Relevant Dimensions Research Articles

Working on new applications: Use of economic evaluation in burden of disease estimates

Abstract Burden of disease (BoD) analyses provide policy-makers with useful evidence to prioritise policy responses to major public health threats. Increasingly, however, epidemiological data alone is not considered as sufficient to inform decisions, particularly when funding is allocated within a single government approach and different sectors compete for a larger share of the overall budget. Similarly, other funders, such as charities and foundations, may want to prioritise budget allocation between health and non-health objectives. In all these cases, traditional BoD analyses need to be complemented by economic evaluations. In its simplest form, the economic component may mean adding an assessment of the healthcare costs caused by the diseases in the study. A more comprehensive, though still with limitations, approach is to use monetary values to measure the extent to which individuals are willing to exchange their income - which can be spent on other things - for the health outcomes they experience. Finally, in its most advanced and comprehensive form, analyses can include assessments of a number of relevant dimensions, such as those in the OECD’s Better Life Index. The latter approach is also consistent with, and its results support the implementation of, a health in all policies approach. This presentation will look at traditional and innovative approaches that can be used to add an economic dimension to BoD analyses. After introducing the rationale and key methodological issues of each approach, the presentation will discuss the advantages and disadvantages of each methodology and will identify areas where their use can be beneficial in guiding the decision-making process. Examples of the use of these methodologies in real-world analyses will also be presented to support the theoretical part of the discussion.

Highly demarcated structural alterations in the brain and impaired social incentive learning in Tbx1 heterozygous mice.

Copy number variants (CNVs) are robustly associated with psychiatric disorders and changes in brain structures. However, because CNVs contain many genes, the precise gene-phenotype relationship remains unclear. Although various volumetric alterations in the brains of 22q11.2 CNV carriers have been identified in humans and mouse models, it is unknown how each gene encoded in the 22q11.2 region contributes to structural alterations, associated mental illnesses, and their dimensions. Our previous studies identified Tbx1, a T-box family transcription factor encoded in the 22q11.2 CNV, as a driver gene for social interaction and communication, spatial and working memory, and cognitive flexibility. However, it remains unclear how TBX1 impacts the volumes of various brain regions and their functionally linked behavioral dimensions. In this study, we used volumetric magnetic resonance imaging analysis to comprehensively evaluate brain region volumes and behavioral alterations relevant to affected structures in congenic Tbx1 heterozygous mice. Our data showed that the volumes of the anterior and posterior portions of the amygdaloid complex and its surrounding cortical regions were most robustly reduced in Tbx1 heterozygous mice. In an amygdala-dependent task, Tbx1 heterozygous mice were impaired in their ability to learn the incentive value of a social partner. The volumes of the primary and secondary auditory cortexes were increased, and acoustic, but not non-acoustic, sensorimotor gating was impaired in Tbx1 heterozygous mice. Our findings identify the brain's regional volume alterations and their relevant behavioral dimensions associated with Tbx1 heterozygosity.

The Oncology QCARD Initiative: Fostering efficient evaluation of initial real-world data proposals.

The oncology quality, characterization, and assessment of real-world data (Oncology QCARD) Initiative was formed to develop a set of minimum study design and data elements needed to evaluate the fitness of the real-world data (RWD) source(s) proposed in an initial study concept as part of early interaction with scientific reviewers. A multidisciplinary executive committee (EC) was established to guide the Oncology QCARD Initiative. The EC conducted a landscape review of published literature, guidances, and guidelines to evaluate relevant dimensions of data quality measurement. Guided by the review and informed by expert feedback, the Oncology QCARD Initial Protocol Characterization (IPC) provides a summary of minimum elements needed to adequately describe an initial clinical study concept that involves RWD and is intended to support decision-making. Fit-for-use data and fit-for-purpose design emerged as themes from the landscape analysis. Data that are fit-for-use are both relevant (sufficiently capturing exposure, outcomes, and covariates) and reliable (understanding data accrual and quality control and whether the data represent the underlying concepts they are intended to represent) to answer a specific research question. A fit-for-purpose design takes appropriate steps to ensure internal and external validity and allows for transparency in reporting. The QCARD-IPC focuses on high-level characteristics of RWD sources and study design domains including data temporality, population, medical product exposure, comparators, and covariates, endpoints, statistical analysis, and data quality assurance plans. Evaluation of studies including RWD requires understanding the data source, study design, and potential biases to preliminarily evaluate whether selected RWD are fit-for-use for the research question. The Oncology QCARD-IPC provides a structured, transparent approach to facilitate early review and enhanced communication between study sponsors and scientific reviewers of initial study proposals including RWD.

