Purpose: We aimed to identify assistive technologies that are promising for addressing loneliness in people living with dementia in long-term care.

Materials And Methods: A scoping review was conducted. EBSCO, PubMed, Cochrane Library, and ProQuest were searched from 2000 to 2020. The included studies were selected by three independent researchers and summarised, compared, and categorized according to technology type. Publications were eligible for inclusion when they reported on psychosocial interventions aiming to reduce loneliness and/or social isolation in people with dementia in long-term care settings.

Results: Twenty-four papers were included (20 original research papers and four reviews). Most studies were conducted in Australia and Europe. The studies aimed to investigate two different types of assistive technology: social robots, and multimedia computer systems. Most studies focussed on behaviour, engagement, and mood as primary outcomes. Only one study directly aimed to alleviate loneliness.

Conclusions: Even though only one study addressed loneliness directly, it became clear that assistive technologies used to apply psychosocial interventions have the potential to impact loneliness in people with dementia in long-term care. However, it remains unclear why loneliness was not included as an outcome and how loneliness could become a key outcome in evaluating assistive technologies.IMPLICATIONS FOR REHABILITATIONLoneliness among older adults is associated with health risks, such as the development of dementia, depression, and increased mortality.Ambient Assisted Living (AAL) technologies have been studied to address loneliness for older adults; however people with dementia are often excluded from such studies.This diverse group of technologies is shown to have a promising impact on outcomes, such as social engagement, quality of life, and mood, but loneliness was studied less often.More research is needed to discover the potential of assistive technologies for people with dementia living in long-term care.

Download full-text PDF

Source
http://dx.doi.org/10.1080/17483107.2021.1984594DOI Listing

Publication Analysis

Top Keywords

assistive technologies
16
long-term care
16
people dementia
16
psychosocial interventions
12
dementia long-term
12
loneliness
9
impact loneliness
8
scoping review
8
technologies promising
8
loneliness people
8

Similar Publications

Enhancing the Travel Experience for People with Visual Impairments through Multimodal Interaction: NaviGPT, A Real-Time AI-Driven Mobile Navigation System.

GROUP ACM SIGCHI Int Conf Support Group Work

January 2025

College of Information Sciences and Technology, The Pennsylvania State University, University Park, Pennsylvania, USA.

Assistive technologies for people with visual impairments (PVI) have made significant advancements, particularly with the integration of artificial intelligence (AI) and real-time sensor technologies. However, current solutions often require PVI to switch between multiple apps and tools for tasks like image recognition, navigation, and obstacle detection, which can hinder a seamless and efficient user experience. In this paper, we present NaviGPT, a high-fidelity prototype that integrates LiDAR-based obstacle detection, vibration feedback, and large language model (LLM) responses to provide a comprehensive and real-time navigation aid for PVI.

View Article and Find Full Text PDF

User Acceptance of a Home Robotic Assistant for Individuals With Physical Disabilities: Explorative Qualitative Study.

JMIR Rehabil Assist Technol

January 2025

Department of Health and Nursing Science, Faculty of Health and Sport Sciences, University of Agder, Kristiansand, Norway.

Background: Health care is shifting toward 5 proactive approaches: personalized, participatory, preventive, predictive, and precision-focused services (P5 medicine). This patient-centered care leverages technologies such as artificial intelligence (AI)-powered robots, which can personalize and enhance services for users with disabilities. These advancements are crucial given the World Health Organization's projection of a global shortage of up to 10 million health care workers by 2030.

View Article and Find Full Text PDF

Background: There is a global need for synthetic speech development in multiple languages and dialects, as many children who cannot communicate using their natural voice struggle to find synthetic voices on high-technology devices that match their age, social and linguistic background.

Aims: To document multiple stakeholders' perspectives surrounding the quality, acceptability and utility of newly created synthetic speech in three under-resourced South African languages, namely South African English, Afrikaans and isiXhosa.

Methods & Procedures: A mixed methods research design was selected.

View Article and Find Full Text PDF

Empowering People with Disabilities in Smart Homes Using Predictive Informing.

Sensors (Basel)

January 2025

University of Zagreb, Faculty of Transport and Traffic Sciences, Vukelićeva 4, 10000 Zagreb, Croatia.

The possibilities of the Ambient Assisted Living (AAL)/Enhanced Living Environments (ELE) concept in the environment of a smart home were investigated to improve accessibility and improve the quality of life of a person with disabilities. This paper focuses on the concept of predictive information for a person with disabilities in a smart home environment concept where artificial intelligence (AI) and machine learning (ML) systems use data on the user's preferences, habits, and possible incident situations. A conceptual mathematical model is proposed, the purpose of which is to provide predictive user information from defined data sets.

View Article and Find Full Text PDF

Improving Imitation Skills in Children with Autism Spectrum Disorder Using the NAO Robot and a Human Action Recognition.

Diagnostics (Basel)

December 2024

Computer Science Department, College of Computer and Information Sciences, King Saud University, Riyadh 11543, Saudi Arabia.

Autism spectrum disorder (ASD) is a group of developmental disorders characterized by poor social skills, low motivation in activities, and a lack of interaction with others. Traditional intervention approaches typically require support under the direct supervision of well-trained professionals. However, teaching and training programs for children with ASD can also be enhanced by assistive technologies, artificial intelligence, and robotics.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!