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Qirtas MM, Zafeiridi E, Pesch D, White EB. Loneliness and Social Isolation Detection Using Passive Sensing Techniques: Scoping Review. JMIR Mhealth Uhealth 2022; 10:e34638. [PMID: 35412465 PMCID: PMC9044142 DOI: 10.2196/34638] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2021] [Revised: 02/21/2022] [Accepted: 02/25/2022] [Indexed: 01/23/2023] Open
Abstract
BACKGROUND Loneliness and social isolation are associated with multiple health problems, including depression, functional impairment, and death. Mobile sensing using smartphones and wearable devices, such as fitness trackers or smartwatches, as well as ambient sensors, can be used to acquire data remotely on individuals and their daily routines and behaviors in real time. This has opened new possibilities for the early detection of health and social problems, including loneliness and social isolation. OBJECTIVE This scoping review aimed to identify and synthesize recent scientific studies that used passive sensing techniques, such as the use of in-home ambient sensors, smartphones, and wearable device sensors, to collect data on device users' daily routines and behaviors to detect loneliness or social isolation. This review also aimed to examine various aspects of these studies, especially target populations, privacy, and validation issues. METHODS A scoping review was undertaken, following the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews). Studies on the topic under investigation were identified through 6 databases (IEEE Xplore, Scopus, ACM, PubMed, Web of Science, and Embase). The identified studies were screened for the type of passive sensing detection methods for loneliness and social isolation, targeted population, reliability of the detection systems, challenges, and limitations of these detection systems. RESULTS After conducting the initial search, a total of 40,071 papers were identified. After screening for inclusion and exclusion criteria, 29 (0.07%) studies were included in this scoping review. Most studies (20/29, 69%) used smartphone and wearable technology to detect loneliness or social isolation, and 72% (21/29) of the studies used a validated reference standard to assess the accuracy of passively collected data for detecting loneliness or social isolation. CONCLUSIONS Despite the growing use of passive sensing technologies for detecting loneliness and social isolation, some substantial gaps still remain in this domain. A population heterogeneity issue exists among several studies, indicating that different demographic characteristics, such as age and differences in participants' behaviors, can affect loneliness and social isolation. In addition, despite extensive personal data collection, relatively few studies have addressed privacy and ethical issues. This review provides uncertain evidence regarding the use of passive sensing to detect loneliness and social isolation. Future research is needed using robust study designs, measures, and examinations of privacy and ethical concerns.
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Affiliation(s)
- Malik Muhammad Qirtas
- School of Computer Science & Information Technology, University College Cork, Cork, Ireland
| | - Evi Zafeiridi
- School of Computer Science & Information Technology, University College Cork, Cork, Ireland
| | - Dirk Pesch
- School of Computer Science & Information Technology, University College Cork, Cork, Ireland
| | - Eleanor Bantry White
- School of Computer Science & Information Technology, University College Cork, Cork, Ireland
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Haslam-Larmer L, Shum L, Chu CH, McGilton K, McArthur C, Flint AJ, Khan S, Iaboni A. Real-time location systems technology in the care of older adults with cognitive impairment living in residential care: A scoping review. Front Psychiatry 2022; 13:1038008. [PMID: 36440422 PMCID: PMC9685159 DOI: 10.3389/fpsyt.2022.1038008] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Accepted: 10/24/2022] [Indexed: 11/12/2022] Open
Abstract
INTRODUCTION There has been growing interest in using real-time location systems (RTLS) in residential care settings. This technology has clinical applications for locating residents within a care unit and as a nurse call system, and can also be used to gather information about movement, location, and activity over time. RTLS thus provides health data to track markers of health and wellbeing and augment healthcare decisions. To date, no reviews have examined the potential use of RTLS data in caring for older adults with cognitive impairment living in a residential care setting. OBJECTIVE This scoping review aims to explore the use of data from real-time locating systems (RTLS) technology to inform clinical measures and augment healthcare decision-making in the care of older adults with cognitive impairment who live in residential care settings. METHODS Embase (Ovid), CINAHL (EBSCO), APA PsycINFO (Ovid) and IEEE Xplore databases were searched for published English-language articles that reported the results of studies that investigated RTLS technologies in persons aged 50 years or older with cognitive impairment who were living in a residential care setting. Included studies were summarized, compared and synthesized according to the study outcomes. RESULTS A total of 27 studies were included. RTLS data were used to assess activity levels, characterization of wandering, cognition, social interaction, and to monitor a resident's health and wellbeing. These RTLS-based measures were not consistently validated against clinical measurements or clinically important outcomes, and no studies have examined their effectiveness or impact on decision-making. CONCLUSION This scoping review describes how data from RTLS technology has been used to support clinical care of older adults with dementia. Research efforts have progressed from using the data to track activity levels to, most recently, using the data to inform clinical decision-making and as a predictor of delirium. Future studies are needed to validate RTLS-based health indices and examine how these indices can be used to inform decision-making.
