From Legislation to Human Flourishing: Unveiling the

Characteristics of Digital Well-Being by Taxonomy Development

from an EU Perspective

Katharina-Maria Illgen

and Oliver Thomas

1,2

German Research Center for Artificial Intelligence, Osnabrück, Germany, Smart Enterprise Engineering,

Hamburger Str. 24, 49084 Osnabrück, Germany

Usnabrück University, Information Management and Information Systems, Hamburger Str. 24,

49084 Osnabrück, Germany

Keywords: Digital Well-Being, Legislation, Taxonomy, European Union, Human-Computer Interaction.

Abstract: With pervasive digitalization, human well-being is intimately connected with the condition of the information

environment and the digital technologies that shape human interaction with it. With the increased exposure to

technologies like Artificial Intelligence, concerns about well-being grow. However, there is no thorough

understanding of the conditions necessary to enhance digital well-being, particularly from a legislative

perspective. The European Union (EU) addresses this through various guidelines and regulations for a more

trustworthy and human-centered approach. This study translates EU directives into practical, holistic advice

via taxonomy development, helping practitioners assess their adherence to digital well-being characteristics

and as a dynamic resource encouraging innovation and creation in promoting digital well-being goals. By

advancing awareness and supporting human flourishing in the digital age, this research contributes to the

ongoing Information Systems research discourse on critical challenges like human-technology symbiosis and

well-being, especially in Human-Computer Interaction and Human-Centered AI research.

1 INTRODUCTION

The digital landscape has evolved significantly, and

digital technologies increasingly shape our everyday

lives. As these technologies become more embedded

in society, human well-being is increasingly

entangled with the information environment and

digital tools humans interact with. Technological

advancement, while linked to human progress (Stahl

et al., 2021), raises ethical concerns about its potential

to limit human flourishing (Hylving et al., 2024).

Research highlights the adverse impacts of

digitalization, including stress and social disconnect

(Hylving et al., 2024; Rövekamp, 2019). Further,

rapid advancements in artificial intelligence (AI)

(Maslej et al., 2024) present both opportunities and

uncertainties, particularly concerning human well-

being, including out-of-control robots, biased

decision-making, disinformation, and challenges to

human rights (Shneiderman, 2020). Especially

regarding the emergence of AI technology, with its

still unclear impact on users’ well-being (Bentley et

al., 2024; Burnell et al., 2023; Capel and Brereton,

2023), is driving paradigm shifts towards human-

centeredness in human-computer interaction (HCI)

and human-centered artificial intelligence (HCAI)

research (e.g., including challenges like human-

technology symbiosis, well-being, eudaimonia which

demands authentic and meaningful activities, and

democracy) (Shen et al., 2022; Stephanidis et al.,

2019).

Despite the extensive exploration of digital well-

being in Information Systems (IS) research (Burr et

al., 2020), there remains a lack of comprehensive

understanding of the conditions required to enhance

digital well-being (Hylving et al., 2024). Notably, the

role of legislation in shaping digital well-being is

often overlooked. Legal frameworks offer a

structured approach to addressing digital well-being

challenges, especially given the increasing regulation

in this field over the past few years. However, the

complexity of digitalization legislation poses

challenges for practitioners (Cleven and Winter,

2009). This complexity makes it difficult for them to

Illgen, K.-M. and Thomas, O.

From Legislation to Human Flourishing: Unveiling the Character istics of Digital Well-Being by Taxonomy Development from an EU Perspective.

DOI: 10.5220/0013195400003929

Paper published under CC license (CC BY-NC-ND 4.0)

In Proceedings of the 27th International Conference on Enter prise Information Systems (ICEIS 2025) - Volume 2, pages 393-404

ISBN: 978-989-758-749-8; ISSN: 2184-4992

393

gain a holistic understanding of digital well-being,

limiting their ability to develop effective strategies for

improvement in their enterprises. Given the rising

global digital connectivity, it is increasingly relevant

to acquire an adequate level of digital awareness

. In

this light, it is crucial to simplify and clarify the

complex legislation related to digital well-being and

provide a thorough understanding of its relevant

components in a holistic overview.

