BUSCADOR RECOLECTA

Assessing chronic pain in dogs has been greatly favoured by the development of Owner-Reported Outcome Measures. Among them, the Liverpool Osteoarthritis in Dogs (LOAD) has been widely used for this purpose. Most of these tools have been written in English and its use by non-English natives requires not only translation but also linguistic validation for use by veterinarians and owners. For its use, the LOAD has not undergone translation into Spanish and the objective was to generate a linguistically validated Spanish translation of the LOAD. Following the World Health Organization and the International Society for Pharmacoeconomics and Outcomes Research published guidelines, the original LOAD English version underwent analysis and translation by two native linguists proficient in the target language. Both translations were then reviewed by a third native linguist to identify potential disparities and establish a cohesive translation (reconciliation). Subsequently, an independent linguist, fluent in both English and the target language, conducted the back-translation. Finally, the research team compared the original and back-translated versions to pinpoint and resolve any significant differences. Following the creation of the translated version, a cognitive debriefing was conducted to assess the questionnaire within the target population. A total of 89 surveys were distributed to dog owners of varying ages, genders, and socio-economic backgrounds. Although there were some suggestions and comments, and some adjustments were made, all respondents found the survey to be clear, achieving a linguistic validation of the Spanish LOAD.

Twitter dataset for a research on the 2015 Spanish General Election. The tweets were obtained through the Twitter API's Search function since November 2 to December 21, 2015. Three criteria for filtering tweets were established: two general terms linked to the elections ("#20D", "20-D"); the name and usernames of the four main parties (PP, PSOE, Podemos and Ciudadanos), and the name and usernames of the four candidates from those parties. The research assessed the tweet's issue according to Patterson (1980)'s typology for evaluating political mediatisation. The dataset contains three files: the unlabelled collection of the 15.8 million tweet ids obtained through the API, the annotated sample of the 3,117 tweet ids for assessing the issue via machine learning, and the readme.txt file. It is recommended to open the file from a text editor or through a script. The id_str must be handled as a string. If the file is open from Excel, the id_str will be interpreted as a number, and then converted into a float, losing information in this transformation