Aims. The aim of this study is to gain insight into the level of emotional intelligence of mental health nurses in the Netherlands. Background. The focus in research on emotional intelligence to date has been on a variety of professionals. However, little is known about emotional intelligence in mental health nurses. Method. The emotional intelligence of 98 Dutch nurses caring for psychiatric patients is reported. Data were collected with the Bar-On Emotional Quotient Inventory within a cross-sectional research design. Results. The mean level of emotional intelligence of this sample of professionals is statistically significant higher than the emotional intelligence of the general population. Female nurses score significantly higher than men on the subscales Empathy, Social Responsibility, Interpersonal Relationship, Emotional Self-awareness, Self-Actualisation and Assertiveness. No correlations are found between years of experience and age on the one hand and emotional intelligence on the other hand. Conclusions. The results of this study show that nurses in psychiatric care indeed score above average in the emotional intelligence required to cope with the amount of emotional labour involved in daily mental health practice. Relevance to clinical practice. The ascertained large range in emotional intelligence scores among the mental health nurses challenges us to investigate possible implications which higher or lower emotional intelligence levels may have on the quality of care. For instance, a possible relation between the level of emotional intelligence and the quality of the therapeutic nurse–patient relationship or the relation between the level of emotional intelligence and the manner of coping with situations characterised by a great amount of emotional labour (such as caring for patients who self-harm or are suicidal).
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With artificial intelligence (AI) systems entering our working and leisure environments with increasing adaptation and learning capabilities, new opportunities arise for developing hybrid (human-AI) intelligence (HI) systems, comprising new ways of collaboration. However, there is not yet a structured way of specifying design solutions of collaboration for hybrid intelligence (HI) systems and there is a lack of best practices shared across application domains. We address this gap by investigating the generalization of specific design solutions into design patterns that can be shared and applied in different contexts. We present a human-centered bottom-up approach for the specification of design solutions and their abstraction into team design patterns. We apply the proposed approach for 4 concrete HI use cases and show the successful extraction of team design patterns that are generalizable, providing re-usable design components across various domains. This work advances previous research on team design patterns and designing applications of HI systems.
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Worldwide, schools implement social-emotional learning programs to enhance students' social-emotional skills. Although parents play an essential role in teaching these skills, knowledge about their perspectives on social-emotional learning is limited. In providing insight into the perspectives of parents from adolescent students this paper adds to this knowledge. An explorative qualitative study was conducted to gain insight into parents' perspectives on adolescent social-emotional learning. A broadly used professional framework for social emotional learning was used as a frame of reference in interviews with parents from diverse backgrounds. Within and across case analyses were applied to analyze the interviews. A conceptual model of four social-emotional skills constructs considered crucial learning by parents emerged from the data: respectful behavior, cooperation, self-knowledge and self-reliance. Parents' language, interpretations and orderings of skills indicate that the model underlying these constructs differs from skills embedded in the professional framework.
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