Person: Pérez Pérez, Teresa
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First Name
Teresa
Last Name
Pérez Pérez
Affiliation
Universidad Complutense de Madrid
Faculty / Institute
Estudios estadísticos
Department
Estadística y Ciencia de los Datos
Area
Estadística e Investigación Operativa
Identifiers
5 results
Search Results
Now showing 1 - 5 of 5
Item Mental health and drug use in college students: should we take action?(Journal of Affective Disorders, 2023) Pérez Pérez, Teresa; Pardo Llorente, M. Del Carmen; Cabellos, Yolanda; Peressini Álvarez, Melina; Ureña Vacas, Isabel María; Serrano López, Dolores Remedios; González Burgos, Elena MaríaBackground College students are vulnerable to suffering from anxiety and depression. Moreover, mental disorders can contribute to drug consumption or inappropriate use of prescribed drugs. Studies on this topic in Spanish college students are limited. This work analyses anxiety and depression and psychoactive drug intake pattern in the post-COVID era in college students. Methods An online survey was conducted among college students from UCM (Spain). The survey collected data including demographic, academic student perception, GAD-7 and PHQ-9 scales, and psychoactive substances consumption. Results A total of 6,798 students were included; 44.1% (CI95%: 42.9 to 45.3) showed symptoms of severe anxiety and 46.5% (CI95%: 45.4 to 47.8) symptoms of severe or moderately severe depression. The perception of these symptoms did not change after returning to face-to-face university classes in the post-COVID19 era. Despite the high percentage of cases with clear symptoms of anxiety and depression, most students never had a diagnosis of mental illnesses [anxiety 69.2% (CI95%: 68.1 to 70.3) and depression 78.1% (CI95%: 77.1 to 79.1)]. Regarding psychoactive substances, valerian, melatonin, diazepam, and lorazepam were the most consumed. The most worrying issue was the consumption of diazepam, 10.8% (CI95%: 9.8 to 11.8), and lorazepam, 7.7% (CI95%: 6.9 to 8.6) without medical prescription. Amongst illicit drugs, cannabis is the most consumed. Limitations The study was based on an online survey. Conclusions The high prevalence of anxiety and depression aligned with poor medical diagnosis and high intake of psychoactive drugs should not be underestimated. University policies should be implemented to improve the well-being of students.- Project number: PIMCD144/23-24
Item Uso del cine y otros medios audiovisuales como herramienta en la docencia de Matemáticas y Estadística(2024) Cabrera Gómez, Gloria; Gamboa Pérez, María; Mateo Navas, Luis Miguel; Monge Romojaro; Mireya; Pérez Pérez, Teresa; Pons Bordería, María Jesús; Susi García, María Del Rosario; Taipe Hidalgo, Diana Paulina; Cabrera Gómez, GloriaEl presente proyecto de innovación docente tiene como objetivo utilizar imágenes, podcasts, vídeos, canciones, cortes de películas, series de televisión, prensa digital, programa de radio o mensajes en redes sociales, en los que aparezcan contenidos matemáticos o estadísticos e insertarlos de manera dinámica en el desarrollo de la clase con el fin de mejorar la motivación, atención y aprendizaje. - Project number: 4
Item Gamificación en el aula con Kahoot! en la Facultad de Estudios Estadísticos(2020) Calviño Martínez, Aída; Rapado Vicente, María Eva; Peressini Álvarez, Melina; Cabrera Gómez, Gloria; Cáceres García, Inés María; Alonso Revenga, Juana María; Latorre Muñoz, María De La Concepción; Amador Pacheco, Julia; Rodríguez Cánovas, María Belén; Rodríguez Palanquex, María Cruz; Cintas Del Rio, María Del Rosario; Susi García, María Del Rosario; López Herrero, María Jesús; Alcón Giménez, María José; Pérez Pérez, Teresa; Gamboa Pérez, MaríaMemoria final del proyecto de innovación docente titulado: "Gamificación en el aula con Kahoot! en la Facultad de Estudios Estadísticos" Item Impact of selection for birth weight variability on reproductive longevity: A mice model(Journal of Animal Breeding and Genetics, 2022) Formoso Rafferty, Nora; Gutiérrez García, Juan Pablo; García Álvarez, Andrés; Pérez Pérez, Teresa; Cervantes Navarro, IsabelUniformity, understood as a similar performance in relevant