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Background: There has been a growing concern regarding research waste and the mismatch between conducted research and the research needs of knowledge users. The Needs Led Research (NLR) approach is proposed as an effective method to ensure that research address actual evidence gaps that are relevant to the users of the knowledge. By search and reviewing literature and involving knowledge users, NLR aims to identify, verify, and prioritize research needs. This paper describes and compares the implementation of the NLR approach in two separate PhD projects within maternity care, and addresses the challenges encountered throughout the processes, aiming to offer valuable insights for future NLR initiatives. Methods: The NLR processes consisted of four phases: (1) defining the scope (2) identifying and verifying research needs (3) prioritizing research needs and (4) designing the PhD projects. Literature searches were conducted during Phase 2, while knowledge user involvement took place in Phases 2 and 3. The knowledge user involvement, at a co-thinker and advocatory level, included knowledge user groups and surveys. Project groups, who were responsible for all decision-making, conducted Phases 1 and 4. The scopes of the PhD projects were labor induction (NLR-LINO) and fetal monitoring in low-risk deliveries (NLR-LISTEN). Results: In NLR-LINO, 17 research needs were identified and verified as actual evidence gaps relevant for the knowledge users. Among these, ten were rated as "very important" by a majority of the 322 survey respondents. The aim of the PhD LINO project was defined as "To investigate whether outpatient induction of labor is beneficial in a Norwegian setting." In NLR-LISTEN, seven research needs were identified and verified as actual evidence gaps relevant for the knowledge users. These were prioritized by 466 survey respondents, and the aim of the PhD LISTEN project was defined as "To investigate the methods used for fetal monitoring in low-risk deliveries in Norway and evaluate adherence to evidence-based practice while also exploring potential reasons for any deviations." Conclusions: This paper shows that the NLR is a viable approach for prioritizing research. The findings highlight the impact of the initial scope on subsequent phases and emphasize the importance of pragmatic decision-making throughout the process. However, it is crucial to acknowledge that NLR requires dedicated resources, and if integrated into PhD projects, additional time and training should be allocated accordingly. Plain English summary: This paper addresses the issue of research waste and the mismatch between conducted research and the actual needs of the users of the knowledge. The Needs Led Research (NLR) approach is proposed as an effective method for identifying and prioritizing research needs that are relevant to knowledge users and have not been adequately addressed by existing research. The paper specifically examines the implementation of the NLR approach in two separate PhD projects within the field of maternity care, aiming to provide valuable insights for future NLR initiatives. The NLR process consists of four phases: defining the scope, identifying and verifying research needs, prioritizing those needs, and designing the PhD projects. Literature searches were conducted during Phase 2 to identify existing evidence gaps in the research literature. Knowledge users were involved in both the identification and prioritization of research needs in Phases 2 and 3 through surveys and group discussions. In conclusion, this paper shows that NLR is a viable approach for prioritizing research and ensuring its relevance to the users of the knowledge. It emphasizes the importance of defining a clear scope and making pragmatic decisions throughout the process. However, it also highlights the need for dedicated resources and additional time and training when integrating the NLR approach into PhD projects. [ABSTRACT FROM AUTHOR]

Background: After curative surgery for early-stage breast cancer, patients face a decision on whether to undergo surgery alone or to receive one or more adjuvant treatments, which may lower the risk of recurrence. Variations in survival outcomes are often marginal but there are differences in the side effects and other features of the options that patients may value differently. Hence, the patient's values and preferences are critical in determining what option to choose. It is well-researched that the use of shared decision making and patient decision aids can support this choice in a discussion between patient and clinician. However, it is still to be investigated what impact the timing and format of the patient decision aid have on shared decision making outcomes. In this trial, we aim to investigate the impact of a digital pre-consult compared to a paper-based in-consult patient decision aid on patients' involvement in shared decision making, decisional conflict and preparedness to make a decision. Methods: The study is a randomised controlled trial with 204 patients at two Danish oncology outpatient clinics. Eligible patients are newly diagnosed with early-stage breast cancer and offered adjuvant treatments after curative surgery to lower the risk of recurrence. Participants will be randomised to receive either an in-consult paper-based patient decision aid or a pre-consult digital patient decision aid. Data collection includes patient and clinician-reported outcomes as well as observer-reported shared decision making based on audio recordings of the consultation. The primary outcome is the extent to which patients are engaged in a shared decision making process reported by the patient. Secondary aims include the length of consultation, preparation for decision making, preferred role in shared decision making and decisional conflict. Discussion: This study is the first known randomised, controlled trial comparing a digital, pre-consult patient decision aid to an identical paper-based, in-consult patient decision aid. It will contribute evidence on the impact of patient decision aids in terms of investigating if pre-consult digital patient decisions aids compared to in-consult paper-based decision aids support the cancer patients in being better prepared for decision making. Trial registration: ClinicalTrials.gov (NCT05573022). [ABSTRACT FROM AUTHOR]

Background: Deaths in paediatric intensive care units (PICUs) are not uncommon. End-of-life care in PICUs is generally considered more challenging than other settings since it is framed within a context where care is focused on curative or life-sustaining treatments for children who are seriously ill. This review aimed to identify and synthesise literature related to the essential elements in the provision of end-of-life care in the PICU from the perspectives of both healthcare professionals (HCPs) and families. Methods: A systematic integrative review was conducted by searching EMBASE, CINAHL, MEDLINE, Nursing and Allied Health Database, PsycINFO, Scopus, Web of Science, and Google Scholar databases. Grey literature was searched via Electronic Theses Online Service (EthOS), OpenGrey, Grey literature report. Additionally, hand searches were performed by checking the reference lists of all included papers. Inclusion and exclusion criteria were used to screen retrieved papers by two reviewers independently. The findings were analysed using a constant comparative method. Results: Twenty-one studies met the inclusion criteria. Three elements in end-of-life care provision for children in the PICUs were identified: 1) Assessment of entering the end-of-life stage; 2) Discussion with parents and decision making; 3) End of life care processes, including care provided during the dying phase, care provided at the time of death, and care provided after death. Conclusion: The focus of end-of-life care in PICUs varies depending on HCPs' and families' preferences, at different stages such as during the dying phase, at the time of death, and after the child died. Tailoring end-of-life care to families' beliefs and rituals was acknowledged as important by PICU HCPs. This review also emphasises the importance of HCPs collaborating to provide the optimum end-of-life care in the PICU and involving a palliative care team in end-of-life care. [ABSTRACT FROM AUTHOR]

In the realm of disease prognosis and diagnosis, a plethora of medical images are utilized. These images are typically stored either within the local on-premises servers of healthcare providers or within cloud storage infrastructures. However, this conventional storage approach often incurs high infrastructure costs and results in sluggish information retrieval, ultimately leading to delays in diagnosis and consequential wastage of valuable time for patients. The methodology proposed in this paper offers a pioneering solution to expedite the diagnosis of medical conditions while simultaneously reducing infrastructure costs associated with data storage. Through this study, a high-speed biomedical image processing approach is designed to facilitate rapid prognosis and diagnosis. The proposed framework includes Deep learning QR code technique using an optimized database design aimed at alleviating the burden of intensive on-premises database requirements. The work includes medical dataset from Crawford Image and Data Archive and Duke CIVM for evaluating the proposed work suing different performance metrics, The work has also been compared from the previous research further enhancing the system's efficiency. By providing healthcare providers with high-speed access to medical records, this system enables swift retrieval of comprehensive patient details, thereby improving accuracy in diagnosis and supporting informed decision-making. [ABSTRACT FROM AUTHOR]

Background: The concept of a financial scarcity mindset has raised much attention as an explanation for poor decision-making and dysfunctional behavior. It has been suggested that financial scarcity could also impair dietary behavior, through a decline in self-control. Underlying cognitive mechanisms of tunneling (directing attention to financial issues and neglecting other demands), cognitive load (a tax on mental bandwidth interfering with executive functioning) and time orientation (a shift towards a present time horizon, versus a future time horizon) may explain the association between financial scarcity and self-control related dietary behavior. The current scoping review gathers recent evidence on how these mechanisms affect dietary behavior of people experiencing financial scarcity. It builds on a theoretical framework based on insights from behavioral economics and health psychology. Methods: A literature search was executed in six online databases, which resulted in 9.975 papers. Search terms were tunneling, cognitive load and time orientation, financial scarcity, and dietary behavior. Screening was performed with ASReview, an AI-ranking tool. In total, 14 papers were included in the scoping review. We used PRISMA-ScR guidelines for reporting. Results: Limited evidence indicates that a scarcity mindset could increase tunneling, through attentional narrowing on costs of food, which then directly impacts dietary behavior. A scarcity mindset involves experiencing financial stress, which can be understood as cognitive load. Cognitive load decreases attentional capacity, which could impair self-control in dietary choices. Financial scarcity is related to a present time orientation, which affects dietary choices by shifting priorities and decreasing motivation for healthy dietary behavior. Conclusions: A scarcity mindset affects dietary behavior in different ways. Tunneling and a shift in time orientation are indicative of an attentional redirection, which can be seen as more adaptive to the situation. These may be processes indirectly affecting self-control capacity. Cognitive load could decrease self-control capacity needed for healthy dietary behavior because it consumes mental bandwidth. How a changing time orientation when experiencing financial scarcity relates to motivation for self-control in dietary behavior is a promising theme for further inquiry. [ABSTRACT FROM AUTHOR]

Background: Globally, a growing number of calls to formalize and strengthen evidence-support systems have been released, all of which emphasize the importance of evidence-informed decision making. To achieve this, it is critical that evidence producers and decision-makers interact, and that decision-makers' evidence needs can be efficiently translated into questions to which evidence producers can respond. This paper aims to create a taxonomy of demand-driven questions for use by evidence producers, intermediaries (i.e., people working in between researchers and decision-makers) and decision-makers. Methods: We conducted a global cross-sectional survey of units providing some type of evidence support at the explicit request of decision-makers. Unit representatives were invited to answer an online questionnaire where they were asked to provide a list of the questions that they have addressed through their evidence-support mechanism. Descriptive analyses were used to analyze the survey responses, while the questions collected from each unit were iteratively analyzed to create a mutually exclusive and collectively exhaustive list of types of questions that can be answered with some form of evidence. Results: Twenty-nine individuals completed the questionnaire, and more than 250 submitted questions were analysed to create a taxonomy of 41 different types of demand-driven questions. These 41 questions were organized by the goal to be achieved, and the goals were grouped in the four decision-making stages (i) clarifying a societal problem, its causes and potential impacts; (ii) finding and selecting options to address a problem; (iii) implementing or scaling-up an option; and (iv) monitoring implementation and evaluating impacts. Conclusion: The mutually exclusive and collectively exhaustive list of demand-driven questions will help decision-makers (to ask and prioritize questions), evidence producers (to organize and present their work), and evidence-intermediaries (to connect evidence needs with evidence supply). [ABSTRACT FROM AUTHOR]

Background: Health and care research involving people who lack capacity to consent requires an alternative decision maker to decide whether they participate or not based on their 'presumed will'. However, this is often unknown. Advance research planning (ARP) is a process for people who anticipate periods of impaired capacity to prospectively express their preferences about research participation and identify who they wish to be involved in future decisions. This may help to extend individuals' autonomy by ensuring that proxy decisions are based on their actual wishes. This qualitative study aimed to explore stakeholders' views about the acceptability and feasibility of ARP and identify barriers and facilitators to its implementation in the UK., Methods: We conducted semi-structured interviews with 27 researchers, practitioners, and members of the public who had participated in a preceding survey. Interviews were conducted remotely between April and November 2023. Data were analysed thematically., Results: Participants were supportive of the concept of ARP, with differing amounts of support for the range of possible ARP activities depending on the context. Six main themes were identified: (1) Planting a seed - creating opportunities to initiate/engage with ARP; (2) A missing part of the puzzle - how preferences expressed through ARP could help inform decisions; (3) Finding the sweet spot - optimising the timing of ARP; (4) More than a piece of paper - finding the best mode for recording preferences; (5) Keeping the door open to future opportunities - minimising the risk of unintended consequences; and (6) Navigating with a compass - principles underpinning ARP to ensure safeguarding and help address inequalities. Participants also identified a number of implementation challenges, and proposed facilitative strategies that might overcome them which included embedding advance research planning in existing future planning processes and research-focused activities., Conclusions: This study provides a routemap to implementing ARP in the UK to enable people anticipating impaired capacity to express their preferences about research, thus ensuring greater opportunities for inclusion of this under-served group, and addressing the decisional burden experienced by some family members acting as proxies. Development of interventions and guidance to support ARP is needed, with a focus on ensuring accessibility., (© 2024. The Author(s).)

