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Negotiating the caring role and carer identity over time: ‘living well’ and the longitudinal narratives of family members of people with dementia from the IDEAL cohort
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IDEAL data were deposited with the UK data archive in April 2020. Details of how to access the data can be found at https://reshare.ukdataservice.ac.uk/854317/.Longitudinal studies can provide insights into how family members negotiate the caring role and carer identity over time. The analyses of the longitudinal, qualitative interviews on ‘living well’ with dementia from the IDEAL cohort study aimed to identify the shifting, embedded narratives of family members of people with dementia as they negotiated the caring role and carer identity over time. Twenty semi-structured, qualitative interviews were conducted with family members of people with dementia and 14 were repeated one year later; these interviews were analysed using cross-sectional and longitudinal thematic and structural narrative analyses. Longitudinal, interrelated themes, including the care needs and decline of the person with dementia, relationship change and variable service support, framed the narrative types of family members. Six shifting narratives, apparent as dominant and secondary narrative types, characterized negotiating the caring role over time: absent/normalizing, active role adoption / carer identity, resistance, acceptance and resignation, hypervigilance/submergence and role entrapment, and foreshadowed future. The presence or absence of a carer identity was also evident from interviewees’ accounts, although, even where family members were overburdened by the caring role, they did not necessarily express a carer identity. Rather than considering transition into a carer identity, hearing different narratives within the caring role is important to understand how family members experience caring, whether they see themselves as ‘carers’, and when and how they need support. Timely and continued post-diagnostic support, where different caring narratives are recognized, is needed, as well as international initiatives for carer identification.‘Improving the experience of Dementia and Enhancing Active Life: living well with dementia. The IDEAL study’ was funded jointly by the Economic and Social Research Council (ESRC) and the NIHR through grant ES/L001853/2. Investigators: L. Clare, I. R. Jones, C. Victor, J. V. Hindle, R. W. Jones, M. Knapp, M. Kopelman, R. Litherland, A. Martyr, F. E. Matthews, R. G. Morris, S. M. Nelis, J. A. Pickett, C. Quinn, J. Rusted and J. Thom. The ESRC is part of UK Research and Innovation (UKRI). ‘Improving the experience of Dementia and Enhancing Active Life: a longitudinal perspective on living well with dementia. The IDEAL-2 study’ is funded by the Alzheimer’s Society, grant number 348, AS-PR2-16-001. Investigators: L. Clare, I. R. Jones, C. Victor, C. Ballard, A. Hillman, J. V. Hindle, J. Hughes, R. W. Jones, M. Knapp, R. Litherland, A. Martyr, F. E. Matthews, R. G. Morris, S. M. Nelis, C. Quinn and J. Rusted. Linda Clare acknowledges support for this independent research report from the NIHR Applied Research Collaboration South-West Peninsula. The support of ESRC, the NIHR and the Alzheimer’s Society is gratefully acknowledged
How do we know if an intelligence analytic product is good?
Get PDFHow can an intelligence analysis production organization determine whether analysis is successful? This article explores the three methods that intelligence communities have applied to determine whether analysis is good: Did the analysis meet analytic tradecraft standards? Were the assessments accurate? And did the product make a difference with a decision maker? Unfortunately, none of those evaluation methods is perfect and all three leave questions. It can be just as difficult to determine whether analysis is good as it is to produce intelligence analysis itself. However, all three methods can identify products that approach the ideal
Editorial: Tuberculosis: host immunity, diagnostics and therapeutics
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The author(s) declare that no Generative AI was used in the creation of this manuscript.Editorial on the Research Topic
Tuberculosis: host immunity, diagnostics and therapeutics
Tuberculosis (TB) remains one of the world’s most significant infectious diseases, with approximately 8.7 million new cases of active disease and 1.4 million deaths annually. A third of the world’s population is estimated to harbour latent TB infection (LTBI), creating a vast reservoir for potential disease dissemination and reactivation. The complexity of host-pathogen interaction in TB, particularly during early infection and latency, continues to challenge our ability to develop effective diagnostics, vaccines, and therapeutics.
