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1. Psychiatric Profiles of eHealth Users Evaluated Using Data Mining Techniques: Cohort Study

Author

Lopez-Castroman, Jorge, Abad-Tortosa, Diana, Cobo Aguilera, Aurora, Courtet, Philippe, Barrigón, Maria Luisa, Artés, Antonio, and Baca-García, Enrique

Subjects
Psychology, BF1-990
Abstract

BackgroundNew technologies are changing access to medical records and the relationship between physicians and patients. Professionals can now use e-mental health tools to provide prompt and personalized responses to patients with mental illness. However, there is a lack of knowledge about the digital phenotypes of patients who use e-mental health apps. ObjectiveThis study aimed to reveal the profiles of users of a mental health app through machine learning techniques. MethodsWe applied a nonparametric model, the Sparse Poisson Factorization Model, to discover latent features in the response patterns of 2254 psychiatric outpatients to a short self-assessment on general health. The assessment was completed through a mental health app after the first login. ResultsThe results showed the following four different profiles of patients: (1) all patients had feelings of worthlessness, aggressiveness, and suicidal ideas; (2) one in four reported low energy and difficulties to cope with problems; (3) less than a quarter described depressive symptoms with extremely high scores in suicidal thoughts and aggressiveness; and (4) a small number, possibly with the most severe conditions, reported a combination of all these features. ConclusionsUser profiles did not overlap with clinician-made diagnoses. Since each profile seems to be associated with a different level of severity, the profiles could be useful for the prediction of behavioral risks among users of e-mental health apps.

Published
2021
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2. Clinical Applications of Mobile Health Wearable–Based Sleep Monitoring: Systematic Review

Author

Guillodo, Elise, Lemey, Christophe, Simonnet, Mathieu, Walter, Michel, Baca-García, Enrique, Masetti, Vincent, Moga, Sorin, Larsen, Mark, Ropars, Juliette, and Berrouiguet, Sofian

Subjects
Information technology, T58.5-58.64, Public aspects of medicine, RA1-1270
Abstract

BackgroundSleep disorders are a major public health issue. Nearly 1 in 2 people experience sleep disturbances during their lifetime, with a potential harmful impact on well-being and physical and mental health. ObjectiveThe aim of this study was to better understand the clinical applications of wearable-based sleep monitoring; therefore, we conducted a review of the literature, including feasibility studies and clinical trials on this topic. MethodsWe searched PubMed, PsycINFO, ScienceDirect, the Cochrane Library, Scopus, and the Web of Science through June 2019. We created the list of keywords based on 2 domains: wearables and sleep. The primary selection criterion was the reporting of clinical trials using wearable devices for sleep recording in adults. ResultsThe initial search identified 645 articles; 19 articles meeting the inclusion criteria were included in the final analysis. In all, 4 categories of the selected articles appeared. Of the 19 studies in this review, 58 % (11/19) were comparison studies with the gold standard, 21% (4/19) were feasibility studies, 15% (3/19) were population comparison studies, and 5% (1/19) assessed the impact of sleep disorders in the clinic. The samples were heterogeneous in size, ranging from 1 to 15,839 patients. Our review shows that mobile-health (mHealth) wearable–based sleep monitoring is feasible. However, we identified some major limitations to the reliability of wearable-based monitoring methods compared with polysomnography. ConclusionsThis review showed that wearables provide acceptable sleep monitoring but with poor reliability. However, wearable mHealth devices appear to be promising tools for ecological monitoring.

Published
2020
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3. Combining Continuous Smartphone Native Sensors Data Capture and Unsupervised Data Mining Techniques for Behavioral Changes Detection: A Case Series of the Evidence-Based Behavior (eB2) Study

Author

Berrouiguet, Sofian, Ramírez, David, Barrigón, María Luisa, Moreno-Muñoz, Pablo, Carmona Camacho, Rodrigo, Baca-García, Enrique, and Artés-Rodríguez, Antonio

Subjects
Information technology, T58.5-58.64, Public aspects of medicine, RA1-1270
Abstract

