Manage your Emotions!:Encouraging Parents to Engage in Introspective Analysis and Help-Seeking

In the Danish context, a new risk-preventive parent-child policy agenda has recently paved the way for new intimate support interventions that focus on parents' mentalisation capabilities, attachment patterns and their control over emotions. In this article, based on fieldwork and interviews, we show that the policy agenda has been significantly embedded and complied with in the approaches and tone adopted by visiting children’s nurses acting as frontline workers in the Danish welfare state, but also expanded beyond its initial intention and reconfigured in various ways. The article discusses the possible implications of targeting alleged emotional (dis)orientation in parents and defining emotional self-control as a central characteristic of what constitutes ‘good’ parenting. Ultimately, we argue that the current therapeutic self-help approach to parenting education in the Danish welfare state not only constitutes a psychologising of parenting; it also represents a pathologisation of everyday life in ways where more parents than before are positioned as 'troubled'

The organisation of evaluations:The influence of the ministry of finance on evaluation systems

Background:Despite increasing scholarly interest in the organisation of evaluations within different countries’ political-administrative landscapes, not much attention has hitherto been paid to the consequences of a specific institutional set-up for the function of evaluations within government.Aims and objectives:This article investigates how the organisational anchorage of policy evaluations within central administration shapes the function those evaluations primarily serve.Methods:We focus on the role of ministries of finance for coordinating countries’ evaluation systems, and study its influence in Denmark and the Netherlands through a combination of document analysis and interviews with centrally placed civil servants.Findings:Our analysis shows how the ministries of finance come to influence the evaluation activities of the whole central administration by constituting a specific economic outlook on evaluation, which (1) narrows down the applied evaluation methods and criteria; (2) inserts the ministry of finance as primary evaluation user; and hereby (3) furthers accountability rather than learning as the main function of evaluations within central administration. In both countries, the result is that the ministry of finance’s main role in the evaluation systems favours somewhat defensive qualities, where evaluations are primarily used for control and piecemeal changes in policies, rather than fundamental revisions or reflections on the appropriateness of specific policies.Discussion and conclusions:Our findings indicate that the influence of evaluation systems is not only dependent on the degree of institutional anchorage of evaluation activities, but also very much a matter of whom the evaluation systems is centred around

Reasoning with Generative AI

Based on a case study of ChatGPT-4’s ability to solve a third-semester BA exam question in Logic and Argumentation Theory, this article argues that students should be encouraged to reason alongside ChatGPT. Echoing previous findings, we confirm that while ChatGPT demonstrates impressive linguistic abilities, including skills in formalizing arguments, it often makes basic mistakes. However, these errors can be advantageous in a teaching setting focused on logic and argumentation. The article argues that, instead of viewing generative AI as a threat, teaching students critical thinking with ChatGPT can embolden them by clarifying the difference between their role and AI.</p

A Nationwide Factorial Randomized Trial of Electronic Nudges to Patients with Chronic Kidney Disease and Their General Practices for Increasing Guideline-Directed Medical Therapy:The NUDGE-CKD Trial

BACKGROUND: Many individuals with chronic kidney disease (CKD) face a considerable but modifiable risk of cardiovascular and renal outcomes because of suboptimal implementation of guideline-directed medical therapy (GDMT). We investigated whether electronic letter-based nudges delivered to individuals with CKD and their general practices could increase GDMT uptake. METHODS: This was a nationwide 2×2 factorial implementation trial with randomization at the patient and general practice level and analyzed at the patient level. All Danish adults with a hospital diagnosis of CKD and access to the official Danish electronic letter system were individually randomized at a 1:1 ratio to usual care (no letter) or to receive an electronic letter-based nudge on GDMT for CKD; general practitioners of individuals with CKD were independently randomized (1:1) to receive no letter or an electronic informational letter on GDMT. Intervention letters were delivered on August 19, 2024. Data were collected through the Danish administrative health registries. The primary end point was a filled prescription of a renin-Angiotensin system inhibitor or a sodium-glucose cotransporter 2 inhibitor within 6 months of intervention delivery. RESULTS: A total of 22 617 patients with CKD were randomized to the patient-level intervention, with 11 223 allocated to receive the electronic nudge letter and 11 394 to usual care. Separately, 1540 general practices caring for 28 069 patients with CKD were randomized to the provider-level intervention, with 774 practices (13 959 patients) allocated to the intervention and 766 practices (14 110 patients) to usual care. During follow-up, 7303 (65.1%) allocated to the patient-directed nudge had filled a prescription for a renin-Angiotensin system inhibitor or sodium-glucose cotransporter 2 inhibitor compared with 7505 (65.9%) in usual care (difference,-0.79 percentage points [95% CI,-2.03 to 0.45]; P=0.21). Among patients of practices receiving the provider-directed letter, 8921 (63.9%) filled a prescription for a renin-Angiotensin system inhibitor or sodium-glucose cotransporter 2 inhibitor compared with 9086 (64.4%) in the usual care group (difference,-0.49 percentage points [95% CI,-1.64 to 0.66]; P=0.41). No interaction was observed between the two interventions (Pinteraction=0.85). CONCLUSIONS: In this nationwide pragmatic, 2×2 factorial implementation trial, electronic letter-based nudges on GDMT delivered to patients with CKD or their general practice did not increase the uptake of a renin-Angiotensin system inhibitor or sodium-glucose cotransporter 2 inhibitor as compared with usual care. REGISTRATION: URL: https://www.clinicaltrials.gov; Unique identifier: NCT06300086.</p

