Positive mental health of Latin American university professors: A scientific framework for intervention and improvement
Artículo Materias > Psicología Universidad Europea del Atlántico > Investigación > Artículos y libros Abierto Español The post-pandemic stage covid-19 has revealed overloads, ambiguities, and conflicts of teachers in the performance of new roles in hybrid classrooms that demanded an urgent adaptation, this highlighted the need for priority attention to the mental health of teachers, however, there are still insufficient studies that transcend the diagnosis and are committed to establish proposals for improvement. OBJECTIVE: This study aims to establish a proposal for the promotion of positive mental health (PMH). METHODS: The study was deployed from a qualitative approach; using an ethnomethodological design that allowed studying how teachers create meanings and sense in their work context, an appreciative interview was conducted with an affirmative theme that allowed teachers to expose their experiences that were systematized and processed with ATLAS. ti software. The application of the interview was conducted online through a Google form, during the months of February and March 2023. Three hundred university professors who experienced the pandemic in universities in Brazil, Chile, Colombia, Ecuador, Mexico, and Peru participated, based on a convenience sampling. RESULTS: The results of the deductive phase confirmed Lluch's PMH theoretical framework; however, new nuances or variations have been identified, which must be considered in the complex and dynamic nature of each PMH factor. From there, the results of the inductive phase allowed revealing emerging concepts, that is, new categories that would have the function of improving the PMH factors, which is why they have been denominated: dynamizing nuclei. PMH dynamizing nuclei are adjustment to work environment, soft skills, work-family balance, self-motivation, self-efficacy, subjective well-being, proactive strategies, engagement, resilience. CONCLUSIONS: Finally, with the results of both phases, the creation of an integrated model was generated, which was evaluated by six experts in a round of feedback, who highlighted the relevance of the findings and offered recommendations that were considered in the study. The new integrated model has revealed an interesting association, since it not only legitimizes the PMH's dynamizing cores, but also informs on which specific factor of the PMH these cores have the greatest impact, which has a high guiding value for intervention and improvement based on focused strategies. metadata Deroncele-Acosta, Angel; Rojas Vistorte, Angel Olider; Sartor-Harada, Andresa; Ulloa-Guerra, Oscar; López-Mustelier, Rosendo y Cruzata-Martínez, Alejandro mail SIN ESPECIFICAR, angel.rojas@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR (2024) Positive mental health of Latin American university professors: A scientific framework for intervention and improvement. Heliyon, 10 (2). e24813. ISSN 24058440
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The post-pandemic stage covid-19 has revealed overloads, ambiguities, and conflicts of teachers in the performance of new roles in hybrid classrooms that demanded an urgent adaptation, this highlighted the need for priority attention to the mental health of teachers, however, there are still insufficient studies that transcend the diagnosis and are committed to establish proposals for improvement. OBJECTIVE: This study aims to establish a proposal for the promotion of positive mental health (PMH). METHODS: The study was deployed from a qualitative approach; using an ethnomethodological design that allowed studying how teachers create meanings and sense in their work context, an appreciative interview was conducted with an affirmative theme that allowed teachers to expose their experiences that were systematized and processed with ATLAS. ti software. The application of the interview was conducted online through a Google form, during the months of February and March 2023. Three hundred university professors who experienced the pandemic in universities in Brazil, Chile, Colombia, Ecuador, Mexico, and Peru participated, based on a convenience sampling. RESULTS: The results of the deductive phase confirmed Lluch's PMH theoretical framework; however, new nuances or variations have been identified, which must be considered in the complex and dynamic nature of each PMH factor. From there, the results of the inductive phase allowed revealing emerging concepts, that is, new categories that would have the function of improving the PMH factors, which is why they have been denominated: dynamizing nuclei. PMH dynamizing nuclei are adjustment to work environment, soft skills, work-family balance, self-motivation, self-efficacy, subjective well-being, proactive strategies, engagement, resilience. CONCLUSIONS: Finally, with the results of both phases, the creation of an integrated model was generated, which was evaluated by six experts in a round of feedback, who highlighted the relevance of the findings and offered recommendations that were considered in the study. The new integrated model has revealed an interesting association, since it not only legitimizes the PMH's dynamizing cores, but also informs on which specific factor of the PMH these cores have the greatest impact, which has a high guiding value for intervention and improvement based on focused strategies.
