IMPORTANCE: Agitation events are increasing in emergency departments (EDs), exacerbating safety risks for patients and clinicians. A wide range of clinical etiologies and behavioral patterns in the emergency setting make agitation prediction difficul...
Journal of the American Medical Directors Association
26096582
OBJECTIVES: To examine effects on symptoms of agitation and depression in nursing home residents with moderate to severe dementia participating in a robot-assisted group activity with the robot seal Paro.
INTRODUCTION: Apathy, agitated behaviours, loneliness and depression are common consequences of dementia. This trial aims to evaluate the effect of a robotic animal on behavioural and psychological symptoms of dementia in people with dementia living ...
Psychogeriatrics : the official journal of the Japanese Psychogeriatric Society
26510632
BACKGROUND: Previous studies have suggested that visiting dogs can have positive effects on elderly people in nursing homes. We wanted to study the effects of biweekly dog visits on sleep patterns and the psychiatric well-being of elderly people.
BACKGROUND: A variety of group activities is promoted for nursing home (NH) residents with dementia with the aim to reduce apathy and to increase engagement and social interaction. Investigating behaviors related to these outcomes could produce insig...
Journal of the American Medical Directors Association
29325922
OBJECTIVES: To examine the within-trial costs and cost-effectiveness of using PARO, compared with a plush toy and usual care, for reducing agitation and medication use in people with dementia in long-term care.
Journal of the American Medical Directors Association
29656838
OBJECTIVES: To explore whether severity of cognitive impairment and agitation of older people with dementia predict outcomes in engagement, mood states, and agitation after a 10-week intervention with the robotic seal, PARO.
BMC medical informatics and decision making
38500135
OBJECTIVE: To address the challenge of assessing sedation status in critically ill patients in the intensive care unit (ICU), we aimed to develop a non-contact automatic classifier of agitation using artificial intelligence and deep learning.
BACKGROUND: Agitation and sedation management is critical in intensive care as it affects patient safety. Traditional nursing assessments suffer from low frequency and subjectivity. Automating these assessments can boost intensive care unit (ICU) eff...