Search

Despite extensive developments in the field of Human Resource Management, we still have limited and fragmented knowledge of how the external and internal environment of an organization influences direct employee voice. In this conceptual paper, we draw on signaling theory and theorize on whether and, if so, how direct employee voice and organizational voice climate are shaped at times of macro and organizational turbulence. Specifically, we introduce the concepts of solidary, utilitarian, and opportunistic crisis‐related Human Resource (HR) practices and propose that they send different signals to employees, influencing their voice perceptions in distinctive ways. We also theorize that employees interpret these signals vis‐à‐vis the experienced meso‐ and macroturbulence, a process that affects HR system strength and the subsequent formulation of voice perceptions and voice climate emergence. With this work, we contribute to the voice and strategic HR literature by offering an integrated and multilayered understanding of how top‐down processes at turbulent times such as crisis‐related HR practices can influence bottom‐up emergent phenomena. [ABSTRACT FROM AUTHOR]

Decision prediction based on neurophysiological signals is of great application value in many real‐life situations, especially in human–AI collaboration or counteraction. Single‐trial analysis of electroencephalogram (EEG) signals is a very valuable step in the development of an online decision‐prediction system. However, previous EEG‐based decision‐prediction methods focused mainly on averaged EEG signals of all decision‐making trials to predict an individual's general decision tendency (e.g., risk seeking or aversion) over a period rather than on a specific decision response in a single trial. In the present study, we used a rock–paper–scissors game, which is a common multichoice decision‐making task, to explore how to predict participants' single‐trial choice with EEG signals. Forty participants, comprising 20 females and 20 males, played the game with a computer player for 330 trials. Considering that the decision‐making process of this game involves multiple brain regions and neural networks, we proposed a new algorithm named common spatial pattern‐attractor metagene (CSP‐AM) to extract CSP features from different frequency bands of EEG signals that occurred during decision making. The results showed that a multilayer perceptron classifier achieved an accuracy significantly exceeding the chance level among 88.57% (31 of 35) of participants, verifying the classification ability of CSP features in multichoice decision‐making prediction. We believe that the CSP‐AM algorithm could be used in the development of proactive AI systems. [ABSTRACT FROM AUTHOR]

Reviews have long been recognized as among the most important forms of scientific communication. The rapid growth of the primary literature has further increased the need for reviews to distill and interpret the literature. This review on Reviews and Reviewing: Approaches to Research Synthesis encompasses the evolution of the review literature, taxonomy of review literature, uses and users of reviews, the process of preparing reviews, assessment of review quality and impact, the impact of information technology on the preparation of reviews, and research opportunities for information science related to reviews and reviewing. In addition to providing a synthesis of prior research, this review seeks to identify gaps in the published research and to suggest possible future research directions. [ABSTRACT FROM AUTHOR]

After offering great promise and attracting substantial investment in technology development, fields emission did not succeed in the competition against liquid crystal technology for computer screens and plasma technology for large flat panel television. We review and analyze some of the challenges that prevented field emission from becoming a mayor information display technology. W e report the development of a novel modelling tool that can be used to support the design of field emitters optimized to the application requirements. The previous lack of such a simulation tool that incorporates the range of phenomena that affect field emission has been a limiting factor in emitter performance and data analysis. The new model enables more accurate and effective design of field emitters including the emission dynamics and thermal behaviour for a wide range of geometries and materials. It provides a powerful tool with high accessibility to support engineers to make informed decisions as part of the product design process. This increases opportunities for field emission to be used in a range of non‐display applications. [ABSTRACT FROM AUTHOR]

Introduction: Collaborative approaches in speech‐language pathology (SLP) aim to integrate the experience of clients and people important to them by including these stakeholders actively in decision making. This inclusion can lead to more effective, engaging, and safer SLP practice. A variety of collaborative approaches have evolved in response to sociocultural contexts, and as a result, there are many different approaches currently in use such as co‐design, co‐production, and co‐creation. However, despite widening acceptance and utilisation of collaborative approaches, the use and evidence for these in SLP literature have not been considered collectively. The current study aims to explore how collaborative approaches, used to develop products or services in SLP, are reported in literature. Methods: Using narrative review methodology, a systematic search of three databases and hand searching were conducted to explore how collaborative approaches, used to develop products or services, are reported in SLP. Search terms reflected the breadth of collaborative approaches and the diverse nature of SLP across clinical practice. Following screening of initial data, 59 articles were identified for data extraction and narrative synthesis. An internationally recognised reporting checklist for stakeholder involvement called the Guidance for Reporting Involvement of Patients and the Public, Version 2 (GRIPP2), informed the reviewing process in addition to qualitative description. Results: Collaborative approaches across SLP practice were found to be diverse as were the terminology and tools used for collaboration. Two‐thirds of the studies were published after 2020. The timing and involvement of stakeholders in collaborative approaches varied greatly; however, most stakeholder involvement was found in the conducting of research activities, compared to other areas such as planning, analysis, and reporting. The GRIPP2 review indicated strengths and opportunities in reporting of stakeholder involvement. When stakeholder involvement was rigorously reported it could include reflection on how stakeholders contributed within their communication abilities and how this contribution benefited the study. Conclusion: Collaborative approaches reported in SLP focused on valuing and respecting people with living experience of communication and swallowing difficulties. This narrative review contributes to the resources available to support decision‐making and working together with stakeholders, encouraging SLPs to reflect, consider the context and respond. Future research could continue to strengthen consistency in terminology for collaborative approaches, use frameworks to plan and report stakeholder involvement and carefully consider involvement across the research continuum. WHAT THIS PAPER ADDS: What is already known on this subject: There is an expectation that health services include stakeholders in development and evaluation of services. Collaborative approaches in speech‐language pathology (SLP) aim to integrate the lived experience of people with communication and swallowing difficulties and those important to them. These approaches, including but not limited to, co‐design, co‐production and participatory action research, have shared philosophies of being community‐driven, strengths based and inclusive (Loeffler & Bovaird, 2021). What this paper adds to existing knowledge: This study contributes information about current SLP practice when collaborative approaches have been employed to develop a product or service. The study maps diverse collaborative approaches and their frequency in the literature, as well as the various stakeholders involved, using the Guidance for Reporting Involvement of Patients and the Public, Version 2 (GRIPP2) checklists to guide the review of reporting stakeholder involvement. What are the potential or actual clinical implications of this work?: This synthesis of literature supports researchers and clinicians in making intentional decisions in implementation and reporting of collaborative approaches. This decision‐making can strengthen the implementation of collaborative approaches, which has implications for person‐centred care in SLP. [ABSTRACT FROM AUTHOR]

