Evidence map›Paper›PMID 40575107›Full record

ArticleFrontiers in public health2025

Measures of healthcare decision-making ability in cognitive aging: a scoping review from the Advancing Reliable Measurement in Cognitive Aging and Decision-Making Ability (ARMCADA) research initiative.

Molly A Mather, Berivan Ece, Tatiana Karpouzian-Rogers, Emily H Ho, Patricia Bucko, Elizabeth M Dworak, Miriam A Novack, Sarah Pila, Zahra Hosseinian, Janel Hanmer and 2 more

Abstract readScoping Review
In one paragraph

Article in Frontiers in public health, 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

12 authors.

Molly A MatherMesulam Center for Cognitive Neurology and Alzheimer's Disease, Northwestern University Feinberg School of Medicine, Chicago, IL, United States.
Berivan EceDepartment of Medical Social Sciences, Northwestern University Feinberg School of Medicine, Chicago, IL, United States.
Tatiana Karpouzian-RogersDepartment of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of Medicine, Chicago, IL, United States.
Emily H HoDepartment of Medical Social Sciences, Northwestern University Feinberg School of Medicine, Chicago, IL, United States.
Patricia BuckoDepartment of Medical Social Sciences, Northwestern University Feinberg School of Medicine, Chicago, IL, United States.
Elizabeth M DworakDepartment of Medical Social Sciences, Northwestern University Feinberg School of Medicine, Chicago, IL, United States.
Miriam A NovackDepartment of Medical Social Sciences, Northwestern University Feinberg School of Medicine, Chicago, IL, United States.
Sarah PilaDepartment of Medical Social Sciences, Northwestern University Feinberg School of Medicine, Chicago, IL, United States.
Zahra HosseinianDepartment of Medical Social Sciences, Northwestern University Feinberg School of Medicine, Chicago, IL, United States.
Janel HanmerDepartment of Medicine, University of Pittsburgh, Pittsburgh, PA, United States.
Richard C GershonDepartment of Medical Social Sciences, Northwestern University Feinberg School of Medicine, Chicago, IL, United States.
Sandra WeintraubMesulam Center for Cognitive Neurology and Alzheimer's Disease, Northwestern University Feinberg School of Medicine, Chicago, IL, United States.

Funding

ARMCADA - Advancing Reliable Measurement in Cognitive Aging and Decision-making AbilityU24AG082022 · NIA · NORTHWESTERN UNIVERSITY AT CHICAGO · PI RICHARD GERSHON, SANDRA WEINTRAUB · 2023 to 2026
$7.9M
NIA NIH HHS U24 AG082022
6 · The paper itself

Abstract

Introduction: Declines in decision-making (DM) ability are often observed with increasing age and pose significant risk for negative health, financial, and functional outcomes. The Advancing Reliable Measurement in Cognitive Aging and Decision-making Ability (ARMCADA) research initiative aims to improve measurement of DM ability in aging to facilitate early detection of cognitive and functional decline. This scoping review summarizes the extant literature on DM measures in aging, focusing specifically on measures relevant to healthcare decision-making (HCDM). Methods: We identified articles published between 2018 and 2023 using keywords related to DM abilities in aging populations. Titles and abstracts were first reviewed by two trained reviewers, followed by full-text review and extraction. Results of the current scoping review are reported in adherence to PRISMA-ScR guidelines. Results: The scoping review identified 16,286 articles across multiple domains of decision-making, 705 of which met criteria for extraction, and 246 of which were related to healthcare decision-making. There were 86 unique measures across these articles, and 18 of these measures directly targeted decision-making ability. Most measures were administered to clinical groups in English and in-person with a trained examiner. Measures of healthcare DM ability tended to consist of semi-structured interviews or performance-based items, though there were also several self-report measures. Discussion: The most commonly used measures to assess HCDM ability require trained administration of a semi-structured interview to assess ability to reason about health-related scenarios and are often time-intensive. Creation of a streamlined, standardized measure to assess HCDM ability will benefit both research and clinical care for the aging population.

Indexed as

Cognitive AgingDecision MakingAgedHumanscapacity assessment instrumentsdecision-making assessmentdecision-making capacityhealthcare decisionhealth outcomespatient decision-making

Identifiers

PMID40575107
PMCPMC12198135

What OpenQuestion holds

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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.