This study addresses this gap. It aims to enhance

digital awareness by proposing a compelling and

timely exploration of digital well-being in the form of

a digital well-being taxonomy, informed by

legislation, often neglected in IS research (Butler et

al., 2023). Specifically, when scanning legislation

from a global perspective throughout this study, EU

legislation was found to provide an ideal foundation

for developing a taxonomy for digital well-being that

has the potential to be universally applicable due to

its proven global influence and alignment with

universally relevant ethical principles. The “Brussels

Effect” (Bradford, 2020) demonstrates how EU

regulations often become de facto global standards as

companies and nations adopt them. Additionally, the

EU is a clear frontrunner in addressing digitalization

challenges, with more comprehensive frameworks

than many other nations, which often lack

comparable standards. These, such as the AI Act and

Ethics Guidelines for Trustworthy AI, emphasize

trust, human-centeredness, and the common good,

offering a valuable foundation for conceptualizing

digital well-being. Focusing on the EU’s well-

established, globally influential legislation ensures

the taxonomy is robust and potentially further

applicable beyond Europe. The term directives

throughout this study includes guidelines as well as

regulations. Guidelines set objectives for member

states to implement through national laws, while

regulations are binding across all member states. The

following research question is put forth for

examination via taxonomy development:

RQ. Based on globally recognized EU directives,

which characteristics within a digital well-being

taxonomy promote digital well-being and human

flourishing in an information society, particularly in

Europe and beyond?

In proposing the resulting taxonomy, this study

offers various contributions: It adds value to the IS

research community in HCI and HCAI contexts and

practitioners in the EU, but also beyond, by providing

a structured, user-friendly, and legislative-informed

Digital awareness is empowering individuals in the use of

technology, focusing on using it correctly, effectively,

and safely, fostering an understanding of the

taxonomy that enhances understanding of digital

well-being characteristics. The taxonomy provides a

foundation for developing strategies, frameworks, or

other artifacts in IS research and practice, including

digital awareness training. Besides, this study has

societal relevance by applying a social science focus

to IS research – emphasizing the need for

interdisciplinary approaches and recognizing social

science’s importance in understanding technology’s

broader impact on society (Akkermans, 2023). The

paper is structured as follows: Section 2 reviews

related research, particularly HCI and HCAI. Section

3 outlines the qualitative research methodology,

followed by a presentation of findings in Section 4.

Section 5 discusses the results, and the study

concludes with a summary in Section 6.

2 RELATED RESEARCH

Within Positive Psychology, research on well-being

and technology appeared (e.g., Biswas-Diener, 2011;

Riva et al., 2012; Shen et al., 2022a). Technology can

impact mental health, including smartphone addiction

and challenges due to excessive social media use

(Abhari and Vaghefi, 2022; Wacks and Weinstein,

2021). The COVID-19 pandemic accelerated these

trends, as it forced our lives to take place online (Shen

et al., 2022), and well-being in Europe fell to its

lowest level in 40 years during the pandemic (Allas et

al., 2020). Recently, digital well-being has received

increased attention from scholars and tech enterprises

(Burr et al., 2020), and society and IS research have

reached a stage where the highest level of human

experience can be pursued by prioritizing digital well-

being (Shen et al., 2022). This shifts the HCI and

HCAI community towards a genuinely human-

centered approach with explicit goals of designing

digital experiences that enable human flourishing,

referred to in this study as digital well-being (Shen et

al., 2022; Stephanidis et al., 2019). We refer to the

following terms throughout this paper: Digital well-

being encompasses the impact of digital technologies

on physical, mental, and emotional health, as well as

autonomy and a sense of belonging and support

within a community (van der Maden et al., 2023;

World Health Organization, 2024). Human

flourishing, in this context, refers to the optimal

continuing development of human beings’ potential

and the desire to live well as a human being in an

opportunities, and especially the risks, and developing a

problem-solving mindset that ensures safe and sensible

usage of technology (Vidal Ferré et al., 2021).

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information society (Hylving et al., 2024; Shen et al.,

2022). Thereby, this study focuses on societal well-

being, which, in the context of this paper, also has

impacts on an individual level (Burr et al., 2020). This

is in line with existing scientific discussions in the

field of HCI, which include challenges like well-

being, health, eudaimonia, and human-technology

symbiosis (Gorichanaz, 2024; Shen et al., 2022;

Stephanidis et al., 2019). Usmani et al. (2023) further

reinforce human-centeredness and argue for a

harmonious coexistence between humans and

technology, suggesting its significance for enhancing

well-being and autonomy and creating a future where

technology benefits humanity. Scholars emphasize

the positive and dark side of technology: On the one

hand, a growing number of research focus on the

design and development of technologies to support

well-being and human potential, called positive

computing (Calvo and Peters, 2014). Besides models

implementing principles of flourishing, positive

computing, and eudaimonia into development

concepts (Desmet and Pohlmeyer, 2013; Sander,

2011; van der Maden et al., 2023), value-sensitive

design theorists propose incorporating values like

well-being into the engineering of future social robots

in HCI to enhance the well-being of users (Dennis,

2022). Another focus is developing socially

responsible recommender systems that avoid filter

bubbles and prioritize well-being (Bonenberger et al.,

2022). On the other hand, HCI and HCAI research

increasingly address the adverse impacts of

technology, investigating various challenges, such as

technostress (stress experienced by users due to IS)

(Ragu-Nathan et al., 2008), impacts on democracy, as

well as ethics, privacy, and security (Stephanidis et

al., 2019).

