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Large language models (LLMs) are being integrated into socially assistive robots (SARs) and other conversational agents providing mental health and well-being support. These agents are often designed to sound empathic and supportive in order to maximize user's engagement, yet it remains unclear how increasing the level of supportive framing in system prompts influences safety relevant behavior. We evaluated 6 LLMs across 3 system prompts with varying levels of supportiveness on 80 synthetic queries spanning 4 well-being domains (1440 responses). An LLM judge framework, validated against human ratings, assessed safety and care quality. Moderately supportive prompts improved empathy and constructive support while maintaining safety. In contrast, strongly validating prompts significantly degraded safety and, in some cases, care across all domains, with substantial variation across models. We discuss implications for prompt design, model selection, and domain specific safeguards in SARs deployment.

Virtual Reality (VR) is increasingly being used to support workplace well-being, but many interventions focus narrowly on a single activity or goal. Our work explores how VR can meet the diverse physical and mental needs of knowledge workers. We developed Tranquil Loom, a VR app offering stretching, guided meditation, and open exploration across four environments. The app includes an AI assistant that suggests activities based on users' emotional states. We conducted a two-phase mixed-methods study: (1) interviews with 10 knowledge workers to guide the app's design, and (2) deployment with 35 participants gathering usage data, well-being measures, and interviews. Results showed increases in mindfulness and reductions in anxiety. Participants enjoyed both structured and open-ended activities, often using the app playfully. While AI suggestions were used infrequently, they prompted ideas for future personalization. Overall, participants viewed VR as a flexible, ``drop-in'' tool, highlighting its value for situational rather than prescriptive well-being support.

Traditionally, European social policies have focused on material well-being and social justice, neglecting subjective indicators. This review systematically examines the scientific understanding of well-being, its indicators, and its relationship with governance. It suggests that political systems and institutions significantly impact well-being, and that subjective indicators should be incorporated into public policy decisions. The findings advocate for a more holistic approach to well-being measurement, encompassing both objective and subjective dimensions.

Many logical properties are known to be undecidable for normal modal logics, with few exceptions such as consistency and coincidence with $\mathsf{K}$. This paper shows that the property of being a union-splitting in $\mathsf{NExt}\mathsf{K}$, the lattice of normal modal logics, is decidable, thus answering the open problem [WZ07, Problem 2]. This is done by providing a semantic characterization of union-splittings in terms of finite modal algebras. Moreover, by clarifying the connection to union-splittings, we show that in $\mathsf{NExt}\mathsf{K}$, having a decidable axiomatization problem and being a (un)decidable formula are also decidable. The latter answers [CZ97, Problem 17.3] for $\mathsf{NExt}\mathsf{K}$.

Is emotional well-being monotonically increasing in the level of income or does it reach a plateau at some income threshold, whereafter additional income does not contribute to further well-being? Conflicting answers to this question has been suggested in the academic literature. In a recent paper, using an income threshold of $100,000 per year, Killingsworth et al. (2023) appears to have resolved these conflicts, concluding that emotional well-being is monotonically increasing in income for all but the unhappiest individuals. In this paper, we show that this conclusion is sensitive to the placement of the income threshold at which the relationship between emotional well-being and income is allowed to plateau. Using standard econometric methods, we propose a data-driven approach to detect the placement of the threshold. Using this data-driven income threshold, a flat relationship between household income and emotional well-being above a threshold around $200,000 per year is found. While our analysis relaxes the assumption of a pre-specified income threshold, it relies on a number of other assumptions, which we briefly discuss. We conclude that although the analysis of this paper pr

Sustainable Development Goals (SDGs) give the UN a road map for development with Agenda 2030 as a target. SDG3 "Good Health and Well-Being" ensures healthy lives and promotes well-being for all ages. Digital technologies can support SDG3. Burnout and even depression could be reduced by encouraging better preventive health. Due to the lack of patient knowledge and focus to take care of their health, it is necessary to help patients before it is too late. New trends such as positive psychology and mindfulness are highly encouraged in the USA. Digital Twins (DTs) can help with the continuous monitoring of emotion using physiological signals (e.g., collected via wearables). DTs facilitate monitoring and provide constant health insight to improve quality of life and well-being with better personalization. Healthcare DTs challenges are standardizing data formats, communication protocols, and data exchange mechanisms. As an example, ISO has the ISO/IEC JTC 1/SC 41 Internet of Things (IoT) and DTs Working Group, with standards such as "ISO/IEC 21823-3:2021 IoT - Interoperability for IoT Systems - Part 3 Semantic interoperability", "ISO/IEC CD 30178 - IoT - Data format, value and coding". T

