Within the pediatric hospitalization experience, fear and anxiety are two emotions commonly felt by children of all ages. Hospitalized children can greatly benefit from interventions designed to help them cope with these emotions throughout their medical experiences. This study draws on each of our clinical experiences as volunteers at Phoenix Children’s Hospital, and uses a qualitative analysis of three semi-structured interviews with currently employed Child Life Specialists to understand and analyze the use of medical play, a form of play intervention with a medical theme or medical equipment. We explore the goals and benefits of medical play for hospitalized pediatric patients, the process of using medical play as an intervention, including the activity design process, the assessments and adjustments made throughout the child’s hospitalization, and the considerations and limitations to implementing medical play activities. Ultimately, we found that the element of fun that defines play can be channeled into medical play activities implemented by skilled Child Life Specialists, who are experts in their field, in clinical settings to promote several different and beneficial goals, including pediatric patient coping.
Within the pediatric hospitalization experience, fear and anxiety are two emotions commonly felt by children of all ages. Hospitalized children can greatly benefit from interventions designed to help them cope with these emotions throughout their medical experiences. This study draws on each of our clinical experiences as volunteers at Phoenix Children’s Hospital, and uses a qualitative analysis of three semi-structured interviews with currently employed Child Life Specialists to understand and analyze the use of medical play, a form of play intervention with a medical theme or medical equipment. We explore the goals and benefits of medical play for hospitalized pediatric patients, the process of using medical play as an intervention, including the activity design process, the assessments and adjustments made throughout the child’s hospitalization, and the considerations and limitations to implementing medical play activities. Ultimately, we found that the element of fun that defines play can be channeled into medical play activities implemented by skilled Child Life Specialists, who are experts in their field, in clinical settings to promote several different and beneficial goals, including pediatric patient coping.
In this experiment, a haptic glove with vibratory motors on the fingertips was tested against the standard HTC Vive controller to see if the additional vibrations provided by the glove increased immersion in common gaming scenarios where haptic feedback is provided. Specifically, two scenarios were developed: an explosion scene containing a small and large explosion and a box interaction scene that allowed the participants to touch the box virtually with their hand. At the start of this project, it was hypothesized that the haptic glove would have a significant positive impact in at least one of these scenarios. Nine participants took place in the study and immersion was measured through a post-experiment questionnaire. Statistical analysis on the results showed that the haptic glove did have a significant impact on immersion in the box interaction scene, but not in the explosion scene. In the end, I conclude that since this haptic glove does not significantly increase immersion across all scenarios when compared to the standard Vive controller, it should not be used at a replacement in its current state.
Designing these agents to cover every case of human interaction is difficult, and usually
imperfect, as human players are capable of learning to overcome these agents in unintended
ways. Artificial intelligence is a growing field that seeks to solve problems by simulating
learning in specific environments. The aim of this paper is to explore the applications that the
self play learning branch of artificial intelligence may pose on game development in the future,
and to attempt to implement a working version of a self play agent learning to play a Pokemon
battle. Originally designed Pokemon battle behavior is often suboptimal, getting stuck making
ineffective or incorrect choices, so training a self play model to learn the strategy and structure of
Pokemon battles from a clean slate would result in an organic agent that would outperform the
original behavior of the computer controlled agents. Though unsuccessful in my implementation,
this paper serves as a record of the exploration of this field, and a log of what worked and what
did not, in order to benefit any future person interested in the same topics.