The aim is to link back to digital well-being and

how this paper contributes to ongoing research.

What’s missing in HCI is a legislative lens on digital

well-being, despite growing legislative action,

particularly in the EU, where there has been a notable

rise in related directives. On this basis, this work

focuses on a thorough understanding of well-being

characteristics. Starting from an EU perspective is a

valuable first approach, as it provides a solid

foundation emphasizing various well-being aspects

that have the potential to be universally applicable

(Bradford, 2020). Identifying key characteristics one

must be especially aware of within a digital well-

being taxonomy could benefit developing

interventions aimed at mitigating the adverse impacts

of digitalization. In organizational training, the

taxonomy could provide a structured foundation for

designing training modules that address specific

components of digital well-being. These modules

could contribute to prevention strategies and

programs, that have yet to be evaluated concerning

content in mitigating adverse impacts of technology

use (Rohwer et al., 2022).

3 METHODOLOGY

With the taxonomy development in this contribution,

the aim is to provide a suitable method for analyzing

and categorizing existing directives concerning

digital well-being from a legislative perspective,

advancing the understanding of this topic. To ensure

methodological rigor, we based our taxonomy

development on the method of Nickerson et al.

(2013), adapting it to our needs.

Step 1: We first determined the meta-

characteristic, which is the primary feature guiding

the selection of characteristics for the taxonomy. The

meta-characteristic, “the intersection of technology

and its impact on well-being in legislation,” was

defined based on the taxonomy’s purpose and target

users, including researchers interested in well-being

and human-technology symbiosis and practitioners

pursuing digital well-being goals. Step 2: Next, we set

conditions to terminate the iterative process. The

method ended when both objective and subjective

conditions were met. Objectively, this meant that

each characteristic was unique within its dimension

(no characteristic duplication); each dimension was

unique within the taxonomy (no dimension

duplication); no dimensions or characteristics were

added in the last iteration; and no dimensions or

characteristics were merged or split in the last

iteration. Subjectively, the method ended when the

taxonomy was determined to be concise, robust,

comprehensive, extendible, and explanatory

(Nickerson et al., 2013). Each iteration employed an

empirical-to-conceptual or conceptual-to-empirical

approach, checking pre-defined ending conditions.

Four iterations were conducted before meeting all

conditions, which was similar to the study of

Grueneke et al. (2024). We detail our iterations in the

following:

Iteration 1: To structure our research area and

address the increasing number of documents in

legislation, a conceptual-to-empirical approach was

used to develop the initial taxonomy. We conducted

a systematic literature review, selecting relevant

directives following the guidelines of Webster and

Watson (2002). Before conducting the review, we

scanned some of the most recent directives in the field

of this study’s research from a global perspective to

From Legislation to Human Flourishing: Unveiling the Characteristics of Digital Well-Being by Taxonomy Development from an EU

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395

determine the search term. These included, for

example, the EU AI Act; EU AI Action Plan; Ethics

Guidelines for Trustworthy AI; Digital Services Act

Package; General Data Protection Regulation

(GDPR); NIST AI Risk Management Framework;

ISO: 42001 Artificial Intelligence – Management

System (AIMS); UK AI Regulation White Paper;

Singapore`s Approach to AI Governance; Artificial

Intelligence and Data Act (AIDA) (Canada); US

White House Blueprint for an AI Bill of Rights.

Subsequently, EU directives were chosen for the

taxonomy development because they have the

potential to be universally applicable (see Section 1).

They have a user-friendly and concrete framing

compared to other directives, which often lack

comparable standards. Besides, the EU directives

strongly focus on societal well-being and ethical

technology use, making them highly relevant for

digital well-being, not only in the EU. For instance,

one of the first sentences of the European

Commission’s (2019) Ethics Guidelines for

Trustworthy AI follows the wording that AI systems

must be human-centered, and their use must be in the

service of humanity and the common good to increase

human well-being and freedom. The EU provides a

well-documented and practical approach to

protecting and promoting digital well-being.

