Managing Perceived Loneliness and Social-Isolation Levels for Older Adults: A Survey with Focus on Wearables-Based Solutions
As an inevitable process, the number of older adults is increasing in many countries worldwide. Two of the main problems that society is being confronted with more and more, in this respect, are the inter-related aspects of feelings of loneliness and social isolation among older adults. In particula...
| Main Authors: | , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-02-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/22/3/1108 |
| _version_ | 1797484626563825664 |
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| author | Aditi Site Elena Simona Lohan Outi Jolanki Outi Valkama Rosana Rubio Hernandez Rita Latikka Daria Alekseeva Saigopal Vasudevan Samuel Afolaranmi Aleksandr Ometov Atte Oksanen Jose Martinez Lastra Jari Nurmi Fernando Nieto Fernandez |
| author_facet | Aditi Site Elena Simona Lohan Outi Jolanki Outi Valkama Rosana Rubio Hernandez Rita Latikka Daria Alekseeva Saigopal Vasudevan Samuel Afolaranmi Aleksandr Ometov Atte Oksanen Jose Martinez Lastra Jari Nurmi Fernando Nieto Fernandez |
| author_sort | Aditi Site |
| collection | DOAJ |
| description | As an inevitable process, the number of older adults is increasing in many countries worldwide. Two of the main problems that society is being confronted with more and more, in this respect, are the inter-related aspects of feelings of loneliness and social isolation among older adults. In particular, the ongoing COVID-19 crisis and its associated restrictions have exacerbated the loneliness and social-isolation problems. This paper is first and foremost a comprehensive survey of loneliness monitoring and management solutions, from the multidisciplinary perspective of technology, gerontology, socio-psychology, and urban built environment. In addition, our paper also investigates machine learning-based technological solutions with wearable-sensor data, suitable to measure, monitor, manage, and/or diminish the levels of loneliness and social isolation, when one also considers the constraints and characteristics coming from social science, gerontology, and architecture/urban built environments points of view. Compared to the existing state of the art, our work is unique from the cross-disciplinary point of view, because our authors’ team combines the expertise from four distinct domains, i.e., gerontology, social psychology, architecture, and wireless technology in addressing the two inter-related problems of loneliness and social isolation in older adults. This work combines a cross-disciplinary survey of the literature in the four aforementioned domains with a proposed wearable-based technological solution, introduced first as a generic framework and, then, exemplified through a simple proof of concept with dummy data. As the main findings, we provide a comprehensive view on challenges and solutions in utilizing various technologies, particularly those carried by users, also known as wearables, to measure, manage, and/or diminish the social isolation and the perceived loneliness among older adults. In addition, we also summarize the identified solutions which can be used for measuring and monitoring various loneliness- and social isolation-related metrics, and we present and validate, through a simple proof-of-concept mechanism, an approach based on machine learning for predicting and estimating loneliness levels. Open research issues in this field are also discussed. |
| first_indexed | 2024-03-09T23:08:09Z |
| format | Article |
| id | doaj.art-abb081bb43d340fd848e4dfe9ebc0130 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-09T23:08:09Z |
| publishDate | 2022-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-abb081bb43d340fd848e4dfe9ebc01302023-11-23T17:50:35ZengMDPI AGSensors1424-82202022-02-01223110810.3390/s22031108Managing Perceived Loneliness and Social-Isolation Levels for Older Adults: A Survey with Focus on Wearables-Based SolutionsAditi Site0Elena Simona Lohan1Outi Jolanki2Outi Valkama3Rosana Rubio Hernandez4Rita Latikka5Daria Alekseeva6Saigopal Vasudevan7Samuel Afolaranmi8Aleksandr Ometov9Atte Oksanen10Jose Martinez Lastra11Jari Nurmi12Fernando Nieto Fernandez13Faculty of Information Technology and Communication Sciences, Tampere University, 33720 Tampere, FinlandFaculty of Information Technology and Communication Sciences, Tampere University, 33720 Tampere, FinlandFaculty of Social Sciences, Tampere University, 33720 Tampere, FinlandFaculty of Social Sciences, Tampere University, 33720 Tampere, FinlandFaculty of Built Environment, Tampere University, 33720 Tampere, FinlandFaculty of Social Sciences, Tampere University, 33720 Tampere, FinlandFaculty