BackgroundThe emergence of smartphones, wearable sensor technologies, and smart homes allows the nonintrusive collection of activity data. Thus, health-related events, such as activities of daily living (ADLs; eg, mobility patterns, feeding, sleeping, ...) can be captured without patients’ active participation. We designed a system to detect changes in the mobility patterns based on the smartphone’s native sensors and advanced machine learning and signal processing techniques. ObjectiveThe principal objective of this work is to assess the feasibility of detecting mobility pattern changes in a sample of outpatients with depression using the smartphone’s sensors. The proposed method processed the data acquired by the smartphone using an unsupervised detection technique. MethodsIn this study, 38 outpatients from the Hospital Fundación Jiménez Díaz Psychiatry Department (Madrid, Spain) participated. The Evidence-Based Behavior (eB2) app was downloaded by patients on the day of recruitment and configured with the assistance of a physician. The app captured the following data: inertial sensors, physical activity, phone calls and message logs, app usage, nearby Bluetooth and Wi-Fi connections, and location. We applied a change-point detection technique to location data on a sample of 9 outpatients recruited between April 6, 2017 and December 14, 2017. The change-point detection was based only on location information, but the eB2 platform allowed for an easy integration of additional data. The app remained running in the background on patients’ smartphone during the study participation. ResultsThe principal outcome measure was the identification of mobility pattern changes based on an unsupervised detection technique applied to the smartphone’s native sensors data. Here, results from 5 patients’ records are presented as a case series. The eB2 system detected specific mobility pattern changes according to the patients’ activity, which may be used as indicators of behavioral and clinical state changes. ConclusionsThe proposed technique could automatically detect changes in the mobility patterns of outpatients who took part in this study. Assuming these mobility pattern changes correlated with behavioral changes, we have developed a technique that may identify possible relapses or clinical changes. Nevertheless, it is important to point out that the detected changes are not always related to relapses and that some clinical changes cannot be detected by the proposed method.

Published
2018
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5. What seems to explain suicidality in Yucatan Mexican young adults? Findings from an app-based mental health screening test using the SMART-SCREEN protocol

Author

Martínez-Nicolás, Ismael, Molina-Pizarro, Cristian Antonio, Franco, Arsenio Rosado, Arenas Castañeda, Pavel E., Maya, Cynthya, Barahona, Igor, Martínez-Alés, Gonzalo, Bisquert, Fuensanta Aroca, Delgado-Gomez, David, Dervic, Kanita, Lopez-Fernandez, Olatz, Baca-García, Enrique, and Barrigón, María Luisa

Published
2023
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13. Suicide Classificaction for News Media Using Convolutional Neural Network

Author

Bello, Hugo J., Palomar-Ciria, Nora, Baca-García, Enrique, and Lozano, Celia

Subjects
Computer Science - Social and Information Networks
Abstract

Currently, the process of evaluating suicides is highly subjective, which limits the efficacy and accuracy of prevention efforts. Artificial intelligence (AI) has emerged as a means of investigating large datasets to identify patterns within "big data" that can determine the factors on suicide outcomes. Here, we use AI tools to extract the topic from (press and social) media text. However, news media articles lack of suicide tags. Using tweets with hashtags related to sucide, we train a neuronal model which identifies if a given text has a suicidade-related contagion. Our results suggest a high level of the impact of mediatic into suicide cases, and a intrinsic thematic relationship of suicide news. These results pave the way to build more interpretable suicide data, which may help to better track, understand its origin, and improve prevention strategies.

Published
2021

14. Passive detection of behavioral shifts for suicide attempt prevention

Author

Moreno-Muñoz, Pablo, Romero-Medrano, Lorena, Moreno, Ángela, Herrera-López, Jesús, Baca-García, Enrique, and Artés-Rodríguez, Antonio

Subjects
Computer Science - Computers and Society, Computer Science - Machine Learning
Abstract

More than one million people commit suicide every year worldwide. The costs of daily cares, social stigma and treatment issues are still hard barriers to overcome in mental health. Most symptoms of mental disorders are related to the behavioral state of a patient, such as the mobility or social activity. Mobile-based technologies allow the passive collection of patients data, which supplements conventional assessments that rely on biased questionnaires and occasional medical appointments. In this work, we present a non-invasive machine learning (ML) model to detect behavioral shifts in psychiatric patients from unobtrusive data collected by a smartphone app. Our clinically validated results shed light on the idea of an early detection mobile tool for the task of suicide attempt prevention., Comment: Machine Learning for Mobile Health Workshop at NeurIPS 2020

