Bullying in Adolescents Practising Sport: A Structural Model Approach.

This article aims to analyse the relationship between the bullying aggressor and bullying victim profile related to practising or not practising sport in adolescents living in southern Spain. The research includes male and female participants aged between 12 and 16 years in different secondary schools in the provinces of Andalusia, Ceuta and Melilla in the period between February 2022 and June 2022. The study aims to extend the existing scientific, theoretical and empirical knowledge on the influence of playing sport or not on disruptive bullying attitudes in adolescents. To this end, two initial hypotheses were designed; the first hypothesises that bullying victim behaviours are associated with future bullying aggressor behaviours when practising sport; and the second states that victim behaviours are associated with future bullying aggressor behaviours when not practising sport. To verify them, SPSS software was used for the preliminary analysis of the scale and sociodemographic profile. Additionally, the study is based on structural equation modelling methodology and variance-based methods employing SmartPLS v3.3 software. The results show the importance of sport or physical activity to reduce the chances of carrying out bullying actions on other peers and/or classmates. Therefore, it is considered necessary to prevent bullying in the classroom by implementing sports intervention programmes in educational centres.

Analysis of the coexistence of gaming and viewing activities in Twitch users and their relationship with pathological gaming: a multilayer perceptron approach.

The enormous expansion of the video game sector, driven by the emergence of live video game streaming platforms and the professionalisation of this hobby through e-sports, has spurred interest in research on the relationships with potential adverse effects derived from cumulative use. This study explores the co-occurrence of the consumption and viewing of video games, based on an analysis of the motivations for using these services, the perceived positive uses, and the gamer profile. To that end, a multilayer perceptron artificial neural network is developed and tested on a sample of 970 video game users. The results show that the variables with a significant influence on pathological gaming are the motivation of a sense of belonging to the different platforms, as well as the positive uses relating to making friends and the possibility of making this hobby a profession. Furthermore, the individual effects of each of the variables have been estimated. The results indicate that the social component linked to the positive perception of making new friends and the self-perceived level as a gamer have been identified as possible predictors, when it comes to a clinical assessment of the adverse effects. Conversely, the variables age and following specific streamers are found to play a role in reducing potential negative effects.

Dataset for holiday rentals' daily rate pricing in a cultural tourism destination.

This data article describes a holiday rental dataset from a medium-size cultural city destination. Daily rate and variables related to location, size, amenities, rating, and seasonality are highlighted as the main features. The data was extracted from Booking.com, legal registration of the accommodation (RTA) and Google Maps, among other sources. This dataset contains data from 665 holiday rentals offered as entire flat (rent per room was discarded), with a total of 1623 cases and 28 variables considered. Regarding data extraction, RTA is ordered by registration number, which is taken and, through a Google search with the following structure: "apartment registration no. + Booking + Seville", the holiday rental profile in Booking.com is found. Then, it is verified that both the address of the accommodation and the registration number match in RTA and Booking.com, proceeding with data extraction to a Microsoft Excel's file. Google Maps is used to determine the minutes spent walking from the accommodation to the spot of maximum tourist interest of the city. A price index based on the average price per square meter of real estate per district is also incorporated to the dataset, as well as a visual appeal rating made by the authors of every holiday rental based on its Booking.com photos profile. Only cases with complete data were considered. A statistics summary of all variables of the data collected is presented. This dataset can be used to develop an estimation model of daily prices of stay in holiday rentals through predetermined variables. Econometrics methodologies applied to this dataset can also allow testing which variables included affecting the composition of holiday rentals' daily rates and which not, as well as determining their respective influence on daily rates.