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Find studies

Showing 1–13 of 13 studies in Cognitive tests and assessment in Research square · 27,380 in the whole library · How the 0–100 score works

Browse by subject, author or institution

Each number is how many studies that link shows, with your other filters kept.

What “Cognitive tests and assessment” covers

Cognitive tests and assessment — Memory and thinking tests, screening tools and rating scales: how well they measure what they claim to.

A note on reading research. One study is rarely the final word.

We try to note the size of a study, whether it was in humans or animals, and how early-stage the finding is. If a summary here doesn't make that clear, treat it with extra caution and check the original source.

Identifying and Predicting Cognitive Decline Using Multi-Modal Sensor Data and Machine Learning Approach

⚠ Preprint — not yet peer-reviewed alzhub usefulness score 16 out of 100. Research square 2025-06-18

Our results demonstrate that the multi-modal classifier achieved strong classification performance (accuracy = 68.64%; precision = 73.97%; F1-score=74.48%), with the highest recall (76.39%) from a model incorporating demographics and driving features, and prediction performance (accuracy = 70.48%; precision = 71.88%; F1-score = 74.80%, recall = 77.97%). 1 key finding →

Participants: 118 Evidence: low

Factors Influencing the Implementation of Computerized Cognitive Training in Chinese Community-Dwelling Elderly: A Qualitative Study

⚠ Preprint — not yet peer-reviewed alzhub usefulness score 16 out of 100. Research Square 2026-10-28

Four main themes were extracted: (1) Positive experiences, including perceived improvement in cognitive function and mood; (2) Facilitators and barriers to training participation, with facilitators comprising dementia care experience, higher educational attainment, and availability of free time, and barriers including unfamiliarity with computer operation, low awareness of cognitive training, and lengthy training sessions; (3) Training content preferences, reflecting a desire for both relaxed, engaging content and professional guidance; and (4) Practical dilemmas and suggestions, including difficulties in understanding task instructions and complex login procedures, with recommendations for detailed task descriptions and simplified procedures. 4 key findings →

Evidence: low

Although smartphone usage time is not directly associated with ikigai in older adults, it may reflect preserved physical and cognitive abilities required to navigate digital environments. 5 key findings →

Design: cross-sectional Evidence: low

This study provides quantitative evidence supporting the complementary use of multiple cognitive assessment tools. 4 key findings →

Design: cross-sectional Participants: 250 Evidence: low

Living arrangements shape the determinants of life-sustaining treatment preferences among Korean older adults

⚠ Preprint — not yet peer-reviewed alzhub usefulness score 16 out of 100. Research Square 2026-08-31

Although most Korean older adults declined LST regardless of living arrangement, determinants of LST preferences differed according to household structure. 5 key findings →

Design: longitudinal study Participants: 3,787 Evidence: moderate

The Ignite app detects early cognitive impairment and tracks disease severity in genetic frontotemporal dementia

⚠ Preprint — not yet peer-reviewed alzhub usefulness score 16 out of 100. Research Square 2026-08-03

Ignite is a sensitive digital cognitive assessment capable of detecting early cognitive changes in genetic FTD and demonstrates improved discrimination compared with standard neuropsychological measures at milder disease severity. 5 key findings →

Participants: 190 Evidence: low

rTMS renews long-tract myelination to improve AD cognitive function predicted by baseline myelin and E-field

⚠ Preprint — not yet peer-reviewed alzhub usefulness score 16 out of 100. Research Square 2026-09-25

This study reveals a myelin-mediated mechanism of rTMS action in AD, demonstrating the potential of promoting myelination as a novel therapeutic strategy for alleviating AD-related cognitive impairment. 3 key findings →

Evidence: low

How Reliable and Explainable Are Machine Learning Models for Dementia Detection? A Leakage-Aware Evaluation

⚠ Preprint — not yet peer-reviewed alzhub usefulness score 16 out of 100. Research Square 2026-09-09

Reported dementia-classification performance depends on how the label is defined, which clinical information the model sees, and whether participants are separated between training and test data. 5 key findings →

Participants: 150 Evidence: moderate

Cognitive Performance in Spouses of Individuals with Alzheimer’s Disease: A Controlled Cross-Sectional Study

⚠ Preprint — not yet peer-reviewed alzhub usefulness score 16 out of 100. Research Square 2026-08-25

We compared global and domain-level cognitive performance in older adults without a prior dementia diagnosis based on whether their cohabiting spouse had Alzheimer’s disease. 1 key finding →

