Neuromarketing Applied to Education. Analysis of face-to-face versus online teaching

[EN] The use of new technologies applied to e-learning has created a few issues related to the attention, as well as the improvement (or the lack) of learning. Thanks to the knowledge and technologies applied in neuromarketing, it has been proven that the levels of attention and commitment to learning, as well as the emotional intensity felt, are greater in a face-to-face classroom compared to a deferred broadcast of a class. Therefore, all this reconsiders a new field of study where distance education can be as effective as face-to-face education.[ES] El uso de las nuevas tecnologías aplicadas a la educación a distancia ha generado una serie de interrogantes respecto a la atención, así como el mejoramiento o no del aprendizaje. Gracias a los conocimientos y tecnologías aplicados en neuromarketing, se ha comprobado que los niveles de atención y compromiso con el aprendizaje, así como la intensidad emocional sentida, son mayores en un aula presencial frente a una retransmisión de una clase en diferido. Por lo que todo esto replantea un nuevo campo de estudio donde la educación a distancia pueda ser tan efectiva como la presencial.Bellido García, I.; Lomello, M.; Serrano Agudelo, D.; Olarte Valencia, MS.; Pérez Micharet, P.; Larios De Medrano Gutiérrez, A.; Gil Escobedo, J.... (2022). Neuromarketing Aplicado a la Educación. Análisis de la enseñanza presencial versus la enseñanza online. Editorial Universitat Politècnica de València. 1359-1373. https://doi.org/10.4995/INRED2022.2022.159171359137

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Collaborative intelligence and gamification for on-line malaria species differentiation

Abstract Background Current World Health Organization recommendations for the management of malaria include the need for a parasitological confirmation prior to triggering appropriate treatment. The use of rapid diagnostic tests (RDTs) for malaria has contributed to a better infection recognition and a more targeted treatment. Nevertheless, low-density infections and parasites that fail to produce HRP2 can cause false-negative RDT results. Microscopy has traditionally been the methodology most commonly used to quantify malaria and characterize the infecting species, but the wider use of this technique remains challenging, as it requires trained personnel and processing capacity. Objective In this study, the feasibility of an on-line system for remote malaria species identification and differentiation has been investigated by crowdsourcing the analysis of digitalized infected thin blood smears by non-expert observers using a mobile app. Methods An on-line videogame in which players learned how to differentiate the young trophozoite stage of the five Plasmodium species has been designed. Images were digitalized with a smartphone camera adapted to the ocular of a conventional light microscope. Images from infected red blood cells were cropped and puzzled into an on-line game. During the game, players had to decide the malaria species (Plasmodium falciparum, Plasmodium malariae, Plasmodium vivax, Plasmodium ovale, Plasmodium knowlesi) of the infected cells that were shown in the screen. After 2 months, each player’s decisions were analysed individually and collectively. Results On-line volunteers playing the game made more than 500,000 assessments for species differentiation. Statistically, when the choice of several players was combined (n > 25), they were able to significantly discriminate Plasmodium species, reaching a level of accuracy of 99% for all species combinations, except for P. knowlesi (80%). Non-expert decisions on which Plasmodium species was shown in the screen were made in less than 3 s. Conclusion These findings show that it is possible to train malaria-naïve non-experts to identify and differentiate malaria species in digitalized thin blood samples. Although the accuracy of a single player is not perfect, the combination of the responses of multiple casual gamers can achieve an accuracy that is within the range of the diagnostic accuracy made by a trained microscopist

Collaborative intelligence and gamification for on-line malaria species differentiation

Background: Current World Health Organization recommendations for the management of malaria include the need for a parasitological confrmation prior to triggering appropriate treatment. The use of rapid diagnostic tests (RDTs) for malaria has contributed to a better infection recognition and a more targeted treatment. Nevertheless, low-density infections and parasites that fail to produce HRP2 can cause false-negative RDT results. Microscopy has traditionally been the methodology most commonly used to quantify malaria and characterize the infecting species, but the wider use of this technique remains challenging, as it requires trained personnel and processing capacity. Objective: In this study, the feasibility of an on-line system for remote malaria species identifcation and diferentia‑ tion has been investigated by crowdsourcing the analysis of digitalized infected thin blood smears by non-expert observers using a mobile app. Methods: An on-line videogame in which players learned how to diferentiate the young trophozoite stage of the fve Plasmodium species has been designed. Images were digitalized with a smartphone camera adapted to the ocular of a conventional light microscope. Images from infected red blood cells were cropped and puzzled into an on-line game. During the game, players had to decide the malaria species (Plasmodium falciparum, Plasmodium malariae, Plasmodium vivax, Plasmodium ovale, Plasmodium knowlesi) of the infected cells that were shown in the screen. After 2 months, each player’s decisions were analysed individually and collectively. Results: On-line volunteers playing the game made more than 500,000 assessments for species diferentiation. Statistically, when the choice of several players was combined (n>25), they were able to signifcantly discriminate Plasmodium species, reaching a level of accuracy of 99% for all species combinations, except for P. knowlesi (80%). Non-expert decisions on which Plasmodium species was shown in the screen were made in less than 3 s. Conclusion: These fndings show that it is possible to train malaria-naïve non-experts to identify and diferentiate malaria species in digitalized thin blood samples. Although the accuracy of a single player is not perfect, the combination of the responses of multiple casual gamers can achieve an accuracy that is within the range of the diagnostic accuracy made by a trained microscopist.Spanish Ministry of Economy and CompetitivenessSpanish Society of Hematology and HemotherapyUniversidad Politécnica de MadridMadrid Regional GovernmentSpain’s Science, Innovation & Universities MinistrySpanish Ministry of Economy, Industry and CompetitivenessEuropean Regional Development FundsAmazon Web ServicesFundación Renta CorporaciónAshokaDepto. de Bioquímica y Biología MolecularFac. de FarmaciaTRUEpu

The immunogenetic diversity of the HLA system in Mexico correlates with underlying population genetic structure

International audienc

The immunogenetic diversity of the HLA system in Mexico correlates with underlying population genetic structure

International audienc