Hedonic vs Eudaimonic Well-Being: Two Traditions in the Science of Human Flourishing

Last Updated May 23, 2026

One of the most important debates in well-being research concerns a deceptively simple question: what does it mean to live well? For centuries, philosophers, theologians, moral psychologists, political thinkers, and social scientists have offered different answers. Some traditions define well-being primarily in terms of pleasure, happiness, tranquility, comfort, or life satisfaction. Others argue that flourishing requires meaning, virtue, agency, autonomy, moral development, relational depth, practical wisdom, and the realization of human capacities. This tension has not disappeared in modern science. It has been reformulated in psychological, economic, public-health, and policy language.

Within contemporary psychology, the debate is often framed as the distinction between hedonic well-being and eudaimonic well-being. The hedonic tradition focuses on happiness, affective balance, subjective life satisfaction, and the felt quality of life. The eudaimonic tradition emphasizes purpose, virtue, agency, psychological functioning, growth, autonomy, self-realization, and the development of human potential. Both traditions capture something real about flourishing. The deeper question is whether either can stand alone, or whether a serious science of well-being must hold them together without collapsing one into the other.

The distinction matters because well-being is now used far beyond academic psychology. It appears in public policy, economics, workplace design, education, public health, sustainability, human development, and beyond-GDP measurement. A government measuring life satisfaction is making one kind of claim about progress. A school cultivating purpose and character is making another. A workplace measuring engagement is making yet another. Each use depends on an underlying theory of what well-being is, what counts as evidence, and what kind of life institutions should help make possible.

A mature science of well-being therefore needs conceptual discipline. Happiness matters, but not all happy lives are fully flourishing. Meaning matters, but a meaningful life may still include pain, grief, sacrifice, and difficulty. Life satisfaction matters, but satisfaction can coexist with constraint, adaptation, or injustice. Virtue and growth matter, but they can become paternalistic if imposed without respect for lived experience, culture, freedom, and plural ways of living well. The hedonic-eudaimonic distinction gives researchers, educators, policymakers, and institutions a vocabulary for holding these tensions in view.

This article examines how these two traditions developed, how they are measured scientifically, why the distinction remains central to the study of flourishing, and why the debate now matters not only for psychology, but also for public policy, institutional design, education, sustainability, and the measurement of social progress.

Philosophical Origins of the Debate

The distinction between hedonic and eudaimonic well-being has deep philosophical roots. The hedonic tradition reaches back to schools of thought that defined the good life in relation to pleasure, tranquility, satisfaction, and the avoidance of unnecessary pain. In simplified form, the hedonic position asks whether a life goes well because it feels good to the person living it. Pleasure, enjoyment, comfort, serenity, and satisfaction become central criteria of value.

This tradition has often been misunderstood. Hedonism does not always mean reckless indulgence. Classical forms of hedonistic ethics, especially Epicurean thought, often emphasized moderation, friendship, the absence of disturbance, and the wise regulation of desire. The hedonic question is therefore not merely whether a person has intense pleasure, but whether life is experienced as satisfying, bearable, pleasant, and free from excessive suffering.

A different perspective emerged in Aristotle’s ethics. Aristotle argued that the highest human good is eudaimonia, often translated as flourishing, living well, or human fulfillment. But this was never meant to describe pleasure alone. In Aristotle’s framework, flourishing concerns the realization of human capacities through virtuous activity, practical reason, ethical development, and meaningful participation in social life. A person may feel pleasure and yet live badly. Conversely, a worthwhile life may include sacrifice, discipline, grief, and difficulty while still counting as deeply good.

This distinction remains powerful because it separates two different questions. The hedonic question asks: How does life feel? The eudaimonic question asks: What kind of life is being lived? Both questions matter. A life of constant misery is difficult to call flourishing, no matter how noble its aims. But a life of comfort without meaning, relation, or moral substance may also seem incomplete.

Modern well-being science inherits both intuitions. Subjective well-being research continues the hedonic concern with lived experience, life satisfaction, and affect. Psychological well-being research continues the eudaimonic concern with purpose, growth, autonomy, relationships, competence, and self-realization. The debate remains unresolved not because science has failed to choose a side, but because human life appears to require more than one vocabulary of value.

This is why the distinction is not merely academic. It shapes how people evaluate their own lives, how institutions design programs, how governments measure progress, and how societies define development. A society organized only around comfort may become shallow. A society organized only around demanding ideals may become coercive. A wise account of flourishing must ask how happiness, meaning, virtue, agency, relation, and justice can be held together.

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The Hedonic Tradition in Well-Being Research

In modern psychology, the hedonic approach is most strongly associated with research on subjective well-being. This tradition asks how individuals evaluate their own lives and how frequently they experience positive and negative emotions. Subjective well-being is often described as comprising three broad components: life satisfaction, positive affect, and negative affect. It became especially influential because it offered a relatively clear way to make happiness scientifically measurable.

Ed Diener’s work was central to this development. His research helped establish subjective well-being as a legitimate scientific domain and contributed to the widespread use of the Satisfaction With Life Scale, a short five-item measure designed to capture global cognitive judgments of life satisfaction. The SWLS remains one of the field’s most widely used instruments precisely because it is brief, interpretable, and conceptually clear. It does not attempt to measure every aspect of flourishing. It measures a person’s evaluative sense of whether life is going well overall.

The hedonic model has important strengths. It takes lived experience seriously. It respects the fact that people are not merely objects of external evaluation; they are interpreters of their own lives. It allows researchers to compare well-being across persons, groups, regions, and nations. It has proven valuable in psychology, economics, public policy, public health, and comparative international work. Large cross-national projects, including the World Happiness Report, draw heavily on this tradition by using life evaluation as a core indicator.

The model also gives policy a human-centered corrective. Economic output, employment figures, or institutional performance data may suggest one story, while people’s own reports of life satisfaction may reveal another. If a society becomes wealthier but its people feel increasingly insecure, lonely, exhausted, or distrustful, subjective well-being data can make that contradiction visible. In this respect, hedonic measures have helped move social progress debates beyond income alone.