Background: Accessibility of data visualization has been explored for users with visual disabilities but the needs of users with language disabilities have seldom been considered. Aim: This scoping review synthesised what is known about data visualization for adults with language disabilities, specifically the acquired language disability, aphasia and Developmental Language Disorder. It sought to extract key findings and identify what practices support effective visualization for decision making for people with language disabilities. Method: Papers were included if they investigated visualization of data, and the consumers of the data visualization were people with aphasia or developmental language disability. Seven databases were searched: CINAHL, Academic Search, Medline, PsychINFO, Ovid, ACM Digital Library and IEEE Xplore. Included studies were charted to extract title, author(s), year, country, paper type, scientific field, participant number(s), participant group(s), main topic, subtopic, method, task description, task category, data visualization, summary, key findings relevant to the review question, and guidelines or recommendations. Narrative synthesis was used to describe how people with language disability have interacted with data visualization from a range of literature. Main Contribution: Six studies (seven publications) were included in the review. One study came from the field of health, one from a disability rights collaboration and four studies from computer science. No studies satisfying the review criteria explored data visualization for Developmental Language Disorder; however, five studies explored participants with cognitive disabilities that included impairments of language, so these were included. A range of visualization designs were found. Studies predominantly explored understanding of visualization (4/6). One study explored how to express data visually, and one explored the use of the visualization that is, for an action, choice, or decision. Cognitively accessible data visualization practices were described in four papers and synthesized. Supportive practices reported were reducing the cognitive load associated with processing a visualization and increasing personal relevance of data visualization. Conclusion: Accessible data visualization for adults with aphasia and Developmental Language Disorder has only minimally been explored. Practices to specifically support users with language disability are not yet apparent. As data use in making everyday decisions is widespread, future research should explore how people with language disabilities make use of data visualization. WHAT THIS PAPER ADDS: What is already known on this subject: Visual resources are used widely to support people with language disabilities in understanding of language. That is, icons, maps timelines and so forth, are used to support auditory processing. However, data visualization is used routinely by people without a language disability to support everyday decisions for example, visualization of live traffic data is used to provide users with the best route to their destination. It is unclear whether any work has explored data visualization for people with language disabilities. What this paper adds to existing knowledge: This paper brings together research on the use of data visualization by adults with either Developmental Language Disorder or aphasia, collectively people with language disabilities. It highlights a gap in the design of inclusive data visualization for language disabilities and the minimal research exploring the use of data visualization for decision making in these populations. What are the clinical implications of this work?: Access to data can be empowering. It has potential to enable agency in decisions and increase social participation. The existing gap in knowledge about how to design inclusive data visualization for people with language disabilities thus poses a risk of exclusion and threats to informed decision making. Highlighting the current field of literature may drive research and clinical activity. [ABSTRACT FROM AUTHOR]

This paper presents a case study narrative of one woman. Drawing on her storied recollections, from infancy into childhood through young motherhood into adulthood, we trace the interlocking relationship between policies and practices intended to offer welfare support facilitating her criminalization. A collaborative approach to producing knowledge, representing 8 years of narrative, dialogue and reflection surfaces a looming panopticon. The gendered power of the state to intervene across the life course is revealed, as is the failed and harmful nature of this panopticon. Three distinct themes emerge from the analysis: the power to define and the fixing nature of gendered policy and practice narratives; the gendered control strategies that reproduce harms in women's lives; and the lifelong nature of the panopticon for some girls and women. Cutting across these experiences are processes of silencing and ultimately resistance, strategies for surviving the enduring forms of institutional surveillance and intervention. The paper closes with clear implications for the hegemonic trio of social science research and social work and criminal justice policy and practice. We must confront and dismantle our complicity in the silent silencing and gendered harms of the panopticon. [ABSTRACT FROM AUTHOR]

Aboriginal children and young people are over‐represented in the out‐of‐home care system, yet their voices are largely absent in practice and policy decision‐making. This paper presents a review of research that captures the voices of Aboriginal children and young people in out‐of‐home care. Three key themes are discussed: connection to culture, connection to family and participation. This paper argues for culturally meaningful research that honours child and youth citizenship, voice and roles in decision‐making as critical to quality care and positive outcomes. This paper aims to highlight the importance of listening and responding to the voices of Aboriginal children and young people as critical to the provision of appropriate care and supporting positive outcomes. [ABSTRACT FROM AUTHOR]

Introduction: The Activating Lived Experience Leadership (ALEL) project was a South Australian participatory action research project that aimed to improve the ways lived experience is recognised, valued and integrated across mental health and social sector systems. ALEL was completed during 2019–2021, where it engaged 182 participants in generating community action and research knowledge. Objective: Our paper discusses the project's processes of building a collective partnership among lived experience leaders and other leaders from within the sector, so that the actions and strategies identified through research could be implemented by systems‐level impact. We describe the collaborative process and key learnings that resulted in eight key action areas for transformative systems change in South Australia. Methods: The project invited a diverse range of self‐identified lived experience and other leaders to be involved in a PAR process featuring formal qualitative research (focus groups, surveys and interviews) as well as community development activities (leaders' summit meetings, consultations, training and community of practice meetings). These processes were used to help us describe the purpose, achievements and potential of lived experience leadership. Project priorities and systems‐level analysis was also undertaken with lived experience sector leaders and project advisors across two leaders' summit meetings, integrating research outcomes with sector planning to define high‐level actions and a vision for transformational change. Results: Participatory action research as informed by systems change and collective impact strategies assisted the project to generate detailed findings about the experiences and complexities of lived experience leadership, and collective responses of how systems could better support, be accountable to and leverage lived experience perspectives, experience and peer‐work approaches. Conclusion: Systems change to define, value and embed lived experience leadership benefits from collective efforts in both formal research and sector development activities. These can be used to generate foundational understandings and guidance for working together in genuine ways for transforming mental health and social sector systems, experience and outcomes. Public Contribution: Members of lived experience communities codesigned the project, and contributed to project governance and the development of all findings and project reports. [ABSTRACT FROM AUTHOR]

Background: Children with medical complexity (CMC) have high healthcare utilization and face unique challenges during hospital admissions. The evidence describing their experiences of inpatient care is distributed across disciplines. The aim of this scoping review was to map the evidence related to the inpatient experience of care for CMC and their families, particularly related to key aspects and methodological approaches, and identify gaps that warrant further study. Methods: This scoping review was conducted in accordance with JBI methodology and included all studies that reported experiences of acute hospital care for CMC/families. All study designs were included. Databases searched included EMBASE, CINAHL Plus with Full Text, Web of Science, MEDLINE(R) and APA PsycInfo from 2000 to 2022. Details about the participants, concepts, study methods and key findings were abstracted using a data abstraction tool. A thematic analysis was conducted. Results: Forty‐nine papers were included: 27 qualitative studies, 10 quantitative studies, six mixed methods studies, two descriptive studies and four reviews. Some quantitative studies used validated instruments to measure experience of care, but many used non‐validated surveys. There were a few interventional studies with a small sample size. Results of thematic analysis described the importance of negotiating care roles, shared decision‐making, common goal setting, relationship‐building, communication, sharing expertise and the hospital setting itself. Conclusion: CMC and families value relational elements of care and partnering through sharing expertise, decision‐making and collaborative goal‐setting when admitted to hospital. Patient or Public Contribution: This review was conducted in alignment with the principles of patient and family engagement. The review was conceptualized, co‐designed and conducted with the full engagement of the project's parent–partner. This team member was involved in all stages from constructing the review question, to developing the protocol, screening articles and drafting this manuscript. Practitioner Points: Qualitative research describes key elements of inpatient experience of care for CMC and their families as relationships, communication, respect for parent/provider expertise and the hospital setting. There is less evidence on measuring experience of care using quantitative methodology, particularly using validating instruments. This would be helpful to support the evaluation of inpatient interventions to improve the experiences of CMC. [ABSTRACT FROM AUTHOR]

Study Aims: The present paper aimed at discussing how the process of decision‐making should be taken care of in healthcare services. Methods: This is a position paper based on a review of the relevant literature about meaning‐making processes in medical encounters and psychotherapy. Discussion: Authors argued that choice options could be perceived as meaningful by patients if their uncertainties were taken into account and grounded on mutual understanding and reciprocal trust. To this end, any decision‐making process should satisfy the patient's legitimate expectations by making choices and habits compatible. Conclusion: In depht analysis of meaning‐making processes is crucial for better refining good practices of shared decision‐making. [ABSTRACT FROM AUTHOR]

