Review of "Development and Application of a Fear of Missing Out Scale for College Students' Mobile Social Media Use" (DOI: 10.13266/j.issn.0252-3116.2019.05.013)

Academic fraud report · Geng Detector

Summary

This review assesses a 2019 scale-development paper published in Library and Information Service (图书情报工作) by Ye Fengyun and Li Junjun on mobile social media fear-of-missing-out (FoMO) in Chinese university students. The overall verdict is "questionable" — no definitive evidence of fraud was identified, but multiple formal and methodological concerns warrant follow-up. The most striking issue is that references [1] and [3] cite the identical Przybylski et al. (2013) paper in full, used to support two separate claims; this is most plausibly a copy-paste editing error rather than deliberate fabrication. Exploratory factor analysis results map cleanly onto the four pre-specified dimensions after deleting three cross-loading items, an unusually tidy pattern in social-science data. Sampling is highly imbalanced (Hefei 67.8%, Hangzhou 21.5%, Nanjing 10.7%), and the closing claim that high-FoMO concentration in one major demonstrates discriminant validity is logically strained, though the underlying figures were genuinely reported. Confidence is limited because the assessment is text-based; raw data, SPSS syntax, and random seeds remain private.

Verdict

Questionable (🟡). No conclusive evidence of data fabrication or scientific misconduct was found; however, the paper contains formal reference errors, a suspiciously clean EFA structure, and interpretational overreach that collectively warrant author clarification and data release.

Key findings

Duplicate reference entry: References [1] and [3] are identical (Przybylski A.K., Kou M., Dehaan C.R., et al. "Motivational, emotional, and behavioral correlates of fear of missing out", *Computers in Human Behavior*, 2013, 29(4): 1841-1848), used to support two distinct claims. Most consistent explanation: editorial/compilation error rather than fabrication.
Unusually clean EFA structure: After deleting S10, B3, and B8, the remaining 32 items load almost perfectly on the four pre-specified dimensions (情景/行为/结果/心理). Such a tidy match is uncommon in social-science data but is plausible when items were authored to fit a predefined theoretical framework (Przybylski et al. + STAR interview protocol).
Severe sampling imbalance: Table 10 shows Hefei n=559 (67.8%), Hangzhou n=177 (21.5%), Nanjing n=88 (10.7%); Hefei sample is 6.35× the Nanjing sample. Consistent with first-author institutional convenience but limits generalizability.
Discriminant-validity overreach: The closing argument equates a 60% high-FoMO concentration in one major (Anhui University, n=21/35) at the "information management and information systems" major with "clear discriminant validity" of the scale; this conflates within-group concentration with cross-group differentiation. Table 18 does show differing distribution shapes across schools (安徽 21/7/7; 南京 18/?; 杭州 14/11/10), so the claim has a descriptive basis but is imprecisely framed.
Sample split follows standard practice: 410 + 414 split for EFA / CFA using Anderson & Gerbing (1988) two-step procedure, as described in §3.3. No anomaly detected.
Item deletion rule applied consistently: Items B1 (CITC=.222, CAID=.767 vs α=.755) and R4 (CITC=.141, CAID=.786 vs α=.765) deleted per the stated CITC<0.4 & CAID>dimension-α criterion; other items retained. Execution matches the protocol.

Evidence highlights

DOI: 10.13266/j.issn.0252-3116.2019.05.013
Publication: 图书情报工作 (Library and Information Service), Vol. 63, Issue 5, March 2019, pp. 110-118.
Reference [1] verbatim: "PRZYBYLSKI A K，KOU M，DEHAAN C R，et al. Motivational, emotional, and behavioral correlates of fear of missing out[J]. Computers in human behavior, 2013, 29(4): 1841-1848." — identical to reference [3].
Table 12 rotated component matrix: S1–S9 → Component 1; B2/B4/B5/B6/B7/B9 → Component 2; R1–R3, R5–R10 → Component 3; P1–P8 → Component 4; S10, B3, B8 removed for cross-loading.
Table 13 labelled "四维度模型" with item counts 9/6/9/8.
Table 10 city distribution: 合肥 559 (67.8%) / 杭州 177 (21.5%) / 南京 88 (10.7%).
Table 18 high-FoMO counts by university/major: 安徽大学 21; 南京农业大学 18; 杭州电子科技大学 14.
Funding: 国家社会科学基金青年项目 (14CTQ024).
Preprint: ChinaXiv 202307.00568v1.

Notes

Confidence is limited because analysis is based solely on the published text; raw questionnaire data, SPSS syntax, and the random seed used for the 410/414 split were not made available and are essential for reproducing the cluster and discriminant analyses.
All "severity 🟡" findings carry plausible benign explanations reviewed in the source report; none independently rises to misconduct.
Recommended author actions: (1) merge references [1] and [3] or annotate differing usages; (2) publicly archive de-identified responses and SPSS syntax; (3) document the randomisation seed for the 410/414 split; (4) add a limitations paragraph addressing city-level sampling imbalance; (5) reword the "discriminant validity" claim in the closing paragraph.
This assessment is text-based and AI-assisted; final judgement of academic misconduct requires an institutional investigation.