This Research Topic aimed to attract studies that would enhance our understanding of host immunity against TB and its role in both pathogenesis and protection. The submitted papers represent diverse approaches to understanding TB, from biomarker discovery and drug resistance surveillance to host genetic factors and immune cell responses in both human and bovine TB.The author(s) declare that financial support was received for the research, authorship, and/or publication of this article. UK acknowledges UAEU grants 12F061, 12R278 and 12R273
Current transformer saturation detection by cross-correlation with independent target signal
Get PDF...The saturation of current transformers (CTs) leads to distortion in secondary current, potentially causing malfunction in protective relays within power systems. Detecting the saturated portions in the measured signal and reconstructing the primary reference current are essential to prevent relay malfunctions and ensure sensitivity during faults. Existing methods in the literature still face challenges in improving accuracy, especially in the presence of noise in the measured signal. The proposed method in this paper is more robust under noisy conditions compared to existing signal processing-based methods. It relies on a cross-correlation algorithm that uses an independent target signal. This method is parameter-less and independent of the CT’s specifications. Additionally, no extra hardware equipment is required. The proposed method identifies the saturated portions in the measured secondary current in each cycle, enabling the reconstruction of the saturated current to obtain the reference primary current. A test system has been simulated, and the data are processed using MATLAB. Various test cases are executed, and the results confirm that the proposed method is highly effective in providing fast and accurate detection of CT saturation, with improved robustness against noise.The authors extend their appreciation to the Deanship of Scientific Research at Northern Border University, Arar, KSA for funding this research work through the project number “NBU-FPEJ-2025–1250-01
Implications of assisted dying for nursing practice
No full textAuthor note: This article is based on a presentation delivered at the 24th International Nursing Ethics Conference, Brunel University of London on the 30th August 2024.This conceptual paper considers the practice implications of assisted dying for contemporary nursing practice within the United Kingdom in response to the publication of a parliamentary report leading to a private members’ bill that will form the basis of a debate and possible change in legislation. A recurring theme within the nursing research is how nurses should respond to patients expressing an interest or making a request for assisted dying. This paper explores contemporary evidence and argues that the procedure of assisted dying is a complex (manifold) and puzzling (paradoxical) practice. The UK nursing profession may replicate recent healthcare catastrophes if the response to a proposal for assisted dying is based on a technical-rational stance, or if nurses merely coalesce around a single determinant such as patient autonomy. The paper presents two nursing communicative interventions that seek to address how to respond to a patient request for an assisted death that foregrounds the preferences and personhood of the patient whilst providing opportunities for enquiry-based approaches to enhance nursing responses to intractable suffering.The author(s) received no financial support for the research, authorship, and/or publication of this article
Performance Analysis of IRS-Assisted Multi-Cell Data and Energy Integrated Networks
Get PDFIntelligent reflecting surface (IRS) can significantly enhance the performance of data and energy integrated networks (DEIN) by adjusting its amplitude and/or phase. However, there is a lack of comprehensive performance analysis model for realistic DEIN where multiple cells exist rather than only one cell as assumed by most existing work. In this paper, we consider an IRS-assisted multi-cell DEIN. Specifically, in the downlink wireless energy transfer (WET) stage, the hybrid access point (HAP) in each cell broadcasts radio frequency (RF) energy signals to edge user equipments (UEs). Subsequently, during the uplink wireless information transfer (WIT) stage, the edge UEs employ the harvested energy to send their information to the HAP. We first represent the statistical characteristics of the signal-to-interference-plus-noise ratio (SINR) at the edge UE. Then, we derive the closed-form expressions for outage probability, ergodic rate and average symbol error probability of the edge UE in the typical cell. To gain more insights, we obtain the minimum required number of reflection elements and a sub-optimal solution for time allocation coefficients. Finally, extensive numerical results are provided to validate the correctness of the theoretical results
Decision Frameworks for Assessing Cost-Effectiveness Given Previous Nonoptimal Decisions
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Economic evaluations identify the best course of action by a decision maker with respect to the level of health within the overall population. Traditionally, they identify 1 optimal treatment choice. In many jurisdictions, multiple technologies can be covered for the same heterogeneous patient population, which limits the applicability of this framework for directly determining whether a new technology should be covered. This article explores the impact of different decision frameworks within this context.
Methods:
Three alternate decision frameworks were considered: the traditional normative framework in which only the optimal technology will be covered (normative); a commonly adopted framework in which the new technology is recommended for reimbursement only if it is optimal, with coverage of other technologies remaining as before (current); and a framework that assesses specifically whether coverage of the new technology is optimal, incorporating previous reimbursement decisions and the market share of current technologies (positivist). The implications of the frameworks were assessed using a simulated probabilistic Markov model for a chronic progressive condition.