Thereby, EU legislation is globally recognized,

remaining an influential superpower shaping the

world and its image (Bradford, 2020; European

Parliament and Council of the European Union,

2024). Focusing on these directives ensures our

taxonomy is built on solid and proven standards. We

used the EU official website to identify relevant

directives. Moreover, we searched sites managed by

the EU publications office, specifically: EUR-Lex,

EU-Publications, the official portal for European data

(data.europa.eu); CORDIS, Portal of the Publications

Office of the EU, and N-Lex. We additionally

searched Google Scholar to include current

developments. We also conducted a backward

reference search. The scope was limited to directives

until 2018, amid growing related legislation. We

exclusively reviewed documents published in

English. Within the search process, we selected the

following keywords to ensure a comprehensive

inclusion of directives specifically addressing the

intersection of technology and its impact on well-

being, as determined in the meta-characteristic in step

1: “(‘well-being’ OR ‘ethics’ OR ‘humans’ OR

‘human flourishing’ OR ‘awareness’) AND (‘digital’

OR ‘digitalization’ OR ‘artificial intelligence’ OR

‘technology’ OR ‘information and communication

technology’ OR ‘internet’ OR ‘systems’).” The

search was conducted from April to May 2024.

Organizing the information from the literature

involved an iterative process, combining elements of

content and thematic analysis (Bowen, 2009). Within

content analysis, data related to the meta-

characteristic was organized. It entailed scanning

titles, abstracts, and a first-pass document review,

identifying meaningful and relevant text passages or

other data (Corbin and Strauss, 2008; Strauss and

Corbin, 1998). The first-pass document review was

conducted on 42 documents. In total, 11 directives,

directly or indirectly related to digital well-being,

were selected to be relevant to the research question

and the meta-characteristic (see Table 1). These were

lettered a-k for ease of reference throughout the study.

Table 1: Relevant EU directives with implications for digital well-being.

EU Directive Reference Short Summar

(a) Ethics Guidelines for Trustworthy AI European Commission (2019)

An emphasis on several well-being-related principles and

requirements for AI.

(b) The Assessment List for Trustworthy AI European Commission (2020a)

A structured approach to assess the compliance of AI

stems with s

ecific

uidelines.

European Parliament and Council

of the Euro

ean Union

(

2024

)

The world’s first legislation to regulate the use of AI; special

risk cate

orization of AI s

stems.

(d) Digital Services Act

European Parliament and Council of

the Euro

ean Union

(

2022b

)

Creating a safer digital space; protecting fundamental user

hts; establishin

a level

field for enter

rises.

(e) Digital Decade Policy Programme 2030

European Parliament and Council of

the Euro

ean Union

(

2022a

)

A framework guiding all actions related to digital; ensuring

all as

ects of technolo

and innovation work for

le.

(f) European Declaration on Digital Rights and

Princi

les for the Di

ital Decade

European Commission (2023)

Promoting a sustainable, human-centric vision for digital

transformation.

(g) Digital Education Action Plan 2021-2027 European Commission (2020b)

A vision of high-quality, inclusive and accessible digital

education in Euro

(h) Council Conclusions on Supporting Well-being

in Di

ital Education

Council of the European Union

(

2022

)

Conclusions on supporting well-being in digital education.

(i) Digital Workplace Strategy European Commission (2018)

A strategic approach to designing and implementing digital

workin

environments within or

anizations.

(j) Mental Health in the Digital World of Work European Parliament (2023)

A report highlighting the impact of digitalization on mental

well-

ein

in the work

lace.

(k) EU Strategic Framework on Health and Safety

at Work 2021-2027

European Commission (2021)

A framework focusing on occupational safety and health in

the evolvin

world of work.

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With thematic analysis, patterns were recognized

within the data, and the selected data was examined

in more detail to uncover themes pertinent to the

meta-characteristic (Bowen, 2009). These 11

directives from Table 1 yielded the basis for the first

four dimensions and 48 characteristics, organized into

individual and social digital well-being and learning

and work context dimensions. Human-centeredness

emerged as an overall layer of all topics. This process

yielded the initial version of the taxonomy. After

assessing the initial taxonomy, unstructured

dimensions and overlapping characteristics were

found, necessitating further refinement.

Iteration 2: An empirical-to-conceptual approach

was used in the second iteration, involving a focus

group of three research experts in HCI, social science,

and AI and two practitioners in education and

organizational contexts. They reviewed and discussed

the initial taxonomy and provided relevant expert

feedback, enabling the initial taxonomy review,

enhancement, and further development. They helped

identify new characteristics and adjust and remove

dimensions. The critical insights from the focus group

were recapitulated and analyzed, determining their

suitability for the research topic. Subsequently, the

relevant feedback was incorporated into the

taxonomy. This resulted in a revised taxonomy

version with adjustments mainly concerning several

characteristics like information literacy or social

support. Further, individual and social digital well-

being were merged into a single dimension (social

context), as social context implications could also be

drawn to an individual level, which showed

redundancies. Another iteration was required despite

comprehensive improvements, as not all objective

conditions were met.

