There is growing recognition of the important role menstrual health plays in achieving health, education, and gender equity. Yet, stigmatisation and taboo remain present and negative emotions like fear and shame dominate the narrative when speaking about periods. This paper analyses how formal and informal menstrual education is received in Spain, to understand the role of menstrual health literacy in the way menstruation is experienced, and to identify what information would be useful to integrate into formal menstrual education. An online survey with more than 4000 participants (aged between 14 and 80, both people who will/do/have previously menstruate/d and those who do not menstruate) was conducted. Data was gathered using the digital platform Typeform, descriptive and inferential statistical analyses were performed with SPSS software and qualitative data was thematically analysed using Nvivo. Many participants declared not having received sufficient information on menstruation prior to menarche, particularly about how to physically manage it. Furthermore, negative emotions like shame, worry, and fear were recurrently reported to describe menarche; this has not changed between generations. Interestingly, we saw an increase in stress and sadness with an increase in perceived knowledge of the reproductive role of menstruation. We did observe a reduction in negative emotions when people who menstruate perceived they had sufficient information on how to manage their first bleeding. It is recommended that menstrual education beyond reproductive biology, particularly including how to physically manage periods, is integrated into school curricula. Menstrual education of everyone – including those who do not menstruate—can improve how periods are experienced in Spain.

In this paper a new approach to prioritize project portfolio in an efficient and reliable way is presented. The research methodology is based on a combination of a synthesis of the literature across the diverse fields of project management, project alignment, multicriteria decision methods and a parallel analysis of an industrial case study. The paper introduces a rigorous methodology with acceptable complexity which seeks to assist managers of the National Electricity Corporation of Venezuela (Corpoelec) in their yearly resources´ assignment on their projects portfolio. The aim being to determine the degree of alignment of each project to corporate strategy based on the judgments of a group of experts on the expected contribution of the projects to the business strategic objectives. The model presented can be used both as a descriptive and a prescriptive model. The approach presented uses project prioritization based on the multi-criteria decisionmaking technique called Analytic Network Process. Thus the corporate strategic objectives will be used as prioritization criteria to obtain the Relative Alignment Index (RAI).

When elaborating models in ANP, there are two key activities in the process: identify the relationships and weight the relationships to obtain the unweighted and weighted supermatrixes. Habitually this information is avalaible from experts, to those that it is necessary to ask. So, is very interesting build appropriates questionnaires to extract the information that they posses. These questionnaires should be on printed paper for several reasons: the expert doesn't have time to respond in a work session and it should be facilitated so that he gives it to us once answered, to have a font of tracing the data, etc. In big network models, once identified the correct form of asking, elaborate the questionnaires manually is a heavy and arduous task that doesn't contribute value to the decisionmaking process. In this article we show up an application that reads the files of the software Superdecisions, and it elaborates automatically the questionnaires to define the relationships and the questionnaires to prioritize the existing relationships.

This paper presents an analysis to simplify a complex model, based on the Analytic Network Process (ANP); to select photovoltaic (PV) solar power projects. These projects follow a long management and execution process from plant site selection to plant start-up. As a consequence, there are many risks of time delays and even of project stoppage. In a previous work a top manager of an important Spanish company decided on the best PV project (from four alternative projects) to invest based on risk minimization, using a complex ANP model (54 elements grouped into different clusters). This model needs to be simplified in order to solve similar selection problems in future. To identify which risks have to be eliminated from the original model is a difficult task. In this work two ways for doing this identification are proposed: in the fist way we select the 25 more important risks obtained by the original ANP model; in the second way we asked the decision maker to select the 25 risks that he considers have to be included in the future selection problems. The differences between both models are analyzed. In both cases the original ANP model, including its influences between elements of the network, has been simplified using Superdecisions software.