We propose WIBA, a novel framework and suite of methods that enable the comprehensive understanding of "What Is Being Argued" across contexts. Our approach develops a comprehensive framework that detects: (a) the existence, (b) the topic, and (c) the stance of an argument, correctly accounting for the logical dependence among the three tasks. Our algorithm leverages the fine-tuning and prompt-engineering of Large Language Models. We evaluate our approach and show that it performs well in all the three capabilities. First, we develop and release an Argument Detection model that can classify a piece of text as an argument with an F1 score between 79% and 86% on three different benchmark datasets. Second, we release a language model that can identify the topic being argued in a sentence, be it implicit or explicit, with an average similarity score of 71%, outperforming current naive methods by nearly 40%. Finally, we develop a method for Argument Stance Classification, and evaluate the capability of our approach, showing it achieves a classification F1 score between 71% and 78% across three diverse benchmark datasets. Our evaluation demonstrates that WIBA allows the comprehensive unde

Emotion detection is an established NLP task of demonstrated utility for text understanding. However, basic emotion detection leaves out key information, namely, who is experiencing the emotion in question. For example, it may be the author, the narrator, or a character; or the emotion may correspond to something the audience is supposed to feel, or even be unattributable to a specific being, e.g., when emotions are being discussed per se. We provide the ABBE corpus -- Animate Beings Being Emotional -- a new double-annotated corpus of texts that captures this key information for one class of emotion experiencer, namely, animate beings in the world described by the text. Such a corpus is useful for developing systems that seek to model or understand this specific type of expressed emotion. Our corpus contains 30 chapters, comprising 134,513 words, drawn from the Corpus of English Novels, and contains 2,010 unique emotion expressions attributable to 2,227 animate beings. The emotion expressions are categorized according to Plutchik's 8-category emotion model, and the overall inter-annotator agreement for the annotations was 0.83 Cohen's Kappa, indicating excellent agreement. We descr

For most health or well-being interventions, the process of evaluation is distinct from the activity itself, both in terms of who is involved, and how the actual data is collected and analyzed. Tangible interaction affords the opportunity to combine direct and embodied collaboration with a holistic approach to data collection and evaluation. We demonstrate this potential by describing our experiences designing and using the Communal Loom, an artifact for art therapy that translates quantitative data to collectively woven artifacts.

In this article, we describe the endomorphism ring of a finitely generated progenerator module of a weighted Leavitt path algebra $L_{K}(E, w)$ of a finite vertex weighted graph $(E, w)$. Contrary to the case of Leavitt path algebras, we show that a (full) corner of a weighted Leavitt path algebra is, in general, not isomorphic to a weighted Leavitt path algebra. However, using the above result, we show that for every full idempotent $ε$ in $L_{K}(E, w)$, there exists a positive integer $n$ such that $M_n(εL_{K}(E, w) ε)$ is isomorphic to the weighted Leavitt path algebra of a weighted graph explicitly constructed from $(E, w)$. We then completely describe unital algebras being Morita equivalent to weighted Leavitt path algebras of vertex weighted graphs. In particular, we characterize unital algebras being Morita equivalent to sandpile algebras.

Users increasingly face multiple interface features on one hand, and constraints on available resources (e.g., time, attention) on the other. Understanding the sensitivity of users' well-being to feature type and resource constraints, is critical for informed design. Building on microeconomic theory, and focusing on social information features, users' interface choices were conceptualized as an exchange of resources (e.g., time), in return for access to goods (social information features). We studied how sensitive users' well-being is to features' type, and to their cost level and type. We found that (1) increased cost of feature use leads to decreased well-being, (2) users' well-being is a function of features' cost type, and (3) users' well-being is sensitive to differences in feature type. The approach used here to quantify user well-being derived from interface features offers a basis for asynchronous feature comparison.

The criminalization of poverty has been widely denounced as a collective bias against the most vulnerable. NGOs and international organizations claim that the poor are blamed for their situation, are more often associated with criminal offenses than the wealthy strata of society and even incur criminal offenses simply as a result of being poor. While no evidence has been found in the literature that correlates poverty and overall criminality rates, this paper offers evidence of a collective belief that associates both concepts. This brief report measures the societal bias that correlates criminality with the poor, as compared to the rich, by using Natural Language Processing (NLP) techniques in Twitter. The paper quantifies the level of crime-poverty bias in a panel of eight different English-speaking countries. The regional differences in the association between crime and poverty cannot be justified based on different levels of inequality or unemployment, which the literature correlates to property crimes. The variation in the observed rates of crime-poverty bias for different geographic locations could be influenced by cultural factors and the tendency to overestimate the equalit

