ArticleJMIR human factors2025
Understanding the Thoughts and Preferences for Technologies Designed to Detect Feelings of Loneliness: Interview Study Among Older Adults.
Article in JMIR human factors, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.
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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.
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Who cites it
1 citing paper in PubMed, 1 synthesis or guideline pooled it.
- Sensor-Based Technologies for the Detection of Unwanted Loneliness in Older Adults: A Systematic Review.Sensors (Basel, Switzerland) · 2026Pooled it
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Loneliness is a negative emotional state that is common in later life. The accumulative effects of loneliness have a significant impact on the physical and mental health of older adults. Automatic methods for detection and prediction are an emerging field to support early identification of loneliness. Objective: This study aimed to qualitatively explore the thoughts and preferences of people aged 65 years and older regarding technologies to detect feelings of loneliness in later life. Methods: We conducted 60 semistructured interviews with people aged 65 years and older between September 2022 and August 2023. Data were analyzed using a reflective thematic approach on NVivo software (Lumivero). Results: In total, three themes were identified representing what older adults considered important in a system able to detect loneliness: (1) interest and control of data, which was a priority for older adults; (2) perceived usefulness to address loneliness, which related to the importance of providing recommendations to reduce feelings of loneliness after detection; and (3) personalization as a priority, which included the level of loneliness for which an alert was sent and selection of relevant individuals who would be sent a loneliness alert. Conclusions: Findings from this in-depth qualitative study provide important perspectives from people with lived experience of loneliness on the context in which a sensor-based loneliness detection system would be most useful and acceptable to older adults. Future research will include such perspectives in the design of innovative technologies enabling the early detection of loneliness and access to timely interventions to tackle loneliness in later life.
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