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Technology

Assessment of non-directed computer-use behaviours in the home can indicate early cognitive impairment: A proof of principle longitudinal study

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Pages 193-202 | Received 01 Sep 2021, Accepted 21 Jan 2022, Published online: 30 Mar 2022

References

  • Baddeley, A. D., Emslie, H., & Nimmo-Smith, I. (1994). The doors and people test: A test of visual and verbal recall and recognition. Thames Valley Test Company.
  • Balota, D. A., Tse, C. S., Hutchison, K. A., Spieler, D. H., Duchek, J. M., & Morris, J. C. (2010). Predicting conversion to dementia of the Alzheimer’s type in a healthy control sample: The power of errors in Stroop color naming. Psychology and Aging, 25(1), 208–218. https://doi.org/10.1037/a0017474
  • Benjamini, Y., & Hochberg, Y. (1995). Controlling the false discovery rate: A practical and powerful approach to multiple testing. Journal of the Royal Statistical Society: Series B (Methodological)), 57(1), 289–300. www.jstor.org/stable/2346101 https://doi.org/10.1111/j.2517-6161.1995.tb02031.x
  • Bull, C., Asfiandy, D., Gledson, A., Mellor, J., Couth, S., Stringer, G., Rayson, P., Sutcliffe, A., Keane, J., Zeng, X., Burns, A., Leroi, I., Ballard, C., Sawyer, P. (2016). Combining data mining and text mining for detection of early stage dementia: The SAMS framework. Resources and Processing of Linguistic and Extra-Linguistic Data from People with Various Forms of Cognitive/Psychiatric Impairments (RaPID ‘16) Workshop: Proceedings of the 10th International Conference on Language Resources and Evaluation (LREC ‘16). European Language Resources Association (ELRA).
  • Deary, I. J., Liewald, D., & Nissan, J. (2011). A free, easy-to-use, computer-based simple and four-choice reaction time programme: The Deary-Liewald reaction time task [Research Support, Non-U S Gov’t]. Behavior Research Methods, 43(1), 258–268. https://doi.org/10.3758/s13428-010-0024-1
  • Delis, D. C., Kaplan, E., & Kramer, J. H. (2001). Delis-Kaplan executive function system (D-KEFS). The Psychology Corporation.
  • Dodge, H. H., Mattek, N. C., Austin, D., Hayes, T. L., & Kaye, J. A. (2012). In-home walking speeds and variability trajectories associated with mild cognitive impairment. Neurology, 78(24), 1946–1952. https://doi.org/10.1212/WNL.0b013e318259e1de
  • Dorsey, E. R., Papapetropoulos, S., Xiong, M., & Kieburtz, K. (2017). The first frontier: Digital biomarkers for neurodegenerative disorders. Digital Biomarkers, 1(1), 6–13. https://doi.org/10.1159/000477383
  • Farias, S. T., Chou, E., Harvey, D. J., Mungas, D., Reed, B., DeCarli, C., Park, L. Q., & Beckett, L. (2013). Longitudinal trajectories of everyday function by diagnostic status. Psychology and Aging, 28(4), 1070–1075. https://doi.org/10.1037/a0034069
  • Farias, S. T., Mungas, D., Reed, B. R., Cahn-Weiner, D., Jagust, W., Baynes, K., & Decarli, C. (2008). The measurement of everyday cognition (ECog): Scale development and psychometric properties. Neuropsychology, 22(4), 531–544. https://doi.org/10.1037/0894-4105.22.4.531
  • Farias, S., Cahn-Weiner, D., Harvey, D., Reed, B., Mungas, D., Kramer, J., & Chui, H. (2009). Longitudinal changes in memory and executive functioning are associated with longitudinal change in instrumental activities of daily living in older adults. The Clinical Neuropsychologist, 23(3), 446–461. http://www.scopus.com/inward/record.url?eid=2-s2.0-66149095457&partnerID=40&md5=7c80c8a3618197f088d1291ad047c625 https://doi.org/10.1080/13854040802360558
  • Fine, E. M., Delis, D. C., Wetter, S. R., Jacobson, M. W., Jak, A. J., McDonald, C. R., Braga, J. C., Thal, L. J., Salmon, D. P., & Bondi, M. W. (2008). Cognitive discrepancies versus APOE genotype as predictors of cognitive decline in normal-functioning elderly individuals: A longitudinal study. The American Journal of Geriatric Psychiatry: Official Journal of the American Association for Geriatric Psychiatry, 16(5), 366–374. https://doi.org/10.1097/JGP.0b013e3181629957
  • Gledson, A., Asfiandy, D., Mellor, J., Ba-Dhfari, T.O. F., Stringer, G., Couth, S., Burns, A., Leroi, I., Zeng, X., Keane, J., Bull, C., Rayson, P., Sutcliffe, A., & Sawyer, P. (2016). Combining mouse and keyboard events with higher level desktop actions to detect mild cognitive impairment [Paper presentation]. 2016 IEEE International Conference on Healthcare Informatics (ICHI), Chicago, IL, October 4–7.
