Annoyance from transportation noise: relationships with exposure metrics DNL and DENL and their confidence intervals.

We present a model of the distribution of noise annoyance with the mean varying as a function of the noise exposure. Day-night level (DNL) and day-evening-night level (DENL) were used as noise descriptors. Because the entire annoyance distribution has been modeled, any annoyance measure that summarizes this distribution can be calculated from the model. We fitted the model to data from noise annoyance studies for aircraft, road traffic, and railways separately. Polynomial approximations of relationships implied by the model for the combinations of the following exposure and annoyance measures are presented: DNL or DENL, and percentage "highly annoyed" (cutoff at 72 on a scale of 0-100), percentage "annoyed" (cutoff at 50 on a scale of 0-100), or percentage (at least) "a little annoyed" (cutoff at 28 on a scale of 0-100). These approximations are very good, and they are easier to use for practical calculations than the model itself, because the model involves a normal distribution. Our results are based on the same data set that was used earlier to establish relationships between DNL and percentage highly annoyed. In this paper we provide better estimates of the confidence intervals due to the improved model of the relationship between annoyance and noise exposure. Moreover, relationships using descriptors other than DNL and percentage highly annoyed, which are presented here, have not been established earlier on the basis of a large dataset

eHealth in support for daily functioning of people with intellectual disability:Views of service users, relatives, and professionals on both its advantages and disadvantages and its facilitating and impeding factors

Background: The use of eHealth in support for daily functioning of service users with intellectual disability (ID) is a rather unexplored domain. Therefore, the current study identified the a) level of familiarity, b) advantages/disadvantages, and c) facilitating/impeding factors for the use of eHealth in support for daily functioning of people with ID according to service users, relatives, and professionals. Method: Four focus groups and one semi-structured qualitative interview were conducted. Results: Participants were familiar with numerous eHealth applications. Benefits were related to service users (e.g., increased independency) and relatives/professionals (e.g., providing more efficient support). Adequate informing and involving all stakeholders and centrally positioning the needs and possibilities of service users were reported as important facilitators. Contrary, impeding factors were malfunctioning Internet, expenses of eHealth, and lack of proper IT-support. Conclusions: The results provide imperative information for future eHealth implementations and to direct its use more specifically to people with ID

Borders and boundaries in the lives of migrant agricultural workers

In 2018, roughly 72%of the 69,775 temporary migrant agricultural labourers arriving in Canada participated in the Seasonal Agricultural Workers Program (SAWP). Despite having legal status in Canada, these individuals are often systematically excluded from community life and face barriers when accessing health and social services. SAWP workers’ exclusion from many public spaces and their incomplete access to the benefits of Canadian citizenship or residency provide us a unique opportunity to examine social and political mechanisms that construct(in)eligibility for health and protection in society.As individuals seeking to care for the sick and most marginalized, it is important for nurses to understand how migrant agricultural workers are positioned and imagined in society. We argue that the structural exclusion faced by this population can be uncovered by examining:(1)border politics that inscribe inferior status onto migrant agricultural workers;(2) nation-state borders that promote racialized surveillance, and;(3) everyday normalization of exclusionary public service practices. We discuss how awareness of these contextual factors can be mobilized by nurses to work towards a more equitable health services approach for this population

MO4 - Using AHP weights to fill missing gaps in Markov decision models

OBJECTIVES:\ud We propose to combine the versatility of the analytic hierarchy process (AHP) with the decision-analytic sophistication of health-economic modeling in a new methodology for early technology assessment. As an illustration, we apply this methodology to a new technology to diagnose breast cancer.\ud \ud METHODS:\ud The AHP is a technique for multicriteria analysis, relatively new in the fi eld of technology assessment. It can integrate both quantitative and qualitative criteria in the assessment of alternative technologies. We applied the AHP to prioritize a more versatile set of outcome measures than most Markov models do. These outcome measures include clinical effectiveness and costs, but also weighted estimates of patient comfort and safety. Furthermore, as no clinical data are available for this technology yet, the AHP is applied to predict the performance of the new technology with regard to all these outcome measures. Results of the AHP are subsequently integrated in a Markov model to make an early assessment of the expected incremental cost-effectiveness of alternative technologies.\ud \ud RESULTS:\ud We systematically estimated priors on the clinical effectiveness and wider impacts of the new technology using AHP. In our illustration, AHP estimates for sensitivity and specifi city of the new diagnostic technology were used as probability parameters in the Markov model. Moreover, the prioritized outcome measures including clinical effectiveness (weight = 0.61), patient comfort (weight = 0.09), and safety (weight = 0.30) were integrated into one outcome measure in the Markov model.\ud \ud CONCLUSIONS:\ud Combining AHP and Markov modelling is particularly valuable in early technology assessment when evidence about the effectiveness of health care technology is still limited or missing. Moreover, combining these methods is valuable when decision makers are interested in other patient relevant outcomes measures besides the technology’s clinical effectiveness, and that may not (adequately or explicitly) be captured in mainstream utility measures

eHealth in the support of people with mild intellectual disability in daily life:A systematic review

Background:  eHealth has recently made rapid progress in care, support and treatment. However, studies on the use of eHealth to support people with a mild intellectual disability in daily life are limited. A systematic review was conducted to provide an overview of this use of eHealth.  Methods:  Seven databases were searched for relevant studies and assessed according to the PRISMA guidelines. Descriptive analyses were deployed using the Matching Person to Technology model to evaluate the key areas contributing to successful eHealth use.  Results:  Most of the 46 studies included were small-scale case studies and focused on using eHealth to acquire daily living skills and vocational skills. In addition, several studies focused on eHealth use for self-support in daily living, and three studies focused on remote professional support.  Conclusions:  eHealth offers opportunities to support people with mild intellectual disability in various different contexts of daily life. Scientific research on this topic is in its early stage, and further high-quality research is needed