Background: With increased use of artificial intelligence in the classroom, there is now a need to better understand the complementarity of intelligent learning technology and teachers to produce effective instruction. Objective: The paper reviews the current research on intelligent learning technology designed to make models of student learning and instruction transparent to teachers, an area we call model‐based learning analytics. We intended to gain an insight into the coupling between the knowledge models that underpin the intelligent system and the knowledge used by teachers in their classroom decision making. Methods: Using a systematic literature review methodology, we first identified 42 papers, mainly from the domain of intelligent tutoring systems and learning analytics dashboards that conformed to our selection criteria. We then qualitatively analysed the context in which the systems were applied, models they used and benefits reported for teachers and learners. Results and Conclusions: A majority of papers used either domain or learner models, suggesting that instructional decisions are mostly left to teachers. Compared to previous reviews, our set of papers appeared to have a stronger focus on providing teachers with theory‐driven insights and instructional decisions. This suggests that model‐based learning analytics can address some of the shortcomings of the field, like meaningfulness and actionability of learning analytics tools. However, impact in the classroom still needs further research, as in half of the cases the reported benefits were not backed with evidence. Future research should focus on the dynamic interaction between teachers and technology and how learning analytics has an impact on learning and decision making by teachers and students. We offer a taxonomy of knowledge models that can serve as a starting point for designing such interaction. Lay Description: What is currently known: Current learning analytics solutions are often not perceived helpful by teachers What this paper adds: Model‐based learning analytics seeks to make these systems more transparent and actionableOur review shows there is good potential that systems designed in this way would have greater impact on classroom teaching Implications for practitioners: Pedagogical‐psychological models should be an integral part of intelligent learning systems designsWe offer a taxonomy of such models and current good practices of their use as a starting point [ABSTRACT FROM AUTHOR]

Background: Liver disease is an increasing cause of morbidity and mortality in the United Kingdom and can be challenging to live with in the advanced stages. There has been little research exploring the healthcare experiences of UK individuals with decompensated disease when the liver cannot carry out its functions properly. A PhD research project was developed with people who have liver disease to explore care experiences in decompensated advanced liver disease. Public involvement (PI) is an essential aspect of meaningful health research, and this paper reports on the progression of our PI approach in this ongoing study. Objective: To embed PI throughout the research project to ensure that the study is meaningful to individuals with liver disease and the people who support them. Methods: The research adopts a Constructivist Grounded Theory methodology to develop a theory of care experience. Various PI approaches were considered in developing the PI strategy for this qualitative study. Initially, Embedded consultation was the preferred model, which has evolved to include aspects of collaboration and coproduction. A PI group was set up to oversee the project through the national public engagement website VOICE, and reflections on PI from three members of the group are included in this paper to illuminate the PI process. Results: Six individuals with liver disease and three carers from across the United Kingdom are part of an ongoing PI group. Their role includes commenting on the findings of the systematic literature review for this project and contributing to decisions about recruitment, data collection and data analysis. Additionally, they had a direct impact on changing the focus of the research. The PI group will continue involvement until the completion of the project. Conclusion: Successfully embedding PI into doctoral research, as demonstrated in this project, requires commitment, planning and dedication to reciprocal working for the benefit of PI contributors as well as the research. This approach could be adopted by other postgraduate researchers. Patient or Public Contribution: This project is overseen by the PI group, whose contribution is described throughout, including reflections from three PI group members. [ABSTRACT FROM AUTHOR]

With the development of automated vehicles, researches related to automated vehicle platoon (AVP) have received more and more attention. AVP is considered one of the effective means to alleviate traffic congestion and reduce vehicle energy consumption. This paper studies a three‐layer method of avoiding obstacle vehicles in traffic by switching the formation for the automated heavy vehicle platoon. In the decision‐making layer, a decision‐making system based on the finite‐state machine is established for formation switching. In the second layer, the lane‐changing trajectory is optimized based on the quantic polynomial curve fitting for vehicles that need to change lanes. In terms of vehicle control layer, each vehicle has a longitudinal controller based on sliding mode control and a lateral controller based on model predictive control to track the planned trajectory to complete the target formation. Finally, the proposed method is simulated in MATLAB/TruckSim. The simulation results show that the proposed method could effectively avoid the obstacle vehicles by switching the formation and has a small average value of errors in speed tracking and trajectory tracking. [ABSTRACT FROM AUTHOR]

Background: Implementation of shared decision‐making in antenatal care has had limited exploration. Objective: To assess what is known about shared decision‐making in antenatal care. Search Strategy: Five databases were searched (1997–2022) limited to English language studies from OECD countries. Data Collection and Analysis: A data collection table was constructed with findings from 32 papers. A narrative synthesis was conducted with subsequent thematic analysis of included papers. Main Results: Four areas of decision‐making were identified with six themes revealing enablers and barriers to shared decision‐making in antenatal care. Conclusion: Implementation of shared decision‐making requires continuity, time and personalisation of care. [ABSTRACT FROM AUTHOR]

This article is a comment on a previous paper about social learning on networks. The comment corrects a proposition in the original paper, stating that the condition for imitation to be optimal is stronger than previously thought. However, this correction does not affect the other findings and conclusions of the original paper. The comment also discusses the implications of this correction, suggesting that it reduces the set of networks where a few dominant agents determine the beliefs of all network members. [Extracted from the article]

In the cooperative vehicle‐infrastructure system (CVIS), due to its computation limitation, vehicles are difficult to handle computing‐intensive delay‐sensitive tasks, so offload tasks to roadside unit (RSU) become popular. Due to the complexity of vehicles' tasks and tasks generated by different vehicles have different delay constraints, minimize energy consumption of RSUs under task dependence and delay constraints is challenging. This paper defines the task priority queuing criterion for the task priority division problem, proposes a task scheduling strategy for energy‐packet queue length tradeoff (TSET) in CVIS under RSUs distributed task scheduling problem and establishes the vehicle speed state model, task model, data queue model, task computing model and energy consumption model. After Lyapunov optimization theory transformed the optimization model, a knapsack problem was described. The simulation results verify that TSET reduces the average energy consumption of roadside units and ensures the stability of the data queue under task dependence and deadline conditions. [ABSTRACT FROM AUTHOR]

Objectives: Despite high levels of mental ill‐health amongst young people (aged 15–30), this group demonstrates low help‐seeking and high drop‐out from mental health services (MHS). Whilst shared decision‐making can assist people in receiving appropriate and effective health care, young people frequently report that they do not feel involved in treatment decisions. The current study focused on co‐design of a clinical education and participant information programme for the Brain and Mind Centre Youth Model of Care. This model, which articulates a youth‐focused form of highly personalised and measurement‐based care, is designed to promote shared decision‐making between young people and clinical service providers. Methods: We conducted workshops with 24 young people (16–31; MAge = 21.5) who had accessed mental health services. Participants were asked what advice they would give to young people entering services, before giving advice on existing materials. Workshops were conducted and transcripts were coded using thematic analysis by two lived experience researchers and a clinical researcher. Results: Young people found it empowering to be educated on transdiagnostic models of mental illness, namely clinical staging, which gives them a better understanding of why certain treatments may be inappropriate and ineffective, and thus reduce self‐blame. Similarly, young people had limited knowledge of links between mental health and other life domains and found it helpful to be educated on multidisciplinary treatment options. Measurement‐based care was seen as an important method of improving shared decision‐making between young people and health professionals; however, to facilitate shared decision‐making, young people also wanted better information on their rights in care and more support to share their expertise in their own needs, values and treatment preferences. Conclusions: These findings will inform the delivery of the further development and implementation of a youth‐specific clinical education and participant information programme for the BMC Youth Model. Patient or Public Contribution: Workshops were facilitated by researchers with lived expertise in mental ill‐health (A.H. and/or C.G.) and a clinical researcher (who has expertise as an academic and a clinical psychologist). A.H. and C.G. were also involved in conceptualisation, analysis, interpretation, review and editing of this paper. [ABSTRACT FROM AUTHOR]

