This paper presents experiences of integrating assistive robots in Japanese nursing care through semi-structured interviews and site observations at three nursing homes in Japan during the year 2019. The study looked at experiences with the robots Paro, Pepper, and Qoobo. The goal was to investigate and evaluate the current state of using robots within the nursing care context, which involved: firsthand experiences with intended and real users; and response from the elderly, and nursing staff. The qualitative analysis results pointed out user satisfaction, adjusted purpose, therapeutic and entertaining effects. The potentials of using robots to assist in elderly care has been evident. Limitations currently relate to the lack of ways to fully utilize and integrate robots.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.3233/SHTI200524 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Clinical Judgment Model-Based Critical Reflection Program for Newly Graduated Nurses: A Nonrandomized Controlled Trial.
Res Nurs Health
January 2025
Graduate School of Clinical Nursing Science, Sungkyunkwan University, Suwon, Republic of Korea.
This study evaluated the effects of a critical reflection program utilizing the Lasater Clinical Judgment Rubric (LCJR) reflective questions based on the Clinical Judgment Model (CJM) on newly graduated nurses' clinical judgment skills. A total of 153 newly graduated nurses scheduled for on-site training in a ward nursing unit were divided into a control group (receiving only the usual on-site training with preceptorship) and an experimental group (receiving the developed program with the same on-site training with preceptorship as the control group). Data were collected at baseline, 6 weeks, and 3 months after the intervention.
View Article and Find Full Text PDFA nomogram for predicting central venous catheter-related infections in maintenance hemodialysis: A 4-year single-center study.
J Vasc Access
January 2025
College of Nursing, Xuzhou Medical University, Xuzhou, Jiangsu, China.
Objective: To develop and validate a nomogram model for predicting central venous catheter-related infections (CRI) in patients with maintenance hemodialysis (MHD).
Methods: MHD patients with central venous catheters (CVCs) visiting the outpatient hemodialysis (HD) center of Xuzhou Medical University Affiliated Hospital from January 2020 to December 2023 were retrospectively selected through a HD monitoring system. Patient data were collected, and the patients were divided into training and validation sets in a 7:3 ratio.
Effects of a Behavior Intervention Based on the Recurrence Risk Perception and Behavioral Decision Model for Ischemic Stroke Patients: A Randomized Controlled Trial.
Res Nurs Health
January 2025
School of Nursing and Health, Zhengzhou University, Zhengzhou, Henan, China.
Behavioral management is essential to preventing recurrence after stroke, but its adherence is limited worldwide. We aimed to assess the impact of the behavior intervention based on the Recurrence risk perception and Behavioral decision Model for ischemic stroke patients' health behavior. This study was a single-blind, randomized, controlled trial with a 3-month follow-up.
View Article and Find Full Text PDFSituational assessment of physical rehabilitation services in Zambia: issues and challenges.
Disabil Rehabil
January 2025
Discipline of Public Health Medicine, School of Nursing and Public Health, University of KwaZulu-Natal, Durban, Republic of South Africa.
Purpose: The necessity to enhance physical rehabilitation services in Zambia has been recognised. To achieve this through expanding human resources for health in rehabilitation and increasing service coverage, it is essential to comprehensively understand the current issues and challenges in physical rehabilitation within the country. This paper aimed to conduct a situational assessment of physical rehabilitation services in Zambia.
View Article and Find Full Text PDFArtificial intelligence in clinical settings: a systematic review of its role in language translation and interpretation.
Ann Transl Med
December 2024
Division of Advanced Gastrointestinal and Bariatric Surgery, Mayo Clinic, Jacksonville, FL, USA.
Background: Addressing language barriers through accurate interpretation is crucial for providing quality care and establishing trust. While the ability of artificial intelligence (AI) to translate medical documentation has been studied, its role for patient-provider communication is less explored. This review evaluates AI's effectiveness in clinical translation by assessing accuracy, usability, satisfaction, and feedback on its use.
View Article and Find Full Text PDFWant 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!