Digital Well-Being: What It Is, What Shapes It, and What Research Shows

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Author: Ukrainian Psychological Hub · Published: September 27, 2026 · Editorial Policy

Digital well-being describes the quality of a person's relationship with digital technology as it is lived in everyday life: whether digital tools support valued goals, relationships, autonomy, learning, work, recreation, and health without producing a pattern of avoidable interference, loss of control, distress, or functional impairment. It is therefore broader than screen time and more precise than the idea that less technology is automatically better.

The field is still developing. A 2026 scoping review found that digital well-being is defined in several overlapping ways and is best treated as a multidimensional construct spanning psychological and sociotechnological domains. The review identified 26 eligible studies, three broad conceptual perspectives, limited measurement tools, and mixed results for interventions centered on digital disconnection. Septania et al., 2026

That complexity matters because the same number of hours online can contain very different experiences. Two people may each spend four hours with screens: one may be working, talking with family, creating music, navigating health care, and reading; the other may be repeatedly interrupted, scrolling material that leaves them distressed, postponing sleep, and feeling unable to stop. Duration is one exposure variable. Content, purpose, context, timing, control, social meaning, developmental stage, and individual vulnerability are others. OECD, 2024

Digital Well-Being: The Short Answer

Digital well-being is the degree to which a person's digital life supports rather than obstructs their broader well-being. It concerns the fit between technology use and the person's goals, needs, relationships, responsibilities, values, and capacities. A digitally healthy day is not defined by a universal number of minutes. It is defined more usefully by what the technology enables, what it costs, how much control the person has, and whether the overall pattern is sustainable.

One influential account defines digital well-being as a dynamic experience of balance between the benefits and drawbacks of mobile connectivity. In this view, the relevant balance changes across people, devices, activities, and situations rather than existing as a fixed ideal for everyone. Vanden Abeele, 2021

A complementary theoretical framework treats digital well-being as subjective well-being in an environment where digital media are pervasive. Digital practices occur inside social and technological structures, and the same practice can bring benefits and harms at the same time. Büchi, 2024

What Digital Well-Being Includes

Digital well-being is easiest to understand as a relationship among the person, the technology, the activity, and the context. It can include emotional experience, perceived control, social connection, productivity and goal pursuit, physical routines such as sleep and movement, safety and privacy, access and inclusion, and the degree to which digital activity fits into a meaningful life.

Purpose and value

A useful starting question is what a digital activity is for. Work, education, navigation, creative production, communication, entertainment, social support, health management, and civic participation can all be valuable. The psychological meaning of use depends partly on whether it advances a chosen purpose or mainly consumes time and attention without serving one.

Agency and control

Agency refers to the ability to choose when, why, and how technology is used, to stop when intended, and to modify the environment when it conflicts with one's goals. Losing track of time once is ordinary behavior. A persistent pattern of failed attempts to stop, escalating conflict with responsibilities, marked distress, or functional impairment is a different level of concern. The distinction matters because high-frequency use and problematic or dysregulated use are not synonyms.

Emotional experience

Digital activity can be enjoyable, calming, inspiring, frustrating, socially rewarding, threatening, exhausting, or emotionally neutral. Digital well-being includes these experiences without treating every unpleasant feeling as pathology. A stressful work message, disappointment after comparison, or irritation with an app may be meaningful without constituting a clinical disorder.

Social connection and relationship quality

Digital tools can sustain closeness across distance, create communities, and make support more accessible. They can also intrude on face-to-face interaction when attention is repeatedly redirected away from another person. Research on phubbing and technoference in relationships illustrates this contextual principle: the relevant question is not whether a phone was present, but how device use interacted with attention, expectations, responsiveness, and relationship processes.

Attention, cognition, and task fit

Digital well-being also concerns whether an environment supports the kind of attention a task requires. Sustained attention, selective attention, executive control, working memory, task switching, and subjective difficulty concentrating are related but distinct processes. A stream of interruptions may impair performance on a demanding task even when the same device is useful for another activity. A person's digital well-being therefore cannot be inferred from a conversational claim that their 'attention span' is simply longer or shorter.

Physical routines and embodied life

Screens can coexist with healthy sleep, movement, meals, and rest, or they can displace them. Timing and context often matter more than a daily total. Using a device late at night may be relevant because of time displacement, arousal, content, or light exposure; prolonged sedentary use may matter because it replaces movement. These mechanisms are separate from the broader question of total screen duration.