Background: The climate crisis is a significant risk to the health and wellbeing of children, young people, and future generations. While there are calls for children and young people's engagement in climate decision making, current power structures limit their participation. This paper aimed to understand children's perspectives about the impact of the climate crisis on their futures, their ability to influence climate decisions, and strategies and mechanisms to facilitate their greater engagement in decisions made about the climate crisis., Methods: Online in-depth interviews were conducted with n = 28 children (aged 12-16 years) across Australia. Photo elicitation techniques were used to prompt discussion about how the climate crisis impacted their futures, their ability to influence climate decisions, and strategies and mechanisms to engage them in climate decision making. A reflexive approach to thematic analysis was used to construct three themes from data. Images were analysed for ascribed meanings., Results: First, participants stated that they and future generations will inherit the climate crisis from older generations, specifically decision makers. Second, they described a need to address a range of age-related barriers that limit children and young people's engagement in climate decision making, including perceptions about their capabilities. Finally, they discussed strategies and mechanisms to embed children and young people's perspectives within climate decision making, including at civic and political levels., Conclusions: Children and young people have the right to be involved in decisions made about the climate crisis which significantly impact their futures, including their health and wellbeing. They argue for structural changes to embed their views in climate decision making, and describe a range of engagement strategies and mechanisms to structure their perspectives and knowledge with decision making processes. Furthermore, genuine involvement of children and young people in climate discussions must avoid youthwashing and tokenistic participation. The public health community can help address barriers to youth participation in climate action and should actively engage and collaborate with children and young people to facilitate their political and democratic influence over the climate crisis. This involves making room and creating an accessible seat at the decision making table to ensure their perspectives are embedded in climate decisions., (© 2024. The Author(s).)

Background: Development of guidelines for public health, health system, and health policy interventions demands complex systems thinking to understand direct and indirect effects of interventions within dynamic systems. The WHO-INTEGRATE framework, an evidence-to-decision framework rooted in the norms and values of the World Health Organization (WHO), provides a structured method to assess complexities in guidelines systematically, such as the balance of an intervention's health benefits and harms and their human rights and socio-cultural acceptability. This paper provides a worked example of the application of the WHO-INTEGRATE framework in developing the WHO guidelines on parenting interventions to prevent child maltreatment, and shares reflective insights regarding the value added, challenges encountered, and lessons learnt., Methods: The methodological approach comprised describing the intended step-by-step application of the WHO-INTEGRATE framework and gaining reflective insights from introspective sessions within the core team guiding the development of the WHO guidelines on parenting interventions and a methodological workshop., Results: The WHO-INTEGRATE framework was used throughout the guideline development process. It facilitated reflective deliberation across a broad range of decision criteria and system-level aspects in the following steps: (1) scoping the guideline and defining stakeholder engagement, (2) prioritising WHO-INTEGRATE sub-criteria and guideline outcomes, (3) using research evidence to inform WHO-INTEGRATE criteria, and (4) developing and presenting recommendations informed by WHO-INTEGRATE criteria. Despite the value added, challenges, such as substantial time investment required, broad scope of prioritised sub-criteria, integration across diverse criteria, and sources of evidence and translation of insights into concise formats, were encountered., Conclusions: Application of the WHO-INTEGRATE framework was crucial in the integration of effectiveness evidence with insights into implementation and broader implications of parenting interventions, extending beyond health benefits and harms considerations and fostering a whole-of-society-perspective. The evidence reviews for prioritised WHO-INTEGRATE sub-criteria were instrumental in guiding guideline development group discussions, informing recommendations and clarifying uncertainties. This experience offers important lessons for future guideline panels and guideline methodologists using the WHO-INTEGRATE framework., (© 2024. The Author(s).)

Background: Nigeria commenced rollout of vaccination for coronavirus disease 2019 (COVID-19) in March 2021 as part of the national public health response to the pandemic. Findings from appropriately contextualized cost-effectiveness analyses (CEA) as part of a wider process involving health technology assessment (HTA) approaches have been important in informing decision-making in this area. In this paper we outline the processes that were followed to identify COVID-19 vaccine stakeholders involved in the selection, approval, funding, procurement and rollout of vaccines in Nigeria, and describe the process routes we identified to support uptake of HTA-related information for evidence-informed policy in Nigeria., Methods: Our approach to engaging with policy-makers and other stakeholders as part of an HTA of COVID vaccination in Nigeria consisted of three steps, namely: (i) informal discussions with key stakeholders; (ii) stakeholder mapping, analysis and engagement; and (iii) communication and dissemination strategies for the HTA-relevant evidence produced. The analysis of the stakeholder mapping uses the power/interest grid framework., Results: The informal discussion with key stakeholders generated six initial policy questions. Further discussions with policy-makers yielded three suitable policy questions for analysis: which COVID-19 vaccines should be bought; what is the optimal mode of delivery of these vaccines; and what are the cost and cost-effectiveness of vaccinating people highlighted in Nigeria's phase 2 vaccine rollout prioritized by the government, especially the inclusion of those aged between 18 and 49 years. The stakeholder mapping exercise highlighted the range of organizations and groups within Nigeria that could use the information from this HTA to guide decision-making. These stakeholders included both public/government, private and international organizations The dissemination plan developed included disseminating the full HTA results to key stakeholders; production of policy briefs; and presentation at different national and international conferences and peer-reviewed publications., Conclusions: HTA processes that involve stakeholder engagement will help ensure important policy questions are taken into account when designing any HTA including any underpinning evidence generation. Further guidance about stakeholder engagement throughout HTA is required, especially for those with low interest in vaccine procurement and use., (© 2024. The Author(s).)

Background: Oral fluid intake decreases in advanced cancer in the dying phase of illness. There is inadequate evidence to support the assessment, and management, of hydration in the dying. Bioelectrical impedance analysis (BIA) is a body composition assessment tool. BIA has the potential to inform clinal management in advanced cancer, by examining the relationships between hydration status and clinical variables. Aim: BIA was used to determine the association between hydration status, symptoms, clinical signs, quality-of-life and survival in advanced cancer, including those who are dying (i.e. in the last week of life). Materials and methods: We conducted a prospective observational study of people with advanced cancer in three centres. Advance consent methodology was used to conduct hydration assessments in the dying. Total body water was estimated using the BIA Impedance index (Height – H (m)2 /Resistance – R (Ohms)). Backward regression was used to identify factors (physical signs, symptoms, quality of life) that predicted H2/R. Participants in the last 7 days of life were further assessed with BIA to assess hydration changes, and its relationship with clinical outcomes. Results: One hundred and twenty-five people participated (males n = 74 (59.2%), females, n = 51 (40.8%)). We used backward regression analysis to describe a statistical model to predict hydration status in advanced cancer. The model demonstrated that 'less hydration' (lower H2/R) was associated with female sex (Beta = -0.39, p < 0.001), increased appetite (Beta = -0.12, p = 0.09), increased dehydration assessment scale score (dry mouth, dry axilla, sunken eyes - Beta = -0.19, p = 0.006), and increased breathlessness (Beta = -0.15, p = 0.03). 'More hydration' (higher H2/R) was associated with oedema (Beta = 0.49, p < 0.001). In dying participants (n = 18, 14.4%), hydration status (H2/R) was not significantly different compared to their baseline measurements (n = 18, M = 49.6, SD = 16.0 vs. M = 51.0, SD = 12.1; t(17) = 0.64, p = 0.53) and was not significantly associated with agitation (rs = -0.85, p = 0.74), pain (rs = 0.31, p = 0.23) or respiratory tract secretions (rs = -0.34, p = 0.19). Conclusions: This is the first study to use bioimpedance to report a model (using clinical factors) to predict hydration status in advanced cancer. Our data demonstrates the feasibility of using an advance consent method to conduct research in dying people. This method can potentially improve the evidence base (and hence, quality of care) for the dying. Future BIA research can involve hydration assessment of cancers (according to type and stage) and associated variables (e.g., stage of illness, ethnicity and gender). Further work can use BIA to identify clinically relevant outcomes for hydration studies and establish a core outcome set to evaluate how hydration affects symptoms and quality-of-life in cancer. Key message: What is already known about this topic? - Oral fluid intake decreases in people with advanced cancer, especially when they approach the dying phase of their illness. - There is inadequate evidence to support hydration assessment and decision making in the dying phase of illness. - It is important to understand which clinical factors are associated with hydration status in advanced cancer, to enable healthcare professionals, to evaluate hydration status and support clinical decision making. - Bioimpedance is a non-invasive technology, which has potential to identify clinically relevant variables for cancer hydration assessment. What this paper adds. - This is the first study to use bioimpedance to report a model (using clinical factors) to predict hydration status in advanced cancer. - The variables with combined significance for predicting hydration status were biological sex, appetite, dry mouth, dry axilla, sunken eyes, breathlessness and oedema. In the dying phase, hydration status did not significantly change compared to baseline, and hydration status was not significantly associated with survival. Implications for practice, theory or policy. - Further work can use bioimpedance to identify clinically relevant outcomes for hydration studies, to establish a core outcome set to evaluate how hydration affects symptoms and quality-of-life in cancer. [ABSTRACT FROM AUTHOR]

