Publications by authors named "C Akiyama"
Retraction Note to: Effects of artificial intelligence aibo intervention on alleviating distress and fear in children.
Child Adolesc Psychiatry Ment Health
October 2024
Effects of artificial intelligence aibo intervention on alleviating distress and fear in children.
Child Adolesc Psychiatry Ment Health
November 2022
Article Synopsis
- Procedures like vaccinations can cause distress in children, prompting a need for effective interventions to mitigate pain and anxiety during medical treatments.
- A study tested the effectiveness of 'aibo', an AI-driven robot, as a distraction tool for children aged 3 to 12 receiving the Japanese encephalitis vaccine, comparing it to a control group using a stuffed animal.
- Results indicated that children interacting with aibo reported lower pain levels and displayed calmer behaviors post-vaccination, supporting the idea that robotic interventions can help ease children's distress during medical procedures.
Although pregnancy is an important risk factor for autoimmune rheumatic diseases, little is known regarding the association between pregnancy and dermatomyositis (DM) or polymyositis (PM). Herein, we present two patients with DM that developed during the perinatal period. The first patient was positive for anti-aminoacyl synthetase (ARS) antibody and developed DM in the 14th week of pregnancy.
View Article and Find Full Text PDFStaff members in the intensive care unit expect to deal with medical emergencies and are typically well-educated and trained to manage these. However, when faced with unusual threats such as an active shooter in the environment, they may be less well-prepared to take prompt and definitive actions. This brief article outlines the active shooter scenario and suggests strategies to ensure the safety of patients, staff members, and visitors who are in the unit.
View Article and Find Full Text PDFArticle Synopsis
- Land abandonment, especially in agriculture, has significant social and ecological effects, making it crucial to predict its future extent and patterns based on various factors.
- A framework was developed for projecting land abandonment scenarios in Fukushima Prefecture, Japan, examining two socioeconomic growth scenarios from 2014 to 2050: low (LL) and high (HH).
- Results showed that under the HH scenario, agricultural abandonment would increase significantly due to a decline in the farmer population, while under the LL scenario, urban and residential land abandonment would rise because of a greater decline in total population, providing valuable insights for adaptive development planning.