In a study commissioned by the Association of Dutch Municipalities (VNG), the applied research group European Impact has compiled the results from interviews executed by approximately 240 European Studies students at The Hague University of Applied Sciences. The purpose of this report is to compare and contrast the situation of intra-EU labor migrants (hereafter referred to as EU mobile citizens) in regard to registration, housing, and information flows in 12 different municipalities across the EU. Based on semi-structured interviews with municipal workers and individuals from employment agencies/companies from the selected municipalities, the picture that emerges is one of divergence. There are significant variations regarding the registration procedure and information flows for EU mobile citizens across the selected municipalities. For registration, differences include where the registration takes place, the amount of collaboration between municipalities and employment agencies/companies on registering EU mobile citizens, and the importance of addresses in the registration process. Regarding information flows across the selected municipalities, there are significant variations in the amount and type of information available to EU mobile citizens, the number of languages information is available in,as well as how the information is organized (i.e. in a centralized or decentralized way). Furthermore, while all the member states in which the selected municipalities are located provide information regarding registration on the Single Digital Gateway, not all provide information about renting housing. As for housing, the results revealed that most of the selected municipalities face issues with housing and that EU mobile citizens typically find housing either via their employers or personal network. Based on the results, a list of potential best practices and policy areas that could be improved was compiled. Furthermore, in order to have a stronger overview of policy developments in the field of EU mobile citizens among different municipalities, the VNG could consider hosting a Community of Practice with different municipalities across the EU as well as monitoring Interreg Europe projects focused on improving the situation of EU mobile citizens.
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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.
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The inefficiency of maintaining static and long-lasting safety zones in environments where actual risks are limited is likely to increase in the coming decades, as autonomous systems become more common and human workers fewer in numbers. Nevertheless, an uncompromising approach to safety remains paramount, requiring the introduction of novel methods that are simultaneously more flexible and capable of delivering the same level of protection against potentially hazardous situations. We present such a method to create dynamic safety zones, the boundaries of which can be redrawn in real-time, taking into account explicit positioning data when available and using conservative extrapolation from last known location when information is missing or unreliable. Simulation and statistical methods were used to investigate performance gains compared to static safety zones. The use of a more advanced probabilistic framework to further improve flexibility is also discussed, although its implementation would not offer the same level of protection and is currently not recommended.
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Background: Adequate self-management skills are of great importance for patients with chronic obstructive pulmonary disease (COPD) to reduce the impact of COPD exacerbations. Using mobile health (mHealth) to support exacerbation-related self-management could be promising in engaging patients in their own health and changing health behaviors. However, there is limited knowledge on how to design mHealth interventions that are effective, meet the needs of end users, and are perceived as useful. By following an iterative user-centered design (UCD) process, an evidence-driven and usable mHealth intervention was developed to enhance exacerbation-related self-management in patients with COPD. Objective: This study aimed to describe in detail the full UCD and development process of an evidence-driven and usable mHealth intervention to enhance exacerbation-related self-management in patients with COPD. Methods: The UCD process consisted of four iterative phases: (1) background analysis and design conceptualization, (2) alpha usability testing, (3) iterative software development, and (4) field usability testing. Patients with COPD, health care providers, COPD experts, designers, software developers, and a behavioral scientist were involved throughout the design and development process. The intervention was developed using the behavior change wheel (BCW), a theoretically based approach for designing behavior change interventions, and logic modeling was used to map out the potential working mechanism of the intervention. Furthermore, the principles of design thinking were used for the creative design of the intervention. Qualitative and quantitative research methods were used throughout the design and development process. Results: The background analysis and design conceptualization phase resulted in final guiding principles for the intervention, a logic model to underpin the working mechanism of the intervention, and design requirements. Usability requirements were obtained from the usability testing phases. The iterative software development resulted in an evidence-driven and usable mHealth intervention—Copilot, a mobile app consisting of a symptom-monitoring module, and a personalized COPD action plan. Conclusions: By following a UCD process, an mHealth intervention was developed that meets the needs and preferences of patients with COPD, is likely to be used by patients with COPD, and has a high potential to be effective in reducing exacerbation impact. This extensive report of the intervention development process contributes to more transparency in the development of complex interventions in health care and can be used by researchers and designers as guidance for the development of future mHealth interventions.
