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Digital transformation in healthcare improves the safety of health systems. Within our health service, a new digital hospital has been established and two wards from a neighbouring paper-based hospital transitioned into the new digital hospital. This created an opportunity to evaluate the impact of complete digital transformation on medication safety. Here we discuss the impact of transition from a paper-based to digital hospital on voluntarily reported medication incidents and prescribing errors. This study utilises an interrupted time-series design and takes place across two wards as they transition from a paper to a digital hospital. Two data sources are used to assess impacts on medication incidents and prescribing errors: (1) voluntarily reported medication incidents and 2) a chart audit of medications prescribed on the study wards. The chart audit collects data on procedural, dosing and therapeutic prescribing errors. There are 588 errors extracted from incident reporting software during the study period. The average monthly number of errors reduces from 12.5 pre- to 7.5 post-transition (p < 0.001). In the chart audit, 5072 medication orders are reviewed pre-transition and 3699 reviewed post-transition. The rates of orders with one or more error reduces significantly after transition (52.8% pre- vs. 15.7% post-, p < 0.001). There are significant reductions in procedural (32.1% pre- vs. 1.3% post-, p < 0.001), and dosing errors (32.3% pre- vs. 14% post-, p < 0.001), but not therapeutic errors (0.6% pre- vs. 0.7% post-, p = 0.478). Transition to a digital hospital is associated with reductions in voluntarily reported medication incidents and prescribing errors. [ABSTRACT FROM AUTHOR]

Background: Survey response rates have been declining over the past decade. The more widespread use of the Internet and Web-based technologies among potential health survey participants suggests that Web-based questionnaires may be an alternative to paper questionnaires in future epidemiological studies. Objective: To compare response rates in a population of parents by using 4 different modes of data collection for a questionnaire survey of which 1 involved a nonmonetary incentive. Methods: A random sample of 3148 parents of Danish children aged 2-17 years were invited to participate in the Danish part of the NordChild 2011 survey on their children's health and welfare. NordChild was conducted in 1984 and 1996 in collaboration with Finland, Iceland, Norway, and Sweden using mailed paper questionnaires only. In 2011, all countries used conventional paper versions only except Denmark where the parents were randomized into 4 groups: (1) 789 received a paper questionnaire only (paper), (2) 786 received the paper questionnaire and a log-in code to the Web-based questionnaire (paper/Web), (3) 787 received a log-in code to the Web-based questionnaire (Web), and (4) 786 received log-in details to the Web-based questionnaire and were given an incentive consisting of a chance to win a tablet computer (Web/tablet). In connection with the first reminder, the nonresponders in the paper, paper/Web, and Web groups were also present with the opportunity to win a tablet computer as a means of motivation. Descriptive analysis was performed using chi-square tests. Odds ratios were used to estimate differences in response rates between the 4 modes. Results: In 2011, 1704 of 3148 (54.13%) respondents answered the Danish questionnaire. The highest response rate was with the paper mode (n=443, 56.2%). The other groups had similar response rates: paper/Web (n=422, 53.7%), Web (n=420, 53.4%), and Web/tablet (n=419, 53.3%) modes. Compared to the paper mode, the odds for response rate in the paper/Web decreased by 9% (OR 0.91, 95% CI 0.74-1.10) and by 11% (OR 0.89, 95% CI 0.73-1.09) in the Web and Web/tablet modes. The total number of responders for NordChild declined from 10,291 of 15,339 (67.09%) in 1984 and 10,667 of 15,254 (69.93%) in 1996 to 7805 of 15,945 (48.95%) in 2011 with similar declines in all 5 Nordic countries. Conclusions: Web-based questionnaires could replace traditional paper questionnaires with minor effects on response rates and lower costs. The increasing effect on the response rate on participants replying for a nonmonetary incentive could only be estimated within the 2 Web-based questionnaire modes before the first reminder. Alternative platforms to reach higher participation rates in population surveys should reflect the development of electronic devices and the ways in which the population primarily accesses the Internet. [ABSTRACT FROM AUTHOR]

Finishing determines the final dimension and geometric accuracy of parts, and the finishing process directly affects the stiffness and residual stress redistribution of the workpiece, so the optimisation of the finishing process plays a very important role in deformation control. At present, existing data-driven methods for deformation control need a large amount of labelled training data, which is always a challenge in the manufacturing area, especially for machining deformation. To address the above issues, this paper presents a meta-reinforcement learning model incorporated by simulation and real data, which is trained in a simulation environment with a piecewise sampling strategy for data collection, and can be updated in a real machining environment through a very small number of real monitoring data. The finishing process optimisation for deformation control can be realised using the proposed approach. Finally, the effectiveness of the proposed method is verified both in simulation environment and actual machining, and better results are obtained compared with other existing methods. [ABSTRACT FROM AUTHOR]

To understand how the digitalization of higher education influences the inter-relationship between students, teachers, and their broader contexts, research must account for the social, cultural, political, and embodied aspects of teaching and learning in digital environments. Digital ethnography is a research method that can generate rich contextual knowledge of online experiences. However, how this methodology translates to higher education is less clear. In order to explore the opportunities that digital ethnography can provide in higher education research, this paper presents a methodological review of previous research, and discusses the implications for future practice. Through a systematic search of five research databases, we found 20 papers that report using digital ethnographies to explore teaching and learning in higher education. The review synthesizes and discusses how data collection, rigour, and ethics are handled in this body of research, with a focus on the specific methodological challenges that emerge when doing digital ethnographic research in a higher education setting. The review also identifies opportunities for improvement—especially related to participant observation from the student perspective, researcher reflexivity in relation to the dual teacher-researcher role, and increased diversity of data types. This leads us to conclude that higher education research, tasked with understanding an explosion of new digital practices, could benefit from a more rigorous and expanded use of digital ethnography. [ABSTRACT FROM AUTHOR]

This paper aims at highlighting the behaviour of universal fractional-horsepower commutation motor in different operating situations, by using modern means of investigation. For this purpose, a series of direct current and alternating current experimental tests were carried out, with and without compensation winding. The paper presents partial photos of the test stand, the circuit schemes used and the figures obtained from the experiments. From this last category, there are emphasized the phasor representations obtained and the harmonic analyses of the monitored currents. The paper ends with conclusions and references. [ABSTRACT FROM AUTHOR]

