Abstract
Aim
This study aimed to examine the influence of state boredom on craving for smartphone use, as well as the potential moderating effect of individual differences - fear of missing out (FoMO).
Methods
A total of 112 undergraduate students were randomly assigned to either low or high state boredom groups. Participants completed a reference copying task along with assessments for state boredom, craving for smartphone use, and FoMO.
Results
The results indicated that: (1) Participants in the high state boredom group reported higher levels of background craving for smartphone use; (2) The FoMO moderated the association between state boredom and background craving for smartphone use significantly, which was stronger for individuals with a higher level of FoMO.
Discussion
This study broadened the research by focusing on the influences of boredom and the mechanism of smartphone use craving and problematic phone use, which could provide guidance for the intervention of craving, and healthy smartphone use.
Introduction
Can you live without a phone? To some extent, owing to the diverse functions of accessibility and portability offered by smartphones, they have become an indispensable aspect of our lives (Sunday, Adesope, & Maarhuis, 2021). Currently, 85.95% of the global population owns a smartphone, and the smartphones penetration in China is 68.4%, and 99.8% of Chinese netizens use mobile phones to access the Internet (CNNIC, 2023; Turner, 2023). While smartphones offer plentiful benefits and conveniences, they also pose potential adverse effects. Among them, there is no doubt that the problematic smartphone use (PSU) stands out as one of the most prominent issues, referring to the excessive use of smartphones leading to symptoms and dysfunction resembling substance abuse (Elhai, Levine, & Hall, 2019). The PSU may have detrimental effects on individuals' physical and mental health. For example, it could cause eye problems and body pains, sleep disturbances, as well as various psychological and adaptation problems (e.g., loneliness, depression, and suicidal ideation) (Kuang et al., 2020; Ratan, Parrish, Zaman, Alotaibi, & Hosseinzadeh, 2021; Wacks & Weinstein, 2021). At the same time, PSU may also lead to social isolation, and poor relationship quality (Busch & McCarthy, 2021; Tateno et al., 2019). In addition, PSU may also impair working memory and other cognitive functions, and more seriously, may result in dangerous driving and road safety for pedestrians, which will endanger life safety (Busch & McCarthy, 2021; Sunday et al., 2021). Unfortunately, though the incidence of PSU is quite high in all ages, the problematic smartphone use among undergraduate students is relatively more prominent, with the incidence ranging from 8.88% to 62% (De-Sola, Rodríguez de Fonseca, & Rubio, 2016).
Against this background, the influencing factors accounting for PSU have been the focus of relevant research, and numerous findings have been achieved. However, limited studies have examined the development and maintenance mechanisms of PSU, which are important while largely unclear. In the domain of research concerning both traditional addictions (e.g., drug and alcohol dependence) and behavioral addictions (e.g., gambling), craving not only manifests as a distinctive characteristic but also functions as a fundamental mechanism underpinning these addictions, which may offer a novel perspective to uncover the development and maintenance mechanisms of PSU (Brand et al., 2019; Yang, Fu, Liao, & Li, 2020). Thus, this study kept eyes on the craving for smartphone use, to further examine the influencing mechanisms of PSU.
Background craving of smartphone use
Craving can be defined as an irresistible and uncontrollable desire to access the target material (e.g., drugs or alcohol) or engage in relevant behaviors (e.g., gambling, using a smartphone, or SNS), regardless of its detrimental effects (De-Sola, Talledo, Rubio, & de Fonseca, 2017). Craving can be categorized into episodic craving (also known as cue-induced craving) and background craving, depending on the means of evocation, internal mechanisms, and neural basis (Tong, Chen, Huang, Gong, & Fang, 2017). Episodic craving is an occasional and intense craving that is typically triggered by related stimuli (Ferguson & Shiffman, 2009; Shiffman, 2000; Tong et al., 2017). Conversely, background craving is a steady craving that persists throughout the day (Shadel et al., 2011; Shiffman, 2000). Background craving frequently emerges subsequent to withdrawal (Shadel et al., 2011) and is mainly related to individual physiological and psychological states (Tong et al., 2017). While extensive research has been conducted on episodic craving using cue exposure paradigms, less attention has been given to understanding background craving (Sun, Duan, Niu, Tian, & Zhang, 2021; You, Rassu, & Meagher, 2023). Additionally, it is noteworthy that episodic craving is founded upon background craving as a crucial mechanism underlying addictive behaviors (Drummond, 2001). Therefore, more research emphasis should be placed on investigating background craving.