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Abstract Background: With the growing shortage of nurses, labor-saving technology has become more important. In health care practice, however, the fit with innovations is not easy. The aim of this study is to analyze the development of a mobile input device for electronic medical records (MEMR), a potentially labor-saving application supported by nurses, that failed to meet the needs of nurses after development. Method: In a case study, we used an axiomatic design framework as an evaluation tool to visualize the mismatches between customer needs and the design parameters of the MEMR, and trace these mismatches back to (preliminary) decisions in the development process. We applied a mixed-method research design that consisted of analyzing of 118 external and internal files and working documents, 29 interviews and shorter inquiries, a user test, and an observation of use. By factoring and grouping the findings, we analyzed the relevant categories of mismatches. Results: The involvement of nurses during the development was extensive, but not all feedback was, or could not be, used effectively to improve the MEMR. The mismatches with the most impact were found to be: (1) suboptimal supportive technology, (2) limited functionality of the app and input device, and (3) disruption of nurses’ workflow. Most mismatches were known by the IT department when the MEMR was offered to the units as a product. Development of the MEMR came to a halt because of limited use. Conclusion: Choices for design parameters, made during the development of labor-saving technology for nurses, may conflict with the customer needs of nurses. Even though the causes of mismatches were mentioned by the IT department, the nurse managers acquired the MEMR based on the idea behind the app. The effects of the chosen design parameters should not only be compared to the customer needs, but also be assessed with nurses and nurse managers for the expected effect on the workflow.
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Background: Patients with chronic obstructive pulmonary disease (COPD) demonstrate reduced levels of daily physical activity (DPA) compared to healthy controls. This results in a higher risk of hospital admission and shorter survival. Performing regular DPA reduces these risks. Objective: To develop an eHealth intervention that will support patients with COPD to improve or maintain their DPA after pulmonary rehabilitation. Methods: The design process consisted of literature research and the iterative developing and piloting phases of the Medical Research Council (MRC) model for complex clinical interventions and the involvement of end users. Participants were healthy adults and persons with COPD. Results: The mobile phone interface met all the set requirements. Participants found that the app was stimulating and that reaching their DPA goals was rewarding. The mean (SD) scores on a 7-point scale for usability, ease of use, ease of learning, and contentment were 3.8 (1.8), 5.1 (1.1), 6.0 (1.6), and 4.8 (1.3), respectively. The mean (SD) correlation between the mobile phone and a validated accelerometer was 0.88 (0.12) in the final test. The idea of providing their health care professional with their DPA data caused no privacy issues in the participants. Battery life lasted for an entire day with the final version, and readability and comprehensibility of text and colors were favorable. Conclusions: By employing a user-centered design approach, a mobile phone was found to be an adequate and feasible interface for an eHealth intervention. The mobile phone and app are easy to learn and use by patients with COPD. In the final test, the accuracy of the DPA measurement was good. The final version of the eHealth intervention is presently being tested by our group for efficacy in a randomized controlled trial in COPD patients.
