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Find studies

Showing 1–25 of 37 studies in Digital health tools published 2014 (page 1 of 2) · 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 “Digital health tools” covers

Digital health tools — Apps, wearables, online tests and other technology used to detect, monitor or support people with dementia.

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.

Preventable hospital readmissions have been recognized as indicators of hospital quality, a source of increased healthcare expenditures, and a burden for patients, families, and caregivers. 2 key findings →

Design: cohort study Participants: 5,133 Evidence: moderate

Association of hearing impairment with brain volume changes in older adults

✓ Peer-reviewed alzhub usefulness score 64 out of 100. NeuroImage 2014-01-09

Hearing impairment in older adults is independently associated in longitudinal studies with accelerated cognitive decline and incident dementia, and in cross-sectional studies, with reduced volumes in the auditory cortex. 5 key findings →

Design: cross-sectional Participants: 126 Evidence: moderate

Digital literacy may help reduce cognitive decline among persons aged between 50 and 89 years. 2 key findings →

Design: longitudinal study Participants: 6,442 Evidence: moderate

Combining multi-modality brain data for disease diagnosis commonly leads to improved performance. 1 key finding →

Evidence: low

Multimorbidity and long-term care dependency--a five-year follow-up

✓ Peer-reviewed alzhub usefulness score 60 out of 100. BMC geriatrics 2014-05-28

The results should form the basis for future health policy decisions on the treatment of patients with multiple chronic diseases and also show the need to introduce new ways of providing long-term care to this population. 3 key findings →

Participants: 115,203 Evidence: moderate

Sensor-derived physical activity parameters can predict future falls in people with dementia

✓ Peer-reviewed alzhub usefulness score 59 out of 100. Gerontology 2014-08-28

Surprisingly, fallers and non-fallers did not differ on any conventional assessment (p = 0.069-0.991), except for 'previous faller' (p = 0.006). 5 key findings →

Design: cohort study Participants: 77 Evidence: moderate

The trial was performed in 109 healthy subjects and 123 SDAT patients of whom 97 healthy subjects and 104 SDAT patients completed the study. 2 key findings →

Evidence: high

Taking more anticholinergic medications is associated with greater risk of hospitalization for confusion or dementia. 3 key findings →

Design: cohort study Evidence: moderate

Claims data studies that include indicators of potentially diminished patient functional status better capture heterogeneity of patients with multiple chronic conditions. 1 key finding →

Participants: 72,056 Evidence: moderate

Multiple instance learning for classification of dementia in brain MRI

✓ Peer-reviewed alzhub usefulness score 51 out of 100. Medical image analysis 2014-05-05

Machine learning techniques have been widely used to detect morphological abnormalities from structural brain magnetic resonance imaging data and to support the diagnosis of neurological diseases such as dementia. 2 key findings →

Participants: 834 Evidence: low

Cognitive impairment is highly prevalent among individuals with late-life depression (LLD) and tends to persist even after successful treatment. 5 key findings →

Evidence: low

Sensitivity and False Alarm Rate of a Fall Sensor in Long-Term Fall Detection in the Elderly

✓ Peer-reviewed alzhub usefulness score 50 out of 100. Gerontology 2014-08-13

The fall detection system detected 12 out of 15 real-life falls, having a sensitivity of 80.0%, with a false alarm rate of 0.049 alarms per usage hour with the implemented real-time system. 3 key findings →

Participants: 15,500 Evidence: low

This study provides pathological validation that the new criteria assist with separating PPA cases with AD pathology into the new lv-PPA syndrome and found that a number of diagnostic clinical features (disinhibition, food preferences and naming) did not assist in discriminating the different FTD syndromes. 2 key findings →

Evidence: low

Differentiation of logopenic (lvPPA) and nonfluent/agrammatic (nfvPPA) variants of Primary Progressive Aphasia is important yet remains challenging since it hinges on expert based evaluation of speech and language production. 3 key findings →

Evidence: low

Predictors of long-term mortality after severe sepsis in the elderly

✓ Peer-reviewed alzhub usefulness score 47 out of 100. The American journal of the medical sciences 2014-04-01

The authors identified several factors, including receipt of mechanical ventilation, which were significantly associated with increased long-term mortality for survivors of severe sepsis. 5 key findings →

Participants: 2,727 Evidence: low

The CPCSSN diagnostic algorithms showed excellent sensitivity and specificity for hypertension, diabetes, epilepsy, and parkinsonism and acceptable values for the other conditions. 1 key finding →

Design: cross-sectional Evidence: low

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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 →

Newest studies, as a dated timeline →    Atom feed