The recreational use of nitrous oxide (N2O; laughing gas) has largely expanded in recent years. Although incidental use of nitrous oxide hardly causes any health damage, problematic or heavy use of nitrous oxide can lead to serious adverse effects. Amsterdam care centres noticed that Moroccan–Dutch young adults reported neurological symptoms, including severe paralysis, as a result of problematic nitrous oxide use. In this qualitative exploratory study, thirteen young adult Moroccan–Dutch excessive nitrous oxide users were interviewed. The determinants of problematic nitrous oxide use in this ethnic group are discussed, including their low treatment demand with respect to nitrous oxide abuse related medical–psychological problems. Motives for using nitrous oxide are to relieve boredom, to seek out relaxation with friends and to suppress psychosocial stress and negative thoughts. Other motives are depression, discrimination and conflict with friends or parents. The taboo culture surrounding substance use—mistrust, shame and macho culture—frustrates timely medical/psychological treatment of Moroccan–Dutch problematic nitrous oxide users. It is recommended to use influencers in media campaigns with the aim to decrease the risks of heavy nitrous oxide use and improve treatment access. Outreach youth workers can also play an important role in motivating socially isolated users to seek medical and or psychological help.
So-called fake news and problematic information on social media assume an increasingly important roles in political debate. Focusing on the (early) run-up to and aftermath of the 2020 U.S. presidential elections, this study examines the extent of the problematic information in the most engaged-with content and most active users in ‘political Twitter’. We demarcated three time spans, the first surrounding Super Tuesday (March 2-22, 2020), the second providing a snapshot of the aftermath of the elections and the run-up to both the Senate run-off elections in Georgia (December 24, 2020 – January 4, 2021) and the (unforeseen) Capitol Hill riots on January 6, 2021. In the third time span (March 10-21, 2021), when election activities had ceased, we examine the effects of Twitter’s deplatforming (or so-called purge) of accounts after the Capitol riots in January, 2021. In order to shed light on the magnitude of problematic information, we mapped shared sources, labelled them and assessed the actors engaged in their dissemination. It was found that overall, mainstream sources are shared more often than problematic ones, but the percentage of problematic sources was much higher in December compared to both the March, 2020 and 2021 periods. Significantly, (hyper)partisan sources are close to half of all sources shared in the first two periods, implying a robust presence of them on social media. By March 2021, both the share of problematic and of (hyper)partisan sources had decreased significantly, suggesting an impact from Twitter’s deplatforming actions. Additionally, highly active, problematic users (fake profiles, bots, or locked/suspended accounts) were found on both sides of the political spectrum, albeit more abundantly from conservative users.
Technology in general, and assistive technology in particular, is considered to be a promising opportunity to address the challenges of an aging population. Nevertheless, in health care, technology is not as widely used as could be expected. In this chapter, an overview is given of theories and models that help to understand this phenomenon. First, the design of (assistive) technologies will be addressed and the importance of human-centered design in the development of new assistive devices will be discussed. Also theories and models are addressed about technology acceptance in general. Specific attention will be given to technology acceptance in healthcare professionals, and the implementation of technology within healthcare organizations. The chapter will be based on the state of the art of scientific literature and will be illustrated with examples from our research in daily practice considering the different perspectives of involved stakeholders.
