Evidence map›Paper›PMID 41252538›Full record

ArticleJMIR aging2025

Digital Measurement of Subjective Experiences in Alzheimer Disease and Related Dementias (AD/ADRD).

Colin Depp, Jason Holden, Eric Granholm

Abstract read
In one paragraph

Article in JMIR aging, 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

3 authors.

Colin DeppDepartment of Psychiatry, University of California, San Diego, 9500 Gilman Drive, MC 0737, La Jolla, CA, 92093, United States, 1 8585342542.ORCID http://orcid.org/0000-0002-1841-6229
Jason HoldenDepartment of Psychiatry, University of California, San Diego, 9500 Gilman Drive, MC 0737, La Jolla, CA, 92093, United States, 1 8585342542.ORCID http://orcid.org/0000-0001-6468-5510
Eric GranholmDepartment of Psychiatry, University of California, San Diego, 9500 Gilman Drive, MC 0737, La Jolla, CA, 92093, United States, 1 8585342542.ORCID http://orcid.org/0000-0003-2040-7951

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Unlabelled: Symptoms such as loss of pleasure, agitation, and sadness are subjective experiences that contribute significantly to caregiver burden and health care costs in Alzheimer disease and related dementias (AD/ADRD). However, traditional self-report measures of subjective experiences are limited in AD/ADRD due to cognitive impairments and awareness. Passive sensing, which collects data without active participant input, has emerged as a promising approach to quantify aspects of subjective experiences. Smartphones, wearables, and in-home sensors can quantify mobility, physiology, speech, and social interaction markers of constructs relevant to AD/ADRD. Available research indicates potential but is largely at the proof-of-concept stage. In this Commentary, we discuss several roadblocks to future translation of passive sensing in measuring subjective experiences in AD/ADRD, including technical implementation, data harmonization, validation, ethical and privacy principles. Addressing these challenges could lead to transformative applications to care for AD/ADRD, enabling precise monitoring of behavioral symptoms and related treatment targets, ultimately improving quality of life for persons with AD/ADRD and their caregivers.

Indexed as

Alzheimer DiseaseDementiaCaregiversHumansQuality of LifeWearable Electronic DevicesAlzheimer's diseasemeasurementmobile assessmentpassive sensingsubjective experience

Identifiers

PMID41252538
PMCPMC12626243

What OpenQuestion holds

Textmetadata
LicenceCC BY
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 OpenQuestion graph.