Evolution of an obstetrics and gynecology interprofessional simulation-based education session for medical and nursing students.

Simulation and Objective Structured Clinical Examination assessment of learners can teach clinical skills proficiency in a safe environment without risk to patients. Interprofessional simulation-based education (IPSE) contributes to a transformation in students' understanding of teamwork and professional roles. Long term outcomes for stimulation and IPSE sessions, are less well studied. We hypothesized that a progressive interprofessional education simulation program incorporating both faculty and interprofessional student collaboration would improve medical students' knowledge retention, comfort with procedural skills, positive teamwork and respectful interaction between students.An Obstetrics and Gynecology IPSE for medical and nursing students (NS) was developed in collaboration between a school of medicine and a school of nursing from 2014 to 2017. By 2017, content includedFrom 2014 to 2016, medical students completed attitude, knowledge, and perception surveys both pre and immediately post simulation, at 4 months, and 8 months. In 2017; all students completed self-assessments and received faculty-assessments.The program trained 443 medical and 136 NS. Medical students' knowledge, comfort, and interest increased significantly post simulation. Outcome scores decreased but were still significantly improved at 4 months but nearly dissipated by 8 months. There were no significant differences between medical and NS self-assessment or faculty-assessment scores regarding IUD insertion, cervical examination, or contraception quiz scores. Medical students' birth simulation self-assessment versus faculty-assessment scores were 8.6 vs 8.9, P < .001.Simulation improved students' short-term medical knowledge, comfort, and perception with some long-term persistence at 4-8 months. Medical and NS learned obstetrics and gynecology skills in a collaborative environment and in role-specific situations. Medical students had the opportunity to learn from NS. Positive teamwork and respectful interaction occurred between the students.

A Professional Development Workshop to Facilitate Self-Forgiveness.

BACKGROUND: Evidence suggests that forgiving one's self, others, and events improves relationships and self-esteem; reduces anxiety, depression, and stress; lowers blood pressure; improves cardiovascular health; and boosts immune function. OBJECTIVE: We determined the efficacy of a workshop to facilitate forgiveness in medical education professionals. METHODS: A 1-hour self-forgiveness workshop conducted by 4 facilitators was presented at a medical education conference in 2018. The workshop included a didactic presentation on forgiveness and Internal Family Systems, small group discussion on self-forgiveness concepts, a 15-minute guided imagery audio meditation on self-forgiveness, and postintervention small group discussion. The 18-item Heartland Forgiveness Scale (HFS), which measures forgiveness for self, others, and situations, was completed preintervention and postintervention (score range, 18-126). RESULTS: There were 91 participants, including graduate medical education managers and directors (61%), deans/clerkship directors (19%), and academic faculty/others (20%). Participants were from the South (20%), West (17%), Midwest (31%), and Northeast (32%) US regions. Baseline HFS scores showed that 53% were forgiving, 47% were neutral, and no participants had unforgiving tendencies. Total HFS score significantly increased (90.31 pre versus 95.7 post, P = .013), with significant increases in forgiveness of self (53% pre versus 73% post; P = .012; odds ratio = 2.47) and forgiveness of others (49% pre versus 69% post; P = .020; odds ratio = 2.3). Preintervention group discussion topics focused on guilt, shame, and barriers to forgiving, while postintervention discussions centered on challenges and benefits. CONCLUSIONS: A brief guided meditation intervention with focused discussions was feasible and improved the immediate tendency to forgive.

QSARpy: A new flexible algorithm to generate QSAR models based on dissimilarities. The log Kow case study.

Several methods exist to develop QSAR models automatically. Some are based on indices of the presence of atoms, other on the most similar compounds, other on molecular descriptors. Here we introduce QSARpy v1.0, a new QSAR modeling tool based on a different approach: the dissimilarity. This tool fragments the molecules of the training set to extract fragments that can be associated to a difference in the property/activity value, called modulators. If the target molecule share part of the structure with a molecule of the training set and differences can be explained with one or more modulators, the property/activity value of the molecule of the training set is adjusted using the value associated to the modulator(s). This tool is tested here on the n-octanol/water partition coefficient (Kow, usually expressed in logarithmic units as log Kow). It is a key parameter in risk assessment since it is a measure of hydrophobicity. Its wide spread use makes these estimation methods very useful to reduce testing costs. Using QSARpy v1.0, we obtained a new model to predict log Kow with accurate performance (RMSE 0.43 and R2 0.94 for the external test set), comparing favorably with other programs. QSARpy is freely available on request.

Autonomic Nervous System Team-Based Learning Module.