LINK
Collaborative networks for sustainability are emerging rapidly to address urgent societal challenges. By bringing together organizations with different knowledge bases, resources and capabilities, collaborative networks enhance information exchange, knowledge sharing and learning opportunities to address these complex problems that cannot be solved by organizations individually. Nowhere is this more apparent than in the apparel sector, where examples of collaborative networks for sustainability are plenty, for example Sustainable Apparel Coalition, Zero Discharge Hazardous Chemicals, and the Fair Wear Foundation. Companies like C&A and H&M but also smaller players join these networks to take their social responsibility. Collaborative networks are unlike traditional forms of organizations; they are loosely structured collectives of different, often competing organizations, with dynamic membership and usually lack legal status. However, they do not emerge or organize on their own; they need network orchestrators who manage the network in terms of activities and participants. But network orchestrators face many challenges. They have to balance the interests of diverse companies and deal with tensions that often arise between them, like sharing their innovative knowledge. Orchestrators also have to “sell” the value of the network to potential new participants, who make decisions about which networks to join based on the benefits they expect to get from participating. Network orchestrators often do not know the best way to maintain engagement, commitment and enthusiasm or how to ensure knowledge and resource sharing, especially when competitors are involved. Furthermore, collaborative networks receive funding from grants or subsidies, creating financial uncertainty about its continuity. Raising financing from the private sector is difficult and network orchestrators compete more and more for resources. When networks dissolve or dysfunction (due to a lack of value creation and capture for participants, a lack of financing or a non-functioning business model), the collective value that has been created and accrued over time may be lost. This is problematic given that industrial transformations towards sustainability take many years and durable organizational forms are required to ensure ongoing support for this change. Network orchestration is a new profession. There are no guidelines, handbooks or good practices for how to perform this role, nor is there professional education or a professional association that represents network orchestrators. This is urgently needed as network orchestrators struggle with their role in governing networks so that they create and capture value for participants and ultimately ensure better network performance and survival. This project aims to foster the professionalization of the network orchestrator role by: (a) generating knowledge, developing and testing collaborative network governance models, facilitation tools and collaborative business modeling tools to enable network orchestrators to improve the performance of collaborative networks in terms of collective value creation (network level) and private value capture (network participant level) (b) organizing platform activities for network orchestrators to exchange ideas, best practices and learn from each other, thereby facilitating the formation of a professional identity, standards and community of network orchestrators.
Performance feedback is an important mechanism of adaptation in learning theories, as it provides one of the motivations for organizations to learn (Pettit, Crossan, and Vera 2017). Embedded in the behavioral theory of the firm, organizational learning from performance feedback predicts the probability for organizations to change with an emphasis on organizational aspirations, which serve as a threshold against which absolute performance is evaluated (Cyert and March 1963; Greve 2003). It postulates that performance becomes a ‘problem’, or the trigger to search for alternative procedures, strategies, products and behaviors, when performance is below that threshold. This search is known as problemistic search. Missing from this body of research, is empirically grounded understanding if the characteristics of performance feedback over time matter for the triggering function of the feedback. I explore this gap. This investigation adds temporality as a dimension of the performance feedback concept guided by a worldview of ongoing change and flux where conditions and choices are not given, but made relevant by actors and enacted upon (Tsoukas and Chia 2002). The general aim of the study is to complement the current knowledge of performance feedback as a trigger for problemistic search with an explicit process temporal approach. The main question guiding this project is how temporal patterns of performance feedback influence organizational change, which I answer in four chapters, each zooming into one sub-question.First, I focus on the temporal order of performance feedback by examining performance feedback and change sequences organizations go through. In this section time is under study and the goal is to explore how feedback patterns have evolved over time, just as the change states organizations pass through. Second, I focus on the plurality of performance feedback by investigating performance feedback from multiple aspiration levels (i.e. multiple qualitatively different metrics and multiple reference points) and how over time clusters of performance feedback sequences have evolved. Next, I look into the rate and scope of change relative to performance feedback sequences and add an element of signal strength to the feedback. In the last chapter, time is a predictor (in the sequences), and, it is under study (in the timing of responses). I focus on the timing of organizational responses in relation to performance feedback sequences of multiple metrics and reference points.In sum, all chapters are guided by the timing problem of performance feedback, meaning that performance feedback does not come ‘available’ at a single point in time. Similarly to stones with unequal weight dropped in the river, performance feedback with different strength comes available at multiple points in time and it is plausible that sometimes it is considered by decision-makers as problematic and sometimes it is not, because of the sequence it is part of. Overall, the investigation is grounded in the general principles of organizational learning from performance feedback, and the concept of time as duration, sequences and timing, with a focus on specification of when things happen. The context of the study is universities of applied sciences and hotels in The Netherlands. Project partner: Tilburg University, School of Social and Behavioral Sciences, Department of Organization Studies
