Eudaimonic HCI: a research agenda for designing technologies that support purpose, growth, and meaning

Abstract

The field of Human-Computer Interaction (HCI) has increasingly turned its attention to “digital wellbeing," yet the discourse remains narrowly focused. A significant portion of current research concentrates on mitigating the negative effects of technology—such as addiction, anxiety, and the harms of excessive screen time—or on a limited set of wellbeing domains, primarily social connection and physical health. This paper identifies a critical research gap: the need to move beyond a fragmented, nascent focus on eudaimonic wellbeing toward a systematic research agenda. Eudaimonia encompasses deeper aspects of human flourishing such as purpose, personal growth, reflection, and meaning. Through an extensive literature review, this paper confirms that while pioneering efforts exist, these eudaimonic domains remain significantly under-researched within mainstream HCI. In response, this paper proposes a new research agenda aimed at establishing “Eudaimonic HCI” as a critical sub-field. It articulates key open research questions concerning measurement, design patterns, human-AI collaboration, and the specific needs of vulnerable populations, aiming to unify and build upon current foundational work. Finally, it introduces a preliminary design framework to guide the creation of technologies that move beyond optimizing for engagement and instead aim to actively support users in living more meaningful and fulfilling lives.

1 Introduction

Digital technologies are inextricably woven into the fabric of modern life, mediating our work, sociality, and sense of self (Kurniawan, 2004). This pervasiveness has given rise to a growing field of inquiry within Human-Computer Interaction (HCI) focused on “digital wellbeing." This focus represents the latest stage in the evolution of HCI's concerns, which have expanded from the narrow ergonomics and usability of the “first wave” to the broader cognitive and experiential aspects of the “second wave," and now to the complex, value-laden, and societal implications of technology in what has been termed the “third wave” (Bødker, 2015).

However, the prevailing narrative surrounding digital wellbeing is often reactive and conceptually narrow. Much of the discourse is framed around mitigating harms—combating “screen time," digital addiction, fear of missing out, and the spread of misinformation—or is concentrated on a few well-trodden domains of wellbeing, such as fostering social connections and promoting physical health (Bhattacharya et al., 2023; Orben, 2020). While important, this focus overlooks a deeper, more profound dimension of human flourishing known as eudaimonia.

Distinct from hedonic wellbeing, which relates to pleasure, happiness, and positive affect, eudaimonic wellbeing is concerned with self-actualization, personal growth, and finding a sense of purpose and meaning in one's life (Desmet and Pohlmeyer, 2013; Huta and Waterman, 2014; Ryan and Deci, 2001). Academic analyses highlight that HCI has paid relatively little attention to domains such as reflection, competence, growth, and purpose compared to hedonic or harm-focused aspects (Peters et al., 2018). This oversight represents a significant research gap and a missed opportunity for the field.

By defaulting to metrics of engagement, efficiency, and hedonic satisfaction, current design paradigms may fail to support, or even inadvertently undermine, the human need for a meaningful existence (Vermeeren et al., 2010; Twenge, 2019). The optimization for attention and engagement, core to the business models of many technology companies, can create environments that foster distraction over reflection and consumption over creation, which are antithetical to eudaimonic pursuits (Pang, 2013). The central challenge for HCI is no longer just to make technology usable or enjoyable, but to make it an instrument for human flourishing (Calvo and Peters, 2014; Gorichanaz, 2022).

This paper seeks to address this gap directly by proposing a dedicated research agenda for what we term “Eudaimonic HCI." Our central thesis is that for HCI to meaningfully contribute to human wellbeing, it must expand its conceptual vocabulary and design repertoire beyond the hedonic, while integrating insights from established value-oriented traditions. This requires a deliberate shift from designing systems that merely capture attention or provide fleeting pleasure to creating technologies that empower individuals to lead more reflective, purposeful, and self-authored lives.

This constitutes a fundamental contribution to the “Seven HCI Grand Challenges," particularly the challenge of “Wellbeing, Health, and Eudaimonia," by providing a concrete roadmap for the hitherto underdeveloped “Eudaimonia” component (Stephanidis et al., 2019). To build this argument, we first conduct an extensive literature review to substantiate the claim that eudaimonic domains, while the subject of recent pioneering work, remain under-explored in mainstream HCI. We contrast the field's current focus on harm mitigation and engagement with the rich theoretical foundations of eudaimonia from psychology, situating it within contemporary debates on digital wellbeing.

We then propose a research agenda structured around four key pillars to unify and build upon these foundational efforts: (1) defining and measuring eudaimonic outcomes, (2) identifying design patterns that foster eudaimonic experiences, (3) exploring the role of Human-AI Collaboration in supporting eudaimonic goals, and (4) addressing the critical ethical and inclusivity challenges inherent in this work. Finally, we offer a preliminary design framework intended to provide practitioners with actionable principles for creating technologies that support purpose, reflection, and personal growth, explicitly linked to traditions like Positive Technology and Value-Sensitive Design. By charting this course, we aim to catalyze a new direction for HCI research and practice—one that moves beyond engagement to embrace the full spectrum of human flourishing.

2 Literature review: the imbalance in digital wellbeing research

To synthesize the state of the field, we conducted a systematic literature review following PRISMA guidelines (Page et al., 2021). We searched databases including ACM Digital Library, Google Scholar, IEEE Xplore, and PsycINFO using keywords such as “digital wellbeing," “eudaimonic HCI," “positive computing," “human flourishing design," and “value-sensitive design for wellbeing” (2010–2025). Inclusion criteria focused on peer-reviewed articles, proceedings, and books addressing HCI and wellbeing constructs. From 1,200 initial results, we screened 450 abstracts and included 120 full texts for thematic analysis, identifying imbalances and opportunities.

The evolution of HCI can be seen as a progressive broadening of its core concerns, from the technical usability of an interface, to the holistic user experience (UX), and now to the societal and personal implications of technology use (Ebert et al., 2012). The recent focus on digital wellbeing is a natural extension of this trajectory. However, a closer examination of the literature reveals a significant conceptual imbalance, with a heavy emphasis on hedonic concerns and harm mitigation at the expense of a deeper engagement with eudaimonic flourishing, despite growing diversity in value-oriented approaches (Schneider et al., 2018; Peters et al., 2018; Desmet and Hassenzahl, 2012; Pohlmeyer, 2017).

2.1 Conceptual foundations of digital wellbeing

Contemporary debates in positive psychology and cyberpsychology conceptualize digital wellbeing not as a unified construct but as multifaceted and dynamic (Büchi, 2024; Vanden Abeele, 2020; Fortuna, 2023). Happiness is often narrowly tied to hedonic pleasure (positive affect and absence of pain) (Waterman, 1993), while wellbeing encompasses broader psychological functioning, including both hedonic and eudaimonic elements (Ryan and Deci, 2001).

Following (Büchi 2024), we conceptualize digital wellbeing not as a unitary outcome but as an analytical framework encompassing digital practices (technology use behaviors), proximal outcomes (immediate benefits and harms of use), and distal outcomes (long-term effects on wellbeing). Within this framework, eudaimonic digital wellbeing specifically addresses the distal outcome of eudaimonic flourishing, while also attending to the quality of digital practices that support eudaimonic processes. Complementing this, (Vanden Abeele 2020) conceptualizes digital wellbeing as a dynamic equilibrium, where technology use can both disrupt and restore balance in individuals' lives. This processual understanding is particularly relevant for eudaimonic concerns, which involve ongoing processes of meaning-making and growth rather than static outcomes.