Simultaneously, current research is increasingly focusing on the moderate smartphone use in daily life, which is commonly observed among the majority of users. It is estimated that 45.8% of Chinese undergraduate students spend 3–6 h per day on their cell phone (iiMedia Research, 2021). Examples include the effects of smartphone presence (simply having a smartphone around without using it) on cognitive function and academic performance, as well as the association between phubbing (snubbing others by focusing on a smartphone) or technoference (intrusion of digital technology into personal lives) and impaired interpersonal relationships (Al-Saggaf & O'Donnell, 2019; McDaniel & Radesky, 2018; Niu et al., 2022; Tanil & Yong, 2020). Research has also indicated that, for smartphone use, craving (both episodic and background craving) is not confined to problematic smartphone users but is also prevalently experienced by ordinary individuals who possess the motivation to interact with their devices everyday (Hämäläinen & Pirkkalainen, 2022), highlighting the significance of examining craving associated with everyday smartphone usage. It should be noted that only a minority of smartphone users exhibit problematic behaviors while the majority are moderate users with a certain degree of excessive use (Coyne, Stockdale, & Summers, 2019). Given that background craving exists extensively among both moderate and problematic smartphone users, the examination of this phenomenon holds broader practical implications (Franken, 2003). In brief, the aim of our study was to explore background craving for smartphone use along with its influencing factor.
The relation between boredom and background craving
Boredom represents not merely a negative tendency and feeling that individuals strive to avoid, but also a powerful impetus for individuals' behaviors (Van Tilburg & Igou, 2011). For instance, boredom may drive individuals to engage in smartphone use, emotional eating, smoking, drinking, and even gambling and drug use (Elhai, Vasquez, Lustgarten, Levine, & Hall, 2018; Kılıç, van Tilburg, & Igou, 2020; Song, Ma, Liu, Xu, & Gao, 2022). Regarding smartphones, the avoidance of boredom constitutes an important motivation for their usage since they provide opportunities for pleasure-seeking and immediate gratification of needs (Elhai et al., 2018; Wen et al., 2023). This constant pursuit can trigger cravings for smartphones or even lead to PSU (Wegmann, Ostendorf, & Brand, 2018; Wolniewicz, Rozgonjuk, & Elhai, 2020). Boredom can generally be divided into trait boredom (also known as boredom proneness, a long-term personality trait), and state boredom (a conscious subjective feeling indicating unsuccessful engagement in valued goal-congruent activities) (Belton & Priyadharshini, 2007; Danckert & Merrifield, 2018; Musharbash, 2007; Westgate & Wilson, 2018). Considerable research has been focused on trait boredom due to its robust association with undesirable behaviors such as PSU and internet addiction (Bench & Lench, 2013; Chou, Chang, & Yen, 2018; Hong et al., 2020; Wolniewicz et al., 2020). However, insufficient attention has been given by researchers to state boredom, which is a prevalent emotional experience in our daily lives. It has been found that nearly 80% of day-to-day boredom is caused by situational factors rather than being an inherent trait (Chin, Markey, Bhargava, Kassam, & Loewenstein, 2017; Elpidorou, 2018). State boredom arises from the monotony of environmental stimuli and the lack of meaning in events, and is often accompanied by unpleasant experiences, difficulty in maintaining attention, perceived meaninglessness, and unchallenging (Chan et al., 2018; Van Tilburg & Igou, 2012). This frequently induces individuals to seek means of escaping or alleviating their boredom by either changing themselves or their environment (Raffaelli, Mills, & Christoff, 2018). As previously stated, when confronted with a boring situation, individuals tend to actively seek novel stimuli as a strategy for escaping or relieving their current state of boredom. This behavior is especially conspicuous in experimental contexts where participants are required to complete repetitive tasks to induce state boredom (Bench & Lench, 2019; Van Tilburg & Igou, 2011). Simultaneously, the smartphone, as a collection of diverse applications, fully serves to provide novelty and excitement, recreation and entertainment, as well as to mitigate boredom (Lepp, Barkley, & Li, 2017). Smartphones have become so deeply intertwined in our lives that positive results could be anticipated even without active usage (Elhai, Hall, Levine, & Dvorak, 2017). Although the environment remains unchanged, individuals can envisage smartphone use to alleviate boredom and generate the craving to use their smartphones. However, this craving is not generated by the stimuli associated with smartphones but originates internally within the individual. Besides, reinforcement theory also suggests that when an individual experiences boredom, the pleasure and satisfaction derived from smartphone use act as a reinforcement to reinforce the craving for smartphone use (Drummond, 2001; Niu et al., 2016). In summary, we hypothesized that experimentally induced state boredom may give rise to background craving for smartphone use.
