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The association of fatigue and cognitive complaints with work-related outcomes and cancer-related anxiety among employees 2–10 years after cancer diagnosis
No full textThis study investigated the association of fatigue and cognitive complaints among employees post-cancer diagnosis, with work-related outcomes, and moderation by cancer-related anxiety. A survey was carried out among workers 2–10 years after cancer diagnosis. Employees without cancer recurrence or metastases were selected (N = 566). Self-reported fatigue and cognitive complaints were classified into three groups. ANOVA’s and regression analyses were used, controlling for age. Group 1 (cognitive complaints, n = 25, 4.4%), group 2 (fatigue, n = 205, 36.2%), and group 3 (cognitive complaints and fatigue, n = 211, 37.3%) were associated with higher burnout complaints and lower work engagement, and group 2 and 3 with lower work ability. Cancer-related anxiety positively moderated the association of group 3 with higher burnout complaints. Employees with both fatigue and cognitive complaints report less favorable work functioning. Cancer-related anxiety needs attention in the context of burnout complaints.</p
Validity assessment of early retirement claimants:Symptom overreporting on the Beck Depression Inventory–II
No full textObjectives: The Beck Depression Inventory-II (BDI-II) is a commonly used clinical measure; however, it contains no method to assess validity of self-report. The primary objective of this research was to examine the possibility of cut scores on the BDI-II indicating possible invalid symptom report in forensic neuropsychological evaluations. Secondary objectives were to explore the utility of education specific cut scores and the effects of the criterion for invalid symptom report. Methods: Two hundred and seventeen early retirement claimants (age range 19–64 years) presenting for forensic neuropsychological examination were considered for this study. Invalid symptom report was determined based on two independent self-report symptom validity tests. Further, all individuals completed the BDI-II as part of their routine assessment battery. Results: Individuals with invalid symptom report (30.9%) showed significantly higher BDI-II scores compared to individuals passing symptom validity assessment. ROC analysis supports the utility of the BDI-II to differentiate valid from invalid symptom report, AUC = 0.822, SE = 0.032, p <.001, 95%-CI = 0.760–0.884. A BDI-II cut score of 38 points reached a desired level of 0.90 specificity with 0.58 sensitivity. Secondary analysis indicated that the recommended cut score may vary depending on the educational level of the examinee. Further, results seem to be largely robust against the chosen criterion for invalid symptom report. Conclusion: The BDI-II appears to be a useful adjunct embedded validity indicator in forensic neuropsychological evaluations.</p
Exploring the concept of a responsive curriculum in teacher education from the perspective of students and teacher educators
No full textEconomic, social and environmental changes place high demands on teachers and teacher education. Consequently, teacher education is challenged to design curricula that respond to and anticipate changes. Curricula are value-driven and even though part of these values might be constant, the relative importance of values and the values themselves may also be subject to change since society is changing rapidly. In vocational education, responsive curriculum development refers to balancing the needs of students, workplaces and society. Vocational education qualifies students for coping with unpredictable situations and complex problems in occupational practice. As in vocational education, teacher education also prepares students for unpredictability and complexity and thus, we adopt the concept of responsiveness from vocational education to explore teacher education. This study explores the concept of a responsive curriculum for teacher education using a qualitative approach. Interviews were conducted with the key actors, namely students and teacher educators, in the context of Dutch teacher education. An initial framework, consisting of three responsive dimensions and five designable elements, was used to guide the interviews and analyse the data. The data revealed 14 relevant themes to identify how a teacher education curriculum can be responsive to changes in society, to a variety of schools and to student diversity. The developed framework can serve as a conceptual frame to study the enactment of responsive curriculum designs. Also, it can support practitioners when designing responsive curricula.</p
Social entrepreneurial ecosystems in Euroregions
