Learning styles vary among general surgery residents: analysis of 12 years of data

PURPOSE: Understanding the learning styles of individuals may assist in the tailoring of an educational program to optimize learning. General surgery faculty and residents have been characterized previously as having a tendency toward particular learning styles. We seek to understand better the learning styles of general surgery residents and differences that may exist within the population. METHODS: The Kolb Learning Style Inventory was administered yearly to general surgery residents at the University of Cincinnati from 1994 to 2006. This tool allows characterization of learning styles into 4 groups: converging, accommodating, assimilating, and diverging. The converging learning style involves education by actively solving problems. The accommodating learning style uses emotion and interpersonal relationships. The assimilating learning style learns by abstract logic. The diverging learning style learns best by observation. Chi-square analysis and analysis of variance were performed to determine significance. RESULTS: Surveys from 1994 to 2006 (91 residents, 325 responses) were analyzed. The prevalent learning style was converging (185, 57%), followed by assimilating (58, 18%), accommodating (44, 14%), and diverging (38, 12%). At the PGY 1 and 2 levels, male and female residents differed in learning style, with the accommodating learning style being relatively more frequent in women and assimilating learning style more frequent in men (Table 1, p < or = 0.001, chi-square test). Interestingly, learning style did not seem to change with advancing PGY level within the program, which suggests that individual learning styles may be constant throughout residency training. If a resident's learning style changed, it tended to be to converging. In addition, no relation exists between learning style and participation in dedicated basic science training or performance on the ABSIT/SBSE. CONCLUSIONS: Our data suggests that learning style differs between male and female general surgery residents but not with PGY level or ABSIT/SBSE performance. A greater understanding of individual learning styles may allow more refinement and tailoring of surgical programs.

Maximising the impact of research: the NCCR North-South approach: Fourth NCCR North-South Report on Effectiveness

Interest is growing in the impact that science can have on reducing poverty in the global South. If we understand impact as the “demonstrable contribution that excellent research makes to society and the economy”, the concept encompasses a variety of contributions of research-related knowledge and skills that benefit people and the environment. One reason for the growing interest in impact in this context is research councils’ increasing focus on documenting the social and environmental benefits of science, as indicated by the above quotation from the British research councils. Another reason is that research funding agencies from the private and public sectors are now more interested in social innovations for solving problems on the ground. Research can indeed influence policymakers’ views, policy development, funding patterns, and implementation or practice. This is promising for those who would like to improve – and prove – the influence research can have on policy and practice. It is also of importance for better understanding the intended and unintended effects of research. This report presents the NCCR North-South approach to increasing the impact of development-oriented research. It explains how we can maximise our impact and how we can assess whether our efforts have worked, based on six case studies from around the world. The report is of interest to all researchers who wish to respond to policy and practice from their point of view and who are keen on publicising their evidence. It is also relevant to those who teach how to maximise research impact.

Global Optimization with Sparse and Local Gaussian Process Models

We present a novel surrogate model-based global optimization framework allowing a large number of function evaluations. The method, called SpLEGO, is based on a multi-scale expected improvement (EI) framework relying on both sparse and local Gaussian process (GP) models. First, a bi-objective approach relying on a global sparse GP model is used to determine potential next sampling regions. Local GP models are then constructed within each selected region. The method subsequently employs the standard expected improvement criterion to deal with the exploration-exploitation trade-off within selected local models, leading to a decision on where to perform the next function evaluation(s). The potential of our approach is demonstrated using the so-called Sparse Pseudo-input GP as a global model. The algorithm is tested on four benchmark problems, whose number of starting points ranges from 102 to 104. Our results show that SpLEGO is effective and capable of solving problems with large number of starting points, and it even provides significant advantages when compared with state-of-the-art EI algorithms.

[Investigation of abortions and other animal health problems in relation to vaccination against Bluetongue virus in 2009]

By the distribution of a questionnaire between all Swiss cattle practitioners it was possible to investigate abortions and other animal health problems related to Bluetongue vaccination 2009. The questionnaire helped to obtain plausibility and timely relation of the reported disorders. 58 abortions in cattle and different herd health problems could be examined. Because there is no possibility to show that a vaccination itself leads to an abortion the results of proven causes of abortions prior and after Bluetongue vaccination were compared regarding their diagnosis. Due to the fact that diagnosis and solving rate of abortions did not differ before and after vaccination, the vaccination itself cannot be responsible for the abortions. Evaluation of different herd health problems showed that Bluetongue vaccination was not responsible for these disorders which often existed already prior to vaccination. Herd health problems generally have multifactorial causes what makes it difficult to asses the effect of Bluetongue vaccination in some cases.