The moderating effect of the FoMO
It is of great importance to note that craving is influenced by both situational and individual factors, with particular emphasis on the role of FoMO. FoMO was defined as “a pervasive apprehension that others might be having rewarding experiences from which one is absent” and may play a critical role in moderating the association between state boredom and background craving for smartphone use (Przybylski, Murayama, DeHaan, & Gladwell, 2013; Wilson, 2022). FoMO represents a stable individual trait characterized by an incessant desire for continuous social contact, prompting individuals to frequently check SNS or smartphones and other electronic devices to maintain social connections and acquire instant information (Chai et al., 2018; Elhai, Yang, & Montag, 2021; Li, Griffiths, Niu, & Mei, 2020). Consequently, individuals with a high level of FoMO may exhibit a stronger craving to use their smartphones and are more likely to develop PSU (Elhai et al., 2018; Wolniewicz et al., 2020). Additionally, both FoMO and boredom are manifestations of self-regulation failures. More precisely, individuals with a high level of FoMO struggle to control their intense desire to be informed about others' activities and attempt to satisfy this desire through excessive smartphone usage (Danckert & Merrifield, 2018). Moreover, a previous study has demonstrated that FoMO moderated the effect of smartphone presence on cognitive function. Specifically, individuals with a high level of FoMO perceived smartphones as more salient in their environment and are more attracted to them, resulting in increased attention towards smartphone functions and positive experiences (Niu et al., 2022). In fact, FoMO is strongly associated with PSU and problematic SNS use, so individuals with a high level of FoMO are prone to overusing their smartphones and experiencing constant cravings for them (Elhai et al., 2020, 2021). Furthermore, FoMO could mediate the association between boredom proneness and PSU, making it even harder for individuals with a high level of FoMO to control their craving for smartphone use during boring situations (Wolniewicz et al., 2020). Overall, FoMO may mediate the effect of state boredom on background craving for smartphone use, and this effect is particularly pronounced among individuals who possess a high level of FoMO.
To summarize, previous studies have revealed the close connections between boredom (encompassing trait boredom and cue-induced boredom) and craving as well as PSU, thereby laying a foundation for our research. However, existing studies have neglected the role of state boredom in the context of more moderate smartphone use. The research on background craving can not only broaden the research perspective but also provide practical guidance for avoiding boredom and excessive craving for smartphones. Therefore, our study examined how state boredom impacts background craving for smartphone use, and the internal mechanism – the moderating effect of FoMO.
Method
Participants and design
We postulated a medium effect size of 0.3 in G∗Power 3.1 for a repeated measure (2 measures) within-between interaction analysis of ANOVA as principal statistical test for background craving analysis. To achieve a power of 80%, and two-sided probability of a type I error (α) of 5%, a minimum of 90 participants was deemed necessary. Given the potential for participant attrition or careless responses, we augmented the estimated sample by 20% on this basis, thereby arriving at 112 participants (with 56 participants in each group). Therefore, we recruited 112 undergraduate students (50% females), who ranged in age from 18 to 24 years (M = 20.67 ± 1.65 years). Prior to their participation in the study, informed consent was procured. All participants fulfilled the criteria of being right-handed and possessing normal or corrected-to-normal vision and hearing.
A between-subjects experimental design was employed, randomly assigning participants into one of two conditions: (a) low state boredom group tasked with transcribing two references with a mixture of text and numbers; (b) high state boredom group tasked with transcribing ten references with a mixture of text and numbers (Van Tilburg & Igou, 2011). Each male and each female had a 50% probability of being assigned to the low state boredom group. As a result, there were 56 participants in each group, and 50% of them were female.
Measures
Reference copying task
This is a repetitive action task designed to induce state boredom by requiring participants to copy 2 (low state boredom group) or 10 (high state boredom group) references (Van Tilburg & Igou, 2011). To prevent them from understanding and contemplating the meaning of the references during the task, uncommon and difficult Chinese physics journal references were used as the experimental material. The 4-item manipulation test was used in this study (Van Tilburg & Igou, 2011), and participants responded on a 7-point Likert scale with higher scores manifesting greater levels of state boredom induced by the reference copying task. The four items corresponded to the four dimensions of state boredom, namely task meaninglessness, subjective meaninglessness, task boredom and subjective boredom.