Background: Given that AI-driven decision support systems (AI-DSS) are intended to assist in medical decision making, it is essential that clinicians are willing to incorporate AI-DSS into their practice. This study takes as a case study the use of AI-driven cardiotography (CTG), a type of AI-DSS, in the context of intrapartum care. Focusing on the perspectives of obstetricians and midwives regarding the ethical and trust-related issues of incorporating AI-driven tools in their practice, this paper explores the conditions that AI-driven CTG must fulfill for clinicians to feel justified in incorporating this assistive technology into their decision-making processes regarding interventions in labor. Methods: This study is based on semi-structured interviews conducted online with eight obstetricians and five midwives based in England. Participants were asked about their current decision-making processes about when to intervene in labor, how AI-driven CTG might enhance or disrupt this process, and what it would take for them to trust this kind of technology. Interviews were transcribed verbatim and analyzed with thematic analysis. NVivo software was used to organize thematic codes that recurred in interviews to identify the issues that mattered most to participants. Topics and themes that were repeated across interviews were identified to form the basis of the analysis and conclusions of this paper. Results: There were four major themes that emerged from our interviews with obstetricians and midwives regarding the conditions that AI-driven CTG must fulfill: (1) the importance of accurate and efficient risk assessments; (2) the capacity for personalization and individualized medicine; (3) the lack of significance regarding the type of institution that develops technology; and (4) the need for transparency in the development process. Conclusions: Accuracy, efficiency, personalization abilities, transparency, and clear evidence that it can improve outcomes are conditions that clinicians deem necessary for AI-DSS to meet in order to be considered reliable and therefore worthy of being incorporated into the decision-making process. Importantly, healthcare professionals considered themselves as the epistemic authorities in the clinical context and the bearers of responsibility for delivering appropriate care. Therefore, what mattered to them was being able to evaluate the reliability of AI-DSS on their own terms, and have confidence in implementing them in their practice. [ABSTRACT FROM AUTHOR]

Background: When deciding whether to implement an intervention, decision-makers typically have questions on feasibility and acceptability and on factors affecting implementation. Descriptions of programme implementation and of policies and systems are rich sources of information for these questions. However, this information is often not based on empirical data collected using explicit methods. To use the information in unconventional source materials in syntheses or other decision support products, we need methods of assessing their strengths and limitations. This paper describes the development and content of the Assessing unConventional Evidence (ACE) tool, a new tool to assess the strengths and limitations of these sources. Methods: We developed the ACE tool in four stages: first, we examined existing tools to identify potentially relevant assessment criteria. Second, we drew on these criteria and team discussions to create a first draft of the tool. Third, we obtained feedback on the draft from potential users and methodologists, and through piloting the tool in evidence syntheses. Finally, we used this feedback to iteratively refine the assessment criteria and to improve our guidance for undertaking the assessment. Results: The tool is made up of 11 criteria including the purpose and context of the source; the completeness of the information presented; and the extent to which evidence is provided to support the findings made. Users are asked to indicate whether each of the criteria have been addressed. On the basis of their judgements for each criterion, users then make an overall assessment of the limitations of the source, ranging from no or very minor concerns to serious concerns. These assessments can then facilitate appropriate use of the evidence in decision support products. Conclusions: Through focussing on unconventional source materials, the ACE tool fills an important gap in the range of tools for assessing the strengths and limitations of policy-relevant evidence and supporting evidence-informed decision-making. [ABSTRACT FROM AUTHOR]

Introduction: This paper outlines the design, implementation, and usability study results of the patient empowerment process for chronic disease management, using Patient Reported Outcome Measurements and Shared Decision-Making Processes. Background: The ADLIFE project aims to develop innovative, digital health solutions to support personalized, integrated care for patients with severe long-term conditions such as Chronic Obstructive Pulmonary Disease, and/or Chronic Heart Failure. Successful long-term management of patients with chronic conditions requires active patient self-management and a proactive involvement of patients in their healthcare and treatment. This calls for a patient-provider partnership within an integrated system of collaborative care, supporting self-management, shared-decision making, collection of patient reported outcome measures, education, and follow-up. Methods: ADLIFE follows an outcome-based and patient-centered approach where PROMs represent an especially valuable tool to evaluate the outcomes of the care delivered. We have selected 11 standardized PROMs for evaluating the most recent patients' clinical context, enabling the decision-making process, and personalized care planning. The ADLIFE project implements the "SHARE approach' for enabling shared decision-making via two digital platforms for healthcare professionals and patients. We have successfully integrated PROMs and shared decision-making processes into our digital toolbox, based on an international interoperability standard, namely HL7 FHIR. A usability study was conducted with 3 clinical sites with 20 users in total to gather feedback and to subsequently prioritize updates to the ADLIFE toolbox. Results: User satisfaction is measured in the QUIS7 questionnaire on a 9-point scale in the following aspects: overall reaction, screen, terminology and tool feedback, learning, multimedia, training material and system capabilities. With all the average scores above 6 in all categories, most respondents have a positive reaction to the ADLIFE PEP platform and find it easy to use. We have identified shortcomings and have prioritized updates to the platform before clinical pilot studies are initiated. Conclusions: Having finalized design, implementation, and pre-deployment usability studies, and updated the tool based on further feedback, our patient empowerment mechanisms enabled via PROMs and shared decision-making processes are ready to be piloted in clinal settings. Clinical studies will be conducted based at six healthcare settings across Spain, UK, Germany, Denmark, and Israel. [ABSTRACT FROM AUTHOR]

Background: The nursing profession considers conscience as the foundation and cornerstone of clinical practice, which significantly influences professional decision-making and elevates the level of patient care. However, a precise definition of conscience in the nursing field is lacking, making it challenging to measure. To address this issue, this study employed the hybrid approach of Schwartz Barcott and Kim to analyze the concept of conscience-based nursing care. Methods: This approach involves a three-phase process; theoretical, fieldwork, and analytical. A systematic literature review was conducted using electronic databases during the first phase to find relevant papers. The content of 42 articles that met the inclusion criteria was extracted to determine the attributes, antecedents, and consequences of consciousness care using thematic analysis. Based on the working definition as a product of this phase, the plan of doing the fieldwork phase was designed. During this phase, data were collected through interviews with nurses all of whom were responsible for patient care in hospitals. In this phase, 5 participants were chosen for in-depth interviewing by purposeful sampling. Data were analyzed using directed content analysis. The findings of the theoretical and fieldwork phases were integrated and the final definition was derived. Results: The integration of the theoretical and fieldwork phases resulted in identifying four key characteristics of conscience-based nursing care. Firstly, it involves providing professional care with a conscientious approach. Secondly, ethics is at the core of conscience-based care. Thirdly, external spirituality plays a significant role in shaping one's conscience in this context. Finally, conscience-based nursing care is both endogenous and exogenous, with professional commitment being the central focus of care. Conclusion: Conscience-based nursing care is an essential component of ethical care, which elevates clinical practice to professional care. It requires the integration of individual and social values, influenced by personal beliefs and cultural backgrounds, and supported by professional competence, resources, and a conducive organizational atmosphere in the healthcare field. This approach leads to the provision of responsive care, moral integrity, and individual excellence, ultimately culminating in the development of professionalism in nursing. [ABSTRACT FROM AUTHOR]

Background: This systematic review contributes to the understanding of the characteristics of built food environments that may be associated with choices of alternative protein foods (APF). Using the built food environment typology proposed by Downs et al., we investigated various environmental structures (e.g., supermarkets, other retailers, farmers' markets, restaurants, schools, and online vendors) and the characteristics that may facilitate or hinder consumers' choices. For example, facilitators and barriers may refer to the physical characteristics of environmental structures, food presentation practices, the organizational strategies or policies operating in the setting, or the actions that retailers or consumers engage in while selling, serving, choosing, trying, or purchasing APF in these environmental structures. Methods: A systematic review (PROSPERO database preregistration; no. CRD42023388700) was conducted by searching 13 databases for peer-reviewed journals focusing on the fields of economics and business, agriculture, medical sciences, and social sciences. Data searches, coding, and quality evaluations were conducted by at least 2 researchers. A total of 31 papers (36 original studies) were included. The risk of bias was evaluated with the Joanna Briggs Institute quality evaluation tool, with 24 publications presenting low risk of bias. Results: The findings indicate that perceived and actual availability facilitate consumers' APF choices across a built food environment. Several barriers/facilitators were associated with APF choices in specific types of built food environments: the way food is presented in produce sections (supermarkets), consumer habits in terms of green and specialty shopping (grocery stores), and mismatches among retailer actions in regard to making APF available in one type of food environment structure (e-commerce) and consumers' preferences for APF being available in other food environment structures (supermarkets, grocery stores). The effect of a barrier/facilitator may depend on the APF type; for example, social norms regarding masculinity were a barrier affecting plant-based APF choices in restaurants, but these norms were not a barrier affecting the choice of insect-based APF in restaurants. Conclusions: Addressing barriers/facilitators identified in this review will help in developing environment-matching interventions that aim to make alternative proteins mainstream. Trial registration: PROSPERO database registration: #CRD42023388700. [ABSTRACT FROM AUTHOR]

Background: Medical Assistance in Dying (MAiD) was legalized in Canada in 2016 and amended in 2021. At the time that this study was conducted, the federal government was considering expanding the eligibility criteria to include patients whose death was not reasonably foreseeable. The purpose of this study was to better understand rural healthcare professionals' experiences with assisted dying set against the backdrop of legislative expansion. Methods: A qualitative exploratory study was undertaken with general rural practice physicians, nurse practitioners, registered nurses, ethicists, patients, and patient families in rural Southern Alberta, Canada. For this paper, data from 18 audio-recorded and transcribed semi-structured interviews with healthcare professionals were analyzed using thematic analysis. Categories and patterns of shared meaning that linked to an overarching theme were identified. Results: Between the binary positions of full support for and conscientious objection to assisted dying, rural healthcare professionals' decisions to participate in MAiD was based on their moral convictions, various contextual factors, and their participation thresholds. Factors including patient suffering; personal and professional values and beliefs; relationships with colleagues, patients and family, and community; and changing MAiD policy and legislation created nuances that informed their decision-making. Conclusions: The interplay of multiple factors and their degree of influence on healthcare professionals' decision-making create multiple decision points between full support for and participation in MAiD processes and complete opposition and/or abstention. Moreover, our findings suggest evolving policy and legislation have the potential to increase rural healthcare professionals' uncertainty and level of discomfort in providing services. We propose that the binary language typically used in the MAiD discourse be reframed to reflect that decision-making processes and actions are often fluid and situational. [ABSTRACT FROM AUTHOR]