Safety, access, and the digital environment

Well-being is influenced by more than personal discipline. Privacy, harassment, accessibility, platform design, workplace expectations, unequal access, information quality, social norms, and economic conditions shape what people can realistically do online. Digital well-being is therefore partly individual and partly environmental.

Digital Well-Being Is Not the Same as Screen Time

Screen time is a duration measure. Digital well-being is an outcome-oriented and context-sensitive construct. The two can be related, but they are not interchangeable.

The OECD's 2025 cross-country analysis of 14,611 people found associations between longer personal screen time and poorer subjective well-being, while also showing that sleep deprivation, financial hardship, low physical activity, loneliness, and other contextual variables were important and in several analyses stronger predictors. The OECD explicitly notes that its models do not establish causality. OECD, 2025

This is why a single daily total cannot tell you whether use was socially nourishing, cognitively demanding, compulsive, productive, restorative, sleep-displacing, conflict-producing, or simply required by a job. A number can be useful for self-observation, yet it becomes misleading when treated as a diagnosis or universal threshold.

There is no universal medical cutoff that defines an acceptable amount of screen time for all adults. Age, occupation, disability, caregiving, education, social circumstances, activity type, and the consequences of use all change the meaning of the same duration.

What Current Research Shows

1. Digital well-being is multidimensional and still lacks a single agreed definition

The 2026 scoping review by Septania and colleagues found three recurring perspectives: digital well-being as well-being influenced by technology use, as the perceived impact of digital engagement, and as a strategy for balanced use. It also synthesized behavioral, eudaimonic, and sociocultural dimensions. Septania et al., 2026

A 2023 scoping review of 87 papers in human-computer interaction reached a similar conclusion: definitions and measures varied considerably, and the literature often borrowed general well-being measures or proxies rather than using a single digital-well-being instrument. Al-Mansoori et al., 2023

The definitional problem remains active in 2026. Montag and Elhai argue that researchers sometimes use the same label for different constructs or different labels for overlapping ones, making results difficult to cumulate. They also caution that measures adapted from addiction frameworks can overpathologize ordinary behavior when applied without sufficient attention to impairment and psychopathology. Montag & Elhai, 2026

2. Benefits and costs often coexist

Digital media can provide information, convenience, social contact, entertainment, learning opportunities, creative tools, health services, and accessibility while also creating distraction, privacy risks, social stress, or opportunity costs. A broad OECD review emphasizes this mixed pattern across multiple dimensions of well-being. Lee & Žarnic, 2024

The important implication is that digital well-being cannot be reduced to maximizing benefits or eliminating all costs. Many useful technologies impose some burden, and many enjoyable technologies create trade-offs. The practical question is whether the balance is acceptable for a particular person in a particular context.

3. Frequency alone often explains less than popular debate suggests

A newly published five-wave panel study of 1,966 U.S. adults examined self-reported use frequency across ten social technologies every three months. At that level of measurement, the authors found little credible evidence that use of any specific social technology predicted subsequent life satisfaction. Between-person associations differed by technology, but cross-lagged effects were sparse. Kushlev et al., 2026

This does not show that digital experiences never affect well-being. It shows why broad exposure measures can miss the relevant mechanism. What a person did, with whom, under what conditions, for what purpose, and what the activity replaced can matter as much as how often an app was opened.

4. Opportunity costs offer one useful mechanism

Kushlev's 2026 opportunity-cost framework describes three routes through which social technologies may affect well-being: displacement, when digital activity reallocates time away from something else; substitution, when technology replaces another way of meeting a need; and interference, when technology redirects attention during an ongoing activity. The framework emphasizes that the consequence depends on what is displaced, substituted, or interrupted. Kushlev, 2026

Ten minutes of messaging that replaces loneliness may have a different consequence from ten minutes of messaging that interrupts a difficult conversation. An hour of video that replaces passive boredom differs from an hour that replaces needed sleep. The mechanism depends on the counterfactual: what would otherwise have happened?

5. Context changes effects

Research in specific settings reinforces the contextual view. A 2026 scoping review focused on learners in higher education found that digital well-being is shaped by individual capabilities, patterns of use, and the educational digital environment rather than by one exposure measure alone. Mohd Bahar et al., 2026

Developmental stage matters too. Evidence drawn from children or adolescents should not be silently generalized to adults, and adult workplace evidence should not be treated as if it describes school settings. Platform, content, culture, and socioeconomic conditions can also change what digital participation means.