Trait boredom scale
The Chinese version (Huang et al., 2010) of the Boredom Proneness Scale (Farmer & Sundberg, 1986) was used in this study. This self-reported instrument consists of 30 items that assess trait boredom levels. Participants rated their responses on a 7-point Likert scale, with a higher score manifesting greater levels of trait boredom. The Cronbach's alpha for this scale in our study was 0.85.
Background craving for smartphone use scale
The revised Chinese version of Background Craving Scale (Liu et al., 2013) derived from the Brief Questionnaire of Smoking Urges (Cox, Tiffany, & Christen, 2001), was adopted to assess individuals' background craving for smartphone use. This self-reported instrument consists of 8 items, and participants rated their responses on a 7-point Likert scale. Higher scores manifest greater levels of background craving for smartphone use. The Cronbach's alpha for this scale in our study was 0.91.
The fear of missing out scale
The trait FoMO subscale of the Chinese version (Xiao & Liu, 2018) of the Trait - State FoMO Scale was adopted in this study (Wegmann, Oberst, Stodt, & Brand, 2017). This self-reported instrument consists of 4 items, and participants were requested to rate their responses on a 5-point Likert scale. Higher scores manifest greater levels of FoMO. The Cronbach's alpha for this scale was 0.81 in this study.
Procedure
To eliminate the potential confounding effects of pre-experimental conditions on the results, participants were instructed to engage in a 5-min muscle relaxation exercise. Subsequently, they completed the Boredom Proneness Scale, Pre-test of Background Craving for Smartphone Use Scale, and assessed their current level of relaxation (Niu et al., 2016). Following this, we assigned participants to either the low or high state boredom group randomly and tasked with completing a reference copying task. Upon completion, participants filled out the State Boredom Scale. Finally, they were requested to complete the post-test of Background Craving for Smartphone Use Scale and FoMO Scale (see Fig. 1).
Flowchart of experimental procedure
Citation: Journal of Behavioral Addictions 2025; 10.1556/2006.2025.00009
Data analysis
Analysis of data using SPSS 27.0 and the SPSS macro PROCESS (http://www.afhayes.com) recommended by Hayes (2016, 2017). Initially, we calculated descriptive statistics and mean differences. Subsequently, we employed independent sample t-tests to examine variations in relaxation levels, trait boredom, state boredom between the low state boredom group and the high state boredom group. Then we used a mixed 2 × 2 ANOVA to examine variations in background craving for smartphone use between 2 groups. Furthermore, Hayes' (2016, 2017) SPSS macro PROCESS (Model 1) was utilized to investigate the potential moderating effect of FoMO.
Ethics
The study procedures were conducted strictly in accordance with the Declaration of Helsinki. The Institutional Review Board of the Central China Normal University approved the study (No. CCNU-IRB-202205010b). All participants were informed about the study, and all provided informed consent.
Results
Homogeneity test
To ensure the homogeneity of the two participant groups before conducting the experiment, we used independent sample t-tests. The results indicated no significant difference between the two groups regarding relaxation, trait boredom, and background craving for smartphone use on the pre-test (see Table 1). These findings indicated that both participant groups were homogeneous.
The independent sample t-test of relaxation, trait boredom and pre-test background craving
| High state boredom | Low state boredom | t | p | |||
| Mean | SD | Mean | SD | |||
| Relaxation | 4.32 | 0.57 | 4.43 | 0.87 | −0.77 | 0.44 |
| Trait boredom | 3.44 | 0.72 | 3.51 | 0.67 | −0.39 | 0.70 |
| Pre-test background craving | 3.15 | 0.94 | 3.01 | 0.87 | 1.62 | 0.19 |
Manipulation test
After completion of the reference copying task, we conducted independent samples t-tests to assess potential differences between the two groups across in four dimensions of state boredom. And the results showed that the scores of the high state boredom group were significantly higher than those of the low state boredom group in all four dimensions of state boredom (ps < 0.001), proving the validity of the experimental manipulation of state boredom (see Table 2).