With the continuous growth of electricity demand, the safe and stable operation of distribution lines is crucial for power transportation. Unmanned aerial vehicle (UAV) inspection has been widely used for the maintenance and repair of distribution lines. Due to the limitations of computational power and endurance, it is difficult for UAVs to independently complete data processing. Combined with mobile edge computing (MEC), this paper proposes a computing offloading strategy based on multi‐agent reinforcement learning and double‐layer offloading mechanism, which can further utilize the computing power of non‐task devices and edge servers. Firstly, three‐layer system architecture, named MEC‐U‐NTDC (MEC‐UAV‐Non‐task Device Cloud), is built. Secondly, double‐layer offloading mechanism is designed to comprehensively utilize the computing power of edge servers and neighbouring non‐task devices. Finally, a multi‐agent algorithm DLMQMIX is proposed to minimize the total cost for UAV inspection. Simulation experiments show that the proposed algorithm can effectively solve the task offloading problem of UAV‐aided distribution line inspection, and compared with algorithms such as PSO, GA, and QMIX, it performs better in terms of average delay, system cost, and load balancing, achieving a smaller total system cost. [ABSTRACT FROM AUTHOR]

Introduction: The real‐world mechanisms underlying prospective entrustment decision making (PEDM) by entrustment or clinical competency committees (E/CCCs) are poorly understood. To advance understanding in this area, the authors conducted a realist synthesis of the published literature to address the following research question: In E/CCC efforts to make defensible prospective entrustment decisions (PEDs), what works, for whom, under what circumstances and why? Methods: Realist work seeks to understand the contexts (C), mechanisms (M) and outcomes (O) that explain how and why things work (or do not). In the authors' study, contexts included individual E/CCC members, E/CCC structures and processes, and training programmes. The outcome (i.e. desired outcome) was a PED. Mechanisms were a substantial focus of the analysis and informed the core findings. To define a final corpus of 52 included papers, the authors searched four databases, screened all results from those searches and performed a full‐text review of a subset of screened papers. Data extraction focused on developing context–mechanism–outcome configurations from the papers, which were used to create a theory for how PEDM leads to PEDs. Results: PEDM is often driven by default (non‐deliberate) decision making rather than a deliberate process of deciding whether a trainee should be entrusted or not. When defaulting, some E/CCCs find red flags that sometimes lead to being more deliberate with decision making. E/CCCs that seek to be deliberate describe PEDM that can be effortful (when data are insufficient or incongruent) or effortless (when data are robust and tell a congruent story about a trainee). Both information about trainee trustworthiness and the sufficiency of data about trainee performance influence PEDM. Several moderators influence what is considered to be sufficient data, how trustworthiness data are viewed and how PEDM is carried out. These include perceived consequences and associated risks, E/CCC member trust propensity, E/CCC member personal knowledge of and experience with trainees and E/CCC structures and processes. Discussion: PEDM is rarely deliberate but should be. Data about trainee trustworthiness are foundational to making PEDs. Bias, equity and fairness are nearly absent from the papers in this synthesis, and future efforts must seek to advance understanding and practice regarding the roles of bias, equity and fairness in PEDM. Entrustment decisions made by committees are rarely deliberate, but should be. These authors provide practical advice, based in the literature, for improvement. [ABSTRACT FROM AUTHOR]

The key motivation of this paper lies in the development of a high‐level decision‐making framework for autonomous overtaking maneuvers on two‐lane country roads with dynamic oncoming traffic. To generate an optimal and safe decision sequence for such scenario, an innovative high‐level decision‐making framework that combines model predictive control (MPC) and switching control methodologies is introduced. Specifically, the autonomous vehicle is abstracted and modelled as a switched system. This abstraction allows vehicle to operate in different modes corresponding to different high‐level decisions. It establishes a crucial connection between high‐level decision‐making and low‐level behaviour of the autonomous vehicle. Furthermore, barrier functions and predictive models that account for the relationship between the autonomous vehicle and oncoming traffic are incorporated. This technique enables us to guarantee the satisfaction of constraints, while also assessing performance within a prediction horizon. By repeatedly solving the online constrained optimization problems, we not only generate an optimal decision sequence for overtaking safely and efficiently but also enhance the adaptability and robustness. This adaptability allows the system to respond effectively to potential changes and unexpected events. Finally, the performance of the proposed MPC framework is demonstrated via simulations of four driving scenarios, which shows that it can handle multiple behaviours. [ABSTRACT FROM AUTHOR]

Human decision making is an act or process that is based on explicit or tacit knowledge, and can be supported in a limitless number of ways. Knowledge is a broad and delicate concept, rich in nuance, a concept that has been interpreted, understood, and categorized in different ways. Even if it may be true that "all knowing is personal knowing," all knowledge is not inevitably personal knowledge. Organizations have a common capability to act (i.e., knowledge capacity or intellectual capital), the lack of which would inevitably prevent organizational action and would lead to unpredictability, disorder and chaos. Hence, the conversion of personal knowledge to organizational usage has become an important and justified stream of research. However, there are serious conceptual barriers to deriving organizational knowledge directly from personal knowledge. Although the term "conversion" is partly misleading, it is used here in the absence of a better alternative to describe a type of knowledge generation process in which one kind of knowledge is used to create another kind of knowledge. In this paper, we define knowledge as the individual or organizational capability to make decisions. We show that the ability to make decisions is determined not only by the personal dimension but also by the social and material dimensions; knowledge is a triangular model that combines these three worlds. In order to explore and manage the resource of knowledge more effectively in organizational contexts, the key question involves how to support and stimulate the deployment of personal knowledge for common usage in organizational decision making. The contributions of this paper are firstly the provision of a theoretical basis for a virtual support context, and secondly a description of an experience with a concrete virtual context that supports and stimulates the conversion of personal knowledge into strategic, organizational decisions. The support system developed here provides a set of virtual conditions that can be used to exercise organizational skills and capabilities for effective decision making. [ABSTRACT FROM AUTHOR]

Model‐Based Systems Engineering (MBSE) is the next step in the evolution of systems engineering (SE) in which documents are replaced by descriptive models as the authoritative embodiment of SE knowledge. These descriptive models possess a unique combination of the features and characteristics of documents, software, and data. Conscientiously applying appropriate modeling principles and practices is essential to make informed decisions to moderate the accumulation of model technical debt. This paper briefly explains the concept of technical debt and its adaptation to the domain of descriptive models for MBSE. The paper then describes 18 foundational modeling principles that model architects should consider when making architectural and implementation decisions about their models and describes some of the key model technical debt tradeoffs that result when these principles are not followed. These principles address commonly observed challenges regarding model federation architecture, the selection and use of model layers, the modeling of the domain, and the semantics of modeling constructs. Applying disciplined model architecting practices to conscientiously manage the accrual and payoff of technical debt can make the difference between an enduring model that provides substantial value throughout the life cycle of the modeled entity and a model whose value collapses under the weight of uncontrolled technical debt. [ABSTRACT FROM AUTHOR]

