Items where Subject is "Subjects > Psychology"
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2026
Article
Subjects > Psychology
Subjects > Nutrition Fundación Universitaria Internacional de Colombia > Research > Articles and books
Ibero-american International University > Research > Articles and books
Universidad Internacional do Cuanza > Research > Articles and books Abierto Inglés Background: Mild Cognitive Impairment (MCI) is viewed as a transitional stage between normal brain aging and dementia and is characterized by subtle cognitive deficits without significant impairment in daily functioning. Growing evidence supports the contribution of neuroinflammation and modifiable lifestyle factors, including diet, in the progression of cognitive decline.Aim: This study aimed to investigate the association between adherence to the Mediterranean diet, neuroinflammatory biomarkers, and MCI status in older adults.Design: Ninety-two participants were enrolled in this cross-sectional study, including 37 subjects with MCI. Dietary intake was assessed using a validated food frequency questionnaire (FFQ) and adherence to the Mediterranean diet explored through the MedDietScore. Plasma levels of TGF-β1 and TNF-α were measured by ELISA. Cognitive status was evaluated using the Mini Mental Examination (MMSE) and the Montreal Cognitive Assessment (MoCA), both adjusted for age and education. Statistical analyses included non-parametric tests, correlation analysis, and logistic regression models.Results: MCI patients showed significantly reduced plasma levels of TGF-β1 and increased TNF-α concentrations compared to other participants. After adjustment for potential confounding factors, greater adherence to the Mediterranean diet was associated with a lower likelihood of MCI in a dose–response manner (highest versus lowest adherence quartile, odds ratio: 0.07, 95% confidence interval: 0.01–0.60). Additional adjustment for inflammatory biomarkers attenuated the associations, suggesting a potential mediating role.Conclusion: Our findings showed that higher adherence to Mediterranean diet is associated with lower likelihood of being MCI. Such a relation might be, at least in part, mediated by inflammatory biomarkers. Overall, these results support the role of dietary modulation in preventive strategies against cognitive decline and progression into MCI. Grasso, Margherita and L’Episcopo, Francesca and Fidilio, Annamaria and Olvera-Moreira, Marco Antonio and Toscano, Giuseppe and Muratore, Stefano and Drago, Margherita and Musso, Sabrina and Bentivegna, Veronica and Costanzo, Lucrezia and Toral-Noristz, Melannie and Zambrano-Villacres, Raynier and León Brizuela, Lisandra and Lanza, Giuseppe and Ferri, Raffaele and Caraci, Filippo UNSPECIFIED
Subjects > Nutrition Fundación Universitaria Internacional de Colombia > Research > Articles and books
Ibero-american International University > Research > Articles and books
Universidad Internacional do Cuanza > Research > Articles and books Abierto Inglés Background: Mild Cognitive Impairment (MCI) is viewed as a transitional stage between normal brain aging and dementia and is characterized by subtle cognitive deficits without significant impairment in daily functioning. Growing evidence supports the contribution of neuroinflammation and modifiable lifestyle factors, including diet, in the progression of cognitive decline.Aim: This study aimed to investigate the association between adherence to the Mediterranean diet, neuroinflammatory biomarkers, and MCI status in older adults.Design: Ninety-two participants were enrolled in this cross-sectional study, including 37 subjects with MCI. Dietary intake was assessed using a validated food frequency questionnaire (FFQ) and adherence to the Mediterranean diet explored through the MedDietScore. Plasma levels of TGF-β1 and TNF-α were measured by ELISA. Cognitive status was evaluated using the Mini Mental Examination (MMSE) and the Montreal Cognitive Assessment (MoCA), both adjusted for age and education. Statistical analyses included non-parametric tests, correlation analysis, and logistic regression models.Results: MCI patients showed significantly reduced plasma levels of TGF-β1 and increased TNF-α concentrations compared to other participants. After adjustment for potential confounding factors, greater adherence to the Mediterranean diet was associated with a lower likelihood of MCI in a dose–response manner (highest versus lowest adherence quartile, odds ratio: 0.07, 95% confidence interval: 0.01–0.60). Additional adjustment for inflammatory biomarkers attenuated the associations, suggesting a potential mediating role.Conclusion: Our findings showed that higher adherence to Mediterranean diet is associated with lower likelihood of being MCI. Such a relation might be, at least in part, mediated by inflammatory biomarkers. Overall, these results support the role of dietary modulation in preventive strategies against cognitive decline and progression into MCI. Grasso, Margherita and L’Episcopo, Francesca and Fidilio, Annamaria and Olvera-Moreira, Marco Antonio and Toscano, Giuseppe and Muratore, Stefano and Drago, Margherita and Musso, Sabrina and Bentivegna, Veronica and Costanzo, Lucrezia and Toral-Noristz, Melannie and Zambrano-Villacres, Raynier and León Brizuela, Lisandra and Lanza, Giuseppe and Ferri, Raffaele and Caraci, Filippo UNSPECIFIED
Adherence to the Mediterranean diet, inflammatory biomarkers and cognitive status in older Italian adults.
