Search

Background: Diagnosis of infected individuals with Mycoplasma genitalium (MG) is often performed by real-time PCR or transcription-mediated amplification (TMA). A limitation of the MG-TMA assay is the relatively short time span of 24 h in which the collected urine is required to be transferred into a Urine Specimen Transport Tube, according to the manufacturer's guidelines. If not transferred within 24 h, the manufacturer's claimed sensitivity cannot be guaranteed anymore, and samples may instead be tested with an in-house validated real-time PCR, despite its recognized lower sensitivity. This study aimed to validate an exception to the sample transport and storage conditions of the MG-TMA assay as set by the manufacturer, being the prolongation of the acceptable testing time limit of 24 h. Methods: From June to December 2022, first-void urines were collected from clients attending the clinic for sexual health in Amsterdam, the Netherlands. Urine samples that tested positive for MG by TMA assay at the day of collection were concomitantly stored at room (18–24 °C) and refrigerator temperature (4–8 °C) for 15 days. The stored urine samples were tested with both an in-house validated real-time PCR and MG-TMA assay after transfer of the original urine samples to the respective test tubes at 3, 7, 12 and 15 days post collection. Results: In total, 47 MG-positive urine samples were collected, stored and tested for MG by real-time PCR and TMA assays. After storage at room temperature, the MG-detection rate by TMA was significantly higher compared to real-time PCR, at days 0 (p ≤ 0.001), 7 (p ≤ 0.001) and 12 (p < 0.05). After storage at refrigerator temperature, the MG-detection rate determined by TMA assay was significantly enhanced in comparison with real-time PCR at days 3 (p < 0.01), 7 (p ≤ 0.001) and 15 (p < 0.01). Conclusions: This validation study showed that the MG-TMA assay has a superior detection rate in urine compared to real-time PCR, up to 15 days post sample collection and irrespective of storage temperature. Accepting urines older than 24 h to be tested by TMA will improve clinical diagnosis of MG infections. [ABSTRACT FROM AUTHOR]

Background: It has often been suggested that high levels of overtime lead to adverse health outcomes. One mechanism that may account for this association is that working overtime leads to elevated levels of stress, which could affect worker's behavioral decisions or habits (such as smoking and lack of physical activity). In turn, this could lead to adverse health. Purpose: The present study examined this reasoning in a prospective longitudinal design. Data from the prospective 2-year Study on Health at Work ( N = 649) were used to test our hypotheses. Methods: Structural equation analysis was used to examine the relationships among overtime, beneficial (exercising, intake of fruit and vegetables) and risky (smoking and drinking) health behaviors, and health indicators (BMI and subjective health). Results: Working overtime was longitudinally related with adverse subjective health, but not with body mass. Moreover, working overtime was associated with lower levels of physical activity and intake of fruit and vegetables, but not with smoking and drinking. Finally, higher levels of risky and lower levels of beneficial health behaviors were longitudinally associated with ill health. Conclusions: The relation between overtime and ill health is partly accounted for by the unhealthy lifestyle in which overworkers tend to engage. However, a direct longitudinal effect of overtime on health suggested that the effects of overtime on health may also partly be due to the sustained physiological activation that results from working overtime. Whereas working a moderate amount of overtime does not usually entail major health risks, these will increase with increasing overtime. [ABSTRACT FROM AUTHOR]

This study examined whether worktime control buffered the impact of worktime demands on work–family interference (WFI), using data from 2,377 workers from various sectors of industry in The Netherlands. We distinguished among three types of worktime demands: time spent on work according to one’s contract (contractual hours), the number of hours spent on overtime work (overtime hours), and the number of hours spent on commuting (commuting hours). Regarding worktime control, a distinction was made between having control over days off and vacations (leave control) and having control over starting and finishing times (flextime). These three worktime demands were expected to have separate as well as joint effects on WFI, whereas worktime control should buffer these adverse effects of worktime demands on WFI. Stepwise regression analyses showed that working high numbers of contractual and overtime hours was indeed associated with high WFI. Further, worktime control indeed made a difference in terms of WFI: whereas leave control contributed directly to lower WFI, flextime buffered the adverse effects of long contractual workhours. Our results suggest that very long working days should be prevented, and that worktime control may be a powerful tool to help workers maintaining a good work–family balance. [ABSTRACT FROM AUTHOR]

Utilisation of operating rooms is high on the agenda of hospital managers and researchers. Many efforts in the area of maximising the utilisation have been focussed on finding the holy grail of 100% utilisation. The utilisation that can be realised, however, depends on the patient mix and the willingness to accept the risk of working in overtime. This is a mathematical modelling study that investigates the association between the utilisation and the patient mix that is served and the risk of working in overtime. Prospectively, consecutively, and routinely collected data of an operating room department in a Dutch university hospital are used. Basic statistical principles are used to establish the relation between realistic utilisation rates, patient mixes, and accepted risk of overtime. Accepting a low risk of overtime combined with a complex patient mix results a low utilisation rate. If the accepted risk of overtime is higher and the patient mix is less complex, the utilisation rate that can be reached is closer to 100%. Because of the inherent variability of health-care processes, the holy grail of 100% utilisation is unlikely to be found. The method proposed in this paper calculates a realistic benchmark utilisation that incorporates the patient mix characteristics and the willingness to accept risk of overtime. [ABSTRACT FROM AUTHOR]

This paper investigates the co-evolution of industry formation, innovation systems and context over time through an analysis of offshore wind in the Netherlands and Norway. We compare these two countries because of their historically weak domestic offshore wind markets, long legacies in the oil and gas (O&G) and maritime industries and active participation in the growing offshore wind market. Our analysis is informed by the technological innovation systems framework and context conditions and we derive our results from nearly 60 interviews with key stakeholders in both countries. Our results point to three main empirical findings: 1) The Netherlands focused much more on explicit innovation system building strategies than Norway; 2) O&G is a critical sectoral and political context condition with a profound impact on offshore wind in both countries: in Norway, O&G price shocks led to fluctuating offshore wind participation; in the Netherlands, offshore O&G has been on a decline since the early 2000s, leading to a constant pressure to diversify. 3) The Netherlands had closer industrial proximity alignment than Norway, leading to stronger innovation system emergence and industrial participation. We highlight three theoretical contributions: 1) Certain context conditions – in our case O&G sectoral and political contexts – play a stronger role than others in influencing TIS emergence; 2) Context conditions strongly overlap. The political and sectoral O&G context is intimately linked; 3) Contexts are not static. As context conditions evolve overtime, so do their effects on the innovation system. • Varying context conditions affect the emergence of innovation systems in different ways. • Different evolutions in oil and gas context are linked to divergent offshore wind developments. • Context conditions and their effects evolve over time and overlap with each other. • Emergence of offshore wind in Norway and the Netherlands took very different pathways. • Proximity alignment strongly affects the emergence of innovation systems. [ABSTRACT FROM AUTHOR]