Fear of Missing Out: An Antecedent of Online Fan Engagement of Sport Teams’ Social Media

Fear of Missing Out

Fear of Missing Out (FoMO) is defined as “a pervasive apprehension that others might be having rewarding experiences from which one is absent” (Przybylski et al., 2013, p. 1841). Due to FoMO, individuals are likely to feel anxious and socially excluded when they fear missing out on social relationships (Blackwell et al., 2017). Self-Determination Theory (SDT; Deci & Ryan, 1985) is the theoretical foundation of the study used to explain the relationships between FoMO and behavioral outcomes. Baumeister and Tice (1990) described the fear of being excluded from social groups as a fundamental and innate anxiety caused by actual or perceived exclusion from crucial social gatherings or events. SDT provides a framework to describe the human motivation for predicting many relevant outcomes, such as individuals' psychological well-being and mental health.

According to SDT, individuals behave to satisfy three primary psychological needs, which are competence, relatedness, and autonomy, and psychological experience in activities is defined by the satisfaction or unsatisfaction of the three needs (Deci & Ryan, 1985; 2008). Based on SDT, missing out on a favorable or popular experience that others are enjoying, may lead to a sense of ‘incompetence’ for restricting one’s knowledge, social status, and adequacy in society (Abel et al., 2016). For example, missing favorable sport games, such as Super Bowl and World Cup soccer final matches, may lead to individuals' sense of ‘incompetence’ because of the lack of knowledge of the match. The lack of 'relatedness' also causes individuals concerns, such as social anxiety, ostracism, and exclusion from their social group (Abel et al., 2016; Beyens et al., 2016). Individuals who experience FoMO often turn to social media as a way to alleviate anxiety, accessing social media is a great alternative to relieve anxiety since social media channels provide social connections and involvement of the social group, which represent the 'relatedness' of SDT. These fears related to ‘competence’ and 'relatedness' can also externally motivate individuals to participate in the experience, potentially limiting their ‘autonomy’ (Alt, 2015). Thus, FoMO can serve as an antecedent of feelings, thoughts, and certain behaviors that are energized by external pressure according to SDT.

In other words, FoMO refers to an individual’s sense of deficit and inherent anxiety caused by social exclusion from social gatherings (Blackwell et al., 2017; Dogan, 2019). In the online environment, where the use of smartphones or the internet is readily accessible, prior research suggests that FoMO is associated with negative affectivity variables such as depression, anxiety severity, and low self-esteem (Buglass et al., 2017; Elhai et al., 2016, 2018). Younger generations who experience FoMO are more likely to use social media channels (Alt, 2015; Przybylski et al., 2013), which has been linked to negative outcomes such as internet addiction (Stead & Bibby, 2017), nighttime social media use (Blackwell et al., 2017; Scott and woods, 2018), and poor sleep quality and depression (Woods & Scott, 2016). However, in the context of sports, FoMO is positively associated with sports media consumption and the use of social media channels. Kim et al. (2020) found that FoMO is positively related to watching sports games via media since FoMO is regarded as an extrinsic motivator. Yim et al. (2021) also demonstrated that individuals who experience FoMO attend, watch, and follow their favorite sports teams' games to avoid missing anything and to avoid negative social evaluations from their peers or family.

FoMO, which is an external motivation, leads to various psychological and behavioral outcomes. The desire to belong is a natural and primary motivation that humans possess (Baumeister & Leary, 1995), and people seek belongingness to social groups and interact to others to satisfy the sense of belonging, which connects to higher levels of social media involvement (Vale & Fernandes, 2018). In addition, FoMO leads to CPA for the constant connection to social groups, and this fear can directly connect to fan behaviors. According to a study by AdColony in 2021, 59% of Super Bowl viewers browsed the internet on a second screen while watching the game on TV, and 43% of respondents browsed social media channels during the Super Bowl telecast to stay connected to others (Koltun, 2022). Previous studies have shown that individuals with FoMO are more likely to post on social media while watching mega sport events, such as the Olympics or the Super Bowl (Conlin et al., 2016). Additionally, sports fans use a second screen to express their emotions, such as joy, anticipation, anger, and fear, in real-time using social media (Yu & Wang, 2015), and they can enjoy sports more when using social media while watching sport on screens (Rubenking & Lewis, 2016; Smith et al., 2019) since they use multiple screens to receive game information and communicate with others (Elishar-Malka et al., 2021). Therefore, FoMO can serve as an external motivator that drives sport media consumption and the use of social media channels simultaneously.