The article reviews the history of well-being to gauge how subjective question surveys can improve our understanding of well-being in Mexico. The research uses data at the level of the 32 federal entities or States, taking advantage of the heterogeneity in development indicator readings between and within geographical areas, the product of socioeconomic inequality. The data come principally from two innovative subjective questionnaires, BIARE and ENVIPE, which intersect in their fully representative state-wide applications in 2014, but also from conventional objective indicator sources such as the HDI and conventional surveys. This study uses two approaches, a descriptive analysis of a state-by-state landscape of indicators, both subjective and objective, in an initial search for stand-out well-being patterns, and an econometric study of a large selection of mainly subjective indicators inspired by theory and the findings of previous Mexican research. Descriptive analysis confirms that subjective well-being correlates strongly with and complements objective data, providing interesting directions for analysis. The econometrics literature indicates that happiness increases with incom

We study "how far away" a finite index subgroup G of SL(2,Z) is from being a congruence group. For this we define its deficiency of being a congruence group. We show that the index of the image of G in SL(2,Z/nZ) is biggest, if n is the general Wohlfahrt level. We furthermore show that the Veech groups of origamis (or square-tiled surfaces) in the stratum H(2) are far away from being congruence groups and that in each genus one finds an infinite family of origamis such that they are "as far as possible" from being a congruence group.

The state of being alone can have a substantial impact on our lives, though experiences with time alone diverge significantly among individuals. Psychologists distinguish between the concept of solitude, a positive state of voluntary aloneness, and the concept of loneliness, a negative state of dissatisfaction with the quality of one's social interactions. Here, for the first time, we conduct a large-scale computational analysis to explore how the terms associated with the state of being alone are used in online language. We present SOLO (State of Being Alone), a corpus of over 4 million tweets collected with query terms 'solitude', 'lonely', and 'loneliness'. We use SOLO to analyze the language and emotions associated with the state of being alone. We show that the term 'solitude' tends to co-occur with more positive, high-dominance words (e.g., enjoy, bliss) while the terms 'lonely' and 'loneliness' frequently co-occur with negative, low-dominance words (e.g., scared, depressed), which confirms the conceptual distinctions made in psychology. We also show that women are more likely to report on negative feelings of being lonely as compared to men, and there are more teenagers amon

A four-pronged approach to dealing with Social Science Phenomenon is outlined. This methodology is applied to Financial Services, Economic Growth and Well-Being. The four prongs are like the four directions for an army general looking for victory. Just like the four directions, we need to be aware that there is a degree of interconnectedness in the below four prongs. -Uncertainty Principle of the Social Sciences -Responsibilities of Fiscal Janitors -Need for Smaller Organizations -Redirecting Growth that Generates Garbage The importance of gaining a more profound comprehension of welfare and delineating its components into those that result from an increase in goods and services, and hence can be attributed to economic growth, and into those that are not related to economic growth but lead to a better quality of life, is highlighted. The reasoning being that economic growth alone is an inadequate indicator of well-being. Hand in hand with a better understanding of the characteristics of welfare, comes the need to consider the metrics we currently have that gauge economic growth and supplement those with measures that capture well-being more holistically.

As a subject, an observer is fundamentally at rest in a reference frame, and this being at rest allows for measuring the motion of physical objects. Exploring the experience of centrifugal force brings to the fore the natural inclination to see oneself at rest in a reference frame. The discrepancy between the experience of centrifugal force and its lack of fundamental significance in Newton's laws of motion points toward the importance of the observer as a subject in his or her own reference frame, specifically the observer's experience of being at rest in this reference frame. In addition, the observer's being at rest for himself or herself in a reference frame is a central feature of both special and general relativity.

Well-being is a relatively broad concept which can be succinctly described as the state of being happy, healthy or successful. Interesting things happen when bridging user interface design with the psychology of human well-being. This position paper aims at providing a short on reflection the challenges and opportunities in this context and presents concrete examples on how to tackle these challenges and exploit the existing design opportunities.

Artificial intelligence (AI) enabled products and services are becoming a staple of everyday life. While governments and businesses are eager to enjoy the benefits of AI innovations, the mixed impact of these autonomous and intelligent systems on human well-being has become a pressing issue. This article introduces one of the first international standards focused on the social and ethical implications of AI: The Institute of Electrical and Electronics Engineering (IEEE) Standard (Std) 7010-2020 Recommended Practice for Assessing the Impact of Autonomous and Intelligent Systems on Human Well-being. Incorporating well-being factors throughout the lifecycle of AI is both challenging and urgent and IEEE 7010 provides key guidance for those who design, deploy, and procure these technologies. We begin by articulating the benefits of an approach for AI centered around well-being and the measurement of well-being data. Next, we provide an overview of IEEE 7010, including its key principles and how the standard relates to approaches and perspectives in place in the AI community. Finally, we indicate where future efforts are needed.