livestock traits, such as birth weight within the litter, is being included as one of the selection objectives in breeding programmes, especially for polytocous livestock species. A divergent selection experiment for birth weight within-litter variability in mice during 23 generations showed that homogeneous animals were better for litter size, survival and feed efficiency but less heavy than heterogeneous animals. The aim of this study was to compare the reproductive longevity in both divergent lines as time to the end of the reproductive period. Two generations from both lines with an initial number of 43 females and 43 males were mated one to one and stayed together to have consecutive parturitions until the end of the reproductive life. Females were discarded when the time elapsed from the last parturition was longer than 63 days. The time to the end of the reproductive period between both lines was compared by fitting a Cox proportional hazard regression model adjusting for line, generation and its interaction. The rate of parturitions in both lines was also compared using a Prentice–Williams–Peterson model adjusted for the same effects. The low variability line was associated with a higher parturition rate, e.g., adjusted hazard ratio was 2.93 (95% CI 2.17–3.94). The Cox model showed that the low variability females also presented benefits of time to the end of the reproductive period, with an adjusted hazard ratio of 0.26 (95% CI 0.16–0.41). The median of reproductive days was 55.50 in the high variability line whilst the median was 252.50 daysforthe low variability females. The homogeneous line presented important reproductive advantages suggesting higher robustness and animal welfare. Further research should confirm whether the findings presented here of a better performance in the low variability line could be properly applied to some livestock species.Item Longitudinal Analysis of Continuous Pulse Oximetry as Prognostic Factor in Neonatal Respiratory Distress(American Journal of Perinatology, 2020) Solís García, Gonzalo; Maderuelo Rodríguez, Elena; Pérez Pérez, Teresa; Torres Soblechero, Laura; Gutiérrez Vélez, Ana; Ramos Navarro, Cristina; López Martínez, Raúl; Sánchez Luna, Manuel RamónObjective: Analysis of longitudinal data can provide neonatologists with tools that can help predict clinical deterioration and improve outcomes. The aim of this study is to analyze continuous monitoring data in newborns, using vital signs to develop predictive models for intensive care admission and time to discharge. Study design: We conducted a retrospective cohort study, including term and preterm newborns with respiratory distress patients admitted to the neonatal ward. Clinical and epidemiological data, as well as mean heart rate and saturation, at every minute for the first 12 hours of admission were collected. Multivariate mixed, survival and joint models were developed. Results: A total of 56,377 heart rate and 56,412 oxygen saturation data were analyzed from 80 admitted patients. Of them, 73 were discharged home and 7 required transfer to the intensive care unit (ICU). Longitudinal evolution of heart rate (p < 0.01) and oxygen saturation (p = 0.01) were associated with time to discharge, as well as birth weight (p < 0.01) and type of delivery (p < 0.01). Longitudinal heart rate evolution (p < 0.01) and fraction of inspired oxygen at admission at the ward (p < 0.01) predicted neonatal ICU (NICU) admission. Conclusion: Longitudinal evolution of heart rate can help predict time to transfer to intensive care, and both heart rate and oxygen saturation can help predict time to discharge. Analysis of continuous monitoring data in patients admitted to neonatal wards provides useful tools to stratify risks and helps in taking medical decisions. Key points: · Continuous monitoring of vital signs can help predict and prevent clinical deterioration in neonatal patients.. · In our study, longitudinal analysis of heart rate and oxygen saturation predicted time to discharge and intensive care admission.. · More studies are needed to prospectively prove that these models can helpmake clinical decisions and stratify patients' risks..