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Each year, a significant number of smartphones are retired, yet retained by consumers. These hibernating smartphones have the reuse potential for another lifecycle. Nonetheless, they often stay in storage for a long time and may ultimately face inadequate recovery. This study explores consumers' perceptions regarding the value of hibernating smartphones over time. It examines the influence of factors such as the duration of smartphone storage and monetary incentives on users' decision-making regarding the End-of-Hibernation (EoH). The findings demonstrate that, on average, participants perceive the value of a newly retired smartphone to be 28% higher than its market value. This perceived value increases to 83% after three years since the smartphone's retirement. Participants' tendency to keep a hibernating smartphone increases as the gap between the monetary incentive and their perceived value of the device increases. Conversely, the longer the smartphone stays in hibernation, the less inclined users are to keep it., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Purpose: To identify Missed Nursing Care (MNC) and related factors, as well as analyze the influence of nurses' decision-making and personality traits on MNC in two Portuguese hospitals dedicated to cancer care., Methods: A cross-sectional, multicentric, descriptive-correlational study was conducted using a convenience sample of 298 nurses working in two hospitals dedicated to cancer care. Data were collected in the first semester of 2023 using a questionnaire that included sociodemographic and professional questions and the Portuguese versions of the MISSCARE Survey, the Nursing Decision-Making Instrument (NDMI-PT), and the Ten-Item Personality Inventory (TIPI-P)., Results: Nurses missed care occasionally, namely in the dimensions related to Patient empowerment/autonomy care and Efficacy of feeding and medication. Staffing, Patient volume and acuity, and Management and organization were moderate to significant reasons for MNC. The flexible decision-making style was predominant (81.5%). The most prevalent personality traits were Conscientiousness, Agreeableness, and Openness to experience. Significant correlations were found between the four stages of the decision-making process and the personality traits and several dimensions of MNC. Data collection to assess a patient's condition was negatively correlated with Team communication and Material resources. Similarly, the Emotional stability trait was negatively correlated with Team communication and Patient volume and acuity., Conclusions: This study identified MNC and factors that can influence the quality of care. It is crucial to promote nurses' training and specialization within healthcare teams, with a particular focus on enhancing some of their personality traits to make them more effective and efficient therapeutic agents., Competing Interests: Declaration of competing interest The authors declare that there are no conficts of interest regarding the publication of this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Decision confidence plays a critical role in humans' ability to make adaptive decisions in a noisy perceptual world. Despite its importance, there is currently little consensus about the computations underlying confidence judgements in perceptual decisions. To better understand these mechanisms, we addressed the extent to which confidence is informed by a naturalistic prior distribution. Contrary to previous research, we did not require participants to internalise parameters of an arbitrary prior distribution. We instead used a novel psychophysical paradigm leveraging probability distributions of low-level image features in natural scenes, which are well-known to influence perception. Participants reported the subjective upright of naturalistic image patches, targets, and then reported their confidence in their orientation responses. We used computational modelling to relate the statistics of the low-level features in the targets to the average distribution of these features across many naturalistic images, a prior. Our results showed that participants' perceptual and importantly, their confidence judgments aligned with an internalised prior for image statistics. Overall, our study highlights the importance of naturalistic task designs that capitalise on existing, long-term priors to further understand the computational basis of confidence., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2025. Published by Elsevier Inc.)

Background: Surrogate decision-makers play a key role in determining whether end-of-life patients receive hospice care. There is a need to better understand families' experiences of surrogate decision-making in hospice care for end-of-life patients to provide a basis for developing targeted interventions, such as decision support tools or counseling, to help family members navigate the decision-making process., Aim: The aim was to analyze and synthesize global qualitative data on family members' experiences of surrogate decision-making regarding whether to receive hospice care for end-of-life patients., Design: This was a systematic review of qualitative studies., Data Sources: The PubMed, Web of Science, Cochrane Library, Embase, Cumulated Index to Nursing and Allied Health Literature, Chinese Biomedical Literature Service System, China National Knowledge Infrastructure, WanFang and China Science and Technology Journal databases were searched from inception to September 2024. Studies related to family members making surrogate decisions about whether to receive hospice care for end-of-life patients were included., Review Methods: This review was guided by the Joanna Briggs Institute Manual for Systematic reviews of qualitative evidence. Two reviewers independently screened the studies and extracted the data. The eligible studies were assessed via the Joanna Briggs Institute critical appraisal instrument for qualitative research. Thematic synthesis was guided by the method developed by Thomas and Harden., Results: A total of nine studies were included. The synthesis of qualitative data resulted in three themes: (1) Decision motivation between rationality and emotion. The reasons surrogate decision-makers considered hospice care for patients involved multiple aspects and were a result of both objective and subjective factors. (2) Decision preparation stemmed from knowledge and experience. A knowledge-based foundation and experiential grounding were needed to ensure that surrogate decision-makers make informed decision. (3) Decision reflection through looking back and forward. Surrogate decision-makers expressed satisfaction with the decision to choose hospice care for patients, coupled with serious consideration of personal future end-of-life decisions., Conclusion: Determining whether patients receive hospice care at end of life is complex for family members. This process begins with the coexistence of rational and emotional motives for decision-making, involves preparation for decision-making through the acquisition of knowledge and experience about hospice care, and culminates in reflection on the entire decision-making process. These findings underscore the importance of providing sufficient informational and emotional support to family decision-makers, which can improve decision-making and promote more compassionate end-of-life care. Future research should focus on developing effective strategies to strengthen these support systems., Study Registration: A protocol was registered on the PROSPERO (CRD42024526197)., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Ltd.)

Objective: Decision-making is important in user-involved maternity care and patient experience instruments Mothers Autonomy in Decision Making scale (MADM) and Mothers on Respect index (MORi) are used internationally to measure the user involvement quality and users' experiences of autonomy and respect. This study aimed to translate and qualitatively adapt the original MADM and MORi instruments to the Danish language and culture., Methods: A forward and backward translation using a standard guideline. Subsequently, qualitative interviews to refine the translation and cultural adaptation by pilot testing the scales., Results: The translation process showed cultural differences linked to linguistic variations between Danish and English. Cognitive interviews with 14 diverse pregnant women revealed challenges in women's understanding of decision-making in maternity care. Changes in wording and assisting descriptive texts were made. Further, the order of the MADM items was changed to improve the understanding of decision-making., Discussion: Primarily, the discussion concerns how decision-making can be understood in the context of maternity care and why women's understanding of decision-making in Danish maternity care in the MADM scale items was challenged., Conclusion: The qualitative pilot test using cognitive interviews after translation of the instruments was a valuable method for cultural adaptation providing important knowledge on women's understanding and perceptions of item contents. The cognitive interviews provided a comprehensive understanding of decision-making and contributed to a thoroughly worked Danish version of the MADM and MORi instruments., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Ltd.)

The purpose of this study is to evaluate the readiness of European inland transport companies for the European Green Deal by analyzing the causal relationships between key factors essential for EGD implementation. The research identifies six critical factors: Investment in Green Technologies, Policy Alignment and Compliance, Stakeholder Collaboration, Resource Management, Employee Training and Engagement, and Emission Reduction Initiatives. This research offers the first integrated evaluation of EGD readiness utilizing a combination of fuzzy-DEMATEL, multiple regression analysis, and Structural Equation Modeling aimed at uncovering systemic interactions among the factors in the system. The study revealed Resource Management and Employee Training as significant drivers in enhancing the readiness, highlighting the role of human capital and resource optimization in environmental sustainability. Expert panel, consisting of 19 industry representatives selected through purposive sampling, provided insights on the effective relationships which offer practical strategies for managers to prioritize resource management and employee engagement to achieve Green Deal compliance and guiding more strategic and efficient allocation of resources to enhance alignment with European Green Deal stipulations., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2025 Elsevier Ltd. All rights reserved.)

