Exploring the validity and reliability of a questionnaire for evaluating virtual patient design with a special emphasis on fostering clinical reasoning

Background: The design of Virtual Patients (VPs) is essential. So far there are no validated evaluation instruments for VP design published. Summary of work: We examined three sources of validity evidence of an instrument to be filled out by students aimed at measuring the quality of VPs with a special emphasis on fostering clinical reasoning: (1) Content was examined based on theory of clinical reasoning and an international VP expert team. (2) Response process was explored in think aloud pilot studies with students and content analysis of free text questions accompanying each item of the instrument. (3) Internal structure was assessed by confirmatory factor analysis (CFA) using 2547 student evaluations and reliability was examined utilizing generalizability analysis. Summary of results: Content analysis was supported by theory underlying Gruppen and Frohna’s clinical reasoning model on which the instrument is based and an international VP expert team. The pilot study and analysis of free text comments supported the validity of the instrument. The CFA indicated that a three factor model comprising 6 items showed a good fit with the data. Alpha coefficients per factor were 0,74 - 0,82. The findings of the generalizability studies indicated that 40-200 student responses are needed in order to obtain reliable data on one VP. Conclusions: The described instrument has the potential to provide faculty with reliable and valid information about VP design. Take-home messages: We present a short instrument which can be of help in evaluating the design of VPs.

Fuzzy Web Knowledge Aggregation, Representation, and Reasoning for Online Privacy and Reputation Management

A social Semantic Web empowers its users to have access to collective Web knowledge in a simple manner, and for that reason, controlling online privacy and reputation becomes increasingly important, and must be taken seriously. This chapter presents Fuzzy Cognitive Maps (FCM) as a vehicle for Web knowledge aggregation, representation, and reasoning. With this in mind, a conceptual framework for Web knowledge aggregation, representation, and reasoning is introduced along with a use case, in which the importance of investigative searching for online privacy and reputation is highlighted. Thereby it is demonstrated how a user can establish a positive online presence.

A Restriction-Centered Theory of Reasoning and Computation to materialize a Web 3.0

Researchers suggest that personalization on the Semantic Web adds up to a Web 3.0 eventually. In this Web, personalized agents process and thus generate the biggest share of information rather than humans. In the sense of emergent semantics, which supplements traditional formal semantics of the Semantic Web, this is well conceivable. An emergent Semantic Web underlying fuzzy grassroots ontology can be accomplished through inducing knowledge from users' common parlance in mutual Web 2.0 interactions [1]. These ontologies can also be matched against existing Semantic Web ontologies, to create comprehensive top-level ontologies. On the Web, if augmented with information in the form of restrictions andassociated reliability (Z-numbers) [2], this collection of fuzzy ontologies constitutes an important basis for an implementation of Zadeh's restriction-centered theory of reasoning and computation (RRC) [3]. By considering real world's fuzziness, RRC differs from traditional approaches because it can handle restrictions described in natural language. A restriction is an answer to a question of the value of a variable such as the duration of an appointment. In addition to mathematically well-defined answers, RRC can likewise deal with unprecisiated answers as "about one hour." Inspired by mental functions, it constitutes an important basis to leverage present-day Web efforts to a natural Web 3.0. Based on natural language information, RRC may be accomplished with Z-number calculation to achieve a personalized Web reasoning and computation. Finally, through Web agents' understanding of natural language, they can react to humans more intuitively and thus generate and process information.

Wirksamkeit des Programms "Reasoning and Rehabilitation Revised" für inhaftierte Frauen in der Schweiz - eine Erkundungsstudie

Hintergrund Bei dem revidierten Programm „Reasoning and Rehabilitation“ (R&R2) handelt es sich um einen gruppentherapeutischen Ansatz zur Behandlung spezifischer Probleme von Straftätern. Hier werden erstmals Effekte der deutschsprachigen Version für Mädchen und junge Frauen berichtet. Material und Methode Die Effekte des Gruppentrainings wurden bei 11 inhaftierten Frauen durch standardisierte Fragebogen erfasst. Hierbei interessierten Veränderungen sozial-interpersoneller, motivationaler, psychopathologischer und emotionsregulatorischer Merkmale. Zudem wurden die Zufriedenheit mit der Behandlung und der klinische Eindruck erhoben. Ergebnisse Die erfassten proximalen Effektmaße unterstützen überwiegend die Hypothese einer Wirksamkeit des R&R2 bei Frauen. Das Programm erwies sich als veränderungsinduzierend und wurde gut angenommen. Schlussfolgerung Die Ergebnisse dieser isolierten Evaluation des R&R2-Trainings bei Frauen weisen auf positive Veränderungen spezieller Problembereiche hin. Jedoch werden weiterführende Studien zum intra- und extramuralen Verhalten sowie distalen Rückfälligkeitsmaß benötigt.

Improving self-control by practicing logical reasoning

We tested the hypothesis that practicing logical reasoning can improve self-control. In an experimental training study (N = 49 undergraduates), for one week participants engaged in daily mental exercises with or without the requirement to practice logical reasoning. Participants in the logic group showed improvements in self-control, as revealed by anagram performance after a depleting self-control task. The benefits of the intervention were short-lived; participants in the two groups performed similarly just one week after the intervention had ended. We discuss the findings with respect to the strength model of self-control and consider possible benefits of regular cognitive challenges in education.