Social Media Involvement

Social media is defined as “a group of Internet-based applications that build on the ideological and technological foundations of Web 2.0, and that allow the creation and exchange of User Generated Content” (Kaplan & Haenlein, 2010, p.61), and involvement is described as the extent of personal relevance to an object (Zaichkowsky, 1994). In previous studies, social media involvement has been presented with various terms, such as an individual’s attachment to social media (Van Meter et al., 2015) and psychological involvement with certain media (Tukachinsky, 2014). These studies commonly highlight the psychological relevance of social media and personal attachment to social media channels. Therefore, social media involvement can be operationalized as the extent of personal relevance of social media use to an individual.

In an era of increased digitalization, social media channels, such as Facebook, Instagram, and Twitter, provide digital media where people can keep in touch with their social groups (Franchina et al., 2018). In the context of sport, previous researchers have identified that social media channels could be utilized to interact with other stakeholders. For example, sport leagues, teams, and athletes operate various social media channels to interact with their fans, advertise endorsed products, and manage their brands (e.g., Brison et al., 2016; Thompson et al., 2018). Fans access these social media channels to directly connect with sports stars and other fans, share their thoughts, and post biased team-related content as expressions of fandom (Vale & Fernandes, 2018; Wann and Grieve., 2005; Yim et al., 2021). Additionally, accessing social media channels enhances fans' psychological status, such as their sense of belonging to a group, sense of self, and team identification (Stavros et al., 2014; Wang, 2013). Similarly, individuals can communicate through online discussions, instant messages, create threads, and contribute to digital communities via social media activities (Lim et al., 2013). Sport communication researchers have investigated how fans expanded their sport consumption via social media by utilizing second screens (Cunningham & Eastin, 2017; Smith et al., 2019; Voorveld & Viswanathan, 2014), which is connected to the CPA and online fan engagement of sport teams' social media.

Continuous Partial Attention

Continuous partial attention (CPA) is part of an umbrella term, multitasking (e.g., Bowman et al., 2010; Rose, 2010). Multitasking involves engaging in multiple tasks and is classified into three primary types: dual-tasking, rapid attention switching, and CPA (Wood & Zivcakova, 2015). Dual-tasking involves simultaneously performing two or more tasks and giving equal attention to each task (e.g., washing dishes while listening to music or talking with others while driving) (Appelbaum et al., 2008; Pashler, 2000). Rapid attention switching involves shifting focus among tasks while doing several tasks (Lau, 2017). For example, when an individual uses a laptop, they may give full attention to a specific task, such as reading e-books, and then rapidly switch their attention to another task, such as writing reports. In this case, it appears as though the two tasks are being done simultaneously, but the individual is actually giving full attention to one task at a time. However, continuous partial attention (CPA) involves giving partial attention to various tasks and doing them simultaneously (Firat, 2013a). Dual-tasking and rapid attention switching assume that individuals can focus on several tasks or a specific task (Appelbaum et al., 2008; Lau, 2017). However, these concepts are not relevant to watching sports and accessing social media channels because checking social media messages and watching sports cannot be done at the same time and require giving partial attention to both tasks simultaneously.

Among the three types of multitasking, the current study focuses on CPA as a behavioral response when individuals simultaneously browse and access social media while watching sport games on screens. CPA indicates the interactions and connections with more than two tasks while individuals miss the focus of anything, such as a student in class surfing the internet (Firat, 2013b). CPA is distinct from other forms of multitasking in terms of motives. Larkin and Fink (2016) found that when sport fans watch sport, they express CPA, which is different from multitasking generated from different motivations. Dual-tasking and rapid attention switching are motivated by the desire to be efficient and the success of performing two or more tasks simultaneously. In contrast, CPA is motivated not by the desire for productivity but by an unsatisfied desire for connectedness (Firat, 2013a).