Iteration 3: A conceptual-to-empirical approach

was used, incorporating the author’s expertise in HCI

and well-being. This involved an intuitive approach,

where the researcher applied her understanding of the

characteristics to be classified to propose the digital

well-being taxonomy based on the researcher’s

perceptions of what makes sense (Nickerson et al.,

2013). Minor adjustments were made, involving

significantly fewer revisions than the previous one,

suggesting an increased explanatory strength and

improved stability within the taxonomy (Grueneke et

al., 2024). However, further iterations were needed to

meet all conditions.

Iteration 4: The final iteration involved another

conceptual-to-empirical approach and a workshop

with four researchers in the HCI field to validate the

taxonomy. The layer, dimensions, and characteristics

were confirmed. Subsequently, the objective ending

conditions were re-examined. It became evident that

each characteristic was unique within its dimension,

and each dimension was unique within the taxonomy.

Thus, duplications did not exist. The characteristic

“social support” was not duplicated and should be

understood in two distinct ways in the respective

dimensions. The overarching dimensions emerged

from three different contexts of digital well-being:

social, learning, and work, with various

characteristics and sub-characteristics. The

characteristics of the social context as the overarching

dimension can also apply to the two named domains,

as they are generally valid in social contexts. This

follows Baier et al. (2023), who also incorporated

non-exclusive characteristics to ensure the flexibility

and relevance of the data. The fourth iteration did not

require any further modifications of the taxonomy.

Consequently, the taxonomy met all objective ending

conditions. To ascertain the quality of the taxonomy,

it was further tested against the subjective ending

conditions, concluding that the taxonomy was

appropriate. After evaluating the taxonomy in each of

the four iterations, a final evaluation was performed,

considering the final taxonomy’s usefulness for the

intended target groups and purpose (Nickerson et al.

(2023). The purpose was to help researchers and

practitioners understand digital well-being

characteristics from a legislative-informed

perspective and assess how their enterprises align

with specific criteria, enabling deeper exploration of

relevant characteristics. The assembled focus group

of three researchers and two practitioners was

consulted again to ensure the integration of the target

groups’ perspectives into the final taxonomy. They

broadly confirmed the validity of the taxonomy. It

revealed that every enterprise is different; therefore,

in practice, the focus on specific characteristics of the

taxonomy must also be re-evaluated depending on the

use case. Practitioners can use the taxonomy to build

digital awareness, evaluate well-being criteria, and

promote innovation. For example, it was mentioned

that the taxonomy could serve as a foundation for

employee digital awareness training. Accordingly,

the final taxonomy was obtained.

4 RESULTS

4.1 Digital Well-Being Taxonomy

Figure 1 presents the digital well-being taxonomy,

providing characteristics and their representation in

the 11 directives and a comprehensive explanation in

Section 4.2, with references to the directives.

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Figure 1: The characteristics of digital well-being: a novel taxonomy from an EU perspective.

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4.2 Explanation of Characteristics

4.2.1 Social Context

C1. Prevention of Harm. Prevent any harm, e.g.,

prevention of harmful content (f); prohibition of AI

systems that deploy subliminal techniques beyond a

person’s consciousness to materially distort a

person’s behavior in a manner that potentially causes

that person or another physical or psychological harm

(c). C2. Risk Management/Awareness. Promote

digital risk awareness and prevention, support safe

digital environments, and address challenges

connected with digital risks, e.g., using digital social

networks (h). Categorize AI systems into the

following risk categories: Unacceptable risks that

include cognitive behavioral manipulation of people

or vulnerable groups, social scoring based on

behavior, socioeconomic status, personal

characteristics, biometric identification and

categorization, and real-time and remote biometric

identification such as facial recognition. High risks

with regulation that cover AI used in critical

infrastructure, AI that affects decisions about

people’s lives or significantly impacts the

environment, and generative AI systems as well as

basic AI models. Limited risks involving AI systems

must comply with transparency requirements,

including those that generate or manipulate image,

audio, or video content, such as deepfakes (c). C3.

Human Agency and Autonomy. Empower everyone

to make their own informed choices online (f); assess

possible influences of AI systems on individuals,

particularly as the system guides, influences, or

supports human decision-making (b). C4. Human

Oversight. Enable humans to always intervene in an

AI system (b). C5. Technical Robustness and

Safety. Resilience to Attack and Security (#5.1).

Protect the system from physical and cyber-attacks

and assess the risks arising from abuse/deficiency (b).

General Safety (#5.2). Assess potential risks from

sloppy design practices (b). Accuracy (#5.3). Assess

the effects that inaccurate predictions of a system

would put forward (b). Reliability (#5.4). Put forward

means to compensate for the system in case of failure

and ongoingly validate it (reliability, fallback plans,

and reproducibility) (b). C6. Privacy and Data

Governance. Handle personal (user) data responsibly

(privacy) (b); right to privacy and human dignity (j);

assure the integrity of data quality and content (data

governance) (b). C7. Transparency/Accountability.

