Smartphone Overuse and Relationship Dissatisfaction: The Mediating Role of Fear of Missing Out (FoMO)
Bibliographic record
Abstract
Objective: The objective of this study was to investigate the relationship between smartphone overuse and relationship dissatisfaction among young adults, with a specific focus on examining the mediating role of fear of missing out (FoMO). Methods and Materials: A descriptive correlational design was employed, involving a sample of 400 young adults recruited from Manchester, United Kingdom. The sample size was determined based on the Morgan and Krejcie table to ensure adequate statistical power. Participants completed three validated instruments: the Smartphone Addiction Scale–Short Version (SAS-SV) for smartphone overuse, the Fear of Missing Out Scale (FoMOS) for FoMO, and the Couples Satisfaction Index (CSI-16) for relationship dissatisfaction. Data analysis was conducted using SPSS-27 for descriptive statistics and Pearson correlation analyses, while Structural Equation Modeling (SEM) was performed with AMOS-21 to test the hypothesized mediational model. Findings: Pearson correlations revealed significant positive associations between smartphone overuse, FoMO, and relationship dissatisfaction (all p < .001). Model fit indices indicated acceptable fit (χ²/df = 2.01, CFI = .96, TLI = .95, RMSEA = .051), supporting the robustness of the mediational model. Smartphone overuse significantly predicted FoMO (β = .48, p < .001) and relationship dissatisfaction both directly (β = .29, p < .001) and indirectly through FoMO (β = .17, p = .002). The total effect of smartphone overuse on relationship dissatisfaction was β = .46 (p < .001), confirming the mediating role of FoMO in this relationship. Conclusion: The findings underscore the need for interventions that address not only digital dependency but also the psychological mechanisms, such as FoMO, that intensify relational strain in the digital age.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".