Skip to main content
Advertisement
Browse Subject Areas
?

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here.

  • Loading metrics

The relationship between fear of missing out, digital technology use, and psychological well-being: A scoping review of conceptual and empirical issues

  • Ellen Groenestein ,

    Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Validation, Visualization, Writing – original draft

    e.groenestein@vu.nl

    Affiliations Department of Communication Science, Vrije Universiteit Amsterdam, Amsterdam, Netherlands, Research Group Communication in the Networked Society, Creating010/Rotterdam University of Applied Sciences, Rotterdam, Netherlands

  • Lotte Willemsen,

    Roles Conceptualization, Data curation, Formal analysis, Supervision, Writing – review & editing

    Affiliation Research Group Communication in the Networked Society, Creating010/Rotterdam University of Applied Sciences, Rotterdam, Netherlands

  • Guido M. van Koningsbruggen,

    Roles Conceptualization, Supervision, Writing – review & editing

    Affiliation Department of Communication Science, Vrije Universiteit Amsterdam, Amsterdam, Netherlands

  • Hans Ket,

    Roles Conceptualization, Methodology, Writing – review & editing

    Affiliation Medical Library, Vrije Universiteit Amsterdam, Amsterdam, Netherlands

  • Peter Kerkhof

    Roles Conceptualization, Supervision, Writing – review & editing

    Affiliation Department of Communication Science, Vrije Universiteit Amsterdam, Amsterdam, Netherlands

Abstract

Given the rise of digital technology and its assumed impact on psychological well-being, this scoping review systematically examines the literature on Fear of Missing Out (FoMO), which is assumed to play a pivotal role in this dynamic. Although adverse effects of FoMO are commonly assumed, there is still no consensus on the nature of the phenomenon or its relations with psychological well-being and digital technology use, making a scoping review essential. To address this need, we comprehensively assess the conceptualizations of the construct of FoMO and its roles in relation to well-being and digital technology use. We conducted a literature search in PubMed, Ebsco/APA PsycINFO, and Web of Science (period 2013 to July 7, 2023), screening 4121 articles at the title and abstract level and assessing 342 full-text articles for eligibility, ultimately including 106 articles. The review revealed a fragmented FoMO literature, emphasizing the need for conceptual clarity to address critical gaps and inconsistencies in existing research. Consensus exists on FoMO’s essence—an unpleasant feeling arising from missed social experiences driven by activity comparison. However, debates include FoMO’s associated affective states and conceptual boundaries, as well as the need to disentangle FoMO as a trait or state. The review also underscored FoMO’s multifaceted roles in well-being and digital technology use, highlighting the need for causal research, theoretical guidance, and unified terminology to advance understanding in the FoMO literature.

Introduction

In the present day and age, individuals live increasingly mediated lives. The constant availability of digital technologies such as smartphones, the Internet and social media allows us to be connected to people and information wherever and whenever ‘needed’ [1]. By 2022, there were more than 4.59 billion social media users worldwide, a number that is expected to grow to 5.42 billion in 2025. In 2022, 16–64-year-olds worldwide spent on average almost 2,5 hours per day only on social media and messaging [2]. The potential for 24/7 connectivity is considered as an important force for why people feel they must always be ‘on’ and engage in technology in order to not miss out, stay current, and connect [3, 4]; a psychological phenomenon commonly known as Fear of Missing Out (FoMO).

In their seminal 2013 article, Przybylski and colleagues made a first attempt to conceptualize and operationalize the concept and provide a theoretical account for how the concept is related to psychological well-being and digital technology use [5]. By conducting a survey study, they provided initial evidence that FoMO is associated with lower general mood and general life satisfaction, and higher social media engagement. The latter was explained by the notion that social media use may provide an attractive behavioral strategy for coping with feelings of anxiety stemming from the idea of missing out on activities [5].

Since Przybylski et al. (2013), there has been a proliferation of studies on FoMO. An article search on Google Scholar shows that from 2013 to June 2023, nearly 15,200 papers and articles mention “fear of missing out”, and more than 30,600 its commonly used abbreviation “FoMO”. Despite the large number of studies that have investigated FoMO, there remains a gap in our understanding of what FoMO entails and how it theoretically and empirically relates to psychological well-being and digital technology use. As stated by Tandon, Dhir, Almugren, et al. (2021), the extant literature on FoMO offers “a fragmented view of this phenomenon, its antecedents and its consequences” [6].

Although numerous studies acknowledge the fragmented nature of the literature, there has not yet been an effort to systematically document the extent to which FoMO’s conceptualization, causes and effects vary across different research studies. The aim of this review is to address these criticisms by systematically assessing the literature that has appeared since Przybylski et al. In doing so, we will answer two research questions (RQs):

  1. RQ1: How has FoMO been conceptualized across the extensive body of literature published?
  2. RQ2: What roles are attributed to FoMO in relation to psychological well-being and digital technology use in the research conducted, and to what extent do findings support these roles across studies?

By focusing on the first research question, the current review addresses prior calls in the literature to explore unanswered questions regarding the FoMO construct (e.g., [7]). In the 10 years of research on FoMO, different ways of conceptualizing and measuring FoMO have occurred. The lack of uniformity in definitions and measurement tools may lead to variability in research outcomes and interpretations [8]. The current study will provide a comprehensive examination of the fragmented landscape of FoMO research, offering insights into diverging views regarding FoMO’s conceptualizations, as well as implications for future research.

By focusing on the second research question, the current review aims to gain more insight into the multifaceted roles that FoMO may play in the context of individuals’ psychological well-being and their use of digital technology. Although adverse effects of FoMO on psychological well-being and digital technology use are taken as a given in popular media, there is still no consensus, about what these effects entail and to what extent they are supported by empirical research and theory. Some studies hypothesize that FoMO is an antecedent of digital technology use (e.g., [912], while other studies suggested vice versa (e.g., [13, 14]). Similar reciprocal effects have been hypothesized for the relationship between FoMO and psychological well-being (resp. e.g., [15, 16]). This review aims to evaluate the extent to which the various roles of FoMO in the relationship between psychological well-being and digital technology use are supported by empirical research findings, and to elucidate the implications of these findings for future research, providing a foundation for further exploration of these complex relationships in the digital age.

Methods

This scoping review was conducted in accordance with the JBI methodology for scoping reviews [17], and in line with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping reviews (PRISMA-ScR; see also S1 Checklist. PRISMA-ScR Checklist) [18]. For transparency, this review was conducted in accordance with an a priori registering with the International Prospective Register of Systematic Reviews (Prospero; CRD42020184146).

Search strategy

A comprehensive search was performed in the databases PubMed, Ebsco/APA PsycINFO and Clarivate Analytics/Web of Science Core Collection, from inception through July 7, 2023, in collaboration with a medical information specialist (JCFK). The search included controlled terms and free text terms or synonyms of ‘fear of missing out’, indicators of digital technology use such as ‘smartphone use’, or ’internet’ and positive and negative psychological well-being indicators such as ‘life satisfaction’ or ’anxiety’. The full search strategies can be found in the S1 Text. Full Search Strategies. Duplicate articles were excluded by a medical information specialist (JCFK) using Endnote X20.0.1 (Clarivatetm), following the Amsterdam Efficient Deduplication (AED)-method [19] and the Bramer-method [20].

Inclusion and exclusion criteria.

Fig 1 outlines the process of article selection utilizing the PRISMA guidelines [21]. Studies were included in this review if they examined FoMO in relation to psychological well-being and/or digital technology use. Psychological well-being refers to feeling good and judging life positively [22], and can be seen as a multidimensional construct that encompasses both positive and negative psychological adjustment [23]. This conceptualization includes both positive indicators of psychological well-being, such as self-esteem, social well-being, and life satisfaction, as well as negative indicators, such as depression, loneliness, and anxiety [24]. Digital technology use is an umbrella term that encompasses various devices (e.g., smartphone, laptop), services (e.g., social networking sites such as Instagram and instant messengers such as WhatsApp), and types of use (e.g., active-, passive use) [25]. In our article we included studies that measure a range of concepts related to digital technology use, including Internet use, smartphone use, social media use–time and frequency but also problematic/ excessive use–among other concepts.

thumbnail
Fig 1. Flow diagram for the review.

(MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ 2021;372:n71. doi: 10.1136/bmj.n71).

https://doi.org/10.1371/journal.pone.0308643.g001

We excluded studies that did not focus on the general population (e.g., clinical samples), studies that did not generate any quantitative results (outcomes given in numbers), and studies that were not published in the English language. Also excluded were systematic reviews, literature reviews, and meta-analysis.

Search results, study selection and data extraction.

Our search resulted in 8300 citations (PubMed N = 1848, PsycINFO N = 2177, Web of Science N = 4275). We included studies up to the year 2022, which yielded 4303 articles, to ensure a thorough exploration of the existing scholarly landscape within a manageable scope. Study selection was accomplished and organized using the Rayyan OCRI software (1). Two reviewers (EG, AvH) independently screened titles and abstracts of the remaining 4303 studies for eligibility (see Fig 1 for flowchart of the search process). This procedure resulted in the identification of 342 potentially relevant articles. These articles either clearly met the inclusion criteria after inspecting the abstract, or required an additional scanning of the full text to determine whether the articles met the inclusion criteria. The full text was then obtained for all included abstracts and subsequently independently evaluated by two reviewers (EG, AvH). Discrepancies were resolved by consensus or adjudication by a third party (LW). This procedure resulted in a selection of 106 relevant articles that met the inclusion criteria.

For each included study, two researchers (EG, TP) independently extracted study characteristics into Microsoft Excel. Extracted data included measures used, hypothesized model, independent variable (IV), dependent variable (DV), mediating variable (M), effects, study and population characteristics and theory used (see S1 Table. Characteristics of Included Articles) [2663]).

Results

We conducted a scoping review of the literature to explore the variability in the conceptualization of FoMO since Przybylski et al.’s 2013 study. Additionally, we aimed to uncover the multifaceted roles ascribed to FoMO in relation to psychological well-being and digital technology use. In the subsequent sections, we present the sample characteristics and our findings on the two research questions.

Sample characteristics

The sample sizes of the studies included in this scoping review varied considerably, ranging from 40 to 5,280 participants. The average sample size across all studies was approximately 659 participants, with a median sample size of 343 participants. The participants’ ages also varied widely, from as young as 9 years old to as old as 80 years. However, the majority of the studies predominantly featured undergraduate students, reflecting a focus on younger demographics, with a mean age of 22 years. Further details on the study characteristics are provided in the S1 Table. Characteristics of Included Articles.

Conceptual scope and structure of FoMO (RQ1)

In response to RQ1, our scoping review addresses a recognized gap in the literature, echoing prior calls for more research on the nature of the FoMO construct (e.g., [7]). Among the included studies, only a handful of studies have examined the conceptual underpinnings of FoMO [6468], originally defined by Przybylski et al. (2013) as: “a pervasive apprehension that others might be having rewarding experiences from which one is absent, […] characterized by the desire to stay continually connected with what others are doing” [5]. Most studies only loosely allude to difficulties that may impede our understanding of FoMO. Reviewing these studies, we posit that clarity regarding the conceptualization of FoMO is impeded by (1) a lack of studies that have tested the conceptual structure of the construct, (2) blurring boundaries regarding the range of affective states that can be experienced in relation to FoMO, (3) ambiguity regarding the conceptual boundaries of FoMO, and (4) diverging perspectives as to whether FoMO is best viewed as a trait or a state.

Lack of studies that have tested the conceptual structure of the construct.

Przybylski et al. ’s definition of FoMO suggests the presence of two underlying dimensions: a “pervasive apprehension for missed social opportunities”, and a “desire to stay continuously connected with what others are doing”. The current literature reveals an ongoing debate about the extent to which both dimensions are defining components of FoMO. While some studies acknowledge both dimensions as defining components of FoMO (e.g., [69]), other scholars focus only on one dimension when describing FoMO. For example, Alt (2018) emphasizes the “pervasive apprehension” component by defining FoMO as: “an anxiety whereby one is compulsively concerned that one might miss an opportunity for social interaction, a rewarding experience, a profitable investment, or other satisfying events” ([70] cf. [71]). Brailovskaia et al. (2021), on the other hand, define FoMO as the desire to be constantly in touch with what others are doing ([72] cf. [1, 73]). Of the 106 included articles in our review, 88 scholars used Przybylski et al.’s original ten-item FoMO-scale (FoMOs). Of them, 12 scholars shortened Przybylski et al.’s original scale: FoMOs, by using only some items (e.g., [7476]). In doing so, they emphasize the anxiety component of FoMO over the desire to stay continuously connected component, or vice versa. For example, Alt (2018) removed items reflecting the desire to stay continually connected, thereby focusing on the anxiety aspect of FoMO [70]. In contrast, Franchina et al. (2018) used only four out of the ten items of the FoMO-scale, three of which reflected the desire to stay continually connected [77].