6. The design of digital environments matters, but users still have agency

Human-computer interaction research increasingly treats digital well-being as a design problem as well as a personal-behavior problem. The 2023 design scoping review concluded that responsibility is often placed too heavily on users and called for greater attention to designers and societal institutions. Al-Mansoori et al., 2023

This does not make people passive victims of interfaces. Digital behavior emerges from an interaction among design features, habits, goals, reinforcement histories, social expectations, individual differences, and situational constraints. Notifications, autoplay, feeds, friction, defaults, and stopping cues can shape behavior, while people can also modify settings, choose tools, establish routines, and leave environments that conflict with their goals.

7. Complete disconnection is not a universal solution

The 2026 digital-well-being scoping review reported mixed findings for disconnection-oriented interventions. Septania et al., 2026 A 2025 systematic review and meta-analysis of social-media abstinence found no significant overall effects on positive affect, negative affect, or life satisfaction across the included studies. Lemahieu et al., 2025

A 2026 scoping review of social-media detox interventions likewise describes an evidence base marked by methodological heterogeneity and effects that are often small, inconsistent, or null. Calvert et al., 2026

A break can still be personally useful. It can reveal habits, remove a specific trigger, create time for another activity, or test whether an environment is contributing to distress. The evidence does not support presenting a digital detox as a universal treatment that automatically improves mood, anxiety, sleep, attention, or life satisfaction.

How Digital Well-Being Is Measured

There is currently no single gold-standard test that can reduce digital well-being to one universally interpretable score. Researchers use several families of measures, and each answers a different question.

Subjective well-being measures

Studies may assess life satisfaction, positive and negative affect, eudaimonic well-being, or general mental well-being. These measures are valuable because well-being is partly subjective, yet they are not specific to technology. A person's life satisfaction can change for many reasons unrelated to digital use.

Digital-well-being questionnaires

Dedicated questionnaires attempt to capture dimensions such as perceived balance, agency, emotional experience, social connection, safety, or digital functioning. The field is still consolidating these measures. The 2026 scoping review identified only a small set of digital-well-being scales and concluded that none yet provided a fully integrated, broadly validated framework. Septania et al., 2026

Behavioral measures

Device logs can record time, pickups, sessions, notifications, app categories, or time of day. These data can be more accurate than memory for some behaviors, but they still require interpretation. A log can show that an app was open; it cannot by itself tell whether the activity was meaningful, distressing, socially supportive, required by work, or experienced as out of control.

Functional outcomes

Sleep timing, task performance, conflict, missed obligations, academic or occupational functioning, and relationship quality may be more informative than raw duration when the question is whether digital behavior is interfering with life. Even here, causality requires appropriate longitudinal or experimental designs rather than simple co-occurrence.

Clinical measures

Depression, anxiety disorders, ADHD, OCD, insomnia, and other clinical conditions require disorder-specific assessment. A high screen-time total, frequent checking, concentration difficulty, or a screening score cannot establish one of these diagnoses. Digital-behavior measures and clinical diagnoses answer different questions.

What Shapes Digital Well-Being?

The activity itself

Video calling, collaborative work, gaming, reading, social comparison, doomscrolling, online shopping, messaging, and passive feed consumption are not interchangeable exposures. Studies that collapse them into a single 'screen time' variable may obscure meaningful differences.

Content

Content can be educational, violent, supportive, appearance-focused, politically arousing, humorous, threatening, or personally relevant. A platform name is often too broad to capture these differences because the same platform can deliver radically different experiences.

Timing and situation

Use during a commute, a work meeting, a family meal, an anxious night, a study session, or a period of social isolation occurs under different psychological conditions. Timing affects what the activity displaces and how costly interruption becomes.

Individual vulnerability and goals

Mood, stress, loneliness, impulsivity, self-control, social support, developmental stage, physical health, and current goals can modify how digital experiences are interpreted and managed. Vulnerability should not be confused with inevitability: it changes probabilities and contexts, not destiny.

Social norms and expectations

Always-on workplace cultures, group chats, family norms, school requirements, and peer expectations can create pressure to remain reachable. A behavior that looks individually chosen may partly reflect social or institutional demands.

Interface and platform architecture

Alerts, defaults, recommendation systems, feed structure, autoplay, infinite scroll, visible social metrics, and friction can alter what becomes salient and how easy it is to continue or stop. Empirical claims about effects should be kept separate from speculation about the intentions of any specific company or designer.