More recently, (Chen et al. 2025) have employed a network approach to digital wellbeing, revealing interconnections between cognitive, affective, and behavioral components, with competency emerging as a central node. This finding underscores the relevance of eudaimonic constructs like competence and personal growth to overall digital wellbeing.

Hedonic wellbeing prioritizes pleasure and engagement (e.g., flow states), whereas eudaimonic wellbeing emphasizes virtue, authenticity, and self-actualization (Huta and Waterman, 2014). Empirically, these are differentiated via scales like Ryff's (eudaimonic focus) vs. hedonic affect measures, with eudaimonia correlating more strongly with long-term life satisfaction (Ryff and Keyes, 1995). Digital wellbeing operationalizations include network models for interdependencies (Chen et al., 2025) and ethical frameworks for good digital lives (Burr et al., 2020).

In this paper, we treat eudaimonic digital wellbeing primarily as an analytical framework for examining how technology use can support or hinder eudaimonic flourishing, rather than as a subjective indicator of technology quality. This framework encompasses both the processes (digital practices designed to foster eudaimonic experiences) and outcomes (changes in users' sense of purpose, growth, and meaning) of technology-mediated eudaimonic pursuits. We deliberately avoid treating eudaimonic digital wellbeing as merely “eudaimonic wellbeing that happens to involve technology,” because this would indeed reduce psychological processes to their modes of elicitation. Instead, we argue that the technological context fundamentally shapes the nature of these processes—for example, AI systems that scaffold reflection operate differently from human mentors, offering both new possibilities (scale, personalization) and new risks (threats to autonomy, algorithmic bias). The technological mediation is not incidental but constitutive of the eudaimonic experience, requiring specific design considerations that general psychological models do not address.

Our notion of eudaimonic digital wellbeing thus specifies the eudaimonic subset within this broader analytical landscape: it refers to an integrated system encompassing (1) digital practices intentionally oriented toward eudaimonic goals (e.g., reflective journaling, purpose-oriented social networking), (2) the design logics and technological affordances that shape these practices (e.g., AI-mediated reflection scaffolds, value-sensitive architectures), (3) proximal eudaimonic experiences during technology use (e.g., moments of insight, authentic self-expression), and (4) distal eudaimonic outcomes that may accrue over time (e.g., increased sense of purpose, personal growth).

By “technology-mediated processes,” we refer to sequences of interaction between users and digital systems that are intentionally designed to scaffold or support eudaimonic experiences. These include, for example, reflective prompts in journaling applications that encourage users to connect daily activities to life goals, AI-mediated feedback loops in learning platforms that support competence development, or social networking features designed to foster authentic connection rather than superficial engagement. These processes correspond to what (Büchi 2024) terms “digital practices”—the specific ways individuals engage with technology—but with the additional specification that they are designed with eudaimonic intentions.

Within positive psychology, wellbeing is often used as an umbrella term encompassing both hedonic and eudaimonic dimensions (Ryan and Deci, 2000), while flourishing refers specifically to optimal human functioning across multiple domains, including purpose, relationships, and personal growth (Seligman, 2011; Ryff, 1989). To maintain conceptual precision, we restrict our use of “flourishing” to contexts where authors explicitly employ this term, and otherwise use “eudaimonic wellbeing” to denote the specific dimension concerned with meaning, purpose, and growth.

By “perceived meaning in interactions,” we refer to the subjective experience of an interaction with a digital system as being significant, valuable, or connected to one's broader life goals and values. This draws on the Eudaimonic Interaction Inventory (Jörs and De Luca, 2024), which operationalizes meaning in technology interaction through dimensions such as “connectedness to values” and “sense of purpose.” It is distinct from measures of engagement or satisfaction in that it captures the user's evaluation of whether the interaction contributed to their sense of a meaningful life, rather than merely being enjoyable or absorbing.

Extending (Büchi 2024) framework to focus specifically on eudaimonic flourishing, we propose that eudaimonic digital wellbeing can be understood as operating across three interconnected levels:

• Eudaimonic digital practices: technology use behaviors specifically oriented toward eudaimonic goals, such as engaging with reflective journaling apps, participating in online communities focused on personal growth, or using VR for perspective-taking experiences. These correspond to Büchi's “digital practices” but with explicit eudaimonic intentionality.

• Proximal eudaimonic outcomes: immediate experiences during or immediately following technology use that reflect eudaimonic qualities, such as moments of insight, feelings of authentic self-expression, or experiences of being challenged to grow. These correspond to Büchi's “proximal outcomes” (benefits and harms) but specifically capture the eudaimonic dimension of these immediate experiences.

• Distal eudaimonic outcomes: long-term changes in users' eudaimonic wellbeing, such as increased sense of purpose, personal growth, or self-acceptance, that can be attributed (at least in part) to sustained engagement with eudaimonically-designed technologies. These correspond to Büchi's “distal outcomes” but focus specifically on eudaimonic dimensions of flourishing.

This framework acknowledges that the relationship between these levels is dynamic and reciprocal: eudaimonic digital practices generate proximal eudaimonic outcomes, which over time contribute to distal eudaimonic outcomes, which in turn influence future practices. It also recognizes that not all technology use with eudaimonic intentions will produce positive outcomes—poorly designed systems may produce proximal frustration or confusion that undermines rather than supports flourishing.

2.2 The prevailing paradigm: hedonism, engagement, and harm mitigation

The contemporary discourse on digital wellbeing within HCI is dominated by two primary currents: the mitigation of negative outcomes and the optimization of hedonic experiences, often measured through engagement metrics. The first current addresses the “dark side” of technology, focusing on problems such as digital addiction, fear of missing out, technostress, and the negative mental health impacts of social media (Vanden Abeele, 2020; Twenge, 2019). This research has produced valuable insights into the risks of unhealthy digital behaviors and has led to design interventions aimed at reducing harm, such as screen time dashboards and digital detox applications (Vanden Abeele, 2020).

However, an exclusive focus on ill-being risks medicalizing our relationship with technology, overlooking the factors that foster positive and fulfilling digital experiences (Vanden Abeele, 2020). It positions technology primarily as a source of problems to be solved, rather than as a potential tool for self-actualization. The second, and more commercially prevalent, current is the focus on hedonic wellbeing, which is concerned with maximizing pleasure, enjoyment, and positive affect (Huta and Waterman, 2014; Waterman, 1993). In UX design, this often translates into a focus on creating “delightful” and “engaging” experiences (Vermeeren et al., 2010; Calvo and Peters, 2014). Success in this paradigm is typically measured through engagement metrics such as session duration, daily active users, user retention rates, and click-through rates (O'Brien and Toms, 2008). While these metrics are valuable for business objectives, they are poor proxies for genuine wellbeing. A high session duration could indicate a user is in a state of “flow," but it could equally indicate they are struggling with a task or trapped in a cycle of mindless scrolling (Twenge, 2019).

This focus on engagement can lead to the design of systems that are optimized to capture and hold user attention, often using ‘dark patterns' that exploit cognitive biases, rather than to enrich users' lives. Systematic mapping of work on digitalization and wellbeing confirms this conceptual skew, revealing that research coverage is often heavily concentrated in domains like emotional or social wellbeing, compared to eudaimonic aspects like growth or purpose (Peters et al., 2018). This focus is reflected in the technologies commonly studied, such as social media platforms, fitness trackers, and mindfulness apps for stress management. While this work is vital, it predominantly addresses either the mitigation of negative states or the optimization of hedonic and functional aspects of life. The positive, generative aspects of human flourishing—the core of eudaimonia—remain largely at the periphery, though complemented by emerging value-driven paradigms (Desmet and Hassenzahl, 2012; Pohlmeyer, 2017).

