The impact of empathy on burnout in medical students: new findings

Introduction: Research on medical students has shown they are at a higher risk for burnout and that this burnout may become more prevalent as they advance in medical school. The literature, thus far, has not explored the construct of ,emotional empathy and whether this can impact burnout in medical students. Objective: To understand the relationship between empathy (Empathic Concern [EC] and Personal Distress [PD]) and burnout in medical students. Method: Five successive classes of medical students enrolled at a new medical school were given the Maslach Burnout Inventory and Davis’ Interpersonal Reactivity Index over the course of three successive years (n = 353). Two dimensions of empathy were evaluated to determine if they have an impact on three dimensions of burnout (Emotional Exhaustion/EE, Depersonalization/DP, Personal Accomplishment/PA). Results: data was analyzed using a linear mixed model for each of the three components of burnout based on gender, age, year in medical school, and two types of empathy: EC, and PD. Conclusion: It was discovered that students with high levels of EC had statistically lower scores of burnout over time while students with high levels of PD empathy showed statistically higher scores of burnout over three years. Implications for these findings are discussed.     

Parkinson’s Disease: Patients’ Knowledge,Attitudes, and Interest in Genetic Counseling

The objective of this study was to assess the genetics knowledge of patients with Parkinson’s disease (PD), and to explore their attitudes on genetic testing and interest in genetic counseling. We surveyed 158 patients from the University of Maryland Parkinson’s Disease and Movement Disorders Center. Patients averaged a score of 63% on general genetics knowledge and 73% on PD genetics knowledge. Participants had an overall positive attitude toward genetic testing: 80% believed that the use of genetic tests among people should be promoted, and 83% would undertake genetic test for PD if it was available. Patients reported a high interest to discuss the benefits, risks, and impacts of genetic testing for PD (mean sum score?=?26, range?=?9–35), and 43% patients expressed interest in meeting with a genetic counselor. Multivariate regression analysis showed that patients who had more positive attitudes toward genetic testing for PD were more interested in meeting with a genetic counselor (β?=?0.6, p?<?0.001). This study is the first to demonstrate an interest in genetic counseling among patients with PD. Our findings demonstrate a new niche for genetic counselors to support patients in clarifying gaps or misconceptions in knowledge about PD genetics as well as the possible risks, benefits, and limitations of genetic testing.     

Zukunftsperspektiven sexualforensischer Psychotherapie

There is a controversial discussion on to what extent sexual forensic psychotherapy has a positive influence on the legal probation of sexually delinquent people. From this the question arises on how treatment with a perspective for success could be structured. This article assumes that such a perspective can only succeed through close cooperation between science and psychotherapeutic practice. Through the analysis of a methodologically elaborate study, considerations on the motivation and the influence of empirically ascertained risk factors are developed and each placed in relation to scientific and therapeutic practice. In this way various problems are tackled, which range from insufficiently described interventions via too little therapeutic flexibility up to limitations in the scientific evaluation. Finally, possible barriers for the development of such a perspective are discussed and the connection to the so-called risk-need-responsivity (RNR) model is explored.     

Automated Item Generation with Recurrent Neural Networks

Utilizing technology for automated item generation is not a new idea. However, test items used in commercial testing programs or in research are still predominantly written by humans, in most cases by content experts or professional item writers. Human experts are a limited resource and testing agencies incur high costs in the process of continuous renewal of item banks to sustain testing programs. Using algorithms instead holds the promise of providing unlimited resources for this crucial part of assessment development. The approach presented here deviates in several ways from previous attempts to solve this problem. In the past, automatic item generation relied either on generating clones of narrowly defined item types such as those found in language free intelligence tests (e.g., Raven’s progressive matrices) or on an extensive analysis of task components and derivation of schemata to produce items with pre-specified variability that are hoped to have predictable levels of difficulty. It is somewhat unlikely that researchers utilizing these previous approaches would look at the proposed approach with favor; however, recent applications of machine learning show success in solving tasks that seemed impossible for machines not too long ago. The proposed approach uses deep learning to implement probabilistic language models, not unlike what Google brain and Amazon Alexa use for language processing and generation.     

形而上学及其当代命运——A.F.科赫教授访谈

A.F.科赫教授因其对康德与德国观念论(尤其是黑格尔)的深入研究而著名,此外他非常熟悉分析哲学与实用主义的当代成果。这使他能够以一种不同于其前辈诠释者的方式来理解德国哲学,并以一种完全不同于布兰顿和麦克道威尔这两位当代著名的分析哲学家的方式对大西洋两岸的两种不同的哲学传统进行让人瞩目的融合。从科赫教授身上我们可以看到,一个在欧陆哲学传统中成长起来的哲学家如何吸收和消化分析哲学的成果并尝试建立起一种新的思想方式。     

Determinants of Scanpath Regularity in Reading

Scanpaths have played an important role in classic research on reading behavior. Nevertheless, they have largely been neglected in later research perhaps due to a lack of suitable analytical tools. Recently, von der Malsburg and Vasishth (2011) proposed a new measure for quantifying differences between scanpaths and demonstrated that this measure can recover effects that were missed with the traditional eyetracking measures. However, the sentences used in that study were difficult to process and scanpath effects accordingly strong. The purpose of the present study was to test the validity, sensitivity, and scope of applicability of the scanpath measure, using simple sentences that are typically read from left to right. We derived predictions for the regularity of scanpaths from the literature on oculomotor control, sentence processing, and cognitive aging and tested these predictions using the scanpath measure and a large database of eye movements. All predictions were confirmed: Sentences with short words and syntactically more difficult sentences elicited more irregular scanpaths. Also, older readers produced more irregular scanpaths than younger readers. In addition, we found an effect that was not reported earlier: Syntax had a smaller influence on the eye movements of older readers than on those of young readers. We discuss this interaction of syntactic parsing cost with age in terms of shifts in processing strategies and a decline of executive control as readers age. Overall, our results demonstrate the validity and sensitivity of the scanpath measure and thus establish it as a productive and versatile tool for reading research.     

A general proof of consistency of heuristic classification for cognitive diagnosis models

The Asymptotic Classification Theory of Cognitive Diagnosis (Chiu et al., 2009, Psychometrika, 74, 633–665) determined the conditions that cognitive diagnosis models must satisfy so that the correct assignment of examinees to proficiency classes is guaranteed when non‐parametric classification methods are used. These conditions have only been proven for the Deterministic Input Noisy Output AND gate model. For other cognitive diagnosis models, no theoretical legitimization exists for using non‐parametric classification techniques for assigning examinees to proficiency classes. The specific statistical properties of different cognitive diagnosis models require tailored proofs of the conditions of the Asymptotic Classification Theory of Cognitive Diagnosis for each individual model – a tedious undertaking in light of the numerous models presented in the literature. In this paper a different way is presented to address this task. The unified mathematical framework of general cognitive diagnosis models is used as a theoretical basis for a general proof that under mild regularity conditions any cognitive diagnosis model is covered by the Asymptotic Classification Theory of Cognitive Diagnosis.