Fear of Missing Out Scale

Abstract

The Fear of Missing Out Scale (FoMOs), developed by Andrew K. Przybylski, Kou Murayama, Cody R. DeHaan, and Valerie Gladwell in 2013, represents the foundational psychometric instrument designed to operationalize and empirically measure the construct of “fear of missing out” (FoMO). Conceptualized as a pervasive apprehension that others might be having rewarding experiences from which one is absent, FoMO is characterized by the desire to stay continuously connected with what others are doing. Grounded in Self-Determination Theory (SDT), the scale evaluates deficits in psychological need satisfaction—specifically autonomy, competence, and relatedness—and quantifies how these deficits manifest as anxiety-driven social monitoring, compulsive social media engagement, and behavioral dysregulation.

The FoMOs is a unidimensional, 10-item self-report questionnaire evaluated on a 5-point Likert-type response scale ranging from 1 (“Not at all true of me”) to 5 (“Extremely true of me”). Across diverse international samples and developmental cohorts, the instrument demonstrates robust psychometric properties, consistently exhibiting high internal consistency (Cronbach’s $\alpha = .87$ to $.90$) and stable test-retest reliability. Confirmatory factor analyses across numerous demographic contexts replicate its unidimensional latent factor structure, demonstrating strong factor loadings ($lambda = .55$ to $.82$) and favorable model fit indices (CFI > .95, RMSEA < .06). The scale shows robust convergent validity with indices of problematic smartphone usage, social media addiction, negative affectivity, depression, and general anxiety, alongside divergent validity against unrelated personality traits. As the gold-standard instrument in digital well-being research, the FoMOs provides critical insights into the affective and behavioral mechanisms driving hyperconnectivity, cyber-distraction, sleep disruption, and compromised psychological health in contemporary digital environments.

Keywords

Fear of Missing Out, FoMOs, Self-Determination Theory, social media addiction, problematic smartphone use, digital well-being, psychological need satisfaction, social comparison, psychometrics, scale validation

Authors

The Fear of Missing Out Scale was conceptualized, operationalized, and psychometrically validated by a collaborative team of researchers in psychology, human behavior, and sports and exercise science:

• Andrew K. Przybylski, Ph.D.: Professor of Human Behaviour and Technology at the Oxford Internet Institute, University of Oxford, United Kingdom. Dr. Przybylski’s research program focuses on applying motivational models to investigate how digital environments, virtual reality, video games, and social media platforms impact human psychological adjustment, well-being, and social interaction.
• Kou Murayama, Ph.D.: Professor of Educational Psychology at the University of Tübingen, Germany, and formerly of the University of Reading, United Kingdom. Dr. Murayama specializes in human motivation, the neurocognitive mechanisms underlying intrinsic rewards, curiosity, and advanced quantitative psychometric modeling.
• Cody R. DeHaan, Ph.D.: Research psychologist formerly affiliated with the Department of Clinical and Social Sciences in Psychology at the University of Rochester, New York, USA. Dr. DeHaan’s scholarship focuses on self-determination theory, close interpersonal relationships, and psychological need fulfillment.
• Valerie Gladwell, Ph.D.: Associate Professor and exercise physiologist at the School of Sport, Rehabilitation and Exercise Sciences, University of Essex, United Kingdom. Dr. Gladwell’s research examines the physiological and autonomic manifestations of psychological stress, workplace well-being, and lifestyle physical activity.

Purpose

Prior to the seminal work by Przybylski et al. (2013), the phrase “Fear of Missing Out” was largely a colloquial cultural meme popularized in marketing spheres, mass media, and early internet culture. The explicit purpose behind the engineering of the FoMOs was to bridge the gap between popular discourse and rigorous psychological science by providing an empirically grounded, validated, and psychometrically sound measurement tool. The authors sought to systematically conceptualize FoMO not as an isolated technological byproduct, but as a self-regulatory deficit rooted in fundamental psychological vulnerabilities.

The instrument was engineered to achieve three overarching objectives:

• Establishing an Empirical Baseline: Transform a vague cultural phenomenon into a measurable latent psychological variable, allowing researchers to quantify individual differences in social apprehension, hypervigilance, and compulsive communication behaviors.
• Investigating Motivational Etiologies: Ground the experience of digital distress within established motivational paradigms—predominantly Self-Determination Theory—to examine how situational and chronic deficits in basic psychological needs (autonomy, competence, and relatedness) drive compensatory digital behaviors.
• Clarifying Behavioral and Clinical Sequelae: Provide clinicians, educators, and social scientists with a standardized tool to evaluate how high levels of FoMO predict problematic media consumption, attentional fragmentation, distracted driving, academic impairment, nocturnal sleep disturbances, and affective psychopathology.