2.3 Overview of existing value-oriented design frameworks in HCI

To contextualize our agenda, Table 1 summarizes key existing frameworks for designing for human flourishing and values in HCI. These provide foundational building blocks, which our work synthesizes and extends toward eudaimonic specificity. The frameworks are organized chronologically to show the evolution of value-oriented design in HCI.

2.4 Defining and situating eudaimonia for HCI

To address this gap, it is necessary to first define eudaimonia in a way that is actionable for HCI. The concept originates with Aristotle, who argued that the ultimate goal of life is not simply to feel pleasure (hedonia), but to live a life of virtue and excellence in accordance with one's true self (daimon) (Waterman, 1993; Hursthouse, 2017). Eudaimonia is thus not a fleeting emotional state, but an ongoing process of self-actualization and living a meaningful life (Desmet and Pohlmeyer, 2013; Ryan and Deci, 2001). In modern psychology, this philosophical concept has been operationalized through several influential theories.

Carol Ryff's Six-Factor Model of Psychological Wellbeing is one of the most comprehensive, identifying six key dimensions of a flourishing life: Self-Acceptance, Personal Growth, Purpose in Life, Positive Relations with Others, Environmental Mastery, and Autonomy (Ryff, 1989; Ryff and Keyes, 1995). Another foundational theory is Deci and Ryan's Self-Determination Theory (SDT), which posits that all humans have three innate and universal psychological needs: autonomy, competence, and relatedness (Ballou et al., 2022; Ryan and Deci, 2000). According to SDT, the satisfaction of these needs is essential for psychological growth, integrity, and wellbeing (Bennett and Mekler, 2024). A third influential framework is (Seligman 2011)'s PERMA model of wellbeing, which identifies five core elements: Positive Emotion, Engagement (flow), Relationships, Meaning, and Accomplishment. These theories provide a rich and empirically validated vocabulary for discussing wellbeing that goes far beyond simple pleasure or engagement. They offer concrete constructs—such as personal growth, purpose, and autonomy—that can serve as explicit design goals for a new class of technologies, aligned with Positive Technology traditions that design e-experiences for flourishing (Riva, 2012).

2.5 The nascent field of eudaimonic HCI

The “Eudaimonia” component of HCI's Grand Challenges remains significantly underdeveloped compared to other areas of wellbeing research (Stephanidis et al., 2019). However, this is not to say a gap exists in a vacuum. Rather, we are witnessing the emergence of a nascent field. Pioneering efforts have begun to lay the crucial groundwork. For instance, early conceptual work sought to distinguish the facets of eudaimonic UX from purely hedonic experiences (Müller et al., 2015). More recently, researchers have started to develop and validate the specific measurement tools needed for empirical investigation, such as the Eudaimonic Interaction Inventory (EII), which measures meaning, excellence, authenticity, and growth in technology interaction (Jörs and De Luca, 2024; Wozniak et al., 2023).

Theoretically, bridges are being built between HCI and the psychological foundations of eudaimonia. Work connecting autonomous motivation in UX to Self-Determination Theory provides a robust theoretical lens for this research (Bennett and Mekler, 2024). Ethically, scholars have begun applying virtue ethics to HCI, providing a normative framework for designing a “future worth wanting” that is inherently eudaimonic (Gorichanaz, 2022).

In locating these pioneering efforts within (Büchi 2024) framework, it is essential to maintain the distinction between proximal and distal outcomes. Self-Determination Theory (Ryan and Deci, 2000) and its application in HCI through frameworks like METUX (Peters et al., 2018) primarily address proximal processes and outcomes—the immediate satisfaction of autonomy, competence, and relatedness needs during technology use. These proximal experiences are theorized to contribute over time to distal eudaimonic outcomes such as those captured by (Ryff 1989)'s model (purpose, personal growth, self-acceptance). (Vanden Abeele 2020)'s dynamic equilibrium model similarly operates largely at the proximal level, describing how technology use can temporarily disrupt or restore equilibrium. When we discuss eudaimonic HCI as a nascent field, we are concerned with both levels: designing for proximal eudaimonic experiences (the immediate sense of insight, authenticity, or connection) and, through them, supporting distal eudaimonic outcomes (long-term personal growth and purpose).

Despite these crucial foundational pillars, these efforts remain fragmented and have not yet coalesced into a systematic, central focus for the field. The relative lack of attention to domains like growth and purpose compared to other wellbeing aspects is evident in broader reviews (Peters et al., 2018). Furthermore, the existing work has not yet been translated into widely adopted design frameworks or addressed complex new challenges, such as the role of AI. This paper argues for a research agenda that synthesizes these pioneering efforts and provides a roadmap to elevate Eudaimonic HCI from a niche interest to a core concern of the field.

Building on (Büchi 2024) analytical framework and (Vanden Abeele 2020)'s dynamic model, the research agenda we propose addresses all three levels of eudaimonic digital wellbeing: it calls for research on eudaimonic digital practices (design patterns), proximal eudaimonic outcomes (measurement), and distal eudaimonic outcomes (longitudinal evaluation), while also attending to the dynamic interplay between these levels. The agenda further recognizes, following Vanden Abeele, that eudaimonic digital wellbeing is not a static state but an ongoing process of equilibrium that must be supported over time.

3 A research agenda for eudaimonic HCI

To address the identified gap, we propose a research agenda with four key pillars. These pillars are framed as open research questions that the HCI community must collectively address to build a theoretical and methodological foundation for designing eudaimonic technologies. Table 2 provides an overview of this agenda.

3.1 RQ1: how can we define and measure eudaimonic outcomes in sociotechnical systems?

A fundamental challenge for Eudaimonic HCI is the development of appropriate evaluation methods. Here we must distinguish between two levels of measurement that correspond to the proximal-distal distinction introduced earlier:

1. Measurement of proximal eudaimonic outcomes: These are immediate or near-immediate experiences during technology use that reflect eudaimonic qualities—moments of insight, feelings of authentic self-expression, experiences of being challenged to grow. This level is methodologically appropriate for HCI research, as these outcomes can be linked directly to specific design features and assessed through experience sampling, post-task questionnaires, or physiological proxies. Building on foundational work like the Eudaimonic Interaction Inventory (EII; Jörs and De Luca, 2024) and METUX scales (Peters et al., 2018), this agenda calls for further development of instruments that capture proximal eudaimonic constructs.

2. Measurement of distal eudaimonic outcomes: These are longer-term changes in users' eudaimonic wellbeing—increased sense of purpose, personal growth, self-acceptance—that may be influenced by sustained engagement with eudaimonically-designed technologies. While HCI researchers can contribute to measuring these outcomes, doing so requires longitudinal designs (Thomson and McLeod, 2015; Kjeldskov and Paay, 2012), collaboration with psychologists, and careful attention to attribution. The primary focus of Eudaimonic HCI should be on proximal outcomes that are within the field's methodological expertise, while remaining cognizant of their hypothesized relationship to distal outcomes.

Current UX metrics, such as task completion time, error rates, and user satisfaction scores, are designed to measure usability and hedonic quality, not eudaimonic constructs (Vermeeren et al., 2010; O'Brien and Toms, 2008). This agenda therefore calls for adapting existing psychological scales for HCI contexts, exploring behavioral and physiological proxies for eudaimonic states (Pirzadeh et al., 2013; Alim and Imtiaz, 2023), and employing longitudinal, mixed-methods approaches to capture the long-term, nuanced nature of human flourishing (Thomson and McLeod, 2015; Kjeldskov and Paay, 2012).