Traceability (#7.1). Assure that the principle of

operation and the decisions of an AI system remain

traceable (b); transparency about the fact that humans

are dealing with an AI system (a). Explainability

(#7.2). Encourage the user’s understanding of an AI

system’s decisions (b), giving transparency and

clarity. Communication (#7.3). Communicate

possible risks and limitations of an (AI-) system to

users and, if applicable, provide disclaimers (b).

Involve and educate stakeholders throughout a

system’s life cycle (a). C8. Information

Literacy/Protection from Disinformation,

Misinformation. Protect people from disinformation

and misinformation; tackle information manipulation

(f); enhance rapid access to relevant information (i).

C9. Social Justice. Diversity (#9.1). Enhance

diversity; design data sets and algorithms so that

results are fair regarding diversity and

representativeness (b). Non-discrimination (#9.2).

Ensure that the system can be used by everyone,

including people with special needs or preferences

(accessibility and universal design) (b). Equality

(#9.3). Ensure access to digital resources and

technologies for all individuals, regardless of their

background, abilities, or circumstances, concerning

factors such as accessibility, connectivity, and

availability of digital equipment (g). Solidarity and

Inclusion (#9.4). Ensure that nobody is left behind by

digital transformation, making sure we make extra

effort to include older adults, people living in rural

areas, persons with disabilities, marginalized,

vulnerable, or disenfranchised people, and those who

act on their behalf (f). Fairness (#9.5). Create fair

digital environments (f); this includes, for example,

designing data sets and algorithms such that results

are fair and unfair bias is avoided (b). C10.

Environmental Well-being/Sustainability. Monitor

and reduce environmental negative impacts (b). C11.

Impact on Society or Democracy. Monitor and

reduce the negative impact that a(n) (AI-) system may

have on society and democracy (b). C12. Physical

and Mental Health. Encourage practices and tools

that promote a positive relationship with technology

to enhance the overall quality of life. Digital

technologies may induce stress and anxiety, affecting

sleep and mental resilience. Excessive digital device

use and ergonomic issues impact physical health,

while social media use and constant connectivity

influence mental health. The stress and mental strain

that can arise from constant connectivity, information

overload, and pressure to adapt to rapidly changing

technologies is also known as technostress (j). C13.

Social Belonging. Leverage technology to foster

connections and social belonging to be mentally and

emotionally healthy and feel like you belong to and

are supported by a community.

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4.2.2 Learning Context

C14. Digital Competence/Digital Literacy.

Technical Skills (#14.1). Possess skills to effectively

engage with the digital world and perform tasks

related to information, communication, and problem-

solving (g). Train for Resilience/Critical Thinking

(#14.2). Create an awareness of potential threats in

the digital world and foster the development of

resilience and critical thinking skills as a proactive

approach (h). Security and Ethics (#14.3). Engage

ethics and safety with digital technologies, including

cybersecurity skills and knowledge of AI algorithms’

limits (h). Social Competence (#14.4). Develop

personal and social competence, which may help

learners to use digital social networks with less risk

of emotional or social harm (h). Creation Skills

(#14.5). Acquire the knowledge, skills, and

competencies necessary to create, share, and use

digital content and be aware of the rules related to

intellectual property (h). C15. Social

Interaction/Collaboration. Consider social

interactions among learners and educators using

technology in digital education systems (h). Crucial

aspects involve cross-sector collaboration, new

models for sharing digital content, and common

standards for education. Exchange of knowledge and

practices fosters cooperation (g). C16. Innovative

Digital Learning Enablers. Support work with

innovative education tools for enhanced learning,

which could include gamification, educational

solutions based on, e.g., extended reality technologies

such as Augmented-/Virtual Reality, AI, learning

analytics, and social networks, which respect an

ethical and transparent approach, data privacy and

nondiscrimination by design, while considering

benefits and potential risks (h). C17. Social Support.

Consider social support in learning a crucial role,

especially regarding motivational aspects (e.g.,

family, digital parenting, educator role) (h), or even

anonymous, through online settings. C18.

Differentiation/Individualization. Differentiate

between different learner groups; tailor education and

training to individual needs through, e.g., algorithms

(influenced by, e.g., health condition, special

educational needs, and socio-economic background)

(h). C19. Quality Education Content. Meet high

standards of excellence, effectiveness, and relevance

regarding educational materials and resources.

Design quality education content to facilitate

meaningful learning experiences and contribute to

individuals’ overall educational development.

Consider a balance of digital and non-digital

approaches (h).

4.2.3 Work Context

C20. Flexibility. Time Flexibility (#20.1).