Patterns of Sexuality, Adjustment to Aging and Satisfaction with Life: A Cluster Analysis of Adults Across the Lifespan

AbstractSexual satisfaction, adjustment to aging, and satisfaction with life are relevant dimensions of overall well-being across the life cycle. Through cluster analysis procedures, this study aims to describe the specific profile of adjustment to aging, sexual satisfaction and satisfaction with life of adults across the life span. This cross-sectional study involved a community-based sample of 619 Portuguese individuals, aged between 18 and 92 years old (M = 47.53 SD = 18.34) evaluated using a two-step cluster analysis. Fours clusters emerged. The most adjusted participants were mostly of a younger age, women and had a high education. The least adjusted participants globally presented low education, poor perceived health, and poor engagement in leisure activities. Well-being focused participants were mostly women of older age, with high education and spirituality. Finally, moderately satisfied participants were mostly men of older age, had a lower education, and presented poor reported health. Complementary comparative analysis among the identified subgroups was performed. The most adjusted participants had the highest perceived overall sexual well-being, sexual attractiveness, sexual openness and communication, and sexual satisfaction. These data characterize the profile of this population and can be used as the basis for developing efficient strategies aimed a combining adjustment to aging, satisfaction with life and sexual satisfaction for tailored interventions to the specific needs of populations across the lifespan.

An Assessment Model of the Algarve as a Sustainable Tourism Destination: A Conceptual Framework

ABSTRACT Sustainable tourism assessment models emphasize the need for holistic, integrated evaluations of tourism destinations, particularly in mature and mass tourism areas. While best practices can be shared, each destination requires a tailored approach, considering its unique features like infrastructure and natural assets. Research shows that sustainable tourism should involve continuous evaluation rather than a one-time assessment. This article develops a model for the ongoing review of sustainable tourism in the Algarve, a famous sun, sea, and sand destination in Portugal. Using qualitative and quantitative methods, the model was designed by analyzing existing frameworks and their relevant dimensions. A questionnaire was then administered to local stakeholders to validate and refine the selected indicators, which were ultimately used to create a framework for monitoring sustainable tourism in the region.

Teachers’ Motivational Skills In Primary Reading

Teachers’ motivational skills in primary reading are essential because they inspire primary learners, foster a love for learning, and contribute to academic success, laying the foundation for lifelong literacy and educational achievement. In this context, this study aimed to determine the level of teachers’ motivational skills at the primary level. The study was tested on 86 primary school teachers using a self-made questionnaire that passed stringent validity and reliability tests. The data were statistically analyzed using the mean, t-test, and analysis of variance. The results revealed that the level of teachers’ motivational skills in attention, confidence, and satisfaction was very high, while the areas of relevance were high. The level of teachers’ motivation skills, when grouped according to the variables above, was lowest in terms of relevance. Further, no significant differences emerged in teachers’ motivational skills when grouped and compared by their profile variables. Notably, the lower motivation in the relevance dimension prompts inquiry into underlying factors affecting its perception. It calls for tailored professional development interventions to address these issues, potentially leading to more effective teaching practices and learner outcomes. Keywords: Teachers’ Motivational Skills, Primary Learners, Education, Valencia, Negros Oriental.