The independent sample t-test of the two groups of state boredom
| High state boredom | Low state boredom | t | p | |||
| Mean | SD | Mean | SD | |||
| Task Meaninglessness | 4.61 | 1.64 | 2.88 | 0.72 | 5.62 | < 0.001 |
| Subjective Meaninglessness | 4.18 | 1.34 | 2.46 | 0.71 | 4.91 | < 0.001 |
| Task Boredom | 4.33 | 1.60 | 3.08 | 1.04 | 4.67 | < 0.001 |
| Subjective Boredom | 3.99 | 1.40 | 2.73 | 0.89 | 4.11 | < 0.001 |
A mixed 2 × 2 ANOVA (between-subjects factor – group: the low state boredom group vs. the high state boredom group; within-subjects factor – testing time: pre-test vs. post-test) showed a significant main effect for group (F(1, 110) = 30.57, p < 0.001, partial η2 = 0.32) as well as a significant main effect for testing time (F(1, 110) = 17.06, p < 0.001, partial η2 = 0.12), indicating that post-test background craving was significantly higher than pre-test background craving, and background craving reported by the high state boredom group was also significantly higher than that of the low state boredom group (see Table 3). The results also yielded a significant interaction (F(1, 110) = 95.06, p < 0.001, partial η2 = 0.49). Then a post-hoc test was performed using Bonferroni method, and the results showed that the differences between pre-test background craving and post-test background craving were significant among the high state boredom group (p < 0.001), while there was no significant difference in the low state boredom group (p = 0.17); the difference between the low state boredom group and the high state boredom group was not statistically significant in the pre-test background craving (p = 0,19), but was significant in the post-test background craving (p < 0.001). In conclusion, state boredom can significantly affect individuals' background craving for smartphone use. Table 3 showed the means of pre-test and post-test background craving for smartphones use reported by 2 groups.
The means of background craving for smartphones use
| Pre-test background craving | Pre-test background craving | |||
| Mean | SD | Mean | SD | |
| Low state boredom | 3.01 | 0.87 | 3.26 | 0.72 |
| High state boredom | 3.15 | 0.94 | 5.07 | 1.17 |
Moderating effect analysis
A multicollinearity analysis was performed before the moderating effect analysis. The VIF values for the pre-test background craving, gender, age, state boredom, FoMO and interaction effect of state boredom and FoMO were all below 2, indicating that multicollinearity was not an issue in this model. To examine the potential moderating role of FoMO in the relationship between state boredom and background craving for smartphone use, analyses were conducted using SPSS macro PROCESS (Model 1), in which gender and age were taken into account as control variables and the difference score between post-test and pre-test of background craving was used as the dependent variable. The results revealed that state boredom and FoMO were both significant positive predictors of background craving for smartphone use (β = 0.45, t = 4.74; β = 0.36, t = 3.87). Moreover, the interaction effect of state boredom and FoMO on background craving for smartphone use was found to be significant (β = −0.29, t = −3.41), indicating that the moderating effect of FoMO is significant (see Table 4).
Testing the moderating effect of the FoMO
| Outcome | Predictors | R2 | F | β | t | 95% LLCI | 95% ULCL |
| Background craving for smartphone use | Gender | 0.47 | 18.95*** | 0.16 | 2.54* | 0.05 | 0.27 |
| Age | 0.09 | 1.73 | −0.10 | 0.34 | |||
| State boredom | 0.45 | 4.74*** | 0.07 | 0.59 | |||
| FoMO | 0.36 | 3.87*** | 0.01 | 0.49 | |||
| State boredom × FoMO | −0.29 | 3.41*** | 0.01 | 0.44 |
Notes: LL = low limit, CI = confidence interval, UL = upper limit. *p < 0.05,**p < 0.01,***p < 0.001.
To further elucidate the moderating effect of FoMO, we conducted a simple effect analysis. More specifically, experimentally induced state boredom was a significant positive predictor of background craving for smartphone use in both the low FoMO group (B = 1.47, p < 0.001) and the high FoMO group (B = 1.95, p < 0.001), but this effect was more significant in the high FoMO group (see Fig. 2). In other words, participants with a high level FoMO exhibited a greater susceptibility to state boredom and experienced an increased background craving for smartphone usage compared to those in a low FoMO group.
