Evidence mapPaperPMID 38959029Full record

SynthesisJMIR mHealth and uHealth2024

mHealth Apps for Dementia, Alzheimer Disease, and Other Neurocognitive Disorders: Systematic Search and Environmental Scan.

Suad Ali, Hira Alizai, Delal Jemal Hagos, Sindy Ramos Rubio, Dale Calabia, Penelope Serrano Jimenez, Vinuu Aarif Senthil, Lora Appel

Abstract readSystematic Review
In one paragraph

Synthesis in JMIR mHealth and uHealth, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Review
  7. Technology for Young Adults with Stroke: An Australian Environmental Scan.International journal of environmental research and public health · 2024
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Suad AliFaculty of Health, York University, Toronto, ON, Canada.ORCID 0009-0003-1516-5852
Hira AlizaiFaculty of Health, York University, Toronto, ON, Canada.ORCID 0009-0009-4882-2912
Delal Jemal HagosFaculty of Health, York University, Toronto, ON, Canada.ORCID 0009-0000-9863-9918
Sindy Ramos RubioFaculty of Health, York University, Toronto, ON, Canada.ORCID 0009-0009-2918-2948
Dale CalabiaFaculty of Health, York University, Toronto, ON, Canada.ORCID 0009-0002-7259-0604
Penelope Serrano JimenezFaculty of Health, York University, Toronto, ON, Canada.ORCID 0009-0008-5992-6613
Vinuu Aarif SenthilFaculty of Health, York University, Toronto, ON, Canada.ORCID 0009-0001-7740-1027
Lora AppelFaculty of Health, York University, Toronto, ON, Canada.ORCID 0000-0002-7176-7191

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLifestyle behaviors including exercise, sleep, diet, stress, mental stimulation, and social interaction significantly impact the likelihood of developing dementia. Mobile health (mHealth) apps have been valuable tools in addressing these lifestyle behaviors for general health and well-being, and there is growing recognition of their potential use for brain health and dementia prevention. Effective apps must be evidence-based and safeguard user data, addressing gaps in the current state of dementia-related mHealth apps.

objectiveThis study aims to describe the scope of available apps for dementia prevention and risk factors, highlighting gaps and suggesting a path forward for future development.

methodsA systematic search of mobile app stores, peer-reviewed literature, dementia and Alzheimer association websites, and browser searches was conducted from October 19, 2022, to November 2, 2022. A total of 1044 mHealth apps were retrieved. After screening, 152 apps met the inclusion criteria and were coded by paired, independent reviewers using an extraction framework. The framework was adapted from the Silberg scale, other scoping reviews of mHealth apps for similar populations, and background research on modifiable dementia risk factors. Coded elements included evidence-based and expert credibility, app features, lifestyle elements of focus, and privacy and security.

resultsOf the 152 apps that met the final selection criteria, 88 (57.9%) addressed modifiable lifestyle behaviors associated with reducing dementia risk. However, many of these apps (59/152, 38.8%) only addressed one lifestyle behavior, with mental stimulation being the most frequently addressed. More than half (84/152, 55.2%) scored 2 points out of 9 on the Silberg scale, with a mean score of 2.4 (SD 1.0) points. Most of the 152 apps did not disclose essential information: 120 (78.9%) did not disclose expert consultation, 125 (82.2%) did not disclose evidence-based information, 146 (96.1%) did not disclose author credentials, and 134 (88.2%) did not disclose their information sources. In addition, 105 (69.2%) apps did not disclose adherence to data privacy and security practices.

conclusionsThere is an opportunity for mHealth apps to support individuals in engaging in behaviors linked to reducing dementia risk. While there is a market for these products, there is a lack of dementia-related apps focused on multiple lifestyle behaviors. Gaps in the rigor of app development regarding evidence base, credibility, and adherence to data privacy and security standards must be addressed. Following established and validated guidelines will be necessary for dementia-related apps to be effective and advance successfully.

Indexed as

Alzheimer DiseaseDementiaMobile ApplicationsHumansTelemedicineAlzheimer diseaseappsdementialifestyle behaviorsmHealthmobile healthmobile phone

Identifiers

PMID38959029
PMCPMC11255539

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 Socratic graph.