., Kessler, A., Kumbhani, S., Greenwald, R., Tosteson, T., & McAllister, T. (2010). Examination of the construct validity of impact™ computerized test, traditional, and experimental neuropsychological measures. Clinical Neuropsychologist, 24(8), 1309-1325. doi: 10.1080/13854046.2010.516072 CrossRefGoogle ScholarPubMed
Mandrekar, J. N. (2010). Receiver operating characteristic curve in diagnostic test assessment. Journal of Thoracic Oncology, 5(9), 1315–1316. doi: 10.1097/JTO.0b013e3181ec173d CrossRefGoogle ScholarPubMed
McGrew, K. S. (2009). CHC theory and the human cognitive abilities project: Standing on the shoulders of the giants of psychometric intelligence research. Intelligence, 37(1), 1–10. doi: 10.1016/j.intell.2008.08.004 CrossRefGoogle Scholar
Moher, D., Liberati, A., Tetzlaff, J., Altman, D. G., & The PRISMA Group. (2009). Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. Plos Medicine, 6(6), e1000097. doi: 10.1371/journal.pmed1000097 CrossRefGoogle ScholarPubMed
Nasreddine, Z. S., Phillips, N. A., Bedirian, V., Charbonneau, S., Whitehead, V., Collin, I., … Chertkow, H. (2005). The Montreal Cognitive Assessment, MoCA: a brief screening tool for mild cognitive impairment. Journal of the American Geriatrics Society, 53(4), 695–699. doi: 10.1111/j.1532-5415.2005.53221.x CrossRefGoogle ScholarPubMed
Parikh, R., Mathai, A., Parikh, S., Sekhar, G. C., & Thomas, R. (2008). Understanding and using sensitivity, specificity and predictive values. Indian Journal of Ophthalmology, 56(1), 45-50. doi: 10.4103/0301-4738.37595 CrossRefGoogle ScholarPubMed
Patel, S. K., Wong, A. L., Cuevas, M., & Van Horn, H. (2013). Parenting stress and neurocognitive late effects in childhood cancer survivors. Psycho-Oncology, 22(8), 1774-1782. doi: 10.1002/pon.3213 CrossRefGoogle ScholarPubMed
Pike, N. A., Poulsen, M. K., & Woo, M. A. (2017). Validity of the montreal cognitive assessment screener in adolescents and young adults with and without congenital heart disease. Nursing Research, 66(3), 222-230. doi: 10.1097/nnr.0000000000000192 CrossRefGoogle Scholar
Portaccio, E., Goretti, B., Lori, S., Zipoli, V., Centorrino, S., Ghezzi, A., … Gallo, P. (2009). The brief neuropsychological battery for children: A screening tool for cognitive impairment in childhood and juvenile multiple sclerosis. Multiple Sclerosis, 15(5), 620–626. doi: 10.1177/1352458508101950 CrossRefGoogle ScholarPubMed
Pottie, K., Rahal, R., Jaramillo, A., Birtwhistle, R., Thombs, B. D., Singh, H., … Tonelli, M. (2016). Recommendations on screening for cognitive impairment in older adults. CMAJ Canadian Medical Association Journal, 188(1), 37–46. doi: 10.1503/cmaj.141165 Google ScholarPubMed
Proffitt, T. M., Brewer, W. J., Parrish, E. M., McGorry, P. D., & Allott, K. A. (2018). Reasons for referral and findings of clinical neuropsychological assessment in youth with mental illness: A clinical file audit. Applied Neuropsychology: Child, 7(2), 164–174.CrossRefGoogle ScholarPubMed
Raiker, J. S., Manning, E., Herrington, B., May, A. C., Haynes, S., Graves, P. E., & Karlson, C. W. (2015). Brief neurocognitive screening in youth with brain tumours: A preliminary investigation of the Lebby-Asbell Neurocognitive Screening Examination (LANSE). Brain Injury, 29(10), 1192-1198. doi: 10.3109/02699052.2015.1035331 CrossRefGoogle Scholar
Roebuck-Spencer, T. M., Glen, T., Puente, A. E., Denney, R. L., Ruff, R. M., Hostetter, G., & Bianchini, K. J. (2017). Cognitive screening tests versus comprehensive neuropsychological test batteries: A national academy of neuropsychology education paper. Archives of Clinical Neuropsychology, 32(4), 491-498. doi: 10.1093/arclin/acx021 CrossRefGoogle Scholar