Model‐Based Systems Engineering (MBSE) is the growing practice of systems engineering (SE) in which descriptive models replace documents as the embodiment of SE knowledge. These descriptive models capture SE information in place of documents, are developed in a similar manner to software source code, and are encoded and used in machine‐to‐machine applications as data. This paper describes how the Technical Debt concept widely used in the software domain—rework deferred to the future for expediency—needs to be modified for the domain of descriptive models. Technical Debt is often associated with agile development practices of software or descriptive models, which emphasize the rapid creation and iterative evolution of a Minimum Viable Product (MVP). Consciously applying appropriate modeling principles and practices is essential to make informed decisions during the modeling process to prevent the accumulation of excessive model Technical Debt—particularly during this iterative evolutionary process—which can require substantial rework to correct. The paper establishes a foundation for characterizing the Technical Debt implications of key model architecture and implementation decisions that are made explicitly or implicitly by modelers when developing descriptive models. To illustrate the model Technical Debt concept, several examples of modeling principles pertaining to model purpose and implementation are described along with their implications on model Technical Debt. [ABSTRACT FROM AUTHOR]

In unmanned aerial vehicle ad‐hoc network (UANET), the node speed of unmanned aerial vehicles (UAVs) may reach up to 400 km/h. The fast or slow movement of UAV nodes leads to different speeds of topology change of the nodes. Traditional optimized link state routing (OLSR) protocol cannot adaptively adjust the routing update period when the network topology changes, which may lead to the nodes calculating incorrect routing tables. This increases the average end‐to‐end delay and packet loss rate for packet transmission. To enhance the adaptability of OLSR routing protocol to network topology changes, this paper proposes a multi‐agent independent deep deterministic policy gradient‐OLSR (MA‐IDDPG‐OLSR) routing protocol based on distributed multi‐agent reinforcement learning. The protocol deploys DDPG algorithm on each UAV node, and each UAV node adaptively adjusts the Hello and TC message sending intervals, according to the one‐hop neighbouring nodes as well as its own state. Simulation results show that the proposed protocol is able to improve the throughput and reduce the packet loss rate as compared to traditional AODV, GRP, OLSR, and distributed multiple‐agent independent proximal policy optimization‐OLSR (MA‐IPPO‐OLSR), distributed multiple‐agent independent twin delayed deep deterministic policy gradient‐OLSR (MA‐ITD3‐OLSR) routing protocols. Since MA‐IDDPG‐OLSR relies only on local information, there is a minor performance degradation in MA‐IDDPG‐OLSR compared to centralized single‐agent DQN‐OLSR routing protocol. But it is more suitable to a completely distributed UAV network without a centralized node. [ABSTRACT FROM AUTHOR]

Vehicular caching (VC) in electro‐mobility networks has become promising for supporting the needs of low end‐to‐end service delays and reducing the load of networks (i.e. edge caching [EC]) for content delivery service. However, since VCs are available only when they are in the vicinity of the user, intermittent connectivity should be considered. In this paper, the opportunistic offloading scheme for content delivery service is proposed, and a decision is made regarding whether to use VC or EC for the content delivery service. In the proposed scheme, when VC is not available, the user determines whether to choose VC or EC for the content download. If VC is chosen, the user delays the content download to increase the VC utilization according to the expectation of VC contacts. This results in the delayed service completion but can reduce the EC load (i.e. offloading gain). If EC is chosen, the user can download the content without any delay or service interruption. To find the optimal policy, this paper formulates a Markov decision process (MDP) problem and uses the value iteration algorithm to solve the problem. The evaluation results show that the proposed scheme outperforms the comparison schemes based on the expected reward. [ABSTRACT FROM AUTHOR]

Background: Collaborations between patient organisations (POs) and the pharmaceutical industry can help identify and address the unmet needs of people living with a disease. In Alzheimer's disease (AD), the scale and complexity of the current unmet needs call for a broad and cross‐sectoral collaboration, including people living with Alzheimer's (PLWA), their care partners and the wider research community. Objective: This study aimed to describe learnings from the Finding Alzheimer's Solutions Together (F.A.S.T.) Council, a collaboration between POs and Roche, convened to better understand the unmet needs of PLWA and their care partners. Results: 1. Learnings from the collaboration, including clarifying objectives and members' expectations upfront, and establishing a set of guiding values and engagement principles. 2. Insights and recommendations for improving care in AD, including a wide range of unmet needs and potential solutions, systematically captured throughout the PLWA journey. These have resulted in several published reports and other outcomes, including (1) 'Portraits of care', highlighting the role of care partners, and the impact of coronavirus disease 2019 on care; (2) Clinical trial guidebook, recommending how PLWA and care partner experience can be incorporated into trial design; (3) 'Commitments Catalogue', highlighting progress by governmental organisations in achieving their commitments; and (4) a report to guide policy on improving diversity, equity and inclusion in clinical trials. Conclusions: Close collaboration between POs and the pharmaceutical industry in AD can enable effective research, in which PLWA and care partners are engaged as 'experts through experience' to help identify key unmet needs and co‐create solutions with the wider AD research community. This paper and the work undertaken by the F.A.S.T. Council may act as a blueprint for meaningful collaboration between POs and the pharmaceutical industry. Patient or Public Contribution: The paper reports the collaboration between POs, the F.A.S.T. Council and Roche to progress towards a future in which PLWA can live fulfilling lives with their disease managed well. Clinical Trial Registration: Not applicable. [ABSTRACT FROM AUTHOR]

Introduction: To guide good practices in patient and public involvement (PPI), several calls have been made to share detailed accounts of practical experiences. We describe our collaboration with young people with a chronic condition (YPCC) in the development, testing and implementation of the digital communication tool MyBoT (Map your Burden of Treatment). Methods: MyBoT was developed by a team of academic researchers, some of whom were practising care providers, YPCC and designers. In addition to the two co‐researchers in the research team, various groups of YPCC were involved in decision‐making through participation in a design session, workshops and a dialogue session. The Involvement Matrix was used to reflect on the PPI of all YPCC. Results: Initially, the two co‐researchers were involved in the roles of informer and co‐thinker, but their decision‐making power within the study increased over time. In the final stages of the study, the co‐researchers and researchers became partners. The other YPCC who participated in the different sessions and workshops were co‐thinkers in all stages of the study. Conclusion: The PPI of two YPCCs as co‐researchers within the research team ensured continuous involvement, whereas the PPI of various groups of YPCCs guaranteed a representative and inclusive approach. Researchers play an essential role in bringing all perspectives together, integrating them within the technical and financial constraints and ultimately building a tool that is tailored to its users' needs. Patient or Public Contribution: YPCC played a significant role in the present study. Two YPCC—who are also co‐authors of this paper—were involved in all stages of this project as members of the research team. In addition, various YPCCs were involved in the development, testing and implementation stage of MyBoT by organizing design sessions, workshops and a dialogue session. [ABSTRACT FROM AUTHOR]