This study represents the first exploration of Large Language Models (LLMs) in environmental decision-making, examining their potential benefits and limitations. To address environmental issues, we propose and compare two generalizable frameworks: an LLMs-assisted framework that leverages LLMs to augment human expertise and coding in traditional decision workflows, and an LLMs-driven framework that aims to automate optimization. Through a water engineering case study focusing on PFAS control, where Environmental Fluid Dynamics Code (EFDC) was used for water environment simulation, we illustrate how to instantiate these frameworks and assess their performance. The case study reveals generalizable insights about these frameworks. Results indicate that both frameworks can contribute to environmental decision-making optimization to varying degrees, though their applicability differs significantly when facing complex decision scenarios. The LLMs-assisted framework, which effectively regulates flow rates and achieves higher PFAS interception, demonstrates how AI can enhance human decision-making while preserving the essential role of domain expertise and professional judgment. In contrast, the LLMs-driven framework faces challenges in handling complex parameter optimization tasks due to constraints such as context window and maximum output length. The findings emphasize the advantages of integrating Artificial Intelligence (AI) with conventional environmental modeling and management practices. This work confirms a crucial principle: LLMs should enhance rather than replace human expertise, with the ultimate responsibility for environmental decisions remaining with humans. The originality of this research lies in its innovative methodological approach, which leverages process design and prompt engineering to integrate cutting-edge AI with conventional environmental models, establishing a foundation for responsible human-AI collaboration in environmental decision-making. While examining current strengths and limitations, this framework robustly generates optimized environmental decision strategies, marking a new exploration in the field., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2025 Elsevier Ltd. All rights reserved.)

Background: A variety of cognitive biases are known to compromise ethical deliberation and decision-making processes. However, little is known about their role in clinical ethics supports (CES)., Methods: We searched five electronic databases (Pubmed, PsychINFO, the Web of Science, CINAHL, and Medline) to identify articles describing cognitive bias in the context of committees that deliberate on ethical issues concerning patients, at all levels of care. We charted the data from the retrieved articles including the authors and year of publication, title, CES reference, the reported cognitive bias, paper type, and approach., Results: Of an initial 572 records retrieved, we screened the titles and abstracts of 128 articles, and identified 58 articles for full review. Four articles were selected for inclusion. Two are empirical investigations of bias in two CES, and two are theoretical, conceptual papers that discuss cognitive bias during CES deliberations. Our main result first shows an overview of bias related to the working human environment and to information gathering that concerns different types of CES. Second, several determinants of cognitive bias were highlighted. Especially, stressful environments could be at risk of cognitive bias, whatever the clinical dilemma., Conclusions: Whether a need for a better taxonomy of cognitive bias in CES is highlighted, a proposal is made to focus on individual, group, institutional and professional biases that can be present during clinical ethics deliberation. However, future studies need to focus on an ecological evaluation of CES deliberations, in order to better-characterize cognitive biases and to study how they impact the quality of ethical decision-making. This information would be useful in considering countermeasures to ensure that deliberation is as unbiased as possible, and allow the most appropriate ethical decision to emerge in response to the dilemma at hand., Competing Interests: Declarations. Ethics approval and consent to participate: Not applicable. Consent for publication: Not applicable. Competing interests: The authors declare no competing interests., (© 2025. The Author(s).)

Aiming at the information asymmetry between pharmaceutical enterprises' technological innovation decisions and government subsidy strategy, this paper establishes a differential game model consisting of the government and a single pharmaceutical company, proposes three different government subsidy strategies, and obtains an equilibrium solution with the help of the Hamilton-Jacobi-Bellman equation, taking into consideration of the transmission effect of the enterprise's reputation. First, the innovation decisions of pharmaceutical firms without government subsidies are analysed, and based on this, the optimal strategies with government subsidies for non-cooperative pacts and cooperation between the government and enterprises are analysed separately. In addition, the effects of different subsidy strategies on the government's investment efficiency, corporate reputation, and the choice of corporate innovation strategies are compared, and the results are verified by numerical analysis. Finally, based on the results of the study, references and suggestions are provided for the formulation of government subsidy policies as well as corporate innovation decisions. The results show that: government subsidies can effectively stimulate the innovation ability of pharmaceutical enterprises and improve their reputation; the more sensitive an enterprise's reputation is to the coefficient of technological innovation, the more it can improve the enterprise's innovation level; and the coordination contract of government-enterprise cooperation can realize the Pareto improvement of the benefits of the government and enterprises., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2025 Kang, Huang. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: The online nature of decision aids (DAs) and related e-tools supporting women's decision-making regarding breast cancer screening (BCS) through mammography may facilitate broader access, making them a valuable addition to BCS programs., Objective: This systematic review and meta-analysis aims to evaluate the scientific evidence on the impacts of these e-tools and to provide a comprehensive assessment of the factors associated with their increased utility and efficacy., Methods: We followed the 2020 PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines and conducted a search of MEDLINE, PsycINFO, Embase, CINAHL, and Web of Science databases from August 2010 to April 2023. We included studies reporting on populations at average risk of breast cancer, which utilized DAs or related e-tools, and assessed women's participation in BCS by mammography or other key cognitive determinants of decision-making as primary or secondary outcomes. We conducted meta-analyses on the identified randomized controlled trials, which were assessed using the revised Cochrane Risk of Bias 2 (RoB 2) tool. We further explored intermediate and high heterogeneity between studies to enhance the validity of our results., Results: In total, 22 different e-tools were identified across 31 papers. The degree of tailoring in the e-tools, specifically whether the tool was fully tailored or featured with tailoring, was the most influential factor in women's decision-making regarding BCS. Compared with control groups, tailored e-tools significantly increased women's long-term participation in BCS (risk ratio 1.14, 95% CI 1.07-1.23, P<.001, I 2 =0%). Tailored-to-breast-cancer-risk e-tools increased women's level of worry (mean difference 0.31, 95% CI 0.13-0.48, P<.001, I 2 =0%). E-tools also improved women's adequate knowledge of BCS, with features-with-tailoring e-tools designed and tested with the general population being more effective than tailored e-tools designed for or tested with non-BCS participants (χ 2 1 =5.1, P=.02). Features-with-tailoring e-tools increased both the rate of women who intended not to undergo BCS (risk ratio 1.88, 95% CI 1.43-2.48, P<.001, I 2 =0%) and the rate of women who had made an informed choice regarding their intention to undergo BCS (risk ratio 1.60, 95% CI 1.09-2.33, P=.02, I 2 =91%). Additionally, these tools decreased the proportion of women with decision conflict (risk ratio 0.77, 95% CI 0.65-0.91, P=.002, I 2 =0%). Shared decision-making was not formally evaluated. This review is limited by small sample sizes, including only a few studies in the meta-analysis, some with a high risk of bias, and high heterogeneity between the studies and e-tools., Conclusions: Features-with-tailoring e-tools could potentially negatively impact BCS programs by fostering negative intentions and attitudes toward BCS participation. Conversely, tailored e-tools may increase women's participation in BCS but, when tailored to risk, they may elevate their levels of worry. To maximize the effectiveness of e-tools while minimizing potential negative impacts, we advocate for an "on-demand" layered approach to their design., (©Patricia Villain, Laura Downham, Alice Le Bonniec, Charlotte Bauquier, Olena Mandrik, Tom Nadarzynski, Lorie Donelle, Raúl Murillo, Eleni L Tolma, Sonali Johnson, Patricia Soler-Michel, Robert Smith. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 29.01.2025.)

