Alber, J., Alladi, S., Bae, H. J., Barton, D. A., Beckett, L. A., Bell, J. M., Berman, S. E., Biessels, G. J., Black, S. E., Bos, I., Bowman, G. L., Brai, E., Brickman, A. M., Callahan, B. L., Corriveau, R. A., Fossati, S., Gottesman, R. F., Gustafson, D. R., Hachinski, V., … Hainsworth, A. H. (2019). White matter hyperintensities in vascular contributions to cognitive impairment and dementia (VCID): Knowledge gaps and opportunities. Alzheimer’s & Dementia: Translational Research & Clinical Interventions, 5, 107–117. https://doi.org/10.1016/J.TRCI.2019.02.001
Anderson, M., Kaufman, A. S., & Kaufman, N. L. (1976). Use of the WISC-R with a learning disabled population: Some diagnostic implications. Psychology in the Schools, 13(4), 381–386. https://doi.org/10.1002/1520-6807
Anstey, K. J., Mack, H. A., Christensen, H., Li, S. C., Reglade-Meslin, C., Maller, J., Kumar, R., Dear, K., Easteal, S., & Sachdev, P. (2007). Corpus callosum size, reaction time speed and variability in mild cognitive disorders and in a normative sample. Neuropsychologia, 45(8), 1911–1920. https://doi.org/10.1016/J.NEUROPSYCHOLOGIA.2006.11.020
Arce Rentería, M., Mobley, T. M., Evangelista, N. D., Medina, L. D., Deters, K. D., Fox-Fuller, J. T., Minto, L. R., Avila-Rieger, J., & Bettcher, B. M. (2023). Representativeness of samples enrolled in Alzheimer’s disease research centers. Alzheimer’s & Dementia: Diagnosis, Assessment & Disease Monitoring, 15(2), e12450. https://doi.org/10.1002/DAD2.12450
Axelrod, B. N., & Wall, J. R. (2007). Expectancy of impaired neuropsychological test scores in a non-clinical sample. International Journal of Neuroscience, 117(11), 1591–1602. https://doi.org/10.1080/00207450600941189
Bangen, K. J., Weigand, A. J., Thomas, K. R., Delano-Wood, L., Clark, L. R., Eppig, J., Werhane, M. L., Edmonds, E. C., & Bondi, M. W. (2019). Cognitive dispersion is a sensitive marker for early neurodegenerative changes and functional decline in nondemented older adults. Neuropsychology, 33(5), 599–608. https://doi.org/10.1037/NEU0000532
Article PubMed PubMed Central Google Scholar
Bayer, A., Phillips, M., Porter, G., Leonards, U., Bompas, A., & Tales, A. (2014). Abnormal inhibition of return in mild cognitive impairment: Is it specific to the presence of prodromal dementia? Journal of Alzheimer’s Disease : JAD, 40(1), 177–189. https://doi.org/10.3233/JAD-131934
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), 31–46. https://doi.org/10.1093/ARCLIN/ACN001
Borenstein, M., Hedges, L. V., Higgins, J. P. T., & Rothstein, H. (2021a). Meta-regression. In J. P. T. Higgins, M. Borenstein, H. Rothstein, & L. V. Hedges (Eds.), Introduction to meta-analysis (2nd ed., pp. 197–212). Wiley.