In predictive modelling for high‐stake decision‐making, predictors must be not only accurate but also reliable. Conformal prediction (CP) is a promising approach for obtaining the coverage of prediction results with fewer theoretical assumptions. To obtain the prediction set by so‐called full‐CP, we need to refit the predictor for all possible values of prediction results, which is only possible for simple predictors. For complex predictors such as random forests (RFs) or neural networks (NNs), split‐CP is often employed where the data is split into two parts: one part for fitting and another for computing the prediction set. Unfortunately, because of the reduced sample size, split‐CP is inferior to full‐CP both in fitting as well as prediction set computation. In this paper, we develop a full‐CP of sparse high‐order interaction model (SHIM), which is sufficiently flexible as it can take into account high‐order interactions among variables. We resolve the computational challenge for full‐CP of SHIM by introducing a novel approach called homotopy mining. Through numerical experiments, we demonstrate that SHIM is as accurate as complex predictors such as RF and NN and enjoys the superior statistical power of full‐CP. [ABSTRACT FROM AUTHOR]

Background: I'm Me is a creative research project co‐created between York St John University and Mind the Gap, investigating learning disabled and autistic artists' understandings of identity, representation and voice. Methods: In this paper, we use Walmsley and Johnson's criteria for inclusive research to reflect on the involvement of people with learning disabilities and autism in I'm Me. Findings: Researchers need to carefully reflect on who benefits from research. Long‐term relationships allow genuine allyship and for research design to emerge in an inclusive manner. Taking the time to develop access and clear structures for decision‐making can support people with learning disabilities' participation and control over research. Part of access is sharing our findings in accessible ways, in this case, by using plain language and artistic outputs. Conclusions: Working out how people with learning disabilities and autism should be involved in research has involved establishing structures, reflecting and responding to create as much involvement and enable as much decision‐making as possible. Accessible Summary: I'm Me is an inclusive research project. As an inclusive research project, people with learning disabilities need to be involved and care about the research. Non‐learning disabled researchers need to respect people with learning disabilities.We tried to make I'm Me inclusive and we learned that:Non‐learning disabled people need to build long‐term working relationships with people with learning disabilities and their support organisations.Non‐learning disabled people need to think about if the research is serving learning disabled people.Understanding access needs takes time and energy. Everyone needs to work on access.Everyone should be clear about how decisions are made. It should be clear when people with learning disabilities are being asked for their opinions and when they are making decisions.Sharing what we've learned in different ways makes it easier for more people to understand.Having clear ways of working can help people with learning disabilities have control over part of the research. [ABSTRACT FROM AUTHOR]

In clinical trials with time‐to‐event data, the evaluation of treatment efficacy can be a long and complex process, especially when considering long‐term primary endpoints. Using surrogate endpoints to correlate the primary endpoint has become a common practice to accelerate decision‐making. Moreover, the ethical need to minimize sample size and the practical need to optimize available resources have encouraged the scientific community to develop methodologies that leverage historical data. Relying on the general theory of group sequential design and using a Bayesian framework, the methodology described in this paper exploits a documented historical relationship between a clinical "final" endpoint and a surrogate endpoint to build an informative prior for the primary endpoint, using surrogate data from an early interim analysis of the clinical trial. The predictive probability of success of the trial is then used to define a futility‐stopping rule. The methodology demonstrates substantial enhancements in trial operating characteristics when there is a good agreement between current and historical data. Furthermore, incorporating a robust approach that combines the surrogate prior with a vague component mitigates the impact of the minor prior‐data conflicts while maintaining acceptable performance even in the presence of significant prior‐data conflicts. The proposed methodology was applied to design a Phase III clinical trial in metastatic colorectal cancer, with overall survival as the primary endpoint and progression‐free survival as the surrogate endpoint. [ABSTRACT FROM AUTHOR]

The influence of personal recommendations on decision‐making is well‐established. To date, however, most research appears to have focussed on decisions of less importance. This study explores how place recommendations may have an impact on internal migration. Drawing on extraordinarily voluminous survey data, based on approximately half a million responses in Swedish municipalities between 2010 and 2018, the analyses of this paper are focused on the extent to which people would recommend friends and acquaintances to move to their respective municipalities, on the locational features influencing such recommendations, and on the relationship between recommendations and net‐migration. Contributing to research on the role of social networks in migration research, the results reveal both a widespread tendency among inhabitants to give positive place recommendations and a very strong positive association between place satisfaction and place recommendations. In addition, a tentative analysis suggests that highly recommended municipalities benefit in terms of net‐migration and, hence, population growth. [ABSTRACT FROM AUTHOR]

In this paper, we develop a generic framework for systemically encoding causal knowledge manifested in the form of hierarchical causality structure and qualitative (or quantitative) causal relationships into neural networks to facilitate sound risk analytics and decision support via causally‐aware intervention reasoning. The proposed methodology for establishing causality‐informed neural network (CINN) follows a four‐step procedure. In the first step, we explicate how causal knowledge in the form of directed acyclic graph (DAG) can be discovered from observation data or elicited from domain experts. Next, we categorize nodes in the constructed DAG representing causal relationships among observed variables into several groups (e.g., root nodes, intermediate nodes, and leaf nodes), and align the architecture of CINN with causal relationships specified in the DAG while preserving the orientation of each existing causal relationship. In addition to a dedicated architecture design, CINN also gets embodied in the design of loss function, where both intermediate and leaf nodes are treated as target outputs to be predicted by CINN. In the third step, we propose to incorporate domain knowledge on stable causal relationships into CINN, and the injected constraints on causal relationships act as guardrails to prevent unexpected behaviors of CINN. Finally, the trained CINN is exploited to perform intervention reasoning with emphasis on estimating the effect that policies and actions can have on the system behavior, thus facilitating risk‐informed decision making through comprehensive "what‐if" analysis. Two case studies are used to demonstrate the substantial benefits enabled by CINN in risk analytics and decision support. [ABSTRACT FROM AUTHOR]

A popular interpretation of "evidence‐based" decision‐making is "rely (only) on the rigorous evidence" (RORE) via "systematic" reviews that: use objective protocols to generating the potentially relevant papers from the literature; then filter those to retain only the small subset that provide impact estimates regarded as "rigorous"; and summarize only those estimates. I use two sets of cross‐country impact estimates—on wage gains for migrants and private school learning gains—to illustrate this seemingly attractive approach is both empirically and conceptually unsound. First, the cross‐country variation in the rigorous estimates of impact is very large, which implies the average(s) from a systematic review is of little predictive use. In both empirical examples the "systematic review of the rigorous estimates" approach leads to worse predictions of impact across countries than the naïve use of country‐specific ordinary least squares estimates. Second, I contrast a systematic review—RORE approach with an "understanding" approach—which seeks to encompass all of the available evidence into coherent understandings in forming judgments. In both examples the notion that the impact effects are constant across countries—"external validity"—is easily rejected. Insisting on privileged reliance on "rigorous" estimates in making context‐specific decisions is logically incoherent and deeply anti‐scientific. [ABSTRACT FROM AUTHOR]

Operational water management is a critical global challenge, and decision making can be improved by using mathematical optimization. This paper provides an overview of optimization techniques, both exact and heuristic, used in water management. It focuses on the use of optimization techniques in the short term: operational planning in reservoir management, control of open channels, hydropower scheduling, and operation of polder drainage pumps. Principles of model predictive control, methods for optimization under forecast uncertainty, and approaches for conflict resolution are explained with the help of educational examples and practical cases. Challenges and research questions to be addressed in the future are presented as an outlook. This article is categorized under:Engineering Water > MethodsScience of Water > Water and Environmental ChangeWater and Life > Conservation, Management, and Awareness [ABSTRACT FROM AUTHOR]