Background: Advanced cancer patients with good Eastern Cooperative Oncology Group (ECOG) performance status (score 0–1) are underrepresented in current qualitative reports compared with their dying counterparts. Aim: To explore the experiences and care needs of advanced cancer patients with good ECOG. Design: A qualitative phenomenological approach using semi-structured interview was employed. Data was analyzed using the Colaizzi's method. Setting/Participants: Purposive sample of terminal solid cancer patients on palliative care aged 18–70 years with a 0–1 ECOG score were recruited from a tertiary general hospital. Results: Sixteen participants were interviewed. Seven themes were generated from the transcripts, including experiencing no or mild symptoms; independence in self-care, decision-making, and financial capacity; prioritization of cancer growth suppression over symptom management; financial concerns; hope for prognosis and life; reluctance to discuss death and after-death arrangements; and use of complementary and alternative medicine (CAM) and religious coping. Conclusions: Advanced cancer patients with good ECOG have distinct experiences and care needs from their dying counterparts. They tend to experience no or mild symptoms, demonstrate a strong sense of independence, and prioritize cancer suppression over symptom management. Financial concerns were common and impact their care-related decision-making. Though being hopeful for their prognosis and life, many are reluctant to discuss death and after-death arrangements. Many Chinese patients use herbal medicine as a CAM modality but need improved awareness of and accessibility to treatment options. Healthcare professionals and policy-makers should recognize their unique experiences and needs when tailoring care strategies and policies. Key statements: What is already known about the topic? • Even in their advanced stage, cancer patients with good ECOG performance status are capable of self-care and less reliant on care provided by other. • Existing qualitative research mainly focuses on advanced cancer patients with poor ECOG, emphasizing pain management, emotional distress, and palliative care. What this paper adds? • Our findings reveal distinct experiences and care needs of advanced cancer patients with good ECOG performance status from their dying counterparts. Implications for practice, theory or policy. • Healthcare professionals should recognize and address the patient group's distinct needs. • Future research should further investigate their symptom trajectory, influencing factors, and care needs to fill the gap in their cancer journey. • Policy-makers should develop tailored policies that consider good ECOG performance status. [ABSTRACT FROM AUTHOR]

Background: Decision-making in healthcare is increasingly complex; notably in hospital environments where the information density is high, e.g., emergency departments, oncology departments, and psychiatry departments. This study aims to discover decisions from logged data to improve the decision-making process. Methods: The Design Science Research Methodology (DSRM) was chosen to design an artifact (algorithm) for the discovery and visualization of decisions. The DSRM's different activities are explained, from the definition of the problem to the evaluation of the artifact. During the design and development activities, the algorithm itself is created. During the demonstration and evaluation activities, the algorithm was tested with an authentic synthetic dataset. Results: The results show the design and simulation of an algorithm for the discovery and visualization of decisions. A fuzzy classifier algorithm was adapted for (1) discovering decisions from a decision log and (2) visualizing the decisions using the Decision Model and Notation standard. Conclusions: In this paper, we show that decisions can be discovered from a decision log and visualized for the improvement of the decision-making process of healthcare professionals or to support the periodic evaluation of protocols and guidelines. [ABSTRACT FROM AUTHOR]

Background: Seasonal Malaria Chemoprevention (SMC) is a highly effective intervention for preventing malaria, particularly in areas with highly seasonal transmission. Monitoring and evaluating (M&E) SMC programmes are complex due to the scale, time-sensitive delivery of the programme, and influence of external factors. This paper describes the process followed to develop a comprehensive M&E framework tailored specifically for the SMC context. Methods: The Framework was developed through a literature and programme review, and stakeholder dialogues across three implementing countries—Burkina Faso, Chad, and Nigeria. Expert consultation further refined the Framework through an iterative approach drawing upon data collected through the three sources. The Framework was designed using the Logical Framework Approach incorporating external factors and intentionally aligned with global malaria M&E standards. Results: An overall aim and seven programme objectives were developed measured by 70 indicators. The indicators also capture the causal links between the implementation and results of the programme. The Framework leverages the use of current data sources and existing mechanisms, ensuring efficient data use without requiring a significant increase in resources for overall programme optimization. It also promotes the use of data triangulation, and stratification for a more nuanced understanding of factors affecting programme performance and timely data informed decision-making. Conclusions: The SMC M&E Framework presented here provides a standardized approach for programme implementers to enhance decision-making for optimal programme performance. This is an essential tool as the scope of SMC programmes expands to new geographies and target age groups. [ABSTRACT FROM AUTHOR]

Background: Patients with severe chronic obstructive pulmonary disease (COPD) could have palliative care (PC) needs because of unmet needs such as dyspnoea. This may lead to anxiety and may have an impact on patients' ability to perform daily activities of living. PC can be started when patients with COPD have unmet needs and can be provided alongside disease-modifying therapies. Non-invasive ventilation (NIV) could be an important measure to manage dyspnoea in patients with COPD in need of PC. A scoping review was conducted to gain an overview of the existing research and to identify knowledge gaps. The aim of this scoping review was to systematically map published studies on the use of NIV in patients with COPD with PC needs, including the perspectives and experiences of patients, families, and healthcare professionals (HCPs). Methods: This review was conducted following the framework of Arksey and O'Malley. The reporting of the review was guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews checklist. The review protocol was published. AMED, CINAHL, Embase, MEDLINE, PEDro, and PsycInfo were searched from inception to November 14, 2022. The included studies had to report the perspectives and experiences of COPD patients, relatives, and HCPs regarding NIV in the care of patients with COPD with PC needs. In pairs, the authors independently assessed studies' eligibility and extracted data. The data were organised thematically. The results were discussed in a consultation exercise. Results: This review included 33 papers from 32 studies. Four thematic groupings were identified: preferences and attitudes towards the use of NIV; patient participation in the decision-making process of NIV treatment; conflicting results on the perceived benefits and burdens of treatment; and heterogenous clinical outcomes in experimental studies. Patients perceived NIV as a 'life buoy' to keep them alive. Many patients wanted to take part in the decision-making process regarding NIV treatment but expressed varying degrees of inclusion by HCPs in such decision-making. Conflicting findings were identified regarding the perceived benefits and burdens of NIV treatment. Diversity in heterogeneous clinical outcomes were reported in experimental studies. Conclusions: There is a need for more studies designed to investigate the effectiveness of NIV as a palliative measure for patients with COPD with PC needs using comprehensive outcomes. It is especially important to gain more knowledge on the experiences of all stakeholders in the use of home-based NIV treatment to these patients. [ABSTRACT FROM AUTHOR]

Background: Talent is a crucial resource for economic and social development, serving as the driving force behind urban progress. As China experiences rapid growth in digital city construction, the capability of e-services continues to improve incessantly. In China, the new-generation highly educated migrants (NGHEMs) account for ~ 20–30% of the total floating populations. This study aimed to explore the settlement intention of new-generation highly educated migrations in China from the new perspective of urban e-service capabilities. Furthermore, the mechanism of the urban e-services on the settlement intention on the NGHEMs will be proved. Methods: This paper employed data of China Migrants Dynamic Survey in 2017 and Evaluation Report of Government E-service Capability Index (2017). Descriptive analyses were conducted to investigate the factors influencing the settlement intention of NGHEMs in the destination city. Based on the principle of utility maximization, LASSO regression was employed to select individual and city characteristics that determined the settlement intention of NGHEMs. The impact of urban e-services on settlement intention was analyzed by using ordinal logit model. Additionally, robustness check, endogeneity analysis, and heterogeneity analysis were performed to validate the benchmark regression results. Finally, mediation model was employed to examine whether urban e-services enhance the settlement intention of NGHEMs by improving urban livability and urban innovation. Results: The results indicate that the urban e-services promote the NGHEMs' settlement intention in the destination cities. Moreover, the results are still robust through a series of robustness tests. Furthermore, from the perspective of individual and regional heterogeneity, urban e-services significantly enhances the settlement intention of NGHEMs with male and female, married and urban household registration, and urban e-services can promote the settlement intention of NGHEMs with over 3 million inhabitants and those in the eastern regions of China. Finally, the intermediary effect test shows that urban e-services promote the settlement intention of NGHEMs through urban livability and urban innovation. Conclusion: This study highlights the important impact of urban e-services on the settlement intention of new-generation highly educated migrants. The conclusions of this study provide suggestions for the government to use when designing policies to enhance the settlement intention of the NGHEMs and to improve the development of urban e-services. [ABSTRACT FROM AUTHOR]

Timely euthanasia of a compromised pig in farming practice has been identified as a critical topic in veterinary medicine. The questions 'why and when are pigs euthanized' and 'what influences the decision making process' need to be answered to improve the situation. In the past five years, work addressing these issues has been published in the literature, however, a synthesis of the findings is missing. With the help of a quantitative and qualitative analysis, this paper has generated a landscape review to outline major topics, the role of clinical signs and further influences on the decision to euthanize a pig. Due to the quantitative content analysis, 58 topics have been identified with the role of welfare as a justification and training for caretakers in making euthanasia decisions as the most frequently mentioned. The qualitative analysis of why and when a pig is euthanized generated a set of clinical signs for organ tracts, and a set of categories influencing the decision making process. The results outline the need to increase research on details specific to understanding how clinical signs evolve over time before euthanasia. In summary, the analysis provides an overview of work in the field and ideas on how to close knowledge gaps in the future. Moreover, the article contributes to harmonize efforts in the field and underlines the need for more research about the care of compromised and injured pigs. [ABSTRACT FROM AUTHOR]

Background: Treatment for anterior cruciate ligament (ACL) rupture may follow a surgical or nonsurgical pathway. At present, there is uncertainty around treatment choice. Two shared decision-making tools have been codesigned to support patients to make a decision about treatment following an ACL rupture. The shared decision-making tools include a patient information leaflet and an option grid. We report the protocol for a mixed-methods feasibility study, with nested qualitative interviews, to understand feasibility, acceptability, indicators of effectiveness and implementation factors of these shared decision-making tools (combined to form one shared decision-making intervention). Methods: A single-centre non-randomised feasibility study will be conducted with 20 patients. Patients diagnosed with an ACL rupture following magnetic resonance imaging will be identified from an orthopaedic clinic. The shared decision-making intervention will be delivered during a clinical consultation with a physiotherapist. The primary feasibility outcomes include the following: recruitment rate, fidelity, acceptability and follow-up questionnaire completion. The secondary outcome is the satisfaction with decision scale. The nested qualitative interview will explore experience of using the shared decision-making intervention to understand acceptability, implementation factors and areas for further refinement. Discussion: This study will determine the feasibility of using a newly developed shared decision-making intervention designed to support patients to make a decision about treatment of their ACL rupture. The acceptability and indicators of effectiveness will also be explored. In the long term, the shared decision-making intervention may improve service and patient outcomes and ensure cost-effectiveness for the NHS; ensuring those most likely to benefit from surgical treatment proceed along this pathway. Trial registration: Pending registration on ISRCTN. [ABSTRACT FROM AUTHOR]

Background: The heterogeneous biology of ductal carcinoma in situ (DCIS), as well as the variable outcomes, in the setting of numerous treatment options have led to prognostic uncertainty. Consequently, making treatment decisions is challenging and necessitates involved communication between patient and provider about the risks and benefits. We developed and investigated an interactive decision support tool (DST) designed to improve communication of treatment options and related long-term risks for individuals diagnosed with DCIS. Findings: The DST was developed for use by individuals aged > 40 years with DCIS and is based on a disease simulation model that integrates empirical data and clinical characteristics to predict patient-specific impacts of six DCIS treatment choices. Personalized risk predictions for each treatment option were communicated using icon arrays and percentages for each outcome. Users of the DST were asked before and after interacting with the DST about: (1) awareness of DCIS treatment options, (2) willingness to consider these options, (3) knowledge of risks associated with DCIS, and (4) helpfulness of the DST. Data were collected from January 2019 to April 2022. Users' median estimated risk of dying from DCIS in 10 years decreased from 9% pre-tool to 3% post-tool (p < 0.0001). 76% (n = 101/132) found the tool helpful. Conclusions: Information about DCIS treatment options and related risk predictions was effectively communicated, and a large majority participants found the DST to be helpful. Successfully informing patients about their treatment options and how their individual risks affect those options is a critical step in the decision-making process. Clinicaltrials.gov Identifier NCT02926911. [ABSTRACT FROM AUTHOR]