In clinical, educational, and organizational applications, the FoMOs serves as a diagnostic screening instrument to evaluate digital compulsive behaviors. It enables researchers to identify populations vulnerable to online social fatigue, technological burnout, and cyberbullying sensitivities, while providing a clear quantitative benchmark for assessing digital detox protocols, cognitive-behavioral therapies (CBT), and mindfulness interventions aimed at decoupling technology reliance from self-worth.

Psychological Construct

The psychological construct captured by the Fear of Missing Out Scale is defined as a pervasive apprehension that others might be having rewarding experiences from which one is absent (Przybylski et al., 2013). It operates simultaneously as a cognitive preoccupation, an affective distress state, and a behavioral imperative to maintain continuous interpersonal surveillance.

Cognitive and Affective Facets

The construct encompasses several interconnected dimensions that operate within an individual’s self-regulatory framework:

• Counterfactual Social Comparison: At the cognitive level, individuals high in FoMO engage in chronic, upward counterfactual thinking. They systematically ruminate on alternate social scenarios, holding the implicit conviction that peers are experiencing greater joy, deeper intimacy, or superior social validation elsewhere. This dynamic evokes strong parallels with Leon Festinger’s social comparison theory, where internal status and belonging are ceaselessly calibrated against external cues.
• Anxiety and Social Exclusion Sensitivity: Affectively, FoMO manifests as acute distress, tension, and worry triggered by perceived ostracism or informational disconnection. The fear of being left out of conversational “in-jokes,” gatherings, or emerging social events activates threat-detection mechanisms analogous to evolutionary anxieties associated with group expulsion.
• Compulsive Behavioral Checking: Behaviorally, this cognitive-affective distress translates into continuous, habitual monitoring of communication conduits. Social networking sites (SNS) such as Instagram, TikTok, Snapchat, and messaging services act as secondary reinforcers, offering an immediate, low-cost mechanism to alleviate social ambiguity, which paradoxically perpetuates a reinforcement loop of chronic checking.

State Versus Trait Dimensions

While the FoMOs was operationalized primarily as an enduring dispositional trait reflecting individual sensitivity to social exclusion, subsequent research has demonstrated that FoMO exhibits both trait-like stability and state-like fluctuations. Trait FoMO reflects a chronic baseline of social anxiety and relational insecurity, whereas state FoMO can be acutely activated by specific contextual cues, such as algorithmic notifications, temporary geographic isolation, or periods of developmental transition (e.g., entering university).

Theoretical Framework

The foundational theoretical architecture underlying the FoMOs is Self-Determination Theory (SDT; Deci & Ryan, 1985, 2000). SDT posits that optimal human functioning, psychological vitality, and subjective well-being are contingent upon the continuous fulfillment of three basic psychological needs:

• Autonomy: The universal need to experience oneself as the author, initiator, and regulator of one’s own life choices, actions, and values.
• Competence: The innate drive to feel effective in interacting with one’s environment, exercising one’s capacities, and mastering challenging tasks.
• Relatedness: The fundamental need to experience meaningful social connection, mutual care, acceptance, and a secure sense of belonging within a social collective.

According to the motivational cascade modeled by Przybylski and colleagues, when an individual’s social environment fails to satisfy these basic needs, self-regulatory resources deplete, leading to compensatory psychological maneuvers. Low baseline satisfaction of autonomy, competence, and relatedness yields heightened subjective vulnerability. Individuals experiencing such deficits frequently perceive their offline existence as impoverished or disconnected. Consequently, digital communication technologies and social networks present an ostensibly effortless, omnipresent arena to seek simulated or compensatory need satisfaction.

However, because online interactions frequently trigger upward social comparisons and surface curated depictions of others’ idyllic experiences, this compensatory pursuit backfires. Rather than resolving relational hunger, continuous immersion in digital feeds exacerbates the perception that one’s peers are enjoying superior social rewards. The FoMO construct thereby functions as a self-regulatory vulnerability: low psychological need satisfaction leads to heightened FoMO, which catalyzes compulsive social media consumption, further undermining authentic well-being in a recurring, maladaptive self-regulatory loop.

Validity

The Fear of Missing Out Scale has undergone exhaustive empirical scrutiny to evaluate its psychometric integrity across multiple dimensions of validity:

Construct and Structural Validity

In the original validation studies encompassing diverse demographic cross-sections ($N > 3,000$), the 10-item unidimensional structure demonstrated exceptional construct validity. Invariance testing confirmed that the single-factor model operated consistently across genders and broad age brackets, establishing that the latent variable captures an identical psychological construct regardless of demographic segmentation (Przybylski et al., 2013).

