Intelligent Virtual Patients for Training Clinical Skills

The article presents the design process of intelligent virtual human patients that are used for the enhancement of clinical skills. The description covers the development from conceptualization and character creation to technical components and the application in clinical research and training. The aim is to create believable social interactions with virtual agents that help the clinician to develop skills in symptom and ability assessment, diagnosis, interview techniques and interpersonal communication. The virtual patient fulfills the requirements of a standardized patient producing consistent, reliable and valid interactions in portraying symptoms and behaviour related to a specific clinical condition.

The Monotonicity Puzzle: An Experimental Investigation of Incentive Structures

Non-monotone incentive structures, which - according to theory - are able to induce optimal behavior, are often regarded as empirically less relevant for labor relationships. We compare the performance of a theoretically optimal non-monotone contract with a monotone one under controlled laboratory conditions. Implementing some features relevant to real-world employment relationships, our paper demonstrates that, in fact, the frequency of income-maximizing decisions made by agents is higher under the monotone contract. Although this observed behavior does not change the superiority of the non-monotone contract for principals, they do not choose this contract type in a significant way. This is what we call the monotonicity puzzle. Detailed investigations of decisions provide a clue for solving the puzzle and a possible explanation for the popularity of monotone contracts.