Online Fan Engagement of Sport Teams’ Social Media Channels

Customer engagement behavior is defined as “A customer’s behavioral manifestations that have a brand or firm focus, beyond purchase, resulting from motivational drivers” (Van Doorn et al., 2010, p. 254). In previous literature, consumer engagement has been viewed as a crucial concept that is expected to present enhanced predictive and informative capabilities of significant consumer behavior outcomes, including brand loyalty and brand love (Carroll & Ahuvia, 2006; Hollebeek et al., 2014). The fan engagement of sport teams' social media channels can be explained by the Uses and Gratification Theory (UGT; Katz et al., 1973), which demonstrates why and how people actively utilize media channels to satisfy their needs and desires (Katz et al., 1973). Many motivation classifications, guided by UGT, have been developed to investigate the use of media for gratification, including social media. The well-known categorization is McQuail et al.'s (1972) four categories: diversion, personal relationships, personal identity, and surveillance. For instance, individuals use social media to escape problems or daily routines (diversion), maintain relationships with friends, relatives, and/or society (personal relationships), achieve self-fulfillment or self-enhancement (personal identity), and search for information (surveillance) (Courtois et al., 2009; Daugherty et al., 2008; Park et al., 2009). Numerous social media studies investigating users' motivations have utilized McQuail et al.'s (1972) four classifications. Researchers have highlighted the capacities of personal relationships (Boyd, 2008; Muntinga et al., 2011) and personal identity (Papacharissi, 2007) and which sub-categories of motivations are deeply related to FoMO. In addition, some unique uses and gratifications of social media related to FoMO were developed, such as maintaining relationships with others online (Sheldon, 2008) and expressing opinions online (Whiting & Williams, 2013). Therefore, individuals can gain a sense of belonging and connection with others by accessing social media channels.

In the current digital age, multiple social media channels such as Facebook, Instagram, and Twitter, and technological devices such as smartphones and tablets are available. Previous studies have indicated that sports teams have used social media to communicate with their fans (e.g., Gibbs et al., 2014; Kim & Hull, 2017; Pegoraro, 2010). Sports teams operate official websites to provide team-related content, such as news, photos, videos, and ticket and merchandise sales. However, even though sports teams' official websites provide fan engagement opportunities, fans directly access social media fan channels and engage with the team, athletes, and other fans because of its accessibility (Pegoraro, 2010). In this context, team webpage managers also provide links to the team’s social network channels to create fan communities. For instance, Real Madrid C.F. has over 34.33 million followers on Twitter, 88.8 million followers on Instagram, and 109.86 million followers on Facebook. Watanabe et al. (2016) found that Major League Baseball fans expressed greater interest in a team’s social media accounts, and Wang (2013) demonstrated that sports fans hold a favorable attitude toward social media channels when users understand how to use the channels and when the account provides game information. These examples illustrate that individuals are inclined to access social media channels to engage with their social groups.

Hypotheses Development

The literature review reveals that previous studies have established a strong link between FoMO and social media use (Blackwell et al., 2017; Moore & Craciun, 2020). FoMO has been shown to play a critical role in explaining individuals' social media involvement and satisfaction, overriding their psychological needs and general mood (Dossey, 2014; Przybylski et al., 2013). FoMO is also evident in sport fans' behavioral responses, such as CPA, while watching games (Larkin & Fink, 2016). Elhai et al. (2018) demonstrated that FoMO influences the social aspect of smartphone use to maintain continuous connections. Moreover, individuals with high levels of FoMO are more likely to post event-related content on social media (Conlin et al., 2016). FoMO has been found to positively affect fans' sport team identity (Larkin & Fink, 2016), and it has a positive impact on sports consumption behaviors (Kim et al., 2020).

Additionally, FoMO has been connected to individuals' distractibility from tasks (Gupta & Sharma, 2021) and decreasing their intentions to repeat a current experience (Hayran et al., 2020). In other words, individuals who have a high level of FoMO cannot focus on a specific task because of the apprehension stemming from missing out on more rewarding experiences than the individuals. Sport fans currently watching live sport broadcasts may not want to miss other possible fun experiences, such as accessing social media channels to check what others are doing or having social interactions to update new information. Likewise, FoMO is linked to individuals' social media involvement, CPA, and online fan engagement of sport team’s social media. Therefore, the following three hypotheses are proposed:

Hypothesis 1:

FoMO is positively associated with social media involvement.

Hypothesis 2:

FoMO is positively associated with continuous partial attention.

Hypothesis 3:

FoMO is positively associated with online fan engagement of sport team's social media.

Social media involvement can affect behavioral responses, which are CPA and online fan engagement of a sport team's social media. An individuals' psychological involvement with social media leads to CPA in various tasks, such as social media access during school classes (Lau, 2017) and driving (Weller et al., 2013). Heavy social media users have high levels of enjoyment when they access social media while watching sport (Smith et al., 2019). High levels of social media use are positively linked to behavioral outcomes for sport organizations, such as (re)visiting team social media channels (Santos et al., 2018; Yim & Byon, 2020). Therefore, the additional two hypotheses are proposed:

Hypothesis 4:

Social media involvement is positively associated with CPA.

