Knowledge, perceptions and attitudes on the sexuality of nursing students and teachers

Introduction: The personal attitudes regarding specific aspects of sexuality are of interest to practices of personal concern, as they are to practices inserted in professional roles. General attitudes towards sexuality and sexual health were evaluated. Objectives: To describe the perceptions and attitudes of students and nursing teachers about sexuality. Methods: We used a mixed methods design with a sequential strategy: QUAN→qual of descriptive and explanatory type. 646 students and teachers participated. The Sexual Attitudes Scale (EAS) of Hendrick & Hendrick (Alferes, 1999) and Attitude Scale Address Sexual and Reproductive Health (EAFSSR) of Nemčić et al (Abreu, 2008) were used. Results: There are significant differences in the level of knowledge about sexuality depending on the sample (χ2KW (2)=18.271; p=.000): students of 1st year have lower levels. The profile of the four dimensions of EAS per sample is identical in all 3 samples, having responsibility the highest average value. In subscales EAFSSR per sample and sex there are significant diferences (p<.05) for all samples and uniform pattern was noted: females have higher median values, indicating that they have more favorable attitudes towards sexual health. Conclusions: Sexual attitudes reveal a multidimensional structure based in the female identity, that shows responsibility towards family planning and sexual education, as well as towards individual self-care regarding the body and sexual and reproductive health. An attitudinal profile by gender emerges, accentuating the polarity between male and female. The importance of the training process in nursing following the personal and social development of students is corroborated.

Age and Gender Identification using Stacking for Classification⋆ Notebook for PAN at CLEF 2016

This paper presents our approach of identifying the profile of an unknown user based on the activities of known users. The aim of author profiling task of PAN@CLEF 2016 is cross-genre identification of the gender and age of an unknown user. This means training the system using the behavior of different users from one social media platform and identifying the profile of other user on some different platform. Instead of using single classifier to build the system we used a combination of different classifiers, also known as stacking. This approach allowed us explore the strength of all the classifiers and minimize the bias or error enforced by a single classifier.