Article
Subjects > Psychology
Europe University of Atlantic > Research > Articles and books
Fundación Universitaria Internacional de Colombia > Research > Articles and books
Ibero-american International University > Research > Articles and books
Ibero-american International University > Research > Articles and Books
Universidad Internacional do Cuanza > Research > Articles and books
University of La Romana > Research > Scientific Production Abierto Inglés With the growing academic pressure and competitive educational environment, students often face mental stress, which can affect their academic performance and mental health. Its accurate and timely detection and prevention is important. Traditionally, mental stress has been reported by self-assessment, which is highly subjective and can be erroneous. With advances in neuroscience, electroencephalogram (EEG) signals have been used to study brain states more objectively. EEG-based features, including time-domain, frequency-domain, and various types of connectivity features, have been used to effectively classify stress signals. However, these individual features are only able to present one aspect of the brain under stress. Several studies have combined a distinct set of features extracted from EEG signals, including time and frequency domain features, with other peripheral signals. Stress is a complex mechanism which leads to alternation in brain dynamics, its connectivity patterns and information flow. This study proposed a feature-fusion model that can effectively combine spatial features, i.e. Microstates (MS), connectivity features like Transfer Entropy (TE) and Granger Causality (GC), which provided a new neuromarker for stress classification. These features are combined with attention fusion, which enhances the discriminant features and mitigates the individual limitations within each modality. We also extracted microstates for stress-based signals. It provided a new set of microstate topomaps to study brain networks when under stress, which was not explored previously. The proposed Attention-fusion based multi-feature set is classified using Support Vector Machine, Linear Discriminant Analysis (LDA) and Multilayer Perceptron (MLP) and gave a reliable accuracy of 95.47%, 98.91%, and 83.49%, respectively. To validate the proposed method, the classification results were compared with individual and binary fusion of MS, TE and GC features, which further confirmed the robustness of the framework. This proposed feature fusion provides a more robust stress classification neuromarker, which can effectively cover the brain dynamics for accurate reporting of the underlying mental state. Ejaz, Saliha and Javed, Soyiba and Shafi, Imran and Ahmad, Jamil and Allende Monje, Samuel and Alemany Iturriaga, Josep and Choi, Jin-Ghoo and Ashraf, Imran UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, samuel.allende@uneatlantico.es, josep.alemany@uneatlantico.es, UNSPECIFIED, UNSPECIFIED
Fundación Universitaria Internacional de Colombia > Research > Articles and books
Ibero-american International University > Research > Articles and books
Ibero-american International University > Research > Articles and Books
Universidad Internacional do Cuanza > Research > Articles and books
University of La Romana > Research > Scientific Production Abierto Inglés With the growing academic pressure and competitive educational environment, students often face mental stress, which can affect their academic performance and mental health. Its accurate and timely detection and prevention is important. Traditionally, mental stress has been reported by self-assessment, which is highly subjective and can be erroneous. With advances in neuroscience, electroencephalogram (EEG) signals have been used to study brain states more objectively. EEG-based features, including time-domain, frequency-domain, and various types of connectivity features, have been used to effectively classify stress signals. However, these individual features are only able to present one aspect of the brain under stress. Several studies have combined a distinct set of features extracted from EEG signals, including time and frequency domain features, with other peripheral signals. Stress is a complex mechanism which leads to alternation in brain dynamics, its connectivity patterns and information flow. This study proposed a feature-fusion model that can effectively combine spatial features, i.e. Microstates (MS), connectivity features like Transfer Entropy (TE) and Granger Causality (GC), which provided a new neuromarker for stress classification. These features are combined with attention fusion, which enhances the discriminant