Hypothesis 5:

Social media involvement is positively associated with online fan engagement of sport team's social media.

CPA can influence online fan engagement of a sport team's social media. Voorveld and Viswanathan (2014) found that any multitasking with watching sport is prevalent. Cunningham and Eastin (2017) identified that the two media sources, watching sport on TV and accessing social media channels, supplement each other mutually and enable coexistence. In their study, 79% of participants used social media channels while watching sport on TV and highlighted that the simultaneous use of two screens could enhance fan experiences by engaging with other fans and participating in discussions about teams, which is online fan engagement via social media channels. Therefore, the additional hypothesis is proposed:

Hypothesis 6:

Continuous partial attention is positively associated with online fan engagement of sport team's social media.

Collectively, the six hypotheses examine the mediating effects of social media involvement and CPA tested to identify the relationship between FoMO and online fan engagement of sport team's social media. The following hypothesis 7 is also proposed:

Hypothesis 7:

Social media involvement and continuous partial attention positively mediate the association between FoMO and online fan engagement of sport team's social media.

The following research model (Figure 1) proposes to investigate the relationships among FoMO, social media involvement, CPA, and online fan engagement of sport teams' social media. Specifically, the current study aims to explore the direct and indirect paths among the suggested constructs to identify the mediating role of social media involvement and CPA in the relationship between FoMO and online fan engagement of sport teams' social media.

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Figure 1.

Proposed research model.

Procedures

Quantitative data was collected using an online survey to test the hypotheses. Participants were recruited for the study using Mechanical Turk (MTurk), operated by Amazon, and data was gathered through an online survey hosted by Qualtrics. To effectively screen participants, predefined criteria were used, such as participants' locations, qualifications, response speed, and fraudulent responses, using prescreening questions and MTurk's customizable qualification system, following recommendations from Buhrmester et al. (2018) and Berinsky et al. (2012). The study was limited to sports fans in the U.S. who regularly watch sports via broadcast or live-streaming services and use social media channels. The aim was to investigate the role of FoMO as an external motivator for watching sports and the role of social media channels as an online communication tool to alleviate FoMO. During the initial process, respondents were introduced to the research context, which described situations of watching their favorite sports teams' games on screens. Participation was voluntary, and a $1 payment was provided as an incentive for each participant.

First, prospective respondents were asked if they were sport fans (“I am a fan of sport in general”), and if they had a particular interest in their favorite sport team (“I like to follow the game of my favorite sport team”) using a 7-point Likert scale ranging from “Strongly Disagree (1)” to “Strongly Agree (7).” Respondents who answered those questions with scores lower than neutral (< 4) were considered non-sport fans, as they were not within the scope of the research and were therefore screened out of the study. Also, the frequency of watching my team's games on screens was asked (“I watch my team's games on screens (TV, internet, DVR, etc.)”) using a 7-point Likert scale ranging from “Hardly ever (1)” to “All games (7)” Second, prospective respondents were asked if they used social media channels (“Please indicate which social media channels you use”), and their frequency of channel use (“In an average week, how many times do you check the social media (e.g., Twitter)?”). Respondents who did not use social media channels at least once a day (< 7 times a week) were considered non-users, as they may have difficulties accessing social media (e.g., non-smartphone users) or intentionally choose not to use social media channels and were therefore screened out of the study. Respondents who selected seven times or more were deemed to use social media regularly and were eligible to participate in the study. Next, participants' levels of FoMO, CPA, and social media engagement of sports team channels were collected to test the hypotheses. Finally, the demographic characteristics of the participants were collected through five items, including gender, age, household income, level of education, and employment status.

Participants

The target population for the study was U.S. sports fans who regularly watch their favorite sports on screens and frequently access related social media channels. A total of 400 respondents started the survey, and after data cleaning processes, 82.0% (N = 328) were included in the data analyses. The participants were composed of 170 males (51.8%) and 158 females (48.2%), who reported high interest in sports (M = 6.32, SD = .89) and their favorite team's games (M = 6.24, SD = 1.01), and frequently watched their games on screens (M = 5.57, SD = 1.97). Additionally, they reported having at least one social media account, with the majority having Facebook (n = 193, 58.8%), followed by Instagram (n = 176, 53.7%) and Twitter (n = 125, 38.1%). On average, respondents reported using social media frequently (M = 30.29 times a week, SD = 20.97). The majority of the sample were between 18–24 years old (n = 125, 38.1%), held a college degree (n = 131, 39.9%), and were employed full-time (n = 148, 45.1%). Respondents were most likely to have a household income of over $60,000 per annum (n = 85, 25.9%). The demographic characteristics of the sample are presented in Table 1.