Objective: This study examines the impact of data collection method on the sociodemographic and health profile of samples of people with diabetes who complete either an online or postal patient-reported outcome measure (PROM) validation survey.Methods: A longitudinal survey of people with diabetes was conducted using online and postal survey versions. The survey consisted of sociodemographic and health questions, a health and self-management PROM (Health and Self-Management in Diabetes [HASMID]), and 5-level version of EQ-5D. Dose adjustment for normal eating Online, Diabetes UK, and social media were used to recruit online survey participants. A panel of patients at a local National Health Service Trust was randomly allocated to participate in either survey version (two-thirds to postal version). Participants were asked to complete the survey again approximately 3 months later.Results: A total of 2784 participants completed the survey (1908 online, 876 postal). The samples (online versus postal) differed; the online sample was younger, with a larger proportion of women and respondents with type 1 diabetes. There were significant differences in sociodemographic characteristics by type of diabetes across data collection mode. The proportion of respondents who responded again at point 2 was higher in the postal sample (525 postal, 698 online).Conclusion: The sociodemographic and health profile of samples of people with diabetes differed depending on whether they completed the online or postal survey. Differences are likely due to different recruitment methods and differences in those choosing to respond to different survey versions. Future PROM validation surveys should select data collection methods carefully because these can affect sample characteristics and results. [ABSTRACT FROM AUTHOR]

Research background: The differences in the legal structures, tax rates, and cultural-linguistic issues of various countries have always been a significant concern for SMEs in their exporting activities and internationalization processes. However, since firm-level characteristics might provide some advantages or disadvantages in their operations, their perceptions of export impediments might vary across size, age, and sector groups. Purpose of the article: This paper investigates the perceptions of export impediments by 408 larger-smaller, older-younger, and manufacturing-nonmanufacturing Czech, Slovakian and Hungarian SMEs in a country-based perspective. Methods: The researchers use the random sampling method to create research samples and employ an internet-mediated questionnaire to collect the research data. The researchers use both Independent Sample T-test and ANOVA analyses to find differences between size, age, and sector groups. Findings & value added: While the differences exist between the perceptions of Slovakian larger-smaller and manufacturing-nonmanufacturing SMEs regarding cultural differences, the perceptions of legal and tax-related export impediments by SMEs do not differ depending on their age, size, and sector. This paper contributes to the literature by confirming various perceptions of SMEs in different countries and different characteristics regarding export obstacles and providing an entity-specific and international scope that policymakers and SMEs can benefit from. Awareness of the policymakers regarding the results of this paper that includes differences and similarities in SMEs' perceptions of export barriers might make them have close interactions with SMEs to reduce SMEs' concerns regarding their export risks. On the other hand, SMEs that are aware of the results of this paper can be more interested in having a broader network that includes close relationships not only with intermediary firms, but also with governments to overcome the export impediments. [ABSTRACT FROM AUTHOR]

Harmony of being, a concept that recognized philosophy, values, social science as a unit whole in understanding humanity holistically. This research paper aimed to discuss the relevance of this approach to NU MOA students and faculty members. The essence of studying how it enhanced personal growth and development was therefore explored through this paper. The research methodology used an exploratory and documentary analysis in which primary and secondary sources were used as data collection tools. In conclusion, the results from this study could be used by NU MOA to come up with programs that enhanced harmony among its students and staff. [ABSTRACT FROM AUTHOR]

The Expanded National Nutrition Survey (ENNS), formerly the National Nutrition Survey, is a regularly conducted survey that records the Philippines' overall nutritional status. This is especially important not only for government intervention and policy-making but also for private sector entities that plan for their nutrition and development programs. First deployed during the conduct of the 2013 ENNS, the electronic data collection system (EDCS) is a tool that implemented computer-assisted personal interviewing (CAPI) functionalities. This paper records the improvements made to this system and its division into separate subsystems, various CAPI subsystems with specialized functionalities, and how they interact with each other. Descriptive analysis was used for the users' feedback and recommendations -- specifically, for usability and navigation, system performance and portability, technicality and security, and visual design. The system is able to support interviews during the ENNS and receive positive feedback -- garnering visual design the highest, whereas technicality and security the lowest acceptability rating -- thereby proving this division useful. Overall, the system is capable of supporting the ENNS and will continue its improvement through the continual user feedback received. [ABSTRACT FROM AUTHOR]

Purpose: Activity sampling is a technique to monitor onsite labourers' time utilisation, which can provide helpful information for the management level to implement suitable labour productivity improvement strategies continuously. However, there needs to be a review paper that compiles research on activity sampling studies to give readers a thorough grasp of the research trend. Hence, this paper aims to investigate the activity sampling techniques applied in earlier research from the angles of activity categories formation, data collection methods and data analysis. Design/methodology/approach: The method used in this paper is a systematic review guided by the PRISMA framework. The search was conducted in Scopus and Web of Science. The inclusion and exclusion criteria were applied, selecting 70 articles published between 2011 and 2022 for data extraction and analysis. The analysis method involved a qualitative synthesis of the findings from the selected articles. Findings: Activity sampling is broadly divided into four stages: targeting trade, determining activity categories, data collection and data analysis. This paper divides the activity categories into three levels and classifies the data collection methods into manual observation, sensor-based activity sampling and computer vision-based activity sampling. The previous studies applied activity sampling for two construction management purposes: labour productivity monitoring and ergonomic safety monitoring. This paper also further discusses the scientific research gaps and future research directions. Originality/value: This review paper contributes to the body of knowledge in construction management by thoroughly understanding current state-of-the-art activity sampling techniques and research gaps. [ABSTRACT FROM AUTHOR]

Charging methods significantly affect the performance and lifespan of lithium-ion batteries. Investigating charging techniques is crucial for optimizing the charging time, charging efficiency, and cycle life of the battery cells. This study introduces a real-time charging monitoring platform based on LabVIEW, enabling observation of battery parameters such as voltage, current, and temperature. The proposed system allows the precise control of charging parameters via a user-friendly interface. Utilizing a programmable DC power supply, it delivers specific charging waveforms, while data acquisition instruments record temperature changes. Key performance metrics, including charging time, efficiency, and temperature rise, are analyzed. Moreover, this paper conducts in-depth research on the constant temperature–constant voltage (CT-CV) charging technique and applies the Taguchi method to identify key parameter configurations that achieve the objectives of the shortest charging time, highest charging efficiency, and lowest average temperature rise. A comprehensive evaluation compares the optimized CT-CV method with conventional constant current–constant voltage (CC-CV) charging. The results demonstrate a 10.7% reduction in charging time compared to the 1C CC-CV method, indicating the efficacy of CT-CV in shortening charging duration while managing temperature rise. [ABSTRACT FROM AUTHOR]