features and mitigates the individual limitations within each modality. We also extracted microstates for stress-based signals. It provided a new set of microstate topomaps to study brain networks when under stress, which was not explored previously. The proposed Attention-fusion based multi-feature set is classified using Support Vector Machine, Linear Discriminant Analysis (LDA) and Multilayer Perceptron (MLP) and gave a reliable accuracy of 95.47%, 98.91%, and 83.49%, respectively. To validate the proposed method, the classification results were compared with individual and binary fusion of MS, TE and GC features, which further confirmed the robustness of the framework. This proposed feature fusion provides a more robust stress classification neuromarker, which can effectively cover the brain dynamics for accurate reporting of the underlying mental state. Ejaz, Saliha and Javed, Soyiba and Shafi, Imran and Ahmad, Jamil and Allende Monje, Samuel and Alemany Iturriaga, Josep and Choi, Jin-Ghoo and Ashraf, Imran UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, samuel.allende@uneatlantico.es, josep.alemany@uneatlantico.es, UNSPECIFIED, UNSPECIFIED
Attention-based multi-feature fusion neuromarker for EEG-driven stress classification in learners.
2024
Article
Subjects > Engineering
Subjects > Psychology Europe University of Atlantic > Research > Articles and books
Fundación Universitaria Internacional de Colombia > Research > Articles and books
Ibero-american International University > Research > Articles and books
Ibero-american International University > Research > Articles and Books
Universidad Internacional do Cuanza > Research > Articles and books Abierto Inglés Predicting depression intensity from microblogs and social media posts has numerous benefits and applications, including predicting early psychological disorders and stress in individuals or the general public. A major challenge in predicting depression using social media posts is that the existing studies do not focus on predicting the intensity of depression in social media texts but rather only perform the binary classification of depression and moreover noisy data makes it difficult to predict the true depression in the social media text. This study intends to begin by collecting relevant Tweets and generating a corpus of 210000 public tweets using Twitter public application programming interfaces (APIs). A strategy is devised to filter out only depression-related tweets by creating a list of relevant hashtags to reduce noise in the corpus. Furthermore, an algorithm is developed to annotate the data into three depression classes: ‘Mild,’ ‘Moderate,’ and ‘Severe,’ based on International Classification of Diseases-10 (ICD-10) depression diagnostic criteria. Different baseline classifiers are applied to the annotated dataset to get a preliminary idea of classification performance on the corpus. Further FastText-based model is applied and fine-tuned with different preprocessing techniques and hyperparameter tuning to produce the tuned model, which significantly increases the depression classification performance to an 84% F1 score and 90% accuracy compared to baselines. Finally, a FastText-based weighted soft voting ensemble (WSVE) is proposed to boost the model’s performance by combining several other classifiers and assigning weights to individual models according to their individual performances. The proposed WSVE outperformed all baselines as well as FastText alone, with an F1 of 89%, 5% higher than FastText alone, and an accuracy of 93%, 3% higher than FastText alone. The proposed model better captures the contextual features of the relatively small sample class and aids in the detection of early depression intensity prediction from tweets with impactful performances. Rizwan, Muhammad and Mushtaq, Muhammad Faheem and Rafiq, Maryam and Mehmood, Arif and Diez, Isabel de la Torre and Gracia Villar, Mónica and Garay, Helena and Ashraf, Imran UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, monica.gracia@uneatlantico.es, helena.garay@uneatlantico.es, UNSPECIFIED
Subjects > Psychology Europe University of Atlantic > Research > Articles and books
Fundación Universitaria Internacional de Colombia > Research > Articles and books
Ibero-american International University > Research > Articles and books
Ibero-american International University > Research > Articles and Books