| Tipo de Documento: | Artículo |
|---|---|
| Palabras Clave: | Mental health; Virtual education; Hybrid classroom; University; Students; Learning; Teaching;COVID-19; Educational innovation; Digital transformation |
| Clasificación temática: | Materias > Psicología |
| Divisiones: | Universidad Europea del Atlántico > Investigación > Artículos y libros |
| Depositado: | 12 Feb 2024 23:30 |
| Ultima Modificación: | 08 May 2024 19:02 |
| URI: | https://repositorio.uneatlantico.es/id/eprint/10842 |
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Enzymatic treatment shapes in vitro digestion pattern of phenolic compounds in mulberry juice
The health benefits of mulberry fruit are closely associated with its phenolic compounds. However, the effects of enzymatic treatments on the digestion patterns of these compounds in mulberry juice remain largely unknown. This study investigated the impact of pectinase (PE), pectin lyase (PL), and cellulase (CE) on the release of phenolic compounds in whole mulberry juice. The digestion patterns were further evaluated using an in vitro simulated digestion model. The results revealed that PE significantly increased chlorogenic acid content by 77.8 %, PL enhanced cyanidin-3-O-glucoside by 20.5 %, and CE boosted quercetin by 44.5 %. Following in vitro digestion, the phenolic compound levels decreased differently depending on the treatment, while cyanidin-3-O-rutinoside content increased across all groups. In conclusion, the selected enzymes effectively promoted the release of phenolic compounds in mulberry juice. However, during gastrointestinal digestion, the degradation of phenolic compounds surpassed their enhanced release, with effects varying based on the compound's structure.
Peihuan Luo mail , Jian Ai mail , Qiongyao Wang mail , Yihang Lou mail , Zhiwei Liao mail , Francesca Giampieri mail francesca.giampieri@uneatlantico.es, Maurizio Battino mail maurizio.battino@uneatlantico.es, Elwira Sieniawska mail , Weibin Bai mail , Lingmin Tian mail ,
Luo
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Background Before the incorporation of enfortumab vedotin with pembrolizumab, the standard of care for patients with locally advanced or metastatic urothelial carcinoma who do not progress after platinum-based chemotherapy was avelumab maintenance therapy, as demonstrated by the JAVELIN 100 trial. However, real-world European data remain scarce. Patients and Methods AVEBLADDER is a retrospective study conducted at 14 hospitals in Northern Spain, including patients with locally advanced or metastatic urothelial carcinoma diagnosed between January 2021 and June 2023. Outcomes of overall survival (OS) and progression-free survival (PFS) were analyzed for patients treated with platinum-based chemotherapy, with and without subsequent avelumab maintenance therapy. non-avelumab patients. Median PFS was 11.33 months (95% CI: 10–13.6) with avelumab and 6.43 months (95% CI: 6–7.6) without. One-year OS probabilities were 81.6% vs. 45.6% (p < 0.001) in the avelumab and non-avelumab groups, respectively. No unexpected toxicities were reported. Conclusions Despite proven survival benefits, avelumab uptake in real-world practice is limited by barriers like access, reimbursement, and awareness. These findings align with JAVELIN 100 and underscore the need for further real-world studies to address treatment disparities.