Access, resources, and inequality

For some people, digital access is a route to education, employment, disability support, health information, community, or services that would otherwise be unavailable. Advice that assumes everyone can simply disconnect can ignore these realities.

Digital Well-Being and Mental Health

Digital well-being overlaps with mental health, yet it is not a psychiatric diagnosis. A person can have good mental health while disliking parts of their digital routine, and a person with depression or anxiety can still have a purposeful, supportive digital life.

Research may find associations between particular digital behaviors and depression, anxiety, loneliness, sleep problems, or distress. An association does not establish that technology caused the condition. Reverse causation is plausible in many settings: people who already feel lonely, depressed, anxious, or stressed may change how they use technology. Shared causes can also produce both the digital behavior and the mental-health outcome.

Causal language should therefore follow the design. Randomized experiments can test short-term consequences of specific interventions; longitudinal studies can examine temporal ordering; natural experiments can exploit policy or environmental changes. Cross-sectional surveys are useful for identifying patterns but are limited for determining direction.

Digital Well-Being in the Age of AI

Artificial intelligence adds new forms of assistance, recommendation, generation, and interaction to digital life. When the primary question is how AI specifically changes focus, verification demands, cognitive load, or algorithmic competition, the dedicated English Hub article Attention in the Age of AI: Focus, Cognitive Load, and Algorithmic Competition owns that narrower intent.

For digital well-being more broadly, the same principle still applies: evaluate the activity, the benefit, the cost, the context, the degree of control, and what the technology displaces or enables. A new tool does not become beneficial or harmful merely because it is new.

How to Evaluate Your Own Digital Well-Being

A useful self-assessment starts with function rather than guilt. Instead of asking only, “How many hours was I on my phone?”, ask what the digital activity was doing in your life and what happened around it.

Ask what the technology helped you do

Identify benefits first: connection, work, learning, creativity, relaxation, organization, accessibility, safety, or practical convenience. This prevents an audit from treating all use as a problem by default.

Ask what it displaced

Look for trade-offs that matter to you: sleep, movement, focused work, in-person interaction, boredom that might otherwise lead to reflection, or another valued activity. The goal is not to eliminate every trade-off but to notice the expensive ones.

Ask whether you can stop or switch deliberately

Notice whether stopping is usually possible when you decide to stop. Occasional overuse is common. Repeated failed attempts to cut back, marked distress, conflict, or impairment deserves more attention than a high count of minutes alone.

Ask how you feel during and after use

Immediate pleasure and later satisfaction are not always the same. A feed can be entertaining while leaving you tense; a difficult online course can be effortful while producing a sense of mastery. Track both short-term affect and longer-term value.

Ask whether the environment matches the task

If you need sustained concentration, reduce avoidable interruptions. If you need social connection, choose channels and activities that actually provide it. Digital well-being improves when the environment is fitted to the goal rather than when every goal is forced through the same interface.

Evidence-Informed Ways to Improve Digital Well-Being

Change the specific problem, not technology as a whole

If bedtime is the problem, change the bedtime pattern. If interruptions are the problem, change notifications or device placement. If social comparison is the problem, change feeds, accounts, or modes of use. If work availability is the problem, address availability expectations. Specific interventions are easier to evaluate than a vague promise to 'use technology less.'

Use friction deliberately

Small barriers can help when a behavior happens automatically: remove nonessential alerts, move a distracting app away from the home screen, log out, use focus modes, or keep the phone out of immediate reach during a chosen task. Friction should serve a defined goal rather than become punishment.

Restore stopping cues

Activities with clear endings are easier to disengage from than continuous feeds. Deliberately defined sessions, episode limits, task lists, or time boundaries can provide a stopping point. A timer is useful when it supports a plan; it is not a medical treatment or proof of addiction.

Protect high-value offline activities

The opportunity-cost approach suggests protecting activities that are easy for digital use to displace: sleep, exercise, face-to-face conversation, deep work, and restorative downtime when those activities matter to the person. The relevant trade-off depends on context. Kushlev, 2026

Experiment instead of moralizing

Try a defined change for a defined reason, then observe the outcome. For example: silence nonessential notifications for a week and track interruptions; move social media out of the bedtime window and note sleep timing; replace passive scrolling during a commute with a chosen activity and compare mood. Personal experiments do not establish universal scientific causality, but they can improve self-knowledge.