The incorporation of ethical settings in Automated Driving Systems (ADSs) has been extensively discussed in recent years with the goal of enhancing potential stakeholders' trust in the new technology. However, a comprehensive ethical framework for ADS decision-making, capable of merging multiple ethical considerations and investigating their consistency is currently missing. This paper addresses this gap by providing a taxonomy of ADS decision-making based on the Agent-Deed-Consequences (ADC) model of moral judgment. Specifically, we identify three main components of traffic moral judgment: driving style, traffic rules compliance, and risk distribution. Then, we suggest distinguishable ethical settings for each traffic component., Competing Interests: Declarations. Conflict of Interest: No conflict of interests., (© 2025. The Author(s).)

The evolution of human behaviour is marked by key decision-making processes reflected in technological variability in the early archaeological record. As part of the technological system, differences in raw material quality directly affect the way that humans produce, design and use stone tools. The selection, procurement and use of various raw materials requires decision-making to evaluate multiple factors such as suitability to produce and design tools, but also the materials' efficiency and durability in performing a given task. Therefore, characterizing the physical properties of various lithic raw materials is crucial for exploring changes in human interactions with their natural environment through time and space and for understanding their technological behaviour. In this paper, we present the first step in an ongoing program designed to understand the decision-making criteria involved in the use of raw materials by the early Acheulian tool-makers at the Melka Wakena (MW) site-complex, located on the Ethiopian highlands. We present the results of the first experimental step, in which we identified and measured the engineering properties of raw materials in the lithic assemblages. These data serve as an objective, quantifiable baseline for natural experiments as well as archaeological inquiries into the technological decision-making processes of early Pleistocene hominins in Africa., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2025 Paixão et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Empathy is central to individual and societal well-being. Numerous studies have examined how trait of empathy affects prosocial behavior. However, little studies explored the psychological and neural mechanisms by which different dimensions of trait empathy influence prosocial behavior. Addressing this knowledge gap is important to understand empathy-driven prosocial behavior. We employed an EEG experiment combined with interpretable machine learning methods to probe these questions. We found that empathic concern (EC) played the most pivotal role in donation decision. Behaviorally, EC negatively moderates the effect of perceived closeness and deservedness of charity projects on the willingness to donate. The machine learning results indicate that EC significantly predicts late positive potential (LPP) and beta-band activity during donation information processing. Further regression analysis results indicate that EC, rather than other dimensions of trait empathy, can positively predict LPP amplitude and negatively predict beta-band activity. These results indicated that participants with higher EC scores may experience heightened emotional arousal and the vicarious experience of others' emotions while processing donation information. Our work adds weight to understanding the relationship between trait empathy and prosocial behavior and provides electrophysiological evidence., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 International Brain Research Organization (IBRO). Published by Elsevier Inc. All rights reserved.)

Patients with Bipolar Disorder type I (BD-I) exhibit maladaptive risky decision-making, which is related to impulsivity, suicide attempts, and aggressive behavior. Currently, there is a lack of effective predictive methods for early intervention in risky behaviors for patients with BD-I. This study aimed to predict risky behavior in patients with BD-I using resting-state functional magnetic resonance imaging (rs-fMRI). We included 48 patients with BD-I and 124 healthy controls (HC) and constructed voxel-wise functional connectivity (FC), dynamic FC (dFC), effective connectivity (EC), and dynamic EC (dEC) for each subject. The Balloon Analogue Risk Task (BART) was employed to measure the risky decision-making of all participants. We applied connectome-based predictive modeling (CPM) with five regression algorithms to predict risky behaviors as well as Barratt Impulsivity Scale (BIS) scores. Results showed that the BD-I had significantly lower risky adjusted pump scores compared to HC. The dEC-based linear regression-CPM model exhibited significant predictive ability for the adjusted pump scores in BD-I, while no significant predictive power was observed in HC. Furthermore, this model successfully predicted non-planning impulsiveness, motor impulsiveness, and BIS total score, but failed for attentional impulsiveness in BD-I. These findings provide a foundation for future work in predicting risky behaviors of psychiatric patients by using voxel-wise dEC underlying resting state., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 International Brain Research Organization (IBRO). Published by Elsevier Inc. All rights reserved.)