Objective: Cardiovascular magnetic resonance enables the quantification of functional and morphological parameters with an impact on therapeutical decision making. While quantitative assessment is established in 2D, novel 3D techniques lack a standardized approach. Multi-planar-reformatting functionality in available software relies on visual matching location and often lacks necessary functionalities for further post-processing. Therefore, the easy-to-use Reslice3Dto2D software tool was developed as part of another research project to fill this gap and is now introduced with this work. Results: The Reslice3Dto2D reformats 3D data at the exact location of a reference slice with a two-step-based interpolation in order to reflect in-plane discretization and through-plane slice thickness including a slice profile selection. The tool was successfully validated on an artificial dataset and tested on 119 subjects with different underlying pathologies. The exported reformatted data could be imported into three different post-processing software tools. The quantified image sharpness by the Frequency Domain Image Blur Measure was significantly decreased by around 40% on rectangular slice profiles with 7 mm slice thickness compared to 0 mm due to partial volume effects. Consequently, Reslice3Dto2D enables the quantification of 3D data with conventional post-processing tools as well as the comparison of 3D acquisitions with their established 2D version. [ABSTRACT FROM AUTHOR]

Background: When doctors seek medical care, there is evidence that the treating doctor can struggle to provide optimal treatment. Guidelines state that doctor-patients should be treated like any other patient, but this is challenging for the treating doctor. This study set out to explore both the positive experiences general practitioners (GPs) have when caring for doctor-patients, and the challenges they confront. It sought to identify whether GPs believe they treat doctor-patients differently to other patients and if so, in what ways, for what reasons, and how this impacts their provision of care. The study also aimed to develop a model that makes sense of GPs' experiences when caring for a patient who is also a medical doctor. Method: Qualitative in-depth interviews with 26 GPs were carried out, with analysis of de-identified transcripts using pragmatic grounded theory. Evolving understandings were used to develop a model to make sense of GPs' experiences caring for their doctor-patients. Results: The core aspects of GPs' experiences of treating fellow doctors centred around concepts of respect and collegiality. These play a central role in mediating how a treating doctor experiences a consultation with a doctor-patient, influencing the quality of care provided. GPs shared that the use of medical language (and assumptions about the doctor-patient's knowledge/behaviours), testing, the exploration of sensitive issues, and the degree of shared decision-making were areas where their treatment might vary when treating a doctor-patient. Treating doctors often experience anxiety about errors and the likely scrutiny from the medical, and wider community. The decision to treat the doctor-patient differently was driven by a desire to maintain a sense of collegiality, to not offend, to meet their doctor-patient's expectations, and to appear competent. Conclusion: The professional socialisation of doctors, with its emphasis on collegiality and respect, plays a significant role in the dynamics of the therapeutic relationship when a doctor treats a doctor-patient. Current guidelines make little reference to these dynamics with the over-simplified 'keep it normal' recommendations. Treating doctors need evidence-informed training to navigate these challenges and ensure they can effectively deliver quality care to their doctor-patients. [ABSTRACT FROM AUTHOR]

Background: French laws governing end-of-life medical practices forbid euthanasia and affirm patients' right to deep and continuous sedation until death. Cultural traditions and disparities in health care provision, as in overseas France, could limit the enforcement of such laws and modify end-of-life medical practices. Aim: This research aims to describe end-of-life medical decisions in overseas France and to compare with those described in mainland France. Methods: A retrospective study of a random sample of adult patients who died between March 2020 and February 2021 was conducted in four overseas French departments. Physicians who certified the deaths were asked to describe end-of-life care and medical decisions in a questionnaire. Results: A total of 1815 deaths were analysed over 8730 questionnaires sent. Withholding treatments was the most frequent decision (41%), treatment for pain or symptoms was intensified for a third of patients, Deep and continuous sedation until death was implemented in 13.3% cases. The use of drugs to deliberately end life was mentioned in 1.3% deaths. At least one decision was made in 61.6% deaths. More decisions that may hasten death were made before predictable deaths. Intensification of pain and symptoms treatment was more frequent in 2022 than in 2010. Deep and continuous sedation was introduced by law in 2016 without prejudice to other decisions. Conclusion: Physicians in overseas France have implemented recent changes in end-of-life laws, including deep and continuous sedation. Comparisons with 2010 mainland France survey show a better implementation of palliative medicine in 2022, with higher proportions of treatment withholding. [ABSTRACT FROM AUTHOR]

Background: Perioperative reflux aspiration presents a grave concern during sedation or general anesthesia, particularly when solid gastric contents prompt acute upper respiratory obstruction, potentially resulting in fatal consequences for patients. Currently, there are limited means for promptly assessing solid gastric contents in clinical settings. Therefore, this study examined the efficacy of ultrasound assessment for solid gastric contents, offering a rapid and non-invasive approach for early detection and decision-making regarding interventions. Methods: The study included 400 patients scheduled for upper endoscopy procedures, which encompassed both gastroscope and gastroscope combined colonoscopy examinations with sedation. Ultrasound scanning of the antrum was performed while patients were positioned semi-sitting or in the right lateral decubitus (RLD) posture. The evaluation of solid gastric contents relied on direct visual observation during endoscopy. Gastric volume measurement occurred subsequent to endoscopic suction of gastric contents. Receiver operating characteristic curves were utilized to assess the effectiveness of ultrasonography in discerning solid contents. Result: Seven patients undergoing gastroscope with sedation were found to have solid gastric contents. The sensitivity, specificity, positive predictive value, and negative predictive value of the ultrasound qualitative evaluation of solid contents were 85.7%, 99%, 60%, and 99.7%, respectively. Conclusion: Solid stomach contents can be evaluated qualitatively with reasonable accuracy using ultrasonography. Additionally, in patients undergoing upper endoscopy and assessed to have solid gastric contents with ultrasound, administration of mild sedation is recommended. Trial registration: www.chictr.org.cn (ChiCTR2100048994); registered 19/07/2021. [ABSTRACT FROM AUTHOR]

Background: Deprescribing has been defined as the planned process of reducing or stopping medications that may no longer be beneficial or are causing harm, with the goal of reducing medication burden while improving patient quality of life. At present, little is known about the specific challenges of decision-making to support deprescribing for patients who are accessing palliative care. By exploring the perspectives of healthcare professionals, this qualitative study aimed to address this gap, and explore the challenges of, and potential solutions to, making decisions about deprescribing in a palliative care context. Methods: Semi-structured interviews were conducted with healthcare professionals in-person or via video call, between August 2022 – January 2023. Perspectives on approaches to deprescribing in palliative care; when and how they might deprescribe; and the role of carers and family members within this process were discussed. Interviews were audio-recorded and transcribed verbatim. Reflexive thematic analysis enabled the development of themes. QSR NVivo (Version 12) facilitated data management. Ethical approval was obtained from the NHS Health Research Authority (ref 305394). Results: Twenty healthcare professionals were interviewed, including: medical consultants, nurses, specialist pharmacists, and general practitioners (GPs). Participants described the importance of deprescribing decision-making, and that it should be a considered, proactive, and planned process. Three themes were developed from the data, which centred on: (1) professional attitudes, competency and responsibility towards deprescribing; (2) changing the culture of deprescribing; and (3) involving the patient and family/caregivers in deprescribing decision-making. Conclusions: This study sought to explore the perspectives of healthcare professionals with responsibility for making deprescribing decisions with people accessing palliative care services. A range of healthcare professionals identified the importance of supporting decision-making in deprescribing, so it becomes a proactive process within a patient's care journey, rather than a reactive consequence. Future work should explore how healthcare professionals, patients and their family can be supported in the shared decision-making processes of deprescribing. Trial registration: Ethical approval was obtained from the NHS Health Research Authority (ref 305394). [ABSTRACT FROM AUTHOR]

Background: "The hidden costs of informal caregiving" is an interdisciplinary concept. While caregivers make a significant contribution to the process of caregiving, they sacrifice their leisure time, and incur risks of dropping out of the job, impaired mental and physical health, and decreased well-being within the context of caregiving. Those invisible sacrifices are often overlooked and described as hidden costs of informal caregiving. However, the conceptualisation of hidden costs of informal caregiving has not yet been clarified and scientifically assessed. The research aimed to clarify the concept of hidden costs of informal caregiving and develop an operational definition. Methods: Walker and Avant's concept analysis was conducted. Databases of CBM, CNKI, WanFang, VIP, PubMed, Embase, CINAHL, Web of Science, MEDLINE, Cochrane Library, Econlit, CINAHL and ProQuest were searched with the term "hidden costs of informal caregiving". Information about the uses of the concept, defining attributes, model cases, antecedents, consequences and empirical referents of hidden costs of informal caregiving was extracted and synthesized. Results: A total of 25 articles were included. The six defining attributes of hidden costs of informal caregiving were identified as including "undertaken by informal caregivers", "the time costs of caregiving", "costs of career development" "physical well-being costs", "mental well-being costs" and "social relationship costs". Personal characteristics of the caregivers and care recipients, along with caregiving attributes, were among the antecedents. The consequences of hidden costs of informal caregiving resulted in negative influences which included poor quality of life, life-altering decisions, options for the type of care, some degree of economic hardship, decreased compliance with treatment plans and monetary value informal caregivers are willing to pay to be replaced. Conclusion: This concept analysis decisively illuminated the hitherto nebulous concept and expanded the contents of hidden costs of informal caregiving, which will foster a deeper appreciation of the invisible cost of caregivers. Moreover, it will provide a reference for the study of the hidden costs of informal caregiving in future, contribute to the development of assessment tools and theoretical models of hidden costs of informal caregiving, and create a basis for designing an evidence-based care program. [ABSTRACT FROM AUTHOR]

The healthcare industry has been put to test the need to manage enormous amounts of data provided by various sources, which are renowned for providing enormous quantities of heterogeneous information. The data are collected and analyzed with different Data Analytic (DA) and machine learning algorithm approaches. Researchers, scientists, and industrialists must manage or select the best approach associated with DA in healthcare. This scientific study is based on decision analysis between the DA factors and alternatives. The information affects the whole system in a rational manner. This information is very important in healthcare sector for appropriate prediction and analysis. The evaluation discusses its benefits and presents an analytic framework. The Fuzzy Analytic Hierarchy Process (Fuzzy AHP) approach is used to address the weight of the factors. The Fuzzy Techniques for Order Preference by Similarity to Ideal Solution (Fuzzy TOPSIS) address the rank of the data analytic alternatives used in healthcare sector. The models used in the article briefly discuss the challenges of DA and approaches to address those challenges. The assorted factors of DA are capture, cleaning, storage, security, stewardship, reporting, visualization, updating, sharing, and querying. The DA alternatives include descriptive, diagnostic, predictive, prescriptive, discovery, regression, cohort and inferential analyses. The most influential factors of the DA and the most suitable approach for the DA are evaluated. The 'cleaning' factor has the highest weight, and 'updating' is achieved at least by the Fuzzy-AHP approach. The regression approach of data analysis had the highest rank, and the diagnostic analysis had the lowest rank. Decision analyses are necessary for data scientists and medical providers to predict diseases appropriately in the healthcare domain. This analysis also revealed the cost benefits to hospitals. [ABSTRACT FROM AUTHOR]