But the hedonic model also invites critique. A satisfying life is not necessarily a flourishing one in the richer ethical sense. People may adapt to unjust conditions and report moderate satisfaction. They may compare themselves to worse-off reference groups. They may value stability over freedom because freedom has never been realistically available. They may report happiness while lacking voice, education, health care, autonomy, or meaningful opportunity. Subjective satisfaction is indispensable evidence, but it is not the whole of well-being.

There is also a temporal issue. Hedonic well-being may capture present affect or current evaluation, but a life can feel pleasant now while undermining future flourishing. A consumer society may generate immediate comfort while weakening health, community, ecological stability, or long-term purpose. A workplace may offer perks while eroding autonomy and meaning. A society may raise reported satisfaction for some groups while transferring burden to others or to future generations.

The hedonic tradition therefore gives well-being science an essential foundation: people’s lived experience matters. But it also requires supplementation. Happiness, satisfaction, and affective balance should be studied alongside meaning, agency, virtue, relationships, capability, health, justice, and future viability. A good life should feel livable from within, but it should also be examined in terms of what kind of life it makes possible.

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Eudaimonic Well-Being and Human Flourishing

Eudaimonic approaches emphasize the quality of human functioning rather than positive feeling alone. This tradition asks whether a person is living meaningfully, developing capabilities, exercising agency, sustaining worthwhile relationships, contributing to others, and becoming more fully what they are capable of being. It shifts attention from momentary happiness to the structure, direction, and ethical texture of life as a whole.

In contemporary psychology, one of the most influential eudaimonic frameworks is Carol Ryff’s model of psychological well-being. Ryff’s framework identifies six dimensions: autonomy, environmental mastery, personal growth, positive relations with others, purpose in life, and self-acceptance. These dimensions became important because they offered a rigorous alternative to the idea that happiness alone could define flourishing. A person might be satisfied and still lack purpose, growth, or meaningful relation to the world. Conversely, someone engaged in demanding but deeply worthwhile activity may not always experience pleasant affect, yet may still be living well in a richer sense.

This perspective connects naturally to research on meaning and purpose in positive psychology. Meaning, purpose, contribution, and the development of capacities are not merely decorative additions to a happy life. They are often part of what makes life worth affirming in the first place. A meaningful life may include struggle, sacrifice, responsibility, grief, and effort. It may not always maximize pleasure. But it may still represent a deeper form of flourishing than comfort alone.

The eudaimonic tradition also connects positive psychology to moral psychology, developmental theory, virtue ethics, education, civic life, and public institutions. If well-being includes autonomy, competence, growth, relational depth, and purpose, then the conditions of well-being are not merely emotional. They include education, care, work, community, voice, public trust, ecological security, and institutional support. A person cannot fully exercise agency if they lack security. They cannot develop capacities if education is unavailable. They cannot sustain purpose if social conditions repeatedly undermine dignity and future possibility.

Eudaimonic well-being therefore has a broader social implication. It asks not only whether people feel well, but whether they have the conditions to become capable, responsible, connected, and meaningfully engaged. This makes it especially relevant to positive education, positive psychology and public health, the economics of well-being, and well-being and sustainable development.

Yet eudaimonic approaches also carry risks. Because they make claims about what constitutes a fuller life, they can become paternalistic if handled carelessly. Who decides what counts as growth? Whose ideals of purpose, autonomy, virtue, or self-realization are being used? Do eudaimonic measures reflect universal human needs, culturally specific ideals, or institutional preferences? These questions matter because a framework that claims to measure flourishing can shape education, employment, policy, and public life.

A mature eudaimonic science must therefore combine normative seriousness with humility. It should acknowledge that meaning, agency, growth, and relationships are central to flourishing while also recognizing cultural plurality, disability, life stage, grief, social constraint, and different moral traditions. Eudaimonia should not become an elite ideal imposed on others. It should become a disciplined inquiry into the conditions under which people can live lives of dignity, purpose, relation, and development.

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Modern Psychological Frameworks

Contemporary positive psychology increasingly attempts to integrate hedonic and eudaimonic perspectives rather than choosing one exclusively. This is one of the field’s real strengths. It has become more common to treat flourishing as multidimensional and to recognize that feeling good and functioning well are related but not identical.

Self-Determination Theory is especially important here. Developed by Richard Ryan and Edward Deci, it argues that well-being depends centrally on the satisfaction of three basic psychological needs: autonomy, competence, and relatedness. This framework has both hedonic and eudaimonic implications. When these needs are met, people often feel better, but they also function better, develop more fully, and sustain more self-endorsed forms of motivation.

Self-Determination Theory also helps correct a narrow individualistic reading of well-being. Autonomy does not mean isolation. Competence does not mean competitive achievement alone. Relatedness does not mean superficial social contact. These needs are supported or frustrated by environments. Families, schools, workplaces, public systems, and cultures can either support autonomy, competence, and relatedness or undermine them. That makes the theory highly relevant to institutional design.

The PERMA model of well-being likewise broadens the field beyond a single-variable understanding of happiness. The PERMA-Profiler measures five pillars—positive emotion, engagement, relationships, meaning, and accomplishment—alongside negative emotion, health, loneliness, and overall happiness. This is significant because it embeds hedonic and eudaimonic elements in the same measurement architecture. Positive emotion reflects the hedonic tradition. Engagement, meaning, relationships, and accomplishment move toward eudaimonic functioning.

Related lines of work on flow and optimal experience and broaden-and-build theory further show that flourishing cannot be reduced to any one dimension. Flow describes states of deep absorption in challenging, meaningful activity. Broaden-and-build theory suggests that positive emotions can expand thought-action repertoires and help build enduring resources. These frameworks bridge feeling and functioning: positive states matter partly because they can support long-term development, social connection, and resilience.

The modern field therefore increasingly treats well-being as an ecology of interacting dimensions. Life satisfaction, positive affect, meaning, autonomy, competence, relation, purpose, growth, health, accomplishment, and social context all matter. The central problem is not choosing a single definitive definition. It is building models that are conceptually clear enough for research, flexible enough for human complexity, and ethically responsible when used in institutions.

This multidimensional direction is promising because it reflects how people actually live. Human beings seek comfort and significance, pleasure and purpose, rest and growth, belonging and autonomy, present relief and future direction. A model that includes only one side of this pattern will always be incomplete.