Organisational cyber resilience: a heuristic for bridging foundations and applications

PurposeThe drive for digitalisation has increased the scope of cyber threats which can exploit the growing footprint of information and communication technology infrastructure supporting modern societies. Despite substantial interest and efforts in researching and building organisational cyber resilience, the resulting body of work is heterogeneous and has yet to reach maturity. This paper aims to address the gap in the conceptualisation of cyber resilience in academic and practice-oriented grey literature.Design/methodology/approachIn this conceptual paper, we firstly seek to explore the available foundations of resilience as a construct and consider how these can be applied to organisational cybersecurity. To that aim, this study employs a targeted literature review approach, incorporating systematic elements to ensure rigour. Literature was identified through comprehensive searches in key academic databases, reference chaining and expert recommendations. Articles were selected based on relevance and contribution to the field, resulting in a thematic analysis to identify gaps and propose a heuristic model for cyber resilience. With this approach, we aim to position the emerging view of cyber resilience relative to risk analysis, while highlighting its domain of “conceptual comparative advantage” – the types of applications it is best suited to address. Finally, a high-level heuristic model for cyber resilience is proposed, which functions across the relevant policy, strategy and operational dimensions while also considering its relationship with cyber risk management.FindingsA conceptual model for organisational cyber resilience is proposed which helps position and frame research contributions in this domain relative to risk analysis, highlighting its domain of comparative advantage. The model integrates policy, strategy and operational dimensions, in a manner conducive to bridging foundations and applications of the concept of cyber risk management. The proposed model provides a critical point of reference to evaluate individual models, frameworks and tools.Originality/valueThis paper is a pioneering effort to overcome the current gaps between conceptual and practical views of cyber resilience. It proposes a new, risk-aligned view of the concept of cyber resilience and provides a structural foundation for further research and practice in the field.

Relevance in Three Dimensions: Teaching Religion With the Comparative Method

ABSTRACTThis article argues that three dimensions of relevance can be identified for the academic study of religion as it is taught at the university: (1) Foundations; (2) General Education; and (3) Application. The analytical distinction of these dimensions also reveals that they are inextricably linked and co‐dependent. This model may help to sort out the tasks and opportunities of a secular, comparative study of religion in academia and society. Importantly, for each dimension, the comparative method has a crucial role.

The Role of Relevance in Shaping Perceptions of Sleep Hygiene Games Among University Students: Mixed Methods Study.

Sleep games are an emerging topic in the realm of serious health game research. However, designing features that are both enjoyable and effective at engaging users, particularly university students, to develop healthy sleep habits remains a challenge. This study aims to investigate user preferences for 3 sleep game prototypes, that is, Hero's Sleep Journey, Sleep Tamagotchi, and Sleepland, and to explore their popularity and perceived utility in promoting sleep health. A mixed methods approach was used in this study. Quantitative and qualitative data were collected through a co-design workshop involving 47 university students. Participants were presented with storyboard cards of game features and were asked to provide an overall rating on each game, as well as ratings for individual features. They were also encouraged to provide free-form comments on the features and suggest improvements. In addition, participants were asked to express their preferences among the 3 games regarding which game they would most like to play and which one they found most useful for promoting sleep health. Surprisingly, while Hero's Sleep Journey was the most popular choice among participants, Sleep Tamagotchi was perceived as the most beneficial for improving sleep health. Relevance emerged as an overarching theme in the qualitative data analysis, with 3 interconnected dimensions: psychological relevance to users' personal lives, logical relevance to sleep health, and situational relevance to users' circumstantial context. We discussed how the 3 dimensions of relevance address the autonomy and relatedness constructs outlined in the self-determination theory and proposed 3 design recommendations. Our serious sleep game prototypes demonstrated the potential to engage university students to develop healthy sleep hygiene. Future sleep game designs should aim to create a sense of relevance to users' personal lives, sleep health goals, and situational contexts. Rather than a one-size-fits-all approach, it is essential to develop a wide range of game genres and features to cater to diverse users. Aligning game features with sleep health goals and educating users on the design rationale through sleep knowledge are also important aspects. Furthermore, allowing users to customize their game experience and manage technology boundaries is necessary to nurture a sense of control and autonomy in the process of forming good sleep hygiene.