The development of cross-border e-commerce platform promotes the new channel model between domestic and international. How to determine the dual-channel pricing decision of manufacturers and retailers under the condition of tariff and transportation heterogeneity has become an important and realistic problem. Based on the perspective of cross-border e-commerce dual-channel supply chain, this paper considers the impact of import tariff, transport heterogeneity and export tax rebate, compares and analyzes the performance difference between decentralized decision-making and centralized decision-making, and analyzes the impact of import tariff, export tax rebate and transport heterogeneity on cross-border e-commerce dual-channel pricing, demand and profit. The results show that the tariff is positively correlated with the manufacturer's direct selling price and the retailer's retail price, while the tariff is negatively correlated with the wholesale price, the demand and profit of direct selling channel and the retail channel. Export tax rebate rate is positively correlated with manufacturers' demand and profit and retailers' demand and profit, and negatively correlated with manufacturers' wholesale price, direct selling price and retail price. The increase of unit freight in direct channel is unfavorable to manufacturers and beneficial to retailers; The increase in unit freight rates in retail channels is bad for both manufacturers and retailers. Centralized decision-making is beneficial to supply chain demand and profits, and can improve the overall performance of the supply chain., Competing Interests: The authors have stated that there is no competing interest., (Copyright: © 2025 Guo et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Previous literature indicates that the later phases of the acute stress response may promote poor decision-making, characterized by riskier choices and a likely inclination towards immediate reward-seeking. However, all studies addressing the effect of this phase have treated decisional capacity as a singular dimension, without analyzing the underlying processes under decision-making. Employing the Value-Plus-Perseveration (VPP) RL model, based on Bayesian logic, this study aims to gain specific insights into how late phase of acute stress impacts the cognitive processes underpinning decision-making in the Iowa Gambling Task (IGT), deciphering whether, as expected, gains are processed in a magnified manner. Seventy-three participants were randomly assigned to two groups, stress (N = 35) and control (N = 38). A virtual version of The Trier Social Stress Test (TSST-VR) was employed as a laboratory stressor. Decision-making was evaluated 35 minutes after the stressor onset, by means of the IGT. Results showed that stressed participants, in comparison to control group, displayed more perseverant and consistent decision-making, enhanced memory, and reinforcement learning capabilities, yet were guided by a greater attraction to decks offering immediate high gains. These results are analyzed with the understanding that in the IGT, short-term decisions focused on instant rewards are seen as counterproductive. This suggests that stress could limit the ability to switch to strategies that are more cautious and offer greater long-term benefits., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Objectives: Maladaptive risky decision-making is a common pathological behavior among patients with various psychiatric disorders. Brain entropy, which measures the complexity of brain time series signals, provides a novel approach to assessing brain health. Despite its potential, the dynamics of brain entropy have seldom been explored. This study aimed to construct a dynamic model of brain entropy and examine its predictive value for risky decision-making in patients with mental disorders, utilizing resting-state functional magnetic resonance imaging (rs-fMRI)., Methods: This study analyzed the rs-fMRI data from a total of 198 subjects, including 48 patients with bipolar disorder (BD), 47 patients with schizophrenia (SZ), 40 patients with adult attention deficit hyperactivity disorder (ADHD), as well as 63 healthy controls (HC). Time series signals were extracted from 264 brain regions based on rs-fMRI. The traditional static entropy and dynamic entropy (coefficient of variation, CV; rate of change, Rate) were constructed, respectively. Support vector regression was employed to predict risky decision-making utilizing leave-one-out cross-validation within each group., Results: Our findings showed that CV achieved the best performances in HC and BD groups (r = -0.58, MAE = 6.43, R 2 = 0.32; r = -0.78, MAE = 12.10, R 2 = 0.61), while the Rate achieved the best in SZ and ADHD groups (r = -0.69, MAE = 10.20, R 2 = 0.47; r = -0.78, MAE = 7.63, R 2 = 0.60). For the dynamic entropy, the feature selection threshold rather than the time window length and overlapping ratio influenced predictive performance., Conclusions: These results suggest that dynamic brain entropy could be a more effective predictor of risky decision-making than traditional static brain entropy. Our findings offer a novel perspective on exploring brain signal complexity and can serve as a reference for interventions targeting risky decision-making behaviors, particularly in individuals with psychiatric diagnoses., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Sequential decision-making, where choices are made one after the other, is an important aspect of our daily lives. For example, when searching for a job, an apartment, or deciding when to buy or sell a stock, people often have to make decisions without knowing what future opportunities might arise. These situations, which are known as optimal stopping problems, involve a risk associated with the decision to either stop or continue searching. However, previous research has not consistently found a clear connection between individuals' search behavior in these tasks and their risk preferences as measured in controlled experimental settings. In this paper, we explore how particular characteristics of optimal stopping tasks affect people's choices, extending beyond their stable risk preferences. We find that (1) the way the underlying sampling distribution is presented (whether it is based on experience or description), (2) the sequential presentation of options, and (3) the unequal frequencies of choices to reject versus to accept significantly bias people choices. These results shed light on the complex nature of decisions that unfold sequentially and emphasize the importance of incorporating context factors when studying human decision behavior., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Objective: This study aims to understand the perspectives of young people towards their Covid-19 vaccination and their involvement in the decision-making process., Methods: Semi-structured interviews were conducted with 25 children and adolescents (aged 8-19 years), who attended a school in Germany during the pandemic. Interviews were explored with structured and evaluative content-analysis., Results: Five overarching themes were identified: 1) Motivators for vaccination: protection against Covid-19, secondary societal benefits and positive experience of peers 2) Barriers to vaccination: perceived lack of risk for severe disease 3) Participation in the decision-making process: mostly adult-initiated shared decisions 4) Role of vaccination status at school: issues of marginalization and stigmatization 5) Wishes to adults and politicians: need for better information CONCLUSION: Involving children at a high level of participation while taking into account their individual maturity could be a favourable strategy in a family`s decision-making process regarding vaccination. Expectations from peers or parents and societal benefits as primary incentive to get vaccinated should be minimized during the decision-process., Practice Implications: Our study highlights the need to include young people`s perspectives in vaccine research, -development and -education campaigns. Future research should develop instruments to structurally embed and promote children and youth participation in healthcare-related decisions., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Objective: Examine decision-making regarding when women would prefer to receive reproductive carrier and cancer predisposition screening and from what clinician., Methods: 20 women completed in-depth interviews via Zoom exploring their views on the provision of reproductive carrier and cancer predisposition screening. Our analysis identified themes related to what informs women's preferences for when they would like to receive a genetic screening offer and by which clinician., Results: Participants' responses to questions about when they would be interested in receiving genetic screening were best understood through the lens of the Extended Parallel Process Model. Specifically, personal utility of the information, a woman's family health history and cost were key factors in decision-making. Women considered their clinician's knowledge and their trust in and relationship with the clinician when deciding from whom they would prefer to receive an offer of genetic screening., Conclusion: OB/GYN clinic patients may accept an offer of genetic screening from a knowledgeable and trusted clinician for carrier and cancer predisposition screening preconceptionally or prenatally., Practice Implications: Integrating genetic reproductive and cancer predisposition screening into the care provided to reproductive age OB/GYN patients may be acceptable to this population., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Objective: Effective decision-making is crucial for children and young people's trial participation, but specific tools to measure it are lacking. The TRECA (TRials Engagement in Children and Adolescents) Decision-Making Questionnaire (DMQ) was developed to fill this gap and has been evaluated for reliability and validity METHODS: We created the TRECA Decision-Making Questionnaire, based on similar measures for adults, and recruited participants through seven Studies-Within-a-Trial (SWATs). Participants were randomly assigned to receive trial information either as a printed Participant Information Sheet or Multimedia Information, or both, and asked to complete the DMQ. We calculated item completion rates, item-remainder statistics and Cronbach's Alpha, and conducted factor analysis., Results: 549 participants (433 parents/guardians, 116 older children) completed a DMQ. It had high completion rates and internal consistency (Alpha = 0.88 for parents/guardians and 0.84 for older children) and moderate to high inter-item correlations. The DMQ had a single factor accounting for 53 % of variance., Conclusions: The TRECA DMQ is a useful tool for evaluating research participation decisions in older children, as well as parents and guardians., Practice Implications: Our study suggests that the TRECA DMQ can be used to assess the quality of decision-making about trials in parents, guardians and older children., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Aim: To understand the steps in the decision-making process regarding pain assessment and management for people living with dementia from the perspectives and experiences of people with dementia, formal and informal carers., Methods: A systematic review was conducted. Seven English databases were searched, including PubMed, Psychological Information Database, Cochrane Library, Scopus, Cumulative Index of Nursing and Allied Health Literature, Web of Science, and ProQuest, using synonyms and derivatives for "dementia", "cognitive impairment", "pain", "pain assessment", "pain management", "decision", "decision support", and "decision-making"., Results: Twenty-eight studies fulfilled the eligibility criteria. Pain assessment and management in dementia are complex, successive, and collaborative processes carried out by different individuals over a period based on one's understanding of the person with dementia but with high uncertainty. Pain assessment involves a certain degree of guesswork, while pain management is a trial-and-error process., Conclusion: More pragmatic approaches are needed to overcome challenges, including uncertainty and decisional conflicts., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

Some seemingly irrational decision behaviors (anomalies), once seen as flaws in human cognition, have recently received explanations from a rational perspective. The basic idea is that the brain has limited cognitive resources to process the quantities (e.g., value, probability, time, etc.) required for decision making, with specific biases arising as byproducts of the resource allocation that is optimized for the environment. While appealing for providing normative accounts, the existing resource-rational models have limitations such as inconsistent assumptions across models, a focus on optimization for one specific aspect of the environment, and limited coverage of decision anomalies. One challenging anomaly is the peanuts effect, a pervasive phenomenon in decision-making under risk that implies an interdependence between the processing of value and probability. To extend the resource rationality approach to explain the peanuts effect, here we develop a computational framework-the Assemblable Resource-Rational Modules (ARRM)-that integrates ideas from different lines of boundedly-rational decision models as freely assembled modules. The framework can accommodate the joint functioning of multiple environmental factors, and allow new models to be built and tested along with the existing ones, potentially opening a wider range of decision phenomena to bounded rationality modeling. For one new and three published datasets that cover two different task paradigms and both the gain and loss domains, our boundedly-rational models reproduce two characteristic features of the peanuts effect and outperform previous models in fitting human decision behaviors., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2025 The Authors. Published by Elsevier Inc. All rights reserved.)