Evaluating Continuous Glucose Monitoring After Total Pancreatectomy With or Without Islet Autotransplantation

Objectives This scoping review aims to provide evidence synthesis of continuous glucose monitoring (CGM) and insulin pump use after undergone total pancreatectomy (TP) with or without islet autotransplantation (TPIAT).Methods The review was conducted adhering to PRISMA-ScR (Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews) checklist.Results Fifteen studies including 147 patients (adult n = 71/pediatric n = 76) reported on CGM use post-TP (n = 42) and TPIAT (n = 105). Four were randomized controlled trials and 10 observational studies. Six studies evaluated CGM use in the perioperative and 6 in the immediate postoperative period (n = 8) with variable follow-up (14 hours to 20 months). CGM was used as a stand-alone device (8 studies), which allowed assessment of glycemic variability (n=5) and detection of hypoglycemia (n = 1), resulting in lower glucose levels (n = 1). Six studies evaluated insulin pump with CGM with reduction in postoperative mean glucose (n = 4) and hypoglycemic episodes (n = 2). No patient-reported outcome measures (PROMs) or quality of life (QoL) measures were reported.Conclusions CGM can be used following TP for glucose monitoring and/or linked with insulin pump device in the perioperative period with improved glycemic control. However, the data are limited by short follow-up and lack of PROMs and QoL measures

Identifying and Visualizing Key Scenarios in a Serverless Edge-Node System

This paper addresses the challenges of monitoring and visualizing cognitive cloud continuum environments by making use of serverless edge nodes. The distributed nature of such nodes has the potential of granting quick and lightweight monitoring capabilities, once relevant challenges are solved, such as consistent monitoring and logging. We focus on recognizing and visualizing a set of key scenarios over serverless edge devices on a cluster. Our solution leverages system logs and metrics collected on the cluster, which are aggregated, analyzed and visualized on a smart dashboard in real-time to produce a comprehensive view of the system’s behavior. The approached is experimented with on a serverless edge-node system integrated in Kubernetes, paired with Loki and Prometheus for log and metrics collection and aggregation, and Grafana for visualization. Our implementation demonstrates the system’s ability to recognize key scenarios such as normal state, overload state, error handling, and load balancing, thereby enhancing the ability of system administrators and developers to oversee and optimize the performance of serverless edge environments. The insights provided by our research will support the development of more robust, efficient, and adaptive monitoring solutions, ultimately raising awareness of the potential of the Cognitive Cloud Continuum. Index Terms— Edge Computing, Serverless Computing, Kubernetes, Dashboard, Workloads

Synthesizing Accurate Relational Data under Differential Privacy

Medical data is sensitive personal data which, according to GDPR and HIPAA, necessitates regulations concerning their use. Anonymizing this data prior to research would allow for broader access, due to a lower sensitivity. Privacy-aware data synthesis has been proposed as a solution. However, current algorithms face difficulties in synthesizing medical data while maintaining privacy and utility. This is due to the structure of medical data which consists of multiple interlinked tables with high dimensional columns containing sequential aspects of the patient trajectory. The resulting number of correlations is intractable to model naively and, if relational correlations are not accounted for, the resulting data has poor utility (e.g., leads to invalid patient trajectories). In this paper, we present MARE, a relational synthesis algorithm which focuses on a set of core correlations found in relational data while pruning others. The resulting lower computational complexity allows MARE to produce accurate relational data. We showcase that MARE can synthesize multiple medical datasets, which contain sequential aspects, while maintaining utility in form of inter-table and inter-row correlations and privacy guarantees