Published
2020

16. Deep Sequential Models for Suicidal Ideation from Multiple Source Data

Author

Peis, Ignacio, Olmos, Pablo M., Vera-Varela, Constanza, Barrigón, María Luisa, Courtet, Philippe, Baca-García, Enrique, and Artés-Rodríguez, Antonio

Subjects
Computer Science - Machine Learning, Statistics - Machine Learning
Abstract

This article presents a novel method for predicting suicidal ideation from Electronic Health Records (EHR) and Ecological Momentary Assessment (EMA) data using deep sequential models. Both EHR longitudinal data and EMA question forms are defined by asynchronous, variable length, randomly-sampled data sequences. In our method, we model each of them with a Recurrent Neural Network (RNN), and both sequences are aligned by concatenating the hidden state of each of them using temporal marks. Furthermore, we incorporate attention schemes to improve performance in long sequences and time-independent pre-trained schemes to cope with very short sequences. Using a database of 1023 patients, our experimental results show that the addition of EMA records boosts the system recall to predict the suicidal ideation diagnosis from 48.13% obtained exclusively from EHR-based state-of-the-art methods to 67.78%. Additionally, our method provides interpretability through the t-SNE representation of the latent space. Further, the most relevant input features are identified and interpreted medically., Comment: Accepted for publication in IEEE Journal of Biomedical and Health Informatics (JBHI)

Published
2019
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17. Video Games for the Treatment of Autism Spectrum Disorder: A Systematic Review

Author

Jiménez-Muñoz, Laura, Peñuelas-Calvo, Inmaculada, Calvo-Rivera, Pilar, Díaz-Oliván, Isaac, Moreno, Manon, Baca-García, Enrique, and Porras-Segovia, Alejandro

Abstract

Video games are a promising area of intervention for children diagnosed with Autism Spectrum Disorders (ASD). However, reviews on this topic are scarce. This review on studies exploring video games for the treatment of ASD followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, and its protocol was registered in PROSPERO. PubMed, PsycInfo, Embase, WebOfScience and clinicaltrials.gov databases were searched. Twenty-four articles were included in the review. Video game-based interventions were effective for alleviating ASD symptoms, albeit with small effect sizes. High rates of acceptability and adherence to treatment were obtained. Conclusion: Video games are a promising area for improving the treatment of children with ASD. Exploring commercial video games is one of the lines for future research.

Published
2022
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20. Text mining methods for the characterisation of suicidal thoughts and behaviour

Author

Aroca, Fuensanta, Artes-Rodriguez, Antonio, Baca-García, Enrique, Berrouiguet, Sofian, Billot, Romain, Carballo-Belloso, Juan Jose, Courtet, Philippe, Gomez, David Delgado, Lopez-Castroman, Jorge, Rodriguez, Mercedes Perez, Aznar-Carbone, Julia, Cegla, Fanny, Gutiérrez-Recacha, Pedro, Izaguirre-Gamir, Leire, Herrera-Sanchez, Javier, Borja, Marta Migoya, Palomar-Ciria, Nora, Martínez, Adela Sánchez-Escribano, Vasquez, Manuel, Vallejo-Oñate, Silvia, Vera-Varela, Constanza, Amodeo-Escribano, Susana, Arrua, Elsa, Bautista, Olga, Barrigón, Maria Luisa, Carmona, Rodrigo, Caro-Cañizares, Irene, Carollo-Vivian, Sonia, Chamorro, Jaime, González-Granado, Marta, Iza, Miren, Jiménez-Giménez, Mónica, López-Gómez, Ana, Mata-Iturralde, Laura, Miguelez, Carolina, Muñoz-Lorenzo, Laura, Navarro-Jiménez, Rocío, Ovejero, Santiago, Palacios, María Luz, Pérez-Fominaya, Margarita, Peñuelas-Calvo, Inmaculada, Pérez-Colmenero, Sonia, Rico-Romano, Ana, Rodriguez-Jover, Alba, SánchezAlonso, Sergio, Sevilla-Vicente, Juncal, Vigil-López, Carolina, Villoria-Borrego, Lucía, Martin-Calvo, Marisa, Alcón-Durán, Ana, Stasio, Ezequiel Di, García-Vega, Juan Manuel, Martín-Calvo, Pedro, Ortega, Ana José, Segura-Valverde, Marta, Bañón-González, Sara María, Crespo-Llanos, Edurne, Codesal-Julián, Rosana, Frade-Ciudad, Ainara, Merino, Elena Hernando, Álvarez-García, Raquel, Coll-Font, Jose Marcos, Portillo-de Antonio, Pablo, Puras-Rico, Pablo, Sedano-Capdevila, Alba, Serrano-Marugán, Leticia, Toledo-Acosta, Mauricio, Barrigon, María Luisa, Morales-González, Eliseo, Torres-Moreno, David, Martínez-Zaldivar, Bolívar, and Hermosillo-Valadez, Jorge