Outcomes in participatory environmental processes are strongly affected by choices about who is engaged. Inclusive engagement diversifies the range of interests and perspectives represented, including those from vulnerable and marginalized groups, ultimately contributing to more socially and environmentally sustainable and equitable outcomes. However, existing "stakeholder analysis" methods often bias participant identification away from disenfranchised groups with limited pre-existing interest or influence, instead favoring the most easily accessed and influential stakeholders. This paper draws on research impact theory and practice to propose a new, more inclusive approach, adding impact to the existing interest and influence criteria (which each begin with the letter "i", hence the 3i framework) that are typically used to identify, categorize and prioritize those who are relevant to be included or excluded from engagement processes. As part of this proposed 3i analysis approach, we articulate a new typology of relevant parties to engage in environmental decision-making processes, including: uninterested; uninterested and impacted; uninterested influencers; disinterested, influential and impacted; only interested; interested and impacted; interested influencers; and interested, influential and impacted. Except for the first group, all types of relevant parties should be considered for engagement wherever possible, with participation strategies tailored to their specific 3i profile. The approach was developed and refined through a series of workshops before developing it into a survey instrument that was piloted to gather 3i data efficiently across several national contexts. Survey findings are presented for a case study identifying those relevant to wetland and peatland restoration in a Scottish catchment. If widely adopted, the 3i framework would be the most consequential change in stakeholder analysis methods since the introduction of interest-influence matrices in the 1980s., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:Mark Reed reports financial support was provided by Scottish GovernmentRural and Environment Science and Analytical Services Division. Mark Reed reports financial support was provided by UK Research and Innovation. Mark Reed reports financial support was provided by Horizon Europe. Mark Reed reports a relationship with Institute for Methods Innovation that includes: speaking and lecture fees. Eric Jensen reports a relationship with Institute for Methods Innovation that includes: Employee; board membership. Corresponding author was previously CEO of Fast Track Impact Ltd If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: Health workforce supply is critical to ensuring the delivery of essential healthcare and may be enhanced via mechanisms which alter the scopes of practice of health professions. The aim of this paper is to study the collective perspectives of allied health decision-makers on factors which influence their development and implementation of advanced and extended scope of practice initiatives, and how they contribute to scope of practice change. The reasoning for the selection of each factor will also be examined., Methods: A grounded-theory, qualitative study of the experiences of allied health directors and senior managers across two Australian State/Territory jurisdictions., Results: Twenty allied health decision-makers participated in the study. Data coding of interview transcripts identified 14 factors specific to scope of practice change, spanning rational (n = 8) and non-rational (n = 6) decision-making approaches. Leadership, Governance, Needs of organisational leaders, Resourcing, Knowledge, skills & experience - clinical, Supporting resources, Knowledge & skills - change and Sustainability were identified as being rational and enabling in and of themselves, with Leadership seen as being most influential. Comparatively, the non-rational factors of Socio-economic & political environment, Perceived patient need, Organisational environment, Change culture & appetite, Perceived professional territorialism and Actual professional territorialism were more varied, and primarily influenced the timing/catalyst and application of decision-making. The complex interplay between these factors was conceptually represented as a decision-making construct., Conclusion: Allied health decision-makers hold a complex, systems-level understanding of scope of practice change. Whilst rational decision criteria were predominant and seen to enable scope change, non-rational influences reflected greater variation in decision timing/catalyst and application, thus emphasising the human dimensions of decision-making. Further research is required to better understand how decision-makers integrate and weight these decision-making factors to determine their relative importance and to inform the development of structured decision tools., (© 2024 The Author(s). The International Journal of Health Planning and Management published by John Wiley & Sons Ltd.)

Objective: To map the existing literature on decision regret among patients with non-communicable diseases (NCDs) and develop an integrated framework to understand its impact on patient outcomes and healthcare processes., Methods: A systematic search of PubMed, Embase, CINAHL, Cochrane Library, Google Scholar, and Scopus databases was conducted until January 2024 using the "Population, Concept, Context" framework. The review identified and analyzed 28 studies published between 2005 and 2023 in North America and Europe., Results: Decision regret primarily arises from mismatches between expected and actual treatment outcomes and is strongly influenced by patient-clinician communication quality. The need for improved informed consent processes and enhanced communication strategies to mitigate regret emerged as prevalent themes. A hypothetical theoretical path was developed to define the relationship between patient expectations, medical outcomes, and emotional responses., Conclusion: Enhanced communication and personalized treatment plans are crucial for addressing the multifaceted nature of regret in healthcare. Improved patient-clinician communication and informed consent processes can significantly reduce decision regret., Practice Implications: Healthcare providers should focus on effective communication and education to personalize care strategies and align treatment decisions with patient expectations. This could ultimately reduce decision regret and improve patient outcomes., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Rosario Caruso reports financial support was provided by IRCCS Policlinico San Donato. Rosario Caruso reports a relationship with IRCCS Policlinico San Donato that includes employment. Other authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Social equity consists of opportunity equity and outcome equity, where outcome equity refers to the equitable distribution of resource, while opportunity equity refers to equivalent sets of opportunities to obtain a satisfactory outcome, ensuring equality in expected payoffs rather than the actual payoffs. Previous studies showed the existence of inequity aversion for opportunity inequality and identified some differences between opportunity equity and outcome equity in the behavior pattern of evaluation and reaction processes. However, the commonalities and distinctions in brain activity during the fairness decision-making of opportunity equity and outcome equity remain unclear. Our study used a modified version of the ultimatum game (UG) and the classic UG, and recorded electroencephalogram (EEG) data to investigate underlying neural mechanisms of fairness decision-making of opportunity equity and outcome equity. The EEG results revealed that both shared the same components of the P300 and delta bands associated with reward processing. Compared to outcome equity, opportunity equity did not identify conflict-related medial frontal negativity (MFN) and theta bands, but showed differences in the P2 and beta bands. Moreover, we used a computational modeling approach to estimate the utility for each trial, and found that larger P2 amplitudes were associated with lower utility in opportunity distribution, while larger P300 amplitudes were associated with higher utility in outcome distribution. Our findings provide electrophysiological evidence for the existence of opportunity equity and shed light on the cognitive processing disparities between opportunity equity and outcome equity. These results not only validate and expand the theory of inequality aversion but also empirically support the targeted resolution of social inequalities in various contexts., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Inc.)