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Affiliation(s)
- Lynn Haslam-Larmer
- KITE Research Institute, Toronto Rehabilitation Institute, University Health Network, Toronto, ON, Canada
| | - Leia Shum
- KITE Research Institute, Toronto Rehabilitation Institute, University Health Network, Toronto, ON, Canada
| | - Charlene H Chu
- KITE Research Institute, Toronto Rehabilitation Institute, University Health Network, Toronto, ON, Canada.,Lawrence S. Bloomberg Faculty of Nursing, University of Toronto, Toronto, ON, Canada
| | - Kathy McGilton
- KITE Research Institute, Toronto Rehabilitation Institute, University Health Network, Toronto, ON, Canada.,Lawrence S. Bloomberg Faculty of Nursing, University of Toronto, Toronto, ON, Canada
| | - Caitlin McArthur
- School of Physiotherapy, Dalhousie University, Halifax, NS, Canada
| | - Alastair J Flint
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada.,Centre for Mental Health, University Health Network, Toronto, ON, Canada
| | - Shehroz Khan
- KITE Research Institute, Toronto Rehabilitation Institute, University Health Network, Toronto, ON, Canada
| | - Andrea Iaboni
- KITE Research Institute, Toronto Rehabilitation Institute, University Health Network, Toronto, ON, Canada.,Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada.,Centre for Mental Health, University Health Network, Toronto, ON, Canada
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Latikka R, Rubio-Hernández R, Lohan ES, Rantala J, Nieto Fernández F, Laitinen A, Oksanen A. Older Adults' Loneliness, Social Isolation, and Physical Information and Communication Technology in the Era of Ambient Assisted Living: A Systematic Literature Review. J Med Internet Res 2021; 23:e28022. [PMID: 34967760 PMCID: PMC8759023 DOI: 10.2196/28022] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2021] [Revised: 06/30/2021] [Accepted: 11/08/2021] [Indexed: 01/22/2023] Open
Abstract
BACKGROUND Loneliness and social isolation can have severe effects on human health and well-being. Partial solutions to combat these circumstances in demographically aging societies have been sought from the field of information and communication technology (ICT). OBJECTIVE This systematic literature review investigates the research conducted on older adults' loneliness and social isolation, and physical ICTs, namely robots, wearables, and smart homes, in the era of ambient assisted living (AAL). The aim is to gain insight into how technology can help overcome loneliness and social isolation other than by fostering social communication with people and what the main open-ended challenges according to the reviewed studies are. METHODS The data were collected from 7 bibliographic databases. A preliminary search resulted in 1271 entries that were screened based on predefined inclusion criteria. The characteristics of the selected studies were coded, and the results were summarized to answer our research questions. RESULTS The final data set consisted of 23 empirical studies. We found out that ICT solutions such as smart homes can help detect and predict loneliness and social isolation, and technologies such as robotic pets and some other social robots can help alleviate loneliness to some extent. The main open-ended challenges across studies relate to the need for more robust study samples and study designs. Further, the reviewed studies report technology- and topic-specific open-ended challenges. CONCLUSIONS Technology can help assess older adults' loneliness and social isolation, and alleviate loneliness without direct interaction with other people. The results are highly relevant in the COVID-19 era, where various social restrictions have been introduced all over the world, and the amount of research literature in this regard has increased recently.