Real-time traffic signal acquisition and network transmission are essential components of intelligent transportation systems, facilitating real-time traffic monitoring, management, and analysis in urban environments. In this paper, we introduce a comprehensive system that incorporates live traffic signal acquisition, real-time data processing, and secure network transmission through a combination of hardware and software modules, called LIDATS. LIDATS stands for Live Intersection Data Acquisition for Traffic Simulators. The design and implementation of our system are detailed, encompassing signal acquisition hardware as well as a software platform that is used specifically for real-time data processing. The performance evaluation of our system was conducted by simulation in the lab, demonstrating its capability to reliably capture and transmit data in real time, and to effectively extract the relevant information from noisy and complex traffic data. Supporting a variety of intelligent transportation applications, such as real-time traffic flow management, intelligent traffic signal control, and predictive traffic analysis, our system enables remote data analysis and decisionmaking, providing valuable insights and enhancing the traffic efficiency while reducing the congestion in urban environments. [ABSTRACT FROM AUTHOR]

With the increasing number of households owning pets, the importance of sensor data for recognizing pet behavior has grown significantly. However, challenges arise due to the costs and reliability issues associated with data collection. This paper proposes a method for classifying pet behavior using cleaned meta pseudo labels to overcome these issues. The data for this study were collected using wearable devices equipped with accelerometers, gyroscopes, and magnetometers, and pet behaviors were classified into five categories. Utilizing this data, we analyzed the impact of the quantity of labeled data on accuracy and further enhanced the learning process by integrating an additional Distance Loss. This method effectively improves the learning process by removing noise from unlabeled data. Experimental results demonstrated that while the conventional supervised learning method achieved an accuracy of 82.9%, the existing meta pseudo labels method showed an accuracy of 86.2%, and the cleaned meta pseudo labels method proposed in this study surpassed these with an accuracy of 88.3%. These results hold significant implications for the development of pet monitoring systems, and the approach of this paper provides an effective solution for recognizing and classifying pet behavior in environments with insufficient labels. [ABSTRACT FROM AUTHOR]

The revolution of the Internet of Things (IoT) and the Web of Things (WoT) has brought new opportunities and challenges for the information retrieval (IR) field. The exponential number of interconnected physical objects and real-time data acquisition requires new approaches and architectures for IR systems. Research and prototypes can be crucial in designing and developing new systems and refining architectures for IR in the WoT. This paper proposes a unified and holistic approach for IR in the WoT, called IR.WoT. The proposed system contemplates the critical indexing, scoring, and presentation stages applied to some smart cities' use cases and scenarios. Overall, this paper describes the research, architecture, and vision for advancing the field of IR in the WoT and addresses some of the remaining challenges and opportunities in this exciting area. The article also describes the design considerations, cloud implementation, and experimentation based on a simulated collection of synthetic XML documents with technical efficiency measures. The experimentation results show promising outcomes, whereas further studies are required to improve IR.WoT effectiveness, considering the WoT dynamic characteristics and, more importantly, the heterogeneity and divergence of WoT modeling proposals in the IR domain. [ABSTRACT FROM AUTHOR]

Aim: Studies of the effects of COVID‐19, especially post‐acute COVID‐19 syndrome, on psychological health in non‐severe cases are limited. We aimed to evaluate the prevalence and associated risk factors of psychological symptoms, and quality‐of‐life in three groups of outpatients, hospitalized and intensive care patients. Methods: A total 276 patients, previously confirmed with SARS‐CoV‐2 infection, attending the COVID‐19 follow‐up outpatient clinic from December 2020 to July 2021 were interviewed face‐to‐face. In this cross‐sectional, retrospective study, all participants were asked our self‐designed demographic and screening questions to assess their psychological symptoms and administered the WHQOOL‐BREF survey to evaluate quality of life. Results: In screening questions, major depressive disorder symptoms were detected at a rate of 20.3%, generalized anxiety disorder symptoms at a rate of 16.7%, panic attack symptoms at a rate of 10.9%, post‐traumatic stress disorder symptoms at a rate of 28.6% and obsessive‐compulsive disorder symptoms at a rate of 18.1%. The outpatient group with COVID‐19 infection had a higher risk of developing psychological symptoms and decreased quality of life. Conclusion: COVID‐19 infection was found to have a considerable psychological impact on those treated as outpatients despite the less severe course of their illness. Summary statement: What is already known about this topic? Post‐intensive care syndrome affects physical, cognitive and psychological health.It is associated with symptoms such as generalized weakness, memory disturbances, cognitive function impairment, depression, anxiety and post‐traumatic stress disorder.Some physical and psychological symptoms persist for over 12 weeks in some patients and have been classified as 'Post‐acute COVID‐19 Condition or Syndrome' (PCS). What this paper adds? At the post‐acute‐COVID‐19 period, a considerable number of outpatients with COVID‐19 infection were at higher risk for psychological distress symptoms than those who had been treated in the hospital or intensive care unit.Depression, anxiety, panic disorder and PTSD symptoms were found to be higher in outpatients and those with these symptoms were also shown to have a lower quality of life.Our findings highlight the significant psychological impact of COVID‐19 on patients, even after their reported recovery from the acute manifestations of this disease. The implications of this paper: Ongoing psychological symptoms in the post‐COVID period are not associated with the severity of the disease in the acute phase.It is important that healthcare professionals are equally concerned not only with physical condition of post‐COVID‐19 patients but also with their psychological state and the patient's psychology‐related quality of life. [ABSTRACT FROM AUTHOR]

Aims: We aim to analyse the effect of menthol on thirst intensity and thirst comfort in surgical patients. Background: Menthol has achieved good results in quenching thirst in patients in intensive care units, but its safety and reliability in perioperative fasting patients are unknown. Design: A systematic review with meta‐analysis of intervention studies was performed. Data Sources: We used Chinese and English databases from their dates of inception to May 2022. Literature was retrieved from PubMed, Web of Science, Cochrane Library, Embase, CINHAL, SinoMed, CNKI, Wanfang and VIP database. Review Methods: Two reviewers independently examined the records according to the eligibility criteria and extracted the data of each included study. Results: A total of seven studies were identified in this review, which included 537 surgical patients. Overall, menthol reduced thirst intensity in surgical patients and decreased thirst discomfort. Further subgroup analysis revealed that the menthol intervention significantly improved thirst intensity in surgical patients during preoperative and postoperative fasting periods. The Egger's tests showed no significant bias (p = 0.113 and 0.553, thirst intensity and thirst discomfort, respectively). Conclusion: Menthol intervention effectively improved thirst intensity and thirst discomfort during fasting in surgical patients, but more large‐scale, multicentre randomized controlled trials are required to confirm these findings further. Summary statement: What is already known about this topic? Thirst is a common symptom of discomfort during fasting in surgical patients.Thirst in surgical patients is an underappreciated, unmeasured and undertreated symptom. What this paper adds? It is safe and feasible to administer menthol immediately after surgery to patients undergoing surgery.Menthol intervention during fasting in surgical patients can significantly reduce thirst intensity and improve thirst discomfort.More high‐quality trials are essential to explore optimal menthol interventions during fasting in surgical patients. The implications of this paper Menthol provides a safe and effective thirst‐quenching method for perioperative fasting in surgical patients.Menthol reduces thirst intensity and thirst discomfort in surgical patients postoperative fasting periods. [ABSTRACT FROM AUTHOR]