  • Gold, M., Amatniek, J., Carrillo, M. C., Cedarbaum, J. M., Hendrix, J. A., Miller, B. B., Robillard, J. M., Rice, J. J., Soares, H., Tome, M. B., Tarnanas, I., Vargas, G., Bain, L. J., & Czaja, S. J. (2018). Digital technologies as biomarkers, clinical outcomes assessment, and recruitment tools in Alzheimer’s disease clinical trials. Alzheimer’s & Dementia (New York, N. Y.), 4, 234–242. https://doi.org/10.1016/j.trci.2018.04.003
  • Greene, J. D., Baddeley, A. D., & Hodges, J. R. (1996). Analysis of the episodic memory deficit in early Alzheimer’s disease: Evidence from the doors and people test. Neuropsychologia, 34(6), 537–551. https://doi.org/10.1016/0028-3932(95)00151-4
  • Grober, E., Ocepek-Welikson, K., & Teresi, J. (2009). The free and cued selective reminding test: Evidence of psychometric adequacy. Psychology Science Quarterly, 51, 266–282.
  • Grober, E., Sanders, A. E., Hall, C., & Lipton, R. B. (2010). Free and cued selective reminding identifies very mild dementia in primary care. Alzheimer Disease and Associated Disorders, 24(3), 284–290. https://doi.org/10.1097/WAD.0b013e3181cfc78b
  • Hagler, S., Austin, D., Hayes, T. L., Kaye, J., & Pavel, M. (2010). Unobtrusive and ubiquitous in-home monitoring: A methodology for continuous assessment of gait velocity in elders. IEEE Transactions on Bio-Medical Engineering, 57(4), 813–820. https://doi.org/10.1109/TBME.2009.2036732
  • Hayes, T. L., Abendroth, F., Adami, A., Pavel, M., Zitzelberger, T. A., & Kaye, J. A. (2008). Unobtrusive assessment of activity patterns associated with mild cognitive impairment. Alzheimer’s & Dementia, 4(6), 395–405. https://doi.org/10.1016/j.jalz.2008.07.004
  • Hsieh, S., Schubert, S., Hoon, C., Mioshi, E., & Hodges, J. R. (2013). Validation of the Addenbrooke’s cognitive examination III in frontotemporal dementia and Alzheimer’s disease. Dementia and Geriatric Cognitive Disorders, 36(3-4), 242–250. https://doi.org/10.1159/000351671
  • Hutchison, K. A., Balota, D. A., Duchek, J. M., & Ducheck, J. M. (2010). The utility of Stroop task switching as a marker for early-stage Alzheimer’s disease. Psychology and Aging, 25(3), 545–559. https://doi.org/10.1037/a0018498
  • Jekel, K., Damian, M., Wattmo, C., Hausner, L., Bullock, R., Connelly, P. J., Dubois, B., Eriksdotter, M., Ewers, M., Graessel, E., Kramberger, M. G., Law, E., Mecocci, P., Molinuevo, J. L., Nygard, L., Olde-Rikkert, M. G., Orgogozo, J. M., Pasquier, F., Peres, K., … Frolich, L. (2015). Mild cognitive impairment and deficits in instrumental activities of daily living: A systematic review. Alzheimer’s Research & Therapy, 7(1), 17. https://doi.org/10.1186/s13195-015-0099-0
  • Kaye, J. A., Maxwell, S. A., Mattek, N., Hayes, T. L., Dodge, H., Pavel, M., Jimison, H. B., Wild, K., Boise, L., & Zitzelberger, T. A. (2011). Intelligent systems for assessing aging changes: Home-based, unobtrusive, and continuous assessment of aging. The Journals of Gerontology. Series B, Psychological Sciences and Social Sciences, 66(Suppl 1), i180–i190. https://doi.org/10.1093/geronb/gbq095