Marta Sotelo mail , Mireia Peláez mail mireia.pelaez@uneatlantico.es, Laura Basterretxea mail , Estrella Varga mail , Ricardo Sánchez-Escribano mail , Eduardo Pujol Obis mail , Carmen Santander mail , Mireia Martínez Kareaga mail , Mikel Arruti Ibarbia mail , Inmaculada Rodríguez Ledesma mail , Carlos Álvarez Fernández mail , Pablo Piedra mail , Verónica Calderero Aragón mail , Nuria Lainez mail , Juan Antonio Verdún Aguilar mail , Irene Gil Arnáiz mail , Ricardo Fernández mail , Cristina Mazas Pérez-Oleaga mail cristina.mazas@uneatlantico.es, Ignacio Duran mail ,
Sotelo
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Although financial literacy would seem relevant to university students’ education, it is not currently offered as a transversal subject within European academic curricula. It should therefore come as no surprise that a common solution are ad-hoc specific courses, with students often additionally acquiring valuable learning through their own experiences in business environments. With this and the recent literature on the drivers of financial literacy in mind, the authors decided to explore the context shaped by socio-demographic, academic and work-related factors that either promote or prevent European university students from developing appropriate financial skills, such as managing personal finances, planning for short- and long-term needs, and distinguishing among different sources of non-traditional funding. The study used a sample of 881 undergraduate and postgraduate university students from Romania, Poland and Spain from different studies, with information obtained through an anonymous online survey. The applied econometric model was cumulative regression with location-scale estimation using the R software, version 4.3.2, with variables associated directly with the development of basic financial skills being age, gender, country, but also specific training as well as work and entrepreneurial experience. The authors stress the importance of providing financial management education connected to the reality, especially the business and entrepreneurial environment.
Inna Alexeeva-Alexeev mail inna.alexeeva@uneatlantico.es, Ana Kaminska mail , Cristina Mazas Pérez-Oleaga mail cristina.mazas@uneatlantico.es, Sorin Gabriel Anton mail ,
Alexeeva-Alexeev
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A novel machine learning-based proposal for early prediction of endometriosis disease
Background Endometriosis is one of the causes of female infertility, with some studies estimating its prevalence at around 10 % of reproductive-age women worldwide and between 30 and 50 % in symptomatic women. However, its diagnosis is complex and often delayed, highlighting the need for more accessible and accurate diagnostic methods. The difficulty lies in its diverse etiology and the variability of symptoms among those affected. Methods This study proposes a predictive model based on supervised machine learning for the early identification of endometriosis, providing support for decision-making by healthcare professionals. For this purpose, an anonymised dataset of 5,143 female patients diagnosed with endometriosis at the private fertility clinic Inebir was used. The model integrates clinical records and genetic analysis through supervised machine learning algorithms, focusing on clinical variables and pathogenic and potentially pathogenic genetic variants. Results The developed predictive model achieves high accuracy in identifying the presence of endometriosis, highlighting the importance of combining clinical and genetic data in diagnosis. The integration of this data into the DELFOS platform, a clinical decision support system, demonstrates the utility of machine learning in improving the diagnosis of endometriosis. Conclusions The findings underscore the potential of clinical and genetic factors in the early diagnosis of endometriosis using supervised machine learning algorithms. This study contributes to the classification of clinical variables that influence endometriosis, offering a valuable tool for clinicians in making therapeutic and management decisions for their female patients.
Elena Enamorado-Díaz mail , Leticia Morales-Trujillo mail , Julián-Alberto García-García mail , Ana Teresa Marcos Rodríguez mail anateresa.marcos@uneatlantico.es, José Manuel Navarro-Pando mail jose.navarro@uneatlantico.es, María-José Escalona-Cuaresma mail ,
Enamorado-Díaz
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Detecting hate in diversity: a survey of multilingual code-mixed image and video analysis
The proliferation of damaging content on social media in today’s digital environment has increased the need for efficient hate speech identification systems. A thorough examination of hate speech detection methods in a variety of settings, such as code-mixed, multilingual, visual, audio, and textual scenarios, is presented in this paper. Unlike previous research focusing on single modalities, our study thoroughly examines hate speech identification across multiple forms. We classify the numerous types of hate speech, showing how it appears on different platforms and emphasizing the unique difficulties in multi-modal and multilingual settings. We fill research gaps by assessing a variety of methods, including deep learning, machine learning, and natural language processing, especially for complicated data like code-mixed and cross-lingual text. Additionally, we offer key technique comparisons, suggesting future research avenues that prioritize multi-modal analysis and ethical data handling, while acknowledging its benefits and drawbacks. This study attempts to promote scholarly research and real-world applications on social media platforms by acting as an essential resource for improving hate speech identification across various data sources.
Hafiz Muhammad Raza Ur Rehman mail , Mahpara Saleem mail , Muhammad Zeeshan Jhandir mail , Eduardo René Silva Alvarado mail eduardo.silva@funiber.org, Helena Garay mail helena.garay@uneatlantico.es, Imran Ashraf mail ,
Raza Ur Rehman