Butler PM, Yang J, Brown R, Hobbs M, Becker A, Penalver-Andres J, Syz P, Muller S, Cosne G, Juraver A, Song HH, Saha-Chaudhuri P, Roggen D, Scotland A, Silveira N, Demircioglu G, Gabelle A, Hughes R, Erkkinen MG, Langbaum JB, Lingler JH, Price P, Quiroz YT, Sha SJ, Sliwinski M, Porsteinsson AP, Au R, Bianchi MT, Lenyoun H, Pham H, Patel M, Belachew S. Smartwatch- and smartphone-based remote assessment of brain health and detection of mild cognitive impairment. Nat Med. 2025 Mar;31(3):829-839. Epub 2025 Mar 4 PubMed.
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Harvard Medical School
I think the main takeaway from this work is that large-scale cognitive monitoring is truly feasible. No other study has been able to collect such detailed cognitive data, remotely, on such a large sample with such geographic, ethnoracial, and educational representation. This is an impressive project!
Their ability to maintain high levels of participation over time was formidable, and indicates that incentivizing participants with smartwatch ownership was a winning strategy. This specific approach of incentivization may not be generalizable to other studies or clinical practice, but it does inform us about motivating factors that could be leveraged in the future.
While this study was remarkable in showing feasibility, I do think it is premature to conclude that MCI can be diagnosed fully remotely with digital tests and surveys—but this is clearly a step in that direction. It was striking that subjective concerns by the participants were the best predictors of MCI diagnosis, rather than more commonly observed measures of objective cognition and age, which raises questions about the robustness of the MCI designation across the different MCI groups. That said, only a small portion of what appears to be an enormous and rich dataset has been published, and we hope that future learnings, if not raw data, from this study will be shared in the name of scientific advancement.
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