BACKGROUND: The number of mobile apps that support smoking cessation is growing, indicating the potential of the mobile phone as a means to support cessation. Knowledge about the potential end users for cessation apps results in suggestions to target potential user groups in a dissemination strategy, leading to a possible increase in the satisfaction and adherence of cessation apps.OBJECTIVE: This study aimed to characterize potential end users for a specific mobile health (mHealth) smoking cessation app.METHODS: A quantitative study was conducted among 955 Dutch smokers and ex-smokers. The respondents were primarily recruited from addiction care facilities and hospitals through Web-based media via websites and forums. The respondents were surveyed on their demographics, smoking behavior, and personal innovativeness. The intention to use and the attitude toward a cessation app were determined on a 5-point Likert scale. To study the association between the characteristics and intention to use and attitude, univariate and multivariate ordinal logistic regression analyses were performed.RESULTS: The multivariate ordinal logistic regression showed that the number of previous quit attempts (odds ratio [OR] 4.1, 95% CI 2.4-7.0, and OR 3.5, 95% CI 2.0-5.9) and the score on the Fagerstrom Test of Nicotine Dependence (OR 0.8, 95% CI 0.8-0.9, and OR 0.8, 95% CI 0.8-0.9) positively correlates with the intention to use a cessation app and the attitude toward cessation apps, respectively. Personal innovativeness also positively correlates with the intention to use (OR 0.3, 95% CI 0.2-0.4) and the attitude towards (OR 0.2, 95% CI 0.1-0.4) a cessation app. No associations between demographics and the intention to use or the attitude toward using a cessation app were observed.CONCLUSIONS: This study is among the first to show that demographic characteristics such as age and level of education are not associated with the intention to use and the attitude toward using a cessation app when characteristics related specifically to the app, such as nicotine dependency and the number of quit attempts, are present in a multivariate regression model. This study shows that the use of mHealth apps depends on characteristics related to the content of the app rather than general user characteristics.
Standard SARS-CoV-2 testing protocols using nasopharyngeal/throat (NP/T) swabs are invasive and require trained medical staff for reliable sampling. In addition, it has been shown that PCR is more sensitive as compared to antigen-based tests. Here we describe the analytical and clinical evaluation of our in-house RNA extraction-free saliva-based molecular assay for the detection of SARS-CoV-2. Analytical sensitivity of the test was equal to the sensitivity obtained in other Dutch diagnostic laboratories that process NP/T swabs. In this study, 955 individuals participated and provided NP/T swabs for routine molecular analysis (with RNA extraction) and saliva for comparison. Our RT-qPCR resulted in a sensitivity of 82,86% and a specificity of 98,94% compared to the gold standard. A false-negative ratio of 1,9% was found. The SARS-CoV-2 detection workflow described here enables easy, economical, and reliable saliva processing, useful for repeated testing of individuals.
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This project develops a European network for transdisciplinary innovation in artistic engagement as a catalyst for societal transformation, focusing on immersive art. It responds to the professionals in the field’s call for research into immersive art’s unique capacity to ‘move’ people through its multisensory, technosocial qualities towards collective change. The project brings together experts leading state-of-the-art research and practice in related fields with an aim to develop trajectories for artistic, methodological, and conceptual innovation for societal transformation. The nascent field of immersive art, including its potential impact on society, has been identified as a priority research area on all local-to-EU levels, but often suffers from the common (mis)perception as being technological spectacle prioritising entertainment values. Many practitioners create immersive art to enable novel forms of creative engagement to address societal issues and enact change, but have difficulty gaining recognition and support for this endeavour. A critical challenge is the lack of knowledge about how their predominantly sensuous and aesthetic experience actually lead to collective change, which remains unrecognised in the current systems of impact evaluation predicated on quantitative analysis. Recent psychological insights on awe as a profoundly transformative emotion signals a possibility to address this challenge, offering a new way to make sense of the transformational effect of directly interacting with such affective qualities of immersive art. In parallel, there is a renewed interest in the practice of cultural mediation, which brings together different stakeholders to facilitate negotiation towards collective change in diverse domains of civic life, often through creative engagements. Our project forms strategic grounds for transdisciplinary research at the intersection between these two developments. We bring together experts in immersive art, psychology, cultural mediation, digital humanities, and design across Europe to explore: How can awe-experiences be enacted in immersive art and be extended towards societal transformation?
DISTENDER will provide integrated strategies by building a methodological framework that guide the integration of climate change(CC) adaptation and mitigation strategies through participatory approaches in ways that respond to the impacts and risks of climatechange (CC), supported by quantitative and qualitative analysis that facilitates the understanding of interactions, synergies and tradeoffs.Holistic approaches to mitigation and adaptation must be tailored to the context-specific situation and this requires a flexibleand participatory planning process to ensure legitimate and salient action, carried out by all important stakeholders. DISTENDER willdevelop a set of multi-driver qualitative and quantitative socio-economic-climate scenarios through a facilitated participatory processthat integrates bottom-up knowledge and locally-relevant drivers with top-down information from the global European SharedSocioeconomic Pathways (SSPs) and downscaled Representative Concentration Pathways (RCPs) from IPCC. A cross-sectorial andmulti-scale impact assessment modelling toolkit will be developed to analyse the complex interactions over multiple sectors,including an economic evaluation framework. The economic impact of the different efforts will be analyse, including damage claimsettlement and how do sectoral activity patterns change under various scenarios considering indirect and cascading effects. It is aninnovative project combining three key concepts: cross-scale, integration/harmonization and robustness checking. DISTENDER willfollow a pragmatic approach applying methodologies and toolkits across a range of European case studies (six core case studies andfive followers) that reflect a cross-section of the challenges posed by CC adaptation and mitigation. The knowledge generated byDISTENDER will be offered by a Decision Support System (DSS) which will include guidelines, manuals, easy-to-use tools andexperiences from the application of the cases studies.
Receiving the first “Rijbewijs” is always an exciting moment for any teenager, but, this also comes with considerable risks. In the Netherlands, the fatality rate of young novice drivers is five times higher than that of drivers between the ages of 30 and 59 years. These risks are mainly because of age-related factors and lack of experience which manifests in inadequate higher-order skills required for hazard perception and successful interventions to react to risks on the road. Although risk assessment and driving attitude is included in the drivers’ training and examination process, the accident statistics show that it only has limited influence on the development factors such as attitudes, motivations, lifestyles, self-assessment and risk acceptance that play a significant role in post-licensing driving. This negatively impacts traffic safety. “How could novice drivers receive critical feedback on their driving behaviour and traffic safety? ” is, therefore, an important question. Due to major advancements in domains such as ICT, sensors, big data, and Artificial Intelligence (AI), in-vehicle data is being extensively used for monitoring driver behaviour, driving style identification and driver modelling. However, use of such techniques in pre-license driver training and assessment has not been extensively explored. EIDETIC aims at developing a novel approach by fusing multiple data sources such as in-vehicle sensors/data (to trace the vehicle trajectory), eye-tracking glasses (to monitor viewing behaviour) and cameras (to monitor the surroundings) for providing quantifiable and understandable feedback to novice drivers. Furthermore, this new knowledge could also support driving instructors and examiners in ensuring safe drivers. This project will also generate necessary knowledge that would serve as a foundation for facilitating the transition to the training and assessment for drivers of automated vehicles.