In eight articles, including the article in which the scale is developed [68], the Trait-State Fear of Missing Out Scale (T-SFoMOSC) by Wegmann et al. was used to assess FoMO (e.g., [78, 79]). This scale builds on the original FoMO construct by distinguishing between trait FoMO and state FoMO. Trait FoMO refers to a stable predisposition to experience FoMO, whereas state FoMO is a more situational and transient experience related to online activities. In the remaining 10 articles, various (self-designed) scales are used. In some cases, a self-designed questionnaire aim to apply FoMO to domains other than social experiences, extending the concept to include the fear of missing out on news information, referred to as News FoMO (e.g., [80, 81]). In other cases, participants are directly asked if they experience FoMO (e.g., [82]) using single item scales.

Within the FoMO literature only a few studies have conducted a dimensionality assessment to explore the factor structure of FoMOs, which yielded equivocal results. Elhai et al. (2018) conducted a confirmatory factor analysis (CFA) and found a good fit for a one-factor model [83]. The Turkish [84] and Spanish [85] translations of FoMOs also supported the original one-factor structure [5]. However, Al-Menayes (2016) conducted a factor analysis and found a two-factor solution for the Arabic translation of the FoMOs, with one factor reflecting feelings of anxiety and a second factor reflecting a desire to stay continually connected [86]. Similarly, Casale and Fioravanti (2020) found a similar two-factor structure for the Italian translation [87], and Li et al. (2021) for the Chinese translation of the original FoMO-scale [88]. None of these studies compared a one-factor model with a two-factor model, which is necessary to adequately assess the psychometric structure of a construct [89].

Blurring boundaries regarding the range of affective states that can be experienced.

Within the body of literature on FoMO, we can identify diverging perspectives on what constitutes feelings of “pervasive apprehension”. All studies seem to agree that FoMO refers to an unpleasant state that people experience when they are not engaged in activities or experiences that they consider rewarding (e.g., [66, 90, 91]. This unpleasant feeling is often conceptualized as anxiety (e.g., [92, 93]). In their definition of the concept, Przybylski et al. (2013) limit this feeling to feelings of apprehension, although the authors do not specify what can be understood as an apprehensive experience [5]. In the psychological literature, apprehension is known as one of the two dimensions of anxiety [94]. According to Elhai, Gallinari, Rozgonjuk et al. (2020) apprehension taps into cognitive aspects of anxiety such as worry or concern that something unpleasant might happen ([95] see also [96]). In this sense, apprehension can be distinguished from the second dimension of anxiety, often referred to as fear, i.e., the predominant type of anxiety present in panic, which is characterized by “a set of somatic symptoms distinct from those associated with anxious apprehension e.g., muscle tensions” [97]. Following the argument that FoMO is conceptually distinct from fear, Hayran et al. (2016) suggests renaming the term ‘fear of missing out’ to ‘feeling of missing out’. In line with this perspective, he broadly defines FoMO as “the negative affective state that individuals encounter as a result of becoming aware of […] experiences that are taking place in the environment, from which one is absent” [98]. Schmuck (2021) also argues that FoMO is related to negative affect, as it revolves around a lack of need satisfaction [78].

Indeed, the literature indicates that FoMO is linked to negative emotional states, rather than a mere absence of enjoyment from missing out on experiences perceived as rewarding. This was demonstrated in Milyavskaya et al.’s (2018) mixed-method study, which involved a longitudinal experience sampling method with nightly diaries and end-of-semester measures among 151 college freshmen (M = 18.0, SD = 1.04). The study showed that FoMO was significantly associated with negative affect, but not with positive affect [66]. There is some debate about the range of negative states that could be experienced in relation to FoMO: some scholars mention negative affective states other than anxiety that may be experienced when FoMO occurs, such as feelings of social exclusion [77, 91, 99], distress (1) envy [75, 91, 100102] and (anticipated/ post) regret [66, 103]. Hayran (2020) made an effort to clarify how, if at all, FoMO relates to these concepts, by examining FoMO in a nomological net [104]. Hayran’s experiments indicate that while other negative emotional states can coincide with FoMO, they don’t always manifest when FoMO is experienced. The author thereby concludes that FoMO is conceptually distinct from social exclusion, envy and (anticipated/post) regret [104]. However, Hayran measured FoMO with a single item (cf. [66]), i.e., "In this moment, to what extent do you feel like you are missing out on alternative activities and experiences taking place in your environment?". This measure does not mention any negative affective state that other scholars consider to be as defining components of FoMO, such as anxiety and apprehension (e.g., [93, 105], which can also be found in Przybylski et al.’s FoMO-scale (e.g., ’I fear […]’, ’I get anxious […]’ ’It bothers me […]’, ’ I get worried […]’ [5]. As such, Hayran measures FoMO as a cognitive rather than a negative affective state, which may explain why FoMO was not related to other affective states such as fear. It is therefore premature to claim, based on Hayran’s study alone, that FoMO is characterized by other affective states than fear or anxiety.

Ambiguity regarding the conceptual boundaries of FoMO.

In Przybylski et al.’s original conceptualization, FoMO is felt in relation to missed experiences. However, there are differing views on the nature of the missed experiences that may trigger the experience of FoMO. Some scholars (e.g., [67, 95, 106, 107]) argue that people are particularly afraid of missing out on social experiences, which are generally perceived as rewarding. This is also reflected in Przybylski et al.’s emphasis on the need to be continuously connected to what others are doing, which the authors argue is part of the FoMO experience [5]. Indeed, all ten items of Przybylski et al’s FoMO-scale refer to missed social experiences (e.g., “I get worried when I find out my friends are having fun without me”, “I fear my friends have more rewarding experiences than me”, “I get anxious when I don’t know what my friends are up to”) [5]. Some scholars add a comparative element (e.g., [64, 108]) by arguing that in order to experience FoMO, a missed social activity should be perceived as superior to the current activity the person is engaged in. These two perspectives are synthesized by Neumann (2020), who argues that FoMO involves two types of comparisons: (1) one’s own experience with those of others (cf. [1]), and (2) one’s current experience with an alternative that is perceived as more enjoyable, pleasurable, or rewarding (cf. [92, 109]).

Against this background, it is not surprising that some scholars limit FoMO to the context of social media. Social updates from others remind people of unattended alternative experiences in real time and are therefore likely to evoke FoMO. Similarly, Dossey (2014) argues that FoMO is: “a compulsive concern that one might miss an opportunity for social interaction, a novel experience, or some other satisfying event, often aroused by posts seen on social media sites” ([110] cf. [111]). This perspective stems in part from the fact that the most commonly used FoMO-scale (FoMOs; [5]) includes one item that refers to the online context, e.g., “When I have a good time it is important to me to share the details online (e.g., updating status)”, whereas Przybylski et al.’s original definition of FoMO does not specifically refer to social media use [87].

Milyavskaya et al. (2018) explored the conceptual boundaries of FoMO by examining whether one would experience FoMO in the case of (1) learning about missed non-social versus social activities, (2) while engaged in an obligatory versus a more rewarding alternative activity (e.g., studying versus meeting a friend), and (3) whether awareness of unattended alternative experiences needs to be established through social media exposure or whether FoMO occurs even if awareness is established otherwise [66]. Based on a vignette study, the authors report that FoMO is more prevalent when one misses out on a social (vs. non-social) activity, a finding that supports a second study by the authors in which FoMO is found to increase during social peak moments, i.e., moments later in the day and week (Thursdays, Fridays, and Saturdays). In addition, the results showed that people experienced FoMO regardless of whether the missed opportunity was communicated via social media or through direct contact with a friend, people equally experienced FoMO [66]. This suggests that FoMO can occur outside the context of social media, although social media can still increase people’s awareness of missed opportunities. This is supported by studies that show that people experience FoMO when they fear that they are missing out on physical gatherings and conversations with peers (e.g., [112, 113]). In the study by Milyavskaya et al. (2018), people also experienced FoMO regardless of whether they were engaged in an obligatory activity (e.g., studying) or an activity that was classified by the authors as self-chosen and more rewarding (e.g., watching a TV show, going to a party) [66]. However, the study design does not provide insight into whether people actually perceive each of these activities as rewarding, either in itself in comparison to alternative activities. Hayran et al. (2016), however, investigated self-relevance when considering the alternative activities of others, that is, the degree to which people perceive an activity as relevant to one’s self and life experiences. Based on the results of five experiments, the authors argue that FoMO is driven by the perception of favorable and self-relevant experiences taking place in one’s environment [98].

Zhang and colleagues (2020) propose two different conceptualizations of FoMO. Drawing on self-concept theory, which argues that a person’s self-concept consists of a public and a private self, the authors propose that people fear not only missing out on experiences that other people enjoy (social FoMO), but also experiences that they had wanted for themselves (personal FoMO) [114]. In line with this perspective, the authors developed a new scale consisting of two dimensions, i.e., a social and a personal FoMO, which showed good psychometric properties in four studies.

Other alternative scales have also been proposed, reflecting the perspective that FoMO may be experienced in relation to both social and non-social, but personally relevant, experiences. For example, Alt (2015) suggests that FoMO can also be experienced in relation to missing an opportunity for a profitable investment, a promotional offer, or news update [80]. Therefore, they extended the original FoMO-scale to include three dimensions: social FoMO (the original FoMO-scale), news information FoMO, and commercial information FoMO. In several studies (e.g., [70, 80, 81]), positive association results were found among the factors studied. Stretching the conceptualization of FoMO to a fear of missing out on news information and commercial information creates conceptual overlap with constructs such as news dependence (i.e., strong interest in and high consumption of news [115]), and market mavenism (i.e., a social-oriented tendency to acquire extensive knowledge of the market, including information about products, services, stores, best deals and buying in general [116, 117], each of which comes with its own causes and consequences.

In summary, the conceptual boundaries of FoMO continue to be a topic of ongoing scholarly debate. While initially linked to missed rewarding experiences, researchers have introduced diverse perspectives on what constitutes these rewarding experiences. While most emphasize that these missed experiences are primarily social in nature, there remains disagreement regarding the definition of what is truly rewarding and the role of comparison in making this assessment. Specifically, the debate centers on whether social experiences are inherently rewarding, or whether they acquire this quality only when they are superior to one’s current activities.

Diverging perspectives as to whether FoMO is best viewed as a trait or a state.

The above discussion alludes to the idea that FoMO is a state that is triggered by specific circumstances in which someone finds themselves at a particular moment in time (e.g., seeing social updates from others). This introduces a perspective on the nature of FoMO that challenges Przybylski et al.’s original conceptualization of FoMO as a trait: i.e., a factor that varies across individuals and remains relatively stable over time. Przybylski et al. (2013) initially described FoMO as an individual disposition, arising from the feeling that others are having rewarding experiences one is absent from [5]. Their FoMO-scale was therefore intended to measure individual differences in FoMO proneness.

While some researchers have embraced this perspective (e.g., [12, 77, 79]), no study to date has empirically tested whether FoMO should be viewed as a trait or as a state. Initial conclusions about the nature of FoMO can only be drawn from longitudinal studies. As part of the longitudinal design, these studies have examined whether FoMO is stable or more volatile over time, thereby providing preliminary insight into whether FoMO can be considered as a trait. In a study among 506 Facebook users aged 13–77 years (M = 20.7, SD = 9.10, Buglass et al. (2017) examined FoMO in two waves, with 6 months in between. They found that the relationship between FoMO measured at wave 1 and FoMO wave 2 was only moderate in magnitude (r = .55, p < .001) [64]. Lo Coco et al. (2020) also used a two-wave longitudinal survey (1 year apart), using two subscales of FoMO and showed positive but weak relationships between time 1 and time 2 measures (β = .19, p < .05; β = .35, p < .001) among university students (N = 506, M = 20.7, SD = 9.10) [67]. These results suggest that FoMO may not be as stable as one would expect from a trait.

Other, more indirect evidence comes from scholars who have examined FoMO in relation to other personality traits such as the Big-5. More specifically, these scholars have tested the extent of the correlation, if any, between FoMO the Big-5 personality traits–i.e., extraversion, neuroticism, conscientiousness, agreeableness, and, openness–and personality traits such as narcissism (e.g., [10, 66, 91, 108, 118120]). The results show mixed results between personality traits and FoMO, ranging from small to moderate effect sizes, or no effect at all (see S1 Table. Characteristics of Included Articles), which again does not provide strong evidence for FoMO as a trait.