Published
2023
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23. Descriptive study on substance uses and risk of sexually transmitted infections in the practice of Chemsex in Spain

Author

del Pozo-Herce, Pablo, primary, Baca-García, Enrique, additional, Martínez-Sabater, Antonio, additional, Chover-Sierra, Elena, additional, Gea-Caballero, Vicente, additional, Curto-Ramos, Javier, additional, Czapla, Michal, additional, Karniej, Piotr, additional, Martínez-Tofe, Jesús, additional, Sánchez-Barba, Mercedes, additional, de Viñaspre, Regina Ruiz, additional, and Juárez-Vela, Raúl, additional

Published
2024
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25. The relationship between negative symptoms, social cognition, and social functioning in patients with first episode psychosis

Author

Leza, Juan C., Ayora, Miriam, Boi, Sara, Nuñez-Doyle, Aggie, Jiménez-Rodríguez, Olga, Albea, Julia García, Quijano, Jose Rodríguez, Saiz-Ruiz, Jerónimo, León-Quismondo, Leticia, Muñoz-Sanjose, Ainoa, Vidal-Villegas, Paz, García, Lucia Albarracin, Barrigon-Esteve, Maria Luisa, Torio, Iosune, García-López, María, Alonso-Sánchez, Miguel, Leal, Itziar, Martín-Hernández, David, Caso, Javier R., Díaz-Caneja, Covadonga M., Andreu-Bernabeu, Álvaro, Arango, Celso, Rodriguez-Jimenez, Roberto, Sánchez-Pastor, Luis, Díaz-Marsá, Marina, Mellor-Marsá, Blanca, Ibáñez, Ángela, Malpica, Norberto, Bravo-Ortiz, Maria-Fe, Baca-Garcia, Enrique, Ayuso-Mateos, Jose Luis, and Izquierdo, Ana

Published
2022
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29. Video Games for the Treatment of Autism Spectrum Disorder: A Systematic Review

Author

Jiménez-Muñoz, Laura, Peñuelas-Calvo, Inmaculada, Calvo-Rivera, Pilar, Díaz-Oliván, Isaac, Moreno, Manon, Baca-García, Enrique, and Porras-Segovia, Alejandro

Subjects
Pervasive developmental disorders -- Technology application -- Care and treatment -- Social aspects, Video games -- Health aspects -- Usage, Autistic children -- Social aspects -- Care and treatment, Technology application, Health
Abstract

Video games are a promising area of intervention for children diagnosed with Autism Spectrum Disorders (ASD). However, reviews on this topic are scarce. This review on studies exploring video games for the treatment of ASD followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, and its protocol was registered in PROSPERO. PubMed, PsycInfo, Embase, WebOfScience and clinicaltrials.gov databases were searched. Twenty-four articles were included in the review. Video game-based interventions were effective for alleviating ASD symptoms, albeit with small effect sizes. High rates of acceptability and adherence to treatment were obtained. Conclusion: Video games are a promising area for improving the treatment of children with ASD. Exploring commercial video games is one of the lines for future research., Author(s): Laura Jiménez-Muñoz [sup.1] [sup.2] , Inmaculada Peñuelas-Calvo [sup.1] [sup.3] [sup.4] , Pilar Calvo-Rivera [sup.5] , Isaac Díaz-Oliván [sup.1] [sup.2] , Manon Moreno [sup.1] [sup.2] , Enrique Baca-García [sup.1] [sup.2] [...]

Published
2022
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31. Effectiveness of Harm Reduction Interventions in Chemsex: A Systematic Review.