Introduction: Violence against healthcare workers in the workplace is a complex issue affecting various healthcare professionals. Workplace violence (WPV) poses significant occupational hazards to healthcare employees. Objectives: To identify the causes, types, and perpetrators of WPV and explore the effects of violence on healthcare workers' well-being. Methods: This literature review analyzes 15 selected research papers published between 2015 and 2020, focusing on WPV against healthcare workers, and gathers insights from healthcare professionals with prior experience of WPV. Through an analysis of the selected research papers, this study provides a comprehensive overview with WPV in the healthcare setting. The respondents in the included studies were healthcare professionals who had encountered WPV in their work. Results: While nurses remain particularly vulnerable to violence due to their constant patient interaction, this study reveals that verbal violence is the most prevalent type, significantly impacting the well-being of healthcare workers as a whole. The identified causes of WPV include long waiting times, understaffing, miscommunication, inadequate security measures, high patient expectations, and overcrowding. Respondents emphasized the importance of education, security enhancements, and administrative support to address or prevent WPV. Conclusion: The findings strongly highlight the crucial role of administrative support in reducing the incidence of WPV. It is crucial to implement broader measures to ensure the safety and well-being of all healthcare workers. [ABSTRACT FROM AUTHOR]

This paper focuses on mission planning and cooperative navigation algorithms for multi-drone systems aimed at LiDAR-based mapping. It aims at demonstrating how multi-UAV cooperation can be used to fulfill LiDAR data georeferencing accuracy requirements, as well as to improve data collection capabilities, e.g., increasing coverage per unit time and point cloud density. These goals are achieved by exploiting the CDGNSS/Vision paradigm and properly defining the formation geometry and the UAV trajectories. The paper provides analytical tools to estimate point density considering different types of scanning LIDAR and to define attitude/pointing requirements. These tools are then used to support centralized cooperation-aware mission planning aimed at complete coverage for different target geometries. The validity of the proposed framework is demonstrated through numerical simulations considering a formation of three vehicles tasked with a powerline inspection mission. The results show that cooperative navigation allows for the reduction of angular and positioning estimation uncertainties, which results in a georeferencing error reduction of an order of magnitude and equal to 16.7 cm in the considered case. [ABSTRACT FROM AUTHOR]

This paper aims to show how changes in survey design, supervision, and data collector affect travel survey data. The results can be used by policymakers and travel behaviour researchers when evaluating or choosing survey design. A document study of public documentation of national travel survey (NTS) methodology, and research using NTS data material from six European countries were conducted to compare the survey design of their respective NTSs. The results show that all countries included in this analysis have some sort of quality challenges. However, the countries have handled them differently, at different stages, and the transparency of the data collection process varies. Transparency in the data collection process and processing of data is essential for improving the survey design, evaluating quality, and ensuring that the time series is intact. [ABSTRACT FROM AUTHOR]

While there are numerous performance metrics that have been developed for the evaluation of distracted driving prevention programs, there is little information on how to select them depending on the requirements and/or objectives of the study. This paper describes a systematic literature review that was conducted on the metrics for evaluating distracted driving countermeasures in order to bridge this research gap. A summary of the evaluation metrics used for the existing distracted driving countermeasures was provided. Guidance for choosing an evaluation measure was provided by analyzing the metrics from the perspectives of functionality, spatial-temporal dimension, and equity. Three examples of distracted driving countermeasure evaluation processes were thoroughly reviewed in order to offer insight into metric selection and measurement. This paper contributes to the body of knowledge by discussing the implications for policy on how to enhance the thoroughness and accuracy of the evaluation of distracted driving countermeasures. Analysis from multiple angles, the development of data collection tools and direct behavior indicators, taking into account temporal dimensions, and equity considerations, are proposed. [ABSTRACT FROM AUTHOR]

Ultrasonic imaging, using ultrasonic phased arrays, has an enormous impact in science, medicine and society and is a widely used modality in many application fields. The maximum amount of information which can be captured by an array is provided by the data acquisition method capturing the complete data set of signals from all possible combinations of ultrasonic generation and detection elements of a dense array. However, capturing this complete data set requires long data acquisition time, large number of array elements and transmit channels and produces a large volume of data. All these reasons make such data acquisition unfeasible due to the existing phased array technology or non-applicable to cases requiring fast measurement time. This paper introduces the concept of an adaptive data acquisition process, the Selective Matrix Capture (SMC), which can adapt, dynamically, to specific imaging requirements for efficient ultrasonic imaging. SMC is realised experimentally using Laser Induced Phased Arrays (LIPAs), that use lasers to generate and detect ultrasound. The flexibility and reconfigurability of LIPAs enable the evolution of the array configuration, on-the-fly. The SMC methodology consists of two stages: a stage for detecting and localising regions of interest, by means of iteratively synthesising a sparse array, and a second stage for array optimisation to the region of interest. The delay-and-sum is used as the imaging algorithm and the experimental results are compared to images produced using the complete generation-detection data set. It is shown that SMC, without a priori knowledge of the test sample, is able to achieve comparable results, while preforming ∼ 10 times faster data acquisition and achieving ∼ 10 times reduction in data size. [ABSTRACT FROM AUTHOR]

For pedestrian detection in all weather conditions, multispectral imagery is the preferred solution for multimodal data acquisition. Due to the complementarity of multispectral data, the performance of pedestrian detection has been continuously improved. However, it is precise because of the diversity of data that the complexity of the model is increased. How to obtain a simple and lightweight high-performance network is the primary problem that the industry needs to solve. To solve this problem, this paper firstly proposes a lightweight high-performance network multi-receptive field and attention mechanism for multispectral pedestrian detection (MAPD). MAPD is a new scalable network based on multi-receptive field and attention mechanism. It cleverly combines multi-receptive field module and convolutional block attention module (CBAM) attention module to obtain multi-receptive field and attention module (MA). The module can be easily embedded into other network structures. After that, we analyze the proportion of pedestrian objects in the image to determine the receptive field range of the target, and use this range to design the multi-receptive field module of the network to obtain a network model suitable for detecting different object tasks. The MAPD network proposed in this paper has a very low parameter amount. Ablation studies on KAIST and CVC-14 datasets show that our method is effective and achieves state-of-the-art detection performance. [ABSTRACT FROM AUTHOR]