Background: Environmental and occupational health (EOH) assessments increasingly utilize systematic review methods and structured frameworks for evaluating evidence about the human health effects of exposures. However, there is no prevailing approach for how to integrate this evidence into decisions or recommendations. Grading of Recommendations Assessment, Development and Evaluation (GRADE) evidence-to-decision (EtD) frameworks provide a structure to support standardized and transparent consideration of relevant criteria to inform health decisions. This study identifies and synthesizes available EOH decision frameworks and evaluates the applicability and usability of an existing GRADE EtD perspective to advance the development of a tailored EOH EtD framework., Methods: We performed a systematic review of MEDLINE, EMBASE, and Cochrane Library, and a manual search of gray literature to identify frameworks that inform decision-making about EOH exposures from the years 2011 to 2021. We abstracted and analyzed decision considerations from each framework through narrative synthesis. Next, we conducted a two-round Delphi process, engaging stakeholders from the following perspectives within environmental and occupational health: risk assessment and management, nutrition and food safety, cancer, and socio-economic analysis. Panelists rated the relevance and wording of each consideration on a 7-point Likert scale and provided free-text comments during both phases. Considerations that did not meet predetermined thresholds were excluded., Results: Out of 5,196 unique references, we identified 22 published reports of EOH decision frameworks. We identified another 16 frameworks in a search of gray literature, totaling 38 source frameworks. We abstracted 560 individual decision considerations from these frameworks, 104 of which may contribute additional information to the guidance, scope, context, or assessment criteria of the GRADE EtD framework. In round 1 of the Delphi study, 50 decision considerations were aggregated or removed, and 9 were aggregated or removed after round 2, for a final total of 47. No new decision considerations were added in either round. We identified several differences between decision criteria that are applied in EOH and the GRADE EtD framework, including vocabulary that is specific to EOH (e.g., toxicity, the precautionary principle), and granularity of the EOH decision considerations (e.g., detailed signaling questions to assess feasibility and resources required). However, this study did not identify any EOH decision criteria that are completely distinct from the GRADE EtD framework., Conclusions: Findings of this mixed-methods study comprise a foundation for a GRADE EtD that is applicable for use in EOH decision-making, with implications for approaches to regulation of environmental and occupational exposures and the formulation of recommendations for interventions to prevent or mitigate undesirable health and other consequences., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Through technical rationality, healthcare professionals address instrumental problems by applying the theory and technique arising from scientific knowledge. Nevertheless, the divergent situations of practice characterised by uncertainty, instability, and uniqueness place nurses in a positivist epistemological dilemma. Decision-making under uncertainty is a challenge that nurses face in clinical practice daily. Nurses anticipate critical events based on the interaction between (un)known factors of clinical reasoning, putting uncertainty tolerance into perspective. With undeniable epistemological relevance, few nursing researchers have addressed this issue. Based on the insights garnered from the panel held at the 26th International Nursing Philosophy Conference, this discussion paper examines the inception of uncertainty within nursing reasoning, intertwining introspection, abstraction, and the rich discussions from the conference. Accordingly, the philosophical underpinnings of the perceived experience of uncertainty will be briefly addressed, while framing the decision-making challenges faced by nurses. A compelling dimension of nursing care emerges when we delve into the inception of uncertainty, prompting a deeper examination of the interplay between its perception and consciousness in clinical practice, and the gravitation of uncertainty in the process of empirical reasoning. Navigating uncertainty involves varying individual responses, influenced by tolerance levels. Moral appropriateness is determined by their adaptability rather than solely their positivity or logical consistency, highlighting constancy as a quality demanding alignment with an understanding of challenges., (© 2024 John Wiley & Sons Ltd.)

Objectives: As life expectancy for individuals living with cystic fibrosis (CF) has increased, many now reach adulthood and face important reproductive decisions with their partners. The aim of this systematic review was to assess the psychosocial and ethical considerations that influence the reproductive decision-making process of individuals living with CF and their partners., Methods: Four databases (Web of science, Pubmed, CINAHL, Cochrane) were searched. Studies meeting inclusion criteria were analyzed using a thematic synthesis approach., Results: Seven psychosocial and ethical themes related to reproductive decision-making were identified: 1) desire for a sense of 'normalcy', 2) (dis)approval of healthcare professionals, 3) possible impact on the 'future' child, 4) idea of good parenting, 5) possibility of transmitting the condition, 6) impact on health and personal well-being, and 7) role of non-CF partner and family/friends., Conclusions: The decision to have a child often originates from a typical desire to become a parent and is further guided by a sense of moral responsibility and the need for a solid partnership/collaborative network., Practice Implications: Routine dialogue about reproductive health between individuals living with CF and their care teams is important, as these individuals depend on reliable, evidence-based information for informed reproductive decision-making. Our findings can guide healthcare professionals to effectively initiate these conversations., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Every child has the right to proper nutrition. As such, child nutrition counselling is recommended to improve child dietary diversity and reduce malnutrition. However, there is limited empirical evidence on how child nutrition counselling, gender dynamics, and intra-household feeding decisions play a role and translate to child dietary diversity in rural contexts. Informed by theoretical conceptions from Health Belief Model (HBM) and Gender and Development (GAD) framework, we analyzed cross-sectional data from 517 smallholder households in Ghana's semi-arid Upper West Region to investigate the relationship between child nutrition counselling, gender dynamics, intra-household feeding decision-making, and their impact on child dietary diversity. Results from ordered logistic regression show that households that received child nutrition counselling reported higher child dietary diversity. Joint intra-household feeding decisions were associated with higher child dietary diversity. Households with good self-rated childcare, engaged in home gardening, and higher wealth, as well as those in the Waala ethnic group, were more likely to have high child dietary diversity. A decrease in household head age was linked to increased high child dietary diversity. On the other hand, female-headed households, Brifo ethnic groups, and those in the Wa East and Wa West districts were less likely to experience high child dietary diversity. Implementing interventions and policies prioritizing nutrition education in the Upper West Region and similar sub-Saharan African contexts is recommended. Strategies like scaling up child nutrition counselling, food demonstrations, mother-to-mother support nutrition outreach, and mobile nutrition clinics can empower women and improve children's well-being., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Green technology innovation (GTI) breaks the vicious cycle of "economic development-environmental pollution," mitigating the supply chain carbon emissions. Previous research focused on exploring supply chain GTI decision-making in the discrete strategy space and ignored the effect of stochastic factors. This paper, grounded in the classical evolutionary game theory, explores the interaction mechanism of supply chain GTI decision-making between suppliers and manufacturers under stochastic interferences and in the continuous strategy space. The main findings are as follows. First, regardless of the game scenario, the government subsidy, carbon price, and consumer green preference are incentive variables, while the innovation cost coefficient is an inhibitory variable. As the incentive variables increase or the inhibitory variables decrease, the game system evolves from the negative to the intermediate state, ultimately converging to the ideal state. Second, the ideal state becomes unstable after considering stochastic interferences, reflecting the fragility of bilateral innovation alliances between suppliers and manufacturers. Simultaneously, the evolution of the game system towards the negative state is also hindered, and the corresponding variable condition region narrows. In other words, stochastic interferences have a dual impact on supply chain GTI strategies. Third, an absolute negative state of no innovation does not exist in the continuous strategy space. Suppliers and manufacturers can determine the optimal innovation intensity to maximize expected returns, making GTI decision-making more flexible and resilient. This paper enriches the theoretical achievements of the evolutionary game theory and provides a reference for GTI strategies of supply chain enterprises., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Understanding how both visual and contextual in-game information influences player's attempts to gain an advantage over their opponent is key to understanding skilled decision-making in fast-ball sports. In the present study, we conducted semi-structured interviews with 15 male professional football players to explore their reported behaviours and perspectives on their in-game decision-making and the ways in which they adapt to gain an advantage over their opponent. Professional players who have competed internationally at either Under 17, Under 19, Under 21, or senior level took part in semi-structured interviews. The data were analysed using reflexive thematic analysis which generated four higher-order themes about players reported behaviours and perspectives on their decision-making and ways of gaining an advantage: (i) being "unpredictable"; (ii) option generation and invitation, comprising two sub-themes: (iia) generating and realising options in action; and (iib) act on what invites you in the moment; (iii) anticipation and awareness; and (iv) dictating and controlling the game. A key finding was that players attempts to gain an advantage were largely grounded in the aim of 'being unpredictable' through the use of deception and disguise, as well as deliberate manipulation of action sequences in order to make their actions 'hard to read'. A further important finding was that players do not always seek a universal optimal decision, as their individual action capabilities influence their available options. These findings have important implications for the assessment of decision-making performance in future empirical research., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Crown Copyright © 2024. Published by Elsevier Ltd. All rights reserved.)