Keep useful technology

Improvement can involve adding rather than subtracting technology: using accessibility tools, calendar systems, blockers for a specific distraction, group chats that provide support, telehealth, exercise prompts, or communication tools that make relationships easier to maintain.

Use disconnection strategically

Temporary abstinence can be a useful personal experiment, but evidence does not support treating it as a universal cure. Meta-analytic and scoping-review findings remain mixed and heterogeneous. Lemahieu et al., 2025 Calvert et al., 2026

When Digital Use May Need More Than a Habit Change

Digital behavior deserves closer attention when it is repeatedly associated with meaningful functional impairment or distress: missed obligations, severe sleep disruption, persistent conflict, unsafe behavior, major financial consequences, inability to disengage despite repeated attempts, or worsening symptoms of a mental-health condition.

Those signs still do not establish a diagnosis by themselves. Terms such as problematic smartphone use and problematic social media use are research constructs; popular labels such as “phone addiction” or “social media addiction” should not be treated as automatic official DSM or ICD diagnoses. Clinical assessment focuses on the full pattern of symptoms, impairment, duration, context, differential explanations, and applicable diagnostic criteria.

If digital behavior is entangled with depression, anxiety, trauma, mania, psychosis, OCD symptoms, an eating disorder, severe insomnia, self-harm, or another clinical concern, addressing only screen time may miss the underlying problem. Professional evaluation can help distinguish a digital habit from a symptom, coping strategy, trigger, maintaining factor, or separate condition.

Common Myths About Digital Well-Being

“Less screen time is always healthier.”

No. Reducing unnecessary or harmful use can help in some contexts, but digital technology also supports work, education, relationships, recreation, accessibility, and health. The value of a reduction depends on what is reduced and what replaces it.

“A high daily total means addiction.”

No. Duration alone cannot establish addiction, problematic use, or a clinical disorder. Functional impairment, distress, loss of control, context, and the specific behavior matter.

“Dopamine explains why everyone gets hooked.”

Dopamine participates in learning, motivation, and reward-related processes throughout ordinary behavior. “Dopamine addiction” is not a sufficient scientific explanation for complex patterns of digital use, and “dopamine detox” is not an established medical treatment for digital behavior.

“Technology has permanently destroyed attention spans.”

This claim compresses multiple cognitive processes into one dramatic metaphor. Digital interruption, multitasking, and task switching can affect performance in specific conditions, but that is different from proving a permanent, general neurological loss of an individual’s “attention span.”

“A digital detox works for everyone.”

Evidence is mixed. Some people benefit from a temporary break, some outcomes show little change, and effects depend on the intervention, population, duration, platform, outcome, and what people do with the freed time.

Frequently Asked Questions

What is digital well-being?

Digital well-being is the quality of a person's relationship with digital technology and the extent to which digital activity supports broader well-being, goals, relationships, autonomy, and functioning. It is multidimensional and context dependent.

Is digital well-being the same as digital wellness?

The terms are often used loosely and sometimes overlap. In research, “digital well-being” is increasingly used for the broader construct involving subjective well-being, digital practices, agency, benefits, harms, and sociotechnical context. Because definitions remain inconsistent across fields, the meaning used in a specific study should be checked rather than assumed.

Is digital well-being just screen time?

No. Screen time measures duration. Digital well-being includes purpose, content, context, timing, control, social experience, opportunity costs, functioning, and individual differences.

How much screen time is healthy for adults?

There is no single universal medical cutoff for all adults. Research can identify associations at population levels, but those findings do not create a diagnostic threshold that applies regardless of activity, occupation, context, or individual needs.

Can digital technology improve well-being?

Yes. Digital technologies can support communication, access, productivity, learning, services, entertainment, and social connection. They can also introduce costs. Broad reviews emphasize that effects are mixed and depend on the technology, use, person, and context. Lee & Žarnic, 2024

Does social media cause depression or anxiety?

The broad evidence does not justify a universal causal statement. Associations vary by population, platform, activity, content, measurement, and research design. Some mechanisms and subgroups may show greater risk, while reverse causation and confounding remain important. Specific causal claims require longitudinal, experimental, or other causal evidence.

Do I need a digital detox?

A detox is one possible strategy, not a universal requirement. A targeted change may be more useful: altering bedtime use, notifications, a particular feed, work availability, or another specific source of interference.

How can I tell whether my phone use is a problem?