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Table 1.

Demographic Characteristics of Respondents.

		N	%
Gender	Male	170	51.8
	Female	158	48.2
Age	18–24	125	38.1
	25–34	108	32.9
	35–44	40	12.2
	45–54	26	7.9
	55–64	20	6.1
	65–74	9	2.7
Income	Less than $20,000	53	16.2
	$20,001 - $40,000	48	14.6
	$40,001 - $60,000	65	19.8
	Over $60,000	85	25.9
	Not prefer to say	77	23.5
Education	Under high school	3	.9
	HS grad/GED	32	9.8
	Some college	116	35.4
	College degree	131	39.9
	Master’s degree	33	10.1
	Ph.D	4	1.2
	Professional degree	9	2.7
Job	Full-time job	148	45.1
	Part-time job	26	7.9
	Homemaker	5	1.5
	Retired	8	2.4
	Student	117	35.7
	Not currently employed	15	4.6
	Other	8	2.4
	Not prefer to say	1	.3
	Total	328	100

Measures

The measurement items were adapted from prior studies that used established scales. All items were presented in a randomized order and rated on seven-point Likert scales, ranging from “1-Strongly Disagree” to “7-Strongly Agree.” To measure respondents' FoMO, ten items adapted from Przybylski et al. (2013) were used, which indicate the anxiety that others might be experiencing beneficial events from which one is missing (e.g., “I get worried when I find out my friends are having fun without me”). Social media involvement was operationalized as the extent of relevance and/or importance of social media usage. Ten items adapted from Zaichkowsky's (1994) personal involvement inventory were modified to measure individuals' social media involvement (e.g., “Social media is important”), which has been used in previous studies examining FoMO and social media use (e.g., Larkin & Fink, 2016). CPA was operationalized as constant fragmented attention to multiple online information and communication channels while watching sport games on screens due to an insatiable desire for connectedness. Three items adapted from Firat's (2013a) CPA scales were modified to measure CPA in the situation of using social media while watching sport games on screens (e.g., “I pay partial attention to watching sport games while following and using social media”). Online fan engagement of a sport team's social media was measured using three items based on Wakefield's (2016) three categories of consumers' social media behaviors (observation, participation, and interaction) that were modified and utilized to measure sport fans' social media behaviors (“I read the team's status updates or posts,” “I post, like, or share on the team's social media page,” and “I exchange comments with the team and others on the sport team's social media page.”).

Data Analysis

Descriptive statistics were calculated using the SPSS 26.0 program to determine the basic demographic profile of participants. Confirmatory factor analysis (CFA) and structural equation modeling (SEM) were performed using AMOS 26 to test the proposed hypotheses. The study was conducted using a two-step process based on Anderson and Gerbing’s (1988) suggestion. First, Confirmatory Factor Analysis (CFA) was used with the Maximum Likelihood (ML) estimation method. Goodness of fit for the research constructs and factor structures were examined with key model indices to confirm the measurement model. The reliability of the constructs was evaluated using composite reliability (CR) for each construct to confirm the internal consistency of the measurement items. Factor loadings were investigated to provide evidence of convergent validity, and correlations of variables and average variance extracted (AVE) were examined to assess the discriminant validities. Next, Path modeling of SEM analysis was used to test the hypotheses of relationships among research constructs. The study also examined the mediation effects of social media involvement and CPA on the relationship between FoMO and online fan engagement of the sport team's social media.

Preliminary Analysis

It is essential to test multivariate analysis assumptions to determine whether the research model is adequately composed. The sample size (N = 328) was adequate, and the assumption of linearity was met with the range of .44 –.74. Based on Kline's (2015) criteria that variables with absolute values of skewness over 3.0 and absolute values of kurtosis over 7.0 are non-normal. The normality of the sample was verified with the range of absolute values of skewness (.01 ∼ .47) and kurtosis (.03 ∼ .65). According to Kline's (2015) criteria, Tolerance values lower than .10, and variance inflation factor (VIF) values higher than 10.0 indicate multicollinearity problems. There were no concerns with multicollinearity in the current study with the ranges of tolerance (.35 ∼ .61) and VIF (1.64 ∼ 2.84) values. Thus, all assumptions of the confirmatory factor analysis were satisfied. The descriptive statistics, including means, standard deviations, and bivariate correlations, are depicted in Table 2.