Background: The most recent Norwegian educational reform, in force from 2020, was the first to include games alongside more traditional language learning resources (e.g., novels, films, music) in the English curriculum for secondary school. This educational emphasis on games provided a unique opportunity to examine how games are actually used in secondary English instruction in combination with other resources. Objectives: The aim of this study was to investigate how the digital commercial game This Land is My Land was used alongside a printed novel in naturally occurring English instruction in two lower secondary classes during a two‐week project labelled 'The Native American Experience'. Methods: Participants involved one teacher, nine student teachers and 52 students (aged 13–14). Using a mixed methods design, we integrated quantitative and qualitative analyses of classroom video recordings (N = 20), screen recordings during gameplay (N = 32), student texts (N = 32) and retrospective student interviews (N = 7). We used the validated Protocol for Language Arts Teaching Observation (PLATO; Grossman, 2015) for analyses of video and screen recordings and reflexive thematic analysis (Braun & Clarke, 2022) of student texts and interviews. Results and Conclusions: The combination of digital game and printed novel during English instruction provided a dual perspective on the Native American experience. While the novel provided a window for observing the topic historically, the game provided a playground to experience the topic interactively. Although the combination of game and novel offered students different perspectives on the Native American experience, we identified missed opportunities for those who gamed before reading, whereas students who read before gameplay used their knowledge from the novel when they engaged with the game content. In the broader context of educational technology and language instruction, this study identified how to combine digital and traditional literacies that acknowledge students' prior knowledge with diverse literacies. Lay Description: What is already known about this topic: Digital games are the most popular literacy used by young people worldwide.Teachers implement digital games as part of their instruction, but often games that are designed for educational purposes.When teachers use digital games that are not designed for educational purposes, that is, commercial games, it often involves researcher intervention. What this paper adds: Observational research on instruction that involved a commercial game in two English classes in Norway, completely without researcher intervention.Commercial gameplay was an integrated part of the English instruction and used in combination with reading a printed novel.The combination of gameplay and reading provided students with different perspectives and experiences on the same topic Implications of study for practitioners: Teachers should use commercial games as an integrated part of their English instruction for subject‐specific purposes.Student engagement in learning might be enhanced when commercial games are used in combination with literature.It might be beneficial to have a pre‐reading activity before gameplay, to provide background knowledge. [ABSTRACT FROM AUTHOR]

Cities are constantly changing to adapt to new societal and environmental challenges. Understanding their evolution is thus essential to make informed decisions about their future. To capture these changes, cities are increasingly offering digital 3D snapshots of their territory over time. However, existing tools to visualise these data typically represent the city at a specific point in time, limiting a comprehensive analysis of its evolution. In this paper, we propose a new method for simultaneously visualising different versions of the city in a 3D space. We integrate the different versions of the city along a new way of 3D timeline that can take different shapes depending on the needs of the user and the dataset being visualised. We propose four different shapes of timelines and three ways to place the versions along it. Our method places the versions such that there is no visual overlap for the user by varying the parameters of the timelines, and offer options to ease the understanding of the scene by changing the orientation or scale of the versions. We evaluate our method on different datasets to demonstrate the advantages and limitations of the different shapes of timeline and provide recommendations so as to which shape to chose. [ABSTRACT FROM AUTHOR]

Evaluating information quality online is increasingly important for healthy decision‐making. People assess information quality using visual interfaces (e.g., computers, smartphones) with visual cues like aesthetics. Yet, voice interfaces lack critical visual cues for evaluating information because there is often no visual display. Without ways to assess voice‐based information quality, people may overly trust or misinterpret information which can be challenging in high‐risk or sensitive contexts. This paper investigates voice information uncertainty in one high‐risk context—health information seeking. We recruited 30 adults (ages 18–84) in the United States to participate in scenario‐based interviews about health topics. Our findings provide evidence of information uncertainty expectations with voice assistants, voice search preferences, and the audio cues they use to assess information quality. We contribute a nuanced discussion of how to inform more critical information ecosystems with voice technologies and propose ways to design audio cues to help people more quickly assess content quality. [ABSTRACT FROM AUTHOR]

Summary: The Internet of Things (IoT) continues to find novel applications across various domains. These applications require the support of efficient communication protocols in the Low Power and Lossy Networks (LLNs). The development of efficient multicast protocols is one such area that requires critical research attention. Efficient multicast protocols are especially important in the non‐storing mode of IPv6 Routing Protocol for LLNs (RPL), considering its applicability in real‐world IoT applications. However, the development of non‐storing RPL multicast protocols needs to handle the intricacies associated with source routing. Addressing these issues, this paper presents a novel multicast protocol named Multicast Forwarding in LLNs under Non‐storing mode (MFLN). MFLN uses Bloom Filters to minimize the overhead that comes with source routing. While retaining the best features of multicast protocols operating in the storing mode of RPL such as bidirectional traffic and cross‐layer optimization with ContikiMAC, MFLN also includes a novel metric named Mode Selection Metric (MSM) to decide the suitable link‐layer forwarding method. MSM makes this decision based on the ability of a node, in terms of its residual energy, to perform multiple link‐layer unicasts. Thus, MFLN saves the node battery from running out and at the same time reduces the duplicate packets created due to link‐layer broadcasts. The simulations conducted using Contiki‐COOJA indicate considerable improvements in terms of packet delivery ratio, energy consumption per delivered packet, packet transmissions, end‐to‐end delay, and normalized routing overhead for the proposed protocol. [ABSTRACT FROM AUTHOR]

This paper is the first to offer a comprehensive literature review of the role of evolutionary psychology (EP) in marketing and consumer behavior. This study takes a holistic approach, combining techniques of a systematic review with bibliometric analysis, to provide a performance analysis and identify theories and methodologies used in the literature. Most importantly, by studying the current state of EP, we elucidate six major themes: the role of gender in families, the role of affect in consumer behavior, food preferences and shopping behavior, motivations for and consequences of status signaling, the impact of ovulation on consumer motives and behaviors, and contributions to the greater good. The findings enable researchers to understand the current state of the literature. Further, to advance the application of EP in consumer behavior, we identify gaps related to each theme and offer research questions that can serve as catalysts for future research. Thus, we offer two primary contributions: a comprehensive overview of the literature as it relates to methods, theories, and themes and detailed guidance that can be used to invigorate research on EP. [ABSTRACT FROM AUTHOR]

Nursing's efforts at organizing in the United States have encompassed various approaches to creating change at a systemic and political level, namely shared governance, professional associations, and nurse unions. The United States is currently experiencing the effects of an authoritarian sociopolitical agenda that has taken aim at our profession's ethic of providing equitable care for all people through legislation that bans gender‐affirming care and abortions. Nursing is simultaneously experiencing a crisis of burnout and moral distress, as we navigate the everyday functions of a for‐profit healthcare system under the Capitalocene. As we situate ourselves within these policies and practices of late‐stage capitalism and an increasingly authoritarian nation‐state, we are compelled to think deeply about how nursing is currently organizing ourselves. Our paper will explore the evolution of various forms of organizing through the lens of intersectionality, which offers a framework for considering the ways that power operates, creating a matrix of sociostructural processes that fuel injustice. Intersectionality also compels us to examine whether our organizing has resisted, or perpetuated, a matrix of oppression. We will conclude by offering examples of radical imagining for a future of nursing resistance, where our collective organizing has a greater impact and responsibility for dismantling the status quo to achieve justice and liberation. [ABSTRACT FROM AUTHOR]