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Measuring Hedonic and Eudaimonic Well-Being

The distinction between hedonic and eudaimonic well-being shapes not only theory, but measurement. Hedonic well-being is typically assessed through life satisfaction scales, affect measures, and subjective well-being surveys. These instruments are attractive because they are relatively efficient, statistically tractable, and suitable for large-scale comparison. They have been especially influential in economics and public policy because they make population-level life evaluation visible.

Eudaimonic well-being is measured differently. Researchers often use instruments that assess meaning in life, purpose, autonomy, personal growth, relationships, environmental mastery, self-acceptance, strengths-related functioning, or psychological well-being. Ryff’s scales remain especially important here. The PERMA-Profiler, by combining multiple domains, represents a hybrid effort to capture a broader architecture of flourishing. The field’s wider measurement work increasingly reflects the recognition that no single instrument adequately captures the full complexity of human well-being.

The measurement distinction can be summarized as follows:

This is why researchers now often combine multiple instruments. A person’s life satisfaction score may reveal one part of the story, while measures of meaning, strengths, psychological well-being, or functioning reveal others. The scientific challenge is not only to measure these domains, but to understand how they interact. A flourishing life may contain both hedonic and eudaimonic dimensions, and the balance between them may vary across persons, cultures, institutions, and life stages.

Measurement also carries theoretical risk. A measure does not merely record a concept; it helps define what researchers later treat as the concept. If well-being is measured only through life satisfaction, then the field may overemphasize subjective evaluation. If it is measured only through purpose and functioning, then it may underemphasize suffering, relief, and lived emotional quality. If it is measured through composite dashboards, then weighting choices become ethically important.

A responsible measurement framework should therefore disclose what it is measuring and what it is not measuring. It should avoid treating one score as the whole of the good life. It should test whether measures function similarly across groups. It should report uncertainty. And it should distinguish between individual experience, psychological functioning, social condition, and institutional context.

The goal is not to build a perfect instrument. The goal is to create disciplined, transparent, and humane measurement that helps researchers and institutions ask better questions about how lives actually go.

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Culture, Meaning, and the Plurality of Good Lives

The hedonic-eudaimonic distinction is useful, but it should not be treated as culturally neutral or universally exhaustive. Different societies, religious traditions, philosophical systems, and communities interpret happiness, meaning, duty, autonomy, suffering, and flourishing differently. A model of well-being that emerges from one cultural setting may illuminate human life broadly, but it may also miss forms of value that matter elsewhere.

Hedonic measures can face cultural challenges because people differ in how they report satisfaction, express emotion, use rating scales, and compare their lives to others. Some cultures may discourage strong claims of personal happiness. Others may encourage positive self-reporting. Some people may define satisfaction relationally, spiritually, or communally rather than individually. Translation can preserve literal wording while losing moral or emotional resonance.

Eudaimonic measures face their own challenges. Concepts such as autonomy, purpose, self-acceptance, personal growth, and environmental mastery may not carry identical meanings across cultures. Autonomy may be understood as self-expression in one setting and as responsible self-governance within obligation in another. Purpose may be individual, familial, religious, civic, ecological, or communal. Growth may be framed as self-actualization, moral refinement, service, discipline, humility, or spiritual maturity.

This does not make measurement impossible. It makes humility necessary. A global science of well-being must be comparative without being imperial. It should ask which dimensions of flourishing appear widely important—relationships, health, meaning, dignity, security, agency, trust—while also studying how those dimensions are locally interpreted and institutionally supported. It should not assume that a Western individualist grammar of happiness, autonomy, or achievement exhausts the meaning of a good life.

The cultural issue also matters for sustainability and public policy. A society’s definition of progress depends on its definition of well-being. If progress is defined through consumption and subjective satisfaction alone, ecological limits may appear as threats to the good life. If progress includes meaning, relation, stewardship, sufficiency, care, and intergenerational responsibility, sustainability can be understood as part of flourishing rather than as a sacrifice imposed from outside.

Many religious, Indigenous, communal, and philosophical traditions contain rich accounts of restraint, gratitude, responsibility, humility, reciprocity, care, and interdependence. These cannot be reduced neatly to hedonic or eudaimonic categories, but they can deepen both. A serious science of well-being should learn from these traditions rather than treating them as pre-scientific background.

The plurality of good lives does not mean that anything counts as flourishing. It means that well-being science must hold universal human concerns together with cultural particularity. Human beings need care, dignity, relation, and meaningful possibility. But the forms through which these goods are understood and lived vary. A mature hedonic-eudaimonic framework must be wide enough to see both sameness and difference.

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Implications for Public Policy and Sustainability

The distinction between hedonic and eudaimonic well-being has important implications for public policy and sustainability. If policy is guided only by hedonic metrics, governments may focus too narrowly on immediate life satisfaction or short-term subjective comfort. If policy is guided only by eudaimonic ideals, it may risk paternalism by privileging externally defined notions of what constitutes a worthy life. The challenge is not simply to pick a side, but to design measures and institutions that respect both lived experience and the broader conditions of flourishing.

This is one reason beyond-GDP frameworks have become so important. The OECD now explicitly frames well-being measurement around current outcomes, inequalities, and the resources shaping future well-being, while UNDP continues to emphasize human development through capabilities and life chances rather than output alone. These approaches imply that flourishing cannot be captured by income or consumption alone. They also suggest that quality of life includes both experienced and developmental dimensions.

From a sustainability perspective, this distinction matters even more. A society organized around consumption and immediate satisfaction may generate hedonic benefits in the short term while undermining the ecological, institutional, and social conditions of flourishing over time. By contrast, a more eudaimonic framework emphasizes meaning, social participation, capability development, responsibility, and durable human functioning—dimensions that align more naturally with long-horizon models of sustainable development.

But eudaimonic policy must also remain democratic. Institutions should not impose a single official model of purpose or virtue. Public systems should create the conditions under which people can pursue meaningful lives, not dictate one meaning of life. This distinction is crucial. A well-being policy framework should support health, education, care, dignity, time, security, voice, ecological stability, public trust, and social participation. It should not convert flourishing into state-managed moral conformity.