Objectives: Granulomatous mastitis is a rare benign inflammatory disease of the breast commonly seen in women at childbearing age. The aim of this study is to describe clinical and paraclinical characteristics of GM patients, to demonstrate the management and follow-up experience of our center, and review the literature on the topic. Methods: 30 GM cases were identified among the 3248 patients who applied to the breast health center of the Liv Bona Dea hospital between January 2018 and August 2023. Cases were identified as granulomatous mastitis histopathologically from the biopsy specimens. Patient data was evaluated from the database, and missing information was retrieved by calling the patients. Results: Among the 3248 patients who were admitted to our breast health center, 30 patients (0.9%) had a diagnosis of GM and were identified as applicable to our study. All the patients were female, with a median age of 33, ranging from 27 to 66. Of the 30 patients, 11 were overweight and 7 were obese at the time of diagnosis (mean BMI: 26.7). While the majority (n=23, 76%) of the patients presented with a breast lump, only 1 (3%) of the patient’s only symptom was breast lump. 8 (27%) of the cases had comorbidities, including Hashimoto Thyroiditis (n=1), Hypertension (n=6), Diabetes Mellitus type 1 (=1), Diabetes Mellitus type 2 (n=4), Major Depression (n=1). Of the lesions, 16 (53%) showed high suspicion with a Bi-Rads score ≥ 4, and 14 (47%) showed low suspicion with a Bi-Rads score ≤ 4. 18 (60%) of patients received only medical treatment, 11 (37%) patients received both surgery (excision) and medical treatment, and only 1 (3%) received surgery (excision) alone. Conclusion: Even though idiopathic GM is the most common GM type, results from the paper of Ercan Kokrut et al. suggest that Tuberculosis should not be skipped, especially in developing countries, with reported 20% as a cause of GM. A multidisciplinary team is crucial in the diagnosis and treatment of GM to be able to distinguish it from breast cancer To conclude, Granulomatous mastitis is a tricky condition that can cause high anxiety in physicians as high as in patients. Idiopathic GM is the most common type, but evaluation of other reasons, such as tuberculosis mastitis, must be on the checklist. More research regarding the outcome of different treatment modalities will give a straightforward approach for physicians. [ABSTRACT FROM AUTHOR]

LoRaWAN is a low-power wide-area network (LPWAN) technology that is well suited for industrial IoT (IIoT) applications. One of the challenges of using LoRaWAN for IIoT is the need to collect data from a large number of devices. Polling is a common way to collect data from devices, but it can be inefficient for LoRaWANs, which are designed for low data rates and long battery life. LoRaWAN devices operating in two specific modes can receive messages from a gateway even when they are not sending data themselves. This allows the gateway to send commands to devices at any time, without having to wait for them to check for messages. This paper proposes various polling mechanisms for industrial IoT applications in LoRaWANs and presents specific considerations for designing efficient polling mechanisms in the context of industrial IoT applications leveraging LoRaWAN technology. [ABSTRACT FROM AUTHOR]

Purpose: The aim of this paper is to examine a model that combines barriers, drivers, government responses, recovery expectations, expected future changes in performance and the extent of digitalisation as a moderator in SMEs. Design/methodology/approach: This study uses exploratory causal methodologies. The study employs a quantitative methodology based on utilising an electronic questionnaire to gather the opinions of home workers and entrepreneurs in Jordan. The cross-sectional data collection approach was conducted in a single time frame, and a total of 1,179 valid questionnaires were analysed using Smart PLS along with SPSS. Findings: The findings demonstrate that the barriers lower the expectations of recovering performance, whilst the drivers and government responses raise the expectations of both performance recovery and change in performance. Concerning digitalisation, this study discovered that firms going digital had a significant positive direct impact on expectations of performance change. This paper also found that expectations of performance change are significantly positively impacted by the interaction between drivers and digitalisation. However, the moderating influence of digitalisation on the positive impact of government responses on expectations of performance change was not verified. Practical implications: The study's conclusions led to the formulation of several policy recommendations aimed at easing the burden on SMEs. Originality/value: This study adds something new to the body of knowledge on SMEs by investigating the effects of barriers, drivers and government responses on expectations of performance recovery and the expected future change in performance moderated by digitalisation. [ABSTRACT FROM AUTHOR]

In recent decades, digital game-based learning (DGBL) has become a trend among scholars and practitioners in many parts of the world. Therefore, there were some systematic literature reviews in the past few years conducted to identify the trends of DGBL research with diverse subjects and educational levels, however, there is a lack of review that focuses only on mathematics education at primary school levels. This study seeks to provide a comprehensive overview of DGBL research within the context of elementary mathematics learning. Using PRISMA (2020) flow diagram, this study identified 45 articles related to the topic during the period of 2006-2023. Papers were coded and analyzed by years, regions, elementary mathematics topics, research issues, outcomes, research approaches, research design, data collection tools, game genres, and gameplay mode. The results from this systematic review identified the trends in DGBL research related to elementary mathematics learning, highlighted gaps in existing literature, provided insights, and oriented future studies on the topic. The findings of the research reveal a pronounced interest among scholars in the content topics of elementary mathematics, highlighting the research issues that attract attention, the methodologies employed in studies, and the types of games and gaming modes frequently utilized for elementary school children. The article discusses the trends of DGBL within elementary mathematics education, offering in-depth analyses and identifying research gaps that could guide future directions. [ABSTRACT FROM AUTHOR]

The 2015 student protests, #RhodesMustFall and #FeesMustFall, gave rise to the call to decolonise curricula and end the dominance of Western ideologies in South African higher education (HE). The argument put forward in this paper is the need to shift from a traditional approach to a humanised pedagogical approach, wherein students frame knowledge around individual experiences to construct personal and shared understanding. Although limited scholarship around decolonising South African fashion HE exists, such scholarship does not focus on storytelling and circle learning as pedagogical strategies. To address this research gap, narrative humanism, referred to in this research as storytelling, and circle learning are put forward as pedagogical strategies to integrate student identities for personal connection in South African fashion HE. This paper aims to explore the affordances of storytelling and circle learning to decolonise South African fashion HE. Through qualitative action research, two teaching and learning interventions, termed the pilot and main studies, were designed and applied with fashion students at a South African HE institution. Data collection entailed semi-structured student questionnaires, artefacts, and a reflective research journal. To analyse the data, content analysis was employed. The findings reveal that, irrespective of cultural lived experiences or diverse backgrounds, storytelling afforded a decolonised approach in terms of inclusivity, collaboration, and a safe environment for socially engaged dialogue and peer feedback. Similarly, circle learning seemed to reduce teacher-student power relations and contrasted traditional modes of delivery. Circle learning appeared to encourage meaningful, engaged participation, affording a progressive pedagogical strategy to accommodate student and teacher voices in open dialogue. This paper contributes to the scholarship of teaching and learning in that storytelling and circle learning are suitable pedagogies to decolonise fashion education in the Global South. [ABSTRACT FROM AUTHOR]