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Affiliation(s)
- Rita Latikka
- Faculty of Social Sciences, Tampere University, Tampere, Finland
| | | | - Elena Simona Lohan
- Faculty of Information Technology and Communication Sciences, Tampere University, Tampere, Finland
| | - Juho Rantala
- Faculty of Social Sciences, Tampere University, Tampere, Finland
| | | | - Arto Laitinen
- Faculty of Social Sciences, Tampere University, Tampere, Finland
| | - Atte Oksanen
- Faculty of Social Sciences, Tampere University, Tampere, Finland
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Qiu S, An P, Kang K, Hu J, Han T, Rauterberg M. A Review of Data Gathering Methods for Evaluating Socially Assistive Systems. SENSORS (BASEL, SWITZERLAND) 2021; 22:82. [PMID: 35009623 PMCID: PMC8747743 DOI: 10.3390/s22010082] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/20/2021] [Revised: 12/16/2021] [Accepted: 12/21/2021] [Indexed: 05/21/2023]
Abstract
Social interactions significantly impact the quality of life for people with special needs (e.g., older adults with dementia and children with autism). They may suffer loneliness and social isolation more often than people without disabilities. There is a growing demand for technologies to satisfy the social needs of such user groups. However, evaluating these systems can be challenging due to the extra difficulty of gathering data from people with special needs (e.g., communication barriers involving older adults with dementia and children with autism). Thus, in this systematic review, we focus on studying data gathering methods for evaluating socially assistive systems (SAS). Six academic databases (i.e., Scopus, Web of Science, ACM, Science Direct, PubMed, and IEEE Xplore) were searched, covering articles published from January 2000 to July 2021. A total of 65 articles met the inclusion criteria for this systematic review. The results showed that existing SASs most often targeted people with visual impairments, older adults, and children with autism. For instance, a common type of SASs aimed to help blind people perceive social signals (e.g., facial expressions). SASs were most commonly assessed with interviews, questionnaires, and observation data. Around half of the interview studies only involved target users, while the other half also included secondary users or stakeholders. Questionnaires were mostly used with older adults and people with visual impairments to measure their social interaction, emotional state, and system usability. A great majority of observational studies were carried out with users in special age groups, especially older adults and children with autism. We thereby contribute an overview of how different data gathering methods were used with various target users of SASs. Relevant insights are extracted to inform future development and research.
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Affiliation(s)
- Shi Qiu
- Department of Design, Shanghai Jiao Tong University, Shanghai 200240, China;
- Department of Industrial Design, Eindhoven University of Technology, 5600MB Eindhoven, The Netherlands; (K.K.); (J.H.); (M.R.)
| | - Pengcheng An
- School of Design, Southern University of Science and Technology, Shenzhen 518055, China;
- School of Computer Science, University of Waterloo, Waterloo, ON N2L 3G1, Canada
| | - Kai Kang
- Department of Industrial Design, Eindhoven University of Technology, 5600MB Eindhoven, The Netherlands; (K.K.); (J.H.); (M.R.)
- Department of Industrial Design, Nantong University, Nantong 226019, China
| | - Jun Hu
- Department of Industrial Design, Eindhoven University of Technology, 5600MB Eindhoven, The Netherlands; (K.K.); (J.H.); (M.R.)
| | - Ting Han
- Department of Design, Shanghai Jiao Tong University, Shanghai 200240, China;
| | - Matthias Rauterberg
- Department of Industrial Design, Eindhoven University of Technology, 5600MB Eindhoven, The Netherlands; (K.K.); (J.H.); (M.R.)