In education, the hedonic-eudaimonic distinction affects whether schools focus only on student happiness and stress reduction or also on agency, meaning, character, belonging, curiosity, and civic development. In public health, it affects whether health is treated only as symptom reduction or also as social functioning, resilience, dignity, and participation. In labor policy, it affects whether work is judged only by wages and satisfaction or also by autonomy, meaning, safety, voice, and relational dignity. In sustainability, it affects whether prosperity is defined by present consumption or by long-term, shared human capability within ecological limits.

A responsible policy framework should therefore combine subjective and objective indicators. It should ask how people evaluate their lives, but also whether they have access to the conditions that make meaningful lives possible. It should measure happiness, but also housing, health, trust, education, care, inequality, ecological exposure, time pressure, and future viability. The goal is not to replace GDP with happiness alone. It is to build a richer public vocabulary of progress.

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Critiques, Misuses, and Conceptual Risks

The hedonic-eudaimonic distinction is powerful, but it can be misused. One risk is oversimplification. Hedonic well-being is sometimes caricatured as shallow pleasure, while eudaimonic well-being is romanticized as morally superior. This is too simple. Relief from pain, joy, comfort, pleasure, affection, and life satisfaction are not trivial. They are central to human life. Likewise, meaning and purpose can become harmful if pursued through fanaticism, exploitation, coercion, or self-neglect. The issue is not that one tradition is superficial and the other profound. The issue is that each captures a different dimension of value.

Another risk is measurement reductionism. Researchers may treat a hedonic or eudaimonic scale as though it exhausts well-being. A life satisfaction score is important, but it is not a full biography. A purpose score is important, but it is not moral wisdom. A PERMA profile is useful, but it is not the whole architecture of a life. Measurement must remain modest about its scope.

A third risk concerns institutional use. Workplaces, schools, platforms, health systems, and governments may use well-being concepts to manage individuals rather than improve conditions. A workplace might measure engagement while ignoring overwork or insecurity. A school might teach resilience while ignoring poverty, disability access, trauma, or underfunding. A government might report average well-being while concealing inequality. In such cases, the language of flourishing can become a tool of adjustment rather than liberation.

A fourth risk is cultural narrowness. Hedonic and eudaimonic categories emerged within particular philosophical and scientific traditions. They are useful, but not exhaustive. Many ways of living well emphasize sacred obligation, community continuity, kinship, land, humility, service, ritual, ecological reciprocity, or collective memory. These should not be forced into narrow psychological categories without careful interpretation.

A fifth risk is moral pressure. Eudaimonic language can unintentionally make people feel obligated to transform suffering into growth, always find purpose, or constantly develop themselves. But some suffering should be mourned, resisted, or repaired rather than converted into personal development. A grieving person does not owe the world a narrative of growth. A marginalized community does not need to prove resilience in order to deserve justice.

A mature science of well-being must therefore be careful. Hedonic measures should not become shallow happiness management. Eudaimonic measures should not become moral surveillance. Integrated flourishing frameworks should not become technocratic dashboards that erase lived complexity. The distinction between hedonia and eudaimonia is most useful when it helps researchers and institutions think more honestly, not when it becomes another simplified tool for ranking lives.

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Toward an Integrated Model of Well-Being

Most contemporary researchers no longer regard hedonic and eudaimonic well-being as mutually exclusive. Instead, flourishing is increasingly understood as a multidimensional phenomenon that includes emotional well-being, meaningful activity, relational depth, agency, development, health, dignity, and accomplishment. Pleasure matters. Satisfaction matters. Meaning matters. So do competence, growth, belonging, autonomy, security, and participation in social life.

The challenge is not to dissolve the distinction, because the distinction remains analytically useful. It helps clarify what exactly is being measured, what kind of good is being discussed, and where competing theories of the good life diverge. But integration is still necessary because human lives are not lived in isolated categories. People seek both enjoyment and significance. They want relief from suffering, but they also want purpose, relation, and the sense that their lives amount to something.

A mature science of well-being therefore needs both traditions. Hedonic research keeps the field attentive to lived experience. Eudaimonic research keeps it attentive to the quality and direction of life. Together they provide a more complete framework for studying what it means to live well.

An integrated model should include at least five commitments:

• Subjective experience matters. People’s own evaluations of their lives are indispensable evidence.
• Functioning matters. A good life includes agency, development, relationship, purpose, and the exercise of capacities.
• Context matters. Well-being is shaped by institutions, culture, social conditions, health, ecology, and power.
• Distribution matters. Average well-being can hide unequal burdens and unequal access to flourishing.
• Time matters. Present happiness should not be purchased by future harm, depletion, or institutional fragility.

Integration does not require every measure to include every dimension. A life satisfaction scale can remain a life satisfaction scale. A meaning measure can remain a meaning measure. The point is that interpretation should be multidimensional. Researchers should know which part of the well-being architecture they are measuring and which parts remain outside the frame.

A strong integrated model also makes room for conflict. Hedonic and eudaimonic well-being do not always move together. A person may choose demanding work that reduces short-term pleasure but increases meaning. A person may leave a comfortable but empty situation in pursuit of purpose. A caregiver may experience stress and fatigue while also living with deep relational significance. A society may reduce consumption but increase community, health, and ecological stability. These tensions are not measurement errors. They are part of the complexity of living well.

The goal of integration is therefore not to flatten hedonia and eudaimonia into one vague idea of wellness. It is to preserve the distinction while understanding how the dimensions interact across lives, communities, institutions, and time.

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A Semi-Formal Framework for Hedonic and Eudaimonic Well-Being

The distinction can be clarified semi-formally. Let overall flourishing at time \(t\) be represented as:

We can specify the hedonic component as:

The eudaimonic component can be expressed as:

A dynamic model can clarify interaction across time:

This formulation is important because it shows that hedonic and eudaimonic well-being are not static traits. They are shaped by life processes, relationships, institutions, stress, opportunity, and time.

An interaction model can also be useful:

A distributional version becomes important for public policy:

The value of these equations is not that they fully capture the good life. They do not. Their value is conceptual discipline. They clarify what is being modeled, how hedonic and eudaimonic domains are separated, where interaction is possible, and why context and inequality cannot be ignored.

