Aplicación on-line del método de Aprendizaje Basado en Proyectos para la enseñanza en alumnos universitarios

Fac. de PsicologíaFALSEsubmitte

How does neighbourhood socio-economic status affect the interrelationships between functioning dimensions in first episode of psychosis? A network analysis approach

The links between psychosis and socio-economic disadvantage have been widely studied. No previous study has analysed the interrelationships and mutual influences between functioning dimensions in first episode of psychosis (FEP) according to their neighbourhood household income, using a multidimensional and transdiagnostic perspective. 170 patients and 129 controls, participants in an observational study (AGES-CM), comprised the study sample. The WHO Disability Assessment Schedule (WHODAS 2.0) was used to assess functioning, whereas participants' postcodes were used to obtain the average household income for each neighbourhood, collected by the Spanish National Statistics Institute (INE). Network analyses were conducted with the aim of defining the interrelationships between the different dimensions of functioning according to the neighbourhood household income. Our results show that lower neighbourhood socioeconomic level is associated with lower functioning in patients with FEP. Moreover, our findings suggest that “household responsibilities” plays a central role in the disability of patients who live in low-income neighbourhoods, whereas “dealing with strangers” is the most important node in the network of patients who live in high-income neighbourhoods. These results could help to personalize treatments, by allowing the identification of potential functioning areas to be prioritized in the treatment of FEP according to the patient's neighbourhood characteristic

The interplay between functioning problems and symptoms in first episode of psychosis: an approach from network analysis

The relationship between psychotic symptoms and global measures of functioning has been widely studied. No previous study has assessed so far the interplay between specific clinical symptoms and particular areas of functioning in first-episode psychosis (FEP) using network analysis methods. A total of 191 patients with FEP (age 24.45 ± 6.28 years, 64.9% male) participating in an observational and longitudinal study (AGES-CM) comprised the study sample. Functioning problems were assessed with the WHO Disability Assessment Schedule (WHODAS), whereas the Positive and Negative Syndrome Scale (PANSS) was used to assess symptom severity. Network analysis were conducted with the aim of analysing the patterns of relationships between the different dimensions of functioning and PANSS symptoms and factors at baseline. According to our results, the most important nodes were “conceptual disorganization”, “emotional withdrawal”, “lack of spontaneity and flow of conversation”, “delusions”, “unusual thought content”, “dealing with strangers” and “poor rapport”. Our findings suggest that these symptoms and functioning dimensions should be prioritized in the clinical assessment and management of patients with FEP. These areas may also become targets of future early intervention strategies, so as to improve quality of life in this populationThis work was supported by the Madrid Regional Government (R&D activities in Biomedicine (grant number S2017/BMD-3740 - AGES-CM 2-CM)) and Structural Funds of the European Union. Ana Izquierdo’s work is supported by the PFIS predoctoral program (FI17/00138) from the Instituto de Salud Carlos III (Spain) and co-funded by the European Union (ERDF/ESF, "A way to make Europe”/ “Investing in your future”) and The Biomedical Research Foundation of La Princesa University Hospital. Angela Ib´a˜nez thanks the support of CIBERSAM and of the Spanish Ministry of Science, Innovation and Universities. Instituto de Salud Carlos III (PI16/00834 and PI19/01295) co-financed by ERDF Funds from the European Commission. Covadonga M. Díaz-Caneja holds a Juan Rod´es Grant from Instituto de Salud Carlos III (JR19/00024). Celso Arango was supported by the Spanish Ministry of Science and Innovation. Instituto de Salud Carlos III (SAM16PE07CP1, PI16/02012, PI19/ 024), co-financed by ERDF Funds from the European Commission, “A way of making Europe”, CIBERSAM. Madrid Regional Government (B2017/BMD-3740 AGES-CM-2), European Union Structural Funds. European Union Seventh Framework Program under grant agreements FP7-4-HEALTH-2009-2.2.1-2-241909 (Project EU-GEI), FP7- HEALTH- 2013-2.2.1-2-603196 (Project PSYSCAN) and FP7- HEALTH-2013- 2.2.1-2-602478 (Project METSY); and European Union H2020 Program under the Innovative Medicines Initiative 2 Joint Undertaking (grant agreement No 115916, Project PRISM, and grant agreement No 777394, Project AIMS-2-TRIALS), Fundaci´on Familia Alonso, Fundaci´on Alicia Koplowitz and Fundaci´on Mutua Madrile˜n