The shift in crop growth in rural households towards non-grain crops is a focus of concern in China's grain security. Land allocation decisions by rural households to abandon farmland can affect crop growth decisions. Prior studies on the relationship between farmland abandonment and rural households' crop growing decisions have been insufficient. This study presents a theoretical framework that encompasses land, labor force, and capital. Using unique survey data from 2448 rural households in China's mountainous areas, we employ an endogenous switching regression model for empirical estimation. The findings demonstrate that farmland abandonment significantly promoted rural households to grow grain crops on their remaining farmland. If rural households had not abandoned their farmland, the crop acreage used for growing non-grain crops would have increased by 16.4%. The effects of abandonment on non-grain production decision-making vary based on per capita farmland area, farmland transfer, and agricultural social services. Furthermore, farmland abandonment by rural households affects decision-making regarding non-grain production by adjusting the agricultural labor force supply. Thus, under policies such as farmland protection and food security, it is necessary to balance the goals of replanting abandoned farmland and preventing non-grain crop growth in mountainous areas, with a focus on enhancing the level of mechanization., Competing Interests: Declaration of competing interest All authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

The article "From the Editor" in Ethnic & Racial Studies Volume 48 discusses the journal's plans for 2025, including new issues and a revamped International Editorial Board. The journal has seen an increase in its CiteScore and Impact Factor metrics, ranking well in various categories. The editors emphasize their commitment to global perspectives, interdisciplinary research, and diverse authorship. They express gratitude to their publishers, authors, referees, and supporters, highlighting the importance of peer review in maintaining the journal's quality and relevance. [Extracted from the article]

Gender inequalities persist in the outcomes of work-family decisions at the transition to parenthood, regardless of men and women’s relative earnings. While existing studies suggest explicit decision-making is necessary for egalitarian divisions of labour and theoretical perspectives often assume couples actively negotiate and discuss alternatives, little attention has been paid to decision-making dynamics within female higher- or equal-earning couples. Drawing on qualitative interviews with 25 heterosexual professional couples in the United Kingdom, this paper offers an in-depth analysis of the process of making fundamental ‘anchoring’ work-family decisions at the transition to parenthood, exploring the content of discussions and identifying mechanisms behind decision-making styles. Contrary to assumptions, the findings reveal that couples rarely negotiate or explicitly discuss work-family scenarios during this critical life transition. Conversations, predominantly led by women, focused on her working arrangements and (non-parental) childcare solutions. Four mechanisms emerged to explain a lack of discussion and women’s key role in driving decision-making: traditional gendered expectations, naivety about the risk of ‘falling into gender’, lack of impetus to discuss men’s working arrangements, and risks associated with men initiating such discussions. The paper underscores the need for active decision-making support, providing recommendations for families, organizations, education providers and policy makers. [ABSTRACT FROM AUTHOR]

With the advent of smart manufacturing, companies are adapting their business processes and procedures to match concepts and requirements related to this industrial revolution. In this scenario, maintenance sector should evolve to keep pace with new technological trends by shifting from traditional approaches to a smart paradigm. Some consolidated methodologies rely on standard evaluation, like Risk Priority Number, to plan maintenance actions on machines and components. However, contemporary and smart approaches should be characterized by data-driven (quantitative knowledge) as well as operator's experience (qualitative knowledge) in order to provide a whole understanding and visibility of the system health status. In this context and with a view of digital twin concepts (under the Industry 4.0 technology), a decision support methodology (or framework) plays an essential role by providing knowledge and assisting operators in the decision-making process. With this concept in mind, this paper focuses on integrating several and not alike fields of study (process mining, multicriteria decision-making (MCDM), and data fusion) to enable the assessment of a risk and criticality analysis to rank industrial machines in order to carry out/plan maintenance tasks on them. Therefore, merging those fields of study aims at accomplishing a dynamic, flexible, and real-time evaluation to perform a robust, accurate, and responsive analysis of the system. The results from different analysis scenarios show the influence of maintenance indicators on the machine ranking process, highlighting the feasibility and flexibility of the approach, as well as expanding the application in modern systems by optimizing quality of maintenance decisions. [ABSTRACT FROM AUTHOR]

This paper describes a consensus-based approach for dealing with multi-person decision-making problems which incorporate probability hesitant fuzzy preference relations. The procedure begins with establishing expected fuzzy preference relations based on the delivered hesitant fuzzy preference relations using a probabilistic aggregation approach, providing the platform for the framework to make decisions. Then, a multiplicative transitive closure formula is defined to construct multiplicative consistent expected fuzzy preference relations and symmetrical matrices, ensuring the reliability of the preference relations. Following that, a consistency analysis is undertaken to assess the consistency levels of the information provided by experts, allowing them to be assigned information priority weights while also guaranteeing that their inputs are balanced and reliable. In order to make sure that all pertinent factors are taken into account during the decision-making process, the ultimate priority weights for the experts are determined through the combination of consistency-based weights with any specified priority weights, if applicable. The consensus process eventually decides whether to aggregate the data and choose the optimal option based on the collective inputs. To strengthen the experts' consensus measure, an enhancement method is provided that detects weak viewpoints in cases of poor consensus and allows for targeted modifications. To highlight the suggested scheme's practicality and usefulness, a comparison example is provided, with results indicating that the method provides valuable insights into the multi-person decision-making process, making it a potential option for achieving agreement in complicated decision-making settings. [ABSTRACT FROM AUTHOR]

This paper investigates ensemble feature selection using the q-rung orthopair hesitant fuzzy multi-criteria decision-making (MCDM) process. A novel algorithm is proposed for the study of ensemble feature selection and it is called as q-rung orthopair hesitant fuzzy MCDM extended to the Visekriterijumska optimizacija Ikompromisno Resenje (VIKOR) (q-ROHFS VIKOR). This is the first time in the literature an ensemble feature selection problem is modelled as a q-rung orthopair hesitant fuzzy MCDM extended to VIKOR technique. In the proposed method, every feature is ranked based on different available rankers and a preference matrix is obtained. In the sigmoidal transformation, the tuning parameter $$a$$ a plays a vital role in the fuzzification process. This tuning parameter reduces the computation run-time in the fuzzification process for different high-dimensional datasets that are considered in this paper. By using q-ROHFS VIKOR method, a score is assigned to each feature based on the values of the preference matrix. At last, an output rank vector is produced for all features from which the user can select the desired number of features. To prove the efficiency and optimality of the proposed method, the comparison with basic filter-based feature selections and ensemble feature selection using feature ranking strategy is obtained. The proposed method in this paper is superior and efficient than the ensemble methods based on the accuracy and F-score levels upto 0.96. [ABSTRACT FROM AUTHOR]

A rough set is an approximation of a subset of a universe. Rough sets are mainly used in decision-making when the given data is uncertain. Rough set theory is a groundbreaking approach that provides a formal framework for extracting facts from imperfect data and helps us classify objects based on their similarities. Developing an algebraic structure for rough sets facilitates a detailed study of the settheoretic properties. In this paper, we consider the universe as a ring and obtain rough set results. We consider a new equivalence relation on a ring R whose equivalence classes form a partition of R. Then, we define upper and lower approximations of a subset of a ring R with respect to the given equivalence relation. Subsequently, we prove related results on these approximations and are illustrated with suitable examples. In addition, we obtain the relationship between the upper and lower approximations defined in this paper and the ones defined earlier. [ABSTRACT FROM AUTHOR]

