T. Hashimoto, H. Nakane, Ryo Kurimoto, Hiroshi Kobayashi
{"title":"Medical interview training using depressed patient robot in psychiatric education","authors":"T. Hashimoto, H. Nakane, Ryo Kurimoto, Hiroshi Kobayashi","doi":"10.1109/RIISS.2014.7009172","DOIUrl":null,"url":null,"abstract":"This paper introduces a psychiatric patient robot that can be used for medical interview training in psychiatric education. The patient robot is developed based on an android robot technology. Medical interview training in psychiatric field is generally conducted by employing human simulated or standardized patient (SP) who is trained to reproduce a set of symptoms of intended mental disorder by veteran psychiatrists. But in the use of a healthy person as a SP there are some problems such as mental burden, time-consuming, the lack of human resources, and so forth. In contrast, the merit of the use of a patient robot is to offer standardized and reproducible interview training to psychiatric trainees. Furthermore, it is expected that psychiatric trainees are able to experience realistic medical interview as if they face to a real human SP by taking advantage of characteristics of android robots. As the first step, the patient robot was particularly designed to simulate a set of symptoms of unipolar depression, because it is a common mental disorder worldwide. The interview scenario, that is question and answer process between an interviewer and the patient robot, was prepared based on the “Structured Interview Guide for the Hamilton Depression Rating Scale (SIGH-D)” which is widely used for interview training and clinical studies. The medical interview training with patient robot was introduced in actual psychiatric education, and eight students participated and evaluated its educational effect.","PeriodicalId":270157,"journal":{"name":"2014 IEEE Symposium on Robotic Intelligence in Informationally Structured Space (RiiSS)","volume":"234 ","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE Symposium on Robotic Intelligence in Informationally Structured Space (RiiSS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RIISS.2014.7009172","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
This paper introduces a psychiatric patient robot that can be used for medical interview training in psychiatric education. The patient robot is developed based on an android robot technology. Medical interview training in psychiatric field is generally conducted by employing human simulated or standardized patient (SP) who is trained to reproduce a set of symptoms of intended mental disorder by veteran psychiatrists. But in the use of a healthy person as a SP there are some problems such as mental burden, time-consuming, the lack of human resources, and so forth. In contrast, the merit of the use of a patient robot is to offer standardized and reproducible interview training to psychiatric trainees. Furthermore, it is expected that psychiatric trainees are able to experience realistic medical interview as if they face to a real human SP by taking advantage of characteristics of android robots. As the first step, the patient robot was particularly designed to simulate a set of symptoms of unipolar depression, because it is a common mental disorder worldwide. The interview scenario, that is question and answer process between an interviewer and the patient robot, was prepared based on the “Structured Interview Guide for the Hamilton Depression Rating Scale (SIGH-D)” which is widely used for interview training and clinical studies. The medical interview training with patient robot was introduced in actual psychiatric education, and eight students participated and evaluated its educational effect.