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Data Design and Measurement Notes

A useful empirical framework for hedonic and eudaimonic well-being should preserve conceptual distinctions while allowing researchers to study interaction. The goal is not to force all dimensions into a single score too quickly. The goal is to measure each domain clearly, then examine how they relate.

Researchers should avoid treating hedonic and eudaimonic measures as interchangeable. A life satisfaction scale does not measure purpose. A purpose scale does not measure happiness. A psychological well-being scale does not measure all social conditions. A composite index may be useful, but only if its dimensions, weights, and assumptions are transparent.

Several practical design principles follow:

• Keep separate scores before combining. Report hedonic, eudaimonic, relational, and contextual indicators separately before building composites.
• Direction-correct carefully. Negative affect, stress load, loneliness, and insecurity should be handled transparently.
• Test reliability within domains. Do not assume that all items belong together because they sound positive.
• Check measurement invariance where possible. Group comparisons may be misleading if scales behave differently across cultures or populations.
• Model interaction. Hedonic and eudaimonic well-being may reinforce one another, compensate for one another, or diverge.
• Report distributions. Average well-being can hide severe gaps across class, race, disability, gender, age, region, or ecological exposure.
• Use qualitative interpretation. Some meanings of flourishing cannot be captured adequately by numeric scores alone.

For institutional or policy use, measurement should be especially cautious. The purpose of well-being data should be to improve conditions, not to rank individuals or pressure people to report positivity. A low hedonic score may signal suffering. A low eudaimonic score may signal lack of opportunity. Neither should be treated as personal failure without context.

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R: Modeling Hedonic and Eudaimonic Well-Being Together

The following R workflow illustrates how a researcher might model hedonic and eudaimonic well-being jointly in a repeated-measures dataset. The example constructs separate indices for hedonic and eudaimonic dimensions, tests reliability, estimates a mixed-effects model, and examines whether hedonic and eudaimonic well-being interact in predicting broader flourishing.

# Hedonic and eudaimonic well-being workflow
#
# Purpose:
#   Model feeling good and functioning well as related but distinct
#   dimensions of flourishing in repeated-measures data.
#
# Notes:
#   This workflow is for research, teaching, and exploratory analysis.
#   It is not a clinical, diagnostic, therapeutic, workplace-screening,
#   employment-selection, or individual well-being assessment tool.

library(tidyverse)
library(psych)
library(lme4)
library(lmerTest)
library(broom.mixed)
library(emmeans)
library(performance)

# Expected columns:
# id, wave, group,
# life_satisfaction, positive_affect, negative_affect,
# autonomy, personal_growth, purpose_life, positive_relations,
# environmental_mastery, self_acceptance,
# flourishing_outcome, stress_load, contextual_support

df <- read_csv("data/hedonic_eudaimonic_panel.csv")

panel <- df %>%
  mutate(
    id = as.factor(id),
    group = as.factor(group),
    wave = as.integer(wave)
  ) %>%
  filter(complete.cases(
    life_satisfaction,
    positive_affect,
    negative_affect,
    autonomy,
    personal_growth,
    purpose_life,
    positive_relations,
    environmental_mastery,
    self_acceptance,
    flourishing_outcome,
    stress_load,
    contextual_support
  ))

# Reliability check for hedonic items.
# Negative affect is direction-corrected so higher values indicate better affective balance.
hedonic_items <- panel %>%
  transmute(
    life_satisfaction,
    positive_affect,
    negative_affect_reversed = -negative_affect
  )

psych::alpha(hedonic_items)

# Reliability check for eudaimonic items.
eudaimonic_items <- panel %>%
  select(
    autonomy,
    personal_growth,
    purpose_life,
    positive_relations,
    environmental_mastery,
    self_acceptance
  )

psych::alpha(eudaimonic_items)

panel_scored <- panel %>%
  mutate(
    life_satisfaction_z = as.numeric(scale(life_satisfaction)),
    positive_affect_z = as.numeric(scale(positive_affect)),
    negative_affect_z = as.numeric(scale(negative_affect)),
    autonomy_z = as.numeric(scale(autonomy)),
    personal_growth_z = as.numeric(scale(personal_growth)),
    purpose_life_z = as.numeric(scale(purpose_life)),
    positive_relations_z = as.numeric(scale(positive_relations)),
    environmental_mastery_z = as.numeric(scale(environmental_mastery)),
    self_acceptance_z = as.numeric(scale(self_acceptance)),
    stress_load_z = as.numeric(scale(stress_load)),
    contextual_support_z = as.numeric(scale(contextual_support)),
    hedonic_index =
      life_satisfaction_z +
      positive_affect_z -
      negative_affect_z,
    eudaimonic_index = rowMeans(
      select(
        .,
        autonomy_z,
        personal_growth_z,
        purpose_life_z,
        positive_relations_z,
        environmental_mastery_z,
        self_acceptance_z
      ),
      na.rm = TRUE
    ),
    integrated_flourishing_index =
      0.40 * hedonic_index +
      0.45 * eudaimonic_index +
      0.20 * contextual_support_z -
      0.20 * stress_load_z,
    wave_c = as.numeric(scale(wave, center = TRUE, scale = FALSE)),
    hedonic_c = as.numeric(scale(hedonic_index, center = TRUE, scale = FALSE)),
    eudaimonic_c = as.numeric(scale(eudaimonic_index, center = TRUE, scale = FALSE)),
    support_c = as.numeric(scale(contextual_support_z, center = TRUE, scale = FALSE)),
    stress_c = as.numeric(scale(stress_load_z, center = TRUE, scale = FALSE))
  )

model_wb <- lmer(
  flourishing_outcome ~
    wave_c +
    hedonic_c +
    eudaimonic_c +
    support_c -
    stress_c +
    hedonic_c:eudaimonic_c +
    eudaimonic_c:support_c +
    hedonic_c:stress_c +
    (1 + wave_c | id),
  data = panel_scored,
  REML = FALSE
)

summary(model_wb)
performance::check_model(model_wb)