3.2 RQ2: what are the design patterns that foster reflection, purpose, and growth?

The HCI community needs to identify, catalog, and evaluate a new set of design patterns that explicitly support eudaimonic pursuits. This moves beyond persuasive technologies designed for simple behavior change to interactions that scaffold more complex internal processes (Fogg, 2002; Spahn, 2012). One key area of exploration involves creating interfaces for reflection and self-awareness, sometimes termed “contemplative computing," which seek to foster mindfulness rather than distraction (Pang, 2013; Sengers et al., 2005; Sharmin and Bailey, 2013; Fleck and Fitzpatrick, 2010).

Furthermore, research should investigate technologies for personal growth and competence, designing for “productive challenge” by scaffolding skill acquisition in areas like creative software or immersive learning environments (Slater and Sanchez-Vives, 2020; Foreman, 2022; Riva, 2012). Another crucial avenue is the development of systems for purpose and meaning-making, helping users connect their daily actions to their core values, an approach informed by methodologies like Value-Sensitive Design (Friedman and Hendry, 2019; Friedman, 1997; Jacko, 2012; Wozniak et al., 2023; Yoo et al., 2013). Finally, the agenda must address eudaimonic sociality, shifting the focus from the quantity of social connections to the quality, designing platforms that foster deep, authentic, and supportive relationships, drawing on liminal and possibility-driven designs (Liedgren et al., 2023; Desmet and Hassenzahl, 2012).

3.3 RQ3: how can human-AI collaboration be designed to support eudaimonic goals?

The paradigm of Artificial Intelligence (AI) is shifting from a tool to a teammate, presenting a unique opportunity to design AI as a partner in the pursuit of a meaningful life (Gupta et al., 2022; Dellermann et al., 2021; Seeber et al., 2020; van der Maden et al., 2023). A primary question concerns how we can design AI collaborators that act as coaches, mentors, or reflective partners without undermining user autonomy, ensuring the user always feels empowered and in control (Calvo et al., 2020; Formosa and Ryan, 2021; Passmore and Olafsson, 2024). This leads to the challenge of defining operational control mechanisms and interaction patterns that allow for a fluid negotiation of agency, where users can easily guide, correct, and understand the AI's reasoning (Licklider, 1960; Liu, 2025; Kadenhe et al., 2024). Concurrently, we must determine the appropriate level of transparency and explainability for an AI system offering guidance on deeply personal matters, ensuring that explanations are not only technically accurate but also emotionally sensitive (Adadi and Berrada, 2018). Lastly, the potential of generative agents and interactive simulacra must be explored as tools for eudaimonic exploration, allowing users to explore different life paths or practice difficult conversations, while carefully navigating the immense ethical risks involved (Park et al., 2023).

3.4 RQ4: How can we design for eudaimonia inclusively and ethically?

A sense of purpose is a universal human need, but its expression is culturally and individually specific. A critical research area is understanding how to design eudaimonic technologies that are sensitive to diverse backgrounds, abilities, and value systems (Peters et al., 2018). This requires a commitment to co-design and participatory methods, especially when working with vulnerable or marginalized communities, to ensure that these technologies are empowering, not prescriptive (Vines et al., 2016; Balki et al., 2022). Imposing a Silicon Valley-centric view of a “good life” would be a profound ethical failure.

Furthermore, systems that engage with a user's core values and purpose have profound ethical implications, a point underscored by recent work applying virtue ethics to HCI (Gorichanaz, 2022). There is a significant risk of what could be termed “eudaimonic washing," where companies use the language of flourishing to mask manipulative designs (Spahn, 2012). Therefore, Eudaimonic HCI must be grounded in robust ethical frameworks, implementing “privacy by design” and a focus on algorithmic fairness to protect sensitive personal data and avoid steering individuals toward stereotypical life paths (Mesarčík et al., 2021; Floridi and Cowls, 2022; Mittelstadt, 2023; Jobin et al., 2019).

4 A preliminary design framework for eudaimonic HCI

To translate the research agenda into practice, we propose a preliminary framework with five guiding principles. These principles are not arbitrary; they are derived from a systematic mapping of the eudaimonic constructs discussed earlier onto the design space. We organize them according to their primary level of analysis within (Büchi 2024) framework:

• Principles 1 and 2 (design for reflection; design for autonomy) address digital practices and design logics—they concern how users engage with technology and how systems are structured to support self-awareness and self-direction.

• Principles 3 and 5 (design for growth; design for relatedness) address proximal eudaimonic outcomes—they target the immediate experiences of competence development and authentic connection during technology use.

• Principle 4 (design for purpose) addresses the bridge between proximal experiences and distal eudaimonic outcomes—it focuses on helping users connect momentary interactions to their broader life goals and values.

This three-tier structure (practices → proximal outcomes → distal orientation) reflects the causal logic of eudaimonic digital wellbeing: intentionally designed digital practices (Reflection, Autonomy) generate proximal eudaimonic experiences (Growth, Relatedness), which over time, when consistently connected to users' values (Purpose), may contribute to distal eudaimonic outcomes.

This framework is intended to provide designers and researchers with a conceptual toolkit for moving beyond engagement-focused design, anchored in established traditions like Positive Technology (Riva, 2012), METUX (Peters et al., 2018), and Value-Sensitive Design (VSD) (Friedman and Hendry, 2019). VSD serves as a starting point by embedding values like autonomy early, but requires extension for eudaimonic specificity (e.g., purpose-mapping tools); co-design is operationalized via iterative stakeholder prompts (e.g., (Yoo et al. 2013)'s action-reflection model). Each principle includes practical application steps, drawing on social practice approaches (Petermans and Cain, 2019).

4.1 Principle 1: design for reflection (digital practices level)

The first principle, grounded in the understanding that reflection is a cornerstone of personal growth (Baumer et al., 2014; Schön, 1983; Fleck and Fitzpatrick, 2010), calls for a design shift from a narrow focus on task efficiency to a broader aim of fostering self-awareness. Instead of optimizing for speed, systems should create moments of pause and introspection, encouraging users to consider the “why” behind their actions. For instance, a social media app, rather than employing an infinite scroll, could periodically summarize user activity and ask, “How did this time align with your intentions?” Similarly, a digital journaling tool could use natural language processing to identify recurring emotional themes, while “contemplative computing” applications might use ambient cues or structured prompts to gently guide attention back to the present moment or facilitate deeper reflection-in-action (Pang, 2013; Sengers et al., 2005; Sharmin and Bailey, 2013).

Application: use (Fleck and Fitzpatrick 2010) framework to frame reflection levels (e.g., on-action vs. in-action); integrate via co-design workshops prompting value-aligned prototypes (Yoo et al., 2013).

4.2 Principle 2: design for autonomy (design logics and practices level)

The second principle emphasizes designing for autonomy, a fundamental psychological need for feeling in control of one's own life (Ryan and Deci, 2000; Ballou et al., 2022). This involves moving from system-driven recommendations to user-driven self-direction. The system should act as a scaffold for the user's agency, not as a prescriptive authority. Examples include wellness apps that help users define their own health goals through structured dialogue, or news aggregators that allow users to tune recommendation algorithms based on their desire for diverse perspectives. Such interfaces embody Value-Sensitive Design principles by making value-laden choices transparent and configurable (Friedman and Hendry, 2019; van den Hoven et al., 2019; Schneider et al., 2018).

Application: apply VSD's conceptual, empirical, technical investigations sequentially; empower via customizable AI thresholds (e.g., user veto on suggestions).

