Evidence map›Paper›PMID 39576984›Full record

ArticleJMIR human factors2024

Mobility-Based Smartphone Digital Phenotypes for Unobtrusively Capturing Everyday Cognition, Mood, and Community Life-Space in Older Adults: Feasibility, Acceptability, and Preliminary Validity Study.

Katherine Hackett, Shiyun Xu, Moira McKniff, Lido Paglia, Ian Barnett, Tania Giovannetti

Abstract read
In one paragraph

Article in JMIR human factors, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 2 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

21 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
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  7. Remote outcome measures in Alzheimer's disease clinical trials: A call to action.The journal of prevention of Alzheimer's disease · 2026
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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

6 authors.

Katherine HackettDepartment of Psychology and Neuroscience, Temple University, Philadelphia, PA, United States.ORCID 0000-0002-3595-1418
Shiyun XuDepartment of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA, United States.ORCID 0009-0006-7778-8571
Moira McKniffDepartment of Psychology and Neuroscience, Temple University, Philadelphia, PA, United States.ORCID 0000-0002-5780-4769
Lido PagliaInformation Technology, College of Science & Technology, Temple University, Philadelphia, PA, United States.ORCID 0009-0003-5034-3474
Ian BarnettDepartment of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA, United States.ORCID 0000-0003-3256-5703
Tania GiovannettiDepartment of Psychology and Neuroscience, Temple University, Philadelphia, PA, United States.ORCID 0000-0001-5661-152X

Funding

Research Training for the Care of Vulnerable Older Adults with Alzheimer’s Disease and Related Dementias and Other Chronic ConditionsT32AG066598 · NIA · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI Alex D Federman · 2020 to 2026
$2.3M
Assessing Everyday Function in Older Adults with the Virtual KitchenR01AG062503 · NIA · TEMPLE UNIV OF THE COMMONWEALTH · PI GIOVANNETTI, TANIA · 2020 to 2024
$1.8M
Statistical methods in mHealth to signal interventional needs for mental health patientsR01MH116884 · NIMH · UNIVERSITY OF PENNSYLVANIA · PI BARNETT, IAN JAMES · 2019 to 2022
$1.6M
Improving Everyday Task Performance through Repeated Practice in Virtual RealityR21AG066771 · NIA · TEMPLE UNIV OF THE COMMONWEALTH · PI GIOVANNETTI, TANIA · 2020 to 2021
$438k
Validation of Smartphone-Derived Digital Phenotypes for Cognitive Assessment in Older AdultsF31AG069444 · NIA · TEMPLE UNIV OF THE COMMONWEALTH · PI HACKETT, KATHERINE · 2020 to 2022
$66k
NIA NIH HHS F31 AG069444NIA NIH HHS R01 AG062503NIA NIH HHS R21 AG066771NIA NIH HHS T32 AG066598NIMH NIH HHS R01 MH116884
6 · The paper itself

Abstract

backgroundCurrent methods of monitoring cognition in older adults are insufficient to address the growing burden of Alzheimer disease and related dementias (AD/ADRD). New approaches that are sensitive, scalable, objective, and reflective of meaningful functional outcomes are direly needed. Mobility trajectories and geospatial life space patterns reflect many aspects of cognitive and functional integrity and may be useful proxies of age-related cognitive decline.

objectiveWe investigated the feasibility, acceptability, and preliminary validity of a 1-month smartphone digital phenotyping protocol to infer everyday cognition, function, and mood in older adults from passively obtained GPS data. We also sought to clarify intrinsic and extrinsic factors associated with mobility phenotypes for consideration in future studies.

methodsOverall, 37 adults aged between 63 and 85 years with healthy cognition (n=31, 84%), mild cognitive impairment (n=5, 13%), and mild dementia (n=1, 3%) used an open-source smartphone app (mindLAMP) to unobtrusively capture GPS trajectories for 4 weeks. GPS data were processed into interpretable features across categories of activity, inactivity, routine, and location diversity. Monthly average and day-to-day intraindividual variability (IIV) metrics were calculated for each feature to test a priori hypotheses from a neuropsychological framework. Validation measures collected at baseline were compared against monthly GPS features to examine construct validity. Feasibility and acceptability outcomes included retention, comprehension of study procedures, technical difficulties, and satisfaction ratings at debriefing.

resultsAll (37/37, 100%) participants completed the 4-week monitoring period without major technical adverse events, 100% (37/37) reported satisfaction with the explanation of study procedures, and 97% (36/37) reported no feelings of discomfort. Participants' scores on the comprehension of consent quiz were 97% on average and associated with education and race. Technical issues requiring troubleshooting were infrequent, though 41% (15/37) reported battery drain. Moderate to strong correlations (r≥0.3) were identified between GPS features and validators. Specifically, individuals with greater activity and more location diversity demonstrated better cognition, less functional impairment, less depression, more community participation, and more geospatial life space on objective and subjective validation measures. Contrary to predictions, greater IIV and less routine in mobility habits were also associated with positive outcomes. Many demographic and technology-related factors were not associated with GPS features; however, income, being a native English speaker, season of study participation, and occupational status were related to GPS features.

conclusionsTheoretically informed digital phenotypes of mobility are feasibly captured from older adults' personal smartphones and relate to clinically meaningful measures including cognitive test performance, reported functional decline, mood, and community activity. Future studies should consider the impact of intrinsic and extrinsic factors when interpreting mobility phenotypes. Overall, smartphone digital phenotyping is a promising method to unobtrusively capture relevant risk and resilience factors in the context of aging and AD/ADRD and should continue to be investigated in large, diverse samples.

Indexed as

AffectCognitionFeasibility StudiesSmartphoneActivities of Daily LivingAgedAged, 80 and overCognitive DysfunctionFemaleGeographic Information SystemsHumansMaleMiddle AgedMobile ApplicationsPhenotypeagingAlzheimer diseasecognitiondepressiondigital biomarkersdigital phenotypinglife spacelocation datamHealthmobile phonemobilitymonitoring

Identifiers

PMID39576984
PMCPMC11624463

What Socratic holds

Textmetadata
LicenceCC BY
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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 Socratic graph.