Delivering Digital Healthcare for Elderly: A Holistic Framework for the Adoption of Ambient Assisted Living

Abstract

Adoption of Ambient Assisted Living (AAL) technologies for geriatric healthcare is suboptimal. This study aims to present the AAL Adoption Diamond Framework, encompassing a set of key enablers/barriers as factors, and describe our approach to developing this framework. A systematic literature review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. SCOPUS, IEEE Xplore, PubMed, ProQuest, Science Direct, ACM Digital Library, SpringerLink, Wiley Online Library and grey literature were searched. Thematic analysis was performed to identify factors reported or perceived to be important for adopting AAL technologies. Of 3717 studies initially retrieved, 109 were thoroughly screened and 52 met our inclusion criteria. Nineteen unique technology adoption factors were identified. The most common factor was privacy (50%) whereas data accuracy and affordability were the least common factors (4%). The highest number of factors found per a given study was eleven whereas the average number of factors across all studies included in our sample was four (mean = 3.9). We formed an AAL technology adoption framework based on the retrieved information and named it the AAL Adoption Diamond Framework. This holistic framework was formed by organising the identified technology adoption factors into four key dimensions: Human, Technology, Business, and Organisation. To conclude, the AAL Adoption Diamond Framework is holistic in term of recognizing key factors for the adoption of AAL technologies, and novel and unmatched in term of structuring them into four overarching themes or dimensions, bringing together the individual and the systemic factors evolving around the adoption of AAL technology. This framework is useful for stakeholders (e.g., decision-makers, healthcare providers, and caregivers) to adopt and implement AAL technologies.

Harnessing digital health interventions to bridge the gap in prevention for older adults

“…Older adult individuals may exhibit apprehension about technology due to perceived complexities and apprehensions around privacy and data security ( 39 ). Addressing these concerns is of utmost importance by implementing user-friendly interfaces, fewer buttons, larger text, improved color contrast, providing clear instructions, and adopting transparent data management methods ( 40 ). The present systems struggle to cope with the demands of processing and securing the vast influx of multi-sensory data captured.…”

Research status of elderly-care robots and safe human-robot interaction methods

“…These systems automatically generate visual health recommendations while assessing the users’ health status. Additionally, the system can provide early intervention for elderly individuals living in the home environment, effectively assess and minimize the long-term impact of various factors on health, and encourage elderly individuals to maintain an active and healthy lifestyle ( Alsulami et al, 2017 , 2022 ; Almalki et al, 2022 ). PHAROS (Physical Assistant Robot System) combines the Pepper robot ( Figure 1A ) and a motion expert system to analyze users’ motion states during daily training using deep learning methods ( Costa et al, 2018 ; Martinez-Martin et al, 2019 ).…”