Despite growing popular interest for the mental health of electronic music artists, scientific research addressing this topic has remained largely absent. As such, the aim of the current study was to examine the mental health of electronic music artists, as well as a number of determinants. Using a cross-sectional quantitative design, a total of 163 electronic music artists participated in this study. In line with the two-continua model of mental health, both symptoms of depression/anxiety and well-being were adopted as indicators for mental health. Furthermore, standardized measures were used to assess potential determinants of mental health, including sleep disturbance, music performance anxiety, alcohol abuse, drug abuse, occupational stress, resilience, and social support. Results highlighted that around 30% of participants experienced symptoms of depression/anxiety. Nevertheless, the majority of these participants still demonstrated at least moderate levels of functioning and well-being. Sleep disturbance formed a significant predictor for both symptoms of depression/anxiety and well-being. Furthermore, resilience and social support were significant predictors for well-being. The results provide a first glimpse into the mental health challenges experienced by electronic music artists and support the need for increased research as well as applied initiatives directed at safeguarding their mental health.
This article describes the relation between mental health and academic performance during the start of college and how AI-enhanced chatbot interventions could prevent both study problems and mental health problems.
Background:Victimization among children is associated with adverse effects on their physical and psychological health. Many health complaints follow as a result of bullying and anxiety and depression also precede bullying. The Dutch school-wide antibullying program ‘Prima’ was developed based on techniques and scientific insights that are known to be effective. In this randomized trial we investigate the effects of school-wide antibullying program on bullying behavior and self-esteem and depression.Methods:A total of 4,229 students of grade 3 to 6 of 31 primary schoolsparticipated in this study. The schools were randomly assigned to three conditions. Condition A was offered a teachertraining, an online screening tool for bullying behavior, and a set of practice- and evidence-based guidelines to deal with difficult bullying situations. Condition B included all of condition A plus a series of eight lessons for the students. Condition C was the control group. A questionnaire was filled out by the students before and after the intervention.Results:Results from the pretest showed that 16% of the students was bullied regularly. There was a significant difference between bullied and non-bullied children in their reported mental health. Bullied students indicated much more depressive symptoms compared to non-bullied students (3,67 vs 1,67, p= .000). Bullied children also indicated lower self-esteem (16,74 vs 19,84, p = .000). The effects of the intervention program are currently analyzed and will be presented at the conference in the fall of 2018.Conclusions:Bullying is strongly related to mental health issues among children. To address mental health issues among youth, schools should focus on evidence-based anti-bullying programs as a vital part of a wider school policy.Key messages:-Bullying has a strong impact on the wellbeing and mental health of children.-School programs focused on preventing bullying can therefore reduce health complaints among children.
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Horse riding falls under the “Sport for Life” disciplines, where a long-term equestrian development can provide a clear pathway of developmental stages to help individuals, inclusive of those with a disability, to pursue their goals in sport and physical activity, providing long-term health benefits. However, the biomechanical interaction between horse and (disabled) rider is not wholly understood, leaving challenges and opportunities for the horse riding sport. Therefore, the purpose of this KIEM project is to start an interdisciplinary collaboration between parties interested in integrating existing knowledge on horse and (disabled) rider interaction with any novel insights to be gained from analysing recently collected sensor data using the EquiMoves™ system. EquiMoves is based on the state-of-the-art inertial- and orientational-sensor system ProMove-mini from Inertia Technology B.V., a partner in this proposal. On the basis of analysing previously collected data, machine learning algorithms will be selected for implementation in existing or modified EquiMoves sensor hardware and software solutions. Target applications and follow-ups include: - Improving horse and (disabled) rider interaction for riders of all skill levels; - Objective evidence-based classification system for competitive grading of disabled riders in Para Dressage events; - Identifying biomechanical irregularities for detecting and/or preventing injuries of horses. Topic-wise, the project is connected to “Smart Technologies and Materials”, “High Tech Systems & Materials” and “Digital key technologies”. The core consortium of Saxion University of Applied Sciences, Rosmark Consultancy and Inertia Technology will receive feedback to project progress and outcomes from a panel of international experts (Utrecht University, Sport Horse Health Plan, University of Central Lancashire, Swedish University of Agricultural Sciences), combining a strong mix of expertise on horse and rider biomechanics, veterinary medicine, sensor hardware, data analysis and AI/machine learning algorithm development and implementation, all together presenting a solid collaborative base for derived RAAK-mkb, -publiek and/or -PRO follow-up projects.
Digital innovations in the field of immersive Augmented Reality (AR) can be a solution to offer adults who are mentally, physically or financially unable to attend sporting events such as premier league football a stadium and match experience. This allows them to continue to connect with their social networks. In the intended project, AR content will be further developed with the aim of evoking the stadium experience of home matches as much as possible. The extent to which AR enriches the experience is then tested in an experiment, in which the experience of a football match with and without AR enrichment is measured in a stadium setting and in a home setting. The experience is measured with physiological signals. In addition, a subjective experience measure is also being developed and benchmarked (the experience impact score). Societal issueInclusion and health: The joint experience of (top) sports competitions forms a platform for vulnerable adults, with a limited social capital, to build up and maintain the social networks that are so necessary for them. AR to fight against social isolation and loneliness.
The ELSA AI lab Northern Netherlands (ELSA-NN) is committed to the promotion of healthy living, working and ageing. By investigating cultural, ethical, legal, socio-political, and psychological aspects of the use of AI in different decision-makingcontexts and integrating this knowledge into an online ELSA tool, ELSA-NN aims to contribute to knowledge about trustworthy human-centric AI and development and implementation of health technology innovations, including AI, in theNorthern region.The research in ELSA-NN will focus on developing and mapping ELSA knowledge around three general concepts of importance for the development, monitoring and implementation of trustworthy and human-centric AI: availability, use,and performance. These concepts will be explored in two lines of research: 1) use case research investigating the use of different AI applications with different types of data in different decision-making contexts at different time periods duringthe life course, and 2) an exploration among stakeholders in the Northern region of needs, knowledge, (digital) health literacy, attitudes and values concerning the use of AI in decision-making for healthy living, working and ageing. Specificfocus will be on investigating low social economic status (SES) perspectives, since health disparities between high and low SES groups are growing world-wide, including in the Northern region and existing health inequalities may increase with theintroduction and use of innovative health technologies such as AI.ELSA-NN will be integrated within the AI hub Northern-Netherlands, the Health Technology Research & Innovation Cluster (HTRIC) and the Data Science Center in Health (DASH). They offer a solid base and infrastructure for the ELSA-NNconsortium, which will be extended with additional partners, especially patient/citizens, private, governmental and researchrepresentatives, to have a quadruple-helix consortium. ELSA-NN will be set-up as a learning health system in which much attention will be paid to dialogue, communication and education.