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Qiu S, An P, Kang K, Hu J, Han T, Rauterberg M. Investigating socially assistive systems from system design and evaluation: a systematic review. UNIVERSAL ACCESS IN THE INFORMATION SOCIETY 2021; 22:609-633. [PMID: 34803565 PMCID: PMC8591319 DOI: 10.1007/s10209-021-00852-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Accepted: 11/02/2021] [Indexed: 05/24/2023]
Abstract
Purpose The development of assistive technologies that support people in social interactions has attracted increased attention in HCI. This paper presents a systematic review of studies of Socially Assistive Systems targeted at older adults and people with disabilities. The purpose is threefold: (1) Characterizing related assistive systems with a special focus on the system design, primarily including HCI technologies used and user-involvement approach taken; (2) Examining their ways of system evaluation; (3) Reflecting on insights for future design research. Methods A systematic literature search was conducted using the keywords "social interactions" and "assistive technologies" within the following databases: Scopus, Web of Science, ACM, Science Direct, PubMed, and IEEE Xplore. Results Sixty-five papers met the inclusion criteria and were further analyzed. Our results showed that there were 11 types of HCI technologies that supported social interactions for target users. The most common was cognitive and meaning understanding technologies, often applied with wearable devices for compensating users' sensory loss; 33.85% of studies involved end-users and stakeholders in the design phase; Four types of evaluation methods were identified. The majority of studies adopted laboratory experiments to measure user-system interaction and system validation. Proxy users were used in system evaluation, especially in initial experiments; 42.46% of evaluations were conducted in field settings, primarily including the participants' own homes and institutions. Conclusion We contribute an overview of Socially Assistive Systems that support social interactions for older adults and people with disabilities, as well as illustrate emerging technologies and research opportunities for future work.
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Affiliation(s)
- Shi Qiu
- Department of Design, Shanghai Jiao Tong University, Shanghai, 800 Dongchuan RD. Minhang District China
- Department of Industrial Design, Eindhoven University of Technology, Eindhoven, Netherlands
| | - Pengcheng An
- School of Design, Southern University of Science and Technology, Shenzhen, China
- School of Computer Science, University of Waterloo, Waterloo, ON Canada
| | - Kai Kang
- Department of Industrial Design, Eindhoven University of Technology, Eindhoven, Netherlands
- Department of Industrial Design, Nantong University, Nantong, China
| | - Jun Hu
- Department of Industrial Design, Eindhoven University of Technology, Eindhoven, Netherlands
| | - Ting Han
- Department of Design, Shanghai Jiao Tong University, Shanghai, 800 Dongchuan RD. Minhang District China
| | - Matthias Rauterberg
- Department of Industrial Design, Eindhoven University of Technology, Eindhoven, Netherlands
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On Supporting University Communities in Indoor Wayfinding: An Inclusive Design Approach. SENSORS 2021; 21:s21093134. [PMID: 33946454 PMCID: PMC8124871 DOI: 10.3390/s21093134] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/24/2021] [Revised: 04/22/2021] [Accepted: 04/28/2021] [Indexed: 11/21/2022]
Abstract
Mobility can be defined as the ability of people to move, live and interact with the space. In this context, indoor mobility, in terms of indoor localization and wayfinding, is a relevant topic due to the challenges it presents, in comparison with outdoor mobility, where GPS is hardly exploited. Knowing how to move in an indoor environment can be crucial for people with disabilities, and in particular for blind users, but it can provide several advantages also to any person who is moving in an unfamiliar place. Following this line of thought, we employed an inclusive by design approach to implement and deploy a system that comprises an Internet of Things infrastructure and an accessible mobile application to provide wayfinding functions, targeting the University community. As a real word case study, we considered the University of Bologna, designing a system able to be deployed in buildings with different configurations and settings, considering also historical buildings. The final system has been evaluated in three different scenarios, considering three different target audiences (18 users in total): i. students with disabilities (i.e., visual and mobility impairments); ii. campus students; and iii. visitors and tourists. Results reveal that all the participants enjoyed the provided functions and the indoor localization strategy was fine enough to provide a good wayfinding experience.
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