Evidence map›Paper›PMID 36178715›Full record

ArticleJMIR aging2022

Validation of a Remote and Fully Automated Story Recall Task to Assess for Early Cognitive Impairment in Older Adults: Longitudinal Case-Control Observational Study.

Caroline Skirrow, Marton Meszaros, Udeepa Meepegama, Raphael Lenain, Kathryn V Papp, Jack Weston, Emil Fristed

2 registry-linked trialsOpen access · goldAbstract read
In one paragraph

Article in JMIR aging, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 24 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed, 1 pooled it
4.9field-weighted citation impact, top 3% of its field
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.

NCT04828122 completednot on this map

A Study to Evaluate the Ability of Speech- and Language-based Digital Biomarkers to Detect and Characterise Prodromal and Preclinical Alzheimer's Disease in a Clinical Setting

Typeobservational_patient_registrySponsorNovoic LimitedRan2020 to 2021Enrolled141ConditionsAlzheimer Disease, Preclinical Alzheimer's Disease, Prodromal Alzheimer's Disease, Alzheimer's Disease (Incl Subtypes)
NCT04928976 completednot on this map

A Study to Evaluate the Ability of Speech- and Language-based Digital Biomarkers to Detect and Characterise Prodromal and Preclinical Alzheimer's Disease in a Clinical Setting

Typeobservational_patient_registrySponsorNovoic LimitedRan2021 to 2021Enrolled67ConditionsAlzheimer Disease, Preclinical Alzheimer's Disease, Prodromal Alzheimer's Disease, Alzheimer's Disease (Incl Subtypes)
3 · Its place in the literature

Who cites it

24 citing papers in PubMed, 1 synthesis or guideline pooled it, 34 citations in OpenAlex.

  1. Pooled it
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  10. Overview of Alzheimer's Disease Neuroimaging Initiative and future clinical trials.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025
    Review
  11. The ADNI Administrative Core: Ensuring ADNI's success and informing future AD clinical trials.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2024
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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

7 authors at 1 institution in 1 country.

Caroline SkirrowNovoic Ltd, London, United Kingdom.ORCID https://orcid.org/0000-0001-8692-7787
Marton MeszarosNovoic Ltd, London, United Kingdom.ORCID https://orcid.org/0000-0003-4937-3062
Udeepa MeepegamaNovoic Ltd, London, United Kingdom.ORCID https://orcid.org/0000-0001-8718-7530
Raphael LenainNovoic Ltd, London, United Kingdom.ORCID https://orcid.org/0000-0001-5345-0628
Kathryn V PappCenter for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States.ORCID https://orcid.org/0000-0003-1687-4370
Jack WestonNovoic Ltd, London, United Kingdom.ORCID https://orcid.org/0000-0001-5344-7840
Emil FristedNovoic Ltd, London, United Kingdom.ORCID https://orcid.org/0000-0002-9590-7275
Brigham and Women's Hospital · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundStory recall is a simple and sensitive cognitive test that is commonly used to measure changes in episodic memory function in early Alzheimer disease (AD). Recent advances in digital technology and natural language processing methods make this test a candidate for automated administration and scoring. Multiple parallel test stimuli are required for higher-frequency disease monitoring.

objectiveThis study aims to develop and validate a remote and fully automated story recall task, suitable for longitudinal assessment, in a population of older adults with and without mild cognitive impairment (MCI) or mild AD.

methodsThe "Amyloid Prediction in Early Stage Alzheimer's disease" (AMYPRED) studies recruited participants in the United Kingdom (AMYPRED-UK: NCT04828122) and the United States (AMYPRED-US: NCT04928976). Participants were asked to complete optional daily self-administered assessments remotely on their smart devices over 7 to 8 days. Assessments included immediate and delayed recall of 3 stories from the Automatic Story Recall Task (ASRT), a test with multiple parallel stimuli (18 short stories and 18 long stories) balanced for key linguistic and discourse metrics. Verbal responses were recorded and securely transferred from participants' personal devices and automatically transcribed and scored using text similarity metrics between the source text and retelling to derive a generalized match score. Group differences in adherence and task performance were examined using logistic and linear mixed models, respectively. Correlational analysis examined parallel-forms reliability of ASRTs and convergent validity with cognitive tests (Logical Memory Test and Preclinical Alzheimer's Cognitive Composite with semantic processing). Acceptability and usability data were obtained using a remotely administered questionnaire.

resultsOf the 200 participants recruited in the AMYPRED studies, 151 (75.5%)-78 cognitively unimpaired (CU) and 73 MCI or mild AD-engaged in optional remote assessments. Adherence to daily assessment was moderate and did not decline over time but was higher in CU participants (ASRTs were completed each day by 73/106, 68.9% participants with MCI or mild AD and 78/94, 83% CU participants). Participants reported favorable task usability: infrequent technical problems, easy use of the app, and a broad interest in the tasks. Task performance improved modestly across the week and was better for immediate recall. The generalized match scores were lower in participants with MCI or mild AD (Cohen d=1.54). Parallel-forms reliability of ASRT stories was moderate to strong for immediate recall (mean rho 0.73, range 0.56-0.88) and delayed recall (mean rho=0.73, range=0.54-0.86). The ASRTs showed moderate convergent validity with established cognitive tests.

conclusionsThe unsupervised, self-administered ASRT task is sensitive to cognitive impairments in MCI and mild AD. The task showed good usability, high parallel-forms reliability, and high convergent validity with established cognitive tests. Remote, low-cost, low-burden, and automatically scored speech assessments could support diagnostic screening, health care, and treatment monitoring.

Indexed as

acceptabilityagingAlzheimer diseasecognitioncognitive declinecognitive impairmentcognitive testdevelopmentelderepisodiclinguisticmemorymHealthmild cognitive impairmentmobile appsmobile healthmobile phoneneurologyobservational studyolder adultpsychometricsrecallreliabilitysemanticsmartphonespeechstoriesstoryusabilityvalidationvalidity

Identifiers

PMID36178715
PMCPMC9568813
OpenAlexW4298087975

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

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.