of Information Technology and Communication Sciences, Tampere University, 33720 Tampere, FinlandFaculty of Engineering and Natural Sciences, Tampere University, 33720 Tampere, FinlandFaculty of Engineering and Natural Sciences, Tampere University, 33720 Tampere, FinlandFaculty of Information Technology and Communication Sciences, Tampere University, 33720 Tampere, FinlandFaculty of Social Sciences, Tampere University, 33720 Tampere, FinlandFaculty of Engineering and Natural Sciences, Tampere University, 33720 Tampere, FinlandFaculty of Information Technology and Communication Sciences, Tampere University, 33720 Tampere, FinlandFaculty of Built Environment, Tampere University, 33720 Tampere, FinlandAs an inevitable process, the number of older adults is increasing in many countries worldwide. Two of the main problems that society is being confronted with more and more, in this respect, are the inter-related aspects of feelings of loneliness and social isolation among older adults. In particular, the ongoing COVID-19 crisis and its associated restrictions have exacerbated the loneliness and social-isolation problems. This paper is first and foremost a comprehensive survey of loneliness monitoring and management solutions, from the multidisciplinary perspective of technology, gerontology, socio-psychology, and urban built environment. In addition, our paper also investigates machine learning-based technological solutions with wearable-sensor data, suitable to measure, monitor, manage, and/or diminish the levels of loneliness and social isolation, when one also considers the constraints and characteristics coming from social science, gerontology, and architecture/urban built environments points of view. Compared to the existing state of the art, our work is unique from the cross-disciplinary point of view, because our authors’ team combines the expertise from four distinct domains, i.e., gerontology, social psychology, architecture, and wireless technology in addressing the two inter-related problems of loneliness and social isolation in older adults. This work combines a cross-disciplinary survey of the literature in the four aforementioned domains with a proposed wearable-based technological solution, introduced first as a generic framework and, then, exemplified through a simple proof of concept with dummy data. As the main findings, we provide a comprehensive view on challenges and solutions in utilizing various technologies, particularly those carried by users, also known as wearables, to measure, manage, and/or diminish the social isolation and the perceived loneliness among older adults. In addition, we also summarize the identified solutions which can be used for measuring and monitoring various loneliness- and social isolation-related metrics, and we present and validate, through a simple proof-of-concept mechanism, an approach based on machine learning for predicting and estimating loneliness levels. Open research issues in this field are also discussed.https://www.mdpi.com/1424-8220/22/3/1108architecture/built environmentsgerontologylonelinessMachine Learning (ML)mobility patternsmultidisciplinarity |
| spellingShingle | Aditi Site Elena Simona Lohan Outi Jolanki Outi Valkama Rosana Rubio Hernandez Rita Latikka Daria Alekseeva Saigopal Vasudevan Samuel Afolaranmi Aleksandr Ometov Atte Oksanen Jose Martinez Lastra Jari Nurmi Fernando Nieto Fernandez Managing Perceived Loneliness and Social-Isolation Levels for Older Adults: A Survey with Focus on Wearables-Based Solutions Sensors architecture/built environments gerontology loneliness Machine Learning (ML) mobility patterns multidisciplinarity |
| title | Managing Perceived Loneliness and Social-Isolation Levels for Older Adults: A Survey with Focus on Wearables-Based Solutions |
| title_full | Managing Perceived Loneliness and Social-Isolation Levels for Older Adults: A Survey with Focus on Wearables-Based Solutions |
| title_fullStr | Managing Perceived Loneliness and Social-Isolation Levels for Older Adults: A Survey with Focus on Wearables-Based Solutions |
| title_full_unstemmed | Managing Perceived Loneliness and Social-Isolation Levels for Older Adults: A Survey with Focus on Wearables-Based Solutions |
| title_short | Managing Perceived Loneliness and Social-Isolation Levels for Older Adults: A Survey with Focus on Wearables-Based Solutions |
| title_sort | managing perceived loneliness and social isolation levels for older adults a survey with focus on wearables based solutions |
| topic | architecture/built environments gerontology loneliness Machine Learning (ML) mobility patterns multidisciplinarity |
| url | https://www.mdpi.com/1424-8220/22/3/1108 |
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