Results:
Results illustrate how the different frameworks can lead to different reimbursement recommendations. This in turn produces differences in population health effects and the resultant price reductions required for covering the new technology.
Conclusion:
By covering only the optimal treatment option, decision makers can maximize the level of health across a population. If decision makers are unwilling to defund technologies, however, the second best option of adopting the positivist framework has the greatest relevance with respect to deciding whether a new technology should be covered.The authors received no financial support for the research, authorship, and/or publication of this article
Transforming Ghana's ASM industry: The intersection of ‘mining schemes’ and stakeholder collaboration
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No data was used for the research described in the article.Weak institutional frameworks related to artisanal and small-scale mining (ASM) operations have exposed many mineral-rich countries to negative environmental consequences. In Ghana, for example, mining-related environmental challenges led to a total ban on ASM activities in 2017. In light of this, the government of Ghana launched a programme dubbed the ‘Community Mining Scheme’ (CMS), premised on multi-stakeholder cooperation, as an alternative to illegal mining. Recently, however, the new (NDC led) government has disbanded the scheme, proposing to replace it with a new scheme – mining cooperatives – which are also expected to be operationalised by local mining communities and other stakeholders. Thus, this study employs a stakeholder analysis framework to examine the roles and agency of the various stakeholders expected to operationalise the framework and structure of the new scheme. We delineate ways by which mining authorities can tap into the synergies of the various stakeholders in order to achieve sustainable mining practices. We conclude by encouraging future research to go further to place the CMS discussion more accurately into the context of how far the project grew, and possibly explore the challenges that confronted the project, so as to provide insights that could either help reshape policy or refine ideas about the new ‘mining cooperatives’ scheme
Care of Children with Complex Needs in Low-Income Families
No full textThis chapter provides an overview of key ethical considerations within the care of children from an interprofessional perspective. We first explore the importance and history of ethics within child health, focusing on how poverty impacts on child health and social care. We provide a composite story relating to ‘The Wilson family’ of two parents and two children with complex needs living in insecure accommodation with unpredictable incomes during the UK's Cost-of-Living Crisis. We consider the competing demands on the family to provide adequate food and housing, and the interprofessional care available to support them. We introduce the concept of ‘utilitarianism’: a philosophical approach which views that the morally right action is the action that produces the most good. We then consider the applications and ethical tensions of viewing childcare issues through a utilitarianism lens. We explore the differences and tensions of care in children between public health ethics and individual choice perspectives. This chapter concludes with an epilogue to the aforementioned story and reflective learning points
Mode-Based Classifier: A Robust and Flexible Discriminant Analysis for High-Dimensional Data
Get PDFThis file available on this institutional repository is a preprint. It has not been certified by peer review. It is freely available at http://www3.stat.sinica.edu.tw/ss_newpaper/SS-2023-0014_na.pdf.Supplementary Materials: In the supplementary materials, we present additional results for simulation examples and real data analysis, and provide the technical results of Theorems 1-3.High-dimensional classification is both challenging and of interest in numerous applications.
Componentwise distance-based classifiers, which utilize partial information with known categories,
such as mean, median and quantiles, provide a convenient way. However, when the input features are
heavy-tailed or contain outliers, performance of the centroid classifier can be poor. Beyond that, it
frequently occurs that a population consists of two or more subpopulations, the mean, median and
quantiles in this scenario fail to capture such a structure that can be instead preserved by mode,
which is an appealing measure of considerable significance but might be neglected. This paper thus
introduces and investigates componentwise mode-based classifiers that can reveal important structures
missed by existing distance-based classifiers. We explore several strategies for defining the family of
mode-based classifiers, including the unimodal classifiers, the multimodal classifier and the quantilemode
classifier. The unimodal classifiers are proposed based on componentwise unimodal distance
and kernel mode estimation, and the multimodal classifier is constructed by identifying all the local
modes of a distribution according to a novel introduced algorithm. We establish the asymptotic
properties of these methods and demonstrate through simulation studies and three real datasets that
the mode-based classifiers compare favorably to the current state-of-art methods.The research of W. Xiong was supported in part by NSFC grants 12001101 and the Fundamental Research Funds for the Central Universities in UIBE CXTD14-05
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