Convergent Validity

The FoMOs demonstrates strong and theoretically coherent convergent correlations with a broad spectrum of psychopathological and behavioral indices:

• Negative Affectivity and Mood: Consistently correlates positively with general negative affect ($r \approx .35$ to $.45$), perceived stress ($r \approx .30$ to $.40$), and somatic symptoms of anxiety and depressive mood (Elhai et al., 2016).
• Problematic Technology Usage: Robustly predicts indices of smartphone addiction ($r = .42$ to $.56$), compulsive social networking site checking frequency ($r = .38$ to $.52$), and problematic internet use across international cohorts (Elhai et al., 2018; Baker et al., 2016).
• Deficits in Basic Psychological Needs: Exhibits significant inverse associations with baseline autonomy ($r = -.31$), competence ($r = -.28$), and relatedness satisfaction ($r = -.36$), confirming its theoretical grounding within SDT.

Discriminant Validity

Discriminant validity has been substantiated by comparing FoMO scores against established personality dimensions from the Big Five Inventory. FoMO is empirically distinct from general extraversion ($r \approx .05$ to $.12$, non-significant to weak) and open-mindedness ($r < .08$). Although moderately correlated with neuroticism ($r = .30$ to $.40$), latent variable modeling demonstrates that FoMO accounts for unique variance in technological engagement and daily distractions above and beyond trait neuroticism or generalized social anxiety disorder.

Criterion and Predictive Validity

The scale possesses remarkable predictive validity in naturalistic and experimental settings. High scores on the FoMOs prospectively predict:

• Distracted smartphone use while operating motor vehicles ($eta = .18, p < .001$).
• Compulsive device checking during university lectures and academic study sessions ($eta = .24, p < .001$).
• Checking social media immediately upon waking up in the morning and directly prior to sleep, leading to reduced objective sleep duration and diminished sleep architecture quality.

Reliability

The psychometric reliability of the FoMOs has been rigorously documented across numerous large-scale replications, cross-cultural adaptations, and longitudinal research designs:

Internal Consistency

In the original psychometric evaluation by Przybylski et al. (2013), internal consistency reliability coefficients (Cronbach’s $\alpha$) ranged from $.87$ to $.90$ across nationally representative samples in the United Kingdom and the United States. Subsequent independent validations have consistently corroborated these parameters:

• Spanish validation: $\alpha = .85$ (Gil et al., 2015).
• Turkish adaptation: $\alpha = .81$ to $.86$ (Gökler et al., 2016).
• Chinese adaptation: $\alpha = .87$, with McDonald’s $\omega = .88$ (Li et al., 2020).
• German translation: $\alpha = .84$ to $.88$.

Mean inter-item correlations reliably hover between $.35$ and $.55$, satisfying the optimal psychometric criteria for homogeneous item pools without introducing semantic redundancy or narrow item bloat.

Test-Retest Stability

Evaluation of temporal stability across intervals ranging from two weeks to three months reveals robust test-retest coefficients. Intra-class correlation coefficients (ICC) and Pearson’s $r$ over a 4-week window routinely exceed $r = .78$ ($p < .001$), confirming that dispositional FoMO represents a stable cognitive-affective trait over time, while remaining appropriately responsive to intensive behavioral or therapeutic interventions.

Factor Analysis

The latent dimensionality of the FoMOs was established through sequential exploratory and confirmatory analytic frameworks:

Exploratory Factor Analysis (EFA)

During initial instrument engineering, Przybylski et al. drafted a candidate pool of over 30 candidate items reflecting various social worries, technological dependencies, and interpersonal apprehensions. Principal axis factoring with oblique rotations (Promax) consistently isolated a dominant primary eigenvalue accounting for over $48%$ of the total variance, with subsequent eigenvalues dropping drastically below Kaiser’s criterion ($lambda < 1.0$), demonstrating a steep scree plot inflection point. Iterative item pruning retained 10 items exhibiting primary factor loadings exceeding $.50$, with negligible cross-loadings, establishing a coherent unidimensional latent construct.

Confirmatory Factor Analysis (CFA)

Subsequent confirmatory factor analyses on independent national and international datasets have repeatedly substantiated the single-factor latent structure. Model fit evaluations consistently satisfy standard structural equation modeling (SEM) thresholds:

• Comparative Fit Index (CFI): Ranges between $.94$ and $.98$.
• Tucker-Lewis Index (TLI): Ranges between $.93$ and $.97$.
• Root Mean Square Error of Approximation (RMSEA): Estimates range from $.042$ to $.062$ ($90%$ CI $[.035, .068]$).
• Standardized Root Mean Square Residual (SRMR): Typically < $.045$.

Standardized factor loadings ($lambda$) for all 10 items in the calibrated CFA models range from $.55$ to $.82$. Items probing direct social exclusion concerns (e.g., “I get worried when I find out my friends are having fun without…” and “I get anxious when I don’t know what my friends are up…”) routinely display the highest standardized loadings ($lambda > .75$), confirming their status as central indicators of the core latent trait.