Borenstein, M., Hedges, L. V., Higgins, J. P. T., & Rothstein, H. (2021b). Random-effects model. In M. Borenstein, L. Hedges, J. Higgins, & H. Rothestein (Eds.), Introduction to meta-analysis (2nd ed., pp. 65–70). Wiley. https://www.wiley.com/en-us/Introduction+to+Meta-Analysis%2C+2nd+Edition-p-9781119558392
Borenstein, M., Hedges, L., Higgins, J., & Rothstein, H. (2022). Comprehensive Meta-Analysis (4). Biostat. https://www.meta-analysis.com/
Brenowitz, W. D., Hubbard, R. A., Keene, C. D., Hawes, S. E., Longstreth, W. T., Woltjer, R. L., & Kukull, W. A. (2017). Mixed neuropathologies and estimated rates of clinical progression in a large autopsy sample. Alzheimer’s & Dementia, 13(6), 654–662. https://doi.org/10.1016/J.JALZ.2016.09.015
Buchholz, A. S., Reckess, G. Z., Del Bene, V. A., Testa, S. M., Crawford, J. L., & Schretlen, D. J. (2023). Within-person test score distributions: How typical is “normal”? Assessment. https://doi.org/10.1177/10731911231201159/ASSET/IMAGES/LARGE/10.1177_10731911231201159-FIG1.JPEG
Bunce, D., Haynes, B. I., Lord, S. R., Gschwind, Y. J., Kochan, N. A., Reppermund, S., Brodaty, H., Sachdev, P. S., & Delbaere, K. (2017). Intraindividual stepping reaction time variability predicts falls in older adults with mild cognitive impairment. The Journals of Gerontology. Series A, Biological Sciences and Medical Sciences, 72(6), 832–837. https://doi.org/10.1093/GERONA/GLW164
Chang, J. (2011). Early detection of dementia of the Alzheimer’s type: Examining the use of cognitive tasks and neuropsychological tests for Chinese with minimal education [The Chinese University of Hong Kong]. https://www.proquest.com/dissertations-theses/early-detection-dementia-alzheimers-type/docview/993968160/se-2
Chow, R., Rabi, R., Paracha, S., Vasquez, B. P., Hasher, L., Alain, C., & Anderson, N. D. (2022). Reaction time intraindividual variability reveals inhibitory deficits in single- and multiple-domain amnestic mild cognitive impairment. The Journals of Gerontology. Series B, Psychological Sciences and Social Sciences, 77(1), 71–83. https://doi.org/10.1093/GERONB/GBAB051
Christ, B. U., Combrinck, M. I., & Thomas, K. G. F. (2018). Both reaction time and accuracy measures of intraindividual variability predict cognitive performance in Alzheimer’s disease. Frontiers in Human Neuroscience, 12. https://doi.org/10.3389/FNHUM.2018.00124
Christensen, H., Dear, K. B. G., Anstey, K. J., Parslow, R. A., Sachdev, P., & Jorm, A. F. (2005). Within-occasion intraindividual variability and preclinical diagnostic status: Is intraindividual variability an indicator of mild cognitive impairment? Neuropsychology, 19(3), 309–317. https://doi.org/10.1037/0894-4105.19.3.309
Cimler, R., Maresova, P., Kuhnova, J., & Kuca, K. (2019). Predictions of Alzheimer’s disease treatment and care costs in European countries. PloS One, 14(1). https://doi.org/10.1371/JOURNAL.PONE.0210958
Cooper, H., Hedges, L. V., & Valentine, J. C. (2019). The handbook of research synthesis and meta-analysis (H. Cooper, L. V. Hedges, & J. C. Valentine, Eds.). Russell Sage Foundation. https://doi.org/10.7758/9781610448864
Cooper, H. M. (1998). Synthesizing research: A guide for literature reviews applied social research methods. Sage.
Daianu, M., Mezher, A., Jahanshad, N., Hibar, D. P., Nir, T. M., Jack, C. R., Weiner, M. W., Bernstein, M. A., & Thompson, P. M. (2015). Spectral graph theory and graph energy metrics show evidence for the Alzheimer’s disease disconnection syndrome in APOE-4 risk gene carriers. Proceedings - International Symposium on Biomedical Imaging, 2015-July, 458–461. https://doi.org/10.1109/ISBI.2015.7163910
Deeks, J. J., Higgins, J. P., Altman, D. G., & on behalf of the Cochrane Statistical Methods Group. (2023). Analysing data and undertaking meta-analyses. In J. Higgins, J. Thomas, J. Chandler, M. Cumpston, T. Li, M. Page, & V. Welch (Eds.), Cochrane handbook for systematic reviews of interventions (6.4, pp. 241–284). John Wiley & Sons.