Background: Multiple clinician adjustable parameters impact upon glycemia in people with type 1 diabetes (T1D) using Medtronic Mini Med 780G (MM780G) AHCL. These include glucose targets, carbohydrate ratios (CR), and active insulin time (AIT). Algorithm-based decision support advising upon potential settings adjustments may enhance clinical decision-making. Methods: Single-arm, two-phase exploratory study developing decision support to commence and sustain AHCL. Participants commenced investigational MM780G, then 8 weeks Phase 1-initial optimization tool evaluation, involving algorithm-based decision support with weekly AIT and CR recommendations. Clinicians approved or rejected CR and AIT recommendations based on perceived safety per protocol. Co-design resulted in a refined algorithm evaluated in a further identically configured Phase 2. Phase 2 participants also transitioned to commercial MM780G following "Quick Start" (algorithm-derived tool determining initial AHCL settings using daily insulin dose and weight). We assessed efficacy, safety, and acceptability of decision support using glycemic metrics, and the proportion of accepted CR and AIT settings per phase. Results: Fifty three participants commenced Phase 1 (mean age 24.4; Hba1c 61.5mmol/7.7%). The proportion of CR and AIT accepted by clinicians increased between Phases 1 and 2 respectively: CR 89.2% vs. 98.6%, p < 0.01; AIT 95.2% vs. 99.3%, p < 0.01. Between Phases, mean glucose percentage time < 3.9mmol (< 70mg/dl) reduced (2.1% vs. 1.4%, p = 0.04); change in mean TIR 3.9-10mmol/L (70-180mg/dl) was not statistically significant: 72.9% ± 7.8 and 73.5% ± 8.6. Quick start resulted in stable TIR, and glycemic metrics compared to international guidelines. Conclusion: The co-designed decision support tools were able to deliver safe and effective therapy. They can potentially reduce the burden of diabetes management related decision making for both health care practitioners and patients. Trial registration: Prospectively registered with Australia/New Zealand Clinical Trials Registry(ANZCTR) on 30th March 2021 as study ACTRN12621000360819. [ABSTRACT FROM AUTHOR]

Background: Paramedics are responsible for critical resuscitation decisions when attending Out of Hospital Cardiac Arrests (OHCA). Existing research indicates that a range of clinical and non-clinical factors moderate their decision-making. Within the United Kingdom (UK), there is little evidence on how and why paramedics make their decisions at actual OHCA events. Methods: We explored the experiences of UK paramedics using individually recalled OHCA events as catalysts for discussion. Pen portraits developed from semi-structured interviews with 31 paramedics across two UK ambulance services were thematically analysed, enabling cross-participant comparisons whilst retaining depth and context. Results: We identified four themes: uncertainties encountered in resuscitation guidelines, influences on decision-making, holistic perspectives, and indirect moderators. We found that paramedics experienced uncertainty at all stages of the resuscitation process. Uncertainties arose from indeterminate, ambiguous or complex information and were described as having both clinical and ethical dimensions. Whilst guidelines drove paramedics' decisions, non-clinical personal, practical and relational factors moderated their assessments of survivability and decision-making, with attitudes to interactions between patient age, frailty and quality of life playing a substantial role. Coping strategies such as uncertainty reduction, assumption-based reasoning and weighing pros and cons were evident from interviews. Conclusions: The complexity of interactions between clinical and non-clinical factors points to an element of variability in paramedics' responses to uncertainty. Exploring UK paramedics' uncertainties and decision-making during specific OHCA events can help acknowledge and address uncertainties in resuscitation guidelines and paramedic training, providing paramedics with the tools to manage uncertainty in a consistent and transparent way. [ABSTRACT FROM AUTHOR]

Background: Syringe services programs (SSPs) provide harm reduction supplies and services to people who use drugs and are often required by funders or partners to collect data from program participants. SSPs can use these data during monitoring and evaluation (M&E) to inform programmatic decision making, however little is known about facilitators and barriers to collecting and using data at SSPs. Methods: Using the Consolidated Framework for Implementation Research (CFIR), we conducted 12 key informant interviews with SSP staff to describe the overall landscape of data systems at SSPs, understand facilitators and barriers to data collection and use at SSPs, and generate recommendations for best practices for data collection at SSPs. We used 30 CFIR constructs to develop individual interview guides, guide data analysis, and interpret study findings. Results: Four main themes emerged from our analysis: SSP M&E systems are primarily designed to be responsive to perceived SSP client needs and preferences; SSP staffing capacity influences the likelihood of modifying M&E systems; external funding frequently forces changes to M&E systems; and strong M&E systems are often a necessary precursor for accessing funding. Conclusions: Our findings highlight that SSPs are not resistant to data collection and M&E, but face substantial barriers to implementation, including lack of funding and disjointed data reporting requirements. There is a need to expand M&E-focused funding opportunities, harmonize quantitative indicators collected across funders, and minimize data collection to essential data points for SSPs. [ABSTRACT FROM AUTHOR]

Background and objectives: Comprehending the research dataset is crucial for obtaining reliable and valid outcomes. Health analysts must have a deep comprehension of the data being analyzed. This comprehension allows them to suggest practical solutions for handling missing data, in a clinical data source. Accurate handling of missing values is critical for producing precise estimates and making informed decisions, especially in crucial areas like clinical research. With data's increasing diversity and complexity, numerous scholars have developed a range of imputation techniques. To address this, we conducted a systematic review to introduce various imputation techniques based on tabular dataset characteristics, including the mechanism, pattern, and ratio of missingness, to identify the most appropriate imputation methods in the healthcare field. Materials and methods: We searched four information databases namely PubMed, Web of Science, Scopus, and IEEE Xplore, for articles published up to September 20, 2023, that discussed imputation methods for addressing missing values in a clinically structured dataset. Our investigation of selected articles focused on four key aspects: the mechanism, pattern, ratio of missingness, and various imputation strategies. By synthesizing insights from these perspectives, we constructed an evidence map to recommend suitable imputation methods for handling missing values in a tabular dataset. Results: Out of 2955 articles, 58 were included in the analysis. The findings from the development of the evidence map, based on the structure of the missing values and the types of imputation methods used in the extracted items from these studies, revealed that 45% of the studies employed conventional statistical methods, 31% utilized machine learning and deep learning methods, and 24% applied hybrid imputation techniques for handling missing values. Conclusion: Considering the structure and characteristics of missing values in a clinical dataset is essential for choosing the most appropriate data imputation technique, especially within conventional statistical methods. Accurately estimating missing values to reflect reality enhances the likelihood of obtaining high-quality and reusable data, contributing significantly to precise medical decision-making processes. Performing this review study creates a guideline for choosing the most appropriate imputation methods in data preprocessing stages to perform analytical processes on structured clinical datasets. Highlights: • The evidence map emphasized the importance of considering missing data characteristics when choosing an imputation method, providing insights for researchers in method selection. • The distinction between statistical and learning-based approaches highlighted the strengths and considerations of each method based on data structure. • Understanding missing data structures can enhance the quality and reliability of data imputation techniques, and improve medical decision-making accuracy. • Simulation studies are crucial for validating imputation techniques and enhancing their robustness in practical applications. • Considering missing data mechanisms, patterns, and ratios can aid researchers in making informed decisions on selecting appropriate imputation methods, leading to high-quality, and reusable data for precise medical decision-making. [ABSTRACT FROM AUTHOR]

Background: Epithelial ovarian cancer (EOC) is one of the deadliest gynaecological malignancies worldwide. The aim of this retrospective study was to create a predictive scoring model based on simple immunological and inflammatory parameters to predict overall survival (OS) and progression-free survival (PFS) in patients with EOC. Methods: We obtained 576 EOC patients and randomly assigned them to the training set (n = 405) and the validation set (n = 171) in a ratio of 7:3. We retrospectively evaluated the association between PIV and OS and PFS using a novel immunoinflammatory marker, according to the optihmal treshold of PIV, we divided the patients into two different subgroups, high PIV (PIV > 254.9) and low PIV (PIV ≤ 254.9). Pan-immune Inflammatory Value (PIV) was computed as follows: neutrophil count (109/L) × platelet count (109/L) × monocyte count (109/L)/lymphocyte count (109/L). Then developed a simple score prediction model based on several independent prognostic parameters using Cox regression analysis. We used receiver operator characteristic (ROC) curves, calibration plots, and decision analysis (DCA) curves to evaluate the performance of the model. Finally, we used Kaplan-Meier curves to ensure that the model could distinguish well between low- and high-risk groups. Results: There was a significant difference in survival outcomes between high PIV (PIV > 310.2) and low PIV (PIV ≤ PIV310.2) (3-year survival rates of 61.34% and 76.71%, respectively); 5-year OS, 25.21% and 51.14%, respectively; 3-year PFS, 40.90% and 65.30%; 5-year PFS, 19.33% and 39.73%, respectively). Column plots of OS and PFS were constructed using independent prognostic factors. In the training module, the 3-, 5-, and 10-year AUCs for OS and PFS column charts were 0.713, 0.796, 0.839, and 0.730, 0.799, 0.826, respectively.In the validation cohort, the 3-, 5-, and 10-year AUCs for OS and PFS column charts were 0.676, 0.803, 0.685, and 0.700, respectively, 0.754, 0.727. The calibration curves showed good agreement between predicted survival and actual observations. The decision analysis curves also showed that the current model has good accuracy and clinical applicability. 3-year OS was 61.34% and 76.71%, respectively; 5-year OS was 25.21% and 51.14%, respectively; 3-year PFS was 40.90% and 65.30%, respectively; 5-year PFS was 19.33% and 39.73%, respectively. Conclusions: We constructed and validated a PIV-based nomogram to predict OS and PFS in EOC patients, with a view to helping gynaecologists converge on oncologists in their treatment and follow-up expertise in epithelial ovarian cancer. [ABSTRACT FROM AUTHOR]