Wegmann et al. (2017) reconcile both perspectives by arguing that FoMO is best be understood as a complex multidimensional construct that consisting of (1) dispositional trait-FoMO, which entails a general tendency to worry and experience anxiety about missing out on others people’s experiences, and (2) state-FoMO, which refers to a state that can be triggered by circumstances, specifically by online content and interactions with others [68]. In line with this perspective, Wegmann et al. (2017) conducted a study with 270 individuals aged 17–39 years (M = 23.43, SD = 4.02) and created a twelve-item FoMO scale intended to measure trait-FoMO and state-FoMO, which showed good psychometric properties [68]. Using this scale, Balta et al. (2018) showed that trait-FoMO does not fully predict state-FoMO in a sample of 423 Instagram users aged 14–21 years (M = 17.15, SD = 2.24), suggesting that factors other than those residing solely within an individual can trigger state-FoMO [118].

Thus, scholars have divergent thoughts regarding FoMO’s stability over time and its associations with personality traits. A multidimensional perspective, introduced by Wegmann et al. (2017), suggests both trait-FoMO and state-FoMO, offering a more comprehensive understanding of this phenomenon [68].

The multiple roles of FoMO in relation to psychological well-being and digital technology use (RQ2)

In addition to the absence of a shared understanding of what FoMO entails, there is also a lack of understanding regarding how FoMO is related to psychological well-being and digital technology use. By focusing on the second research question, the current review aims to gain more insight into the multifaceted roles that FoMO may play in the context of individuals’ psychological well-being and their use of digital technology. Based on the literature, we posit that such an understanding is impeded by (1) uneven attention to various roles ascribed to FoMO (2) the prevalence of correlational research, (3) a dearth of theoretical guidance, and (4) heterogeneity in the operationalization of psychological well-being and digital technology use.

Uneven attention to various roles ascribed to FoMO.

Since FoMO was introduced to the literature, research has proposed several hypotheses regarding the role of FoMO in the relationship between psychological well-being and digital technology use. Fig 2 visualizes all roles that have been attributed to FoMO in relation to psychological well-being and digital technology use in the included articles.

thumbnail
Fig 2. Roles of FoMO in its relationship with psychological well-being and digital technology use.

https://doi.org/10.1371/journal.pone.0308643.g002

The various roles that can be ascribed to FoMO stem from the idea that FoMO is a motivational force for digital technology use arising from deficits in psychological well-being, as initially proposed by Przybylski et al. (2013). The studies that have appeared since then have examined FoMO as a consequence of psychological well-being (path 1, e.g., [121, 122]) and/or as an antecedent of digital technology use reflecting the idea that FoMO may drive people to seek solace in digital technology use with increased levels of social media or smartphone use as the result (path 2, e.g., [123, 124]). Along these lines, FoMO is also hypothesized to act as a mediator in some studies to explain the effect of psychological well-being on digital technology use (path 3, e.g., [96, 125]).

Three more roles have been identified for FoMO, that allude to the commonly held idea, initially proposed by JWT intelligence (2011) and echoed by popular media, that digital technologies such as social media constantly remind people of socially rewarding situations in which they cannot participate [5]. Feelings of missing out that may arise from this continuous stream of social information, are believed to impair people’s well-being, with reduced feelings of life satisfaction and stronger feelings of anxiety and depression as the hypothesized result (e.g., [13, 126]. Studies that follow this line of thinking have examined FoMO as a consequence of technology use (path 4, e.g., [1, 127] and an antecedent of deficits in well-being (path 5, e.g., [16, 128]). Additionally FoMO is proposed to serve as a mediator explaining the hypothesized effects of technology use on well-being (path 6, e.g., [13, 91]).

The literature review shows that scholarly attention is not evenly distributed across the six identified paths between FoMO, psychological well-being and technology use. The direct path from psychological well-being to FoMO (path 1) has been examined in 19 articles, the path from FoMO to digital technology use (path 2) in 74 articles, and the path in which FoMO mediates the relationship between psychological well-being and digital technology use (path 3) in 15 articles. In contrast, the direct path from FoMO to digital technology use (path 4) was examined in 16 articles, the path from FoMO to well-being (path 5) in 24 articles, and the mediated path (path 6) in 7 articles. In 4 articles, the authors did not specify the direction of the hypothesized relationship between psychological well-being and FoMO, and in 12 articles, the authors did not specify the direction of the relationship between digital technology use and FoMO.

The prevalence of correlational research.

In line with the hypotheses that have been proposed, studies suggest that psychological well-being is negatively related with FoMO (path 1), while FoMO is positively related to technology use (path 2). Inverse relations have also been reported with technology use being positively related to FoMO (path 4), and FoMO negatively related to well-being (path 5). These findings suggest that effects can operate in both directions. With the exception of four studies [66, 127, 129, 130], most of the research conducted in this area has been correlational in nature, limiting our ability to make causal claims about the direction of the observed relationships. Only four studies used an experimental design [106, 126, 129, 130] and six used a longitudinal design measuring the variables of interest at multiple (two waves) points in time [64, 66, 67, 78, 131, 132].

Experimental studies were only conducted to test the path from digital technology use to FoMO (path 4), and the path from FoMO on psychological well-being (path 5). Brown and Kuss (2020) conducted an experimental study with 61 participants aged 20–49 years, focusing on the impact of seven days of social media abstinence and its downstream consequences for well-being to test path 4. Their findings revealed significant decreases in FoMO following an abstinence period [129]. Eide and colleagues (2018) also conducted an experimental study, with 127 smartphone users aged 18–48 years (M = 25.0, SD = 4.8), to test path 4. The results of their 72-hour smartphone restriction experiment showed that restricted smartphone use led to increased FoMO, suggesting that the inability to interact with one’s smartphone may also provoke FoMO [130]. Additionally, Fitz et al., (2019) showed in their randomized field experiment involving 237 MTurk smartphone owners (M = 30.3) that receiving no notifications at all–compared to receiving notifications as usual–led to higher levels of phone-related FoMO (C-FoMO-Scale; [133]). However, the indirect effect of never receiving notifications on anxiety via FoMO was not significant (path 5) [126].

Although in correlational research increased social media use is typically associated with more FoMO, in experimental research decreased social media is also found to contribute to more FoMO. This may indicate that the relationship between digital technology use and FoMO follows an inverted U-shape, such that people experience more FoMO when they are unable to use digital technology as well as when they use digital technology extensively. However, an alternative explanation may be provided by the idea that both limited use and excessive and uncontrolled use may threaten feelings of autonomy, one of the three basic human needs according to STD [134], which, if not met, are thought to lead to FoMO [5].

Milyavaskaya et al. (2018) reported the results of two studies that aimed to test path 6. In the first study, the authors used nightly diaries and end-of-semester measures of 151 college students (M = 18.0, SD = 1.04). They showed that those who experienced FoMO more frequently also reported increased levels of negative affect and stress at the end of the semester compared to the beginning of the school year. In a second experimental study among adult participants, the authors showed that experiencing FoMO led to a number of negative outcomes, such as increased negative affect and decreased positive affect in adult participants. Both results emphasize FoMO’s impact on well-being [66].

The two longitudinal studies that were conducted focused mostly on examining potential reciprocal relations between FoMO and technology use (path 2 and path 4) and were restricted to two-wave data. In a study among 242 adolescents aged 12–16 years (M = 14.16, SD = 0.99), Lo Coco et al. (2020) examined the cross-lagged relationship between two domains of FoMO; fear and control [87] and problematic smartphone use (PSU) using a two-wave panel model with a one-year interval. The researchers hypothesized that FoMO could lead to increased problematic social media use. However, the reverse causal effect was also hypothesized, such that an increase in PSU would be expected to lead to an increase in FoMO. The results of the bidirectional relationships examined showed that FoMO and problematic smartphone use were positively related at both points in time. However, the bidirectional findings were not supported longitudinally [67].

In another two-wave longitudinal study amongst 506 Facebook users aged 13–77 (M = 20.7, SD = 9.10), aimed to test path 6, Buglass et al. (2017) showed that an increase in self-reported social media use led to increased levels of FoMO six months later. Moreover, significant indirect effects were observed between SNS use, FoMO, and psychological well-being as measured by self-esteem. The longitudinal results also hinted at a potential cyclic relationship between the main study variables, with low self-esteem at T1 appearing to drive FoMO six months later [67].

To conclude, the current body of research on FoMO and its relationship with psychological well-being and technology use has primarily relied on correlational studies, limiting our ability to establish causal claims (cf. [66]). The few experimental findings supported the impact of FoMO on digital technology use (path 2), as well as the association between restricted technology use and increased FoMO (path 4). However, it is important to note that the results across studies were not consistent, as Lo Coco et al. (2020) did not find cross-lagged support for both of these pathways in their longitudinal study [67]. Also, none of the longitudinal studies employed three wave designs which are better suited to establish causal effects [135]. Nevertheless, there is longitudinal evidence supporting the relationship between digital technology use, FoMO, and well-being (path 6), emphasizing the significant influence of FoMO on psychological well-being.

A dearth of theoretical guidance.

Although some scholarly works analyzed in this review rely on theory to substantiate their hypotheses, there is a noticeable deficit in the use and advancement of theory. In general, it appears that about 45% of studies are theory driven. The other studies merely refers to the role of FoMO within a nomological web without clarity regarding a specific theory or conceptual framework, highlighting a dearth of theoretical guidance for understanding FoMO’s role in the relationship between digital technology usage and psychological well-being. Some hypothesized paths (see Fig 2) are better substantiated with theory than others: 15 of 19 articles in path 1, the path from psychological well-being to FoMO, refer to theory, 38 of 74 articles in path 2, the path from FoMO to digital technology use, 4 of 16 articles in path 4, the path from digital technology use to FoMO, and 10 of 24 articles in path 5, the path from FoMO to psychological well-being.

In theorizing about FoMO, scholars have primarily adopted Przybylski et al.’s perspective that departs from Self-Determination Theory (SDT; [136]) and explains FoMO from a motivational lens. SDT holds that individuals’ purposeful, goal-driven actions are driven by three intrinsic psychological needs that they seek to fulfill in relation to others: the need for autonomy, competence, and relatedness. According to Przybylski et al. (2013), FoMO arises from deficiencies in one or more of these fundamental psychological needs, as these needs must be satisfied for people to function in an optimal and healthy way [5]. Surprisingly, none–except one–of the included studies have examined the relation between psychological needs and FoMO. Studies loosely allude to SDT without actually subjecting it to empirical testing. This holds for articles examining path 1 predicting FoMO as a consequence of deficits in psychological well-being, as SDT seems to suggest, but also for articles examining the reversed relationship (path 5), as well as other paths (paths 2; the path from FoMO to digital technology use and 3, the path in which FoMO mediates the relationship between psychological well-being and digital technology use). The only study that examined the relationship between psychological need satisfaction was correlational. This study, which included 306 university students aged 18–30 years (M = 21.8, SD = 3.19), showed moderate associations between psychological need satisfaction and FoMO (i.e., autonomy r = -.50, competence, r = -.46, relatedness, r = -.43; [137]).

In line with the motivational lens that Przybylski et al. propose, the Compensatory Internet Use Theory (CIUT; [138] is mentioned to explain the relationship between FoMO and technology use (path 2), and vice versa (path 4). CIUT is a psychological framework that was originally proposed to explain (problematic) internet use [138], but has also been applied to explain social media use and smartphone use (e.g., [123, 139]. The theory argues that people turn to digital technologies to compensate for unmet needs or deficits in their offline lives and cope with emotional or psychological issues. For example, individuals experiencing loneliness may engage excessively in social media to fulfill their need for social connection, using these platforms as a means to compensate for their lack of offline social interactions.

A more comprehensive framework that is believed to explain interrelations between FoMO, psychological well-being and digital technology use, is the Interaction of Person-Affect-Cognition-Execution (I-PACE; [140]); a process model grounded in the addiction literature, predicting problematic technology use from a dynamic interplay of a person’s core characteristics and cognitive, affective, and executive processes. The first level of the model comprises of core characteristics such as personality traits (e.g., impulsivity and low conscientiousness), psychopathological symptoms (e.g., depression and social anxiety), use motives, biopsychological factors (e.g., sex and age) and social cognitions (e.g., loneliness and perceived lack of social support), as well as an individual’s subjective perception of situational factors. The second level of the model includes mediators and moderators that can either amplify or mitigate the influence of core characteristics, ultimately shaping an individual’s decision to use technology to satisfy their needs or seek gratification. These factors include cognitive biases linked to technology (i.e., unrealistic expectations about the outcomes of using technology, leading to the expected gratification of pleasure, for instance), as well as cognitive and emotional responses such as those observed in other addictive behaviors (e.g., craving, urge for mood regulation, attentional bias, cue-reactivity). The feeling of gratification strengthens factors residing on the first and second level of the model, resulting in a reinforcing cycle that ultimately leads to addictive use of digital technology at the third level.