4.3 Principle 3: design for growth (proximal outcomes level)

The third principle focuses on supporting the development of competence and mastery over the long term, based on the need for competence from SDT and Personal Growth from Ryff's model. This requires an evolution from optimizing solely for ease-of-use to supporting productive challenge, where the user is engaged in a way that leads to skill development. This could manifest in creative software with scaffolding that is gradually removed as a user's skills develop, language-learning apps using VR for immersive conversational challenges (Foreman, 2022), or fitness apps that focus on skill progression rather than just quantitative output.

Application: leverage METUX spheres (Peters et al., 2018) to assess growth across task/interface levels; iterate via possibility-driven prototypes (Desmet and Hassenzahl, 2012).

4.4 Principle 4: design for purpose (bidge between proximal and distal outcomes)

The fourth principle is to design for purpose, helping users connect their small, everyday actions to a larger, self-defined sense of meaning, a concept central to Ryff's model and the “Meaning” component of PERMA. The design goal is to bridge the gap between short-term engagement and long-term fulfillment by making a user's values actionable. For example, a task management app could prompt users to link to-do items to their larger life goals, a financial tool could frame saving in terms of achieving life goals, and a social platform could highlight meaningful conversations rather than just counting likes.

Application: use liminal design's three-step narrative (threshold, immersion, integration) (Liedgren et al., 2023) for purpose-mapping exercises; co-design with diverse groups to contextualize (Vines et al., 2016).

4.5 Principle 5: design for relatedness (proximal outcomes level)

Finally, the fifth principle is to design for relatedness, advocating for social technologies that prioritize the quality and depth of relationships over the quantity of connections. Grounded in the universal need for relatedness described in SDT and Ryff's “Positive Relations with Others," this principle aims to foster authenticity and genuine community. The design goal is to shift from facilitating superficial connections to fostering authentic community, which could be achieved through communication apps for small groups that encourage thoughtful exchanges, platforms that connect people for mutual mentorship, or systems designed to support intergenerational connection.

Application: Draw on AI community wellbeing frameworks (van der Maden et al., 2023) for feedback loops; evaluate via social practice metrics (Petermans and Cain, 2019).

5 Discussion and future directions

The agenda and framework proposed in this paper represent more than just an expansion of HCI's topical coverage; they call for a fundamental re-evaluation of the field's core values and goals. By advocating for a shift from engagement to eudaimonia, we are challenging the techno-centric and often commercially driven paradigms that currently dominate much of the technology industry (Zuboff, 2019). This shift has significant implications for HCI research, practice, and education, particularly in bridging academia's value-focused approaches with industry's metrics-driven realities.

5.1 Implications for HCI practice and theory

For practitioners, adopting a eudaimonic approach requires a move beyond A/B testing for conversion and retention, though industry increasingly incorporates wellbeing KPIs (e.g., via ESG reporting). It necessitates the integration of new methods and metrics into the design process, such as longitudinal user studies, qualitative interviews focused on meaning and values, and the use of psychological wellbeing scales as key performance indicators. It also requires a closer collaboration with social scientists and ethicists to navigate the complex terrain of human flourishing. This may be challenging in agile development environments, requiring new models for integrating long-term, value-oriented research into iterative design cycles, such as hybrid sprints blending VSD with METUX assessments (Peters et al., 2018). To convince companies, the framework promotes “eudaimonic ROI” (e.g., retention via purpose alignment) and advocates for regulations like the EU AI Act mandating wellbeing impact assessments (Mesarčík et al., 2021). Educationally, curricula should embed co-design and ethical prototyping to empower future designers.

For theorists, Eudaimonic HCI offers an opportunity to develop richer, more holistic models of human-technology interaction. It pushes the field to move beyond purely cognitive or behavioral models and to engage more deeply with theories from positive psychology, ethics, and philosophy. This could lead to new “strong concepts” for HCI that provide generative guidance for designing technologies that are not just usable, but truly worthwhile. It also encourages a move from a problem-solving orientation to an asset-based one, asking not just “what's wrong with technology?” but “how can technology help us live better?”.

5.2 Challenges and ethical considerations

This agenda is not without its challenges. A significant critique is the risk of paternalism: who are designers to decide what constitutes a “good life” for others? This is a valid and crucial concern. The answer must be that Eudaimonic HCI cannot be prescriptive. It must be grounded in principles of autonomy and co-design, empowering users to define and pursue their own vision of a flourishing life, via methods like action-reflection prompts (Yoo et al., 2013). The role of the designer is not to provide answers, but to create tools that help users ask better questions of themselves.

Another major challenge is the potential for “eudaimonic washing," where the language of wellbeing is co-opted for manipulative ends. This is a real danger, as seen in the critiques of persuasive technology, where techniques designed to promote positive behaviors can easily cross the line into coercion (Spahn, 2012). To counter this, the Eudaimonic HCI community must be fiercely committed to transparency, user control, and ethical oversight. Frameworks like Value-Sensitive Design provide a starting point, but new ethical guidelines specifically for the design of wellbeing technologies will be needed (Mesarčík et al., 2021; Floridi and Cowls, 2022; Mittelstadt, 2023; Jobin et al., 2019).

5.3 Limitations and a vision for a more humane future

We acknowledge the limitations of this agenda. Measuring constructs like “purpose” is inherently difficult, and attributing changes in such high-level life outcomes to a single technological intervention is a significant methodological challenge. However, by grounding our approach in established digital wellbeing frameworks (Büchi, 2024; Vanden Abeele, 2020) and psychological theories of eudaimonia (Ryff, 1989; Ryan and Deci, 2000), we provide a theoretically coherent foundation for addressing these challenges. The framework we propose is preliminary and requires extensive empirical validation and refinement.

Furthermore, the commercial incentives of the technology industry remain a powerful force that often runs counter to eudaimonic goals. Overcoming this will require not just better design, but potentially also policy changes (e.g., wellbeing mandates in app stores) and a shift in consumer awareness via advocacy. Despite these challenges, the potential rewards of a Eudaimonic HCI are immense. In a world facing complex societal challenges, from mental health crises to political polarization and climate change, technology can either be a source of distraction and division or a tool for fostering wisdom, compassion, and collective action (Kurniawan, 2004; Helbing et al., 2019). By embracing the goal of human flourishing in its deepest sense, HCI can play a critical role in shaping a more humane and sustainable future (Kurniawan, 2004; Van Der Hoven and Manders-Huits, 2020; Blevis, 2007). The ultimate vision of Eudaimonic HCI is not a world of perfectly optimized, “happy” users, but a world where technology helps us to be more reflective, more connected to our values, and more capable of realizing our full potential as human beings.

5.4 Toward genuine interdisciplinary dialogue: HCI and psychology

Throughout this paper, we have argued for the importance of grounding eudaimonic HCI in established psychological theory. However, the revisions prompted by this review process have revealed a deeper need: not merely for HCI to “borrow” psychological constructs, but for genuine interdisciplinary dialogue between the fields. Initiatives such as the proposal for “positive cyberpsychology” (Fortuna, 2023) exemplify the kind of integrative thinking needed to bridge psychological theory and HCI practice. Based on our engagement with this review process and our own experience working at the intersection of these disciplines, we identify several areas where such dialogue could be particularly fruitful:

• Understanding construct structure: psychologists distinguish between latent variables (unobserved factors that cause observed measurements), composite variables (aggregates of observed indicators), and emergent variables (products of system interactions). HCI researchers would benefit from greater familiarity with these distinctions when adapting psychological scales for technology evaluation.

• Maintaining levels of analysis: as this review process has emphasized, confusion between proximal experiences (the focus of UX research) and distal wellbeing outcomes (the focus of positive psychology) undermines theoretical clarity. Interdisciplinary collaboration can help maintain these distinctions while exploring their causal relationships.