# Estimated marginal means:
# How hedonic well-being relates to flourishing at different levels of eudaimonic well-being.
emm_hedonic_eudaimonic <- emmeans(
  model_wb,
  ~ hedonic_c | eudaimonic_c,
  at = list(
    hedonic_c = c(-1, 0, 1),
    eudaimonic_c = c(-1, 0, 1),
    support_c = 0,
    stress_c = 0,
    wave_c = 0
  )
)

# Estimated marginal means:
# How eudaimonic well-being relates to flourishing under different levels of contextual support.
emm_eudaimonic_support <- emmeans(
  model_wb,
  ~ eudaimonic_c | support_c,
  at = list(
    eudaimonic_c = c(-1, 0, 1),
    support_c = c(-1, 0, 1),
    hedonic_c = 0,
    stress_c = 0,
    wave_c = 0
  )
)

dir.create("outputs", showWarnings = FALSE)

write_csv(
  broom.mixed::tidy(model_wb, effects = "fixed", conf.int = TRUE),
  "outputs/hedonic_eudaimonic_model_results.csv"
)

write_csv(
  broom.mixed::tidy(model_wb, effects = "ran_pars", conf.int = TRUE),
  "outputs/hedonic_eudaimonic_random_effects.csv"
)

write_csv(
  as.data.frame(emm_hedonic_eudaimonic),
  "outputs/hedonic_by_eudaimonic_estimated_margins.csv"
)

write_csv(
  as.data.frame(emm_eudaimonic_support),
  "outputs/eudaimonic_by_support_estimated_margins.csv"
)

write_csv(
  panel_scored,
  "outputs/hedonic_eudaimonic_scored_panel.csv"
)

domain_summary <- panel_scored %>%
  group_by(group) %>%
  summarize(
    mean_hedonic_index = mean(hedonic_index, na.rm = TRUE),
    mean_eudaimonic_index = mean(eudaimonic_index, na.rm = TRUE),
    mean_integrated_flourishing = mean(integrated_flourishing_index, na.rm = TRUE),
    mean_contextual_support = mean(contextual_support_z, na.rm = TRUE),
    mean_stress_load = mean(stress_load_z, na.rm = TRUE),
    .groups = "drop"
  ) %>%
  arrange(desc(mean_integrated_flourishing))

write_csv(
  domain_summary,
  "outputs/hedonic_eudaimonic_group_summary.csv"
)

This workflow is useful because it preserves the distinction between feeling good and functioning well while allowing the analyst to test whether they reinforce one another, compensate for one another, or diverge across persons and time. It also introduces contextual support and stress load so that well-being is not modeled as a purely private psychological state.

The interaction between hedonic and eudaimonic well-being is especially important. In some datasets, life satisfaction may predict flourishing most strongly when meaning and purpose are also high. In others, eudaimonic functioning may remain high even when affective experience is strained, as in caregiving, activism, demanding creative work, or morally serious forms of service. These patterns should be interpreted with care rather than forced into a single hierarchy.

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Python: Network Analysis of Well-Being Structure

The following Python example treats hedonic and eudaimonic well-being as a connected system rather than as isolated categories. It estimates a sparse partial-correlation network across life satisfaction, affect, meaning, growth, autonomy, relationships, self-acceptance, contextual support, and stress load in order to identify structurally central dimensions of flourishing.

"""
Hedonic and eudaimonic well-being network workflow

Purpose:
    Estimate a sparse network of well-being variables using partial
    correlations, then summarize centrality.

Use:
    Research, teaching, exploratory systems analysis, and measurement design.

Not for:
    Clinical diagnosis, therapeutic decision-making, employment selection,
    workplace screening, or individual well-being assessment.
"""

from pathlib import Path

import matplotlib.pyplot as plt
import networkx as nx
import numpy as np
import pandas as pd

from sklearn.covariance import GraphicalLassoCV
from sklearn.decomposition import PCA
from sklearn.impute import SimpleImputer
from sklearn.preprocessing import StandardScaler

DATA_PATH = Path("data/hedonic_eudaimonic_network.csv")
OUTPUT_DIR = Path("outputs")
OUTPUT_DIR.mkdir(exist_ok=True)

cols = [
    "life_satisfaction",
    "positive_affect",
    "negative_affect",
    "autonomy",
    "personal_growth",
    "purpose_life",
    "positive_relations",
    "environmental_mastery",
    "self_acceptance",
    "contextual_support",
    "stress_load",
]

df = pd.read_csv(DATA_PATH)

missing_cols = [col for col in cols if col not in df.columns]
if missing_cols:
    raise ValueError(f"Missing expected columns: {missing_cols}")

# Median imputation is used for demonstration.
# Applied research should document missingness patterns carefully.
imputer = SimpleImputer(strategy="median")
X = pd.DataFrame(imputer.fit_transform(df[cols]), columns=cols)

scaler = StandardScaler()
X_scaled = pd.DataFrame(scaler.fit_transform(X), columns=cols)

# Direction-corrected composite indicators.
X_scaled["hedonic_index"] = (
    X_scaled["life_satisfaction"] +
    X_scaled["positive_affect"] -
    X_scaled["negative_affect"]
)

X_scaled["eudaimonic_index"] = X_scaled[
    [
        "autonomy",
        "personal_growth",
        "purpose_life",
        "positive_relations",
        "environmental_mastery",
        "self_acceptance",
    ]
].mean(axis=1)

X_scaled["integrated_flourishing_index"] = (
    0.40 * X_scaled["hedonic_index"] +
    0.45 * X_scaled["eudaimonic_index"] +
    0.20 * X_scaled["contextual_support"] -
    0.20 * X_scaled["stress_load"]
)

# Dimensional inspection.
pca = PCA(n_components=3)
pca.fit_transform(X_scaled[cols])

pca_summary = pd.DataFrame({
    "component": [1, 2, 3],
    "variance_explained": pca.explained_variance_ratio_,
    "cumulative_variance_explained": np.cumsum(pca.explained_variance_ratio_),
})

pca_summary.to_csv(
    OUTPUT_DIR / "hedonic_eudaimonic_pca_variance.csv",
    index=False
)

