Using robot animal companions in the academic library to mitigate student stress
Autumn Edwards, Chad Edwards, Bryan Abendschein, Juliana Espinosa, Jonathan Scherger, Patricia Vander Meer
- 发表年份
- 2020
- 引用次数
- 33
摘要
Purpose The purpose of this paper is to interrogate the relationship between self-reported levels of acute stress, perceived social support and interactions with robot animals in an academic library. The authors hypothesized that (1) participants would report lower stress and higher positive affect after their interaction with a robot support animal and (2) perceived supportiveness of the robot support animal would positively predict the amount of stress reduction the participants reported. Design/methodology/approach The authors hosted a robot petting zoo in the main library at a mid-sized Midwestern university during finals week. Participants were asked to rate their stress level prior to interacting with the robot pets (T1) and then after their interaction they were asked about their current stress level and the perceived supportiveness of the robot animal (T2). Data were analyzed using paired samples t -tests for the pretest and post-test scores. Findings The results showed a significant decrease in acute stress between T1 to T2, as well as a significant increase in happiness and relaxation. Participants reported feeling less bored and less tired after their interactions with the robot support animals. The findings also reveal that the degree to which individuals experienced a reduction in stress was influenced by their perceptions of the robot animal's supportiveness. Libraries could consider using robot pet therapy. Originality/value This study reveals the benefit of robot support animals to reduce stress and increase happiness of those experiencing acute stress in a library setting. The authors also introduce the concept of socially supportive contact as a type of unidirectional social support.
关键词
相关论文
Artificial intelligence: a modern approach
1995
Are we ready for autonomous driving? The KITTI vision benchmark suite
Andreas Geiger, P Lenz, R. Urtasun
2012
Self-Organizing Maps
Teuvo Kohonen
1995
TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems
Martı́n Abadi, Ashish Agarwal, Paul Barham 等 20 位作者
2016