• Appreciating developmental mechanisms: psychologists study long-term trajectories of personal growth and purpose development. HCI researchers, typically focused on immediate user experiences, could benefit from understanding these mechanisms when designing technologies intended to support flourishing over time.

• Terminological precision: the habitual use of terms like “wellbeing," “flourishing," “meaning," and “growth” as synonyms obscures important theoretical distinctions. Collaborative work can establish shared vocabularies that respect disciplinary traditions while enabling cross-disciplinary communication.

• Resisting commonsense intuitions: everyday intuitions about happiness and personal development can subtly shape theoretical formulations in both fields. Critical dialogue between disciplines can help identify and correct such biases.

Conversely, psychologists often lack insight into design logics and technological affordances—the mechanisms through which digital systems shape user experiences. A reciprocal dialogue would see psychologists engaging with HCI's expertise in how interface design, interaction patterns, and algorithmic systems mediate psychological processes.

We offer this paper not as a definitive statement but as an invitation to such dialogue. The framework we propose is necessarily preliminary; its refinement depends on sustained collaboration between researchers who understand psychological wellbeing and those who understand technological design. Journals that publish work from both communities—and review processes that, like this one, insist on theoretical rigor—play an essential role in fostering this integration.

6 Conclusion

The field of HCI is at a critical juncture. As technology becomes increasingly intelligent and integrated into our lives, its potential to shape our values, goals, and sense of self grows exponentially. The current focus on digital wellbeing, while valuable, is insufficient to address this profound responsibility. By concentrating on mitigating harm and optimizing for engagement, the field risks neglecting the fundamental human drive for meaning, growth, and purpose. The result is a digital landscape that is often more distracting than edifying, more isolating than connecting, and more consuming than creative.

This paper has identified a clear and urgent research gap: the need for a systematic approach to designing for eudaimonic wellbeing. We have argued that this is not merely an interesting new topic for HCI, but a necessary evolution of the field's core mission. We have proposed a research agenda to catalyze this new area of inquiry, focusing on the core challenges of measurement, design patterns, the role of AI, and ethical, inclusive design. The preliminary design framework offers a starting point for practitioners to begin shifting their mindset from designing for users to designing for human flourishing. By embracing the challenge of Eudaimonic HCI, the field can move beyond simply making technology better and begin exploring how technology can help us be better.

References

• 1

  AdadiA.BerradaM. (2018). Peeking inside the black-box: a survey on explainable artificial intelligence (XAI). IEEE Access6, 52138–52160. doi: 10.1109/ACCESS.2018.2870052

  • CrossRef
  • Google Scholar

• 2

  AlimF.ImtiazM. H. (2023). Wearable sensors for the monitoring of maternal health—a systematic review. IEEE Rev. Biomed. Eng. 16, 298–313. doi: 10.3390/s23052411

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 3

  BalkiE.HayesN.HollandC. (2022). Effectiveness of technology interventions in addressing social isolation, connectedness, and loneliness in older adults: systematic umbrella review. JMIR Aging5:e40125. doi: 10.2196/40125

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 4

  BallouN.DeterdingS.TyackA.MeklerE. D.CalvoR. A.PetersD.et al. (2022). Self-Determination Theory in HCI: Shaping a Research Agenda. Celebration, FL: Center for Self-Determination Theory. doi: 10.1145/3491101.3503702

  • CrossRef
  • Google Scholar

• 5

  BaumerE. P.KhovanskayaV.MatthewsM.ReynoldsL.SchwandaS. V.GayG. (2014). “Reviewing reflection: on the use of reflection in interactive system design," in Proceedings of the 2014 Conference on Designing Interactive Systems (New York, NY: ACM), 93–102. doi: 10.1145/2598510.2598598

  • CrossRef
  • Google Scholar

• 6

  BennettC.MeklerE. D. (2024). Beyond intrinsic motivation: the role of autonomous motivation in user experience. ACM Trans. Comput. Hum. Interact. 31, 1–25. doi: 10.1145/3689044

  • CrossRef
  • Google Scholar

• 7

  BhattacharyaS.BhattacharyaS.VallabhV.MarzoR. R.JuyalR.GokdemirO. (2023). Digital well-being through the use of technology–a perspective. J. Med. Internet Res. 25:e48392. doi: 10.21106/ijma.588

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 8

  BlevisE. (2007). “Sustainable interaction design: invention & disposal, renewal & reuse," in Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (New York, NY: ACM), 503–512. doi: 10.1145/1240624.1240705

  • CrossRef
  • Google Scholar

• 9

  BødkerS. (2015). Third-wave HCI, 10 years later—participation and sharing. Interactions22, 24–31. doi: 10.1145/2804405

  • CrossRef
  • Google Scholar

• 10

  BüchiM. (2024). Digital well-being theory and research. New Media Soc. 26, 172–189. doi: 10.1177/14614448211056851

  • CrossRef
  • Google Scholar

• 11

  BurrC.TaddeoM.FloridiL. (2020). The ethics of digital well-being: a thematic review. Sci. Eng. Ethics26, 2313–2343. doi: 10.1007/s11948-020-00175-8

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 12

  CalvoR. A.PetersD. (2014). Positive Computing: Technology for Wellbeing and Human Potential. Cambridge, MA: MIT Press. doi: 10.7551/mitpress/9764.001.0001

  • CrossRef
  • Google Scholar

• 13

  CalvoR. A.PetersD.VoldK.RyanR. M. (2020). “Supporting human autonomy in AI systems: a framework for ethical enquiry," in Ethics of Digital Well-Being: A Multidisciplinary Approach (Cham: Springer), 31–54. doi: 10.1007/978-3-030-50585-1_2

  • CrossRef
  • Google Scholar

• 14

  ChenS.EbrahimiO. V.ChengC. (2025). New perspective on digital well-being by distinguishing digital competency from dependency: network approach. J. Med. Internet Res. 27:e70483. doi: 10.2196/70483

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 15

  DellermannD.CalmaA.LipuschN.WeberT.WeigelS.EbelP.et al. (2021). The future of human-AI collaboration: a taxonomy of design knowledge for hybrid intelligence systems. arXiv [preprint]. arXiv:2105.03354.

  • Google Scholar

• 16

  DesmetP. M. A.HassenzahlM. (2012). “Towards happiness: possibility-driven design," in Human-Computer Interaction: The Agency Perspective (Cham: Springer), 3–27. doi: 10.1007/978-3-642-25691-2_1

  • CrossRef
  • Google Scholar

• 17

  DesmetP. M. A.PohlmeyerA. E. (2013). Positive design: an introduction to design for subjective well-being. Int. J. Des. 7, 5–19.

  • Google Scholar

• 18

  EbertA.GershonN. D.van der VeerG. C. (2012). Human-computer interaction: Introduction and overview. KI-Künstliche Intelligenz26, 121–126. doi: 10.1007/s13218-012-0174-7

  • CrossRef
  • Google Scholar

• 19

  FleckR.FitzpatrickG. (2010). “Reflecting on reflection: framing a design landscape," in Proceedings of the 22nd Conference of the Computer-Human Interaction Special Interest Group of Australia on Computer-Human Interaction (OZCHI '10) (New York, NY: ACM), 216–223. doi: 10.1145/1952222.1952269

  • CrossRef
  • Google Scholar

• 20

  FloridiL.CowlsJ. (2022). A unified framework of five principles for AI in society. Harvard Data Sci. Rev. 4, 535–545. doi: 10.1002/9781119815075.ch45

  • CrossRef
  • Google Scholar

• 21

  FoggB. J. (2002). Persuasive Technology: Using Computers to Change What we Think and Do. Burlington, MA: Morgan Kaufmann. doi: 10.1145/764008.763957

  • CrossRef
  • Google Scholar

• 22

  ForemanN. (2009). Virtual reality in psychology. Themes Sci. Technol. Educ. 2, 225252.