# Graphical Lasso estimates a sparse inverse covariance matrix.
glasso = GraphicalLassoCV()
glasso.fit(X_scaled[cols])

precision = glasso.precision_

# Convert precision matrix to partial correlations.
partial_corr = -precision / np.sqrt(np.outer(np.diag(precision), np.diag(precision)))
np.fill_diagonal(partial_corr, 0)

partial_df = pd.DataFrame(partial_corr, index=cols, columns=cols)
partial_df.to_csv(OUTPUT_DIR / "hedonic_eudaimonic_partial_correlations.csv")

# Build network from thresholded partial correlations.
threshold = 0.08
G = nx.Graph()

for node in cols:
    G.add_node(node)

for i, source in enumerate(cols):
    for j, target in enumerate(cols):
        if j > i:
            weight = partial_df.iloc[i, j]
            if abs(weight) >= threshold:
                G.add_edge(source, target, weight=weight, sign=np.sign(weight))

degree = nx.degree_centrality(G)
betweenness = nx.betweenness_centrality(G, weight="weight")

try:
    eigenvector = nx.eigenvector_centrality_numpy(G, weight="weight")
except nx.NetworkXException:
    eigenvector = {node: np.nan for node in G.nodes()}

centrality = pd.DataFrame({
    "node": list(G.nodes()),
    "degree_centrality": [degree[node] for node in G.nodes()],
    "betweenness_centrality": [betweenness[node] for node in G.nodes()],
    "eigenvector_centrality": [eigenvector[node] for node in G.nodes()],
}).sort_values(
    ["eigenvector_centrality", "degree_centrality"],
    ascending=False
)

centrality.to_csv(
    OUTPUT_DIR / "hedonic_eudaimonic_network_centrality.csv",
    index=False
)

edge_table = pd.DataFrame([
    {
        "source": source,
        "target": target,
        "partial_correlation": data["weight"],
        "absolute_weight": abs(data["weight"]),
        "sign": "positive" if data["weight"] > 0 else "negative",
    }
    for source, target, data in G.edges(data=True)
]).sort_values("absolute_weight", ascending=False)

edge_table.to_csv(
    OUTPUT_DIR / "hedonic_eudaimonic_network_edges.csv",
    index=False
)

X_scaled.to_csv(
    OUTPUT_DIR / "hedonic_eudaimonic_scaled_indices.csv",
    index=False
)

print("\nCentrality summary:")
print(centrality)

print("\nStrongest edges:")
print(edge_table.head(15))

# Draw the network.
plt.figure(figsize=(12, 9))
pos = nx.spring_layout(G, seed=42, k=0.85)

positive_edges = [(u, v) for u, v in G.edges() if G[u][v]["weight"] > 0]
negative_edges = [(u, v) for u, v in G.edges() if G[u][v]["weight"] < 0]

nx.draw_networkx_nodes(G, pos, node_size=1800)
nx.draw_networkx_labels(G, pos, font_size=9)

nx.draw_networkx_edges(
    G,
    pos,
    edgelist=positive_edges,
    width=[abs(G[u][v]["weight"]) * 5 for u, v in positive_edges],
    alpha=0.75,
)

nx.draw_networkx_edges(
    G,
    pos,
    edgelist=negative_edges,
    width=[abs(G[u][v]["weight"]) * 5 for u, v in negative_edges],
    style="dashed",
    alpha=0.75,
)

plt.title("Partial Correlation Network of Hedonic and Eudaimonic Well-Being")
plt.axis("off")
plt.tight_layout()
plt.savefig(OUTPUT_DIR / "hedonic_eudaimonic_network.png", dpi=300)
plt.close()

This kind of analysis can reveal whether meaning, life satisfaction, relationships, personal growth, contextual support, or stress load functions as a more central leverage point in a given population. That matters because different well-being traditions may converge empirically in some contexts and diverge sharply in others.

Network models should not be interpreted as causal proof. They are exploratory tools for identifying relationships that may deserve further investigation, theory-building, longitudinal testing, and qualitative interpretation. If purpose appears central, researchers should examine whether it is functioning as a bridge between affect, autonomy, and relationships. If contextual support appears central, researchers should ask whether individual well-being is being shaped more strongly by institutional or social conditions than by private traits alone. If stress load is highly connected, researchers should avoid treating low well-being as merely a failure of mindset.

The purpose of the model is not to replace theory. It is to help researchers reason more clearly about the structure of well-being.

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Interpretation and Responsible Use

Because hedonic and eudaimonic well-being measures can travel into schools, workplaces, public dashboards, health systems, and policy research, responsible use matters. These measures can clarify important patterns, but they can also be misused when treated as complete assessments of persons, communities, employees, students, or cultures.

The code examples above are designed for population-level research, teaching, exploratory modeling, and measurement design. They should not be used as clinical diagnostic instruments, therapeutic decision tools, workplace-screening systems, employment-selection tools, public-benefits eligibility tools, or individual well-being assessment systems. Well-being data can be sensitive even when they appear nonclinical.

Several principles follow:

• Do not collapse lives into scores. Hedonic and eudaimonic indices are partial indicators, not full accounts of human beings.
• Measure conditions as well as experiences. Life satisfaction and purpose should be interpreted alongside security, health, care, work, environment, and institutional support.
• Avoid moralizing low well-being. Distress, low satisfaction, or low purpose may reflect structural burden, grief, trauma, exclusion, disability, or insecurity.
• Respect cultural meaning. Happiness, autonomy, purpose, and growth may be interpreted differently across communities and traditions.
• Protect privacy. Well-being data should be collected, stored, and reported with safeguards appropriate to sensitive human data.
• Report uncertainty. Reliability, validity, missingness, weighting assumptions, and limitations should be documented.
• Use measurement to improve conditions. The goal should be better environments, not surveillance or pressure to perform positivity.

A responsible approach treats the hedonic-eudaimonic distinction as a tool for understanding flourishing, not as a mechanism for ranking lives. It helps ask better questions: Do people feel their lives are going well? Do they have meaning, agency, and relational support? Are the conditions of flourishing fairly distributed? Are institutions supporting or undermining well-being? Are present forms of satisfaction sustainable over time?