FoMO moderated the relationship between state boredom and background craving for smartphone use
Citation: Journal of Behavioral Addictions 2025; 10.1556/2006.2025.00009
Discussion
Nowadays, smartphones have attained ever-growing popularity due to their multifunctionality. With this comes a common experience of craving for smartphone use in our daily lives, especially the craving is widespread among both moderate and problematic smartphone users. The purpose of this study was to examine whether state boredom influences background cravings for smartphone use based on behavioral experimentation methods. Results demonstrated that state boredom could evoke individuals' background craving for smartphone use, and FoMO could significantly moderate the association between them.
State boredom on background craving for smartphone use
As hypothesized, initially discovered that state boredom could evoke background craving for smartphone use, which was to some extent consistent with Wegmann and her colleagues' study (2018). In contrast to Wegmann's study which focused on the association between trait boredom and episodic craving, we focused on the more widespread boredom and background craving that persist steadily without smartphone-related stimuli. That's to say, even without the physical presence of a smartphone, background craving can be generated in boredom situations. Notably, background craving is a psychological feeling arising from unmet individual needs, and both seeking rewards and alleviating negative emotions are important influencing factors contributing to background craving (Cox et al., 2001; Liu et al., 2013). Boredom, as a commonly encountered negative emotion in daily life, not only exhibits close associations with anxiety and depression but also shares similar emotional experiences with them (Lee & Zelman, 2019). In addition, boredom induces a sense of scarcity in individuals, compelling them to actively seek novel experiences as a means of alleviating this unpleasant feeling (Bench & Lench, 2019). At the same time, smartphones, with their versatility, portability, and accessibility, can provide a wealth of novel stimulation to meet the needs of individuals and bring pleasure (Elhai et al., 2017). Thus, avoiding the negative emotions of boredom as well as seeking pleasurable rewards from novel stimuli motivates individuals in a state of boredom to develop a background craving for smartphone use. Over an extended period, individuals seek rewards by using their smartphones whenever they are in a state of boredom, and they even anticipate rewards when not actively using smartphones (Elhai et al., 2017). This not only establishes a conditioned reflex between boredom and craving but also creates a craving for smartphone use, and more severely, habitual smartphone use, and PSU (Brand et al., 2019).
More importantly, the elaborated intrusion theory of craving proposes that craving derives from learned associations between internal or external cues and specific behaviors (e.g., smartphone use) (May, Kavanagh, & Andrade, 2015; Tapper, 2018). Such learned associations may lead to intrusive thoughts and subsequently to cognitive elaboration that encompasses the construction of multi-sensory mental imagery (May et al., 2014; Tapper, 2018). This vivid mental imagery closely resembles real-life scenarios and serves to maintain and augment cravings (Tapper, 2018). As previously mentioned, the conditioned reflex between boredom and craving for smartphone use represents a learned association that prompts individuals to develop intrusive thoughts related to smartphone use. Initially, those intrusive thoughts are pleasurable, accompanied by positive rewards, being as pleasurable as the actual use of smartphones. They may also stimulate the individual's rich imagination for cognitive elaboration, which aims to construct mental imagery related to smartphone use, and induce the craving for smartphone use. Unfortunately, while these images afford instant gratification, they also create a sense of deficit, especially when what is craved cannot be achieved (e.g., when smartphone use is restricted) (Kavanagh, May, & Andrade, 2009; May, Andrade, Kavanagh, & Hetherington, 2012, 2014). While individuals may attempt to control cognitive elaboration through thought suppression or diversion, achieving this is typically challenging and can even reinforce cognitive elaboration and generate more images (Kavanagh et al., 2009; May et al., 2012; Wegner, 1994). With unfulfilled smartphone use, this may lead to a vicious cycle that exacerbates cravings for smartphone use (May, Andrade, Panabokke, & Kavanagh, 2004). Taking all these considerations into account, state boredom may result in background craving for smartphone use.
The moderating effect of the FoMO
Although the association between state boredom and background cravings for smartphones has been verified, this study delved into the moderating role of FoMO to exam individual differences in behavior. As special forms of anxiety in digital age, antecedent studies have illustrated that FoMO would motivate individuals to use electronic devices frequently to obtain information and keep in touch with others timely, which are the important motivations for smartphone use. Consequently, FoMO is significantly positively linked with the intensity of SNS use, craving for smartphones, and even PSU (Elhai et al., 2018; Wolniewicz et al., 2020). This study also revealed that FoMO could moderate the effect of state boredom on background cravings for smartphones use. Specifically, individuals with a high level of FoMO might experience a more intense craving for smartphone use even in the same boring situation. Since individuals with a high level of FoMO are typically concerned about being left behind by the latest news, leading them to pay greater attention to their smartphones to alleviate this anxiety (Chai et al., 2018). In addition, in many cases, smartphones have become objects of attachment and extensions of individuals' selves, thereby strengthening the emotional bonds between individuals and their smartphones. At the same time, these connections may be more prominent among those with a high level of FoMO (Fullwood, Quinn, Kaye, & Redding, 2017; Gertz, Schütz-Bosbach, & Diefenbach, 2021).