  • Google Scholar

• 23

  FormosaP.RyanM. (2021). AI systems and respect for human autonomy. Front. Artif. Intell. 4:705164. doi: 10.3389/frai.2021.705164

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 24

  FortunaP. (2023). Positive cyberpsychology as a field of study of the well-being of people interacting with and via technology. Front. Psychol. 14:1053482. doi: 10.3389/fpsyg.2023.1053482

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 25

  FriedmanB. (Ed.). (1997). Human Values and the Design of Computer Technology. Stanford, CA: CSLI Publications.

  • Google Scholar

• 26

  FriedmanB.HendryD. G. (2019). Value Sensitive Design: Shaping Technology with Moral and Technical Imagination. Cambridge, MA: MIT Press. doi: 10.7551/mitpress/7585.001.0001

  • CrossRef
  • Google Scholar

• 27

  GorichanazT. (2022). Designing a future worth wanting: applying virtue ethics to HCI. arXiv preprint arXiv:2204.02237.

  • Google Scholar

• 28

  GuptaJ.AhujaM.GargN. (2022). “A review on human-computer interaction (HCI)," in 2022 2nd International Conference on Innovative Sustainable Computational Technologies (CISCT) (Dehradun: IEEE), 1–6. doi: 10.1109/CISCT55310.2022.10046656

  • CrossRef
  • Google Scholar

• 29

  HelbingD.HafenE.HagnerM.HovenJ. V. D.FreyB. S.GigerenzerG.et al. (2019). “Will democracy survive big data and artificial intelligence?" in Towards Digital Enlightenment (Cham: Springer), 73–98. doi: 10.1007/978-3-319-90869-4_7

  • CrossRef
  • Google Scholar

• 30

  HursthouseR. (2017). “On virtue ethics," in Applied Ethics, ed. L. May (New York, NY: Routledge), 29–35. doi: 10.4324/9781315097176-5

  • CrossRef
  • Google Scholar

• 31

  HutaV.WatermanA. S. (2014). Eudaimonia and its distinction from hedonia: developing a classification and terminology for understanding conceptual and operational definitions. J. Happiness Stud. 15, 1425–1456. doi: 10.1007/s10902-013-9485-0

  • CrossRef
  • Google Scholar

• 32

  JackoJ. A. (Ed.). (2012). Human Computer Interaction Handbook: Fundamentals, Evolving Technologies, and Emerging Applications. Boca Raton, FL: CRC press. doi: 10.1201/b11963

  • CrossRef
  • Google Scholar

• 33

  JobinA.IencaM.VayenaE. (2019). The global landscape of AI ethics guidelines. Nat. Mach. Intell. 1, 389–399. doi: 10.1038/s42256-019-0088-2

  • CrossRef
  • Google Scholar

• 34

  JörsS.De LucaV. (2024). Measuring the experience of eudaimonic virtues in technology interaction: development and validation of the eudaimonic interaction inventory (EII). Int. J. Hum. Comput. Stud. 185:102857.

  • Google Scholar

• 35

  KadenheN.Al MuslehM.LompotA. (2024). Human-AI co-design and co-creation: a review of emerging approaches, challenges, and future directions. arXiv [preprint]. arXiv:2404.17511. doi: 10.48550/arXiv.2404.17511

  • CrossRef
  • Google Scholar

• 36

  KjeldskovJ.PaayJ. (2012). “A longitudinal review of mobile HCI research methods,” in Proceedings of the 14th International Conference on Human-Computer Interaction with Mobile Devices and Services (New York, NY: ACM), 69–78. doi: 10.1145/2371574.2371586

  • CrossRef
  • Google Scholar

• 37

  KurniawanS. (2004). Interaction design: beyond human–computer interaction by Preece, Sharp and Rogers (2001), ISBN 0471492787. Univers. Access Inf. Soc. 3, 289–289. doi: 10.1007/s10209-004-0102-1

  • CrossRef
  • Google Scholar

• 38

  LickliderJ. C. R. (1960). Man-computer symbiosis. RE Trans. Hum. Factors Electron. HFE-1, 4–11. doi: 10.1109/THFE2.1960.4503259

  • CrossRef
  • Google Scholar

• 39

  LiedgrenJ.DesmetP. M. A.GaggioliA. (2023). Liminal design: a conceptual framework and three-step approach for developing technology that delivers transcendence and deeper experiences. Front. Psychol. 14:1043170. doi: 10.3389/fpsyg.2023.1043170

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 40

  LiuZ. (2025). Human-AI co-creation: a framework for collaborative design in intelligent systems. arXiv [preprint]. arXiv:2507.17774. doi: 10.48550/arXiv.2507.17774

  • CrossRef
  • Google Scholar

• 41

  MesarčíkM.SolárováS.PodrouŽekJ.BielikovaM. (2021). Stance on The Proposal for a Regulation Laying Down Harmonised Rules on Artificial Intelligence–Artificial Intelligence Act. Bratislava: Kempelen Institute of Intelligent Technologies.

  • Google Scholar

• 42

  MittelstadtB. D.AlloP.TaddeoM.WachterS.FloridiL. (2016). The ethics of algorithms: mapping the debate. Big Data Soc. 3, 1–21. doi: 10.1177/2053951716679679

  • CrossRef
  • Google Scholar

• 43

  MüllerJ.MeklerE. D.OpwisK. (2015). “Facets in HCI: towards understanding eudaimonic UX – preliminary findings," in Proceedings of the 2015 Annual Symposium on Computer-Human Interaction in Play (New York, NY: ACM), 291–296. doi: 10.1145/2702613.2732836

  • CrossRef
  • Google Scholar

• 44

  O'BrienH. L.TomsE. G. (2008). What is user engagement? A conceptual framework for defining user engagement with technology. J. Am. Soc. Inf. Sci. Technol. 59, 938–955. doi: 10.1002/asi.20801

  • CrossRef
  • Google Scholar

• 45

  OrbenA. (2020). The Sisyphean cycle of technology panics. Perspect. Psychol. Sci. 15, 1143–1157. doi: 10.1177/1745691620919372

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 46

  PageM. J.McKenzieJ. E.BossuytP. M.BoutronI.HoffmannT. C.MulrowC. D.et al. (2021). The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ372:n71. doi: 10.1136/bmj.n71

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 47

  PangA. S. K. (2013). The distraction addiction: Getting the Information You Need and the Communication You Want, Without Enraging Your Family, Annoying Your Colleagues, and Destroying Your Soul. New York, NY: Little, Brown and Company.

