OLDER ADULTS’ VIEWS OF SMARTPHONE-BASED MONITORING FOR DEMENTIA RISK - Issue 2 - Acceptability Findings

Sep 29, 2026

Clinical assessment in dementia-risk evaluations is difficult and may be improved through passive smartphone monitoring that continuously tracks everyday behaviors outside the clinic. Acceptability in older adults is essential for these technologies to be useful. Interviews with 17 cognitively normal older adults explored attitudes using a Technology Acceptance Model approach. Analysis identified themes around perceived utility, privacy and ethics, personal characteristics, logistics, and comfort, with privacy concerns as key barriers.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages1

Reading Time3 min

AccessFree to download

Background

Challenges in dementia risk assessment

Role of passive smartphone monitoring

Methods

Participants and interviews

Analytic approach

Findings

Perceived utility and comfort

Privacy, ethics, and barriers

Factors supporting acceptability

Implications

Recommendations for clinical implementation

Innovation in Aging, 2025, Vol. 9, No. S2 1299 acceptability rating (likelihood of future study participation) . Our interview guide drew from the Technology Acceptance Model and preliminary passive smartphone studies to explore a priori themes. Transcripts were analyzed using a hybrid inductive-deductive approach and content analysis. Emergent themes included perceived utility, privacy/ethical concerns, personal characteristics, logistical considerations, and overall comfort level. Key barriers to acceptability included privacy concerns (e.g., unease with monitoring, risk of data breach) which varied by data type (GPS versus call/text meta-data) . Some participants questioned the clinical utility and identified potential confounding variables. Factors contributing to acceptability included recognized scope (i.e., perceived value in tracking behaviors not routinely assessed in clinic), altruistic attitudes toward research, clear understanding of privacy protections, and interest in early detection of dementia. Post-interview, 76% were likely to participate in a future digital monitoring study and 94% agreed to recruitment contact. These findings offer insights to enhance acceptability in future clinical implementation, including transparent review of privacy safeguards, existing evidence, and clinical integration logistics. Abstract citation ID: igaf122.4329 OLDER ADULTS’ VIEWS OF SMARTPHONE-BASED MONITORING FOR DEMENTIA RISK Katherine Hackett1, Heather Wurtz2, Frandys Berroa1, Hillary Ramos Espinoza1, Maria Loizos1, Carolyn Zhu1, Alex Federman1, and Mary Sano1, 1. Icahn School of Medicine at Mount Sinai, New York, New York, United States, 2. University of Southern California, Los Angeles, California, United States Clinical assessment of function in dementia risk evaluationsis challenging and may benefit from passive smartphone monitoring, which enables low-burden, continuous tracking of everyday behaviors outside the clinic. However, acceptability of passive monitoring in older adults is required for such technologies to be useful. To assess acceptability, 17 cognitively normal older adults (mean age=76.9, SD = 8.7; mean education=15.8, SD = 3.4; 59% White, 41% Hispanic) from the Mount Sinai Alzheimer’s Disease Research Center completed a 1-hour semi-structured interview in English or Spanish assessing attitudes toward smartphone monitoring, followed by a 5-point

FAQs

Why is passive smartphone monitoring considered for dementia-risk evaluations?

It supports low-burden, continuous tracking of everyday behaviors outside the clinic, which may complement challenging clinical assessment of function in dementia risk evaluations.

What themes shaped participants’ acceptability of smartphone-based monitoring?

Emergent themes included perceived utility, privacy and ethical concerns, personal characteristics, logistical considerations, and overall comfort level.

What were the main barriers to acceptability, and how did they relate to data type?

Privacy concerns were the key barriers, such as unease about monitoring and risk of data breach, and they varied by data type, including GPS versus call/text meta-data.

Sep 29, 2026

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