De publicatielijst bevat alle publicaties waar Berno van Meijel aan bijgedragen heeft
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There is an upsurge in the use of mobile phones among higher education students in Ghana, which may result in the nomophobia prevalence with the students. Therefore, the need to assess the influence of nomophobia within the student population in Ghana. This descriptive cross-sectional study investigated the prevalence of nomophobia and the sociodemographic variables, and the association with academic achievement of the understudied population. A self-reporting nomophobia questionnaire, composed of 20 dimensions, was answered by 670 university students to measure the nomophobia prevalence. Raw data were estimated using descriptive statistics, and one-way ANOVA and Independent T-test. While the findings showed diverse grades of nomophobia, statistical significance between academic achievement and the level of nomophobia was observed. This study concludes that there is a high nomophobia prevalence among university students in Ghana as the use of smartphones increases. However, follow-up studies should be conducted in Ghanaian universities to monitor nomophobia and its associates in order to reduce the adverse effects of habitual use of smartphones.
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Abstract: Background: Little is known about frailty among patients hospitalized with heart failure (HF). To date, the limited information on frailty in HF is based on a unidimensional view of frailty, in which only physical aspects are considered when determining frailty. The aims of this study were to study different dimensions of frailty (physical, psychological and social) in patients with HF and the effect of different dimensions of frailty on the incidence of heart failure. Methods: The study used a cross-sectional design and included 965 patients hospitalized for heart failure and 164 healthy controls. HF was defined according to the ESC guidelines. The Tilburg Frailty Indicator (TFI) was used to assess frailty. Probit regression analyses and chi-square statistics were used to examine associations between the occurrence of heart failure and TFI domains of frailty. Results: Patients diagnosed with frailty were 15.3% more likely to develop HF compared to those not diagnosed with frailty (p < 0.001). An increase in physical, psychological and social frailty corresponded to an increased risk of HF of 2.9% (p < 0.001), 4.4% (p < 0.001) and 6.6% (p < 0.001), respectively. Conclusions: We found evidence of the association between different dimensions of frailty and incidence of HF.
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Aim: In-hospital prescribing errors (PEs) may result in patient harm, prolonged hospitalization and hospital (re)admission. These events are associated with pressure on healthcare services and significant healthcare costs. To develop targeted interventions to prevent or reduce in-hospital PEs, identification and understanding of facilitating and protective factors influencing in-hospital PEs in current daily practice is necessary, adopting a Safety-II perspective. The aim of this systematic review was to create an overview of all factors reported in the literature, both protective and facilitating, as influencing in-hospital PEs. Methods: PubMed, EMBASE.com and the Cochrane Library (via Wiley) were searched, according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement, for studies that identified factors influencing in-hospital PEs. Both qualitative and quantitative study designs were included. Results: Overall, 19 articles (6 qualitative and 13 quantitative studies) were included and 40 unique factors influencing in-hospital PEs were identified. These factors were categorized into five domains according to the Eindhoven classification (‘organization-related’, ‘prescriber-related’, ‘prescription-related’, ‘technologyrelated’ and ‘unclassified’) and visualized in an Ishikawa (Fishbone) diagram. Most of the identified factors (87.5%; n = 40) facilitated in-hospital PEs. The most frequently identified facilitating factor (39.6%; n = 19) was ‘insufficient (drug) knowledge, prescribing skills and/or experience of prescribers’. Conclusion: The findings of this review could be used to identify points of engagement for future intervention studies and help hospitals determine how to optimize prescribing. A multifaceted intervention, targeting multiple factors might help to circumvent the complex challenge of in-hospital PEs.
MULTIFILE
Light profoundly impacts many aspects of human physiology and behaviour, including the synchronization of the circadian clock, the production of melatonin, and cognition. These effects of light, termed the non-visual effects of light, have been primarily investigated in laboratory settings, where light intensity, spectrum and timing can be carefully controlled to draw associations with physiological outcomes of interest. Recently, the increasing availability of wearable light loggers has opened the possibility of studying personal light exposure in free-living conditions where people engage in activities of daily living, yielding findings associating aspects of light exposure and health outcomes, supporting the importance of adequate light exposure at appropriate times for human health. However, comprehensive protocols capturing environmental (e.g., geographical location, season, climate, photoperiod) and individual factors (e.g., culture, personal habits, behaviour, commute type, profession) contributing to the measured light exposure are currently lacking. Here, we present a protocol that combines smartphone-based experience sampling (experience sampling implementing Karolinska Sleepiness Scale, KSS ratings) and high-quality light exposure data collection at three body sites (near-corneal plane between the two eyes mounted on spectacle, neck-worn pendant/badge, and wrist-worn watch-like design) to capture daily factors related to individuals’ light exposure. We will implement the protocol in an international multi-centre study to investigate the environmental and socio-cultural factors influencing light exposure patterns in Germany, Ghana, Netherlands, Spain, Sweden, and Turkey (minimum n = 15, target n = 30 per site, minimum n = 90, target n = 180 across all sites). With the resulting dataset, lifestyle and context-specific factors that contribute to healthy light exposure will be identified. This information is essential in designing effective public health interventions.
MULTIFILE
From the article : "Based on a review of recent literature, this paper addresses the question of how urban planners can steer urban environmental quality, given the fact that it ismultidimensional in character, is assessed largely in subjective terms and varies across time. A novel perspective of urban environmental quality is proposed, simultaneously exploring three questions that are at the core of planning and designing cities: ‘quality of what?’, ‘quality for whom?’ and ‘quality at what time?’. The dilemmas that urban planners face in answering these questions are illustrated using secondary material. This approach provides perspectives for action. Rather than further detailing the exact nature of urban quality, it calls for sustainable urban environmental quality planning that is integrated, participative and adaptive" ( wileyonlinelibrary.com ) DOI: 10.1002/eet.1759 - Preprint available for free download.
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