Innocampus Explora: Nuevas formas de comunicar ciencia

[EN] Innocampus Explora aims to show the students of the Burjassot-Paterna campus of the Universitat de València how the different scientific degrees are interrelated. To do this we propose activities in which students and teachers work together to cover the interdisciplinary nature of science, both in everyday and professional issues. Throughout this course the activities developed relate to new ways to communicate science. With the development of this project we contribute to a transversal quality education for all the participating students.[ES] Innocampus Explora tiene por objetivo mostrar a los estudiantes del campus de Burjassot-Paterna de la Universitat de València cómo los diferentes grados científicos están interrelacionados. Para ello proponemos actividades en las que estudiantes y profesores trabajen conjuntamente para abarcar la interdisciplinariedad de la ciencia, tanto en temas cotidianos como profesionales. A lo largo de este curso las actividades desarrolladas se relacionan con las nuevas formas de comunicar ciencia. Con el desarrollo de este proyecto contribuimos a una formación transversal de calidad para todos los estudiantes participantes.Moros Gregorio, J.; Rodrigo Martínez, P.; Torres Piedras, C.; Montoya Martínez, L.; Peña Peña, J.; Pla Díaz, M.; Galarza Jiménez, P.... (2019). Innocampus Explora: Nuevas formas de comunicar ciencia. En IN-RED 2019. V Congreso de Innovación Educativa y Docencia en Red. Editorial Universitat Politècnica de València. 814-823. https://doi.org/10.4995/INRED2019.2019.10449OCS81482

Professional counseling in women with serious mental illness: achieving a shift toward a more effective contraceptive method

Objectives Mental disorders in reproductive-aged women have significant implications for the risk of unintended pregnancies. The objective of this study is to assess the professional counseling in clinical practice based on motivational interview in women with serious mental illness (SMI) in order to achieve a change to a more effective contraceptive method. Study design A prospective observational cohort study (2012–2017) was conducted in a convenience sample of women with severe–moderate psychiatric disorders (n = 91). Information related to psychiatric health, contraceptive use, sexual and reproductive health and socio-demographics was collected. To assess the variation in the contraceptive method, follow-up visits were planned before and after medical counseling. All participants underwent an evidence-based individual motivational interview for contraception counseling. A multivariate logistic model was carried out to identify the factors involved in changing to a more effective contraceptive method. Results After evidence-based counseling, 51.6% of participants changed their contraceptive method to a more effective one. This change was associated with gender violence (β coefficient = 1.58, p value = .006). The relation between changing to a more effective contraceptive method and both previous abortions and having children was also positive, although the coefficients did not reach statistical significance. Conclusions Evidence-based contraception counseling in clinical practice, based on an adapted protocol to patients with SMI, has shown, in this study, to be adequate to promote the shift to more effective contraceptive methods, avoiding the need of daily compliance in this population. Gender violence has been significantly associated with the shift to very high effectiveness methods as well as previous abortions and having children, not significantly

Strategic procedure in three stages for the selection of variables to obtain balanced results in public health research

Multidisciplinary research in public health is approached using methods from many scientific disciplines. One of the main characteristics of this type of research is dealing with large data sets. Classic statistical variable selection methods, known as “screen and clean”, and used in a single-step, select the variables with greater explanatory weight in the model. These methods, commonly used in public health research, may induce masking and multicollinearity, excluding relevant variables for the experts in each discipline and skewing the result. Some specific techniques are used to solve this problem, such as penalized regressions and Bayesian statistics, they offer more balanced results among subsets of variables, but with less restrictive selection thresholds. Using a combination of classical methods, a three-step procedure is proposed in this manuscript, capturing the relevant variables of each scientific discipline, minimizing the selection of variables in each of them and obtaining a balanced distribution that explains most of the variability. This procedure was applied on a dataset from a public health research. Comparing the results with the single-step methods, the proposed method shows a greater reduction in the number of variables, as well as a balanced distribution among the scientific disciplines associated with the response variable. We propose an innovative procedure for variable selection and apply it to our dataset. Furthermore, we compare the new method with the classic single-step procedures