Evidence map›Paper›PMID 40190252›Full record

ArticleInternational journal of methods in psychiatric research2025

Psychometric Properties of MyCog 2.0: A Human-Centered Cognitive Screening Tool for Older Adults.

Stephanie Ruth Young, Yusuke Shono, Katherina K Hauner, Jiwon Kim, Elizabeth McManus Dworak, Greg Joseph Byrne, Callie Madison Jones, Julia Noelani Yoshino Benavente, Michael S Wolf, Cindy J Nowinski

Abstract read
In one paragraph

Article in International journal of methods in psychiatric research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

10 authors.

Stephanie Ruth YoungDepartment of Medical Social Sciences, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA.
Yusuke ShonoDepartment of Medical Social Sciences, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA.
Katherina K HaunerDepartment of Medical Social Sciences, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA.ORCID 0009-0008-5648-4979
Jiwon KimDepartment of Medical Social Sciences, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA.
Elizabeth McManus DworakDepartment of Medical Social Sciences, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA.
Greg Joseph ByrneDepartment of Medical Social Sciences, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA.
Callie Madison JonesDepartment of Medical Social Sciences, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA.
Julia Noelani Yoshino BenaventeCenter for Applied Health Research on Aging, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA.
Michael S WolfCenter for Applied Health Research on Aging, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA.
Cindy J NowinskiDepartment of Medical Social Sciences, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA.

Funding

Primary Care Detection of Cognitive Impairment Leveraging Health and Consumer Technologies in Underserved Communities: The MyCog TrialU01NS105562 · NINDS · NORTHWESTERN UNIVERSITY AT CHICAGO · PI MICHAEL S WOLF, Julia Yoshino Benavente · 2022 to 2026
$6.8M
ToolBox Detect: Low Cost Detection of Cognitive Decline in Primary Care SettingsR01AG069762 · NIA · NORTHWESTERN UNIVERSITY AT CHICAGO · PI GERSHON, RICHARD, NOWINSKI, CINDY J. · 2020 to 2025
$6.4M
Development and Validation of a Telehealth Strategy for Routine Detection of Cognitive Impairment in Primary Care: The MyCog Mobile AssessmentR01AG074245 · NIA · NORTHWESTERN UNIVERSITY AT CHICAGO · PI NOWINSKI, CINDY J., WOLF, MICHAEL S · 2021 to 2025
$3.8M
NIA NIH HHS R01 AG069762NIA NIH HHS R01 AG074245NIH HHS 1R01AG074245-01NINDS NIH HHS U01 NS105562
6 · The paper itself

Abstract

objectivesSelf-administered, user-friendly apps that can detect initial symptoms of cognitive impairment have enormous potential to improve early detection of cognitive decline. We examine the psychometric properties of the redesigned version of MyCog, MyCog 2.0, an app-based tool for older adults that assesses executive function and episodic memory. MyCog 2.0 aims to improve usability while maintaining the psychometric validity demonstrated in the original version.

methodsFeedback from clinicians and patients on MyCog was gathered to inform the human-centered design improvements of MyCog 2.0. To assess the psychometric properties of the improved tool, data from a community sample (n = 200; mean age = 73 years) who had completed MyCog 2.0 were compared to an age-matched sample who had completed the original MyCog. Internal consistency and construct validity were evaluated via confirmatory factor analysis. Bayesian differential item functioning was employed to evaluate the evidence for equivalence of MyCog and MyCog 2.0.

resultsInternal consistency was high for executive function and episodic memory tests (ω

conclusionsFindings support MyCog 2.0 as the first reliable self-administered cognitive screener designed specifically for ease of use among older adults. Findings support the internal consistency and construct validity of MyCog 2.0 and provide a foundation for the forthcoming clinical validation studies.

Indexed as

Cognitive DysfunctionExecutive FunctionMemory, EpisodicMobile ApplicationsNeuropsychological TestsPsychometricsAgedAged, 80 and overFemaleHumansMaleMiddle AgedReproducibility of Resultscognitive screenerepisodic memoryexecutive functionMyCog 2.0neuropsychological assessmentolder adultsvalidation

Identifiers

PMID40190252
PMCPMC11973452

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Registered trials

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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.