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Table 2.

Means, standard deviation, and bivariate correlations.

Variable	1	2	3	4
1. Fear of missing out	1
2. Social media involvement	.489**	1
3. Continuous partial intention	.624**	.749**	1
4. Online fan engagement	.440**	.563**	.571**	1
Mean	3.70	4.75	4.07	4.18
Standard deviation	1.25	1.20	1.45	1.46

Measurement Model Analysis

Composite reliability (CR) was utilized to measure internal consistency, which is a better alternative than Cronbach's alpha coefficient (Raykov, 2004). Based on Nunnally's (1978) recommended the cutoff, the composite reliability over .70 is acceptable. The internal consistency of the measurement items was satisfied with the values between .831 (Continuous partial attention) to .925 (Social media involvement) in the current study. Convergent validity explains how well a set of variables report the same traits (Kline, 2015). In the current study, a total of 6 items showed a lack of convergent validity based on Fornell et al.'s (1982) suggestion that each factor loading should be equal to or higher than .70. Thus, the 6 items were removed from the scale to establish the research model. Convergent validity is examined with the average variance extracted (AVE) value of the items, ranging from .558 to .669, based on Fornell and Larcker's (1981) recommendation that the AVE values should be greater than .50. Therefore, convergent validity was confirmed after the deletions of items. The detailed measurement items, factor loadings, AVE values, and composite reliabilities were provided in Table 3.

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Table 3.

Measurement Model Statistics.

Item	Loading	AVE	CR
Fear of missing out (FoMO)		.558	.898
I fear others have more rewarding experiences than me	.757
I fear my friends have more rewarding experiences than me	.786
I get worried when I find out my friends are having fun without me	.748
I get anxious when I don’t know what my friends are up to	.758
When I have a good time it is important for me to share the details online (e.g. updating status)	.756
When I miss out on a planned get-together it bothers me	.710
When I go on vacation, I continue to keep tabs on what my friends are doing	.711
Social media involvement (SMI)		.641	.925
Social media is important	.832
Social media means a lot to me	.885
Social media is valuable	.878
Social media is exciting	.755
Social media is appealing	.717
Social media is fascinating	.722
Social media is needed	.795
Continuous partial attention (CPA)		.621	.831
I constantly follow and get engaged with social media while watching sports	.784
I want to stay in constant connection at any time, not to miss anything while watching sports	.821
I pay partial attention to watching sport games while following and getting engaged with social media	.758
Online fan engagement (OFE)		.669	.857
I read the team’s status updates or posts	.752
I post, like, or share on the team’s social media page	.924
I exchange comments with the team and others on the page	.766

Correlations among latent variables were verified to secure discriminant validity with Kline's (2015) recommendation that less than .90 of correlation coefficients are satisfactory. The correlation coefficients of the present study ranged from .440 to .749. Thus, there was evidence of discriminant validity among the latent variables in the study, namely FoMO, social media involvement, CPA, and online fan engagement. Therefore, discriminant validity was also confirmed. The CFA results (χ² (164) = 789.271, p < .001, RMSEA = .108, CFI = .867, TLI = .846, SRMR = .065) indicated acceptable model fit for further analysis.

Structural Model Analysis

Path modeling of structural equation modeling (SEM) analysis was used to test the hypotheses of relationships among FoMO, social media involvement, CPA, and online fan engagement. The overall measurement model was evaluated using the proposed model fit indices: Model chi-square (χ²), Root Mean Square Error of Approximation (RMSEA), Comparative Fit Index (CFI), Tucker Lewis index (TLI), and Standardized Root Mean Square Residual (SRMR). The SEM results (χ² (164) = 789.271, p < .001, RMSEA = .108, CFI = .867, TLI = .846, SRMR = .065) provided evidence of acceptable fit for the proposed model.

The SEM results indicated that FoMO had a positive impact on social media involvement (β = .568, p < .001) and continuous partial attention (β = .323, p < .001), confirming H1 and H2. However, FoMO had a direct but not significant impact on online fan engagement of sport teams' social media (β = .060, p = .485), rejecting H3. Social media involvement had a positive and significant impact on continuous partial attention (β = .688, p < .001), confirming H4. However, social media involvement had a positive but not significant impact on online fan engagement of sport teams' social media (β = .211, p = .136), rejecting H5. Continuous partial attention had positive effects on online fan engagement of sport teams' social media (β = .429, p = .019), confirming H6.