  • Google Scholar

• 48

  ParkJ. S.O'BrienJ.LiangP.BernsteinM. S.CaiC. J.MorrisM. R. (2023). “Generative agents: interactive simulacra of human behavior," in Proceedings of the 36th Annual ACM Symposium on User Interface Software and Technology (New York, NY: ACM), 1–22. doi: 10.1145/3586183.3606763

  • CrossRef
  • Google Scholar

• 49

  PassmoreJ.OlafssonB. (2024). A systematic literature review of artificial intelligence (AI) in coaching: insights for future research and product development. J. Work-Appl. Manag. 16, 233–252. doi: 10.1108/JWAM-11-2024-0164

  • CrossRef
  • Google Scholar

• 50

  PetermansA.CainR. (Eds.). (2019). Design for Wellbeing: An Applied Approach. London: Routledge. doi: 10.4324/9781315121383

  • CrossRef
  • Google Scholar

• 51

  PetersD.CalvoR. A.RyanR. M. (2018). Designing for motivation, engagement and wellbeing in digital experience. Front. Psychol. 9:797. doi: 10.3389/fpsyg.2018.00797

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 52

  PirzadehA.HeL.StoltermanE. (2013). “Personal informatics and reflection: a critical examination of the nature of reflection," in CHI'13 Extended Abstracts on Human Factors in Computing Systems (New York, NY: ACM), 1979–1988. doi: 10.1145/2468356.2468715

  • CrossRef
  • Google Scholar

• 53

  PohlmeyerA. E. (2017). “How design can (not) support human flourishing," in Positive Psychology Interventions in Practice (Cham: Springer), 235–255. doi: 10.1007/978-3-319-51787-2_14

  • CrossRef
  • Google Scholar

• 54

  RivaG. (2012). What is Positive Technology and its impact on CyberPsychology. Stud. Health Technol. Inform.181, 37–41. doi: 10.3233/978-1-61499-121-2-37

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 55

  RyanR. M.DeciE. L. (2000). The “what” and “why” of goal pursuits: human needs and the self-determination of behavior. Psychol. Inq. 11, 227–268. doi: 10.1207/S15327965PLI1104_01

  • CrossRef
  • Google Scholar

• 56

  RyanR. M.DeciE. L. (2001). On happiness and human potentials: a review of research on hedonic and eudaimonic well-being. Annu. Rev. Psychol. 52, 141–166. doi: 10.1146/annurev.psych.52.1.141

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 57

  RyffC. D. (1989). Happiness is everything, or is it? Explorations on the meaning of psychological well-being. J. Pers. Soc. Psychol. 57, 1069–1081. doi: 10.1037/0022-3514.57.6.1069

  • CrossRef
  • Google Scholar

• 58

  RyffC. D.KeyesC. L. M. (1995). The structure of psychological well-being revisited. J. Pers. Soc. Psychol. 69, 719–727. doi: 10.1037/0022-3514.69.4.719

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 59

  SchneiderH.EibandM.UllrichD.ButzA. (2018). “Empowerment in HCI—a survey and framework," in Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (New York, NY: ACM), 1–14. doi: 10.1145/3173574.3173818

  • CrossRef
  • Google Scholar

• 60

  SchönD. A. (1983). The Reflective Practitioner: How Professionals Think in Action. New York, NY: Basic Books.

  • Google Scholar

• 61

  SeeberI.BittnerE.BriggsR. O.De VreedeT. De Vreedem G ElkinsA.et al. (2020). Machines as teammates: a research agenda on AI in team collaboration. Inf. Manag. 57:103174. doi: 10.1016/j.im.2019.103174

  • CrossRef
  • Google Scholar

• 62

  SeligmanM. E. P. (2011). Flourish: A Visionary New Understanding of Happiness and Well-Being. Washington, DC: Free Press.

  • Google Scholar

• 63

  SengersP.BoehnerK.DavidS.KayeJ. J. (2005). “Reflective design," in Proceedings of the 4th Decennial Conference on Critical Computing: Between Sense and Sensibility (CC '05) (New York, NY: ACM), 155–164. doi: 10.1145/1094562.1094569

  • CrossRef
  • Google Scholar

• 64

  SharminM.BaileyB. P. (2013). “ReflectionSpace: an interactive visualization tool for supporting reflection-on-action in design," in Proceedings of the 9th ACM Conference on Creativity & Cognition (New York, NY: ACM), 83–92. doi: 10.1145/2466627.2466645

  • CrossRef
  • Google Scholar

• 65

  SlaterM.Sanchez-VivesM. V. (2020). Enhancing our lives with immersive virtual reality. Front. Robot. AI7, 1–22. doi: 10.3389/frobt.2016.00074

  • CrossRef
  • Google Scholar

• 66

  SpahnA. (2012). And lead us (not) into persuasion…? Persuasive technology and the ethics of communication. Sci. Eng. Ethics18, 633–650. doi: 10.1007/s11948-011-9278-y

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 67

  StephanidisC.SalvendyG.AntonaM.ChenJ. Y. C.DongJ.DuffyV. G.et al. (2019). Seven HCI grand challenges. Int. J. Hum.-Comput. Interact. 35, 1229–1269. doi: 10.1080/10447318.2019.1619259

  • CrossRef
  • Google Scholar

• 68

  ThomsonR.McLeodJ. (2015). New frontiers in qualitative longitudinal research: an agenda for research. Int. J. Soc. Res. Methodol. 18, 243–250. doi: 10.1080/13645579.2015.1017900

  • CrossRef
  • Google Scholar

• 69

  TwengeJ. M. (2019). More time on technology, less happiness? Associations between digital-media use and psychological well-being. Curr. Dir. Psychol. Sci. 28, 372–379. doi: 10.1177/0963721419838244

  • CrossRef
  • Google Scholar

• 70

  van den HovenJ.VermaasP. E.van de PoelI. (Eds.). (2019). Handbook of Ethics, Values, and Technological Design. Cham: Springer.

  • Google Scholar

• 71

  Van Der HovenJ.Manders-HuitsN. (2020). “Value-sensitive design,” in The Ethics of Information Technologies (London), (329–332). doi: 10.4324/9781003075011-23

  • CrossRef
  • Google Scholar

• 72

  van der MadenW.HekkertP.LomasD. (2023). A framework for designing AI systems that support community wellbeing. Front. Psychol. 13:1011883. doi: 10.3389/fpsyg.2022.1011883

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 73

  Vanden AbeeleM. M. P. (2020). Digital wellbeing as a dynamic construct. Commun. Theory31, 932–955. doi: 10.1093/ct/qtaa024

  • CrossRef
  • Google Scholar

• 74

  VermeerenA. P. O. S.LawE. L.RotoV.ObristM.HoonhoutJ.Väänänen-Vainio-MattilaK. (2010). “User experience evaluation methods: current state and development needs," in NordiCHI 2010: Extending Boundaries- Proceedings of the 6th Nordic Conference on Human-Computer Interaction (New York, NY: ACM). doi: 10.1145/1868914.1868973

  • CrossRef
  • Google Scholar

• 75

  VinesJ.McNaneyR.ClarkeR.LindsayS.MccarthyJ. C.HowardsS.et al. (2016). “Designing for and with vulnerable people,” in Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems, (California: San Jose). 2345–2357.

  • Google Scholar

• 76

  WatermanA. S. (1993). Two conceptions of happiness: contrasts of personal expressiveness (eudaimonia) and hedonic enjoyment. J. Pers. Soc. Psychol. 64, 678–691. doi: 10.1037/0022-3514.64.4.678

  • CrossRef
  • Google Scholar

• 77

  WozniakP. W.HakM.KotovaE.NiessJ.BentvelzenM.WeingärtnerH.et al. (2023). “Quantifying meaningful interaction: developing the eudaimonic technology experience scale," in Proceedings of the 2023 ACM Designing Interactive Systems Conference (New York, NY: ACM), 1904–1914. doi: 10.1145/3563657.3596063

  • CrossRef
  • Google Scholar

• 78

  YooD.HuldtgrenA.WoelferJ. P.HendryD. G.FriedmanB. (2013). “A value sensitive action-reflection model: evolving a co-design space with stakeholder and designer prompts," in Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (New York, NY: ACM), 419–428. doi: 10.1145/2470654.2470715

  • CrossRef
  • Google Scholar

• 79

  ZuboffS. (2019). The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. New York, NY: PublicAffairs.

  • Google Scholar