Rossell, S. L. (2019). Response to: Bryce and Allott – Cognitive screening: A significant unmet need in youth mental health. 30 minutes is too long! Australian And New Zealand Journal Of Psychiatry, 53(8), 814. doi: 10.1177/0004867419832652 CrossRefGoogle ScholarPubMed
Schatz, P., & Putz, B. O. (2006). Cross-validation of measures used for computer-based assessment of concussion. Applied Neuropsychology, 13(3), 151-159. doi: 10.1207/s15324826an1303_2 CrossRefGoogle ScholarPubMed
Schmidt, R. L., & Factor, R. E. (2013). Understanding sources of bias in diagnostic accuracy studies. Archives of Pathology and Laboratory Medicine, 137(4), 558-565. doi: 10.5858/arpa.2012-0198-RA CrossRefGoogle ScholarPubMed
Sheehan, B. (2012). Assessment scales in dementia. Therapeutic Advances in Neurological Disorders, 5(6), 349–358. doi: 10.1177/1756285612455733 CrossRefGoogle ScholarPubMed
Solomon, G. S., & Kuhn, A. (2014). Relationship between concussion history and neurocognitive test performance in national football league draft picks. American Journal of Sports Medicine, 42(4), 934-939. doi: 10.1177/0363546513518742 CrossRefGoogle ScholarPubMed
Straus, S. W., Richardson, W. S., Glasziou, P., & Haynes, R. B. (2010). Evidence-Based Medicine: How to Practice and Teach It. (4th ed.). New York, NY: Churchill Livingstone.Google Scholar
Summers, M. J., Bondi, M. W., & Bowden, S. C. (2019). Brief cognitive screening versus comprehensive neuropsychological assessment - Is one better than the other? National Academy of Neuropsychology Bulletin, 32(1), 8–12.Google Scholar
Tsoi, K. K. F., Chan, J. Y. C., Hirai, H. W., Wong, S. Y. S., & Kwok, T. C. Y. (2015). Cognitive tests to detect dementia a systematic review and meta-analysis. JAMA Internal Medicine, 175(9), 1450-1458. doi: 10.1001/jamainternmed.2015.2152 CrossRefGoogle ScholarPubMed
Valovich McLeod, T. C., Barr, W. B., McCrea, M., & Guskiewicz, K. M. (2006). Psychometric and measurement properties of concussion assessment tools in youth sports. Journal of Athletic Training, 41(4), 399–408.Google ScholarPubMed
Vega-Fernandez, P., Vanderburgh White, S., Zelko, F., Ruth, N. M., Levy, D. M., Muscal, E., … Brunner, H. I. (2015). Cognitive performance scores for the pediatric automated neuropsychological assessment metrics in childhood-onset systemic lupus erythematosus. Arthritis Care and Research, 67(8), 1119–1127. doi: 10.1002/acr.22571 CrossRefGoogle ScholarPubMed
Vos, T., Barber, R. M., Bell, B., Bertozzi-Villa, A., Biryukov, S., Bolliger, I., … Murray, C. J. L. (2015). Global, regional, and national incidence, prevalence, and years lived with disability for 301 acute and chronic diseases and injuries in 188 countries, 1990–2013: A systematic analysis for the Global Burden of Disease Study 2013. The Lancet, 386(9995), 743–800. doi: 10.1016/S0140-6736(15)60692-4 CrossRefGoogle Scholar
Weintraub, S., Dikmen, S., Heaton, R., Tulsky, D., Zelazo, P., Bauer, P., … Gershon, R. (2013). Cognition assessment using the NIH Toolbox. Neurology, 12(80), s54–64.CrossRefGoogle Scholar
Whiting, P. F., Rutjes, A. W. S., Westwood, M. E., Mallett, S., Deeks, J. J., Reitsma, J. B., … Bossuyt, P. M. M. (2011). Quadas-2: A revised tool for the quality assessment of diagnostic accuracy studies. Annals of Internal Medicine, 155(8), 529–536. doi: 10.7326/0003-4819-155-8-201110180-00009 CrossRefGoogle ScholarPubMed