  • Kaye, J., Mattek, N., Dodge, H. H., Campbell, I., Hayes, T., Austin, D., Hatt, W., Wild, K., Jimison, H., & Pavel, M. (2014). Unobtrusive measurement of daily computer use to detect mild cognitive impairment. Alzheimer’s & Dementia: The Journal of the Alzheimer’s Association, 10(1), 10–17. https://doi.org/10.1016/j.jalz.2013.01.011
  • Kirste, T., Hoffmeyer, A., Koldrack, P., Bauer, A., Schubert, S., Schroder, S., & Teipel, S. (2014). Detecting the effect of Alzheimer’s disease on everyday motion behavior. Journal of Alzheimer’s Disease: JAD, 38(1), 121–132. https://doi.org/10.3233/JAD-130272
  • Lezak, M. D., Howieson, D. B., Bigler, E. D., & Tranel, D. (2012). Neuropsychological Assessement (5th ed.). Oxford University Press.
  • Marshall, G. A., Amariglio, R. E., Sperling, R. A., & Rentz, D. M. (2012). Activities of daily living: Where do they fit in the diagnosis of Alzheimer’s disease? Neurodegenerative Disease Management, 2(5), 483–491. https://doi.org/10.2217/nmt.12.55
  • Marshall, G. A., Zoller, A. S., Lorius, N., Amariglio, R. E., Locascio, J. J., Johnson, K. A., Sperling, R. A., & Rentz, D. M. (2015). Functional activities Questionnaire items that best discriminate and predict progression from clinically normal to mild cognitive impairment. Current Alzheimer Research, 12(5), 493–502. https://doi.org/10.2174/156720501205150526115003
  • Mitchell, A. J., & Shiri-Feshki, M. (2009). Rate of progression of mild cognitive impairment to dementia-meta-analysis of 41 robust inception cohort studies. Acta Psychiatrica Scandinavica, 119(4), 252–265. https://doi.org/10.1111/j.1600-0447.2008.01326.x
  • Office for National Statistics. (2019a). Internet access – Households and individuals, Great Britain: 2019. www.ons.gov.uk
  • Office for National Statistics. (2019b). Internet users, UK: 2019. https://www.ons.gov.uk/businessindustryandtrade/itandinternetindustry/bulletins/internetusers/2019
  • Patel, S., Park, H., Bonato, P., Chan, L., & Rodgers, M. (2012). A review of wearable sensors and systems with application in rehabilitation. Journal of NeuroEngineering and Rehabilitation, 9(1), 21. https://doi.org/10.1186/1743-0003-9-21
  • Petersen, R. C. (2004). Mild cognitive impairment as a diagnostic entity. Journal of Internal Medicine, 256(3), 183–194. https://doi.org/10.1111/j.1365-2796.2004.01388.x
  • Piau, A., Wild, K., Mattek, N., & Kaye, J. (2019). Current state of digital biomarker technologies for real-life, home-based monitoring of cognitive function for mild cognitive impairment to mild Alzheimer disease and implications for clinical care: systematic review. Journal of Medical Internet Research, 21(8), e12785. https://doi.org/10.2196/12785
  • Rodakowski, J., Skidmore, E. R., Reynolds, C. F., 3rd, Dew, M. A., Butters, M. A., Holm, M. B., Lopez, O. L., & Rogers, J. C. (2014). Can performance on daily activities discriminate between older adults with normal cognitive function and those with mild cognitive impairment? Journal of the American Geriatrics Society, 62(7), 1347–1352. https://doi.org/10.1111/jgs.12878
  • Scarpina, F., & Tagini, S. (2017). The Stroop color and word test. Frontiers in Psychology, 8, 557–557. https://doi.org/10.3389/fpsyg.2017.00557