No full textPurpose: The purpose of this paper is to extend the knowledge of social entrepreneurial ecosystems and test their effect on social entrepreneurial activity in a cross-border context. Design/methodology/approach: The current research used the fuzzy set Qualitative Comparative Analysis method on a sample of 4,357 cross-border cooperation (CBC) projects implemented between 2014 and 2020, spread over 40 Euroregions. Findings: Single ecosystem elements can be sufficient conditions but with a limited effect on cross-border social entrepreneurship. Configurations of ecosystem elements can be necessary conditions with synergetic effects. A geographical pattern was identified in the spread of configurations across Europe. Research limitations/implications: Geographical, quantitative and project data constraints exist. The authors call for research into synergies between ecosystem elements in cross-border contexts and ecosystem patterns across Europe. Practical implications: Policymakers, their cross-border counterparts and Euroregions could coordinate their efforts to improve ecosystems’ impact and involve social entrepreneurs to scale impact in neighboring countries. Social implications: Involving social entrepreneurs in CBC projects will show how social impact in one country can be valuable for solving issues in the neighboring country. This will increase the valuation of innovative solutions, create opportunities for scaling social impact and contribute to the European (EU) Cohesion Policy. Originality/value: The study uses a novel approach by investigating the effect of social entrepreneurial ecosystems in Euroregions on social entrepreneurial activity in a cross-border context. The study shows that the impact of social entrepreneurial ecosystems does not stop at the country’s borders.</p
The daily reciprocal associations between electroencephalography measured sleep and affect
No full textQuantifying time-dependent flood resilience index in a densely populated urban environment in Manado, Indonesia
No full textFlooding poses significant risks, with severe physical, economic, and psychological impacts. Efforts to mitigate flood risk include improving predictability, developing flood control structures, and enhancing community resilience. Flood resilience indices (FRIs) quantify a community's characteristics regarding prevention, preparedness, response, and recovery aspects around flood events. This study uses a time-dependent FRI in nine wards in a densely populated urban environment at the flood-vulnerable riverbank communities in Singkil Subdistrict, Manado, Indonesia. The FRI considers the temporal flood event propagation, physical vulnerability, and demographics reflecting the community's resilience to flood. The time-dependent FRI is quantified and applied for three flood return periods, 2, 20, and 100 years. Flood discharge was simulated using HEC-HMS, with results input into HEC-RAS for flood scenario modeling. FRI was then assessed using HEC-RAS flood propagation results for the event phase and national socio-economic data for the flood recovery phase. The study captures the community's immediate responses and near-term adaptations, where resilience differs by location and fluctuates across the flood scenarios. Most of the wards have the characteristics of rapid FRI decrease caused by the sudden onset of the incoming flood and a more gradual recovery of the FRI. Comparison between the three return periods shows slight FRI curve differences, indicating that the relatively high probability of 2-year floods is already significantly damaging the community. These findings prompt a call for location-specific, effective and time-sensitive flood mitigation strategies, especially in densely populated vulnerable wards in urban environments.</p
Improving operational decision-making through decision mining - utilizing method engineering for the creation of a decision mining method
No full textContext: This study addresses the challenge of enhancing the efficiency and agility of decision support software supporting both operational decision-making and software production teams developing decision support software. It centers on creating a method that assists in mining decisions, checking decisions on conformance, and improving decisions, which supports software production teams in developing decision support software. Objective: The primary objective is to develop an explicit, clear, and structured approach for discovering, checking, and improving decisions using decision support software. The study aims to create a blueprint for software production teams to develop Decision Mining (DM) software, in line with recent advancements in the field. Additionally, it seeks to provide a consolidated, methodical overview of activities and deliverables in the DM research field. Method: The research employs method engineering principles to construct a method for DM that leverages the existing body of knowledge by utilizing a Systematic Literature Review (SLR). The study focuses on developing individual building blocks and method fragments incorporated into seven DM scenarios. Results: The study led to the creation of a Decision Mining Method (DMM), which includes 138 method fragments grouped into eleven categories. These fragments were systematically merged to form a comprehensive DMM. The method encapsulates the complexity of DM and provides practical applicability in real-world scenarios, highlighted by the identification of seven distinct scenarios in DM phases. The