Background: Schizophrenia is a pervasive and severe mental disorder characterized by significant disability and high rates of recurrence. The persistently high rates of readmission after discharge present a serious challenge and source of stress in treating this population. Early identification of this risk is critical for implementing targeted interventions. The present study aimed to develop an easy-to-use predictive instrument for identifying the risk of readmission within 1-year post-discharge among schizophrenia patients in China. Methods: A prediction model, based on static factors, was developed using data from 247 schizophrenia inpatients admitted to the Mental Health Center in Wuxi, China, from July 1 to December 31, 2020. For internal validation, an additional 106 patients were included. Multivariate Cox regression was applied to identify independent predictors and to create a nomogram for predicting the likelihood of readmission within 1-year post-discharge. The model's performance in terms of discrimination and calibration was evaluated using bootstrapping with 1000 resamples. Results: Multivariate cox regression demonstrated that involuntary admission (adjusted hazard ratio [aHR] 4.35, 95% confidence interval [CI] 2.13–8.86), repeat admissions (aHR 3.49, 95% CI 2.08–5.85), the prescription of antipsychotic polypharmacy (aHR 2.16, 95% CI 1.34–3.48), and a course of disease ≥ 20 years (aHR 1.80, 95% CI 1.04–3.12) were independent predictors for the readmission of schizophrenia patients within 1-year post-discharge. The area under the curve (AUC) and concordance index (C-index) of the nomogram constructed from these four factors were 0.820 and 0.780 in the training set, and 0.846 and 0.796 for the validation set, respectively. Furthermore, the calibration curves of the nomogram for both the training and validation sets closely approximated the ideal diagonal line. Additionally, decision curve analyses (DCAs) demonstrated a significantly better net benefit with this model. Conclusions: A nomogram, developed using pre-discharge static factors, was designed to predict the likelihood of readmission within 1-year post-discharge for patients with schizophrenia. This tool may offer clinicians an accurate and effective way for the timely prediction and early management of psychiatric readmissions. [ABSTRACT FROM AUTHOR]

Background: Patients surgically treated for lumbar spinal stenosis or cervical radiculopathy report improvement in approximately two out of three cases. Advancements in Machine Learning and the utility of large datasets have enabled the development of prognostic prediction models within spine surgery. This trial investigates if the use of the postoperative outcome prediction model, the Dialogue Support, can alter patient-reported outcome and satisfaction compared to current practice. Methods: This is a prospective, multicenter clinical trial. Patients referred to a spine clinic with cervical radiculopathy or lumbar spinal stenosis will be screened for eligibility. Participants will be assessed at baseline upon recruitment and at 12 months follow-up. The Dialogue Support will be used on all participants, and they will thereafter be placed into either a surgical or a non-surgical treatment arm, depending on the decision made between patient and surgeon. The surgical treatment group will be studied separately based on diagnosis of either cervical radiculopathy or lumbar spinal stenosis. Both the surgical and the non-surgical group will be compared to a retrospective matched control group retrieved from the Swespine register, on which the Dialogue Support has not been used. The primary outcome measure is global assessment regarding leg/arm pain in the surgical treatment group. Secondary outcome measures include patient satisfaction, Oswestry Disability Index (ODI), EQ-5D, and Numeric Rating Scales (NRS) for pain. In the non-surgical treatment group primary outcome measures are EQ-5D and mortality, as part of a selection bias analysis. Discussion: The findings of this study may provide evidence on whether the use of an advanced digital decision tool can alter patient-reported outcomes after surgery. Trial registration: The trial was retrospectively registered at ClinicalTrials.gov on April 17th, 2023, NCT05817747. Protocol version: 1. Trial design: Clinical multicenter trial. [ABSTRACT FROM AUTHOR]

Background: Dysfunctional decision-making and intense craving represent pivotal aspects across all addictive behaviors, notably evident in gambling addiction where these factors significantly shape chasing behavior—continuing gambling to recoup losses—indicative of problematic gambling. This study explores the correlation between chasing behavior, craving, affective decision-making, decision-making styles, and gambling severity among habitual Italian gamblers. Methods: One hundred and sixty-six participants from diverse gambling venues completed assessments including the South Oaks Gambling Screen (SOGS), the Iowa Gambling Task (IGT), the General Decision-Making Style (GDMS), the Gambling Craving Scale (GACS), and a computerized task to measure chasing behavior. Participants were randomly assigned to Control and Loss chasing conditions. Results: Regression analyses revealed craving as a predictor of chasing behavior. Interestingly, individuals with a dependent decision-making style exhibited lower tendencies to chase. While IGT performance correlates with chasing frequency, it is not associated with the decision to continue or cease gambling. Intriguingly, gambling severity (SOGS total score) did not feature in the final models of both regression analyses. Discussion: These findings emphasize the significant role of craving in driving chasing behavior. Additionally, this study introduces, for the first time, the idea that a dependent decision-making style could potentially serve as a safeguard against chasing proneness. Conclusions: The study suggests a fundamental dichotomy between chasers and nonchasers among gamblers, irrespective of gambling severity. This distinction could be instrumental in tailoring more effective intervention strategies for gambling disorder treatment. [ABSTRACT FROM AUTHOR]

Background: Spanish-speakers with non-English language preference and complex medical needs suffer disparities in quality of care, safety, and health outcomes. Communication challenges during prolonged hospitalizations for complex illnesses negatively influence how this group engages in their care and decision-making while hospitalized. Limited literature capturing the perspectives of Spanish-speaking patients in this context exists. Given the impact of language barriers on care and medical decision-making, this study documents the experiences of Spanish-speaking patients with NELP and hospitalized with complex care needs as well as caregivers and community leaders. Methods: Using community-engaged recruitment strategies and semi-structured interviews and a focus group, we gathered insights from Spanish-speaking patients hospitalized for prolonged periods, caregivers, and community leaders from three geographic regions. Data were deidentified, transcribed, translated, coded in duplicate, and analyzed guided by grounded theory using NVivo. Results: We interviewed 40 participants: 27 patients, 10 caregivers and 3 community leaders. We identified four major themes: (1) Disconnected experiences impeding interactions, communication, and decision-making (2) Inadequate interpreter services (3) Benefits and consequences of family at the bedside (4) Community -informed recommendations. Conclusion: The study showed that in-person interpreters were preferred to virtual interpreters; yet interpreter access was suboptimal. This resulted in ad hoc family interpretation. Participants noted language negatively impacted patient's hospital experience, including decreasing confidence in medical decision-making. Recommendations from patients, caregivers, and community leaders included expanding interpreter access, bolstering interpreter quality and accuracy, and increasing resources for patient education. [ABSTRACT FROM AUTHOR]

Background: Withholding or withdrawing life-sustaining treatment in end-of-life patients is a challenging ethical issue faced by physicians. Understanding physicians' experiences and factors influencing their decisions can lead to improvement in end-of-life care. Objectives: To investigate the experiences of Thai physicians when making decisions regarding the withholding or withdrawal of life-sustaining treatments in end-of-life situations. Additionally, the study aims to assess the consensus among physicians regarding the factors that influence these decisions and to explore the influence of families or surrogates on the decision-making process of physicians, utilizing case-based surveys. Methods: A web-based survey was conducted among physicians practicing in Chiang Mai University Hospital (June - October 2022). Results: Among 251 physicians (response rate 38.3%), most of the respondents (60.6%) reported that they experienced withholding or withdrawal treatment in end-of-life patients. Factors that influence their decision-making include patient's preferences (100%), prognosis (93.4%), patients' quality of life (92.8%), treatment burden (89.5%), and families' request (87.5%). For a chronic disease with comatose condition, the majority of the physicians (47%) chose to continue treatments, including cardiopulmonary resuscitation (CPR). In contrast, only 2 physicians (0.8%) would do everything, in cases when families or surrogates insisted on stopping the treatment. This increased to 78.1% if the families insisted on continuing treatment. Conclusion: Withholding and withdrawal of life-sustaining treatments are common in Thailand. The key factors influencing their decision-making process included patient's preferences and medical conditions and families' requests. Effective communication and early engagement in advanced care planning between physicians, patients, and families empower them to align treatment choices with personal values. [ABSTRACT FROM AUTHOR]

World Health Organization (WHO) / Pan American Health Organization (PAHO) encouraged the utilization of whole-of-society and whole-of-government strategic approaches to increase countries' resilience towards mitigating the impact of the COVID-19 pandemic. Strategies included the implementation of multi-sectoral, multi-partner and multi-stakeholder planning, coordination, consultation, and action. We reviewed the experiences of three Latin American and Caribbean countries, related to the implementation of collaborative strategies in tackling COVID-19, specifically the nature of the collaboration, the dynamics and the stakeholders involved. A systematic literature review identified relevant publications and content analysis was conducted to determine the collaborative strategies. Colombia, Costa Rica, and Trinidad and Tobago were selected as case studies since they were from different LAC subregions and because of the accessibility of relevant literature. In the three countries, the pandemic response was coordinated by a national executive committee, led by the Ministry of Health. Intersectoral collaboration was evident in each, with the key stakeholders being public sector agencies, the private/corporate sector, private/non-profit, academic institutions, and international agencies. It was used primarily to facilitate data-driven, evidenced-informed decision-making and guidelines; to expand clinical care capacity and strengthen the national medical response; and to provide support for the most vulnerable populations. While the institutionalization of intersectoral collaboration can be recommended for the health sector beyond the pandemic, research is needed to evaluate the impact of specific collaborative strategies as well as barriers and facilitators. [ABSTRACT FROM AUTHOR]

Introduction: Contraceptive use is known to have a positive impact on maternal and child health outcomes; however, its use is still low in low-income countries, especially among people in humanitarian situations. This study explored decision-making processes towards the use of contraceptives by people in humanitarian situations to inform program design and uptake. Methods: A qualitative exploratory study was conducted among women of reproductive age (15–49 years) and men (15–60 years) living in three refugee settlements of Pagirinya, Nyumanzi, and Mirieyi and the surrounding host communities in Adjumani district, Uganda. Data were collected using 49 in-depth interviews (IDIs), 11 Key Informant Interviews (KIIs,) and 20 Focus Group Discussions (FGDs). Inductive thematic analysis was done with the aid of Atlas ti. Version 14. Results: We found that the decision-making processes entailed linear and nonlinear internalized cognitive and contextual processes involving four dynamic pathways. In the linear pathway, participants reported starting with 1) idea inception, 2) followed by cognitive processing, 3) consultation, and 4) decision-making for contraceptive use. The complex linear pathway happened when participants did not go through consultation but went straight to decision-making. However, participants who followed the non-linear pathway repeatedly went back to cognitive processing. Some women after consultation, or those already using and those not using contraceptives, decided to go back to cognitive processing to reconsider their current positions. This study found that some women who were not using contraceptives ended up using, while some who were using contraception ended up dropping out. Conclusions: This study showed dynamic decision-making processes involving both internal and external environments as triggers to decision-making for contraceptive use. Interventions to increase contraceptive use should target both users and significant others who influence the decision to use particularly among refugees. Trial registration: This study was registered by Makerere University School of Public Health Higher Degrees Research and Ethic Committee (HDREC) #188 and approved by Uganda National Council of Science and Technology on 15th/7/2021, Registration number—SS809ES. [ABSTRACT FROM AUTHOR]