Author

Pozo-Herce, Pablo Del, Martínez-Sabater, Antonio, Sanchez-Palomares, Paula, Garcia-Boaventura, Paula Cristina, Chover-Sierra, Elena, Martínez-Pascual, Raquel, Gea-Caballero, Vicente, Saus-Ortega, Carles, Ballestar-Tarín, María Luisa, Karniej, Piotr, Baca-García, Enrique, and Juárez-Vela, Raúl

Subjects
SUBSTANCE abuse treatment, RISK-taking behavior, SELF-efficacy, HUMAN sexuality, MEDICAL care, TREATMENT effectiveness, DESCRIPTIVE statistics, INTERNET, HARM reduction, SYSTEMATIC reviews, MEDLINE, MEDICAL databases, ONLINE information services, HEALTH promotion, PUBLIC health, PSYCHOLOGY information storage & retrieval systems
Abstract

The phenomenon of chemsex has emerged as an essential public health issue in recent years. This systematic review aimed to investigate currently available harm reduction strategies and to evaluate the efficacy of the corresponding interventions. Methods: A systematic review of the scientific literature related to harm and risk reduction strategies and the effectiveness of chemsex interventions. Between January 2024 and May 2024, the articles were retrieved from the electronic databases Pubmed, Web of Science, Scopus, PsycInfo, Cochrane, Dialnet, CUIDEN, and SciELO. The review protocol was registered in the PROSPERO database (registration number CRD42024508953). The inclusion criteria were as follows: (I) original studies published in peer-reviewed journals, (II) studies exploring harm reduction interventions for chemsex, and (III) studies reflecting the efficacy of harm reduction interventions for chemsex. Two reviewers independently selected articles by title, abstract, and full paper review and extracted data. Two authors described the selected studies and assessed their methodological quality. Results: The systematic review comprised six scientific papers that met the selection criteria and were obtained from five countries. Although a limited number of studies were included, it was observed that they presented a medium–high methodological quality. Programs evaluated interventions to reduce harm from chemsex, such as a web-based intervention that improved self-efficacy to refuse risky behaviors and accept HIV testing. The studies suggested that peer-led programs can be effective, especially with facilitators who have experienced chemsex dependence. Conclusion: Harm reduction strategies in chemsex are effective and should be promoted by health professionals. Interventions should be accessible, personalized, and non-judgmental to provide appropriate care and support, ensuring a comprehensive and effective public health response. [ABSTRACT FROM AUTHOR]

Published
2024
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32. Perceived burdensomeness, thwarted belongingness, and hopelessness as predictors of future suicidal ideation in Spanish university students.

Author

Pérez, Sandra, Layrón, Jose Enrique, Barrigón, Maria Luisa, Baca-García, Enrique, and Marco, Jose H.

Subjects
SUICIDE prevention, GOODNESS-of-fit tests, PEARSON correlation (Statistics), SUICIDAL ideation, T-test (Statistics), QUESTIONNAIRES, MULTIVARIATE analysis, DESCRIPTIVE statistics, DESPAIR, MATHEMATICAL models, COLLEGE students, THEORY, DATA analysis software, COMPARATIVE studies, PSYCHOSOCIAL factors
Abstract

The Interpersonal Theory of Suicide (IPTS) has received support for its role in understanding suicidal thoughts and behaviors. However, few longitudinal studies have focused on testing this theory in university students. The present study aimed to confirm the theoretical model of the IPTS in a sample of 225 Spanish university students, using path analysis in a longitudinal study. We assessed thwarted belongingness and perceived burdensomeness at T1 and hopelessness and suicidal ideation at T2, 12-14 weeks later. Moreover, we assessed suicidal ideation weekly for 14 weeks. Path analyses confirmed the Interpersonal Theory of Suicide model, with thwarted belongingness and perceived burdensomeness as direct and indirect predictors of suicidal ideation through hopelessness. Providers of guidance and clinical services in university settings should be trained to identify perceived burdensomeness, social belongingness, hopelessness, and suicidal ideation when screening for suicide prevention. [ABSTRACT FROM AUTHOR]

Published
2024
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37. Jumping to conclusions and suicidal behavior in depression and psychosis