Furthermore, according to the basic points of the meaning and attentional components model of boredom, state boredom appears to be the result of deficits in meaning and attention (simplicity and monotony of the task or complexity of the task are reasons for poor attention) (Danckert & Merrifield, 2018; Westgate & Steidle, 2020; Westgate & Wilson, 2018). Therefore, addressing momentary boredom requires individuals concentrating on the current task at hand, ascribing greater meaning to the current task, or finding new stimuli (Westgate & Steidle, 2020). It is widely acknowledged that the latter approach is more appealing (as boredom frequently propels individuals towards novel alternatives and the pursuit of rewards), while the former two require more cognitive resources (Bench & Lench, 2019; Milyavskaya, Inzlicht, Johnson, & Larson, 2019; Westgate & Steidle, 2020). Nevertheless, an individual's cognitive resources are limited, and particularly, the urgent need to connect with others in individuals with high FoMO consumes cognitive resources. So, not only do they fail to allocate sufficient attention or meaning to the current task, but they also develop a pronounced craving for smartphone use to alleviate their current boredom (Baddeley, 2012; Ding, Zhang, & Zhou, 2020; Niu et al., 2022). In general, FoMO acted as a moderator between state boredom and background cravings for smartphone use.
Theoretical and practical implications
These findings have not simply theoretical implications but practical implications as well. From a theoretical standpoint, this study focused on background craving among moderate smartphone users, broadening the relevant research perspectives on craving. Additionally, the focus on the impact of boredom on craving for smartphone use also provided an in-depth explanation of the behavioral consequences of boredom as well as the potential formation of maintenance mechanisms for the behavioral motivation of moderate and pathological smartphone use, thereby extending and enhancing the discussion of related topics. Practically, they could provide guidance for avoiding boredom and excessive craving for smartphone use. In fact, experiencing boredom is not an inherently negative occurrence, it alerts us to a lack of focus or prompts us to desist from engaging in meaningless things (Westgate & Steidle, 2020). In other words, when engaged in meaningful tasks we should allocate more attention and emphasize their significance to avoid distractions; conversely, we need to seek out more interesting and challenging pursuits to prevent time wastage. Considering the moderating effects of FoMO, interventions such as persuasion and motivational strategies can be used to mitigate the adverse effects associated with a high level of FoMO (Wiesner, 2017).
Limitations and future research
However, several limitations ought to be acknowledged. Firstly, the use of the reference copying task to induce state boredom may lack ecological validity. Therefore, future research could adopt ecological momentary assessment (an approach that emphasizes real-time observation, assessment, and research of real-life behaviors) to examine the relationship between actual occurrences of state boredom and craving (Shiffman, Stone, & Hufford, 2008). Secondly, given the ubiquity of smartphone-related stimuli in real life can lead to episodic cravings for smartphone use, so it is also important to explore the different mechanisms by which boredom leads to cravings in future research. Finally, the study's sample consists solely of undergraduate students aged 18–24, so great caution must be exercised when attempting to generalize the results beyond this population. Future studies should involve participants from diverse age groups.
Funding sources
This work was supported by the National Social Science Foundation of China (grant number 23BSH118). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Authors' contribution
Conceptualization: GN, XS; data curation: YX, KL, ZL.; formal analysis: YX, KL, ZL; writing—original draft preparation: XS, YZ, ZL; writing—review and editing: XS, GN, XS; funding acquisition: XS. All authors have read and agreed to the published version of the manuscript.
Conflicts of interest
All authors declare that they have no conflict of interest.
Data availability
The data that support the findings of this study are available from the Key Laboratory of Adolescent Cyberpsychology and Behavior (CCNU), but restrictions apply to the availability of these data, which were used under licence for the current study, and so are not publicly available. Data are however available from the authors upon reasonable request and with permission of the Key Laboratory of Adolescent Cyberpsychology and Behavior (CCNU).
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