Hostname: page-component-76fb5796d-wq484 Total loading time: 0 Render date: 2024-04-25T11:20:53.192Z Has data issue: false hasContentIssue false

Effects of cognitive speed of processing training on a composite neuropsychological outcome: results at one-year from the IHAMS randomized controlled trial

Published online by Cambridge University Press:  14 September 2015

Fredric D. Wolinsky*
Affiliation:
John W. Colloton Chair of Health Management and Policy, College of Public Health, University of Iowa, Iowa City, Iowa, USA
Mark W. Vander Weg
Affiliation:
Investigator, Center for Comprehensive Access and Delivery Research and Evaluation, Iowa City VA HealthCare System, Iowa City, Iowa, USA
M. Bryant Howren
Affiliation:
Investigator, Center for Comprehensive Access and Delivery Research and Evaluation, Iowa City VA HealthCare System, Iowa City, Iowa, USA
Michael P. Jones
Affiliation:
Professor of Biostatistics, College of Public Health, University of Iowa, Iowa City, Iowa, USA
Megan M. Dotson
Affiliation:
Project Coordinator, College of Nursing, University of Iowa, Iowa City, Iowa, USA
*
Correspondence should be addressed to: Fredric D. Wolinsky, John W. Colloton Chair of Health Management and Policy, College of Public Health, University of Iowa, Iowa City, Iowa 52242, USA. Phone: +319-384-3821; Fax: +319-384-4371. Email: fredric-wolinsky@uiowa.edu.

Abstract

Background:

Age-related cognitive decline is common and well-documented. Cognitive speed of processing training (SOPT) has been shown to improve trained abilities (Useful Field of View; UFOV), but transfer to individual non-trained cognitive outcomes or neuropsychological composites is sparse. We examine the effects of SOPT on a composite of six equally weighted tests – UFOV, Trail-making A and B, Symbol Digit Modality, Controlled Oral Word Association, Stroop Color and Word, and Digit Vigilance.

Methods:

681 patients were randomized separately within two age-bands (50–64, ≥ 65) to three SOPT groups (10 initial hours on-site, 10 initial hours on-site plus 4 hours of boosters, or 10 initial hours at-home) or an attention-control group (10 initial hours on-site of crossword puzzles). At one-year, 587 patients (86.2%) had complete data. A repeated measures linear mixed model was used.

Results:

Factor analysis revealed a simple unidimensional structure with Cronbach's α of 0.82. The time effect was statistically significant (p < 0.001; ηp2 = 0.246), but the time by treatment group (p = 0.331), time by age-band (p = 0.463), and time by treatment group by age-band (p = 0.564) effects were not.

Conclusion:

Compared to the attention-control group who played a computerized crossword puzzle game, assignment to 10–14 hours of SOPT did not significantly improve a composite measure of cognitive abilities.

Type
Research Article
Copyright
Copyright © International Psychogeriatric Association 2015 