This paper presents a dynamic model for the transition of logistics service providers from traditional to green transportation services. Driven by regulatory requirements and increasing market demand for sustainable practices, the need for such a model is critical for logistics providers to manage the complexities and cost implications of adopting green technologies. Utilizing real-world data from a leading Baltic logistics provider, the model integrates both micro and macro-level factors, offering a decision-making tool that simulates various scenarios and fore-casts outcomes over a ten-year period. Key findings reveal that while green transportation costs are projected to decrease below traditional costs, demand for traditional services will persist, highlighting the need for a balanced approach in planning. This research contributes a novel framework that aids logistics providers in strategic planning and forecasting the evolution of green logistics, providing valuable insights into future trends in the industry [ABSTRACT FROM AUTHOR]

This article presents the results of a study on the impact of selected parameters of a building's ground-floor zone (the junction of the external and foundation walls, the ground floor slab, and the ground itself) on the temperature field within the external envelope. This study aims to analyze the influence and optimize the parameters of vertical perimeter insulation in the ground-floor zone of the building. Mathematical modeling was selected as the research method. This paper analyzes the relationships between the temperature ϑimg on the inner surface of the wall at the analyzed node and the linear thermal transmittance coefficient ψim of the thermal bridge occurring in this location, as influenced by the following parameters: dp—thickness of the insulation layer in the ground floor slab; df—thickness of the vertical perimeter insulation layer in the foundation wall; t—location of the insulation layer in the ground floor slab relative to the "external wall-foundation wall" contact surface; r—location of the vertical perimeter insulation layer in the foundation wall; and λs—thermal conductivity of the single-layer external wall material. The analysis was conducted under the climatic conditions of Białystok, Poland. Using THERM 7.6 software for computational experiments, data were obtained to develop deterministic mathematical models of these relationships. The models enabled the assessment of the degree and nature of the influence of the studied factors on ϑimg and ψim, optimization of selected parameters, and mathematical description of safe operating conditions for external walls in the ground-floor zone of heated buildings. It was found that the parameters dp, df, and r have favorable effects, increasing ϑimg by 2.57%, 2.51%, and 4.17%, respectively, when varying from their minimum to maximum levels. Conversely, the parameters t and λs negatively impact ϑimg, contributing reductions of −12.01% and −4.66%, respectively, with a cumulative effect of −16.67%. Optimal parameter values were determined based on energy efficiency criteria. This information may be useful for researchers, designers, engineers, and decision-makers when making informed decisions during the design phase of heated buildings. [ABSTRACT FROM AUTHOR]

The implementation of predictive maintenance (PM) in aviation presents unique challenges due to strict safety requirements, complex operational environments, and regulatory constraints. This paper develops a comprehensive decision-making framework for evaluating the feasibility of implementing PM for aircraft components, addressing the critical need for systematic integration of technical, economic, and regulatory considerations. Through expert surveys involving 78 aviation maintenance professionals and the application of multi-criteria decision analysis, this study identifies and validates 14 key criteria across four categories: technical and operational, economic and feasibility, regulatory and compliance, and organizational and human factors. The analytic hierarchy process is employed to establish criteria weights, with flight safety impact, reliability predictability, and data sufficiency emerging as primary drivers. The framework's effectiveness is demonstrated through case studies comparing turbofan engines and avionics units, validating its ability to discriminate between components suitable for PM implementation. Results indicate that successful PM implementation requires not only technological readiness but also organizational alignment and regulatory compliance. This study contributes to aviation maintenance practice by providing a structured, evidence-based approach to PM implementation decisions, while establishing a foundation for future innovations in maintenance strategies. The framework's practical applicability is enhanced through a detailed implementation roadmap and validation methods, ensuring its relevance for maintenance decision-makers while maintaining alignment with aviation safety standards. [ABSTRACT FROM AUTHOR]

Healthcare 4.0 addresses modernization and digital transformation challenges, such as home-based care and precision treatments, by leveraging advanced technologies to enhance accessibility and efficiency. Semantic technologies, particularly knowledge graphs (KGs), have proven instrumental in representing interconnected medical data and improving clinical decision-support systems. We previously introduced a semantic framework to assist medical experts during patient interactions. Operating iteratively, the framework prompts medical experts with relevant questions based on patient input, progressing toward accurate diagnoses in time-constrained settings. It comprises two components: (a) a KG representing symptoms, diseases, and their relationships, and (b) algorithms that generate questions and prioritize hypotheses—a ranked list of symptom–disease pairs. An earlier extension enriched the KG with a symptom ontology, incorporating hierarchical structures and inheritance relationships to improve accuracy and question-generation capabilities. This paper further extends the framework by introducing strategies tailored to specific medical domains. Strategies integrate domain-specific knowledge and algorithms, refining decision making while maintaining the iterative nature of expert–patient interactions. We demonstrate this approach using an emergency medicine case study, focusing on life-threatening conditions. The KG is enriched with attributes tailored to emergency contexts and supported by dedicated algorithms. Boolean rules attached to graph edges evaluate to TRUE or FALSE at runtime based on patient-specific data. These enhancements optimize decision making by embedding domain-specific goal-oriented knowledge and inference processes, providing a scalable and adaptable solution for diverse medical contexts. [ABSTRACT FROM AUTHOR]

We investigate a bargaining setting between an "informed" player, who has private information, and an "uninformed" player. The informed player has the option to truthfully disclose private information in two unique environments. In the first environment, the informed player is randomly matched with an uninformed player and, after matching, can voluntarily disclose private information prior to a negotiation taking place. In the second environment, the informed player can voluntarily disclose private information before any endogenous matching between players (and subsequent negotiation) takes place. We begin by examining these environments theoretically. When disclosure occurs after matching, we show that low informed types should disclose more often than high informed types to avoid disagreement. However, when disclosure occurs before matching, for a range of parameter values, we show that high informed types should disclose more than low informed types to secure a better match. We test these predictions in a controlled human-subjects experiment and verify many of the theoretical predictions. Among other results, we find that low informed types do indeed disclose their private information to avoid disagreement and that, when it is in their interest to do so, high informed types disclose their private information to secure a better match. Another key insight is that high uninformed types benefit from disclosure regardless of whether it occurs before or after matching. This paper was accepted by Axel Ockenfels, behavioral economics and decision analysis. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2022.03566. [ABSTRACT FROM AUTHOR]

The assignment of individuals with different observable characteristics to different treatments is a central question in designing optimal policies. We study this question in the context of increasing workers' performance via targeted incentives using machine learning algorithms with worker demographics, personality traits, and preferences as input. Running two large-scale experiments, we show that (i) performance can be predicted by accurately measured worker characteristics, (ii) a machine learning algorithm can detect heterogeneity in responses to different schemes, (iii) a targeted assignment of schemes to individuals increases performance significantly above the level of the single best scheme, and (iv) algorithmic assignment is more effective for workers who have a high likelihood to repeatedly interact with the employer or who provide more consistent survey answers. This paper was accepted by Yan Chen, behavioral economics and decision analysis. Funding: Funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany's Excellence Strategy [Grant EXC 2126/1-390838866]. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2022.03362. [ABSTRACT FROM AUTHOR]

A group of individuals is interested in predicting the outcome of a current problem. Each individual has access to private data that are used to form a prior probability over possible outcomes. While individuals may be reluctant or unable to disclose their private data, they are willing to publish their priors. We characterize a procedure for revising the individuals' prior probabilities based on the published priors of others and discuss its implications regarding the formation of a common prior in the group, both in the short and long run. This paper was accepted by Manel Baucells, behavioral economics and decision analysis. Funding: G. Gayer gratefully acknowledges support from ISF [Grant 1443/20]. [ABSTRACT FROM AUTHOR]