Individuals can choose when and how to work.

Enabled by digital tools and remote setups, it allows

for personalized schedules, promoting work-life

balance and satisfaction (i). Mobility/Location

Independence (#20.2). Implement a location-

independent office concept with digital tools

provided to staff, enabling location independence and

working efficiently from the best suitable place.

Shifting the nature of work from physical to virtual

workspaces saves time through improved use of

shadow time (e.g., commuting) and correlates with

enhanced productivity (i). Work-Life-Balance

(#20.3). Support balance between professional and

private life (i). Adaptability (#20.4). Monitor the

impact on the working environment and required

skills and adapt (b). Allow different views of the

digital workplace, be adaptive and flexible to

different types of users, behaviors, and new

technologies – from the simplest to the most complex

ones – with the same building blocks and with the

possibility of replacing or adding new ones easily (i).

C21. IT Environment. Integration (#21.1).

Seamlessly integrate the digital workplace with its

collection of tools, systems, platforms, interfaces,

programs, etc., allowing for a smooth and efficient

user experience (i). Standardization (#21.2). Enable

the potential integration of diverse building blocks

from various sources. Standards drive cost reductions

and low maintenance costs, facilitating rapid user

learning (i). Speed (#21.3). Allow the processes for

introducing new organizational elements to be fast

enough to cope with user expectations; no long and

heavy product management cycles (i). Simplicity

(#21.4). Take it simple; simplicity facilitates the

management of a corporate IT environment, reducing

costs (i). C22. Occupational Health and Safety.

Embrace an expansive and contemporary definition

of occupational health and safety in the evolving

digital workplace, e.g., focusing on AI-related

challenges like the right to disconnect and biased

algorithms causing discrimination. Advocate for

transparent solutions through collaboration between

employers and employee representatives. Address

mental health issues, combat online harassment, and

propose measures against workplace bullying and

violence (j). C23. Supportive Technologies for

Well-being. Provide workers, especially those with

disabilities or older workers and their employers, with

digitally enabled solutions, such as AI-based

conversational agents, to support their health and

well-being (k). C24. Social Support. Social support

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and social networking can decrease stress factors in

the workplace, such as technostress, isolation, or

inadequate organization of (remote) work (j). C25.

Collaboration/Knowledge Management. Facilitate

collaboration and break silos by leveraging

collaboration tools and social networking to allow the

fast creation of focused groups across institutional

boundaries. This enhances the organization’s

responsiveness to situations and crises, emphasizing

improved collaboration, knowledge sharing, and fast

communication. This facilitates faster creation and

dissemination of knowledge, co-creation of

information, and accessing pertinent data (i; k).

5 DISCUSSION

Based on relevant EU directives, this study proposes

a novel digital well-being taxonomy, comprising 25

characteristics with sub-characteristics that promote

human flourishing in an information society –

particularly within the EU and with potential for

broader applicability. The taxonomy provides

valuable insights for both research and practice.

In practice, it offers a structured, accessible

approach for non-legal practitioners, particularly in

the EU, and beyond. Importantly, it does not function

as a prescriptive list of digital well-being

characteristics, but rather as a flexible tool that can be

adapted to the specific needs and contexts of different

enterprises. Given the diversity of organizational

environments, the emphasis on characteristics must

be reassessed according to the relevant use cases, as

highlighted in the evaluation of the final taxonomy.

Practitioners can utilize the taxonomy to enhance

digital awareness by holistically understanding

digital well-being characteristics, assessing well-

being criteria, and formulating targeted strategies that

align with digital well-being objectives while

fostering innovation. For example, practitioners

aiming to promote digital well-being may classify

their enterprises according to the specific digital well-

being characteristics they have implemented, thereby

allowing for tailored strategies that address specific

gaps or areas for improvement.

Furthermore, the taxonomy supports the

development of effective frameworks, processes, and

other artifacts in IS research and practice, such as

interventions designed to mitigate the adverse

impacts of digitalization, like digital awareness

training. Preventative measures like these have not

yet been thoroughly evaluated (Rohwer et al., 2022).

The taxonomy provides a structured foundation for

creating training modules focused on specific

components of digital well-being, such as building

resilience to technostress or combating

misinformation (e.g., Carpenter et al., 2019; Szpitalak

et al., 2021). We encourage experts to apply and

evaluate the taxonomy, especially in the context of

digital awareness training, to explore its potential to

reduce the adverse impacts of technology on

employee well-being.

In theory, IS research has extensively examined

the role of technology in enabling human flourishing

(Burr et al., 2020; Calvo and Peters, 2014) as well as

the adverse impacts of digitalization (Abhari and

Vaghefi, 2022; Bonenberger et al., 2022; Ragu-

Nathan et al., 2008). However, it has frequently

neglected to incorporate a systematic legislative

approach, which has become increasingly relevant

due to a notable increase in related legislative action.