Look beyond hours. Ask whether you repeatedly lose control, continue despite clear negative consequences, experience significant distress, or see impairment in sleep, relationships, work, study, safety, or other important areas. A high total alone is not enough.

Can digital well-being be measured accurately?

It can be studied, but measurement is still evolving. Researchers combine self-report scales, general well-being measures, behavioral logs, functional outcomes, and context-specific indicators. No single measure captures every dimension.

Is digital well-being a clinical diagnosis?

No. Digital well-being is a research and practical framework for understanding how digital life relates to well-being. It is not itself a DSM or ICD diagnosis.

Conclusion: Digital Well-Being Is About Fit, Function, and Agency

Digital well-being is best understood as a multidimensional relationship between people and their digital environments. It asks whether technology supports a person's life, whether its costs are acceptable, whether use remains sufficiently intentional and controllable, and whether important needs and activities are being enabled or displaced.

Current research does not support a one-number model in which fewer minutes automatically equal better well-being. The stronger framework distinguishes duration from content, context, purpose, timing, design, individual vulnerability, social environment, and functional consequences. It also distinguishes ordinary behavior from problematic use, research constructs from diagnoses, and association from causation.

The practical goal is not digital purity. It is a workable digital life: technology that serves valued purposes, environments that reduce avoidable interference, habits that preserve agency, and enough flexibility to change the pattern when the costs begin to outweigh the benefits.

References

Al-Mansoori, R. S., et al. (2023). Designing for Digital Wellbeing: From Theory to Practice a Scoping Review. Human Behavior and Emerging Technologies, 2023, 9924029. https://doi.org/10.1155/2023/9924029

Büchi, M. (2024). Digital well-being theory and research. New Media & Society, 26(1), 172–189. https://doi.org/10.1177/14614448211056851

Burr, C., Taddeo, M., & Floridi, L. (2020). The Ethics of Digital Well-Being: A Thematic Review. Science and Engineering Ethics, 26, 2313–2343. https://doi.org/10.1007/s11948-020-00175-8

Calvert, E., Vaidya, S., Ilagan, G., et al. (2026). Mapping the methodological landscape of social media detox intervention through a scoping review of evidence relevant to social media restriction policies. Communications Psychology. https://doi.org/10.1038/s44271-026-00540-6

Kushlev, K. (2026). An Opportunity Cost Framework of Digital Well-Being. Social and Personality Psychology Compass, 20(5), e70144. https://doi.org/10.1111/spc3.70144

Kushlev, K., Moon, K., Motyl, M., Fast, N. J., & Schroeder, J. (2026). Social technology use and life satisfaction in a five-wave panel study of US adults. Nature Human Behaviour. https://doi.org/10.1038/s41562-026-02564-8

Lee, J., & Žarnic, Ž. (2024). The impact of digital technologies on well-being: Main insights from the literature. OECD Papers on Well-being and Inequalities, No. 29. https://doi.org/10.1787/cb173652-en

Lemahieu, L., Vander Zwalmen, Y., Mennes, M., Koster, E. H. W., Vanden Abeele, M. M. P., & Poels, K. (2025). The effects of social media abstinence on affective well-being and life satisfaction: a systematic review and meta-analysis. Scientific Reports, 15, 7581. https://doi.org/10.1038/s41598-025-90984-3

Mohd Bahar, F. H., Roslan, N. S., Pang Tze Ping, N., et al. (2026). The digital well-being among learners in higher education: a scoping review. BMC Medical Education, 26, 1146. https://doi.org/10.1186/s12909-026-09370-w

Montag, C., & Elhai, J. D. (2026). The jingle jangle fallacy in digital well-being research is hindering scientific progress. BMC Global and Public Health, 4, 89. https://doi.org/10.1186/s44263-026-00327-1

OECD. (2025). Screen time and subjective well-being: Insights from a few countries worldwide. OECD Policy Insights on Well-being, Inclusion and Equal Opportunity, No. 24. https://doi.org/10.1787/c840403c-en

Septania, S., Helmi, A. F., & Thontowi, H. B. (2026). Navigating well-being in the digital era: A scoping review of digital well-being. Wellbeing, Space and Society, 10, 100345. https://doi.org/10.1016/j.wss.2026.100345

Vanden Abeele, M. M. P. (2021). Digital Wellbeing as a Dynamic Construct. Communication Theory, 31(4), 932–955. https://doi.org/10.1093/ct/qtaa024

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