Outpatient readmission in rheumatology: A machine learning predictive model of patient's return to the clinic

Our objective is to develop and validate a predictive model based on the random forest algorithm to estimate the readmission risk to an outpatient rheumatology clinic after discharge. We included patients from the Hospital Clínico San Carlos rheumatology outpatient clinic, from 1 April 2007 to 30 November 2016, and followed-up until 30 November 2017. Only readmissions between 2 and 12 months after the discharge were analyzed. Discharge episodes were chronologically split into training, validation, and test datasets. Clinical and demographic variables (diagnoses, treatments, quality of life (QoL), and comorbidities) were used as predictors. Models were developed in the training dataset, using a grid search approach, and performance was compared using the area under the receiver operating characteristic curve (AUC-ROC). A total of 18,662 discharge episodes were analyzed, out of which 2528 (13.5%) were followed by outpatient readmissions. Overall, 38,059 models were developed. AUC-ROC, sensitivity, and specificity of the reduced final model were 0.653, 0.385, and 0.794, respectively. The most important variables were related to follow-up duration, being prescribed with disease-modifying anti-rheumatic drugs and corticosteroids, being diagnosed with chronic polyarthritis, occupation, and QoL. We have developed a predictive model for outpatient readmission in a rheumatology setting. Identification of patients with higher risk can optimize the allocation of healthcare resources

Learning by educating: e-Service learning experience of oral health promotion

La metodología utilizada durante todo el proyecto fue el recurso en línea, dada la situación de crisis sanitaria debido al COVID-19. Internet fue el medio principal y único para llevar a cabo todas las actividades, desde el reclutamiento y la preparación de los estudiantes hasta la implementación del servicio y su evaluación. La realización de un e-ApS es posible y ofrece las oportunidades necesarias para que los alumnos desarrollen su valor de ciudadanía inclusiva, digna y democrática, al igual que cuando el proyecto se realiza de manera presencial.Due to the health crisis due to COVID-19, the methodology used in the project was the online resource. The Internet was the medium for carrying out all activities, from the recruitment and preparation of students to the implementation of the service and its assessment. Carrying out an e-ApS is possible and it offers the necessary opportunities for students to develop their value of inclusive, respectful and democratic citizenship, just as when the project is carried out in person.Oficina Universitaria de Aprendizaje-Servicio UCMDepto. de Especialidades Clínicas OdontológicasFac. de OdontologíaTRUEsubmitte

The interplay between functioning problems and symptoms in first episode of psychosis: An approach from network analysis

The relationship between psychotic symptoms and global measures of functioning has been widely studied. No previous study has assessed so far the interplay between specific clinical symptoms and particular areas of functioning in first-episode psychosis (FEP) using network analysis methods. A total of 191 patients with FEP (age 24.45 ± 6.28 years, 64.9% male) participating in an observational and longitudinal study (AGES-CM) comprised the study sample. Functioning problems were assessed with the WHO Disability Assessment Schedule (WHODAS), whereas the Positive and Negative Syndrome Scale (PANSS) was used to assess symptom severity. Network analysis were conducted with the aim of analysing the patterns of relationships between the different dimensions of functioning and PANSS symptoms and factors at baseline. According to our results, the most important nodes were “conceptual disorganization”, “emotional withdrawal”, “lack of spontaneity and flow of conversation”, “delusions”, “unusual thought content”, “dealing with strangers” and “poor rapport”. Our findings suggest that these symptoms and functioning dimensions should be prioritized in the clinical assessment and management of patients with FEP. These areas may also become targets of future early intervention strategies, so as to improve quality of life in this population.Depto. de Psicobiología y Metodología en Ciencias del ComportamientoFac. de PsicologíaTRUEpu