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Background: There is an emergence of mobile health (mHealth) interventions to support self-management in patients with chronic obstructive pulmonary disease (COPD). Recently, an evidence-driven mHealth intervention has been developed to support patients with COPD in exacerbation-related self-management: the Copilot app. Health care providers (HCPs) are important stakeholders as they are the ones who have to provide the app to patients, personalize the app, and review the app. It is, therefore, important to investigate at an early stage whether the app is feasible in the daily practice of the HCPs. Objective: The aim of this study is to evaluate the perceived feasibility of the Copilot app in the daily practice of HCPs. Methods: A multimethods design was used to investigate how HCPs experience working with the app and how they perceive the feasibility of the app in their daily practice. The feasibility areas described by Bowen et al were used for guidance. HCPs were observed while performing tasks in the app and asked to think aloud. The System Usability Scale was used to investigate the usability of the app, and semistructured interviews were conducted to explore the feasibility of the app. The study was conducted in primary, secondary, and tertiary care settings in the Netherlands from February 2019 to September 2019. Results: In total, 14 HCPs participated in this study—8 nurses, 5 physicians, and 1 physician assistant. The HCPs found the app acceptable to use. The expected key benefits of the app were an increased insight into patient symptoms, more structured patient conversations, and more tailored self-management support. The app especially fits within the available time and workflow of nurses. The use of the app will be influenced by the autonomy of the professional, the focus of the organization on eHealth, costs associated with the app, and compatibility with the current systems used. Most HCPs expressed that there are conditions that must be met to be able to use the app. The app can be integrated into the existing care paths of primary, secondary, and tertiary health care settings. Individual organizational factors must be taken into account when integrating the app into daily practice. Conclusions: This early-stage feasibility study shows that the Copilot app is feasible to use in the daily practice of HCPs and can be integrated into primary, secondary, and tertiary health care settings in the Netherlands. The app was considered to best fit the role of the nurses. The app will be less feasible for those organizations in which many conditions need to be met to use the app. This study provides a new approach to evaluate the perceived feasibility of mHealth interventions at an early stage and provides valuable insights for further feasibility testing.
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This study evaluates the maximum theoretical exposure to radiofrequency (RF) electromag- netic fields (EMFs) from a Fifth-generation (5G) New Radio (NR) base station (BS) while using four commonly used mobile applications: YouTube for video streaming, WhatsApp for voice calls, Instagram for posting pictures and videos, and running a Video game. Three factors that might affect exposure, i.e., distance of the measurement positions from the BS, measurement time, and induced traffic, were examined. Exposure was assessed through both instantaneous and time-averaged extrapolated field strengths using the Maximum Power Extrapolation (MPE) method. The former was calculated for every measured SS-RSRP (Secondary Synchronization Reference Signal Received Power) power sample obtained with a sampling resolution of 1 second, whereas the latter was obtained using a 1-min moving average applied on the applications’ instantaneous extrapolated field strengths datasets. Regarding distance, two measurement positions (MPs) were selected: MP1 at 56 meters and MP2 at 170 meters. Next, considering the measurement time, all mobile application tests were initially set to run for 30 minutes at both MPs, whereas the video streaming test (YouTube) was run for an additional 150 minutes to investigate the temporal evolution of field strengths. Considering the traffic, throughput data vs. both instantaneous and time-averaged extrapolated field strengths were observed for all four mobile applications. In addition, at MP1, a 30-minute test without a User Equipment (UE) device was conducted to analyze exposure levels in the absence of induced traffic. The findings indicated that the estimated field strengths for mobile applications varied. It was observed that distance and time had a more significant impact than the volume of data traffic generated (throughput). Notably, the exposure levels in all tests were considerably lower than the public exposure thresholds set by the ICNIRP guidelines.INDEX TERMS 5G NR, C-band, human exposure assessment, mobile applications, traffic data, maximum extrapolation method, RF-EMF.
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This review offers a detailed examination of the current landscape of radio frequency (RF) electromagnetic field (EMF) assessment tools, ranging from spectrum analyzers and broadband field meters to area monitors and custom-built devices. The discussion encompasses both standardized and non-standardized measurement protocols, shedding light on the various methods employed in this domain. Furthermore, the review highlights the prevalent use of mobile apps for characterizing 5G NR radio network data. A growing need for low-cost measurement devices is observed, commonly referred to as “sensors” or “sensor nodes”, that are capable of enduring diverse environmental conditions. These sensors play a crucial role in both microenvironmental surveys and individual exposures, enabling stationary, mobile, and personal exposure assessments based on body-worn sensors, across wider geographical areas. This review revealed a notable need for cost-effective and long-lasting sensors, whether for individual exposure assessments, mobile (vehicle-integrated) measurements, or incorporation into distributed sensor networks. However, there is a lack of comprehensive information on existing custom-developed RF-EMF measurement tools, especially in terms of measuring uncertainty. Additionally, there is a need for real-time, fast-sampling solutions to understand the highly irregular temporal variations EMF distribution in next-generation networks. Given the diversity of tools and methods, a comprehensive comparison is crucial to determine the necessary statistical tools for aggregating the available measurement data.
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