The paper is focused on the spatial differentiation of the quality of life at a district level, drawing data from the World Value Survey Round 7 (2017–2022). Spatial quality of life research in the traditional sense is based on the premise that quality of life is experienced by the individual in a physical geographical space, and therefore the research focuses on the objective, spatial dimension of quality of life, measured using the objective indicators, usually from statistical sources. The novelty of the paper lies in the premise that a spatial investigation of the subjective dimension of quality of life is also possible, focusing on the question of where people are satisfied with their lives. The indicator of this dimension is a self-related evaluation, obtained using the face-to-face method or the internet. In the case of the World Value Survey 7, data collection was done using the Computer-Assisted Personal Interviewing (CAPI) technique. The aim of the paper is to conceptualize the subjective dimension of quality of life, apply the concept using data from WVS 7 and to find out which of the selected variables—also contained in WVS 7—are predictors of quality of life. [ABSTRACT FROM AUTHOR]

Suter curves for the Wh and Wm characteristics and four-quadrant (4Q) diagrams of 11 radial pump–turbine models with different specific speeds (nq = 24.34, 24.8, 27, 28.6, 38, 41.6, 41.9, 43.83, 50, 56, and 64.04) are presented for the first time in this paper, as well as Suter curves for two pump models (nq = 25 and 41.8) previously published in the literature. All of these curves were analyzed to establish a certain universal law of behavior, depending on the specific speed. To determine such a law, a fitting procedure using regression and spline methods was carried out. This paper provides details of a research plan and structures (including data collection for four-quadrant diagrams for pump–turbine and pump models under different specific speeds nq), a procedure for re-calculating four-quadrant diagrams of the models as Suter curves for the Wh and Wm characteristics, definitions of the optimal points for pump and turbine operating modes in pump–turbine models under different specific speeds, and the development of numerical models in MATLAB to obtain a universal equation for the Wh and Wm characteristics. The scientific contribution of this paper is that it is the first to publish original mathematical curves using universal equations for the Wh and Wm characteristics of radial pumps and pump–turbines. The applicability of the equations is demonstrated by considering a pumping station in which two radial pumps were installed, for which the calculation of transient processes was performed using a numerical model developed in MATLAB by the authors. The transition process results are compared for two cases: first, when input data in the numerical model are used with the values of the Suter curves for the Wh and Wm characteristics obtained by re-calculating the four-quadrant operating characteristics (Q11, n11, M11) at a given specific speed, and second, when the values of the Suter curves for the Wh and Wm characteristics are obtained from the universal equations. [ABSTRACT FROM AUTHOR]

The aim of this paper is to further understanding on the ethical and conceptual challenges associated with researching human trafficking in Edo state, Nigeria. The contribution addresses perceptions of these phenomena among some local actors in the state. Based on five years' research on human trafficking from Nigeria to Europe, this paper puts into perspective local perceptions, and some dynamics of data collection. Also considered here are ethical challenges bordering on trust and suspicion of the researcher's intent, informed consent and suspicion of researcher's motive especially those linked to funding. The paper concludes by recommending ways of navigating as well as overcoming the associated challenges in researching human trafficking in Edo state. [ABSTRACT FROM AUTHOR]

The Underwater Internet of Things (IoUT) shows significant future potential in enabling a smart ocean. Underwater sensor network (UWSN) is a major form of IoUT, but it faces the problem of reliable data collection. To address these issues, this paper considers the use of the autonomous underwater vehicles (AUV) as mobile collectors to build reliable collection systems, while the value of information (VoI) is used as the primary measure of information quality. This paper first builds a realistic model to characterize the behavior of sensor nodes and the AUV together with challenging environments. Then, improved deep reinforcement learning (DRL) is used to dynamically plan the AUV's navigation route by jointly considering the location of nodes, the data value of nodes, and the status of the AUV to maximize the data collection efficiency of the AUV. The results of the simulation show the dynamic data collection scheme is superior to the traditional path planning scheme, which only considers the node location, and greatly improves the efficiency of AUV data collection. [ABSTRACT FROM AUTHOR]

The name "Arduino" made its international debut in 2005, marking the age of Arduino as one of the most user-friendly and cost-effective microcontroller boards (MCBs) for novices. The science implementation of Arduino boards in automation, networking and data acquisition has been increasing steadily. This study provides a thorough Bibliometric analysis from 1122 papers focused on the Scopus database of published microcontroller research, from the first year the Arduino keyword appeared in 2008 until 2022. Various science articles indexed by Scopus and referring to the use of Arduino MCBs are selected. The Bibliometric analysis explores comprehensive and general key attributes that form a trend from the Scopus articles based on authors, titles, publication years, keywords, citations, affiliations, abstracts, funding information, and languages. The generated data is visualized and analyzed to find patterns that appear within the time span. This study found a significant increase in the number of articles on Arduino boards in Biology, Physics, Chemistry, Science, and STEM category of the paper. Despite using only the Scopus database, this study opens up to view the direction of the growing application of Arduino boards in Science. The use of Bibliometric analysis maps the scientific implementation of Arduino boards as an extensive guide for future collaborations in education and industry. [ABSTRACT FROM AUTHOR]

With the continuous development of information technology, the information environment while driving is constantly being enriched, and driver information processing and application are also dynamically evolving. Analysing information processing and application can better provide information services and is particularly important for traffic safety. Based on VOSviewer bibliometric software, this paper explores the research hotspots and future development trends of the driver information processing and application fields using the Web of Science (WoS) core collection as the data source. The results show that the field has a long history and has grown steadily in recent years. The United States, China and Germany are the top three countries in terms of the number of published articles. “Situational awareness and visual load”, “route selection under variable information signs”, “en-route information and behaviour” and “new information technology attitudes” are important knowledge bases for driver information processing and application. En-route information sources, human-computer interaction, and autonomous vehicle information are the research trends of the driver information processing and application field. The results of this research can help people comprehensively and systematically understand the current situation of driver information processing and application research, provide directions for future driver information processing and application research, and promote the engineering application of such research. [ABSTRACT FROM AUTHOR]