  • Seelye, A., Hagler, S., Mattek, N., Howieson, D. B., Wild, K., Dodge, H. H., & Kaye, J. A. (2015). Computer mouse movement patterns: A potential marker of mild cognitive impairment. Alzheimer’s & Dementia: Diagnosis, Assessment & Disease Monitoring, 1(4), 472–480. https://doi.org/10.1016/j.dadm.2015.09.006
  • Seelye, A., Mattek, N., Sharma, N., Riley, T., Austin, J., Wild, K., Dodge, H. H., Lore, E., & Kaye, J. (2018). Weekly observations of online survey metadata obtained through home computer use allow for detection of changes in everyday cognition before transition to mild cognitive impairment. Alzheimer’s & Dementia, 14(2), 187–194. https://doi.org/10.1016/j.jalz.2017.07.756
  • Shindo, A., Terada, S., Sato, S., Ikeda, C., Nagao, S., Oshima, E., Yokota, O., & Uchitomi, Y. (2013). Trail making test part a and brain perfusion imaging in mild Alzheimer’s disease. Dementia and Geriatric Cognitive Disorders Extra, 3(1), 202–211. https://doi.org/10.1159/000350806
  • Sikkes, S. A., Visser, P. J., Knol, D. L., de Lange-de Klerk, E. S., Tsolaki, M., Frisoni, G. B., Nobili, F., Spiru, L., Rigaud, A. S., Frolich, L., Rikkert, M. O., Soininen, H., Touchon, J., Wilcock, G., Boada, M., Hampel, H., Bullock, R., Vellas, B., Pijnenburg, Y. A., … Uitdehaag, B. M. (2011). Do instrumental activities of daily living predict dementia at 1- and 2-year follow-up? Findings from the development of screening guidelines and diagnostic criteria for predementia Alzheimer’s disease study. Journal of the American Geriatrics Society, 59(12), 2273–2281. https://doi.org/10.1111/j.1532-5415.2011.03732.x
  • Starkstein, S. E., Mayberg, H. S., Preziosi, T. J., Andrezejewski, P., Leiguarda, R., & Robinson, R. G. (1992). Reliability, validity, and clinical correlates of apathy in Parkinson’s disease. The Journal of Neuropsychiatry and Clinical Neurosciences, 4(2), 134–139. https://doi.org/10.1176/jnp.4.2.134
  • Stringer, G., Couth, S., Brown, L. J. E., Montaldi, D., Gledson, A., Mellor, J., Sutcliffe, A., Sawyer, P., Keane, J., Bull, C., Zeng, X., Rayson, P., & Leroi, I. (2018). Can you detect early dementia from an email? A proof of principle study of daily computer use to detect cognitive and functional decline. International Journal of Geriatric Psychiatry, 33(7), 867–874. https://doi.org/10.1002/gps.4863
  • Stroop, J. R. (1935). Studies of interference in serial verbal reactions. Journal of Experimental Psychology, 18(6), 643–662. https://doi.org/10.1037/h0054651
  • Tun, P. A., & Lachman, M. E. (2010). The association between computer use and cognition across adulthood: Use it so you won’t lose it? Psychology and Aging, 25(3), 560–568. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3281759/pdf/nihms350608.pdf https://doi.org/10.1037/a0019543
  • Van Selst, M., & Jolicoeur, P. (2018). A Solution to the Effect of Sample Size on Outlier Elimination. The Quarterly Journal of Experimental Psychology Section A, 47(3), 631–650. https://doi.org/10.1080/14640749408401131
  • Vizer, L. M., & Sears, A. (2015). Classifying text-based computer interactions for health monitoring. IEEE Pervasive Computing, 14(4), 64–71. https://doi.org/10.1109/Mprv.2015.85
  • Yesavage, J. A. (1988). Geriatric depression scale. Psychopharmacology Bulletin, 24(4), 709–711.