Background and aims: Previous evidence has indicated that problematic social media use (PSMU) is characterized by an attentional bias to social media icons (such as Facebook icons), but not to social webpages (such as Facebook webpages). They suggest that there may be other factors influencing attentional bias like fear of missing out (FoMO). But it remains unclear how FoMO moderates attentional bias in PSMU. This study aims to investigate whether PSMU show attentional bias for stimuli associated with social media, and how FoMO moderates on attentional bias among PSMU through experimental methods.Methods: Based on the Interaction of Person-Affect-Cognition-Execution (I-PACE) model, this study explored mechanisms of attentional bias to social media icons (such as WeChat) related to PSMU and further examined the role of FoMO in this relationship. Specifically, attentional bias patterns to social media icons of 62 participants (31 PSMU and 31 control group) were explored during a dot-probe paradigm combined with eye-tracking in Experiment 1, and attentional bias patterns to social media icons of another 61 individuals with PSMU with different FoMO levels was explored during a dot-probe paradigm combined with eye-tracking in Experiment 2.Results: Results revealed that individuals with PSMU had an attentional bias toward social media icons, demonstrated by attentional maintenance, and such bias such bias was moderated by FoMO negatively, demonstrated by attentional vigilance and maintenance in PSMU/high FoMO.Conclusion: These results suggest that attentional bias is a common mechanism associated with PSMU, and FoMO is a key factor on the development of PSMU.

Fear of missing out (FoMO) is a cognitive-affective factor that has been consistently linked to problematic social media use (PSMU), but less is known about whether this association differs across severity-based subgroups or changes over time at the node level. This study examined the cross-sectional and two-wave associations between FoMO and PSMU in Chinese university students. Two-wave data were collected one year apart from 853 participants at Time 1 and 817 participants at Time 2. Partial correlation and regression analyses showed that FoMO was positively associated with PSMU. Latent profile analysis identified broad higher- and lower-level subgroups for both FoMO and PSMU. Node-level network analyses further indicated that FoMO and PSMU nodes were positively interconnected. Most subgroup and two-wave network comparisons suggested that overall network structure was relatively stable. The clearest temporal difference emerged in the global strength of the PSMU network. When differences were observed, they were more evident in the relative prominence of specific nodes, including several bridging nodes, than in broader network organization. Overall, the findings suggest that the FoMO-PSMU association is robust, whereas subgroup- and time-related variation appears limited and is better understood as node-level variation within a broader pattern of structural stability.

BACKGROUND Previous studies have explored the relationship between fear of missing out (FoMO) and problematic social media use (PSMU) through cross-sectional designs. However, the relationship between core nodes of FoMO and PSMU still requires further analysis and research. OBJECTIVE This study investigated the relationship between FoMO and PSMU, and further explored the characteristics and stability of the relationship both from a cross-sectional and longitudinal design based on network analysis. METHODS It was conducted by using the Chinese version of the FoMO and PSMU scales on a sample of 853 and 817 Chinese university students at T1 and T2, respectively. Differences in the combined FoMO-PSMU network structures between T1 and T2 were analyzed. RESULTS Results showed that: (1) FoMO was significant positively correlated with PSMU, and FoMO predicted PSMU positively; (2) individuals with different levels of FoMO and PSMU differed in core nodes, and the high FoMO-PSMU group and the low FoMO-PSMU group differed in core nodes and invariant global strength of network structure; (3) longitudinal analyses found core nodes changed from item 3 to item 6 in FoMO and from item 2 to item 6 in PSMU as time passed from T1 to T2, and there were differences in invariant global strength of combined network structures. CONCLUSIONS These findings suggest that FoMO is a key influencing factor for PSMU. Variations in core nodes and network structures were observed across different levels of FoMO and PSMU. Furthermore, over time, PSMU exhibited a shift from an increased desire for social media use to a focus on actual negative outcomes, while FoMO transitioned from emotional anxiety to psychological conflict. These results support the validity of the I-PACE model in explaining PSMU.