SynthesisFrontiers in aging neuroscience2023
An update on mobile applications collecting data among subjects with or at risk of Alzheimer's disease.
Synthesis in Frontiers in aging neuroscience, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it, 10 citations in OpenAlex.
- Evaluation of fatty liver disease self-care applications: a systematic review and evaluation of apps using the mobile application rating scale (MARS).BMC gastroenterology · 2026Pooled it
- Artificial Intelligence and Digital Biomarkers for Early Detection and Monitoring of Neurological Disorders: A Narrative Review.Diagnostics (Basel, Switzerland) · 2026Review
- Recent Advances in AI-Driven Mobile Health Enhancing Healthcare-Narrative Insights into Latest Progress.Bioengineering (Basel, Switzerland) · 2025Review
- Clinical definition, biological characterization, and detection guidelines of subjective cognitive decline due to Alzheimer's disease and related dementia: A position paper from ISTAART SCD PIA.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025Article
- Unresolved ethical questions of mHealth apps for Alzheimer's disease prevention.Medicine, health care, and philosophy · 2025Article
- Terrapino: a mobile application for Alzheimer's risk assessment and cognitive health promotion.Frontiers in digital health · 2025Article
- Machine Learning and Digital Biomarkers Can Detect Early Stages of Neurodegenerative Diseases.Sensors (Basel, Switzerland) · 2024Review
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Smart mobile phone use is increasing worldwide, as is the ability of mobile devices to monitor daily routines, behaviors, and even cognitive changes. There is a growing opportunity for users to share the data collected with their medical providers which may serve as an accessible cognitive impairment screening tool. Data logged or tracked in an app and analyzed with machine learning (ML) could identify subtle cognitive changes and lead to more timely diagnoses on an individual and population level. This review comments on existing evidence of mobile device applications designed to passively and/or actively collect data on cognition relevant for early detection and diagnosis of Alzheimer's disease (AD). The PubMed database was searched to identify existing literature on apps related to dementia and cognitive health data collection. The initial search deadline was December 1, 2022. Additional literature published in 2023 was accounted for with a follow-up search prior to publication. Criteria for inclusion was limited to articles in English which referenced data collection via mobile app from adults 50+ concerned, at risk of, or diagnosed with AD dementia. We identified relevant literature (
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.