Universidad Internacional do Cuanza > Research > Articles and books Abierto Inglés Predicting depression intensity from microblogs and social media posts has numerous benefits and applications, including predicting early psychological disorders and stress in individuals or the general public. A major challenge in predicting depression using social media posts is that the existing studies do not focus on predicting the intensity of depression in social media texts but rather only perform the binary classification of depression and moreover noisy data makes it difficult to predict the true depression in the social media text. This study intends to begin by collecting relevant Tweets and generating a corpus of 210000 public tweets using Twitter public application programming interfaces (APIs). A strategy is devised to filter out only depression-related tweets by creating a list of relevant hashtags to reduce noise in the corpus. Furthermore, an algorithm is developed to annotate the data into three depression classes: ‘Mild,’ ‘Moderate,’ and ‘Severe,’ based on International Classification of Diseases-10 (ICD-10) depression diagnostic criteria. Different baseline classifiers are applied to the annotated dataset to get a preliminary idea of classification performance on the corpus. Further FastText-based model is applied and fine-tuned with different preprocessing techniques and hyperparameter tuning to produce the tuned model, which significantly increases the depression classification performance to an 84% F1 score and 90% accuracy compared to baselines. Finally, a FastText-based weighted soft voting ensemble (WSVE) is proposed to boost the model’s performance by combining several other classifiers and assigning weights to individual models according to their individual performances. The proposed WSVE outperformed all baselines as well as FastText alone, with an F1 of 89%, 5% higher than FastText alone, and an accuracy of 93%, 3% higher than FastText alone. The proposed model better captures the contextual features of the relatively small sample class and aids in the detection of early depression intensity prediction from tweets with impactful performances. Rizwan, Muhammad and Mushtaq, Muhammad Faheem and Rafiq, Maryam and Mehmood, Arif and Diez, Isabel de la Torre and Gracia Villar, Mónica and Garay, Helena and Ashraf, Imran UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, monica.gracia@uneatlantico.es, helena.garay@uneatlantico.es, UNSPECIFIED
Depression Intensity Classification from Tweets Using FastText Based Weighted Soft Voting Ensemble.
2023
Article
Subjects > Teaching
Subjects > Comunication
Subjects > Psychology Europe University of Atlantic > Research > Articles and books
Fundación Universitaria Internacional de Colombia > Research > Articles and books
Ibero-american International University > Research > Articles and books
Ibero-american International University > Research > Articles and Books
Universidad Internacional do Cuanza > Research > Articles and books Abierto Inglés Communication professionals are experiencing a growing level of exposure to traumatic events as a result of their involvement in the coverage of various tragedies, including accidents, climatic disasters, rights violations, and acts of terrorism. However, it is worth noting that journalism and communication university courses often lack comprehensive instruction on effectively managing emotional challenges, anxiety, trauma, self-care, and the prevention of vicarious trauma. The objective of this study is to assess the inclusion of emotional management within the curricula of Journalism and Communication programmes offered by two universities in Catalonia, namely the University of Barcelona and the Autonomous University of Barcelona. In order to accomplish this objective, a series of semi-structured interviews were carried out with a total of twelve (12) professors who specialise in the fields of Journalism and Communication. Additionally, a thorough analysis was conducted on a set of 97 study plan guides. The results indicate that none of the participants in the interviews possess knowledge regarding any existing training programmes focused on emotional management. Furthermore, they unanimously agree on the importance of implementing such courses. The study plans did not include any subjects that were specifically dedicated to the topic of emotional management. This study presents a set of strategies aimed at creating a cross-disciplinary teaching-learning model that offers a comprehensive educational experience for students. This entails integrating precise subject matter on the previously mentioned topics, fostering critical contemplation and discourse regarding emotions within the educational setting, and advocating for ethical and sound professional behaviours. Escudero, Carolina and Prola, Thomas and Fraga, Leticia and Soriano Flores, Emmanuel UNSPECIFIED, thomas.prola@uneatlantico.es, leticia.fraga@uneatlantico.es, emmanuel.soriano@uneatlantico.es