In addition to the direct relationships, we tested the indirect effects of FoMO on online fan engagement of sport teams' social media through social media involvement and continuous partial attention. The results showed that FoMO had a positive indirect impact on online fan engagement of sport teams' social media (β = .425) through social media involvement and continuous partial attention, confirming H7. Detailed results are presented in Figure 2 and Table 4.OPEN IN VIEWER

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Table 4.

mediating Effect of Social Media Involvement and Continuous Partial Attention on The Relationship Between Fear of Missing out and Online Fan Engagement.

Path	Direct Effects		Indirect Effects	Total Effects
	Standardized Coefficient	C.R.	Standardized Coefficient	Standardized Coefficient
FoMO → SMI	.568	9.163	.000	.568
FoMO → CPA	.323	6.260	.390	.713
FoMO → OFE	.060	.698	.425	.485
SMI → CPA	.688	11.629	.000	.688
SMI → OFE	.211	1.493	.295	.506
CPA → OFE	.429	2.355	.000	.429

Theoretical Implications

The current study made three main theoretical contributions in understanding the processes behind online fan behaviors. First, the study validates that FoMO can be considered an external motivator that predicts online fan engagement when applying SDT. Fans feel pressure to connect with others and not miss out on pleasurable experiences, leading them to access sport teams' social media channels. Previous studies by Conlin et al. (2016) identified theoretical accounts of the role of FoMO in TV consumption behaviors, and Kim et al. (2020) provided empirical evidence supporting the role of FoMO in shaping consumer behavior in a sport setting. Although previous studies mostly focused on the negative aspects of FoMO, such as internet addiction (Stead & Bibby, 2017), excessive social media use (Blackwell et al., 2017; Scott and Woods, 2018), and depression (Woods & Scott, 2016), the current study contributes to the new research stream that examines the positive aspects of FoMO as an external motivator based on SDT by providing evidence of online fan behaviors caused by FoMO in sport team social media.

Secondly, individuals experiencing FoMO are often psychologically engaged in social media channels and pay partial attention to other tasks so as not to miss out on anything. This can be explained by the Uses and Gratifications Theory (UGT; Katz et al., 1973), which states that individuals use certain media to satisfy their desires and psychological needs. Muntinga et al. (2011) verified consumers' motivations for engaging in online activities related to branding, while Conlin et al. (2016) applied and verified the UGT in situations where TV viewers felt apprehensive about missing out on social interactions with their peers. In addition, Sheldon (2008) found that individuals access social media to maintain their social relationships to relieve FoMO. Therefore, the current study provides empirical evidence of the application of the UGT to explain the motivations of sports fans. The study shows that relieving FoMO can motivate individuals to access sport teams' social media channels while watching live sports on screens. According to the UGT, these behaviors can be linked to other fan-engaged behaviors, such as accessing sport teams' social media channels while watching sports games to gratify their needs.

Finally, the study contributes to the existing literature on sport fans' behavior that gives continuous partial attention to both social media use and watching sport while live broadcasts. Previous studies have focused on the use of multiple screens while watching sport games on screens to communicate with other fans (Cunningham & Eastin, 2017) and to enhance their social network by supporting the same national team (Brown-Devlin et al., 2021). In addition, individuals use multiple screens to express their emotions (Yu & Wang, 2015), receive game-related information, and have conversations with others (Elishar-Malka et al., 2021) while watching sport on the first screen. However, those studies did not classify the individuals' motivations for second screen use, which could be efficiency, convenience, or connectedness. In addition, sport communication studies have focused on finding practical social media channels for facilitating sport fandoms, such as Snapchat (Billings et al., 2017) and WhatsApp (Weimann-Saks et al., 2020). However, the current study investigated the motivation of CPA as an insatiable desire for connectedness that stems from FoMO, not for the productivity of multiple-screen use. This study also focused on the psychological status of individuals who feel FoMO on interesting experiences and social connections of peer groups. Therefore, the study contributes to the literature about multitasking with a new point of view that individuals' use of dual or multiple screens is not motivated by the desire for productivity but by the desire to seek connectedness.