Exploring the validity and reliability of a questionnaire for evaluating virtual patient design with a special emphasis on fostering clinical reasoning

Background: Virtual patients (VPs) are increasingly used to train clinical reasoning. So far, no validated evaluation instruments for VP design are available. Aims: We examined the validity of an instrument for assessing the perception of VP design by learners. Methods: Three sources of validity evidence were examined: (i) Content was examined based on theory of clinical reasoning and an international VP expert team. (ii) The response process was explored in think-aloud pilot studies with medical students and in content analyses of free text questions accompanying each item of the instrument. (iii) Internal structure was assessed by exploratory factor analysis (EFA) and inter-rater reliability by generalizability analysis. Results: Content analysis was reasonably supported by the theoretical foundation and the VP expert team. The think-aloud studies and analysis of free text comments supported the validity of the instrument. In the EFA, using 2547 student evaluations of a total of 78 VPs, a three-factor model showed a reasonable fit with the data. At least 200 student responses are needed to obtain a reliable evaluation of a VP on all three factors. Conclusion: The instrument has the potential to provide valid information about VP design, provided that many responses per VP are available.

Predicting the onset of psychosis in patients at clinical high risk: practical guide to probabilistic prognostic reasoning

Prediction of psychosis in patients at clinical high risk (CHR) has become a mainstream focus of clinical and research interest worldwide. When using CHR instruments for clinical purposes, the predicted outcome is but only a probability; and, consequently, any therapeutic action following the assessment is based on probabilistic prognostic reasoning. Yet, probabilistic reasoning makes considerable demands on the clinicians. We provide here a scholarly practical guide summarising the key concepts to support clinicians with probabilistic prognostic reasoning in the CHR state. We review risk or cumulative incidence of psychosis in, person-time rate of psychosis, Kaplan-Meier estimates of psychosis risk, measures of prognostic accuracy, sensitivity and specificity in receiver operator characteristic curves, positive and negative predictive values, Bayes’ theorem, likelihood ratios, potentials and limits of real-life applications of prognostic probabilistic reasoning in the CHR state. Understanding basic measures used for prognostic probabilistic reasoning is a prerequisite for successfully implementing the early detection and prevention of psychosis in clinical practice. Future refinement of these measures for CHR patients may actually influence risk management, especially as regards initiating or withholding treatment.

Computer-based summative assessment of clinical reasoning in clerkships: A mixed-method comparison of key feature problems with case-based multiple choice questions

Background: It is yet unclear if there are differences between using electronic key feature problems (KFPs) or electronic case-based multiple choice questions (cbMCQ) for the assessment of clinical decision making. Summary of Work: Fifth year medical students were exposed to clerkships which ended with a summative exam. Assessment of knowledge per exam was done by 6-9 KFPs, 9-20 cbMCQ and 9-28 MC questions. Each KFP consisted of a case vignette and three key features (KF) using “long menu” as question format. We sought students’ perceptions of the KFPs and cbMCQs in focus groups (n of students=39). Furthermore statistical data of 11 exams (n of students=377) concerning the KFPs and (cb)MCQs were compared. Summary of Results: The analysis of the focus groups resulted in four themes reflecting students’ perceptions of KFPs and their comparison with (cb)MCQ: KFPs were perceived as (i) more realistic, (ii) more difficult, (iii) more motivating for the intense study of clinical reasoning than (cb)MCQ and (iv) showed an overall good acceptance when some preconditions are taken into account. The statistical analysis revealed that there was no difference in difficulty; however KFP showed a higher discrimination and reliability (G-coefficient) even when corrected for testing times. Correlation of the different exam parts was intermediate. Conclusions: Students perceived the KFPs as more motivating for the study of clinical reasoning. Statistically KFPs showed a higher discrimination and higher reliability than cbMCQs. Take-home messages: Including KFPs with long menu questions into summative clerkship exams seems to offer positive educational effects.

Desing and Validation of a Light Inference System to Support Embedded Context Reasoning

Embedded context management in resource-constrained devices (e.g. mobile phones, autonomous sensors or smart objects) imposes special requirements in terms of lightness for data modelling and reasoning. In this paper, we explore the state-of-the-art on data representation and reasoning tools for embedded mobile reasoning and propose a light inference system (LIS) aiming at simplifying embedded inference processes offering a set of functionalities to avoid redundancy in context management operations. The system is part of a service-oriented mobile software framework, conceived to facilitate the creation of context-aware applications—it decouples sensor data acquisition and context processing from the application logic. LIS, composed of several modules, encapsulates existing lightweight tools for ontology data management and rule-based reasoning, and it is ready to run on Java-enabled handheld devices. Data management and reasoning processes are designed to handle a general ontology that enables communication among framework components. Both the applications running on top of the framework and the framework components themselves can configure the rule and query sets in order to retrieve the information they need from LIS. In order to test LIS features in a real application scenario, an ‘Activity Monitor’ has been designed and implemented: a personal health-persuasive application that provides feedback on the user’s lifestyle, combining data from physical and virtual sensors. In this case of use, LIS is used to timely evaluate the user’s activity level, to decide on the convenience of triggering notifications and to determine the best interface or channel to deliver these context-aware alerts.d