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GitHub Repository

The companion repository for this article organizes the R, Python, data-schema, and documentation materials into a reproducible workflow for modeling hedonic and eudaimonic well-being together. It includes sample data dictionaries, scripts for model estimation, network-analysis outputs, validation notes, and guidance for responsible interpretation.

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Conclusion

The debate between hedonic and eudaimonic well-being reflects a deeper question about the nature of human flourishing. The hedonic tradition emphasizes happiness, affect, and subjective life evaluation. The eudaimonic tradition emphasizes meaning, virtue, agency, growth, autonomy, relation, and psychological development. Each tradition illuminates something important, but neither is sufficient on its own.

Modern positive psychology increasingly integrates these perspectives, recognizing that flourishing involves both feeling good and functioning well. That integration is not a vague compromise. It is an acknowledgment that human lives are evaluated along more than one axis, and that a serious science of well-being must remain open to both experiential and developmental conceptions of the good life.

The distinction also matters beyond psychology. Public policy, education, public health, sustainability, economics, workplace design, and institutional governance all depend on theories of well-being, whether explicit or hidden. A society that measures only subjective satisfaction may miss meaning, agency, capability, and justice. A society that imposes a single ideal of flourishing may ignore freedom, culture, suffering, and lived experience. The challenge is to measure and support well-being without reducing it.

A mature account of flourishing should therefore ask several questions at once. Do people experience happiness and relief from suffering? Do they have purpose, agency, relationship, and development? Are the conditions of flourishing socially supported? Are burdens distributed fairly? Are present forms of satisfaction compatible with future well-being? Are institutions helping people live meaningful lives, or merely asking them to adapt to conditions that should be changed?

Hedonic and eudaimonic traditions are not rival slogans. They are two enduring ways of seeing the good life. The future of well-being science depends on holding them together with enough clarity, humility, and ethical seriousness to do justice to the complexity of human life.

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Related articles

• Positive Psychology article map
• Subjective Well-Being and Life Satisfaction
• The PERMA Model of Well-Being
• Self-Determination Theory and Positive Psychology
• Meaning and Purpose in Positive Psychology
• The Science of Flourishing: How Positive Psychology Measures Well-Being
• Flow and Optimal Experience in Positive Psychology
• Broaden-and-Build Theory in Positive Psychology
• The Economics of Well-Being
• Well-Being and Sustainable Development
• The Future of Well-Being Science

Further reading

• Kahneman, D., Diener, E. and Schwarz, N. (eds.) (1999) Well-Being: The Foundations of Hedonic Psychology. New York: Russell Sage Foundation.
• Nussbaum, M.C. (2011) Creating Capabilities: The Human Development Approach. Cambridge, MA: Harvard University Press.
• Ryan, R.M. and Deci, E.L. (2001) ‘On happiness and human potentials: A review of research on hedonic and eudaimonic well-being’, Annual Review of Psychology, 52, pp. 141–166. Available at: https://doi.org/10.1146/annurev.psych.52.1.141.
• Ryff, C.D. (2014) ‘Psychological well-being revisited: Advances in the science and practice of eudaimonia’, Psychotherapy and Psychosomatics, 83(1), pp. 10–28. Available at: https://doi.org/10.1159/000353263.
• Sen, A. (1999) Development as Freedom. New York: Oxford University Press.
• VanderWeele, T.J. (2017) ‘On the promotion of human flourishing’, Proceedings of the National Academy of Sciences, 114(31), pp. 8148–8156. Available at: https://doi.org/10.1073/pnas.1702996114.
• World Happiness Report (2025) World Happiness Report 2025. Oxford: Wellbeing Research Centre, University of Oxford. Available at: https://www.worldhappiness.report/ed/2025/.

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References

• Deci, E.L. and Ryan, R.M. (2008) ‘Hedonia, eudaimonia, and well-being: An introduction’, Journal of Happiness Studies, 9, pp. 1–11. Available at: https://doi.org/10.1007/s10902-006-9018-1.
• Diener, E., Emmons, R.A., Larsen, R.J. and Griffin, S. (1985) ‘The Satisfaction With Life Scale’, Journal of Personality Assessment, 49(1), pp. 71–75. Available at: https://labs.psychology.illinois.edu/~ediener/Documents/Diener-Emmons-Larsen-Griffin_1985.pdf.
• Ed Diener, Subjective Well-Being Laboratory (n.d.) Satisfaction With Life Scale. Available at: https://labs.psychology.illinois.edu/~ediener/SWLS.html.
• OECD (2026) Measuring well-being and progress. Available at: https://www.oecd.org/en/topics/measuring-well-being-and-progress.html.
• OECD (2026) Well-being and beyond GDP. Available at: https://www.oecd.org/en/topics/well-being-and-beyond-gdp.html.
• Positive Psychology Center (n.d.) PERMA Profiler. University of Pennsylvania. Available at: https://ppc.sas.upenn.edu/resources/questionnaires-researchers/perma-profiler.
• Positive Psychology Center (n.d.) PERMA Theory of Well-Being. University of Pennsylvania. Available at: https://ppc.sas.upenn.edu/learn-more/perma-theory-well-being-and-perma-workshops.
• Ryan, R.M. and Deci, E.L. (2001) ‘On happiness and human potentials: A review of research on hedonic and eudaimonic well-being’, Annual Review of Psychology, 52, pp. 141–166. Available at: https://doi.org/10.1146/annurev.psych.52.1.141.
• Ryff, C.D. (1989) ‘Happiness is everything, or is it? Explorations on the meaning of psychological well-being’, Journal of Personality and Social Psychology, 57(6), pp. 1069–1081. Available at: https://doi.org/10.1037/0022-3514.57.6.1069.
• Ryff, C.D. and Keyes, C.L.M. (1995) ‘The structure of psychological well-being revisited’, Journal of Personality and Social Psychology, 69(4), pp. 719–727. Available at: https://midus.wisc.edu/findings/pdfs/830.pdf.
• UNDP (2026) Human Development Reports. Available at: https://hdr.undp.org/.
• World Happiness Report (2025) World Happiness Report 2025. Oxford: Wellbeing Research Centre, University of Oxford. Available at: https://www.worldhappiness.report/ed/2025/.

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