Within the I-PACE model, FoMO has been attributed different roles by various scholars. For instance, Wegmann et al. (2017) (cf. [141]) conceptualize FoMO as a cognitive bias, defined as "the expectation of experiencing pleasure or avoiding negative emotions when using Internet-communication applications such as social media" [68]. In the same line, Elhai, Yang, Fang, et al. (2020) [125] and Elhai, Yang, Rozgonjuk, et al (2020) [142] views FoMO as a cognitive biases, although Elhai, Gallinari, Rozgonjuk, et al. (2020) [95], sees FoMO also as an affective response. While these authors ascribe different roles to FoMO, they share the hypothesis that FoMO serves as a variable linking psychological well-being to digital technology use (paths 1, 2, and 3). On the other hand, Fabris (2020), presents an alternative perspective, arguing that FoMO can be regarded as a core characteristic, specifically a need or motive, that leads to decreased well-being manifested as emotional distress [128] (path 5; cf. [143]). Ambiguity regarding the role of FoMO in the relationship between psychological well-being and digital technology thus seems to stem from ambiguity in the conceptualization of FoMO (see RQ1).

In addition to these theories, various other theoretical approaches have been mentioned to explain the relationship between FoMO, psychological well-being and digital technology use, including Social Comparison Theory (SCT; [144]), Differential Susceptibility to Media Effects Model (DSMM; [145]), and Threaded Cognition Model (TCM; [146]). Since these theories are referenced in the context of hypothesis development but not empirically tested, there is a limited empirical basis to confirm their value in explaining hypothesized relationships. This hinders the construction of theory development to guide our understanding of FoMO and the role it plays in the relationship with psychological well-being and digital technology use.

Heterogeneity in the operationalization of FoMO’s antecedents and consequences.

The review shows that research is inconsistent in how it operationalizes and assesses digital technology use. This can be attributed to various factors, including differences in the specific digital technology behaviors being studied (e.g., engagement with social media use, smartphone use, or general internet browsing) and variations in the timeframes employed for data collection. Some studies focus on immediate effects resulting from brief interactions with specific social media platforms, spanning minutes to hours (e.g., [77]), while others explore the consequences of prolonged usage based on overall social media engagement [147].

Moreover, there is an uneven distribution of attention across paths in terms of the type of digital technology studied. Studies examining FoMO as a consequence of digital technology use (path 4) and those examining FoMO as a mediator in the relationship between technology use and psychological well-being (path 6), have primarily focused on social media use, with less emphasis on smartphone use. In contrast, studies that examined the reversed path–i.e., FoMO as a mediator in the relationship between psychological well-being and technology use (path 3)–focused primarily on various forms of smartphone use, such as average time spent on smartphones and problematic smartphone use, with less attention to social media use. What may further complicate our understanding is the fact that individuals often access social media through their smartphones (3). This is supported by large associations between (problematic) smartphone use and (problematic) social media use (e.g., [148]), indicating that two forms of digital technology use are partly overlapping phenomena (3).

There has not only been limited research on how social media relates to smartphones in their potential to trigger FoMO, but there has also been scant exploration of distinctions between social media. Assuming that platforms differ in the types of users they attract, the types of interactions they facilitate (private vs. public), and the types of content they feature, they are likely to engender differential effects on the manifestation of FoMO. In a large-scale study involving 2,663 high school pupils (M = 14.87, SD = 1.67), Franchina et al. (2018) offers preliminary insights, indicating that FoMO was a stronger predictor of social media use on more private platforms, exemplified by Facebook and SnapChat, compared to more public platforms like YouTube and Twitter. The authors posit that private platforms, distinguished by more restricted content access, are better suited to provide relief from FoMO, due to their ability to provide users with a sense of relief from anxieties associated with staying informed about the activities of friends and family. In contrast, platforms with content accessible to a broader and predominantly unknown audience may not offer the same level of reassurance [77].

Another study by Fumagalli et al. (2021), involving 334 young adults (M = 21.50, SD = 2.03), aligns with this notion, suggesting that the nature of social network usage can significantly impact feelings of FoMO [149]. The findings indicate that social networking apps like Facebook and Instagram, characterized by passive content consumption enabling users to observe others’ activities, are associated with increased feeling of FoMO. In contrast, interactive messaging apps like WhatsApp or iMessage, which facilitate a more direct form of peer-to-peer communication, are not linked to heightened FoMO.

The nature of the content being viewed may be particularly imperative to study, as people might feel a sense of missing out only if exposed to content illustrating socially rewarding situations from which they were excluded. Hence, the predominant focus on digital technology use in terms of time spent, motivations, and problematic use, should be broadened to also include the specific content being consumed.

Finally, most studies rely on self-reported technology use. Only four studies [131, 149151] have employed objective measures of digital technology use such as providing screenshots to display usage, while all other studies have relied on self-report measures. In a study involving 85 adolescents aged 12–16 years (M = 14.04, SD = 1.09), Sela et al. (2020) demonstrated that although objective time spent online did not exhibit a significant correlation with FoMO, the objective duration of engagement with social networking sites did (r = 0.28, p < 0.05) [150]. Similarly, Hunt et al. (2018), in a study with 143 undergraduate university students, also established a significant association between FoMO and objectively measured social media usage (r = 0.20, p < 0.05) [131]. The findings from Shoval et al.’s (2020) study involving 40 college students aged 19–30 years (M = 23.0, SD = 2.4), highlight the significance of disparities between objective and subjective measures. In their study, only those identified by the objective measure as checking their smartphone during the night showed significant differences (checked vs not checked) in FoMO experiences, whereas the subjectively measured data did not [151].

Heterogeneity also exists in terms of variables studied as indicators of psychological well-being or a lack thereof. The review shows that studies on FoMO have examined a diverse range of indicators of well-being (e.g. life satisfaction, positive affect, e.g., [121]), as well as a range of indicators of ill-being (e.g. depression, negative affect) (e.g., [140]). Among all pathways, ill-being indicators have received significantly more attention in the literature compared to well-being indicators, particularly depression and anxiety (e.g., [126, 152]), which have emerged as the most frequently studied aspects in the context of FoMO research. Only on Path 6, the mediated path of digital technology psychological well-being via FoMO, the ill- and well-being indicators have been studied more proportionately.

Moreover, many studies lump together different psychological well-being indicators (ill-being as well as well-being indicators) to draw general conclusions about the impact of FoMO on individuals psychological well-being and vice versa. For instance, Akyol et al. (2021) combine measures of depression, anxiety, and stress under the umbrella term "mental health" in their examination of its impact on FoMO [153], while Wegmann et al. (2017) aggregate measures of depression and interpersonal sensitivity to assess the construct of “psychopathological symptoms” [68].

The inconsistencies in the operationalization and assessment of digital technology use and psychological well-being make it challenging to synthesize the results of the studies and draw conclusions about the relationships between FoMO, digital technology use and psychological well-being, as the effects may vary depending on the digital technology use and psychological well-being indicator studied. This challenge becomes evident in the studies of Yin et al. (2019) [102] and Błachnio and Przepiórka (2018) [108], both of which used the Facebook Intrusion Questionnaire [154], but Yin et al. aimed to measure SNS addiction, whereas Błachnio and Przepiórka aimed to measure Facebook intrusion. Researchers have coined the term "jingle-jangle problem" to elucidate the potential confusion and ambiguity arising when similar terms are used to describe different phenomena [155]. This phenomenon is exemplified in instances such as the terms "self-esteem" and "self-confidence", which some researchers may use interchangeably, assuming their equivalence, while others may assert nuanced disparities between these constructs. Similarly, some scholars use “social media use” to describe a wide range of experiences, from active engagement with close friends on platforms like SnapChat (e.g., [107]), to passive scrolling through captivating Twitter threads or Instagram photos (e.g., [13]). Likewise, the terms “online social networking” may refer to the identical phenomena, hindering knowledge accumulation in the field. The diversity in measures and approaches to measure psychological well-being and digital technology use in relation to FoMO presents a significant challenge. Inconsistencies in operationalization, limited use of objective measures, and varying emphasis on well-being and ill-being indicators make it challenging to synthesize findings and advance research in this field.

Discussion and research agenda

This study conducted a scoping review of the existing literature on FoMO, which has been characterized as fragmented and lacking a unified understanding of its nature, causes, and consequences. Despite a surge in research since its initial conceptualization by Przybylski and colleagues in 2013, a disjointed understanding of FoMO persists. To address these issues, we systematically analyzed the literature since Przybylski et al.’s seminal work, focusing on two key research questions to clarify how FoMO is conceptualized and uncover its roles in psychological well-being and digital technology use. The first research question aimed to gain more insight into how FoMO has been conceptualized in the literature, and how this conceptualization has varied across the extensive body of research published (RQ1). The second research question aimed to investigate the roles attributed to FoMO in relation to psychological well-being and digital technology use and to assess the extent to which findings supported these roles and the variations in findings across studies (RQ2).

By pursuing these research questions, we aimed to offer clarity and insight into the diverse perspectives on FoMO’s definition, determinants, and consequences, as well as its multifaceted roles in shaping individuals’ psychological well-being and digital technology use. This endeavor was driven by the necessity to bridge gaps in the fragmented FoMO literature and to establish a robust foundation for future research in the digital age.

Moving towards conceptual clarity and parsimony (RQ1)

Our literature review shows that FoMO is universally acknowledged as an unpleasant feeling stemming from a missed opportunity to engage in an experience, often described as apprehension [65]. Scholars widely concur that these missed experiences fundamentally represent social phenomena rooted in human interaction (e.g., [7, 67]). FoMO revolves around the idea that one is not engaged in an experience others are engaged in. Unpleasant feelings arising from this comparison drive a desire to stay continuously connected with ongoing social experiences. This desire is not confined to the physical aspect of presence. It manifests as a need to engage with what others are doing or discussing, transcending the boundaries of physical participation (e.g., [112]). Nor is FoMO confined to the context of social media [66]. Research shows that people may experience FoMO irrespective of the manner in which missed experiences are brought to their attention. Yet, the literature does show that social media may amplify people’s awareness of missed opportunities [66].

Hence, our literature review suggests that scholars widely agree that FoMO can be seen as (1) an unpleasant feeling over (2) missed social experiences (3) revolving around a comparison of one’s own activities with possible alternative activities, (4) that gives rise to a desire to stay connected with what others are involved in. Yet, the literature review also identifies four key debates concerning the conceptualization of FoMO, which present valuable pathways for future research.

Examine the range of feelings that can be experienced in relation to FoMO.

Although scholars agree that FoMO involves unpleasant feelings that people experience about unattended experiences, there is still debate about the range of feelings that people encounter when they experience FoMO. While some scholars conceptualize FoMO narrowly as feelings of pervasive apprehension, others are in favor of a broader conceptualization that includes other feelings as well. Hayran et al.’s (2020) proposal to rename FoMO to “Feeling of Missing Out” instead of “Fear of Missing Out” and expand the definition to “the negative affective state that individuals encounter […]”, illustrates this line of thinking [104]. However, this broadening of the conceptual scope may lead to conceptual overlap, making it increasingly difficult to distinguish FoMO from other concepts that have been proposed as antecedents or consequences of FoMO. For example, Przybylski et al. (2013) position negative affect as an antecedent rather than a defining component of FoMO, such that negative affect is more likely to lead to FoMO experiences [5]. With this in mind, it is important to examine the range of affective states fundamental to FoMO in order to determine the conceptual scope of the construct, as well as its boundaries with other constructs such as social comparison and regret tendency (e.g., [156, 157]).

Gain insight in the manifestations of FoMO to clarify conceptual boundaries.

The literature seems to agree that comparison is central to the FoMO experience. However, there is still ambiguity about what this comparison refers to: (1) one’s own experience with that of someone else (social), and (2) one’s present experience with a more rewarding alternative (competitive), or (3) a combination of both (e.g., [66, 98, 114]). These conceptual boundaries need to be clarified through follow-up research to gain more insight into the situations in which FoMO is likely to manifest. This requires scholars to collect data on the nature (e.g., social, non-social) of one’s current activity and that of the potential alternative activities, as well as the manner in which these alternative activities were brought to one’s attention (e.g., social media). It is also important to explore the extent to which these activities are perceived as rewarding and self-relevant [98], as this will shed light on the psychological processes that drive individuals to constantly seek alternative, potentially more rewarding experiences. Diary research combined with content analysis (what do they see, what are they aware of) can potentially address these questions.

Test the conceptual structure of FoMO.

The review highlights that there is ambiguity regarding the structure and dimensionality of FoMO. The debate surrounding the conceptualization of FoMO centers on the two key elements of FoMO as proposed by Przybylski et al. (2013): "pervasive apprehension for missed social opportunities" and "a desire to stay continuously connected with what others are doing" [5]. The literature review shows that some scholars emphasize one dimension over the other when defining FoMO, leading to variations in its conceptualization. Moreover, some studies have shortened the original FoMO scale, inadvertently emphasizing either pervasive apprehension or the desire to stay connected component. Despite these variations, only a limited number of studies have tested the dimensionality of FoMO, leaving the psychometric structure of FoMO relatively unexplored. If FoMO indeed does not have a unidimensional structure, but rather consists of two subdimensions, as some research suggests (e.g., [5688]), this may have implications for the development of a coherent theoretical body of literature on FoMO. As argued by Garrido et al. (2019), approaching FoMO as a unidimensional construct carries the potential risks of "leading to biased item parameter estimates, loss of information, and factor score estimates that cannot be univocally interpreted because they reflect the impact of multiple sources of variance”, when actually it is actually a multidimensional construct [158]. Therefore, future research should examine the conceptual structure of FoMO.

