Are female students in general and nursing students more ready for teamwork and interprofessional collaboration in healthcare?

<p>Abstract</p> <p>Background</p> <p>Interprofessional Education (IPE) is now spreading worldwide and many universities are now including IPE in their curricula. The aim of this study was to investigate whether or not such student characteristics as gender, previous working experience in healthcare, educational progress and features of the learning environment, such as educational programmes and curriculum design, have an impact on their open-mindedness about co-operation with other professions.</p> <p>Methods</p> <p>Medical and nursing students at two Swedish universities were invited to fill in the Readiness for Interprofessional Learning Scale (RIPLS). Totally, 955 students were invited and 70.2% (n = 670) participated in the study. A factor analysis of the RIPLS revealed four item groupings (factors) for our empirical data, but only one had sufficient internal consistency. This factor was labelled "Team Player".</p> <p>Results</p> <p>Regardless of the educational programme, female students were more positive to teamwork than male students. Nursing students in general displayed more positive beliefs about teamwork and collaboration than medical students. Exposure to different interprofessional curricula and previous exposure to interprofessional education were only to a minor extent associated with a positive attitude towards teamwork. Educational progress did not seem to influence these beliefs.</p> <p>Conclusions</p> <p>The establishment of interprofessional teamwork is a major challenge for modern healthcare. This study indicates some directions for more successful interprofessional education. Efforts should be directed at informing particularly male medical students about the need for teamwork in modern healthcare systems. The results also imply that study of other factors, such as the student's personality, is needed for fully understanding readiness for teamwork and interprofessional collaboration in healthcare. We also believe that the RIPL Scale still can be further adjusted.</p

The Practice of Thresholds: Autonomy in Clinical Education Explored Through Variation Theory and the Threshold Concepts Framework

This paper demonstrates a practical dimension to the discussion about threshold concepts. Threshold concepts have thus far mostly been acknowledged to elucidate learning processes mainly connected to theoretical concepts. By exploring situations that prompted experiences of autonomy and authenticity in clinical learning, findings showed how a practical experience could have the same power to transform thinking and identity as theoretical thresholds and serve as a trigger for transformational learning, therefore making the discussion about ‘practical thresholds' or thresholds in practice possible. The present study explores situations that prompted autonomy and authenticity, and offers context for and substance to these situations by adopting variation theory and the threshold concept framework. In order to learn more about situations that prompt experiences of autonomy and authenticity, and create prerequisites for such experiences, this paper examines how students discern and interpret these situations by analysing them through variation theory and the threshold concept framework

Common Genetic Variation And Age at Onset Of Anorexia Nervosa

Background Genetics and biology may influence the age at onset of anorexia nervosa (AN). The aims of this study were to determine whether common genetic variation contributes to AN age at onset and to investigate the genetic associations between age at onset of AN and age at menarche. Methods A secondary analysis of the Psychiatric Genomics Consortium genome-wide association study (GWAS) of AN was performed which included 9,335 cases and 31,981 screened controls, all from European ancestries. We conducted GWASs of age at onset, early-onset AN (< 13 years), and typical-onset AN, and genetic correlation, genetic risk score, and Mendelian randomization analyses. Results Two loci were genome-wide significant in the typical-onset AN GWAS. Heritability estimates (SNP-h2) were 0.01-0.04 for age at onset, 0.16-0.25 for early-onset AN, and 0.17-0.25 for typical-onset AN. Early- and typical-onset AN showed distinct genetic correlation patterns with putative risk factors for AN. Specifically, early-onset AN was significantly genetically correlated with younger age at menarche, and typical-onset AN was significantly negatively genetically correlated with anthropometric traits. Genetic risk scores for age at onset and early-onset AN estimated from independent GWASs significantly predicted age at onset. Mendelian randomization analysis suggested a causal link between younger age at menarche and early-onset AN. Conclusions Our results provide evidence consistent with a common variant genetic basis for age at onset and implicate biological pathways regulating menarche and reproduction.Peer reviewe

Prediction of voice aperiodicity based on spectral representations in HMM speech synthesis

In hidden Markov model-based speech synthesis, speech is typically parameterized using source-filter decomposition. A widely used analysis/synthesis framework, STRAIGHT, decomposes the speech waveform into a framewise spectral envelope and a mixed mode excitation signal. Inclusion of an aperiodicity measure in the model enables synthesis also for signals that are not purely voiced or unvoiced. In the traditional approach employing hidden Markov modeling and decision tree-based clustering, the connection between speech spectrum and aperiodicities is not taken into account. In this paper, we take advantage of this dependency and predict voice aperiodicities afterwards based on synthetic spectral representations. The evaluations carried out for English data confirm that the proposed approach is able to provide prediction accuracy that is comparable to the traditional approach. Copyright © 2011 ISCA

Using robust Viterbi algorithm and HMM-modeling in unit selection TTS to replace units of poor quality

In hidden Markov model-based unit selection synthesis, the benefits of both unit selection and statistical parametric speech synthesis are combined. However, conventional Viterbi algorithm is forced to do a selection also when no suitable units are available. This can drift the search and decrease the overall quality. Consequently, we propose to use robust Viterbi algorithm that can simultaneously detect bad units and select the best sequence. The unsuitable units are replaced using hidden Markov model-based synthesis. Evaluations indicate that the use of robust Viterbi algorithm combined with unit replacement increases the quality compared to the traditional algorithm. © 2010 ISCA

COSIMA data analysis using multivariate techniques

We describe how to use multivariate analysis of complex TOF-SIMS (time-of-flight secondary ion mass spectrometry) spectra by introducing the method of random projections. The technique allows us to do full clustering and classification of the measured mass spectra. In this paper we use the tool for classification purposes. The presentation describes calibration experiments of 19 minerals on Ag and Au substrates using positive mode ion spectra. The discrimination between individual minerals gives a cross-validation Cohen κ for classification of typically about 80%. We intend to use the method as a fast tool to deduce a qualitative similarity of measurements