Due to the advantages of ease of use, less motion disturbance, and low cost, wearable systems have been widely used in the human–machine interaction (HRI) field. However, HRI in complex clinical rehabilitation scenarios has further requirements for wearable sensor systems, which has aroused the interest of many researchers. However, the traditional wearable system has problems such as low integration, limited types of measurement data, and low accuracy, causing a gap with the actual needs of HRI. This paper will introduce the latest progress in the current wearable systems of HRI from four aspects. First of all, it introduces the breakthroughs of current research in system integration, which includes processing chips and flexible sensing modules to reduce the system's volume and increase battery life. After that, this paper reviews the latest progress of wearable systems in electrochemical measurement, which can extract single or multiple biomarkers from biological fluids such as sweat. In addition, the clinical application of non-invasive wearable systems is introduced, which solves the pain and discomfort problems caused by traditional clinical invasive measurement equipment. Finally, progress in the combination of current wearable systems and the latest machine-learning methods is shown, where higher accuracy and indirect acquisition of data that cannot be directly measured is achieved. From the evidence presented, we believe that the development trend of wearable systems in HRI is heading towards high integration, multi-electrochemical measurement data, and clinical and intelligent development. [ABSTRACT FROM AUTHOR]

Given the popularity of Big Data (BD), there can be an impression that fields such as design of experiments (DOE) are now irrelevant. We would like to thank the authors for starting the conversation about the possible relationship between these two fields. A key contribution of this paper is in showing how DOE principles, as summarized under the name designed data collection (DDC), can be applied throughout the BD process. This name is quite appropriate, demonstrating that these principles apply not just to designed experiments, but to any form of data collection. This is especially important for situations where designed experiments are either impossible (i.e., assessing how a country's economy may impact certain responses) or unethical (i.e., certain sensitive types of medical studies). It shows that DOE is more than a particular choice of design type, but is rather a methodology for approaching data collection. One that seeks to extract the most relevant information from the data while also taking into account the various nuances and constraints of physical and social processes, which are ever present, even in massive datasets. The paper divides BD efforts into three general phases: Before BD, During BD, and After BD. As such, we have grouped our discussion accordingly, with general comments provided for the suggested contributions of DDC in each phase. We then close with some additional thoughts. [ABSTRACT FROM AUTHOR]

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Agricultural technologies (agri-techs) have focused on developing the AI perspective of human-AI interaction rather than human perceptions and responses. A lack of understanding of their employees' behavioral responses when interacting with advanced technologies can lead to unexpected problems in the future. Drawing on the theoretical perspective of advanced user engagement, this paper examines the impact of five different technostressors on user engagement and, consequently, user experience. For data collection, 464 participants from the U.S. and Asian (Singaporean) agri-tech sectors were interviewed via an electronic survey. The U.S. study showed that techno-overload, techno-complexity, and techno-uncertainty were positively related to user engagement (t = 2.609; t = 6.998, and t = 6.013, respectively), whereas techno-invasion and techno-uncertainty were negatively correlated with user engagement (t = –2.167 and t = –3.119, respectively). The Singapore study showed that techno-overload, techno-complexity, and techno-invasion were negatively related to user engagement (t = –2.185, t = –2.765; t = –5.062, respectively), while techno-insecurity and techno-uncertainty surprisingly showed nonlinear correlations with user engagement. In both studies, user engagement is positively related to user experience (t = 2.009 for the U.S. study and t = 2.887 for the Singapore study). First, this paper provides agri-techs with a modern framework to better predict the behavioral responses of their employees when managing AI. Second, this paper expands the equation of change in the discipline of change management by introducing the dimension of readiness. [ABSTRACT FROM AUTHOR]

With the development of the social economy and the continuous growth of the population, emergencies within field stations are becoming more frequent. To improve the efficiency of emergency evacuation of field stations and further protect people's lives, this paper proposes a method based on improved YOLOv5s target detection and Anylogic emergency evacuation simulation. This method applies the YOLOv5s target detection network to the emergency evacuation problem for the first time, using the stronger detection capability of YOLOv5s to solve the problem of unstable data collection under unexpected conditions. This paper first uses YOLOv5s, which incorporates the SE attention mechanism, to detect pedestrians inside the site. Considering the height of the camera and the inability to capture the whole body of the pedestrian when the site is crowded, this paper adopts the detection of the pedestrian's head to determine the specific location of the pedestrian inside the site. To ensure that the evacuation task is completed in the shortest possible time, Anylogic adopts the principle of closest distance evacuation, so that each pedestrian can leave through the exit closest to him or her. The experimental results show that the average accuracy of the YOLOv5s target detection model incorporating the SE attention mechanism can reach 94.01%; the constructed Anylogic emergency evacuation model can quickly provide an evacuation plan to guide pedestrians to leave from the nearest exit in an emergency, effectively verifying the feasibility of the method. The method can be extended and applied to research related to the construction of emergency evacuation aid decision-making systems in field stations. [ABSTRACT FROM AUTHOR]

This paper aims to critique approaches to qualitative coding that carry a bottom-up or inductive thinking. Despite the wide contributions of this epistemology to the social sciences, this paper contends that contemporary research and methodological debates have inadequately explored different epistemologies for coding. As such, this paper proposes and explores the concept of 'reverse coding.' In applying reverse coding to ethnographic data collected from observations of a multicultural language classroom, I demonstrate that reverse coding can explore intuitions or 'hunches' generated from the data that may not be supported by conventional qualitative coding. By finding such support through reverse coding, or the process of identifying preliminary propositions first and its constituent features afterward, this paper asserts that research employing multiple approaches to coding can extend its range of analysis to generate more robust findings. [ABSTRACT FROM AUTHOR]

Background: The diversity of patient experiences of orphan drug development has until recently been overlooked, with the existing literature reporting the experience of some patients and not others. The current evidence base (the best available current research) is dominated by quantitative surveys and patient reported outcome measures defined by researchers. Where research that uses qualitative methods of data collection and analysis has been conducted, patient experiences have been studied using content analysis and automatic textual analysis, rather than in-depth qualitative analytical methods. Systematic reviews of patient engagement in orphan drug development have also excluded qualitative studies. The aim of this paper is to review qualitative literature about how patients and other members of the public engage with orphan drug development. Methods: We conducted a systematic search of qualitative papers describing a range of patient engagement practices and experiences were identified and screened. Included papers were appraised using a validated tool (CASP), supplemented by reporting guidance (COREQ), by two independent researchers. Results: 262 papers were identified. Thirteen papers reported a range of methods of qualitative data collection. Many conflated patient and public involvement and engagement (PPIE) with qualitative research. Patients were typically recruited via their physician or patient organisations. We identified an absence of overarching philosophical or methodological frameworks, limited details of informed consent processes, and an absence of recognisable methods of data analysis. Our narrative synthesis suggests that patients and caregivers need to be involved in all aspects of trial design, including the selection of clinical endpoints that capture a wider range of outcomes, the identification of means to widen access to trial participation, the development of patient facing materials to optimise their decision making, and patients included in the dissemination of trial results. Conclusions: This narrative qualitative synthesis identified the explicit need for methodological rigour in research with patients with rare diseases (e.g. appropriate and innovative use of qualitative methods or PPIE, rather than their conflation); strenuous efforts to capture the perspectives of under-served, under-researched or seldom listened to communities with experience of rare diseases (e.g. creative recruitment and wider adoption of post-colonial practices); and a re-alignment of the research agenda (e.g. the use of co-design to enable patients to set the agenda, rather than respond to what they are being offered). [ABSTRACT FROM AUTHOR]

