Evidence map›Paper›PMID 30619948›Full record

ArticleInnovation in aging2019

Mobile Technology for Cognitive Assessment of Older Adults: A Scoping Review.

Bon Mi Koo, Lisa M Vizer

Abstract readScoping Review
In one paragraph

Article in Innovation in aging, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 110 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
110citing papers in PubMed, 3 pooled it
–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

110 citing papers in PubMed, 3 syntheses or guidelines pooled it.

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50 more citing papers are in PubMed but not listed here.

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

2 authors.

Bon Mi KooSchool of Medicine, University of North Carolina at Chapel Hill.
Lisa M VizerSchool of Medicine, University of North Carolina at Chapel Hill.ORCID 0000-0002-4922-2275

Funding

Re-Entry Supplement: Investigation of Oral Microbial Enzymes for the Detection and Treatment of Periodontal DiseaseUL1TR002489 · NCATS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI BUSE, JOHN BERNARD, SHAHEEN, NICHOLAS J · 2018 to 2022
$48.6M
NCATS NIH HHS UL1 TR002489
6 · The paper itself

Abstract

BACKGROUND AND

objectivesThe number of people diagnosed with dementia is rising appreciably as the population ages. In an effort to improve outcomes, many have called for facilitating early detection of cognitive decline. Increased use of mobile technology by older adults provides the opportunity to deliver convenient, cost-effective assessments for earlier detection of cognitive impairment. This article presents a review of the literature on how mobile platforms-smartphones and tablets-are being used for cognitive assessment of older adults along with benefits and opportunities associated with using mobile platforms for cognitive assessment. RESEARCH DESIGN AND

methodsWe searched MEDLINE, Web of Science, PsycInfo, CINAHL, EMBASE, and Cochrane Central Register of Controlled Trials in October 2018. This search returned 7,024 articles. After removing 1,464 duplicates, we screened titles and abstracts then screened full-text for those articles meeting inclusion and exclusion criteria.

resultsTwenty-nine articles met our inclusion criteria and were categorized into 3 groups as follows: (a) mobile versions of existing article or computerized neuropsychological tests; (b) new cognitive tests developed specifically for mobile platforms; and (c) the use of new types of data for cognitive assessment. This scoping review confirms the considerable potential of mobile assessment. DISCUSSION AND IMPLICATIONS: Mobile technologies facilitate repeated and continuous assessment and support unobtrusive collection of auxiliary behavioral markers of cognitive impairment, thus allowing users to view trends and detect acute changes that have traditionally been difficult to identify. Opportunities include using new mobile sensors and wearable devices, improving reliability and validity of mobile assessments, determining appropriate clinical use of mobile assessment information, and incorporating person-centered assessment principles and digital phenotyping.

Indexed as

Alzheimer’s diseaseCognitionDementiaInformation technologyMemorymHealthPsychometrics

Identifiers

PMID30619948
PMCPMC6312550

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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 OpenQuestion graph.