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

Ball, K. K., Beard, B. L., Roenker, D. L. and Miller, R. L. (1988). Age and visual search: expanding the useful field of view. Journal of the Optical Society of America, 5, 22102219. doi:10.1364/jossa.5.00210.Google Scholar
Ball, K. K., Edwards, J. D. and Ross, L. A. (2007). The impact of speed of processing training on cognitive and everyday functions. Journals of Gerontology: Psychological Sciences, Social Sciences, 62, 1931.CrossRefGoogle ScholarPubMed
Ball, K. K., Owsley, C., Sloane, M. E., Roenker, D. L. and Bruni, J. R. (1993). Visual attention problems as a predictor of vehicle crashes in older drivers. Investigations in Ophthalmological Visual Sciences, 34, 31103123.Google Scholar
Ball, K. K. et al. (2002). Effects of cognitive training interventions with older adults: a randomized controlled trial. JAMA, 288, 22712281. doi.org/10.1001/jama.288.18.2271.CrossRefGoogle ScholarPubMed
Barnes, D. E. et al. (2013). The Mental Activity and Exercise (MAX) Trial: a randomized controlled trial to enhance cognitive function in older adults. JAMA Internal Medicine, 173, 797804. doi:10.1001/jamainternmed.2013.189.CrossRefGoogle Scholar
Benton, A. L., Hamsher, K. and Silvan, A. B. (1994). Multilingual Aphasia Examination, 3rd edn. Iowa City, IA: AJA Associates.Google Scholar
Buitenweg, J. I., Murre, J. M. and Ridderinkhof, K. R. (2012). Brain training in progress: a review of trainability in healthy seniors. Frontiers of Human Neuroscience, 6, 183. doi:10.3389/fnhum.2012.00183.CrossRefGoogle ScholarPubMed
Calamia, M., Markon, K. and Tranel, D. (2012). Scoring higher the second time around: meta-analyses of practice effect in neuropsychological assessment. Clinical Neuropsychology, 26, 543570. doi:10.1080/13854046.2012.680913.Google Scholar
Christensen, H. (2001). What cognitive changes can be expected with normal ageing? Australia New Zealand Psychiatry, 35, 768775. doi:10.1046%2Fj.1440-1614.2001.00966.x.Google Scholar
Edwards, J. D. et al. (2005). Reliability and validity of useful field of view test scores as administered by personal computer. Journal of Clinical and Experimental Neuropsychology, 27, 529543.CrossRefGoogle ScholarPubMed
Freemantle, N., Calvert, M., Wood, J., Eastaugh, J. and Griffin, C. (2003). Composite outcomes in randomized trials: greater precision but with greater uncertainty? JAMA, 289, 25542559.CrossRefGoogle ScholarPubMed
Goldberg, R., Gore, J. M., Barton, B. and Gurwitz, J. (2014). Individual and composite study endpoints: separating the wheat from the chaff. American Journal of Medicine, 127, 379384. doi.org/10.1016/j.amjmed.2014.01.011.Google Scholar
Golden, C. J. (1978). The Stroop Color and Word Test. Chicago, IL: Stoelting Company.Google Scholar
Howren, M. B., Vander Weg, M. W. and Wolinsky, F. D. (2014). Computerized cognitive training interventions to improve health outcomes: evidence and future directions in the CER era. Journal of Comparative Effectiveness Research, 3, 145154. doi:10.2217/CER.14.6.Google Scholar
Lewis, R. and Rennick, P. M. (1979). Manual for the Repeatable Cognitive-Perceptual-Motor Battery. Gross Point, MI: Axon.Google Scholar
Lovden, M., Backman, L., Lindenberger, U., Schaefer, S. and Schmidek, F. (2010). A theoretical framework for the study of adult cognitive plasticity. Psychological Bulletin, 136, 659676.CrossRefGoogle Scholar
Mahncke, H. W. et al. (2006). Memory enhancement in health older adults using a brain plasticity-based training program: a randomized controlled study. Proceedings of the National Academy of Science, 103, 1252312528.Google Scholar
Montori, V. M. et al. (2005). Validity of composite end points in clinical trials. BMJ, 330, 594596.Google Scholar
Murphy, M., O’Sullivan, K. and Kelieher, K. G. (2014). Daily crosswords improve verbal fluency: a brief intervention study. International Journal of Geriatric Psychiatry, 29, 915919.CrossRefGoogle ScholarPubMed
National Institutes of Health. (2014). RFA-AG-14–016: Plasticity and Mechanisms of Cognitive Remediation in Older Adults. Bethesda, MD: National Institutes of Health.Google Scholar
Pfeiffer, E. (1975). A short portable mental status questionnaire for the assessment of organic brain deficit in elderly patients. Journal of the American Geriatrics Society, 23, 433–41. pmid:1159263.CrossRefGoogle Scholar
Rebok, G. L. et al. (2014). Cognitive training: results from the ACTIVE study at 10 years. Journal of the American Geriatrics Society, 62, 1624. doi:10.1111/jgs.12607.Google Scholar
Reitan, R. M. and Wolfson, D. (1993). The Halstead-Reitan Neuropsychological Test Battery: Therapy and Clinical Interpretation. Tucson, AZ: Neuropsychological Press.Google Scholar
Roenker, D. L., Cissell, G. M., Ball, K. K., Wadley, V. G. and Edwards, J. D. (2003). Speed of processing and driver simulator training result in improved driving performance. Human Factors, 45, 218233. doi:10.1518/hfes.45.2.218.27241.CrossRefGoogle ScholarPubMed
Smith, A. (1982). Symbol Digit Modality Test. Los Angeles, CA: Western Psychological Services.Google Scholar
Smith, G. E. et al. (2009). A cognitive training program based on principles of brain plasticity: results from the Improvement in Memory with Plasticity-based Adaptive Cognitive Training (IMPACT) study. Journal of the American Geriatrics Society, 57, 94603. doi:10.1111/j.1532-5415.2008.02167.Google Scholar
Wadley, V. G., Benz, R. I., Ball, K. K., Roenker, D. L., Edwards, J. D. and Vance, D. E. (2006). Development and evaluation of home-based speed of processing training for older adults. Archives of Physical and Medical Rehabilitation, 87, 757763. doi.org/10.1016/j.apmr.2006.02.027.Google Scholar
Willis, S. L. et al. (2006). Long-term effects of cognitive training on everyday functional outcomes in older adults. JAMA, 296, 28052814. doi.org/10.1001/jama.296.23.2805.Google Scholar
Wolinsky, F. D., Vander Weg, M. W., Howren, M. B., Jones, M. P. and Dotson, M. M. (2013). A randomized controlled trial of cognitive training using a visual speed of processing intervention in middle aged and older adults. PLoS One, 8, e61624. doi:10.1371/journal.pone.0061624.Google Scholar
Wolinsky, F. D. et al. (2011). Interim results from a randomized controlled trial to improve visual processing speed in older adults: the Iowa Healthy and Active Minds Study. BMJ Open, 1, 113. doi:10.1136/bmjopen-2011-000225.Google Scholar