Analysis of the Concept of Obstetric Violence: Scoping Review Protocol.

(1) Background: Obstetric violence has been highlighted in the political and social agenda of several countries. Efforts have been made to create policies to humanize obstetric care, guarantee the rights of pregnant women and respond to this form of violence. The lack of consensus on the appropriate terminology to name and define the behaviours that constitute obstetric violence, hinders this process. (2) Objective: To analyse the concept of obstetric violence related to assistance to women during labor. (3) Methodology: Scoping review protocol, according to the Joanna Briggs Institute method. The search will be performed on EBSCOhost Research Platform, PubMed, Virtual Health Library and SciVerse Scopus databases. The Open Scientific Repository of Portugal will also be considered. All types of studies, published in the last 10 years, in English, Spanish and Portuguese languages, constitute inclusion criteria. Studies of women experiencing labor, in a hospital setting, that address the dimensions of the concept of obstetric violence will be reviewed. (4) Discussion: The results will serve as a basis for identifying the appropriate terminology of the concept of obstetric violence, in order to direct future research with interest in the problem.

Extraction of Phenolic Compounds with Antioxidant Activity from Strawberries: Modelling with Artificial Neural Networks (ANNs).

This research study focuses on the evaluation of the total phenolic compounds (TPC) and antioxidant activity (AOA) of strawberries according to different experimental extraction conditions by applying the Artificial Neural Networks (ANNs) technique. The experimental data were applied to train ANNs using feed- and cascade-forward backpropagation models with Levenberg-Marquardt (LM) and Bayesian Regulation (BR) algorithms. Three independent variables (solvent concentration, volume/mass ratio and extraction time) were used as ANN inputs, whereas the three variables of total phenolic compounds, DPPH and ABTS antioxidant activities were considered as ANN outputs. The results demonstrate that the best cascade- and feed-forward backpropagation topologies of ANNs for the prediction of total phenolic compounds and DPPH and ABTS antioxidant activity factors were the 3-9-1, 3-4-4-1 and 3-13-10-1 structures, with the training algorithms of trainlm, trainbr, trainlm and threshold functions of tansig-purelin, tansig-tansig-tansig and purelin-tansig-tansig, respectively. The best R2 values for the predication of total phenolic compounds and DPPH and ABTS antioxidant activity factors were 0.9806 (MSE = 0.0047), 0.9651 (MSE = 0.0035) and 0.9756 (MSE = 0.00286), respectively. According to the comparison of ANNs, the results showed that the cascade-forward backpropagation network showed better performance than the feed-forward backpropagation network for predicting the TPC, and the FFBP network, in predicting the DPPH and ABTS antioxidant activity factors, had more precision than the cascade-forward backpropagation network. The ANN technique is a potential method for estimating targeted total phenolic compounds and the antioxidant activity of strawberries.

The Eating Motivations Scale (EATMOT): Development and Validation by Means of Confirmatory Factor Analysis (CFA) and Structural Equation Modelling (SEM).

INTRODUCTION: The objective was to develop and validate an instrument that measures different determinants of people's food choices and simultaneously accounts for a variety of factors: health, emotions, price and availability, society and culture, environment and politics, and marketing and advertising. METHODS: This is a cross-sectional study focusing on food choice determinants. It was carried out in 16 countries in 2017 and 2018. This study included 11,960 volunteer adult participants from different countries. The data was validated using Confirmatory Factor Analysis (CFA) and Structural Equation Modelling (SEM). RESULTS: Validation using CFA with SEM revealed that multi-factor modelling produced first- and second-order models that could be used to define the EATMOT scale, the first presenting better fitting indices, with the goodness-of-fit and comparative-fit indices very close to 1, as well as root-mean-square-error-of-approximation, root-mean-square-residual and standardised-root-mean-square-residual at practically zero. CONCLUSION: The validated EATMOT scale guarantees confidence in the information obtained through this instrument, and can be used in future studies to better understand food choice determinants in different geographical areas and help plan strategies to improve healthy eating patterns and diminish the burden of non-communicable diseases.

Influence of sociodemographic factors on eating motivations - modelling through artificial neural networks (ANN).

This study aimed at investigating the influence of some sociodemographic factors on the eating motivations. A longitudinal study was carried conducted with 11960 participants from 16 countries. Data analysis included t-test for independent samples or ANOVA, and neural network models were also created, to relate the input and output variables. Results showed that factors like age, marital status, country, living environment, level of education or professional area significantly influenced all of the studied types of eating motivations. Neural networks modelling indicated variability in the food choices, but identifying some trends, for example the strongest positive factor determining health motivations was age, while for emotional motivations was living environment, and for economic and availability motivations was gender. On the other hand, country revealed a high positive influence for the social and cultural as well as for environmental and political and also for marketing and commercial motivations.

Perceptions Towards Healthy Diet of the Portuguese According to Area of Work or Studies.

INTRODUCTION: A healthy diet is crucial for the maintenance of health. Therefore, the aim of this work is to evaluate the perceptions towards a healthy diet among the participants with work or studies in areas related to diet and nutrition and those who did not. METHODS: Anonymous questionnaire data was collected in a cross-sectional study on a non-probabilistic sample of 902 participants living in Portugal. RESULTS: The results showed that the participants' perceptions were, in general, compliant with a healthy diet. However, significant differences were found between gender (p=0.004), between the different civil state groups (p=0.016), between the participants who were responsible for buying their own food and those who were not and also regarding the living environment. The variable area of work or studies also showed significant differences (p=0.001), so that people who had work or studies related to agriculture obtained a higher score. Regarding this variable, the mean values of nutrition and agriculture areas were not statistically different between them, but were statistically different from the mean values of psychology and health areas. The participants who had work or studies in areas showing diet and nutrition-related issues achieved a higher mean score (0.72±0.35) when compared to the participants who did not (0.58±0.30). CONCLUSION: However, despite the results, it is important to continue developing campaigns that better communicate nutritional aspects, so that people can increase their knowledge on this subject.