Melanie Wong

Alzheimer’s disease (AD) afflicts as many as 5.8 million Americans, and the prevalence is expected to triple to 14 million people by 2060 [1]. Currently, there are no pharmacological treatments on the market to treat the pathogenesis of the disease itself – only the accompanying symptoms. Since the exact pathophysiology of the disease is relatively unclear, it is challenging to develop therapies that target a specific pathway like in other disease states. While novel therapeutics for AD continue to be evaluated in clinical trials, other non-pharmacologic approaches to treating the disease, including computerized cognitive training (CCT), have been developed to improve cognitive outcomes amongst patients with impaired cognition [2].

CCT is a digital brain therapy that has revolutionized the field of neurology. It is an application in which individuals are able to engage in exercises that stimulate their minds and promote overall enhanced cognitive functioning. Exercises include those that target memory and learning, attention, speed, and executive functioning in order to improve activities of daily living for those diagnosed with AD [2]. 

The integration of technology into the healthcare arena, especially in the field of neurology, does not have as much robust data to support its efficacy in treating patients with cognitive impairments. However, there is a growing body of research from various observational research studies, randomized controlled trials, and meta-analyses to highlight the benefits of CCT in older adults.

The Advanced Cognitive Training for Independent and Vital Elderly (ACTIVE) trial aimed to address how systematic cognitive training therapies translated to real-world functional outcomes in late adulthood [3]. The test targeted abilities of memory, reasoning, and speed and were designed to enhance everyday problem-solving, speed, and activities of daily living amongst individuals aged 65 years or older with intact cognitive functioning. The participants were assigned to one of the three interventions and followed for five years and re-assessed for any improvements in cognitive tasks. Those in the reasoning group reported fewer issues with daily living, while those in the speed group were involved in fewer at-fault motor vehicle accidents. The memory group showed no discernible benefits after 5 years of training [3].

A randomized controlled trial evaluating CCT in improving cognitive function in older adults assessed the use of this technology in those with mild cognitive impairment (MCI) or mood-related neuropsychiatric symptoms (MrNPS) [4]. In the MCI group, it was found that those who used CCT had greater improvements on composite measures of memory, learning, and global cognition at the three month follow-up. Furthermore, individuals with MrNPS in the CCT group were reported to have fewer depressive symptoms immediately following the intervention [4].

A meta-analysis comprised of 52 studies evaluating the effects of CCT in enhancing cognitive performance amongst healthy older adults showed modest effects in improving cognition compared to the control group [5]. Verbal memory, non-verbal memory, working memory, processing speed, and visuospatial skills were assessed and showed small to moderate statistically significant beneficial effect size amongst all studies (g=0.22, 95% CI 0.15-0.29). The meta-analysis also illuminated the notion that group-based training had more positive effects in augmenting cognitive abilities compared to home-based training. This finding suggests that online supervision of patients using CCT may promote improved functional outcomes in the future compared to those who engage in solo training [5].

Although CCT shows promising results in enhancing cognitive outcomes, its use has not been widely studied amongst those who have already been diagnosed with AD. However, given that CCT is safe, relatively inexpensive, and adaptable to an individual’s specific cognitive needs, healthcare providers may consider it as an adjunctive non-pharmacologic therapy to promote mental stimulation as medical practice continues to conform to the digital health revolution.

This article has been approved and reviewed by the Scientific Writing Team Lead of Esurgi : Ishtiak Ahmed Chowdhury

References

  1. Matthews, K. A., Xu, W., Gaglioti, A. H., Holt, J. B., Croft, J. B., Mack, D., & McGuire, L. C. (2018). Racial and ethnic estimates of Alzheimer’s disease and related dementias in the United States (2015–2060) in adults aged≥ 65 years. Alzheimer’s & Dementia. https://doi.org/10.1016/j.jalz.2018.06.3063 
  2. Bodner, K. A., Goldberg, T. E., Devanand, D. P., & Doraiswamy, P. M. (2020). Advancing Computerized Cognitive Training for MCI and Alzheimer’s Disease in a Pandemic and Post-pandemic World. Frontiers in psychiatry, 11, 557571. https://doi.org/10.3389/fpsyt.2020.557571
  3. ​​Tennstedt, S. L., & Unverzagt, F. W. (2013). The ACTIVE study: study overview and major findings. Journal of aging and health, 25(8 Suppl), 3S–20S. https://doi.org/10.1177/0898264313518133
  4. Bahar-Fuchs, A., Webb, S., Bartsch, L., Clare, L., Rebok, G., Cherbuin, N., & Anstey, K. J. (2017). Tailored and Adaptive Computerized Cognitive Training in Older Adults at Risk for Dementia: A Randomized Controlled Trial. Journal of Alzheimer’s disease : JAD, 60(3), 889–911. https://doi.org/10.3233/JAD-170404
  5. Lampit, A., Hallock, H., & Valenzuela, M. (2014). Computerized cognitive training in cognitively healthy older adults: a systematic review and meta-analysis of effect modifiers. PLoS medicine, 11(11), e1001756. https://doi.org/10.1371/journal.pmed.1001756
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