Disentangle FoMO as a trait or a state.

Research to date lacks evidence to support Przybylski et al.’s perspective that FoMO should be viewed as an individual disposition, i.e., a trait, implying that it remains relatively stable across individuals and over time. Initial research seems to indicate that FoMO can be triggered under certain circumstances at a specific moment in time, and thus can also be considered a state (e.g., [64, 67]). The discussion on whether FoMO should be classified as a trait or a state or perhaps a more complex construct that encompasses both trait and state elements (as suggested by [68]), represents a critical juncture in our understanding of this phenomenon. Future research can validate this by using advanced statistical methods such as Random Intercept Cross-Lagged Panel Model (RI-CLPM), which can disentangle between-person effects (trait-like) from within-person effects (state-like) over time [159]. This approach will provide a more rigorous and nuanced examination of the trait versus state dimension of FoMO, shedding light on its fundamental nature. Ultimately, clarifying the nature of FoMO is crucial to advance our theoretical understanding but also for developing targeted interventions and strategies aimed to mitigate FoMO’s impact on individuals’ psychological well-being and digital technology behaviors.

Unraveling the multifaceted roles of FoMO in psychological well-being and digital technology use (RQ2)

Our comprehensive review of the literature on the second research question reveals a spectrum of roles attributed to FoMO in relation to psychological well-being and digital technology use, with expected relations from psychological well-being to digital technology use via FoMO and vice versa. Overall, there is ample evidence for a negative relationship between psychological well-being and FoMO, while FoMO is positively associated with technology use. The limited experimental studies that have been conducted, also provide preliminary causal support for an opposing effect; i.e., that restricted technology use increases FoMO (path 4). Hence, it’s important to acknowledge that there is variability in the results of these studies. Nevertheless, the longitudinal evidence strengthens the case for the interrelationship between digital technology use, FoMO, and well-being (path 6), underscoring the important role that FoMO plays in shaping psychological well-being. These findings tentatively indicate that the relationships are bidirectional and that FoMO plays a critical role in these complex interactions. In addition, research indicates that the associations between FoMO and problematic digital technology use are markedly more pronounced than the association between FoMO and conventional usage metrics.

Balance research efforts.

Since its introduction, research has proposed multiple roles for FoMO in the relationship between psychological well-being and digital technology use. These roles include FoMO as a consequence of well-being (path 1), an antecedent of increased technology use (path 2), as well as a mediator linking the relationship between well-being and technology use (path 3). The literature also hypothesizes reciprocal effects where FoMO functions as a consequence of technology use (path 4), an antecedent of well-being deficits (path 5), and a mediator for the effects of technology use on well-being (path 6). Interestingly, the literature review reveals varying levels of scholarly attention across these paths. While paths 1–3 have received considerable attention, highlighting the initial hypothesis that FoMO motivates technology use due to well-being deficits, as suggested by Przybylski et al. (2013) [5], the underexplored paths 4–6 indicate a need for further investigation. In particular, the limited exploration of path 4, where FoMO arises as a consequence of technology use, calls for more comprehensive research to address societal concerns about technology’s impact on FoMO and psychological well-being [160]. This research would contribute to a more nuanced understanding of the complex interplay between FoMO, digital technology use, and psychological well-being.

Unbalanced is also the disproportionate attention given to young adults in the study of FoMO and its antecedents and consequences. Although there was variation in the study samples, most studies have focused on young adults. Therefore, future research is needed among a more diverse sample to enhance the generalizability of findings and understand FoMO’s impact across different demographics.

In need of causal research. Empirical findings seem to provide some support for FoMO’s role as both an antecedent and consequence of psychological well-being and digital technology use. However, the vast majority research in this area has been correlational and cross-sectional in nature, limiting our ability to make causal claims. Experimental studies have provided some insights, supporting the impact of restricted technology use on FoMO (path 4; e.g., [130]). Only one longitudinal study has provided further support for an effect of digital technology use on FoMO (path 4), and through FoMO on stress (path 6; [64]), providing some support for FoMO’s influence on psychological well-being. Yet, these findings relied on two-wave data which can’t fully capture bidirectional dynamics of these relationships. These findings imply that further research should employ experimental and longitudinal designs to better establish causality within these complex relationships. Additionally, exploring the potential cyclic nature of these pathways would be another valuable research endeavor. to put such dynamics to the test, these studies would require scholars to measure FoMO, psychological well-being and technology use at three waves or more [135].

In need of theoretical guidance.

Most studies eschew the inclusion of theory as an explanatory framework for the presumed relations between FoMO and psychological well-being and/ or digital technology usage. Hence, it is imperative that future research explicitly specify the theoretical lens through which it examines the role of FoMO within the broader nomological network, not only to establish a solid foundation but also to ensure theoretical clarity and empirical validation. The studies that do use theory mostly follow Przybylski et al. who adopted a motivation-based perspective grounded in SDT [161] to explain FoMO and its relationships with psychological well-being and digital technology use. More specifically, they proposed that FoMO arises as a negative emotional state stemming from deficiencies in one or more of these basic psychological needs [5], thereby motivating the desire to stay connected to what others are doing through digital technology use. While scholars have largely embraced Przybylski et al.’s perspective, empirical testing of this theoretical premise has been limited, with only one study reporting moderate associations between psychological need satisfaction and FoMO [137].

Besides SDT [161], a number of other theories have been alluded to explain not only the effects of psychological well-being on FoMO and their downstream consequences for technology use, but also vice versa, such as CIUT) [138] and SCT [144]. Many of these theories are not specific in their explanation of how digital technology use contributes to FoMO and how that negatively affects psychological well-being. This is reflected in our observation that these theories are only mentioned as possible explanations for associations between these variables but are not explicitly tested. As a consequence, these theories are used as bulk theories, that is, as theories that are used to explain the effects of psychological well-being and digital technology use as both consequence and effect of FoMO, when in essence these theories were not developed for this for explaining such bi-directional relationships. Hence, hypotheses formulated in the FoMO literature appear to lack a robust integration with the cited foundational theories, raising concerns about the coherence of the theoretical basis underpinning these hypotheses and hindering our ability to accurately assess the antecedents and consequences of FoMO. Particularly given the potential bidirectional relations between psychological well-being, FoMO, and digital technology use.

One way to advance our theoretical understanding of FoMO is to develop a unifying theory that explains the bi-directionality of psychological well-being, FoMO and digital technology use. The I-PACE model [140] attempts to elucidate these dynamics, but due to conceptual ambiguities, there is no consensus regarding the specific role FoMO plays in this model. Developing a unifying theory would address the concerns raised by various scholars regarding the fragility and fragmentation of the theoretical foundations within the current FoMO literature (e.g., [6]).

Unifying terminology in FoMO research.

The current state of the literature reveals a heterogeneous landscape in how researchers conceptualize, operationalize and assess psychological well-being and digital technology use, presenting barriers to synthesizing findings and advancing research on FoMO. Factors contributing to this lack of coherence include the uneven distribution of attention to indicators of digital technology use across different pathways. For instance, research on the impact of digital technology use on FoMO (path 4) and its subsequent influence on psychological well-being (path 6) tends to focus more on social media use, while the reverse pathway, examining the effect of psychological well-being on digital technology use via FoMO (path 3), is more commonly explored concerning smartphone use, impeding a holistic understanding.

Additionally, variability in operationalizing digital technology behaviors further complicates the issue, as some studies concentrate on smartphone addiction (e.g., [26]), others explore motives for social media use [27], or internet and online communication use (e.g., [14]), making comparison and generalizations challenging. Differences in time frames used for data collection further exacerbate the problem, with research spanning short-term cross-sectional surveys (e.g., [77]) to longitudinal studies spanning months (e.g., [64]). Moreover, the reliance on self-report measures in lieu of objective data, such as device logs, introduces subjectivity and potential reporting biases. Adding to this complexity is the common practice of individuals accessing social media through their smartphones (e.g., [3, 148]), which makes it hard to distinguish smartphone use from social media use. Understanding these intricacies and relationships will require a more integrated approach to research.

In addition, the literature also reveals a noticeable imbalance in the exploration of indicators of psychological well-being, with a greater emphasis on indicators of ill-being than on indicators of well-being. In the absence of standardized terminology and uniform measures, researchers may use overlapping or interchangeable terms to describe phenomena, which can lead to confusion and hinder cumulative knowledge development. The variation in conceptualizations, measurement methods and approaches to assess the connection between FoMO and psychological well-being poses a substantial obstacle. Incoherent operationalization, restricted use of objective metrics, and differences in the emphasis on indicators of well-being and ill-being create difficulties in consolidating results and pushing forward research in this domain.

To address these challenges and support future research, scholars must agree on a common lexicon that covers the full range of relevant variables. Standardized terms and adopting objective measures, will facilitate cross-study comparison and promote clarity enhancing our understanding of the intricate relationships between FoMO, psychological well-being, and digital technology use.

Supporting information

S1 Table. Characteristics of included articles.

https://doi.org/10.1371/journal.pone.0308643.s003

(PDF)

Acknowledgments

We like to thank Aniek van Heck (AvH) and Tijs Portegies (TP) for their assistance in the study selection process.