Design: cross-sectional Participants: 350 Evidence: low

HbA1c levels had warning value for cognitive impairment in non diabetes patients with WMH, and a nonlinear correlation exists between HbA1c and WMH-related cognitive impairment. 3 key findings →

Participants: 497 Evidence: low

A study on the Mini-cog scale in the general screening of cognitive status among the elderly in Putian city

⚠ Preprint — not yet peer-reviewed alzhub usefulness score 16 out of 100. Research Square 2026-08-03

In dialect-dominant, educationally diverse elderly, Mini-cog provides superior diagnostic accuracy for MCI versus HKBC and MoCA, and comparable accuracy for dementia. 4 key findings →

Design: cross-sectional Participants: 450 Evidence: low

Irrespective of ERG modality, ADRD was consistently associated with retinal dysfunction marked by impaired synaptic transmission and delayed neural processing across retinal circuits. 3 key findings →

Design: meta-analysis Participants: 18 Evidence: high

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Where “Free full text” comes from

Free full text links and the Full text may need a subscription label come from Unpaywall, Europe PMC and OpenAlex records of free copies, checked 10 Oct 2026. A study with neither is unknown, not paywalled. Show only studies that are free to read

How the 0–100 score works — and why some entries are capped

This is alzhub's own score. It is not an official metric, not an impact factor, and no journal, publisher or ranking body endorses it. We built it so that a reader who is not a scientist can tell a landmark trial from a conference abstract without having to already know the difference. Every point comes from one of 20 components, all of them printed on the study itself, so you can disagree with our arithmetic rather than having to trust the total.

  • Journal tier up to 10 pts
  • Journal's citation record up to 4 pts
  • Study design up to 12 pts
  • Strength of evidence up to 5 pts
  • Peer-review validation up to 10 pts
  • How recent up to 5 pts
  • Sample size up to 4 pts
  • Effect reported up to 3 pts
  • Studied in people up to 3 pts
  • Randomised / blinded up to 2 pts
  • Times cited up to 7 pts
  • Citations per year up to 5 pts
  • Impact for its field and year up to 6 pts
  • Cited by studies here up to 6 pts
  • Still being cited up to 4 pts
  • Senior author's track record up to 4 pts
  • Institution's track record up to 3 pts
  • Multi-centre collaboration up to 3 pts
  • Indexed in PubMed up to 2 pts
  • Free to read up to 2 pts

Journals are placed in ordered tiers, never given a numeric impact factor — we could not verify current impact factors from a source we control, and an invented one would be worse than none. Tier 1 is the top-tier general journals (NEJM, The Lancet, JAMA, Nature, Science, Nature Medicine); tier 2 is the leading specialty journals; tier 3 is every other peer-reviewed journal. A separate part scores how much the journal's own papers are cited, which tells the tier-3 journals apart.

Two rules we don't bend. First, we never fill in a missing value: if a record does not state a sample size or a design, that component scores zero, and if we simply have no data for a part, such as a citation count, that part is left out and the study is scored on the parts we could check. The study card says which. Second, anything that is not a peer-reviewed article is capped at 16/100 and carries a warning chip — so a conference abstract or a company press release can never outrank a peer-reviewed paper, no matter how good it looks.

We rank a rigorous null result — a good trial showing that something does not work — above an early positive finding. Someone deciding whether to buy a supplement is served by that, and the rigour is already counted by the design and journal components.

The score is computed from the published data alone and is reproducible: the same file always yields the same numbers.

See the whole rubric drawn out → — four charts covering all 27,380 studies: how the scores are spread and where the cap bites, which of the 20 components the library is strong and weak on, which subjects rest on stronger evidence, and what kinds of study each subject is actually built from.

What this library is — and isn't

This is a large sample of the Alzheimer's literature, not an exhaustive index of it. It holds 27,380 records, built mostly from automated pulls of Europe PMC (60.6% of the library) and OpenAlex (18.6%), plus smaller pulls from PubMed, Crossref and medRxiv. If a study, a drug, or a finding isn't here, that is not evidence it doesn't exist in the literature — it may simply not have been pulled in yet.

1,032 records (3.8% of the library) are not peer-reviewed — 962 of those are preprints posted before any journal review, and the rest are conference abstracts, regulatory notices and reports. Every study card on this page states its status plainly, and the score above is capped for anything that isn't a peer-reviewed article.

See the full, machine-readable breakdown of this library's coverage →

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