INTRODUCTION: The team-based learning (TBL) instructional strategy promotes learning and retention, enhances student engagement, allows for a deeper understanding of foundational and applied concepts, and helps students' develop lifelong learning skills. The autonomic nervous system (ANS) TBL was created for first-year medical students in the Neuroscience 1 course at Oakland University William Beaumont School of Medicine. METHODS: The module covered the pathophysiology of ANS-related diseases and therapeutic agents that impact ANS function. By the conclusion of the module, students were able to diagnose different disease processes of the ANS, identify potential complications, and formulate appropriate management strategies. Four faculty members used backward design to create the ANS TBL. The preparatory assignment included reviewing content from previous didactic lectures and consolidating key information in provided tables. Key concepts were evaluated with readiness assurance tests. All application exercises adhered to the 4 S's. RESULTS: Over the course of 2 years, the class averages for the individual readiness assurance test were 79.8% and 87.6%. The class averages for the team readiness assurance test and application exercises were similar across both years. Course evaluations revealed that students found the TBL relevant and valuable. DISCUSSION: Similar TBL modules available on MedEdPORTAL are not integrated to include different aspects of the basic and clinical sciences. This ANS TBL was used to help students integrate several essential concepts, including neuroanatomy, neurophysiology, neuropharmacology, and clinical neurology. Students were very enthusiastic and engaged throughout the ANS TBL as it contained relevant case-based scenarios with questions that were meaningful for clinical practice.

A new in silico classification model for ready biodegradability, based on molecular fragments.

Regulations such as the European REACH (Registration, Evaluation, Authorization and restriction of Chemicals) often require chemicals to be evaluated for ready biodegradability, to assess the potential risk for environmental and human health. Because not all chemicals can be tested, there is an increasing demand for tools for quick and inexpensive biodegradability screening, such as computer-based (in silico) theoretical models. We developed an in silico model starting from a dataset of 728 chemicals with ready biodegradability data (MITI-test Ministry of International Trade and Industry). We used the novel software SARpy to automatically extract, through a structural fragmentation process, a set of substructures statistically related to ready biodegradability. Then, we analysed these substructures in order to build some general rules. The model consists of a rule-set made up of the combination of the statistically relevant fragments and of the expert-based rules. The model gives good statistical performance with 92%, 82% and 76% accuracy on the training, test and external set respectively. These results are comparable with other in silico models like BIOWIN developed by the United States Environmental Protection Agency (EPA); moreover this new model includes an easily understandable explanation.

An open source multistep model to predict mutagenicity from statistical analysis and relevant structural alerts.

BACKGROUND: Mutagenicity is the capability of a substance to cause genetic mutations. This property is of high public concern because it has a close relationship with carcinogenicity and potentially with reproductive toxicity. Experimentally, mutagenicity can be assessed by the Ames test on Salmonella with an estimated experimental reproducibility of 85%; this intrinsic limitation of the in vitro test, along with the need for faster and cheaper alternatives, opens the road to other types of assessment methods, such as in silico structure-activity prediction models.A widely used method checks for the presence of known structural alerts for mutagenicity. However the presence of such alerts alone is not a definitive method to prove the mutagenicity of a compound towards Salmonella, since other parts of the molecule can influence and potentially change the classification. Hence statistically based methods will be proposed, with the final objective to obtain a cascade of modeling steps with custom-made properties, such as the reduction of false negatives. RESULTS: A cascade model has been developed and validated on a large public set of molecular structures and their associated Salmonella mutagenicity outcome. The first step consists in the derivation of a statistical model and mutagenicity prediction, followed by further checks for specific structural alerts in the "safe" subset of the prediction outcome space. In terms of accuracy (i.e., overall correct predictions of both negative and positives), the obtained model approached the 85% reproducibility of the experimental mutagenicity Ames test. CONCLUSIONS: The model and the documentation for regulatory purposes are freely available on the CAESAR website. The input is simply a file of molecular structures and the output is the classification result.

[Social anxieties in a clinical sample]. / Soziale Angste in einer klinischen Population.

Under the label of social phobia a complex of ailments was introduced into the syndromal diagnostic classification system of ICD-10 and DSM-IV, which is characterized by fear of embarrassing and humiliating experiences in relation to other persons. According to our experiences, however, social phobias and other problems in interpersonal relations are not yet paid the clinical attention that these problems deserve, when the severity of impairments subjects affected by social phobias suffer from is taken into account. There is a considerable lack of research of the psychodynamic aspects of social phobia as well. For this reason, we studied the frequency and extent of social anxieties in a sample of patients requiring psychiatric-psychotherapeutic inpatient treatment suffering from social anxieties (N = 930). This sample was compared to another sample of patients without social anxieties. We applied standardized diagnostic and psychometric instruments in order to collect information about anamnestic and social data as well as data about symptom severity, interpersonal impairments and comorbid disorders. The results do not only show the high frequency of social anxieties (45 %), but also the severe impairments in various domains of personal functioning of patients suffering from social anxieties compared to the patients without severe social anxieties. According to our clinical experiences and to the results presented here, the construct of social phobia as it is currently used in the psychiatric classification systems is an syndromal additive description that falls short of a form of suffering that is characterized by the facts that it is interwoven with the complete social existence of an affected person. For this reason, the term social phobia should be replaced by the more appropriate term of social anxiety.