Evidence map›Paper›PMID 42158458›Full record

ArticleInnovation in aging2026

Older adults' views of passive smartphone monitoring for dementia risk: a multi-method analysis.

Katherine Hackett, Heather Wurtz, Carolyn W Zhu, Maria Loizos, Frandys Berroa, Hillary Ramos Espinoza, Alex Federman, Mary Sano

Abstract read
In one paragraph

Article in Innovation in aging, 2026. 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

8 authors.

Katherine HackettDivision of General Internal Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, United States.
Heather WurtzDepartment of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, California, United States.
Carolyn W ZhuBrookdale Department of Geriatrics and Palliative Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, United States.
Maria LoizosAlzheimer's Disease Research Center, Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York, United States.
Frandys BerroaDivision of General Internal Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, United States.
Hillary Ramos EspinozaDivision of General Internal Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, United States.
Alex FedermanDivision of General Internal Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, United States.
Mary SanoAlzheimer's Disease Research Center, Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York, United States.

Funding

Research Education ComponentP30AG066514 · NIA · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI Margaret Sewell · 2020 to 2026
$31.0M
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
NIA NIH HHS P30 AG066514NIA NIH HHS T32 AG066598
6 · The paper itself

Abstract

Background and Objectives: Functional difficulties are hallmark signs of incident cognitive decline and progression to dementia but are challenging to measure in clinics. Passive smartphone monitoring enables continuous tracking of everyday behaviors and may improve the status quo of dementia risk assessment, but acceptability is understudied. This study evaluated older adults' attitudes toward personal smartphone monitoring for dementia risk and identified barriers and facilitators to acceptability. Methods: Seventeen older adults completed a semi-structured interview followed by a Likert-scale rating to measure acceptability. Transcripts were analyzed using hybrid inductive-deductive thematic analysis. Exploratory correlations examined associations between acceptability ratings and participant features. Results: Participants identified unique benefits of smartphone monitoring, including enhanced scope of measurement, greater ecological validity and personalization, and improved accessibility. Potential disadvantages were confounding variables that threaten validity and concerns about privacy/data security. Preferences for clinical implementation that may improve acceptability included extended monitoring options, assurances of privacy safeguards, control over data, and continued face-to-face interactions with one's medical team. Most participants (13/17) were likely or extremely likely to participate in future smartphone monitoring research; higher likelihood was associated with lower depression ( Discussion and Implications: Findings offer insights to enhance the acceptability of smartphone monitoring, including transparent review of procedures, privacy safeguards, and existing evidence. Outstanding requirements for clinical implementation include streamlining results to minimize physician burden and accounting for confounders that threaten data integrity. Our small, research-savvy cohort necessitates follow-up in other settings.

Indexed as

AcceptabilityAlzheimer’s diseaseDigital assessmentNeuropsychologyTechnology

Identifiers

PMID42158458
PMCPMC13180638

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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.