Subjects > Comunication
Subjects > Psychology Europe University of Atlantic > Research > Articles and books
Fundación Universitaria Internacional de Colombia > Research > Articles and books
Ibero-american International University > Research > Articles and books
Ibero-american International University > Research > Articles and Books
Universidad Internacional do Cuanza > Research > Articles and books Abierto Inglés Communication professionals are experiencing a growing level of exposure to traumatic events as a result of their involvement in the coverage of various tragedies, including accidents, climatic disasters, rights violations, and acts of terrorism. However, it is worth noting that journalism and communication university courses often lack comprehensive instruction on effectively managing emotional challenges, anxiety, trauma, self-care, and the prevention of vicarious trauma. The objective of this study is to assess the inclusion of emotional management within the curricula of Journalism and Communication programmes offered by two universities in Catalonia, namely the University of Barcelona and the Autonomous University of Barcelona. In order to accomplish this objective, a series of semi-structured interviews were carried out with a total of twelve (12) professors who specialise in the fields of Journalism and Communication. Additionally, a thorough analysis was conducted on a set of 97 study plan guides. The results indicate that none of the participants in the interviews possess knowledge regarding any existing training programmes focused on emotional management. Furthermore, they unanimously agree on the importance of implementing such courses. The study plans did not include any subjects that were specifically dedicated to the topic of emotional management. This study presents a set of strategies aimed at creating a cross-disciplinary teaching-learning model that offers a comprehensive educational experience for students. This entails integrating precise subject matter on the previously mentioned topics, fostering critical contemplation and discourse regarding emotions within the educational setting, and advocating for ethical and sound professional behaviours. Escudero, Carolina and Prola, Thomas and Fraga, Leticia and Soriano Flores, Emmanuel UNSPECIFIED, thomas.prola@uneatlantico.es, leticia.fraga@uneatlantico.es, emmanuel.soriano@uneatlantico.es
Emotional Management in Journalism and Communication Studies.
2018
Revista
Subjects > Psychology
Europe University of Atlantic > Research > Scientific Magazines
Fundación Universitaria Internacional de Colombia > Research > Scientific Magazines
Ibero-american International University > Research > Scientific Magazines
Ibero-american International University > Research > Scientific Journals
Universidad Internacional do Cuanza > Research > Scientific Magazines Abierto Inglés MLS Psychology Research es una revista científica que tiene como finalidad publicar artículos originales de investigación y de revisión tanto en áreas básicas como aplicadas y metodológicas que supongan una contribución al progreso de cualquier ámbito de la psicología científica como objetivo principal. MLSPR acogerá a artículo que analicen la conducta y procesos mentales tanto de individuos como de grupos, y que abarque aspectos de la experiencia humana. MLSPR atenderá a diferentes enfoques dentro de la psicología: Psicología clínica, Psicoterapea, Psicología educativa, Psicología del desarrollo, Neuropsicología, Psicología social, etc. UNSPECIFIED mls@devnull.funiber.org
Fundación Universitaria Internacional de Colombia > Research > Scientific Magazines
Ibero-american International University > Research > Scientific Magazines
Ibero-american International University > Research > Scientific Journals
Universidad Internacional do Cuanza > Research > Scientific Magazines Abierto Inglés MLS Psychology Research es una revista científica que tiene como finalidad publicar artículos originales de investigación y de revisión tanto en áreas básicas como aplicadas y metodológicas que supongan una contribución al progreso de cualquier ámbito de la psicología científica como objetivo principal. MLSPR acogerá a artículo que analicen la conducta y procesos mentales tanto de individuos como de grupos, y que abarque aspectos de la experiencia humana. MLSPR atenderá a diferentes enfoques dentro de la psicología: Psicología clínica, Psicoterapea, Psicología educativa, Psicología del desarrollo, Neuropsicología, Psicología social, etc. UNSPECIFIED mls@devnull.funiber.org
MLS Psychology Research.
This list was generated on Sun Jul 19 01:39:04 2026 UTC.