By integrating EU directives such as the Ethics

Guidelines for Trustworthy AI and the Digital

Services Act, the study extends current models of

digital well-being in IS. It encourages scholars to

engage more with legislative frameworks as integral

components of technology design, not external

constraints. In introducing the novel taxonomy, this

contribution aligns with calls for interdisciplinary

research approaches in HCI and HCAI, recognizing

the importance of social science in understanding the

broader impact of technology on society (Akkermans,

2023). This supports the ongoing shift from a techno-

centric to a human-centric approach in IS research,

contributing to the discourse on human-technology

symbiosis and well-being (Gorichanaz, 2024;

Stephanidis et al., 2019). The existing literature,

including studies by Lanzl (2023) on the role of social

support in reducing technostress in the workplace and

Seidler et al. (2020) on the use of gamification to

promote eco-sustainable behavior, can be mapped to

the taxonomy as social support in the work context

and environmental well-being/sustainability within

the social context. This demonstrates its relevance for

classifying research.

Future research should broaden the scope beyond

Europe, as although this study provides a strong

foundation, comparative analyses of legislative

frameworks governing digital well-being across

various regions could offer valuable insights.

Investigating and comparing the fundamentals and

principles embedded in different legislative contexts

could inform practitioners seeking to provide IS

services across diverse cultural landscapes. For

example, Schwartz (2012) has compared values

across different cultures and countries. Scholars could

be inspired to do something similar in the context of

legislation specifications of digital well-being. In

From Legislation to Human Flourishing: Unveiling the Characteristics of Digital Well-Being by Taxonomy Development from an EU

Perspective

401

addition, exploring public discourses surrounding

social interactions that influence perceptions of

digital well-being may also yield deeper insights.

Researchers should continue to evaluate and refine

the taxonomy, exploring its characteristics in greater

depth and considering it as a basis for design

principles in IS to evaluate existing or new prototypes

within design science research. Studies could also

investigate individual prevention strategies for

achieving digital well-being, like coping with

technostress. Applying the taxonomy in practice is

essential to enhance its validity. In the context of

digital awareness training, we encourage researchers

to empirically evaluate its efficacy as a foundation in

forming training modules designed to mitigate the

adverse impacts of technology on well-being.

Moreover, future research could employ

configurational theorizing (Gresov and Drazin, 1997;

Shortell, 1977) and systems thinking approaches

(Burton-Jones et al., 2015; Sarker et al., 2019) to

better understand how different characteristics

interact to shape digital well-being, providing a

nuanced framework for examining complex societal

and technical interactions. Given the multifaceted

nature of digital well-being, characterized by a web

of technical intricacies and societal implications, a

singular or dyadic approach cannot capture its

entirety. Instead, researchers should explore how

diverse configurations can produce similar outcomes

and how these are shaped by varying factors (Furnari

et al., 2021; Misangyi et al., 2017). This study

provides a comprehensive basis for further

investigation and advocates for ongoing exploration

and scholarly discourse on digital well-being and

human flourishing, fostering greater digital

awareness in an evolving digital landscape.

Limitations. The selected EU directives provide a

solid foundation for deriving characteristics of digital

well-being but are not exhaustive. Furthermore,

ethical priorities may shift over time (Kortum et al.,

2022), and the development of the taxonomy reflects

the authors’ expertise in an intuitive approach,

introducing some subjectivity. To this, explanations

concerning the taxonomy development, and its

findings are provided to allow other researchers to

follow and draw conclusions. Furthermore, the

taxonomy’s general nature allows broad application

but may limit specificity in particular use cases.

Future research should consider mapping digital well-

being to specific use cases and contexts for more

targeted applications.

6 CONCLUSION

This study introduces a digital well-being taxonomy

grounded in EU legislation, comprising 25 key

characteristics. It addresses the often-overlooked role

of legislation in shaping digital well-being. By

categorizing complex legislative aspects into clear,

understandable characteristics, the taxonomy

enhances digital awareness and provides a foundation

for developing strategies and artifacts in IS research

and practice that mitigate digitalization’s adverse

impacts, including digital awareness training. It is

relevant for European scholars and practitioners,

although the findings hold potential for wider

application in global contexts. Furthermore, it opens

new avenues for future research and highlights the

importance of interdisciplinary approaches,

integrating social science and legislation to address

technology’s broader impacts on well-being. By

offering a structured approach to digital well-being

from a legislative angle, this work addresses a gap in

the field and encourages ongoing exploration in HCI

and HCAI towards human flourishing in the digital

age.

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