The data science era is characterized by data-driven automated decision systems (ADS) enabling, through data analytics and machine learning, automated decisions in many contexts, deeply impacting our lives. As such, their downsides and potential risks are becoming more and more evident: technical solutions, alone, are not sufficient and an interdisciplinary approach is needed. Consequently, ADS should evolve into data-informed ADS, which take humans in the loop in all the data processing steps. Data-informed ADS should deal with data responsibly, guaranteeing nondiscrimination with respect to protected groups of individuals. Nondiscrimination can be characterized in terms of different types of properties, like fairness and diversity. While fairness, i.e., absence of bias against minorities, has been widely investigated in machine learning, only more recently this issue has been tackled by considering all the steps of data processing pipelines at the basis of ADS, from data acquisition to analysis. Additionally, fairness is just one point of view of nondiscrimination to be considered for guaranteeing equity: other issues, like diversity, are raising interest from the scientific community due to their relevance in society. This paper aims at critically surveying how nondiscrimination has been investigated in the context of complex data science pipelines at the basis of data-informed ADS, by focusing on the specific data processing tasks for which nondiscrimination solutions have been proposed. [ABSTRACT FROM AUTHOR]

Hypoxia in coastal environments is a worldwide problem and is expected to worsen in future. Due to the stratification of the water column in many enclosed or semi-enclosed gulfs, deep waters are isolated and hypoxic or anoxic conditions frequently become dominant. The most common method for the oxygenation of these isolated anoxic water masses is vertical mixing. However, there are enclosed gulfs which rarely have the appropriate energy to ensure the mixing of the entire water column. The main purpose of this paper is to find if there are any other hydrodynamic processes which can cause oxygenation of deep waters, apart from vertical mixing. In order to achieve this aim, an enclosed gulf, Amvrakikos in Western Greece, was chosen to be the case study area and bimonthly physicochemical data were collected for one year and used in combination with a three-dimensional model in order to simulate the hydrodynamic circulation of the system. According to our results, another hydrodynamic process can lead to the oxygenation of the deepest water in an enclosed gulf. This process is the horizontal intrusion of well oxygenated water from the open sea. The key factor in determining the success of this horizontal intrusion is the density difference between the deepest area of the enclosed gulf and the open sea outside the gulf. From autumn to winter, when the open sea water is denser than that inside the gulf, the well oxygenated open sea water inflows into the gulf near the bottom sea floor and re-oxygenates the isolated deep waters through mixing. However, from spring to summer, when the deep water of the gulf is characterized by higher density in comparison with the open sea water, the inflow of well oxygenated water stops, causing the development of hypoxic/anoxic conditions during the summer months. [ABSTRACT FROM AUTHOR]

Background: Paper questionnaires have traditionally been the first choice for data collection in research. However, declining response rates over the past decade have increased the risk of selection bias in cross-sectional studies. The growing use of the Internet offers new ways of collecting data, but trials using Web-based questionnaires have so far seen mixed results. A secure, online digital mailbox (e-Boks) linked to a civil registration number became mandatory for all Danish citizens in 2014 (exemption granted only in extraordinary cases). Approximately 89% of the Danish population have a digital mailbox, which is used for correspondence with public authorities.Objective: We aimed to compare response rates, completeness of data, and financial costs for different invitation methods: traditional surface mail and digital mail.Methods: We designed a cross-sectional comparative study. An invitation to participate in a survey on help-seeking behavior in out-of-hours care was sent to two groups of randomly selected citizens from age groups 30-39 and 50-59 years and parents to those aged 0-4 years using either traditional surface mail (paper group) or digital mail sent to a secure online mailbox (digital group). Costs per respondent were measured by adding up all costs for handling, dispatch, printing, and work salary and then dividing the total figure by the number of respondents. Data completeness was assessed by comparing the number of missing values between the two methods. Socioeconomic variables (age, gender, family income, education duration, immigrant status, and job status) were compared both between respondents and nonrespondents and within these groups to evaluate the degree of selection bias.Results: A total 3600 citizens were invited in each group; 1303 (36.29%) responded to the digital invitation and 1653 (45.99%) to the paper invitation (difference 9.66%, 95% CI 7.40-11.92). The costs were €1.51 per respondent for the digital group and €15.67 for paper group respondents. Paper questionnaires generally had more missing values; this was significant in five of 17 variables (P<.05). Substantial differences were found in the socioeconomic variables between respondents and nonrespondents, whereas only minor differences were seen within the groups of respondents and nonrespondents.Conclusions: Although we found lower response rates for Web-based invitations, this solution was more cost-effective (by a factor of 10) and had slightly lower numbers of missing values than questionnaires sent with paper invitations. Analyses of socioeconomic variables showed almost no difference between nonrespondents in both groups, which could imply that the lower response rate in the digital group does not necessarily increase the level of selection bias. Invitations to questionnaire studies via digital mail may be an excellent option for collecting research data in the future. This study may serve as the foundational pillar of digital data collection in health care research in Scandinavia and other countries considering implementing similar systems. [ABSTRACT FROM AUTHOR]

This study conducts a systematic review of salesperson sampling within the pages of the Journal of Personal Selling and Sales Management from 2013 to 2022. A total of 284 papers (all inclusive) were identified in the first step of the review. Next articles were qualified based on article types, methodology (research approach), and respondent type before additional analysis was conducted. This resulted in 109 published manuscripts with 147 unique salesperson samples for further review. Specifically, sample scope and participant profiles were examined based on the 109 articles. The sample scope included response metrics, study deployment, and contextual aspects. Participant profile includes the examination of demographics, experience, work details, and performance. Ensuing the systematic review, managerial importance and implications, best practices, and research insights and future research directions are provided. This includes guidance on the sampling frame overview, data collection, and sample contexts of participants for a better understanding of what information should be included in research studies. In turn, this study puts forth evidence that one type of salesperson sample does not fit all sales research, and the generalizability of the sample should be carefully considered. [ABSTRACT FROM AUTHOR]