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Detection and Continuous Monitoring of Memory Dysfunction in Mild Cognitive Impairment and Healthy Aging Through Adaptive Computational Phenotyping
Hake, H. S.; van der Velde, M.; Grabowski, T.; van Rijn, H.; Stocco, A.. medRxiv (preprint), 2026-09-12
Topic: Risk, prevention and care in population studies
These findings show that model-based, adaptive assessments can support high-frequency, remote detection and scalable longitudinal monitoring of early memory decline, providing a new way to assess memory decline trajectories in healthy aging and dementia. As a result, changes in memory function are often detected too late and their trajectories cannot be traced. These results demonstrate that digital, model-driven cognitive assessments can support scalable, high-frequency monitoring of memory decline.
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APA 7th
Hake, H. S., van der Velde, M., Grabowski, T., van Rijn, H., & Stocco, A. (2026). Detection and Continuous Monitoring of Memory Dysfunction in Mild Cognitive Impairment and Healthy Aging Through Adaptive Computational Phenotyping. medRxiv (preprint). https://doi.org/10.1101/2024.03.15.24304345
Vancouver
Hake HS, van der Velde M, Grabowski T, van Rijn H, Stocco A. Detection and Continuous Monitoring of Memory Dysfunction in Mild Cognitive Impairment and Healthy Aging Through Adaptive Computational Phenotyping. medRxiv (preprint). 2026. doi:10.1101/2024.03.15.24304345.
BibTeX
@article{hake2026-e09a5c42,
author = {Hake, H. S. and van der Velde, M. and Grabowski, T. and van Rijn, H. and Stocco, A.},
title = {{Detection and Continuous Monitoring of Memory Dysfunction in Mild Cognitive Impairment and Healthy Aging Through Adaptive Computational Phenotyping}},
journal = {medRxiv (preprint)},
year = {2026},
doi = {10.1101/2024.03.15.24304345},
url = {https://doi.org/10.1101/2024.03.15.24304345}
}
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Key findings
- These findings show that model-based, adaptive assessments can support high-frequency, remote detection and scalable longitudinal monitoring of early memory decline, providing a new way to assess memory decline trajectories in healthy aging and dementia.
- As a result, changes in memory function are often detected too late and their trajectories cannot be traced.
- These results demonstrate that digital, model-driven cognitive assessments can support scalable, high-frequency monitoring of memory decline.
Why it matters
This study shows that model-based, adaptive digital assessments can support high-frequency remote monitoring of early memory decline in healthy aging and mild cognitive impairment. It is a monitoring tool, not a treatment, cure, or prevention for Alzheimer's disease.
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Study details
- Study designlongitudinal study
- Participants24
- Effect size0.2%
- Evidence strengthModerate
How this study scored 16/100
Preprint — not yet peer-reviewed. It scored 44 on the same rubric, but non-peer-reviewed sources are capped at 16, so it shows as 16. Scored zero for randomised / blinded because the record does not state it. We have no data on times cited, citations per year, impact for its field and year, still being cited, senior author's track record, institution's track record and multi-centre collaboration, so those were left out: it earned 30 of the 68 points we could judge it on, which is 44 out of 100.
| Component | Points | Why |
|---|---|---|
| Journal tier | 2 / 10 | Tier 4 — not a peer-reviewed journal (medRxiv (preprint)) |
| Journal's citation record | 0 / 4 | Not a journal article, so the journal's record does not count |
| Study design | 7 / 12 | A longitudinal study following the same people over time |
| Strength of evidence | 3 / 5 | Rated “moderate” in our summary |
| Peer-review validation | 4 / 10 | Preprint — not yet peer-reviewed. Hosted on a preprint server. |
| How recent | 5 / 5 | 2026 — within 1 year(s) of the newest study here |
| Sample size | 1 / 4 | 24 participants |
| Effect reported | 2 / 3 | Effect reported as a number, without an interval or test |
| Studied in people | 3 / 3 | Studied in people (participant count stated) |
| Randomised / blinded | 0 / 2 | No randomisation or blinding stated — scores zero (not stated in the record — scored 0) |
| Times cited | — / 7 | No citation count (OpenAlex dates this DOI to 2024, the record says 2026; OpenAlex values not used) — left out of this score |
| Citations per year | — / 5 | No citation count or no year — left out of this score |
| Impact for its field and year | — / 6 | No field-weighted citation impact (OpenAlex has none yet) — left out of this score |
| Cited by studies here | 0 / 6 | No other study in this library cites it |
| Still being cited | — / 4 | No yearly citation counts — left out of this score |
| Senior author's track record | — / 4 | Senior author's record not available — left out of this score |
| Institution's track record | — / 3 | No institution listed in OpenAlex — left out of this score |
| Multi-centre collaboration | — / 3 | Institutions not listed — left out of this score |
| Indexed in PubMed | 1 / 2 | Not in PubMed, but has a DOI |
| Free to read | 2 / 2 | Free to read |
| Points | 30 / 68 | Scored on 13 of 20 parts. We have no data for the rest, so they are left out: 30 of the 68 points we could judge it on is 44 out of 100. |
| Total | 44 / 100 | Capped to 16 because this is not a peer-reviewed article. |
What each of these 20 components measures, and what this score is not →
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Also tagged “assessment”
840 studies in the library carry the topic tag “assessment”; these are this study's neighbours in a fixed, alphabetical-by-hash tour of them, not the closest in content. All 840 tagged studies.