Practical Implications

Insights into how sport entities can leverage individuals' FoMO and use social media channels to engage with sport teams are provided. First, the present study offers practical implications for social media managers of sport teams. The results of the study indicate that when individuals experience FoMO, they are more likely to be psychologically attached to social media and access social media channels while watching live sports on screens. This suggests that individuals seek a sense of belonging and social interaction through social media (Vale & Fernandes, 2018), which can be connected to fans' enhanced self-esteem (Wang, 2013), sense of self (Stavros et al., 2014), and team identification when fans access biased and favored team-related content (Wann et al., 2005). Therefore, social media managers of sport teams should provide team-related posts that can alleviate FoMO, enhance fans' sense of belonging, and generate social interaction by posting team-supporting content such as “we dominated the game” or “we deserved to win the game.”

Moreover, sports teams should operate multiple fan pages to increase their media exposure in addition to their official social media channels. For instance, an NFL football team, Philadelphia Eagles, has more than 10 fan channels on Twitter, such as @Eagles, @EAGLES_DYNASTY, @Eagles_Nation3, etc. In contrast, an MLB baseball team in the same city, Philadelphia Phillies, has three fan channels on Twitter, such as @PhilliesFanSite, @Phillies4TheWin, and @GoPhilliesGo717. Furthermore, the official sport team sites should provide links to various social media channels to induce fan engagement and encourage easy accessibility to sport teams.

Secondly, sport event sponsors and advertising companies can capitalize on individuals' FoMO to promote their brand names by providing opportunities for fan engagement. Various promotional strategies can be suggested. For instance, sponsors and advertisers can offer rewards or prizes to sport fans who post photos that include their fun moments with social groups and sponsor products on their social media channels. These sponsors and advertisers can also promote their brand names and logos to individuals who watch the sport game alone. The firms can also provide physical locations for sport fans to watch games together and opportunities for starting new social connections (Brown et al., 2015). Therefore, sponsors and advertisers can use these opportunities to interact with fans and increase brand exposure.

Third, sports fans have more options to alleviate FoMO by accessing social media channels and official team homepages. Currently, social media channels offer various online engagement opportunities for sports fans. Previous studies have shown that soccer clubs provide fan areas in social media, such as discussion boards, polls for starting lineups before games, or schedules to encourage fans to support their teams (Vale & Fernandes, 2018). Besides sports teams' social media channels, by accessing the sports team’s website, fans can quickly obtain information and establish a direct relationship with the team and other fans, which can help to eliminate FoMO.

Limitations and Future Research

The current study contained two main limitations that should be addressed for future research. First, an online survey using Mechanical Turk (MTurk) with a convenience sampling method was utilized to collect data. The majority of participants were young generations who are younger than 35 years old. Older generations might not be familiar with the online survey, and that led to the limited number of elderly participants. Also, since the participants were effectively restricted by predefined criteria in MTurk, a limited sample size was generated. Thus, the findings might not apply to all sport spectators' behaviors and should be utilized for foundational knowledge in the area. Future work is encouraged to test the generalizability of the findings by examining diverse people and larger sample size.

Second, the present study was centered on investigating the relationship between FoMO and fans' online engagement of team social media channels. The study limited the online fan behavior to accessing team social media channels. Thus, future studies should examine the impact of FoMO on a broader range of potential online fan behaviors. For instance, sport fans may participate in group chatting at live-streaming channels, team-generated media channels, or online video channels. Future work is also encouraged to expand the research model that examines the antecedents of online fan behaviors. For example, individuals' sedentary lifestyles, personal traits, and the accessibility of multi-screens might impact online fan engagement toward a sport team.

Conclusion

The current study suggests that individuals' fear of missing out (FoMO) on their social group leads to a high level of social media involvement and the desire to constantly stay connected with others in real time. The study also demonstrates that increased social media involvement positively affects social media users' continuous attention to the use of social media channels during sport games. This strong desire to stay connected affects sport consumer behavior, such as accessing the social media channels of sport teams. Interestingly, although fans felt FoMO, they did not directly engage with sport teams' social media. However, after being involved in social media activities and connecting with others, sport fans engage with sport teams' social media channels.

The study findings contribute to our understanding of self-determination theory (SDT) in general and FoMO in the context of sport in particular. Essentially, FoMO motivates sport fans to access the social media channels of sport teams. Fans feel external pressure that other people have a pleasurable experience by watching sport games and continuously connecting with others. This leads to engaging in social media related to the sport team. The study also provides practical communication implications related to fans' social media assessment, as well as for social media managers of sport teams by suggesting the operation of live broadcasts during sport games and the provision of opportunities to continuously chat with other fans to satisfy fans' needs and secure more fans.