Author

Acevedo, A., Anglès, J., Argany, M.A., Barajas, A., Barrigón, M.L., Beltrán, M., Birulés, I., Bogas, J.L., Camprubí, N., Carbonero, M., Carmona Farrés, C., Carrasco, E., Casañas, R., Cid, J., Conesa, E., Corripio, I., Cortes, P., Crosas, J.M., de Apraiz, A., Delgado, M., Domínguez, L., Escartí, M.J., Escudero, A., Esteban Pinos, I., Figueras, M., Franco, C., García, C., Gil, V., Giménez-Díaz, D., Gonzalez-Casares, R., González Higueras, F., González- Montoro, MaL., González, E., Grasa Bello, E., Guasp, A., Huerta-Ramos, Ma E., Huertas, P., Jiménez-Díaz, A., Lalucat, L.L., LLacer, B., López-Alcayada, R., López- Carrilero, R., Lorente, E., Luengo, A., Mantecón, N., Mas-Expósito, L., Montes, M., Moritz, S., Murgui, E., Nuñez, M., Ochoa, S., Palomer, E., Paniego, E., Peláez, T., Pérez, V., Planell, K., Planellas, C., Pleguezuelo-Garrote, P., Pousa, E., Rabella, M., Renovell, M., Rubio, R., Ruiz- Delgado, I., San Emeterio, M., Sánchez, E., Sanjuán, J., Sans, B., Schilling, L., Sió, H., Teixidó, M., Torres, P., Vila, M.A., Vila-Badia, R., Villegas, F., Villellas, R., Sastre-Buades, Aina, Ochoa, Susana, Lorente-Rovira, Esther, Barajas, Ana, Grasa, Eva, López-Carrilero, Raquel, Luengo, Ana, Ruiz-Delgado, Isabel, Cid, Jordi, González-Higueras, Fermín, Sánchez-Alonso, Sergio, Baca-García, Enrique, and Barrigón, Maria L.

Published
2021
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38. How does neighbourhood socio-economic status affect the interrelationships between functioning dimensions in first episode of psychosis? A network analysis approach

Author

Leza, Juan Carlos, Molina-García, Mariola, Andreu-Bernabeu, Álvaro, Dompablo, Mónica, Sánchez-Pastor, Luis, López-Torres, Isabel, León-Quismondo, Leticia, Muñoz Sanjose, Ainoa, Vidal-Villegas, María-Paz, Puras-Rico, Pablo, Albarracín-García, Lucía, Izquierdo, Ana, Cabello, María, Leal, Itziar, Ayora, Miriam, Rodriguez-Jimenez, Roberto, Ibáñez, Ángela, Díaz-Marsá, Marina, Bravo-Ortiz, María-Fé, Baca-García, Enrique, Madrigal, José L.M., Fares-Otero, Natalia E., Díaz-Caneja, Covadonga M., Arango, Celso, and Ayuso Mateos, Jose Luis

Published
2021
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40. The interplay between functioning problems and symptoms in first episode of psychosis: An approach from network analysis

Author

García-Albea, Julia, Saiz-González, Dolores, Durán-Cutilla, Manuel, Merchán-Naranjo, Jessica, Mediavilla-Torres, Roberto, Muñoz-Sanjosé, Ainoa, Sanchez-Pastor, Luis, Dompablo, Monica, Fernández-Martín, Patricia, León-Quismondo, Leticia, Carlos Leza, Juan, Puras-Rico, Pablo, Albarracin-García, Lucía, Izquierdo, Ana, Cabello, María, Leal, Itziar, Mellor-Marsá, Blanca, Ayora, Miriam, Bravo-Ortiz, María-Fe, Rodriguez-Jimenez, Roberto, Ibáñez, Ángela, MacDowell, Karina S., Malpica, Norberto, Díaz-Marsá, Marina, Baca-García, Enrique, Fares-Otero, Natalia E., Melero, Helena, López-García, Pilar, Díaz-Caneja, Covadonga M., Arango, Celso, and Ayuso-Mateos, Jose Luis

Published
2021
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45. Application of the Delphi Method for Content Validity Analysis of a Questionnaire to Determine the Risk Factors of the Chemsex

Author

del Pozo-Herce, Pablo, primary, Martínez-Sabater, Antonio, additional, Chover-Sierra, Elena, additional, Gea-Caballero, Vicente, additional, Satústegui-Dordá, Pedro José, additional, Saus-Ortega, Carles, additional, Tejada-Garrido, Clara Isabel, additional, Sánchez-Barba, Mercedes, additional, Pérez, Jesús, additional, Juárez-Vela, Raúl, additional, Santolalla-Arnedo, Iván, additional, and Baca-García, Enrique, additional

Published
2023
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