Enhancing Learning Abilities in Students Using a Cognitive Neuroscience Model Based on Brain-Computer Interface Signal Analysis

Computational intelligence is used to create artificially intelligent systems with the ability to learn, adapt, and solve problems. Learners’ computational abilities can be improved with the help of Cognitive Neuroscience techniques. Computational intelligence refers to the ability of a learner based on the complex operations of the brain in the four relevant dimensions: Visual (V), Aural (A), Kinematic (K), and Reading/Writing (R/W). Our proposed framework consists of electroencephalogram (EEG) data acquisition, signal extraction, and EEG signal categorization to assess students’ cognitive learning abilities. Our proposed approach uses an EEG device equipped with a microprocessor, a Think Gear (TGAM) EEG sensor, and a PCB of 16 dry electrodes. The EEG device and the remote processing device are connected by Bluetooth. The EEG signal provides the students with neurofeedback on their cognitive learning capability. The feedback obtained through the learning process will be endowing to improvise computational intelligence. The statistical derivative, Pearson Co-efficient, is used to find the correlation among the derived attributes. The attributes considered are the learner’s gender, stream, age, and geographical region. The results obtained highlight that gender, stream, and age have no correlation with the detectable learning index, and the most accurate learners are kinesthetic ones. Bi-modal learners, who can maintain focus while reading and using their kinematic abilities, had the second highest learning capacity.

Communication and Organizational Learning in Teachers of Public Educational Institutions

The study focuses on analysing internal communication and organizational learning as current constructs in regular basic education in public educational institutions, establishing the correlation of variables and explaining the level of significance of these interactions in some of their most relevant dimensions. A quantitative approach and correlational design were used for the methodology. The sampling was probabilistic, composed of 172 regular elementary school teachers. The data collection technique was the survey. Spearman's Rho statistic was used to process the information. The conclusion of the study showed that there is a significant inverse relationship between internal communication and organizational learning in the teaching staff, explaining that while internal communication obtained 74.4% of satisfactory mastery, organizational learning reached 7.6% at the high level, which reveals the need and urgency for teachers and managers to innovate strategies to achieve organizational learning, taking as a starting point the high levels of internal communication experienced by the teaching staff in the educational institutions investigated.

Bridging the gap: Innovative human-based in vitro approaches for nanomaterials hazard assessment and their role in safe and sustainable by design, risk assessment, and life cycle assessment

The application of nanomaterials in industry and consumer products is growing exponentially, which has pressed the development and use of predictive human in vitro models in pre-clinical analysis to closely extrapolate potential toxic effects in vivo. The conventional cytotoxicity investigation of nanomaterials using cell lines from cancer origin and culturing them two-dimensionally in a monolayer without mimicking the proper pathophysiological microenvironment may affect a precise prediction of in vitro effects at in vivo level. In recent years, complex in vitro models (also belonging to the new approach methodologies, NAMs) have been established in unicellular to multicellular cultures either by using cell lines, primary cells or induced pluripotent stem cells (iPSCs), and reconstituted into relevant biological dimensions mimicking in vivo conditions. These advanced in vitro models retain physiologically reliant exposure scenarios particularly appropriate for oral, dermal, respiratory, and intravenous administration of nanomaterials, which have the potential to improve the in vivo predictability and lead to reliable outcomes. In this perspective, we discuss recent developments and breakthroughs in using advanced human in vitro models for hazard assessment of nanomaterials. We identified fit-for-purpose requirements and remaining challenges for the successful implementation of in vitro data into nanomaterials Safe and Sustainable by Design (SSbD), Risk Assessment (RA), and Life Cycle Assessment (LCA). By addressing the gap between in vitro data generation and the utility of in vitro data for nanomaterial safety assessments, a prerequisite for SSbD approaches, we outlined potential key areas for future development.

A hierarchical reinforcement learning model explains individual differences in attentional set shifting.

Attentional set shifting refers to the ease with which the focus of attention is directed and switched. Cognitive tasks, such as the widely used CANTAB IED, reveal great variation in set shifting ability in the general population, with notable impairments in those with psychiatric diagnoses. The attentional and learning processes underlying this cognitive ability and how they lead to the observed variation remain unknown. To directly test this, we used a modelling approach on two independent large-scale online general-population samples performing CANTAB IED, with one including additional psychiatric symptom assessment. We found a hierarchical model that learnt both feature values and dimension attention best explained the data and that compulsive symptoms were associated with slower learning and higher attentional bias to the first relevant stimulus dimension. These data showcase a new methodology to analyse data from the CANTAB IED task, as well as suggest a possible mechanistic explanation for the variation in set shifting performance, and its relationship to compulsive symptoms.