References

  1. 1. Barry CT, Wong M. Fear of missing out (FoMO): A generational phenomenon or an individual difference? Journal of Social and Personal Relationships [Internet]. 2020 Aug 7;37(12):2952–66. Available from:
  2. 2. Statista: Number of worldwide social network users 2027 [Internet]. Statista. 2023 [cited 2023 Sep 6]. https://www.statista.com/statistics/278414/number-of-worldwide-social-network-users/
  3. 3. Kuss DJ, Griffiths MD. Social networking sites and Addiction: Ten lessons learned. International Journal of Environmental Research and Public Health [Internet]. 2017 Mar 17;14(3):311. Available from: pmid:28304359
  4. 4. Taylor SH, Bazarova NN. Always Available, Always attached: A relational perspective on the effects of mobile phones and social media on Subjective Well-Being. Journal of Computer-Mediated Communication [Internet]. 2021 Jul 1;26(4):187–206. Available from:
  5. 5. Przybylski AK, Murayama K, DeHaan CR, Gladwell V. Motivational, emotional, and behavioral correlates of fear of missing out. Computers in Human Behavior [Internet]. 2013 Jul 1;29(4):1841–8. Available from:
  6. 6. Tandon A, Dhir A, Almugren I, AlNemer GN, Mäntymäki M. Fear of missing out (FoMO) among social media users: a systematic literature review, synthesis and framework for future research. Internet Research [Internet]. 2021 Feb 12;31(3):782–821. Available from:
  7. 7. Elhai JD, Yang H, Montag C. 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 [Internet]. 2021 Apr 1;43(2):203–9. Available from: pmid:32401865
  8. 8. Bayer JB, Triệu P, Ellison NB. Social media elements, ecologies, and effects. Annual Review of Psychology [Internet]. 2020 Jan 4;71(1):471–97. Available from: pmid:31518525
  9. 9. Alt D, Boniel-Nissim M. Parent–Adolescent communication and Problematic Internet Use: The Mediating Role of Fear of Missing Out (FOMO). Journal of Family Issues [Internet]. 2018 Jun 20;39(13):3391–409. Available from:
  10. 10. Alt D, Boniel-Nissim M. Using multidimensional scaling and PLS-SEM to assess the relationships between personality traits, problematic internet use, and fear of missing out. Behaviour & Information Technology [Internet]. 2018 Jul 26;37(12):1264–76. Available from:
  11. 11. Alt D, Boniel-Nissim M. Links between Adolescents’ Deep and Surface Learning Approaches, Problematic Internet Use, and Fear of Missing Out (FoMO). Internet Interventions [Internet]. 2018 Sep 1;13:30–9. Available from: pmid:30206516
  12. 12. Busch PA, Hausvik GI, Ropstad OK, Pettersen D. Smartphone usage among older adults. Computers in Human Behavior [Internet]. 2021 Aug 1;121:106783. Available from:
  13. 13. Burnell K, George MJ, Vollet JW, Ehrenreich SE, Underwood MK. Passive social networking site use and well-being: The mediating roles of social comparison and the fear of missing out. Cyberpsychology [Internet]. 2019 Jul 12;13(3). Available from:
  14. 14. Radić A, Ariza-Montes A, Hernández-Perlines F, Giorgi G. Connected At Sea: The influence of the internet and online communication on the Well-Being and Life Satisfaction of Cruise Ship employees. International Journal of Environmental Research and Public Health [Internet]. 2020 Apr 20;17(8):2840. Available from: pmid:32326093
  15. 15. Beyens I, Frison E, Eggermont S. “I don’t want to miss a thing”: Adolescents’ fear of missing out and its relationship to adolescents’ social needs, Facebook use, and Facebook related stress. Computers in Human Behavior [Internet]. 2016 Nov 1;64:1–8. Available from:
  16. 16. Orta İM. Fear of missing out, Internet Addiction and TheirRelationship to Psychological Symptoms. Addicta: The Turkish Journal on Addictions [Internet]. 2020 Jan 1;7(1):67–73. Available from: https://app.trdizin.gov.tr/makale/TXpVNE1qUTNOdz09/fear-of-missing-out-internet-addiction-and-their-relationship-to-psychological-symptoms
  17. 17. Peters MDJ, Godfrey C, McInerney P, Munn Z, Trico A, Khalil H. Chapter 11: Scoping reviews. In: JBI eBooks [Internet]. 2020.
  18. 18. Tricco AC, Lillie E, Zarin W, O’Brien KK, Colquhoun H, Levac D, et al. PRISMA Extension for Scoping Reviews (PRISMA-SCR): Checklist and explanation. Annals of Internal Medicine [Internet]. 2018 Oct 2;169(7):467–73. Available from: pmid:30178033
  19. 19. Otten R, De Vries R, Schoonmade L. Amsterdam Efficient Deduplication (AED) method. https://zenodo.org/records/3582928 [Internet]. 2019 Dec 12; https://zenodo.org/record/3685604
  20. 20. Bramer WM, Giustini D, De Jonge GB, Holland L, Bekhuis T. De-duplication of database search results for systematic reviews in EndNote. Journal of the Medical Library Association [Internet]. 2016 Jul 1;104(3):240–3. Available from: pmid:27366130
  21. 21. Moher D. Preferred reporting items for Systematic Reviews and Meta-Analyses: the PRISMA statement. Annals of Internal Medicine [Internet]. 2009 Aug 18;151(4):264. Available from: pmid:19622511
  22. 22. Diener E, Suh EM, Lucas RE, Smith H. Subjective well-being: Three decades of progress. Psychological Bulletin [Internet]. 1999 Mar 1;125(2):276–302. Available from:
  23. 23. Houben M, Van Den Noortgate W, Kuppens P. The relation between short-term emotion dynamics and psychological well-being: A meta-analysis. Psychological Bulletin [Internet]. 2015 Jul 1;141(4):901–30. Available from: pmid:25822133
  24. 24. Hancock JT, Liu SX, Luo M, Mieczkowski H. Social media and psychological well-being. In: American Psychological Association eBooks [Internet]. 2022. p. 195–238.
  25. 25. Johannes N, Dienlin T, Bakhshi H, Przybylski AK. No effect of different types of media on well-being. Scientific Reports [Internet]. 2022 Jan 6;12(1). Available from: pmid:34992220
  26. 26. Çatıker A, Büyüksoy GDB, Özdi L K. Is there a relationship between nursing students’ smartphone use, their fear of missing out and their care-related behaviour? Nurse Education in Practice [Internet]. 2021 Jul 1;54:103111. Available from: pmid:34118778
  27. 27. Moore K, Crăciun G. Fear of missing out and personality as predictors of social networking sites usage: the Instagram case. Psychological Reports [Internet]. 2021;124(4):1761–87. Available from: pmid:32659168
  28. 28. Al-Jallad MSY, Radwan AF. Exploring social media fatigue among youth in the United Arab Emirates. Journal of Print and Media Technology Research [Internet]. 2021 Nov 14;10(3):163–78. Available from: https://www.jpmtr.org/index.php/journal/article/view/28
  29. 29. Barry CT, Sidoti CL, Briggs SM, Reiter SR, Lindsey RA. Adolescent social media use and mental health from adolescent and parent perspectives. Journal of Adolescence [Internet]. 2017 Sep 5;61(1):1–11. Available from: pmid:28886571
  30. 30. Blanca MJ, Bendayan R. Spanish version of the Phubbing Scale: Internet addiction, Facebook intrusion, and fear of missing out as correlates. PubMed [Internet]. 2018 Nov 1;30(4):449–54. Available from: https://pubmed.ncbi.nlm.nih.gov/30353848
  31. 31. Bloemen N, De Coninck D. Social media and Fear of missing out in Adolescents: The role of Family Characteristics. Social Media + Society [Internet]. 2020 Oct 1;6(4):205630512096551. Available from:
  32. 32. Boustead R, Flack M. Moderated-mediation analysis of problematic social networking use: The role of anxious attachment orientation, fear of missing out and satisfaction with life. Addictive Behaviors [Internet]. 2021 Aug 1;119:106938. Available from: pmid:33845255
  33. 33. Casale S, Rugai L, Fioravanti G. Exploring the role of positive metacognitions in explaining the association between the fear of missing out and social media addiction. Addictive Behaviors [Internet]. 2018 Oct 1;85:83–7. Available from: pmid:29864680
  34. 34. Chen K, Cheung HL. Unlocking the power of ephemeral content: The roles of motivations, gratification, need for closure, and engagement. Computers in Human Behavior [Internet]. 2019 Aug 1;97:67–74. Available from:
  35. 35. Classen B, Wood JK, Davies P. Social network sites, fear of missing out, and psychosocial correlates. Cyberpsychology [Internet]. 2020 Aug 10;14(3). Available from:
  36. 36. Durak H, Seferoğlu SS. Antecedents of social media usage status: Examination of predictiveness of digital literacy, academic performance, and fear of missing out variables. Social Science Quarterly [Internet]. 2020 Mar 20;101(3):1056–74. Available from:
  37. 37. Gugushvili N, Täht K, Rozgonjuk D, Raudlam M, Ruiter R a. C, Verduyn P. Two dimensions of problematic smartphone use mediate the relationship between fear of missing out and emotional well-being. Cyberpsychology [Internet]. 2020 May 13;14(2). Available from:
  38. 38. Handa M, Ahuja P. Disconnect to detox: a study of smartphone addiction among young adults in India. Young Consumers: Insight and Ideas for Responsible Marketers [Internet]. 2020 Apr 25;21(3):273–87. Available from:
  39. 39. Lee KH, Lin CH, Tsao J, Hsieh LF. Cross-Sectional study on relationships among FOMO, social influence, positive outcome expectancy, Refusal Self-Efficacy and SNS usage. International Journal of Environmental Research and Public Health [Internet]. 2020 Aug 14;17(16):5907. Available from: pmid:32823977
  40. 40. Lenhard, Lenhard. Computation of different effect sizes like d, f, r and transformation of different effect sizes: Psychometrica [Internet]. Computation of Effect Sizes. 2022. https://www.psychometrica.de/effect_size.html
  41. 41. Lipsey MW, Wilson DB. Practical Meta-Analysis. Vol. 49. SAGE Publications, Inc; 2000.
  42. 42. Liu C, Ma J. Social support through online social networking sites and addiction among college students: The mediating roles of fear of missing out and problematic smartphone use. Current Psychology [Internet]. 2018 Nov 22;39(6):1892–9. Available from:
  43. 43. Marengo D, Settanni M, Fabris MA, Longobardi C. Alone, together: Fear of missing out mediates the link between peer exclusion in WhatsApp classmate groups and psychological adjustment in early-adolescent teens. Journal of Social and Personal Relationships [Internet]. 2021 Feb 11;38(4):1371–9. Available from:
  44. 44. Müller SM, Wegmann E, Stolze D, Brand M. Maximizing social outcomes? Social zapping and fear of missing out mediate the effects of maximization and procrastination on problematic social networks use. Computers in Human Behavior [Internet]. 2020 Jun 1;107:106296. Available from:
  45. 45. Patel V, Chaudhary P, Kumar P, Vasavada DA, Tiwari D. A study of correlates of social networking site addiction among the undergraduate health professionals. Asian Journal of Social Health and Behavior [Internet]. 2021 Jan 1;4(1):30. Available from:
  46. 46. Pontes HM, Taylor M, Stavropoulos V. Beyond “Facebook Addiction”: The Role of Cognitive-Related Factors and Psychiatric Distress in social networking site addiction. Cyberpsychology, Behavior, and Social Networking [Internet]. 2018 Apr 1;21(4):240–7. Available from: pmid:29589972
  47. 47. Quaglieri A, Biondi S, Roma P, Varchetta M, Fraschetti A, Burrai J, et al. From Emotional (Dys)Regulation to Internet Addiction: A Mediation Model of Problematic Social Media Use among Italian Young Adults. Journal of Clinical Medicine [Internet]. 2021 Dec 30;11(1):188. Available from: pmid:35011929
  48. 48. Reyes MES, Marasigan JP, Gonzales HJQ, Hernandez KLM, Medios MAO, Cayubit RFO. Fear of missing out and its link with social media and problematic Internet use among Filipinos. North American Journal of Psychology [Internet]. 2018 Dec 1;20(3):503. Available from: https://psycnet.apa.org/record/2018-59228-003
  49. 49. Röttinger D, Bischof G, Brandt D, Bischof A, Orlowski S, Besser B, et al. Dispositional and online-specific Fear of Missing Out are associated with the development of IUD symptoms in different internet applications. Journal of Behavioral Addictions [Internet]. 2021 Oct 5;10(3):747–58. Available from: pmid:34534104
  50. 50. Rozgonjuk D, Elhai JD, Ryan T, Scott GG. Fear of missing out is associated with disrupted activities from receiving smartphone notifications and surface learning in college students. Computers & Education [Internet]. 2019 Oct 1;140:103590. Available from:
  51. 51. Ruscio J. A probability-based measure of effect size: Robustness to base rates and other factors. Psychological Methods [Internet]. 2008 Jan 1;13(1):19–30. Available from: pmid:18331151
  52. 52. Scott H, Woods H. Fear of missing out and sleep: Cognitive behavioural factors in adolescents’ nighttime social media use. Journal of Adolescence [Internet]. 2018 Jul 20;68(1):61–5. Available from: pmid:30031979
  53. 53. Servidio R. Self-control and problematic smartphone use among Italian University students: The mediating role of the fear of missing out and of smartphone use patterns. Current Psychology [Internet]. 2019 Jul 18;40(8):4101–11. Available from:
  54. 54. Sha P, Sariyska R, Riedl R, Lachmann B, Montag C. Linking Internet Communication and Smartphone Use Disorder by taking a closer look at the Facebook and WhatsApp applications. Addictive Behaviors Reports [Internet]. 2019 Jun 1;9:100148. Available from: pmid:31193857