Instrument / Measurement Tool

The Fear of Missing Out Scale (FoMOs) is structured as follows:

• Test Type: Self-report psychological screening instrument / psychometric inventory.
• Administration Format: Paper-and-pencil, computerized survey, or mobile testing platform.
• Item Count: 10 declarative statements.
• Response Scale: 5-point Likert-type rating format:
  • 1 = Not at all true of me
  • 2 = Slightly true of me
  • 3 = Moderately true of me
  • 4 = Very true of me
  • 5 = Extremely true of me
• Scoring Protocol:
  • All 10 items are positively valenced; there are no reverse-coded items.
  • An individual’s composite FoMO score is computed by summing the ratings across all 10 items and dividing by 10, producing an overall average score ranging continuously from 1.0 to 5.0.
  • Alternatively, researchers may utilize the total raw sum score (ranging from 10 to 50).
• Score Interpretation:
  • 1.0 – 2.0 (Low FoMO): Minimal social anxiety regarding peer activities; high autonomy and strong self-regulation over media connectivity.
  • 2.1 – 3.4 (Moderate FoMO): Normative levels of social concern; occasional compulsive checking of digital media without severe day-to-day functional impairment.
  • 3.5 – 5.0 (High FoMO): Severe interpersonal anxiety, chronic hypervigilance toward peer activities, elevated vulnerability to problematic social media usage, attentional disruption, and psychological distress.
• Administration Guidelines: Respondents should be instructed to answer candidly according to their typical everyday experiences, rather than idealized behaviors. Item randomization is recommended where technically feasible to mitigate order and framing effects.

Permissions & Fee and Test Year

The Fear of Missing Out Scale was originally published in 2013 by Andrew K. Przybylski and colleagues in the journal Computers in Human Behavior. Under the terms set forth by the primary authors, the FoMOs is made freely accessible for personal, non-commercial, and academic research purposes without fee or licensing constraints, provided that the foundational validation study is formally and accurately cited.

For commercial deployment, organizational diagnostic integration, or inclusion within proprietary for-profit applications and technologies, explicit formal permission and commercial licensing agreements must be secured directly from the copyright holders and corresponding authors.

References

Below is a curated selection of key peer-reviewed literature detailing the development, psychometric evaluation, and empirical application of the Fear of Missing Out Scale:

• Baker, Z. G., Krieger, H., & LeRoy, A. S. (2016). Fear of missing out: Relationships with depression, mindfulness, and physical symptoms. Translational Issues in Psychological Science, 2(3), 275–282. https://doi.org/10.1037/tps0000075
• Buglass, S. L., Binder, J. F., Betts, L. R., & Underwood, J. D. (2017). Motivators of online vulnerability: The impact of social network site use and fear of missing out on online harassment and problematic internet use. Computers in Human Behavior, 66, 248–255. https://doi.org/10.1016/j.chb.2016.09.055
• Deci, E. L., & Ryan, R. M. (2000). The “what” and “why” of goal pursuits: Human needs and the self-determination of behavior. Psychological Inquiry, 11(4), 227–268. https://doi.org/10.1207/S15327965PLI1104_01
• Elhai, J. D., Levine, J. C., Dvorak, R. D., & Hall, B. J. (2016). Fear of missing out, need for touch, anxiety and depression are related to problematic smartphone use. Computers in Human Behavior, 63, 509–516. https://doi.org/10.1016/j.chb.2016.07.058
• Elhai, J. D., Yang, H., & Montag, C. (2018). Fear of missing out (FOMO): Overview, theoretical underpinnings, and literature review on relations with severity of negative affectivity and problematic technology use. Revista Brasileira de Psiquiatria, 43(2), 203–209. https://doi.org/10.1590/1516-4446-2020-0870
• Festinger, L. (1954). A theory of social comparison processes. Human Relations, 7(2), 117–140. https://doi.org/10.1177/001872675400700202
• Gil, F., Del Valle, G., Oberst, U., & Chamarro, A. (2015). Nuevas tecnologías ¿Nuevas patologías? El smartphone y el “fear of missing out”. Aloma: Revista de Psicologia, Ciències de l’Educació i de l’Esport, 33(2), 77–83.
• Li, L., Niu, Z., Mei, S., & Griffiths, M. D. (2020). A psychometric evaluation of the Chinese version of the Fear of Missing Out Scale (FoMOs). Current Psychology, 40(6), 2888–2897. https://doi.org/10.1007/s12144-019-00564-1
• Przybylski, A. K., Murayama, K., DeHaan, C. R., & Gladwell, V. (2013). Motivational, emotional, and behavioral correlates of fear of missing out. Computers in Human Behavior, 29(4), 1841–1848. https://doi.org/10.1016/j.chb.2013.02.014

13. Items of the Scale (Questionnaire)