Evidence map›Paper›PMID 41605500›Full record

ArticleJournal of medical Internet research2026

Development and User-Centered Evaluation of Smart Systems for Loneliness Monitoring in Older Adults: Mixed Methods Study.

Yi Zhou, Jessica Rees, Faith Matcham, Ashay Patel, Michela Antonelli, Anthea Tinker, Sebastien Ourselin, Wei Liu

Abstract read
In one paragraph

Article in Journal of medical Internet research, 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.

Yi ZhouDepartment of Engineering, King's College London, London, United Kingdom.ORCID https://orcid.org/0000-0002-4176-5793
Jessica ReesDepartment of Global Health and Social Medicine, King's College London, London, United Kingdom.ORCID https://orcid.org/0000-0002-9471-2134
Faith MatchamSchool of Psychology, Faculty of Science, Engineering and Medicine, University of Sussex, Brighton, United Kingdom.ORCID https://orcid.org/0000-0002-4055-904X
Ashay PatelSchool of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom.ORCID https://orcid.org/0000-0003-4212-2578
Michela AntonelliSchool of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom.ORCID https://orcid.org/0000-0002-3005-4523
Anthea TinkerDepartment of Global Health and Social Medicine, King's College London, London, United Kingdom.ORCID https://orcid.org/0000-0002-0305-7198
Sebastien OurselinSchool of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom.ORCID https://orcid.org/0000-0002-5694-5340
Wei LiuDepartment of Engineering, King's College London, London, United Kingdom.ORCID https://orcid.org/0000-0002-8014-7218

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLoneliness is a critical issue among older adults and constitutes a significant risk factor for a range of physical and mental health conditions. However, current assessment methods primarily rely on self-report questionnaires and clinical evaluations, which are susceptible to recall bias and social desirability bias, highlighting the need for more objective and continuous assessment approaches. Recent studies have reported associations between physiological and behavioral indicators and the experience of loneliness in older adults. While these technologies have demonstrated correlations between physiological and behavioral sensor data and the experience of loneliness, their implementation has been limited. Most systems rely on fixed-location sensors or smartphone apps, with little attention given to the integration of these tools into users' daily routines. To date, no published studies have applied smart textile technology, which integrates sensing capabilities directly into garments or furniture, as a medium for loneliness detection. This study addresses that gap by exploring the usability, experiential acceptability, and ethical considerations of smart textile-based monitoring systems.

objectiveThis study aims to assess the perceived usability, acceptability, and emotional resonance of a smart loneliness monitoring system integrating sensing garments, furniture, and a mobile app and identify design implications to guide future improvement and promote sustained engagement among older adults.

methodsBuilding on earlier conceptual research, a functional prototype system was developed and evaluated through 2 immersive in-person workshops with older adults (N=10). A mixed methods approach was applied, combining structured questionnaires, sensory ethnographic observations, focus group discussions, and experience-based co-design. Quantitative data were analyzed descriptively, and qualitative data were analyzed thematically to explore user perceptions related to system usability, emotional response, lifestyle compatibility, and ethical considerations.

resultsQuantitative data indicated high user satisfaction in dimensions such as comfort, ease of use, and feedback clarity. However, trust in long-term monitoring and willingness to use the system regularly varied. Thematic analysis revealed 4 main areas influencing acceptance, including wearability, usability, and daily integration; trust, privacy, and data control; perceptions of loneliness and the limits of detection; and adoption, applicability, and ethical futures. Participants emphasized the need for discretion, personalization, and human oversight in system feedback and data-sharing mechanisms.

conclusionsThe resulting prototype was positively received, demonstrating the potential of smart systems for passive and personalized loneliness monitoring among older adults. However, adoption is influenced by perceptions of autonomy, emotional sensitivity, and contextual integration. Future development should focus on modularity, transparency, and integration within care infrastructures to ensure ethical and sustainable deployment.

Indexed as

LonelinessMobile ApplicationsAgedAged, 80 and overFemaleHumansIntelligent SystemsMaleSmartphonelonelinessmental healthmonitoringolder adultssmart textileuser-centered designwearable and ambient technologywearable technology

Identifiers

PMID41605500
PMCPMC12895156

What Socratic holds

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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.