  55. 55. Świątek AH, Szczęśniak M, Bielecka G. Trait anxiety and social media fatigue: fear of missing out as a mediator. Psychology Research and Behavior Management [Internet]. 2021 Sep 1;Volume 14:1499–507. Available from: pmid:34616190
  56. 56. Tandon A, Dhir A, Talwar S, Kaur P, Mäntymäki M. Dark consequences of social media-induced fear of missing out (FoMO): Social media stalking, comparisons, and fatigue. Technological Forecasting and Social Change [Internet]. 2021 Oct 1;171:120931. Available from:
  57. 57. Tandon A, Kaur P, Dhir A, Mäntymäki M. Sleepless due to social media? Investigating problematic sleep due to social media and social media sleep hygiene. Computers in Human Behavior [Internet]. 2020 Dec 1;113:106487. Available from:
  58. 58. Tuğtekin U, Tuğtekin EB, Kurt AA, Demir K. Associations between fear of missing out, problematic smartphone use, and social networking services fatigue among young adults. Social Media + Society [Internet]. 2020 Oct 1;6(4):205630512096376. Available from:
  59. 59. Vally Z, Alghraibeh AM, Elhai JD. Severity of depression and anxiety in relation to problematic smartphone use in the United Arab Emirates: The mediational roles of rumination and fear of missing out. Human Behavior and Emerging Technologies [Internet]. 2021 Mar 31;3(3):423–31. Available from:
  60. 60. Wang J, Wang P, Yang X, Zhang G, Wang X, Zhao F, et al. Fear of missing out and procrastination as mediators between sensation seeking and adolescent smartphone addiction. International Journal of Mental Health and Addiction [Internet]. 2019 Jun 26;17(4):1049–62. Available from:
  61. 61. Weaver JL, Swank JM. An examination of college students’ social media use, fear of missing out, and mindful attention. Journal of College Counseling [Internet]. 2021 Jun 30;24(2):132–45. Available from:
  62. 62. Yang H, Liu B, Fang J. Stress and problematic smartphone use severity: smartphone use frequency and fear of missing out as mediators. Frontiers in Psychiatry [Internet]. 2021 Jun 1;12. Available from: pmid:34140901
  63. 63. Yin FS, Liu ML, Lin C. Forecasting the continuance intention of social networking sites: Assessing privacy risk and usefulness of technology. Technological Forecasting and Social Change [Internet]. 2015 Oct 1;99:267–72. Available from:
  64. 64. Buglass SL, Binder JF, Betts LR, Underwood J. Motivators of online vulnerability: The impact of social network site use and FOMO. Computers in Human Behavior [Internet]. 2017 Jan 1;66:248–55. Available from:
  65. 65. Elhai JD, Yang H, Montag C. Anxiety and stress severity are related to greater fear of missing out on rewarding experiences: A latent profile analysis. PsyCh Journal [Internet]. 2021 May 12;10(5):688–97. Available from: pmid:33977668
  66. 66. Milyavskaya M, Saffran M, Hope N, Koestner R. Fear of missing out: prevalence, dynamics, and consequences of experiencing FOMO. Motivation and Emotion [Internet]. 2018 Mar 17;42(5):725–37. Available from:
  67. 67. Lo Coco G, Salerno L, Franchina V, La Tona A, Di Blasi M, Giordano C. Examining bi-directionality between Fear of Missing Out and problematic smartphone use. A two-wave panel study among adolescents. Addictive Behaviors [Internet]. 2020 Jul 1;106:106360. Available from: pmid:32135397
  68. 68. Wegmann E, Oberst Ú, Stodt B, Brand M. Online-specific fear of missing out and Internet-use expectancies contribute to symptoms of Internet-communication disorder. Addictive Behaviors Reports [Internet]. 2017 Jun 1;5:33–42. Available from: pmid:29450225
  69. 69. Fúster H, Chamarro A, Oberst Ú. Fear of Missing Out, online social networking and mobile phone addiction: A latent profile approach. Aloma [Internet]. 2017 Oct 13;35(1):22–30. Available from:
  70. 70. Alt D. Students’ Wellbeing, Fear of Missing out, and Social Media Engagement for Leisure in Higher Education Learning Environments. Current Psychology [Internet]. 2018;37(1):128–38. Available from:
  71. 71. Duan W, He C, Tang X. Why Do People Browse and Post on WeChat Moments? Relationships among Fear of Missing Out, Strategic Self-Presentation, and Online Social Anxiety. Cyberpsychology, Behavior, and Social Networking [Internet]. 2020 Oct 1;23(10):708–14. Available from: pmid:32845716
  72. 72. Brailovskaia J, Stirnberg J, Rozgonjuk D, Margraf J, Elhai JD. From low sense of control to problematic smartphone use severity during Covid-19 outbreak: The mediating role of fear of missing out and the moderating role of repetitive negative thinking. PLOS ONE [Internet]. 2021 Dec 22;16(12):e0261023. Available from: pmid:34936651
  73. 73. Qutishat M, Sharour LA. Relationship between fear of missing out and academic performance among Omani University students: A Descriptive correlation study. Oman Medical Journal [Internet]. 2019 Sep 17;34(5):404–11. Available from: pmid:31555416
  74. 74. Dhir A, Yossatorn Y, Kaur P, Chen S. Online social media fatigue and psychological wellbeing—A study of compulsive use, fear of missing out, fatigue, anxiety and depression. International Journal of Information Management [Internet]. 2018 Jun 1;40:141–52. Available from:
  75. 75. Tomczyk L, Selmanagic-Lizde E. Fear of Missing Out (FOMO) among youth in Bosnia and Herzegovina—Scale and selected mechanisms. Children and Youth Services Review [Internet]. 2018 May 1;88:541–9. Available from:
  76. 76. Zhou B. Fear of missing out, feeling of acceleration, and being permanently online: a survey study of university students’ use of mobile apps in China. Chinese Journal of Communication [Internet]. 2018 Dec 22;12(1):66–83. Available from:
  77. 77. Franchina V, Vanden Abeele M, Van Rooij AJ, Lo Coco G, De Marez L. Fear of Missing Out as a Predictor of Problematic Social Media Use and Phubbing Behavior among Flemish Adolescents. International Journal of Environmental Research and Public Health [Internet]. 2018 Oct 22;15(10):2319. Available from: pmid:30360407
  78. 78. Schmuck D. Following Social Media Influencers in Early Adolescence: Fear of Missing Out, Social Well-Being and Supportive Communication with Parents. Journal of Computer-Mediated Communication [Internet]. 2021 Sep 1;26(5):245–64. Available from:
  79. 79. Koessmeier C, Büttner OB. Why are we distracted by social media? Distraction situations and strategies, reasons for distraction, and individual differences. Frontiers in Psychology [Internet]. 2021 Dec 2;12. Available from: pmid:34925123
  80. 80. Alt D. College students’ academic motivation, media engagement and fear of missing out. Computers in Human Behavior [Internet]. 2015 Aug 1;49:111–9. Available from:
  81. 81. Alt D. Students’ social media engagement and fear of missing out (FoMO) in a diverse classroom. Journal of Computing in Higher Education [Internet]. 2017 May 24;29(2):388–410. Available from:
  82. 82. Hayran C, Anik L. Well-Being and Fear of Missing Out (FOMO) on Digital Content in the Time of COVID-19: A Correlational Analysis among University Students. International Journal of Environmental Research and Public Health [Internet]. 2021 Feb 18;18(4):1974. Available from: pmid:33670639
  83. 83. Elhai JD, Levine JC, Alghraibeh AM, Alafnan AA, Aldraiweesh AA, Hall BJ. Fear of missing out: Testing relationships with negative affectivity, online social engagement, and problematic smartphone use. Computers in Human Behavior [Internet]. 2018 Dec 1;89:289–98. Available from:
  84. 84. Can G, Satıcı SA. Adaptation of fear of missing out scale (FoMOs): Turkish version validity and reliability study. Psicologia: Reflexão E Crítica [Internet]. 2019 Jan 22;32(1). Available from: pmid:32026206
  85. 85. Gil , Chamarro, Oberst. PO-14: Addiction to online social networks: A question of “Fear of Missing Out”? Journal of Behavioral Addictions [Internet]. 2015;4(S1). Available from: https://link.gale.com/apps/doc/A457602805/AONE?u=anon~1adc4c76&sid=googleScholar&xid=35749bc7
  86. 86. Al-Menayes JJ. The Fear of Missing out Scale: Validation of the Arabic Version and Correlation with Social Media Addiction. International Journal of Applied Psychology [Internet]. 2016 Jan 1;6(2):41–6. Available from: http://www.sapub.org/global/showpaperpdf.aspx?doi=10.5923/j.ijap.20160602.04
  87. 87. Casale S, Fioravanti G. Factor structure and psychometric properties of the Italian version of the fear of missing out scale in emerging adults and adolescents. Addictive Behaviors [Internet]. 2020 Mar 1;102:106179. Available from: pmid:31704432
  88. 88. Li Y, Huang YT, Dou K. Validation and psychometric properties of the Chinese version of the fear of missing out scale. International Journal of Environmental Research and Public Health [Internet]. 2021 Sep 20;18(18):9896. Available from: pmid:34574819
  89. 89. Koufteros X, Babbar S, Kaighobadi M. A paradigm for examining second-order factor models employing structural equation modeling. International Journal of Production Economics [Internet]. 2009 Aug 1;120(2):633–52. Available from:
  90. 90. Oberst Ú, Wegmann E, Stodt B, Brand M, Lusar AC. Negative consequences from heavy social networking in adolescents: The mediating role of fear of missing out. Journal of Adolescence [Internet]. 2016 Dec 27;55(1):51–60. Available from: pmid:28033503
  91. 91. Stead H, Bibby PA. Personality, fear of missing out and problematic internet use and their relationship to subjective well-being. Computers in Human Behavior [Internet]. 2017 Nov 1;76:534–40. Available from:
  92. 92. Deniz M. Fear of missing out (FoMO) mediate relations between social self-efficacy and life satisfaction. Psicologia: Reflexão E Crítica [Internet]. 2021 Aug 23;34(1). Available from: pmid:34424439
  93. 93. Lin L, Wang X, Li Q, Xia B, Chen P, Wang W. The influence of interpersonal sensitivity on smartphone Addiction: A Moderated Mediation model. Frontiers in Psychology [Internet]. 2021 Jul 22;12. Available from: pmid:34366988
  94. 94. Härpfer K, Spychalski D, Kathmann N, Riesel A. Diverging patterns of EEG alpha asymmetry in anxious apprehension and anxious arousal. Biological Psychology [Internet]. 2021 May 1;162:108111. Available from: pmid:33961931
  95. 95. Elhai JD, Gallinari EF, Rozgonjuk D, Yang H. Depression, anxiety and fear of missing out as correlates of social, non-social and problematic smartphone use. Addictive Behaviors [Internet]. 2020 Jun 1;105:106335. Available from: pmid:32062337
  96. 96. Heller W, Nitschke JB, Etienne MA, Miller GA. Patterns of regional brain activity differentiate types of anxiety. Journal of Abnormal Psychology [Internet]. 1997 Aug 1;106(3):376–85. Available from: pmid:9241939
  97. 97. Nitschke JB, Heller W, Palmieri PA, Miller GA. Contrasting patterns of brain activity in anxious apprehension and anxious arousal. Psychophysiology [Internet]. 1999 Sep 1;36(5):628–37. Available from: pmid:10442031
  98. 98. Hayran C, Anik L, Gürhan-Canli Z. Feeling of missing out (FOMO) and its marketing implications [Internet]. Marketing Science Institute; 2016. https://thearf-org-unified-admin.s3.amazonaws.com/MSI/2020/06/MSI_Report_16-131.pdf
  99. 99. Tsai HYS, Hsu PJ, Chang CL, Huang CC, Ho HF, LaRose R. High tension lines: Negative social exchange and psychological well-being in the context of instant messaging. Computers in Human Behavior [Internet]. 2019 Apr 1;93:326–32. Available from:
  100. 100. Reer F, Tang WY, Quandt T. Psychosocial well-being and social media engagement: The mediating roles of social comparison orientation and fear of missing out. New Media & Society [Internet]. 2019 Jan 20;21(7):1486–505. Available from:
  101. 101. Wang P, Wang X, Nie J, Zeng P, Liu K, Wang J, et al. Envy and problematic smartphone use: The mediating role of FOMO and the moderating role of student-student relationship. Personality and Individual Differences [Internet]. 2019 Aug 1;146:136–42. Available from:
  102. 102. Yin L, Wang P, Nie J, Guo J, Feng J. Social networking sites addiction and FoMO: The mediating role of envy and the moderating role of need to belong. Current Psychology [Internet]. 2019 Jul 2;40(8):3879–87. Available from:
  103. 103. Baker ZG, Krieger H, LeRoy AS. Fear of missing out: Relationships with depression, mindfulness, and physical symptoms. Translational Issues in Psychological Science [Internet]. 2016 Sep 1;2(3):275–82. Available from:
  104. 104. Hayran C, Anik L, Gürhan-Canlı Z. A threat to loyalty: Fear of missing out (FOMO) leads to reluctance to repeat current experiences. PLOS ONE [Internet]. 2020 Apr 30;15(4):e0232318. Available from: pmid:32353059
  105. 105. Çoşkun S, K Muslu G. Investigation of problematic mobile phones use and fear of missing out (FOMO) level in adolescents. Community Mental Health Journal [Internet]. 2019 Jun 17;55(6):1004–14. Available from: pmid:31209716
  106. 106. Chotpitayasunondh V, Douglas KM. How “phubbing” becomes the norm: The antecedents and consequences of snubbing via smartphone. Computers in Human Behavior [Internet]. 2016 Oct 1;63:9–18. Available from:
  107. 107. Sheldon P, Antony MG, Sykes B. Predictors of Problematic Social Media Use: Personality and Life-Position Indicators. Psychological Reports [Internet]. 2020 Jun 24;124(3):1110–33. Available from: pmid:32580682
