Deep Learning Architectures and Strategies for Early Detection of Self-harm and Depression Level Prediction

[EN] This paper summarizes the contributions of the PRHLT- UPV team as a participant in the eRisk 2020 tasks on self-harm detection and prediction of depression levels from social media. Computational methods based on machine learning and natural language processing have a great potential to assist with early detection of mental disorders of social media users, based on their online activity.We use multi-dimensional representations of language, and compare various deep learning models' performance, exploring rarely approached avenues in previous research, including hierarchical deep learning architectures and pre-trained transformers and language models.The work of Paolo Rosso was in the framework of the research project PROMETEO/2019/121 (DeepPattern) by the Generalitat Valenciana.Uban, A.; Rosso, P. (2020). Deep Learning Architectures and Strategies for Early Detection of Self-harm and Depression Level Prediction. CEUR Workshop Proceedings. 2696:1-12. http://hdl.handle.net/10251/166536S112269

A call to leverage a health equity lens to accelerate human neuroscience research

Investigation of health inequities tend to be examined, in human neurosciences, as biological factors at the level of the individual. In actuality, health inequities arise, due largely in part, to deep-seated structural factors. Structural inequality refers to the systemic disadvantage of one social group compared to others with whom they coexist. The term encompasses policy, law, governance, and culture and relates to race, ethnicity, gender or gender identity, class, sexual orientation, and other domains. These structural inequalities include but are not limited to social segregation, the intergenerational effects of colonialism and the consequent distribution of power and privilege. Principles to address inequities influenced by structural factors are increasingly prevalent in a subfield of the neurosciences, i.e., cultural neurosciences. Cultural neuroscience articulates the bidirectional relationship between biology and environmental contextual factors surrounding research participants. However, the operationalization of these principles may not have the intended spillover effect on the majority of human neurosciences: this limitation is the overarching focus of the present piece. Here, we provide our perspective that these principles are missing and very much needed in all human neuroscience subdisciplines to accelerate our understanding of the human brain. Furthermore, we provide an outline of two key tenets of a health equity lens necessary for achieving research equity in human neurosciences: the social determinants of health (SDoH) framework and how to deal with confounders using counterfactual thinking. We argue that these tenets should be prioritized across future human neuroscience research more generally, and doing so is a pathway to further gain an understanding of contextual background intertwined with the human brain, thus improving the rigor and inclusivity of human neuroscience research

MENINGKATKAN HASIL BELAJAR SISWA TENTANG SERVIS ATAS DALAM PERMAINAN BOLA VOLI MENGGUNAKAN PENDEKATAN PEMBELAJARAN DRIIL DAN BERMAIN PADA SISWA KELAS V SD INPRES LAMAGEWOK

The background in this study is the low value of student learning outcomes which illustrates the low level of ability of 18 grade V students of SDI Lamagewok based on the formative test results of service on volleyball games which are below the ideal value of 5.33. Researchers want to do research in this school by implementing a drift learning approach and playing to improve activities and learning outcomes about top service in volleyball games. The Research Method uses class action. For the population and sample are the fifth grade students of SD Inpres Lamagewok, East Adonara District, East Flores Regency. The research procedures include planning, implementing, observing, and reflecting through the application of driil learning approaches and playing top service activities for fifth grade students of Lamagewok Elementary School Inpres 2016/2017 academic year. Based on the results of discussions with fellow learning colleagues on physical education subjects in class V, the increase in the results of the evaluation at the beginning (Pre Cycle) showed that the average score was very low. After improvement in learning Cycle I and Cycle II experienced a significant increase. The results of the PJOK evaluation for Volleyball games in Class V, where there were 18 students, were obtained as follows: Pre-cycle students who scored 7 and above had 6 people and a class average of 5.33 or 53%, cycle I students who scored 7 and above there are 7 people with a class average of 6 or 60%, cycle II of students who get a score of 7 and above there are 18 people with a class average of 8.22 or 82%. From the data above, there is a significant change in student learning outcomes in each cycle due to learning by using methods and approaches to learning and playing in accordance with the learning material

The implications of socioeconomic factors on salivary bioscience methodological variables in a large pediatric multi-site study

IntroductionSalivary bioscience has found increased utilization within pediatric research, given the non-invasive nature of self-collecting saliva for measuring biological markers. With this growth in pediatric utility, more understanding is needed of how social-contextual factors, such as socioeconomic factors or status (SES), influence salivary bioscience in large multi-site studies. Socioeconomic factors have been shown to influence non-salivary analyte levels across childhood and adolescent development. However, less is understood about relationships between these socioeconomic factors and salivary collection methodological variables (e.g., time of saliva collection from waking, time of day of saliva collection, physical activity prior to saliva collection, and caffeine intake prior to saliva collection). Variability in salivary methodological variables between participants may impact the levels of analytes measured in a salivary sample, thus serving as a potential mechanism for non-random systematic biases in analytes.MethodsOur objective is to examine relationships between socioeconomic factors and salivary bioscience methodological variables within the Adolescent Brain Cognitive Development Study© cohort of children aged 9–10 years old (n = 10,567 participants with saliva samples).ResultsWe observed significant associations between household socioeconomic factors (poverty status, education) and salivary collection methodological variables (time since waking, time of day of sampling, physical activity, and caffeine intake). Moreover, lower levels of household poverty and education were significantly associated with more sources of potential bias in salivary collection methodological variables (e.g., longer times since waking, collections later in the day, higher odds of caffeine consumption, and lower odds of physical activity). Consistent associations were not observed with neighborhood socioeconomic factors and salivary methodological variables.DiscussionPrevious literature demonstrates associations between collection methodological variables and measurements of salivary analyte levels, particularly with analytes that are more sensitive to circadian rhythms, pH levels, or rigorous physical activity. Our novel findings suggest that unintended distortions in measured salivary analyte values, potentially resulting from the non-random systematic biases in salivary methodology, need to be intentionally incorporated into analyses and interpretation of results. This is particularly salient for future studies interested in examining underlying mechanisms of childhood socioeconomic health inequities in future analyses