This paper addresses personality psychological determinants of migration behaviour. Using pooled data of two related probability samples (GERPS and SOEP), we examined the association between the Big Five personality traits and the propensity to become internationally mobile. Relying on advanced pre‐processing methods that control for key socio‐demographic and economic determinants, our results show that migration propensity was significantly related to three of the Big Five personality traits. Moreover, we found gender‐specific and cultural differences (based on the language spoken in the destination country) in these relation for some of the Big Five dimensions. These results help to elucidate the process of a migration decision using a personality‐psychological perspective. [ABSTRACT FROM AUTHOR]

Improved global access to novel age‐appropriate formulations for paediatric subsets, either of new chemical entities or existing drugs, is a priority to ensure that medicines meet the needs of these patients. However, despite regulatory incentives, the introduction to the market of paediatric formulations still lags behind adult products. This is mainly caused by additional complexities associated with the development of acceptable age‐appropriate paediatric medicines. This position paper recommends the use of a paediatric Quality Target Product Profile as an efficient tool to facilitate early planning and decision making across all teams involved in paediatric formulation development during the children‐centric formulation design for new chemical entities, or to repurpose/reformulate off‐patent drugs. Essential key attributes of a paediatric formulation are suggested and described. Moreover, greater collaboration between formulation experts and clinical colleagues, including healthcare professionals, is advocated to lead to safe and effective, age‐appropriate medicinal products. Acceptability testing should be a secondary endpoint in paediatric clinical trials to ensure postmarketing adherence is not compromised by a lack of acceptability. Not knowing the indications and the related age groups and potential dosing regimens early enough is still a major hurdle for efficient paediatric formulation development; however, the proposed paediatric Quality Target Product Profile could be a valuable collaborative tool for planning and decision making to expedite paediatric product development, particularly for those with limited experience in developing a paediatric product. [ABSTRACT FROM AUTHOR]

Background: Achieving universal health coverage (UHC) in the context of limited resources will require prioritising the most vulnerable and ensuring health policies and services are responsive to their needs. One way of addressing this is through the engagement of marginalised voices in the priority setting process. Public engagement approaches that enable group level deliberation as well as individual level preference capturing might be valuable in this regard, but there are limited examples of their practical application, and gaps in understanding their outcomes, especially with rural populations. Objective: To address this gap, we implemented a modified priority setting tool (Choosing All Together—CHAT) that enables individuals and groups to make trade‐offs to demonstrate the type of health services packages that may be acceptable to a rural population. The paper presents the findings from the individual choices as compared to the group choices, as well as the differences among the individual choices using this tool. Methods: Participants worked in groups and as individuals to allocate stickers representing the available budget to different health topics and interventions using the CHAT tool. The allocations were recorded at each stage of the study. We calculated the median and interquartile range across study participants for the topic totals. To examine differences in individual choices, we performed Wilcoxon rank sum tests. Results: The results show that individual interests were mostly aligned with societal ones, and there were no statistically significant differences between the individual and group choices. However, there were some statistically significant differences between individual priorities based on demographic characteristics like age. Discussion: The study demonstrates that giving individuals greater control and agency in designing health services packages can increase their participation in the priority setting process, align individual and community priorities, and potentially enhance the legitimacy and acceptability of priority setting. Methods that enable group level deliberation and individual level priority setting may be necessary to reconcile plurality. The paper also highlights the importance of capturing the details of public engagement processes and transparently reporting on these details to ensure valuable outcomes. Public Contribution: The facilitator of the CHAT groups was a member from the community and underwent training from the research team. The fieldworkers were also from the community and were trained and paid to capture the data. The participants were all members of the rural community‐ the study represents their priorities. [ABSTRACT FROM AUTHOR]

Introduction: For too many people, their care plans are designed without fully accounting for who they are, the lives they live, what matters to them or what they aspire to achieve. We aimed to summarize instruments capable of measuring dimensions of patient–clinician collaboration to make care fit. Methods: We systematically searched several databases (Medline, Embase, Cochrane, Scopus and Web of Science) from inception to September 2021 for studies using quantitative measures to assess, evaluate or rate the work of making care fit by any participant in real‐life clinical encounters. Eligibility was assessed in duplicate. After extracting all items from relevant instruments, we coded them deductively on dimensions relevant to making care fit (as presented in a recent Making Care Fit Manifesto), and inductively on the main action described. Results: We included 189 papers, mostly from North America (N = 83, 44%) and in the context of primary care (N = 54, 29%). Half of the papers (N = 88, 47%) were published in the last 5 years. We found 1243 relevant items to assess efforts of making care fit, included within 151 instruments. Most items related to the dimensions 'Patient‐clinician collaboration: content' (N = 396, 32%) and 'Patient‐clinician collaboration: manner' (N = 382, 31%) and the least related to 'Ongoing and iterative process' (N = 22, 2%) and in 'Minimally disruptive of patient lives' (N = 29, 2%). The items referred to 27 specific actions. Most items referred to 'Informing' (N = 308, 25%) and 'Exploring' (N = 93, 8%), the fewest items referred to 'Following up', 'Comforting' and 'Praising' (each N = 3, 0.2%). Discussion: Measures of the work that patients and clinicians do together to make care fit focus heavily on the content of their collaborations, particularly on exchanging information. Other dimensions and actions previously identified as crucial to making care fit are assessed infrequently or not at all. The breadth of extant measures of making care fit and the lack of appropriate measures of this key construct limit both the assessment and the successful implementation of efforts to improve patient care. Patient Contribution: Patients and caregivers from the 'Making care fit Collaborative' were involved in drafting the dimensions relevant to patient–clinician collaboration. [ABSTRACT FROM AUTHOR]

Background: Informal care features high on the policy agenda of many countries to deal with workforce shortages. As a consequence, care provision increasingly takes place in the care triad of care recipients, informal caregivers and care professionals. How collaboration between care partners takes shape depends on how the different partners perceive this collaboration. This paper aims to investigate the relative importance of the different aspects of collaboration from the perspectives of care recipients, informal caregivers and care professionals in the context of the care for older persons in The Netherlands. Methods: Using Q‐methodology, 32 participants ranked 28 statements that reflect different aspects of collaboration in the care triad and explained their ranking during a follow‐up interview. Participants comprised 9 older persons, 10 informal caregivers and 13 care professionals. Data were analysed using by‐person factor analysis to identify common patterns in the rankings of the statements. Emerging patterns were interpreted and described as views on collaboration using aggregated rankings and qualitative data from the interviews. Results: Five distinct views on collaboration were found: (1) Emphasizing warm collaboration, (2) trusting care professional's expertise, (3) open and compassionate care professionals, (4) responsive decision‐making by autonomous care professionals and (5) prioritizing care recipient's and informal caregiver's interests. Care recipients and/or informal caregivers were associated with views 1, 3 and, 5, whereas care professionals were associated with all five views. Conclusions: Our study highlights the importance of recognizing the potential diversity of views between and within different partner groups in care triads. Governmental and organizational policy makers, as well as healthcare professionals who aim to increase or support the involvement of informal caregivers, should take this heterogeneity into consideration. Patient or Public Contribution: An advisory board of older persons (care recipients and informal caregivers) was involved in the recruitment of the participants, the formulation of the statements and the reflection on the findings of the study and potential implications. [ABSTRACT FROM AUTHOR]