DerSimonian, R., & Laird, N. (1986). Meta-analysis in clinical trials. Controlled Clinical Trials, 7(3), 177–188. https://doi.org/10.1016/0197-2456(86)90046-2
Article CAS PubMed Google Scholar
Duchek, J. M., Balota, D. A., Tse, C. S., Holtzman, D. M., Fagan, A. M., & Goate, A. M. (2009). The utility of intraindividual variability in selective attention tasks as an early marker for Alzheimer’s disease. Neuropsychology, 23(6), 746–758. https://doi.org/10.1037/A0016583
Article PubMed PubMed Central Google Scholar
Dykiert, D., Der, G., Starr, J. M., & Deary, I. J. (2012). Age differences in intra-individual variability in simple and choice reaction time: Systematic review and meta-analysis. PloS One, 7(10). https://doi.org/10.1371/JOURNAL.PONE.0045759
Filippini, N., MacIntosh, B. J., Hough, M. G., Goodwin, G. M., Frisoni, G. B., Smith, S. M., Matthews, P. M., Beckmann, C. F., & Mackay, C. E. (2009). Distinct patterns of brain activity in young carriers of the APOE-ε4 allele. Proceedings of the National Academy of Sciences, 106(17), 7209–7214. https://doi.org/10.1073/PNAS.0811879106
Fiske, D. W., & Rice, L. (1955). Intra-individual response variability. Psychological Bulletin, 52(3), 217–250. https://doi.org/10.1037/H0045276
Article CAS PubMed Google Scholar
Fu, R., Gartlehner, G., Grant, M., Shamliyan, T., Sedrakyan, A., Wilt, T. J., Griffith, L., Oremus, M., Raina, P., Ismaila, A., Santaguida, P., Lau, J., & Trikalinos, T. A. (2011). Conducting quantitative synthesis when comparing medical interventions: AHRQ and the Effective Health Care Program. Journal of Clinical Epidemiology, 64(11), 1187–1197. https://doi.org/10.1016/J.JCLINEPI.2010.08.010
Gleason, C. E., Norton, D., Anderson, E. D., Wahoske, M., Washington, D. T., Umucu, E., Koscik, R. L., Dowling, N. M., Johnson, S. C., Carlsson, C. M., & Asthana, S. (2018). Cognitive variability predicts incident Alzheimer’s disease and mild cognitive impairment comparable to a cerebrospinal fluid biomarker. Journal of Alzheimer’s Disease : JAD, 61(1), 79–89. https://doi.org/10.3233/JAD-170498
Article CAS PubMed Google Scholar
Gorus, E., De Raedt, R., Lambert, M., Lemper, J. C., & Mets, T. (2008). Reaction times and performance variability in normal aging, mild cognitive impairment, and Alzheimer’s disease. Journal of Geriatric Psychiatry and Neurology, 21(3), 204–218. https://doi.org/10.1177/0891988708320973
Haan, M. N., Shemanski, L., Jagust, W. J., Manolio, T. A., & Kuller, L. (1999). The role of APOE ∊4 in modulating effects of other risk factors for cognitive decline in elderly persons. JAMA, 282(1), 40–46. https://doi.org/10.1001/JAMA.282.1.40
Article CAS PubMed Google Scholar
Halliday, D. W. R., Stawski, R. S., Cerino, E. S., Decarlo, C. A., Grewal, K., & Macdonald, S. W. S. (2018). Intraindividual variability across neuropsychological tests: Dispersion and disengaged lifestyle increase risk for Alzheimer’s disease. Journal of Intelligence, 6(1), 1–12. https://doi.org/10.3390/JINTELLIGENCE6010012
Haynes, B. I., Bauermeister, S., & Bunce, D. (2017). A systematic review of longitudinal associations between reaction time intraindividual variability and age-related cognitive decline or impairment, dementia, and mortality. Journal of the International Neuropsychological Society: JINS, 23(5), 431–445. https://doi.org/10.1017/S1355617717000236
Herukka, S. K., Simonsen, A. H., Andreasen, N., Baldeiras, I., Bjerke, M., Blennow, K., Engelborghs, S., Frisoni, G. B., Gabryelewicz, T., Galluzzi, S., Handels, R., Kramberger, M. G., Kulczyńska, A., Molinuevo, J. L., Mroczko, B., Nordberg, A., Oliveira, C. R., Otto, M., Rinne, J. O., … Waldemar, G. (2017). Recommendations for cerebrospinal fluid Alzheimer’s disease biomarkers in the diagnostic evaluation of mild cognitive impairment. Alzheimer’s & Dementia : The Journal of the Alzheimer’s Association, 13(3), 285–295. https://doi.org/10.1016/J.JALZ.2016.09.009
Hill, B. D., Rohling, M. L., Boettcher, A. C., & Meyers, J. E. (2013). Cognitive intra-individual variability has a positive association with traumatic brain injury severity and suboptimal effort. Archives of Clinical Neuropsychology, 28(7), 640–648. https://doi.org/10.1093/ARCLIN/ACT045
Hogan, M. J., Carolan, L., Roche, R. A. P., Dockree, P. M., Kaiser, J., Bunting, B. P., Robertson, I. H., & Lawlor, B. A. (2006). Electrophysiological and information processing variability predicts memory decrements associated with normal age-related cognitive decline and Alzheimer’s disease (AD). Brain Research, 1119(1), 215–226. https://doi.org/10.1016/J.BRAINRES.2006.08.075
Article CAS PubMed Google Scholar
Holtzer, R., Verghese, J., Wang, C., Hall, C. B., & Lipton, R. B. (2008). Within-person across-neuropsychological test variability and incident dementia. JAMA, 300(7), 823–830. https://doi.org/10.1001/JAMA.300.7.823
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