Understanding the Thoughts and Preferences of Older Adults for Technologies Designed to Detect Feelings of Loneliness: A Qualitative Study (Preprint)
Open Access
- 10 March 2025
- journal article
- Published by JMIR Publications Inc. in JMIR Human Factors
- Vol. 12, e73694
Abstract
Journal of Medical Internet Research - International Scientific Journal for Medical Research, Information and Communication on the Internet #Preprint #PeerReviewMe: Warning: This is a unreviewed preprint. Readers are warned that the document has not been peer-reviewed by expert/patient reviewers or an academic editor, may contain misleading claims, and is likely to undergo changes before final publication, if accepted, or may have been rejected/withdrawn. Readers with interest and expertise are encouraged to sign up as peer-reviewer, if the paper is within an open peer-review period. Please cite this preprint only for review purposes or for grant applications and CVs (if you are the author). Background: Loneliness is a negative emotional state which is common in later life. The accumulative effects of loneliness have significant impact on physical and mental health of older adults. Automatic methods for detection and prediction are an emerging field to support early identification of loneliness. Objectives: We aim to qualitatively explore the thoughts and preferences of people aged 65 and over regarding technologies to detect feelings of loneliness in later life. Methods: We conducted 60 semi-structured interviews with people aged 65 and over between September 2022 and August 2023. Data were analysed using a reflective thematic approach on NVIVO software. Results: 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) Personalisation 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. Conclusion: 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.Keywords
This publication has 68 references indexed in Scilit:
- The effectiveness of technology interventions in reducing social isolation and loneliness among community-dwelling older people: A mixed methods systematic reviewArchives of Gerontology and Geriatrics Plus, 2024
- Risk factors for loneliness: A literature reviewSocial Science & Medicine, 2023
- A new deep convolutional neural network incorporating attentional mechanisms for ECG emotion recognitionComputers in Biology and Medicine, 2023
- A machine learning model for emotion recognition from physiological signalsBiomedical Signal Processing and Control, 2020
- The growing problem of lonelinessThe Lancet, 2018
- Loneliness in the Modern Age: An Evolutionary Theory of Loneliness (ETL)2018
- Social exclusion of older persons: a scoping review and conceptual frameworkEuropean Journal of Ageing, 2016
- Practical issues related to the implication of elderlies in the design process – The case of a Living Lab approach for designing and evaluating social TV servicesIRBM, 2015
- The De Jong Gierveld short scales for emotional and social loneliness: tested on data from 7 countries in the UN generations and gender surveysEuropean Journal of Ageing, 2010
- Lonely traits and concomitant physiological processes: the MacArthur social neuroscience studiesInternational Journal of Psychophysiology, 2000