Resultados de investigación

This dataset contains anonymised data collected from healthcare professionals who participated in a study evaluating the acceptability, usability, and perceived effectiveness of two personal protective equipment (PPE) training modalities during the COVID-19 pandemic: immersive virtual reality (IVR) training and conventional video-based training. Data were collected in a university hospital and five primary care centres in Catalonia, Spain, between January and December 2021. The dataset includes participants' demographic and professional characteristics, training modality received, healthcare setting, and responses to a post-intervention questionnaire assessing perceived safety and learning, usefulness and performance, satisfaction and training experience, and usability. The data support analyses comparing perceptions of PPE training across professional groups, age categories, healthcare settings, and educational approaches. The post-intervention questionnaire was specifically developed for the present study and included demographic and professional variables, previous experience with PPE and virtual reality training, and perceptions of training modalities. The instrument comprised 15 quantitative items organised into four domains: Safety and Learning (3 items), Usefulness and Performance (4 items), Satisfaction and Experience (4 items), and Usability (4 items). Responses were rated on a 10-point scale, with higher scores indicating more favourable perceptions of the training intervention

Reflectance data (Vis-NIR and NIR region) for single oat kernels is provided. Also, deoxynivalenol and zearalenone concentration of that kernels and if they are above (U) or under (L) the legal limit for oats is indicated.

This repository contains the source code and processed datasets for a deep learning framework designed to multivariate event-based time series classification applied to monitor police firearm usage via embedded sensor fusion. The software features a custom-built Recurrent Neural Network (RNN) library implemented in pure Python/NumPy, enabling the training of lightweight models (Vanilla RNN, GRU, MGRU) suitable for deployment on low-resource embedded systems. The framework utilizes a multi-objective architecture to process simultaneous inputs from piezoelectric (vibration) and photoelectric (light) sensors. Key capabilities include "Zoneout" regularization, custom Backpropagation Through Time (BPTT), and export functionality to C-style headers for microcontroller integration. The included datasets consist of pre-processed, labelled time-series vectors representing real-world firearm manipulations (shots, reloads, and handling events)

This data examines perceptions of profiguration, intergenerational relations and sustainability through a series of interviews. Participants, primarily local people from an anonymized territory, were asked about their views on life in the territory and its connection to language, culture, and sustainability. They were also asked for their opinions on the development of intergenerational relationships within this context, as well as on technical aspects of organizational bodies and institutions in the area. Overall, intergenerational relationships are perceived as positive and supported by local traditions and culture. Additionally, participants expressed growing awareness of the importance of social development, sustainability of the territory and gender equality.

This dataset contains responses from a quasi-experimental health education study conducted among adults aged 18 years or older from different municipalities in the Segrià region (Catalonia, Spain). Data were collected to evaluate the effectiveness of the "Rethinking COVID-19" intervention in relation to knowledge, preventive practices, and emotional coping. The dataset includes pre- and post-intervention questionnaire data from an intervention group and pre-intervention data from a non-equivalent control group. Variables cover basic sociodemographic characteristics, hand hygiene knowledge and practices, healthy habits related to COVID-19, and self-reported emotions and coping strategies. A post-intervention satisfaction questionnaire, including Likert-scale items and a Net Promoter Score, is also included for the intervention group. Data are fully anonymised, contain no direct identifiers, and consist mainly of categorical and ordinal variables with explicit coding.

This dataset contains data from an observational study conducted among undergraduate nursing students at a public university in Spain during the 2025–2026 academic year. Data were collected to examine the association between students’ knowledge, attitudes, and practices regarding Advance Care Planning, including Planning Anticipated Decisions and Advance Directives, and their person-centred care orientation in critical health situations. The dataset includes self-administered questionnaire responses covering sociodemographic characteristics and validated scale measures, specifically the PROPAD-pro scale and the Patient–Practitioner Orientation Scale (PPOS). Variables are mainly categorical and ordinal, including Likert-scale items. All data were anonymised, contain no direct identifiers, and were collected using an online questionnaire platform.

Referencias incluidas en una revisión sistemática de estudios empíricos sobre la violencia digital contra las mujeres con muestras de los principales países del sur de Europa. Las referencias registradas corresponden a los estudios incluidos en una revisión sistemática realizada conforme a la declaración PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses). Se incluyeron exclusivamente estudios empíricos publicados entre 2015 y 2025 que abordaran de manera explícita la violencia digital contra las mujeres. Los trabajos seleccionados cuentan con muestras procedentes de España, Portugal, Italia o Grecia, con independencia del país de afiliación de las autoras o autores. Estas referencias constituyen la base empírica de la revisión.

Conjunto de datos cuantitativo de corte transversal compuesto por 200 registros y 51 variables, construido a partir de un cuestionario dirigido a profesorado. El dataset integra variables de identificación y perfil profesional, formación académica, especialización en enseñanza de lenguas, experiencia docente, contextos institucionales, competencia lingüística y experiencia de inmersión, junto con bloques de evaluación sobre enfoques didácticos, motivación intrínseca, motivación extrínseca, factores institucionales, clima de aula, autoeficacia docente y engagement. Su estructura permite analizar de forma empírica la relación entre condiciones profesionales, percepciones del contexto educativo y dimensiones psicoeducativas asociadas a la motivación para la enseñanza del inglés como lengua extranjera.

High-throughput targeted lipidomic data obtained from biological replicates (n=12) of four cellular models of Alexander disease using U-87 MG non-transfected and GFP-GFAP expressing cells (WT, R239C, R239G, R79C, and E373K variants).

To analyse changes in nursing students’ clinical decision-making, self-confidence, and anxiety in a telenursing context following a simulation-based video consultation intervention. There is a dataset containing the results of nursing students’ responses. The collected data include sociodemographic and academic information, baseline indicators of digital competence and innovative capacity, and repeated measurements of clinical decision-making–related self-confidence and anxiety assessed using the Nursing Anxiety and Self-Confidence with Clinical Decision Making (NASC-CDM) scale. Data were collected before and after the educational intervention in both an intervention group and a comparison group. In the intervention group, additional data on satisfaction and perceived learning were collected using the Student Satisfaction and Self-Confidence in Learning Scale. This dataset contains survey responses from 115 nursing students at two Spanish universities collected during the 2024-2025 academic year. The data matrix includes sociodemographic variables, digital competence indicators, and detailed scores from the NASC-CDM scales (27 self-confidence items and 27 anxiety items) and the SCLS (13 items on learning satisfaction). The data structure reflects a quasi-experimental design featuring pre-test and post-test measurements related to a video consultation simulation intervention