  108. 108. Błachnio A, Przepiórka A. Facebook intrusion, fear of missing out, narcissism, and life satisfaction: A cross-sectional study. Psychiatry Research [Internet]. 2018 Jan 1;259:514–9. Available from: pmid:29154204
  109. 109. Neumann D. Fear of missing out. The International Encyclopedia of Media Psychology [Internet]. 2020 Jun 13;1–9. Available from:
  110. 110. Dossey L. FOMO, digital dementia, and our dangerous experiment. Explore-the Journal of Science and Healing [Internet]. 2014 Mar 1;10(2):69–73. Available from: pmid:24607071
  111. 111. Fioravanti G, Casale S, Benucci SB, Prostamo A, Falone A, Ricca V, et al. Fear of missing out and social networking sites use and abuse: A meta-analysis. Computers in Human Behavior [Internet]. 2021 Sep 1;122:106839. Available from:
  112. 112. Adams SK, Williford DN, Vaccaro A, Kisler TS, Francis A, Newman BM. The young and the restless: Socializing trumps sleep, fear of missing out, and technological distractions in first-year college students. International Journal of Adolescence and Youth [Internet]. 2016;22(3):337–48. Available from:
  113. 113. Riordan BC, Flett J a. M, Hunter J, Scarf D, Conner TS. Fear of missing out (FoMO): the relationship between FoMO, alcohol use, and alcohol-related consequences in college students. Journal of Psychiatry and Brain Functions [Internet]. 2015 Jan 1;2(1):9. Available from:
  114. 114. Zhang Z, Jiménez FR, Cicala JE. Fear Of Missing Out Scale: A self‐concept perspective. Psychology & Marketing [Internet]. 2020 Sep 13;37(11):1619–34. Available from:
  115. 115. Fisher C, Park S, Lee JY, Holland K, John E. Older people’s news dependency and social connectedness. Media International Australia [Internet]. 2021 Apr 8;1329878X2110064. Available from:
  116. 116. Feick L, Price LL. The Market Maven: a diffuser of marketplace information. Journal of Marketing [Internet]. 1987 Jan 1;51(1):83. Available from:
  117. 117. Zhang J, Lee W. Exploring the impact of cultural value orientations on market mavenism and opinion leadership. Journal of Promotion Management [Internet]. 2013 Nov 1;19(5):534–55. Available from:
  118. 118. Balta S, Emirtekin E, Kırcaburun K, Griffiths MD. Neuroticism, trait fear of missing out, and phubbing: the mediating role of state fear of missing out and problematic Instagram use. International Journal of Mental Health and Addiction [Internet]. 2018 Jul 12;18(3):628–39. Available from:
  119. 119. Blackwell D, Leaman C, Tramposch R, Osborne C, Liss M. Extraversion, neuroticism, attachment style and fear of missing out as predictors of social media use and addiction. Personality and Individual Differences [Internet]. 2017 Oct 1;116:69–72. Available from:
  120. 120. Hadlington L, Scase MO. End-user frustrations and failures in digital technology: exploring the role of Fear of Missing Out, Internet addiction and personality. Heliyon [Internet]. 2018 Nov 1;4(11):e00872. Available from: pmid:30426098
  121. 121. Li L, Griffiths MD, Mei S, Niu Z. Fear of missing out and smartphone addiction mediates the relationship between positive and negative affect and sleep quality among Chinese university students. Frontiers in Psychiatry [Internet]. 2020 Aug 27;11. Available from: pmid:33192635
  122. 122. Wegmann E, Brandtner A, Brand M. Perceived strain due to COVID-19-Related restrictions mediates the effect of social needs and fear of missing out on the risk of a problematic use of social networks. Frontiers in Psychiatry [Internet]. 2021 Apr 23;12. Available from: pmid:33967850
  123. 123. Dempsey AE, O’Brien KD, Tiamiyu MF, Elhai JD. Fear of missing out (FoMO) and rumination mediate relations between social anxiety and problematic Facebook use. Addictive Behaviors Reports [Internet]. 2019 Jun 1;9:100150. Available from: pmid:31193746
  124. 124. Riordan BC, Cody L, Flett J a. M, Conner TS, Hunter J, Scarf D. The development of a single item FoMO (Fear of Missing Out) scale. Current Psychology [Internet]. 2018 Mar 12;39(4):1215–20. Available from:
  125. 125. Elhai JD, Yang H, Fang J, Bai X, Hall BJ. Depression and anxiety symptoms are related to problematic smartphone use severity in Chinese young adults: Fear of missing out as a mediator. Addictive Behaviors [Internet]. 2020 Feb 1;101:105962. Available from: pmid:31030950
  126. 126. Fitz NS, Kushlev K, Jagannathan R, Lewis T, Paliwal D, Ariely D. Batching smartphone notifications can improve well-being. Computers in Human Behavior [Internet]. 2019 Dec 1;101:84–94. Available from:
  127. 127. Aygar H, Göktaş S, Zencirci SA, Alaiye M, Önsüz MF, Metintaş S. Association between fear of missing out in social media and problematic internet use in university students. Düşünen Adam [Internet]. 2020 Jan 1; Available from:
  128. 128. Fabris MA, Marengo D, Longobardi C, Settanni M. Investigating the links between fear of missing out, social media addiction, and emotional symptoms in adolescence: The role of stress associated with neglect and negative reactions on social media. Addictive Behaviors [Internet]. 2020 Jul 1;106:106364. Available from: pmid:32145495
  129. 129. Brown L, Kuss DJ. Fear of missing out, mental wellbeing, and social connectedness: A Seven-Day Social Media Abstinence Trial. International Journal of Environmental Research and Public Health [Internet]. 2020 Jun 24;17(12):4566. Available from: pmid:32599962
  130. 130. Eide TA, Aarestad SH, Andreassen CS, Bilder RM, Pallesen S. Smartphone restriction and its effect on subjective withdrawal related scores. Frontiers in Psychology [Internet]. 2018 Aug 13;9. Available from: pmid:30150959
  131. 131. Hunt MG, Marx R, Lipson C, Young J. No more FOMO: Limiting social media decreases loneliness and depression. Journal of Social and Clinical Psychology [Internet]. 2018 Dec 1;37(10):751–68. Available from:
  132. 132. Rogers AP, Barber LK. Addressing FoMO and telepressure among university students: Could a technology intervention help with social media use and sleep disruption? Computers in Human Behavior [Internet]. 2019 Apr 1;93:192–9. Available from:
  133. 133. Hato. (Compulsive) mobile phone checking behavior out of a fear of missing out: Development [Internet]. Tilburg University; 2013. https://arno.uvt.nl/show.cgi?fid=130541
  134. 134. Deci EL, Ryan RM. Handbook of Self-determination Research. University Rochester Press; 2004.
  135. 135. Raymaekers K, Luyckx K, Moons P. A guide to improve your causal inferences from observational data. European Journal of Cardiovascular Nursing [Internet]. 2020 Dec 1;19(8):757–62. Available from: pmid:33040589
  136. 136. Deci EL, Ryan RM. The “What” and “Why” of goal pursuits: human needs and the Self-Determination of behavior. Psychological Inquiry [Internet]. 2000 Oct 1;11(4):227–68. Available from:
  137. 137. Varchetta M, Fraschetti A, Mari E, Giannini AM. Social Media Addiction, Fear of Missing Out (FoMO) and Online Vulnerability in university students. Revista Digital De Investigación En Docencia Universitaria [Internet]. 2020 Jun 22;14(1):e1187. Available from:
  138. 138. Kardefelt-Winther D. A conceptual and methodological critique of internet addiction research: Towards a model of compensatory internet use. Computers in Human Behavior [Internet]. 2014 Feb 1;31:351–4. Available from:
  139. 139. Wolniewicz CA, Tiamiyu MF, Weeks JW, Elhai JD. Problematic smartphone use and relations with negative affect, fear of missing out, and fear of negative and positive evaluation. Psychiatry Research [Internet]. 2018 Apr 1;262:618–23. Available from: pmid:28982630
  140. 140. Brand M, Young K, Laier C, Wölfling K, Potenza MN. Integrating psychological and neurobiological considerations regarding the development and maintenance of specific Internet-use disorders: An Interaction of Person-Affect-Cognition-Execution (I-PACE) model. Neuroscience & Biobehavioral Reviews [Internet]. 2016 Dec 1;71:252–66. Available from: pmid:27590829
  141. 141. Wolniewicz CA, Rozgonjuk D, Elhai JD. Boredom proneness and fear of missing out mediate relations between depression and anxiety with problematic smartphone use. Human Behavior and Emerging Technologies [Internet]. 2019 Jul 12;2(1):61–70. Available from:
  142. 142. Elhai JD, Yang H, Rozgonjuk D, Montag C. Using machine learning to model problematic smartphone use severity: The significant role of fear of missing out. Addictive Behaviors [Internet]. 2020 Apr 1;103:106261. Available from: pmid:31901886
  143. 143. Rozgonjuk D, Sindermann C, Elhai JD, Montag C. Fear of Missing Out (FoMO) and social media’s impact on daily-life and productivity at work: Do WhatsApp, Facebook, Instagram, and Snapchat Use Disorders mediate that association? Addictive Behaviors [Internet]. 2020 Nov 1;110:106487. Available from: pmid:32674020
  144. 144. Festinger L. A theory of social comparison processes. Human Relations [Internet]. 1954 May 1;7(2):117–40. Available from:
  145. 145. Valkenburg PM, Peter J. The differential susceptibility to media Effects model. Journal of Communication [Internet]. 2013 Mar 7;63(2):221–43. Available from:
  146. 146. Salvucci DD, Taatgen N. Threaded cognition: An integrated theory of concurrent multitasking. Psychological Review [Internet]. 2008 Jan 1;115(1):101–30. Available from: pmid:18211187
  147. 147. D’Lima P, Higgins A. Social media engagement and Fear of Missing Out (FOMO) in primary school children. Educational Psychology in Practice [Internet]. 2021 Jul 3;37(3):320–38. Available from:
  148. 148. Marino C, Canale N, Melodia F, Spada MM, Vieno A. The Overlap Between Problematic Smartphone Use and Problematic Social Media Use: a Systematic Review. Current Addiction Reports [Internet]. 2021 Oct 7;8(4):469–80. Available from:
  149. 149. Fumagalli E, Dolmatzian MB, Shrum LJ. Centennials, FOMO, and Loneliness: An investigation of the impact of Social Networking and Messaging/VOIP apps usage during the initial stage of the coronavirus pandemic. Frontiers in Psychology [Internet]. 2021 Feb 9;12. Available from: pmid:33633646
  150. 150. Sela Y, Zach M, Amichay-Hamburger Y, Mishali M, Omer H. Family environment and problematic internet use among adolescents: The mediating roles of depression and Fear of Missing Out. Computers in Human Behavior [Internet]. 2020 May 1;106:106226. Available from:
  151. 151. Shoval D, Tal N, Tzischinsky O. Relationship of smartphone use at night with sleep quality and psychological well-being among healthy students: A pilot study. Sleep Health [Internet]. 2020 Aug 1;6(4):495–7. Available from: pmid:32336603
  152. 152. Leung AYM, Law W, Liang YY, Au ACL, L Cheng, Ng HKS. What Explains the Association between Usage of Social Networking Sites (SNS) and Depression Symptoms? The Mediating Roles of Self-Esteem and Fear of Missing Out. International Journal of Environmental Research and Public Health [Internet]. 2021 Apr 8;18(8):3916. Available from: pmid:33917894
  153. 153. A Akyol N, A Ergin D, Krettmann AK, Essau CA. Is the relationship between problematic mobile phone use and mental health problems mediated by fear of missing out and escapism? Addictive Behaviors Reports [Internet]. 2021 Dec 1;14:100384. Available from: pmid:34938842
  154. 154. Elphinston RA, Noller P. Time to face it! Facebook intrusion and the implications for romantic jealousy and relationship satisfaction. Cyberpsychology, Behavior, and Social Networking [Internet]. 2011 Nov 1;14(11):631–5. Available from: pmid:21548798
  155. 155. Kross E, Verduyn P, Sheppes G, Costello C, Jonides J, Ybarra O. Social Media and Well-Being: Pitfalls, progress, and next steps. Trends in Cognitive Sciences [Internet]. 2021 Jan 1;25(1):55–66. Available from: pmid:33187873
  156. 156. Lin SC, Jian ET. Effects of personality traits concerning media use decisions on fear of missing out and social media use behavior. Behavioral Sciences [Internet]. 2022 Nov 18;12(11):460. Available from: pmid:36421756
  157. 157. Mao J, Zhang B. Differential Effects of Active Social Media use on general Trait and Online-Specific State-FOMO: Moderating Effects of Passive social Media use. Psychology Research and Behavior Management [Internet]. 2023 Apr 1;Volume 16:1391–402. Available from: pmid:37124075
  158. 158. Garrido CC, Navarro‐González D, Lorenzo‐Seva U, Ferrando PJ. Multidimensional or essentially unidimensional? A multi-faceted factor-analytic approach for assessing the dimensionality of tests and items. PubMed [Internet]. 2019 Nov 1;31(4):450–7. Available from: https://pubmed.ncbi.nlm.nih.gov/31634091
  159. 159. Hamaker EL. The within-between dispute in cross-lagged panel research and how to move forward. Psychological Methods [Internet]. 2023 Oct 30; Available from: pmid:37902677
  160. 160. Akbari M, Seydavi M, Palmieri S, Mansueto G, Caselli G, Spada MM. Fear of missing out (FoMO) and internet use: A comprehensive systematic review and meta-analysis. Journal of Behavioral Addictions [Internet]. 2021 Dec 31;10(4):879–900. Available from: pmid:34935633
  161. 161. Deci EL, Ryan RM. Intrinsic Motivation and Self-Determination in human behavior [Internet]. Springer eBooks. 1985.