Nexus between customer relationship management dimensions, customer involvement and customer retention: a mediation analysis in Ghana’s hotel industry

PurposeThis research investigates the role of customer involvement (CINV) in customer relationship management (CRM) dimensions and customer retention (CR) in Ghana’s hotel industry.Design/methodology/approachThis quantitative-based explanatory research obtained primary data via structured questionnaires from 277 hotel customers in Ghana, processed it with SmartPLS4.0 software, and analysed it with structural equation modelling.FindingsCRM dimensions (CRM-based technology, managing knowledge and personalisation of services) and CINV positively affect CR. Also, CINV partially mediates the interactions between the CRM dimensions and CR in Ghana’s hotel industry.Research limitations/implicationsThe study is geographically limited to hotels in Ghana and conceptually limited to three CRM dimensions, CINV and CR. Methodologically, the study was limited to the quantitative approach. However, our outcomes imply that hotels in Ghana that invest in relevant CRM dimensions would improve CR. CRM-CR association can also be improved through CINV.Practical implicationsThe study outcomes imply that when Ghanaian hotels implement the CRM dimensions and foster active CINV, their customers’ retention will improve significantly. Hence, CRM and CINV are prerequisites for enhancing CR in Ghana’s hotel industry.Originality/valueThe study offers valuable contributions to the current literature on CRM, consumer behaviour and hospitality management, especially in a developing economy context. Its novel contribution, the mediating role of CINV, would advance CRM studies in the hospitality sector.

Explainable Generative AI (GenXAI): a survey, conceptualization, and research agenda

Generative AI (GenAI) represents a shift from AI’s ability to “recognize” to its ability to “generate” solutions for a wide range of tasks. As generated solutions and applications grow more complex and multi-faceted, new needs, objectives, and possibilities for explainability (XAI) have emerged. This work elaborates on why XAI has gained importance with the rise of GenAI and the challenges it poses for explainability research. We also highlight new and emerging criteria that explanations should meet, such as verifiability, interactivity, security, and cost considerations. To achieve this, we focus on surveying existing literature. Additionally, we provide a taxonomy of relevant dimensions to better characterize existing XAI mechanisms and methods for GenAI. We explore various approaches to ensure XAI, ranging from training data to prompting. Our paper provides a concise technical background of GenAI for non-technical readers, focusing on text and images to help them understand new or adapted XAI techniques for GenAI. However, due to the extensive body of work on GenAI, we chose not to delve into detailed aspects of XAI related to the evaluation and usage of explanations. Consequently, the manuscript appeals to both technical experts and professionals from other fields, such as social scientists and information systems researchers. Our research roadmap outlines over ten directions for future investigation.

Development of a novel circular saw blade substrate with high stiffness for mitigating vibration noise and improving sawing performance

The circular saw blade substrates featuring a large diameter-thickness ratio and multiple saw teeth are increasingly required to accomplish the first or second machining tasks with high efficiency in sawing operations. However, the weak bending stiffness of this substrate can easily cause intense vibrations and harsh noises, while its special structure characteristics pose further challenges to vibration mitigation. This research develops a novel circular saw blade substrate with high bending stiffness to improve dynamic stability. Taking the geometric features and boundary conditions of the substrate into account, a transverse vibration differential equation for high-speed sawing operation is established to investigate the relationship between the mode shapes of the substrate and the stability performance of the sawing system. Theoretical analysis shows that the laminated structure can enhance the bending stiffness. Using this finding, the novel substrate is designed equipped with an m-shaped damping cavity and a laminated core structure, and its dynamic performance is quantified by the complex modulus law and thin-plate vibration theory. Then, the optimized design of the relevant materials and geometrical dimensions of the novel substrate is executed by the pseudo-density method. Finally, the novel substrate is fabricated and then certified by sawtooth point dynamics tests and sawing experiments. The experimental results show that the sawing quality of the novel substrate is improved by more than 50.2 %, and the sawing vibration and weighted sound pressure level are reduced by about 35 % and 12 dB(A), respectively, compared with the conventional one.