study also conducted the first SLR in the DM field, providing a comprehensive overview of current practices and outcomes. Conclusion: The study helps in advancing the DM field by creating a structured approach and a comprehensive method for DM, aligning with recent developments in the field. It successfully aggregated the fragmented DM domain into a cohesive methodological overview, crucial for future research. The study also lays out a detailed agenda for future research, focusing on expanding and validating the DMM, incorporating cross-disciplinary insights, and addressing the challenges in machine learning within DM. The future research directions aim to refine and broaden the applicability of the DMM, ensuring its effectiveness in diverse practical contexts and contributing to a more holistic and comprehensive approach to decision mining.</p
Abstract Dialectical Frameworks are Boolean Networks
No full textAbstract dialectical frameworks are a unifying model of formal argumentation, where argumentative relations between arguments are represented by assigning acceptance conditions to atomic arguments. Their generality allows them to cover a number of different approaches with varying forms of representing the argumentation structure. Boolean regulatory networks are used to model the dynamics of complex biological processes, taking into account the interactions of biological compounds, such as proteins or genes. These models have proven highly useful for comprehending such biological processes, allowing to reproduce known behaviour and testing new hypotheses and predictions in silico, for example in the context of new medical treatments. While both these approaches stem from entirely different communities, it turns out that there are striking similarities in their appearence. In this paper, we study the relation between these two formalisms revealing their communalities as well as their differences, and introducing a correspondence that allows to establish novel results for the individual formalisms.</p
Reasoning about group responsibility for exceeding risk threshold in one-shot games
No full textTracing and analysing the responsibility for unsafe outcomes of actors' decisions in multi-agent settings have been studied in recent years. These studies often focus on deterministic scenarios and assume that the unsafe outcomes for which actors can be held responsible are actually realized. This paper considers a broader notion of responsibility where unsafe outcomes are not necessarily realized, but their probabilities are unacceptably high. We present a logic combining strategic, probabilistic and temporal primitives designed to express concepts such as the risk of an undesirable outcome and being responsible for exceeding a risk threshold in one-shot games. We demonstrate that the proposed logic is (weakly) complete, decidable and has an efficient model-checking procedure. Finally, we define a probabilistic notion of responsibility and study its formal properties in the proposed logic setting.</p
Human centred explainable AI decision-making in healthcare
No full textHuman-centred AI (HCAI1) implies building AI systems in a manner that comprehends human aims, needs, and expectations by assisting, interacting, and collaborating with humans. Further focusing on explainable AI (XAI2) allows to gather insight in the data, reasoning, and decisions made by the AI systems facilitating human understanding, trust, and contributing to identifying issues like errors and bias. While current XAI approaches mainly have a technical focus, to be able to understand the context and human dynamics, a transdisciplinary perspective and a socio-technical approach is necessary. This fact is critical in the healthcare domain as various risks could imply serious consequences on both the safety of human life and medical devices.A reflective ethical and socio-technical perspective, where technical advancements and human factors co-evolve, is called human-centred explainable AI (HCXAI3). This perspective sets humans at the centre of AI design with a holistic understanding of values, interpersonal dynamics, and the socially situated nature of AI systems. In the healthcare domain, to the best of our knowledge, limited knowledge exists on applying HCXAI, the ethical risks are unknown, and it is unclear which explainability elements are needed in decision-making to closely mimic human decision-making. Moreover, different stakeholders have different explanation needs, thus HCXAI could be a solution to focus on humane ethical decision-making instead of pure technical choices.To tackle this knowledge gap, this article aims to design an actionable HCXAI ethical framework adopting a transdisciplinary approach that merges academic and practitioner knowledge and expertise from the AI, XAI, HCXAI, design science, and healthcare domains. To demonstrate the applicability of the proposed actionable framework in real scenarios and settings while reflecting on human decision-making, two use cases are considered. The first one is on AI-based interpretation of MRI scans and the second one on the application of smart flooring