Health interventions often do not reach blue-collar workers. Citizen science engages target groups in the design and execution of health interventions, but has not yet been applied in an occupational setting. This preliminary study determines barriers and facilitators and feasible elements for citizen science to improve the health of blue-collar workers. The study was conducted in a terminal and construction company by performing semi-structured interviews and focus groups with employees, company management and experts. Interviews and focus groups were analyzed using thematic content analysis and the elements were pilot tested. Workers considered work pressure, work location and several personal factors as barriers for citizen science at the worksite, and (lack of) social support and (negative) social culture both as barriers and facilitators. Citizen science to improve health at the worksite may include three elements: (1) knowledge and skills, (2) social support and social culture, and (3) awareness about lifestyle behaviors. Strategies to implement these elements may be company specific. This study provides relevant indications on feasible elements and strategies for citizen science to improve health at the worksite. Further studies on the feasibility of citizen science in other settings, including a larger and more heterogeneous sample of blue-collar workers, are necessary.
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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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.
