AIMC Topic: Long-Term Care

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Staff's Attitudes towards the Use of Mobile Telepresence Robots in Long-Term Care Homes in Canada.

Canadian journal on aging = La revue canadienne du vieillissement
This cross-sectional study investigated staff's attitudes towards the use of mobile telepresence robots in long-term care (LTC) homes in western Canada. We drew on a Health Technology Assessment Core Model 3.0 to design a survey examining attitudes t...

Facilitators and barriers to using AI-enabled robots with older adults in long-term care from staff perspective: a scoping review protocol.

BMJ open
INTRODUCTION: Assistive and service robots have been increasingly designed and deployed in long-term care (LTC) but little evidence guides their use. This scoping review synthesises existing studies on facilitators and barriers to using artificial in...

Beyond Plan-Do-Study-Act cycle - staff perceptions on facilitators and barriers to the implementation of telepresence robots in long-term care.

BMC health services research
BACKGROUND: Quality improvement (QI) programs with technology implementations have been introduced to long-term care (LTC) to improve residents' quality of life. Plan-Do-Study-Act (PDSA) cycle is commonly adopted in QI projects. There should be an ap...

Integrating Artificial Intelligence and Wearable IoT System in Long-Term Care Environments.

Sensors (Basel, Switzerland)
With the rapid advancement of information and communication technology (ICT), big data, and artificial intelligence (AI), intelligent healthcare systems have emerged, including the integration of healthcare systems with capital, the introduction of h...

A Risk Prediction Model for Physical Restraints Among Older Chinese Adults in Long-term Care Facilities: Machine Learning Study.

Journal of medical Internet research
BACKGROUND: Numerous studies have identified risk factors for physical restraint (PR) use in older adults in long-term care facilities. Nevertheless, there is a lack of predictive tools to identify high-risk individuals.

Long-term care insurance purchase decisions of registered nurses: Deep learning versus logistic regression models.

Health policy (Amsterdam, Netherlands)
OBJECTIVE: The purpose of this study was to use a deep learning model and a traditional statistical regression model to predict the long-term care insurance decisions of registered nurses.

Strategies to Implement Pet Robots in Long-Term Care Facilities for Dementia Care: A Modified Delphi Study.

Journal of the American Medical Directors Association
OBJECTIVES: Pet robots are technology-based substitutes for live animals that have demonstrated psychosocial benefits for people living with dementia in long-term care. However, little research has been conducted to understand how pet robots should b...

Text mining in long-term care: Exploring the usefulness of artificial intelligence in a nursing home setting.

PloS one
OBJECTIVES: In nursing homes, narrative data are collected to evaluate quality of care as perceived by residents or their family members. This results in a large amount of textual data. However, as the volume of data increases, it becomes beyond the ...

The adoption of socially assistive robots for long-term care: During COVID-19 and in a post-pandemic society.

Healthcare management forum
The rapid spread of COVID-19 has prompted a surge in the adoption of technology, highlighting a number of potential applications for Socially Assistive Robots (SARs). Our entire healthcare system has been under unprecedented strain, and going forward...

Promoting activity in long-term care facilities with the social robot Pepper: a pilot study.

Informatics for health & social care
About 40 000 individuals depend on assisted living in long-term care facilities in Norway. Around 80% of these have a cognitive impairment or suffer from dementia. This actualizes the need for activities that are tailored to individual needs. For som...