An emotion and cognitive based analysis of mental health disorders from social media data

[EN] Mental disorders can severely affect quality of life, constitute a major predictive factor of suicide, and are usually underdiagnosed and undertreated. Early detection of signs of mental health problems is particularly important, since unattended, they can be life-threatening. This is why a deep understanding of the complex manifestations of mental disorder development is important. We present a study of mental disorders in social media, from different perspectives. We are interested in understanding whether monitoring language in social media could help with early detection of mental disorders, using computational methods. We developed deep learning models to learn linguistic markers of disorders, at different levels of the language (content, style, emotions), and further try to interpret the behavior of our models for a deeper understanding of mental disorder signs. We complement our prediction models with computational analyses grounded in theories from psychology related to cognitive styles and emotions, in order to understand to what extent it is possible to connect cognitive styles with the communication of emotions over time. The final goal is to distinguish between users diagnosed with a mental disorder and healthy users, in order to assist clinicians in diagnosing patients. We consider three different mental disorders, which we analyze separately and comparatively: depression, anorexia, and self-harm tendencies.The authors thank the EU-FEDER Comunitat Valenciana 2014- 2020 grant IDIFEDER/2018/025. The work of Paolo Rosso was in the framework of the research project PROMETEO/2019/121 (DeepPattern) by the Generalitat Valenciana.Uban, A.; Chulvi-Ferriols, MA.; Rosso, P. (2021). An emotion and cognitive based analysis of mental health disorders from social media data. Future Generation Computer Systems. 124:480-494. https://doi.org/10.1016/j.future.2021.05.032S48049412

Behavioral and psychosocial factors related to mental distress among medical students

IntroductionPhysicians die by suicide at rates higher than the general population, with the increased risk beginning in medical school. To better understand why, this study examined the prevalence of mental distress (e.g., depressive symptoms and suicide risk) and behavioral and psychosocial risk factors for distress, as well as the associations between mental distress and risk factors among a sample of medical students in a pre–COVID-19-era.MethodsStudents enrolled in a large California medical school in 2018–2019 (N = 134; 52% female) completed questionnaires assessing sociodemographic characteristics, depression and suicide family history, health behaviors, and psychosocial wellbeing. Assessment scores indexing mental distress (e.g., depressive symptoms, thoughts of suicide in the past 12 months, suicide risk, and history of suicidality) and risk factors (e.g., stress, subjective sleep quality, alcohol use, impostor feelings, and bill payment difficulty) were compared across biological sex using chi-squared tests, and associations between mental distress and risk factors were determined through logistic regression.ResultsElevated mental distress indicators were observed relative to the general public (e.g., 16% positive depression screen, 17% thought about suicide in previous 12 months, 10% positive suicide risk screen, and 34% history of suicidality), as well as elevated risk factors [e.g., 55% moderate or high stress, 95% at least moderate impostor feelings, 59% poor sleep quality, 50% screened positive for hazardous drinking (more likely in females), and 25% difficulty paying bills]. A positive depression screen was associated with higher stress, higher impostor feelings, poorer sleep quality, and difficulty paying bills. Suicidal ideation in the previous 12 months, suicide risk, and a history of suicidality were independently associated with higher levels of impostor feelings.DiscussionHigher scores on assessments of depressive symptoms and suicidal thoughts and behaviors were related to several individual-level and potentially modifiable risk factors (e.g., stress, impostor feelings, sleep quality, and bill payment difficulties). Future research is needed to inform customized screening and resources for the wellbeing of the medical community. However, it is likely that the modification of individual-level risk factors is limited by the larger medical culture and systems, suggesting that successful interventions mitigate suicide risk for medical providers need to address multiple socio-ecological levels

COMUNICACIÓN ASERTIVA DE LA DIRIGENCIA PARA EL FORTALECIMIENTO DEL RENDIMIENTO DEPORTIVO DEL EQUIPO DE UN CLUB DE VOLEIBOL

Un psicólogo deportivo busca optimizar la salud física del deportista con el bienestar mental y permitir así un mejor rendimiento. Se trabajan los recursos psicológicos del mismo deportista (gestión de la tensión y de la concentración, control de expectativas, orientación motivacional, otros). Gracias a los excelentes resultados que ofrece la aplicación de la psicología en el deporte, esta práctica se ha convertido en una tendencia que cada día capta más seguidores, ya que ha demostrado alta efectividad tanto a nivel profesional como aficionado. En tal sentido, el presente trabajo tuvo como propósito aplicar estrategias para fomentar la Comunicación Asertiva de la Dirigencia para el fortalecimiento del rendimiento deportivo del equipo de voleibol femenino del club de voleibol “La Montaña” Turmero, Edo. Aragua. Desde el punto de vista metodológico se fundamentó en el paradigma Postpositivismo, enfoque Cualitativo, bajo el método de Investigación Acción Participativa, tomando como sujetos de estudio los dirigentes y atletas del equipo de voleibol femenino del club de voleibol “La Montaña”. Utilizando como diseño de la recolección de la información de la presente investigación, se realizó a través de los grupos focales; a quienes se les aplicó una clínica deportiva con resultados satisfactorios para todos los involucrados