Background: Previous studies have shown that shared decision-making (SDM) between a practitioner and a patient strengthens the ideal of treatment adherence. This study employed a multi-method approach to SDM in healthcare to reinforce the theoretical and methodological grounds of this argument. As the study design, self-reported survey items and experimental vignettes were combined in one electronic questionnaire. This technique aimed to analyze the effects of previous experiences and the current preferences regarding SDM on the intentions to follow-through with the medical recommendations. Method: Using quantitative data collected from the members of the Finnish Pensioners' Federation (N = 1610), this study focused on the important and growing population of older adults as healthcare consumers. Illustrated vignettes were used in the evaluation of expected adherence to both vaccination and the treatment of an illness, depending on the decision-making style varying among the repeated scenarios. In a within-subjects study design, each study subject acted as their own control. Results: The findings demonstrated that SDM correlates with expected adherence to a treatment and vaccination. Both the retrospective experiences and prospective aspirations of SDM in clinical encounters supported the patients' expected adherence to vaccination and treatment while decreasing the probability of pseudo-compliance. The association between SDM and expected adherence was not affected by the perceived health of the respondents. However, the associations among the expected adherence and decision-making styles were found to differ between the treatment and vaccination scenarios. Conclusions: SDM enables expected treatment adherence among older adults. Thus, the multi-method study emphasizes the importance of SDM in various healthcare encounters. The findings further imply that SDM research benefits from questionnaires combining self-report methods and experimental study designs. Further cross-validation studies using various types of written and illustrated scenarios are encouraged. [ABSTRACT FROM AUTHOR]

Background: High completed fertility among married and cohabiting women has profound consequences, including straining resources, increasing healthcare challenges, and contributing to educational and gender inequalities. This study examined the factors associated with high completed fertility among married and cohabiting women aged 40–49 years in Ghana. Methods: Data for the study was sourced from the 2022 Ghana Demographic and Health Survey (GDHS). A spatial map was used to present the women's geographic variations in high completed fertility. A mixed-effect multilevel binary logistic regression analysis was performed to identify the factors associated with high completed fertility. The findings were presented as adjusted odds ratios (aOR) with a 95% confidence interval (CI). Results: The national proportion of high completed fertility among married and cohabiting women aged 40–49 years in Ghana was 52.0% [48.8, 55.2]. Women who were Ga/Dangme/Ewe by tribe [aOR = 2.32, 95% CI = 1.06, 5.08] had higher odds of high completed fertility than Akans. Women who indicated 6 + as their ideal number of children had a higher [aOR = 5.60, 95% CI = 2.90, 10.82] likelihood of high completed fertility compared to those whose ideal number of children was 0–3. Those who were using contraceptives at the time of the survey had a higher [aOR = 2.31, 95% CI = 1.17, 4.55] likelihood of high completed fertility compared to those who were not using contraceptives. Women with secondary/higher education [aOR = 0.32, 95% CI = 0.17, 0.58] had lower odds of high completed fertility than those without no formal education. Women with females as household heads [aOR = 0.56, 95% CI = 0.33, 0.95] had lower odds of high completed fertility than males. Women in Volta, Western North, Ahafo, and Bono regions had lower odds of high completed fertility compared to those living in the Northeast region, with the lowest odds among those living in the Volta region [aOR = 0.08, 95% CI = 0.02, 0.40]. Conclusion: High completed fertility is prevalent in Ghana, with more than half of married and cohabiting women having at least five or more children. The government and policymakers in Ghana should promote education for women, increase culturally sensitive family planning programs, increase access to family planning resources, address ideal family size preferences, and improve understanding of contraceptive use. [ABSTRACT FROM AUTHOR]

Background: Worldwide, the culturally and linguistically diverse (CALD) population is increasing, and is predicted to reach 405 million by 2050. The delivery of emergency care for the CALD population can be complex due to cultural, social, and language factors. The extent to which cultural, social, and contextual factors influence care delivery to patients from CALD backgrounds throughout their emergency care journey is unclear. Using a systematic approach, this review aims to map the existing evidence regarding emergency healthcare delivery for patients from CALD backgrounds and uses a social ecological framework to provide a broader perspective on cultural, social, and contextual influence on emergency care delivery. Methods: The Joanna Briggs Institute (JBI) scoping review methodology will be used to guide this review. The population is patients from CALD backgrounds who received care and emergency care clinicians who provided direct care. The concept is healthcare delivery to patients from CALD backgrounds. The context is emergency care. This review will include quantitative, qualitative, and mixed-methods studies published in English from January 1, 2012, onwards. Searches will be conducted in the databases of CINAHL (EBSCO), MEDLINE (Ovid), Embase (Elsevier), SocINDEX (EBSCO), Scopus (Elsevier), and a web search of Google Scholar. A PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) flow diagram will be used to present the search decision process. All included articles will be appraised using the Mixed Methods Appraisal Tool (MMAT). Data will be presented in tabular form and accompanied by a narrative synthesis of the literature. Discussion: Despite the increased use of emergency care service by patients from CALD backgrounds, there has been no comprehensive review of healthcare delivery to patients from CALD backgrounds in the emergency care context (ED and prehospital settings) that includes consideration of cultural, social, and contextual influences. The results of this scoping review may be used to inform future research and strategies that aim to enhance care delivery and experiences for people from CALD backgrounds who require emergency care. Systematic review registration: This scoping review has been registered in the Open Science Framework https://doi.org/10.17605/OSF.IO/HTMKQ [ABSTRACT FROM AUTHOR]

Background: Risk prediction models are routinely used to assist in clinical decision making. A small sample size for model development can compromise model performance when the model is applied to new patients. For binary outcomes, the calibration slope (CS) and the mean absolute prediction error (MAPE) are two key measures on which sample size calculations for the development of risk models have been based. CS quantifies the degree of model overfitting while MAPE assesses the accuracy of individual predictions. Methods: Recently, two formulae were proposed to calculate the sample size required, given anticipated features of the development data such as the outcome prevalence and c-statistic, to ensure that the expectation of the CS and MAPE (over repeated samples) in models fitted using MLE will meet prespecified target values. In this article, we use a simulation study to evaluate the performance of these formulae. Results: We found that both formulae work reasonably well when the anticipated model strength is not too high (c-statistic < 0.8), regardless of the outcome prevalence. However, for higher model strengths the CS formula underestimates the sample size substantially. For example, for c-statistic = 0.85 and 0.9, the sample size needed to be increased by at least 50% and 100%, respectively, to meet the target expected CS. On the other hand, the MAPE formula tends to overestimate the sample size for high model strengths. These conclusions were more pronounced for higher prevalence than for lower prevalence. Similar results were drawn when the outcome was time to event with censoring. Given these findings, we propose a simulation-based approach, implemented in the new R package 'samplesizedev', to correctly estimate the sample size even for high model strengths. The software can also calculate the variability in CS and MAPE, thus allowing for assessment of model stability. Conclusions: The calibration and MAPE formulae suggest sample sizes that are generally appropriate for use when the model strength is not too high. However, they tend to be biased for higher model strengths, which are not uncommon in clinical risk prediction studies. On those occasions, our proposed adjustments to the sample size calculations will be relevant. [ABSTRACT FROM AUTHOR]

Background: Lesotho experienced high rates of maternal (566/100,000 live births) and under-five mortality (72.9/1000 live births). A 2013 national assessment found centralized healthcare management in Ministry of Health led to fragmented, ineffective district health team management. Launched in 2014 through collaboration between the Ministry of Health and Partners In Health, Lesotho's Primary Health Care Reform (LPHCR) aimed to improve service quality and quantity by decentralizing healthcare management to the district level. We conducted a qualitative study to explore health workers' perceptions regarding the effectiveness of LPHCR in enhancing the primary health care system. Methods: We conducted 21 semi-structured key informant interviews (KII) with healthcare workers and Ministry of Health officials purposively sampled from various levels of Lesotho's health system, including the central Ministry of Health, district health management teams, health centers, and community health worker programs in four pilot districts of the LPHCR initiative. The World Health Organization's health systems building blocks framework was used to guide data collection and analysis. Interviews assessed health care workers' perspectives on the impact of the LPHCR initiative on the six-health system building blocks: service delivery, health information systems, access to essential medicines, health workforce, financing, and leadership/governance. Data were analyzed using directed content analysis. Results: Participants described benefits of decentralization, including improved efficiency in service delivery, enhanced accountability and responsiveness, increased community participation, improved data availability, and better resource allocation. Participants highlighted how the reform resulted in more efficient procurement and distribution processes and increased recognition and status in part due to the empowerment of district health management teams. However, participants also identified limited decentralization of financial decision-making and encountered barriers to successful implementation, such as staff shortages, inadequate management of the village health worker program, and a lack of clear communication regarding autonomy in utilizing and mobilizing donor funds. Conclusion: Our study findings indicate that the implementation of decentralized primary health care management in Lesotho was associated a positive impact on health system building blocks related to primary health care. However, it is crucial to address the implementation challenges identified by healthcare workers to optimize the benefits of decentralized healthcare management. [ABSTRACT FROM AUTHOR]

Background: Similar to other low and middle-income countries, Ethiopia faces limitations in using local health data for decision-making.We aimed to assess the effect of an intervention, namely the data-informed platform for health, on the culture of data-based decision making as perceived by district health office staff in Ethiopia's North Shewa Zone. Methods: By designating district health offices as 'clusters', a cluster-randomised controlled trial was implemented. Out of a total of 24 districts in the zone, 12 districts were allocated to intervention arm and the other 12 in the control group arms. In the intervention arm district health office teams were supported in four-monthly cycles of data-driven decision-making over 20 months. This support included: (a) defining problems using a health system framework; (b) reviewing data; (c) considering possible solutions; (d) value-based prioritizing; and (e) a consultative process to develop, commit to, and follow up on action plans. To measure the culture of data use for decision-making in both intervention and control arms, we interviewed 120 health management staff (5 per district office). Using a Likert scale based standard Performance of Routine Information System Management tool, the information is categorized into six domains:- evidence-based decision making, emphasis on data quality, use of information, problem solving, responsibility and motivation. After converting the Likert scale responses into percentiles, difference-in-difference methods were applied to estimate the net effect of the intervention. In intervention districts, analysis of variance was used to summarize variation by staff designation. Results: The overall decision-making culture in health management staff showed a net improvement of 13% points (95% C.I:9, 18) in intervention districts. The net effect of each of the six domains in turn was an 11% point increase (95% C.I:7, 15) on culture of evidence based decision making, a 16% point increase (95% C.I:8, 24) on emphasis on data quality, a 20% point increase (95% C.I:12, 28) on use of information, a 21% point increase (95% C.I:13, 29) on problem solving, and a 10% point increase (95% C.I:4, 16) on responsibility and motivation. In terms of variation by staff designation within intervention districts, statistically significant differences were observed only for problem solving and responsibility. Conclusion: The data-informed platform for health strategy resulted in a measurable improvement in data use and structured decision-making culture by using existing systems, namely the Performance Monitoring Team meetings. The intervention supported district health offices in identifying and solving problems through a structured process. After further research, DIPH intervention could also be applied to other health administration and facility levels. Trial registration: ClinicalTrials.gov ID: NCT05310682, Dated 25/03/ 2022. [ABSTRACT FROM AUTHOR]