Problematic social networking site use refers to compulsive and excessive engagement with social media platforms. This kind of use becomes harmful when it starts interfering with everyday life—such as affecting sleep, mood, academic work, or relationships.

It is more than just heavy use; it reflects difficulty in controlling online behavior, similar to behavioral addiction.

Illustration of sad, lonely woman sat on the floor while scrolling on phone

Wang, Y., Sun, Y., & Li, T. (2025). The longitudinal relationship between loneliness and problematic social networking site use in college students: The mediating role of trait- and state-fear of missing out. Frontiers in Psychology, 16, 1477239. https://doi.org/10.3389/fpsyg.2025.1477239

Key Points

Loneliness positively correlates with problematic social networking site use (PSNSU) among Chinese college students.
Trait-Fear of Missing Out (FoMO) and state-FoMO fully mediate the relationship between loneliness and PSNSU.
Trait-FoMO is more strongly associated with loneliness, while state-FoMO is more directly linked to PSNSU.
Loneliness influences PSNSU through two distinct pathways: directly via trait-FoMO, and indirectly through trait-FoMO leading to state-FoMO.
The study distinguishes between trait- and state-FoMO, adding nuance to understanding FoMO’s role in digital overuse.
Based on the I-PACE model, the findings illustrate how personality, affect, cognition, and executive functioning interact in PSNSU development.
Results support a multidimensional, mediated understanding of how negative emotions foster digital addiction.

Rationale

Problematic social networking site use (PSNSU) among youth has raised concerns due to its associations with depression, sleep disruption, and reduced well-being.

Previous studies found loneliness to be a potential contributor to PSNSU, yet findings remain inconsistent.

One reason may be the lack of clarity in differentiating normal social networking from problematic use and failing to account for mediating variables.

Fear of missing out (FoMO) has emerged as a key predictor of PSNSU, but its subtypes—trait-FoMO (a stable tendency) and state-FoMO (a temporary condition)—are often conflated.

The I-PACE model offers a framework for understanding how personality predispositions (e.g., loneliness) lead to maladaptive digital behavior via affective and cognitive intermediaries.

This study builds on these theories to test whether loneliness predicts PSNSU through distinct FoMO mechanisms over time.

Method

This study followed a longitudinal design, meaning data were collected at two different time points to track how students’ feelings and behaviors changed over time.

Time Points

Time 1 (T1): In November 2022, students completed surveys measuring loneliness and problematic social networking site use (PSNSU).
Time 2 (T2): One year later, in November 2023, the same students completed follow-up surveys measuring their levels of trait-FoMO, state-FoMO, and PSNSU again.

Participants

417 Chinese college students participated in both time points.
Ages ranged from 17 to 23 years, with slightly more females than males.
Students were from first, second, and third year of university.
The small number of students who didn’t complete the second survey were not different in key ways from those who did, so their absence didn’t affect the results.

Measures

Loneliness: Measured how often students felt socially isolated or lacking in meaningful connection.
Trait-FoMO: Assessed general, ongoing worry about missing out on fun or rewarding experiences that others are having.
State-FoMO: Measured short-term or in-the-moment anxiety while online, such as checking for updates or fearing they missed something important.
PSNSU: Evaluated signs of social networking overuse, such as constant checking, needing to be online first thing in the morning, or difficulty stopping.

Procedure

Students were invited through university announcements and completed paper surveys in class. Participation was voluntary and confidential.

Researchers explained the purpose, and students gave written consent. Data collection was supervised by trained graduate students to ensure everything was done properly.

Results

The study explored how loneliness influences problematic social networking site use over time, and whether different types of FoMO help explain this connection.

Here are the main findings:

Students who felt lonelier at the first time point were more likely to report higher FoMO and greater social networking problems one year later.
Loneliness did appear to predict problematic social networking site use, but this link disappeared once the researchers considered FoMO. This means FoMO might explain why loneliness leads to increased online problems.
Trait-FoMO acted as a key link between loneliness and PSNSU. Students who were lonelier were more likely to feel a constant fear of missing out, and those students were in turn more likely to overuse social networking sites.
State-FoMO, by itself, was not strongly influenced by loneliness. However, it did play a role when combined with trait-FoMO. Students with high trait-FoMO were more likely to experience momentary anxiety while online (state-FoMO), which then contributed to PSNSU.
In other words, loneliness led to higher trait-FoMO, which led to higher state-FoMO, and both of those contributed to more problematic social networking over time.
Trait-FoMO was found to be a more powerful and lasting influence, acting like a personality trait that makes people more vulnerable to overuse of social media.
State-FoMO was more of an immediate, in-the-moment feeling, and it was closely tied to checking behaviors and compulsive online use

Insight

The study revealed that loneliness contributes to PSNSU not directly but through internal dispositions and social anxieties reflected in FoMO.

Trait-FoMO emerges from unmet social needs and can trigger state-FoMO, which is context-specific and directly linked to excessive social networking.

This nuance helps refine the understanding of digital addiction by identifying both stable and reactive psychological processes.

Future research could explore interventions aimed at reducing trait-FoMO or testing real-time emotional triggers of state-FoMO using ecological momentary assessment.

Implications

Practitioners and policymakers should design interventions to reduce trait-FoMO (e.g., via improved self-esteem, offline social engagement) and manage state-FoMO (e.g., via digital literacy, self-regulation).

Universities can implement mental health programs targeting FoMO to reduce PSNSU. Apps could be redesigned to reduce triggers for FoMO.

Strengths

This study had several methodological strengths, including:

Longitudinal design with a 12-month follow-up.
Clear distinction between trait and state-FoMO.
Large, statistically powered sample size.
Use of validated psychometric instruments.
Strong statistical modeling (SEM with bootstrapping).
Controlled for gender and prior PSNSU levels.

Limitations

This study also had several limitations, including:

Only two time points may limit dynamic mediation analysis.
Self-report data may introduce bias or social desirability effects.
Sample restricted to one region in China; limits generalizability.
Lacks qualitative or behavioral data to complement findings.
Trait- and state-FoMO distinctions need further theoretical clarity.

Socratic Questions

How does distinguishing between trait and state-FoMO enhance our understanding of digital behavior?
Could PSNSU be a coping strategy for emotional distress rather than a cause of distress?
What alternative explanations might exist for the mediation pathway identified?
How might interventions differ if they target trait-FoMO versus state-FoMO?
Would the same relationships hold in older adults or younger adolescents?
How might cultural norms in China shape the relationship between loneliness and social media use?
Can the I-PACE model be extended to other forms of behavioral addiction beyond social networking?
How might peer influence or offline social networks buffer the impact of loneliness on PSNSU?
Would real-time behavioral data (e.g., phone use tracking) confirm the self-reported PSNSU trends?
Should tech companies be responsible for designing platforms that reduce FoMO triggers?

The relationship between loneliness and problematic social networking site use in college students