To assess first-year gastroenterology fellows’ ability to address difficult interpersonal situations in the workplace using objective structured clinical examinations (OSCE).METHODSTwo OSCEs (“distracted care team”...To assess first-year gastroenterology fellows’ ability to address difficult interpersonal situations in the workplace using objective structured clinical examinations (OSCE).METHODSTwo OSCEs (“distracted care team” and “frazzled intern”) were created to assess response to disruptive behavior. In case 1, a fellow used a colonoscopy simulator while interacting with a standardized patient (SP), nurse, and attending physician all played by actors. The nurse and attending were instructed to display specific disruptive behavior and disregard the fellow unless requested to stop the disruptive behavior and focus on the patient and procedure. In case 2, the fellow was to calm an intern managing a patient with massive gastrointestinal bleeding. The objective in both scenarios was to assess the fellows’ ability to perform their duties while managing the disruptive behavior displayed by the actor. The SPs used checklists to rate fellows’ performances. The fellows completed a self-assessment survey.RESULTSTwelve fellows from four gastrointestinal fellowship training programs participated in the OSCE. In the “distracted care team” case, one-third of the fellows interrupted the conflict and refocused attention to the patient. Half of the fellows were able to display professionalism despite the heated discussion nearby. Fellows scored lowest in the interprofessionalism portion of post-OSCE surveys, measuring their ability to handle the conflict. In the “frazzled intern” case, 68% of fellows were able to establish a calm and professional relationship with the SP. Despite this success, only half of the fellows were successfully communicate a plan to the SP and only a third scored “well done” in a domain that focused on allowing the intern to think through the case with the fellow’s guidance.CONCLUSIONFellows must receive training on how to approach disruptive behavior. OSCEs are a tool that can assess fellow skills and set a culture for open discussion.展开更多
The facial expression recognition systn using the Ariaboost based on the Split Rectangle feature is proposed in this paper. This system provides more various featmes in increasing speed and accuracy than the Haarolike...The facial expression recognition systn using the Ariaboost based on the Split Rectangle feature is proposed in this paper. This system provides more various featmes in increasing speed and accuracy than the Haarolike featrue of Viola, which is commonly used for the Adaboost training algorithm. The Split Rectangle feature uses the nmsk-like shape composed with 2 independent rectangles, instead of using mask-like shape of Haar-like feature, which is composed of 2 --4 adhered rectangles of Viola. Split Rectangle feature has less di- verged operation than the Haar-like feaze. It also requires less oper- ation because the stun of pixels requires ordy two rectangles. Split Rectangle feature provides various and fast features to the Adaboost, which produrces the strong classifier with increased accuracy and speed. In the experiment, the system had 5.92 ms performance speed and 84 %--94 % accuracy by leaming 5 facial expressions, neutral, happiness, sadness, anger and surprise with the use of the Adaboost based on the Split Rectangle feature.展开更多
文摘To assess first-year gastroenterology fellows’ ability to address difficult interpersonal situations in the workplace using objective structured clinical examinations (OSCE).METHODSTwo OSCEs (“distracted care team” and “frazzled intern”) were created to assess response to disruptive behavior. In case 1, a fellow used a colonoscopy simulator while interacting with a standardized patient (SP), nurse, and attending physician all played by actors. The nurse and attending were instructed to display specific disruptive behavior and disregard the fellow unless requested to stop the disruptive behavior and focus on the patient and procedure. In case 2, the fellow was to calm an intern managing a patient with massive gastrointestinal bleeding. The objective in both scenarios was to assess the fellows’ ability to perform their duties while managing the disruptive behavior displayed by the actor. The SPs used checklists to rate fellows’ performances. The fellows completed a self-assessment survey.RESULTSTwelve fellows from four gastrointestinal fellowship training programs participated in the OSCE. In the “distracted care team” case, one-third of the fellows interrupted the conflict and refocused attention to the patient. Half of the fellows were able to display professionalism despite the heated discussion nearby. Fellows scored lowest in the interprofessionalism portion of post-OSCE surveys, measuring their ability to handle the conflict. In the “frazzled intern” case, 68% of fellows were able to establish a calm and professional relationship with the SP. Despite this success, only half of the fellows were successfully communicate a plan to the SP and only a third scored “well done” in a domain that focused on allowing the intern to think through the case with the fellow’s guidance.CONCLUSIONFellows must receive training on how to approach disruptive behavior. OSCEs are a tool that can assess fellow skills and set a culture for open discussion.
基金supported by the Brain Korea 21 Project in2010,the MKE(The Ministry of Knowledge Economy),Koreathe ITRC(Information Technology Research Center)support programsupervised by the NIPA(National ITIndustry Promotion Agency)(NI-PA-2010-(C1090-1021-0010))
文摘The facial expression recognition systn using the Ariaboost based on the Split Rectangle feature is proposed in this paper. This system provides more various featmes in increasing speed and accuracy than the Haarolike featrue of Viola, which is commonly used for the Adaboost training algorithm. The Split Rectangle feature uses the nmsk-like shape composed with 2 independent rectangles, instead of using mask-like shape of Haar-like feature, which is composed of 2 --4 adhered rectangles of Viola. Split Rectangle feature has less di- verged operation than the Haar-like feaze. It also requires less oper- ation because the stun of pixels requires ordy two rectangles. Split Rectangle feature provides various and fast features to the Adaboost, which produrces the strong classifier with increased accuracy and speed. In the experiment, the system had 5.92 ms performance speed and 84 %--94 % accuracy by leaming 5 facial expressions, neutral, happiness, sadness, anger and surprise with the use of the Adaboost based on the Split Rectangle feature.
