Evidence map›Paper›PMID 40424138›Full record

ArticleNeuropsychology2025

Updating the self-appraisal of one's cognitive performance with 7 days of repeated exposure: From test-naïve to experienced.

Daniel Soberanes, Mark A Dubbelman, Roos J Jutten, Cassidy P Molinare, Stephanie Hsieh, Hairin Kim, Geoffroy Gagliardi, Patrizia Vannini, Gad A Marshall, Kathryn V Papp and 1 more

Abstract read
In one paragraph

Article in Neuropsychology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

11 authors.

Daniel SoberanesCenter for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School.
Mark A DubbelmanCenter for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School.ORCID 0000-0002-5708-4925
Roos J JuttenDepartment of Neurology, Massachusetts General Hospital, Harvard Medical School.
Cassidy P MolinareCenter for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School.
Stephanie HsiehCenter for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School.
Hairin KimCenter for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School.
Geoffroy GagliardiCenter for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School.
Patrizia VanniniCenter for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School.
Gad A MarshallCenter for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School.
Kathryn V PappCenter for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School.
Rebecca E AmariglioCenter for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School.

Funding

Vascular factors, physical activity, and inflammation as modulators of neurodegenerative and cognitive trajectories (Project 2)P01AG036694 · NIA · MASSACHUSETTS GENERAL HOSPITAL · PI Hyun-Sik Yang · 2010 to 2026
$50.2M
Novel automated performance-based ADL outcomes for early AD clinical trialsR01AG053184 · NIA · BRIGHAM AND WOMEN'S HOSPITAL · PI MARSHALL, GAD ASHER · 2018 to 2023
$4.5M
Characterizing the evolution of Subjective Cognitive Decline in preclinical Alzheimer's diseaseR01AG058825 · NIA · BRIGHAM AND WOMEN'S HOSPITAL · PI AMARIGLIO, REBECCA E · 2019 to 2024
$4.0M
Neural Correlates of Apathy Across the Alzheimer's Disease ContinuumR01AG067021 · NIA · MASSACHUSETTS GENERAL HOSPITAL · PI MARSHALL, GAD ASHER · 2020 to 2025
$3.6M
Ahead of the Curve: Early detection and monitoring of learning decrements in Alzheimers diseaseR01AG084017 · NIA · BRIGHAM AND WOMEN'S HOSPITAL · PI Kathryn Victoria Papp · 2024 to 2026
$2.5M
NIA NIH HHS P01 AG036694NIA NIH HHS R01 AG053184NIA NIH HHS R01 AG058825NIA NIH HHS R01 AG067021NIA NIH HHS R01 AG084017NIH HHS
6 · The paper itself

Abstract

objectiveSelf-appraisal of cognitive performance, a potentially useful marker of brain functioning, is typically assessed at a single time point where tests are naïve to what constitutes "good" or "bad" performance. Here, we determine whether familiarizing individuals with self-appraisal with daily memory testing for 7 days provide a more accurate estimate of cognitive functioning and mood.

methodTwo hundred twenty-five participants (

resultsAccuracy (Day 1: 0.44 ± 0.12; Day 7: 0.81 ± 0.16) and self-appraisal (Day 1: 0.36 ± 0.15; Day 7: 0.70 ± 0.21) increased, as did the association between accuracy and self-appraisal, Day 1: correlation coefficient (

conclusionsRepeated remote cognitive assessments may help elucidate individuals' capacities to refine their self-perception of cognitive performance during multiday learning. The weak association between accuracy and test-naïve self-appraisal warrants caution about using this metric cross-sectionally. Experienced self-appraisal could be especially relevant at the early stages of neurodegenerative diseases when subtle learning difficulties emerge and could improve our capacity to detect early meta-cognitive changes. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

Indexed as

AffectCognitionSelf-AssessmentAgedAged, 80 and overFemaleHumansMaleMiddle AgedNeuropsychological TestsTime Factors

Identifiers

PMID40424138
PMCPMC12339199

What OpenQuestion holds

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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.