Auditory objects in working memory include task-irrelevant features

Object-based attention operates both in perception and visual working memory. While the efficient perception of auditory stimuli also requires the formation of auditory objects, little is known about their role in auditory working memory (AWM). To investigate whether attention to one object feature in AWM leads to the involuntary maintenance of another, task-irrelevant feature, we conducted four experiments. Stimuli were abstract sounds that differed on the dimensions frequency and location, only one of which was task-relevant in each experiment. The first two experiments required a match–nonmatch decision about a probe sound whose irrelevant feature value could either be identical to or differ from the memorized stimulus. Matches on the relevant dimension were detected more accurately when the irrelevant feature matched as well, whereas for nonmatches on the relevant dimension, performance was better for irrelevant feature nonmatches. Signal-detection analysis showed that changes of irrelevant frequency reduced the sensitivity for sound location. Two further experiments used continuous report tasks. When location was the target feature, changes of irrelevant sound frequency had an impact on both recall error and adjustment time. Irrelevant location changes affected adjustment time only. In summary, object-based attention led to a concurrent maintenance of task-irrelevant sound features in AWM.

Examining Behavioral Intention to Use Mobile Government Services in Bangladesh: An Empirical View

Purpose: This study aims to identify factors influencing users’ behavioural intentions towards mobile government services. Methodology: We develop a research model with information quality, interaction quality, perceived value, power distance, and perceived compatibility. The structural equation modeling method was used to analyze the data collected through an online survey of 301 participants who are mobile government service users in Bangladesh. Findings: The results of this study show that information quality, interaction quality, perceived value, and perceived compatibility have significant and positive influences on behavioural intention to use mobile government services. Practical Implications: This research identified users' specific requirements and expectations about government services, and the necessary actions that the government should take in the event of dissatisfaction among the public. Moreover, the results indicate that giving users succinct and uncomplicated information suitable for standard mobile phones will motivate them to use mobile government services. Originality/Value: This study significantly contributes to information systems literature, particularly in the domain of mobile government services. Researchers developed an integrated model with the relevant dimensions of mobile government services, explaining the variation in the behavioural intention of mobile government services. Limitations: This research has some limitations. Initially, this investigation was confined only to the geographical boundaries of Bangladesh. Furthermore, the study model considers a limited number of factors that impact individuals' behaviour about their intention to use mobile government services. Most of the respondents are under the 20-30 age range; hence, the conclusions may not be relevant for older individuals.

Feasibility of ultrarelativistic bubbles in SMEFT

A first order electroweak phase transition probes physics beyond the Standard Model on multiple frontiers and therefore is of immense interest for theoretical exploration. We conduct a model-independent study of the effects of relevant dimension 6 and dimension 8 operators, of the Standard Model effective field theory, on electroweak phase transition. We use a thermally corrected and renormalization group improved potential and study its impact on nucleation temperature. We then outline bubble dynamics that lead to ultrarelativistic bubble wall velocities which are mainly motivated from the viewpoint of gravitational wave detection. We highlight the ranges of the Wilson coefficients that give rise to such bubble wall velocities and predict gravitational wave spectra generated by such transitions which can be tested in future experiments. Published by the American Physical Society 2024

On resolution coresets for constrained clustering

Specific data compression techniques, formalized by the concept of coresets, proved to be powerful for many optimization problems. In fact, while tightly controlling the approximation error, coresets may lead to significant speed up of the computations and hence allow to extend algorithms to much larger problem sizes. The present paper deals with a weight-balanced clustering problem, and is specifically motivated by an application in materials science where a voxel-based image is to be processed into a diagram representation. Here, the class of desired coresets is naturally confined to those which can be viewed as lowering the resolution of the input data. While one might expect that such resolution coresets are inferior to unrestricted coreset we prove bounds for resolution coresets which improve known bounds in the relevant dimensions and also lead to significantly faster algorithms in practice.