Students as peer tutors and mentors

Time is limited and there are many benefits, for students and their teachers, when learners become more deeply involved in the education and support of their peers. We describe a training programme that helped students develop the skills and insight they need to fulfill these roles. In the three-day workshop we modeled a coherent educational approach. We used a wide variety of instructional methods, including large and small group activities as well as an Objective Structured Teaching Exercise (OSTE). At the end of the workshop each participant had a profound understanding of the role and potential of a mentor and felt more comfortable about extending and developing their teaching. In health professions education in particular the role of the mentor is to help students cross barriers and boundaries to become new members of their chosen profession. 14.02.2014 | David Taylor (Liverpool), Elizabeth K. Kachur (New York), Angelika Hofhansl & Richard März (Vienna

Gender Awareness bei Medizinstudierenden der Medizinischen Universität Wien: Eine empirische Analyse von Geschlechtersensibilität und Geschlechterstereotypisierungen

'Gender Awareness' und seine Komponenten 'Gender Sensitivity' und 'Gender Role Ideology' beziehen sich auf ein sensibles, offenes und bewusstes Handeln gegenüber den Bedürfnissen von Patientinnen und Patienten auf biologischer, sozialer und psychologischer Ebene. Gemeinsamkeiten und Unterschiede der Geschlechter sollen berücksichtigt und Geschlechterstereotypisierungen vermieden werden. Mithilfe eines validierten Fragebogens 'Nijmegen Gender Awareness in Medicine' (N-GAMS) wurden die Einstellungen der Studierende im ersten Semester als auch der Studierenden im zwölften Semester an der Medizinischen Universität (MedUni) Wien erhoben. Insgesamt lässt sich eine ausgeprägte Gendersensibilität bei Frauen und Männern in beiden Semestergruppen feststellen. In der vorliegenden Erhebung zeigte sich, dass der Faktor Gender RoleIdeologytowardspatients (Geschlechtersterotypisierungen gegenüber PatientInnen) stärker ausgeprägt war, als der Faktor Gender RoleIdeologytowardsdoctors (Geschlechterstereotypisierungen gegenüber Ärztinnen und Ärzten). Das scheint ein Hinweis darauf zu sein, dass Studierende dem Geschlecht der PatientInnen mehr Einfluss zuschreiben als dem Geschlecht der Ärztinnen und Ärzte.In order to improve the quality of health care for both men and women, awareness of sex and gender in illness and health is essential. Implementation of sex and gender aspects in medical education is therefore needed. The aim of this study is to survey the students’ attitudes to gender and gender stereotyping at the Medical University of Vienna.583 first year medical students and 110 final year medical students completed the validated "Nijmegen Gender Awareness in Medicine" Scale. The questionnaire consists of the subscales gender sensitivity, gender role ideology towards patients and gender role ideology towards doctors. A pronounced sensitivity towards gender issues appeared in both sexes, which is comparable to other international studies. The factor Gender Role Ideology towards Patients was more pronounced than the factor Gender Role Ideology towards Doctors. This seems to be an indication that the students ascribe more influence to the gender of the patient than the gender of the doctors

Effects of soil organic matter properties and microbial community composition on enzyme activities in cryoturbated arctic soils

Enzyme-mediated decomposition of soil organic matter (SOM) is controlled, amongst other factors, by organic matter properties and by the microbial decomposer community present. Since microbial community composition and SOM properties are often interrelated and both change with soil depth, the drivers of enzymatic decomposition are hard to dissect. We investigated soils from three regions in the Siberian Arctic, where carbon rich topsoil material has been incorporated into the subsoil (cryoturbation). We took advantage of this subduction to test if SOM properties shape microbial community composition, and to identify controls of both on enzyme activities. We found that microbial community composition (estimated by phospholipid fatty acid analysis), was similar in cryoturbated material and in surrounding subsoil, although carbon and nitrogen contents were similar in cryoturbated material and topsoils. This suggests that the microbial community in cryoturbated material was not well adapted to SOM properties. We also measured three potential enzyme activities (cellobiohydrolase, leucine-amino-peptidase and phenoloxidase) and used structural equation models (SEMs) to identify direct and indirect drivers of the three enzyme activities. The models included microbial community composition, carbon and nitrogen contents, clay content, water content, and pH. Models for regular horizons, excluding cryoturbated material, showed that all enzyme activities were mainly controlled by carbon or nitrogen. Microbial community composition had no effect. In contrast, models for cryoturbated material showed that enzyme activities were also related to microbial community composition. The additional control of microbial community composition could have restrained enzyme activities and furthermore decomposition in general. The functional decoupling of SOM properties and microbial community composition might thus be one of the reasons for low decomposition rates and the persistence of 400 Gt carbon stored in cryoturbated material

Properties of the microbial community.

<p>Total amount of PLFAs, fungi∶bacteria ratios and statistical results for the first three principal components derived from a PCA with relative abundances of all PLFA biomarkers. Values are mean values (± standard error) over all sites and for each horizon per site. Letters in parentheses indicate significantly different (P<0.05) groups between horizons derived from ANOVA and Tukey-HSD tests.</p

Climate and Vegetation.

<p>Climate data are derived from WorldClim database including mean annual temperature (MAT), maximum temperature of the warmest month (Tmax), minimum temperature of the coldest month (Tmin) mean annual range in temperature (MART) and mean annual precipitation (MAP).</p

Direct and indirect drivers of extracellular enzyme activities.

<p>Structural equation models for extracellular enzyme activities, cellobiohydrolase (CBH; a, d), leucine-amino-peptidase (LAP; b, e) and phenoloxidase (POX; c,f). Graphs on the left show regular soil (organic topsoil, mineral topsoil, mineral subsoil), right panel shows cryoturbated material. Black boxes and arrows indicate significant factors and paths. Boxes and arrows in grey were removed from the model because either the paths (arrows) were not significant, or the factors (boxes) had no direct or indirect effect on the enzyme activity. The boxes with C, N and Clay are the contents of organic carbon, nitrogen, and clay. Microbial biomass (MicBM) was calculated as total amount of PLFAs. PC1, PC2 and PC3 are the first three axes of PCAs with relative abundances of all PLFAs. PCAs for regular soil and cryoturbated material have been done individually. Arrow width indicates the strength of the effect and reflects the scaled estimates, which are also given as the numbers beside the respective arrows. The numbers below the boxes with the respective enzymes show R² and indicate how much of the variance in enzyme activity is explained by the model.</p

Differences in microbial community composition in different horizons in arctic soils.

<p>Principal component analysis (PCA) with relative abundances of all PFLA biomarkers. Colors indicate different horizon categories: organic topsoil (O) is dark grey, mineral topsoil (A) is light grey, mineral subsoil (B) is white, and cryoturbated material (J) is black. Symbols indicate sites: circles Cherskiy, diamonds Logata, and triangles Tazovsky. Symbols are the mean values of the coordinates for the individual categories, derived from the PCA with individual samples (n = 101). Error bars are SE. Colors of PLFA markers indicate general markers (grey), gram-positive markers (red), gram-negative markers (orange), bacterial markers (blue) and fungal markers (green).</p