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FinTech and older adults: a global synthesis of enablers, barriers, and research trends for inclusive digital finance

Authors: Anupama S,Angan Sengupta
Journal: Humanities and Social Sciences Communications
Publisher: Springer Science and Business Media LLC
Publish date: 2025-11-20
ISSN: 2662-9992 DOI: 10.1057/s41599-025-06077-z
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1. In Table 2: The US shows 1,166 citations in the VOSviewer panel (46 documents) but 12,686 citations in the Scopus panel (12 documents). China similarly jumps from 8,805 to 37,628 citations. This ~10-fold difference suggests a serious data extraction or reporting error. How do you explain this impossibility?

2. Figure 4: You report a “gradient change of 9.826 (SE=0.725)” from pre- to post-COVID. But with only 3-4 post-COVID data points (2021-2025), your standard error is likely severely underestimated. Did you test for autocorrelation or use Newey-West standard errors? Without this, your significant p-value is meaningless.

3. Your PRISMA flow diagram (Fig. 3) shows 204 documents retained, but your country analysis in Table 2 (first panel) only accounts for 46+37+25+9+12+… summing to far fewer than 204 documents. Where did the remaining ~100 countries’ publications go?

4. The “55 most-cited articles” selection introduces fatal bias. You claim to reduce bias against recent publications, but a 2024 paper cannot mathematically compete with a 2015 paper in raw citations. Why not use citation velocity (citations/year) or percentile rank to avoid systematically excluding methodologically superior recent research?

5. You report two researchers independently coded themes, but provide no inter-rater reliability coefficient (e.g., Cohen’s kappa). With subjective constructs like “psychological dimensions of caregiving,” what was your agreement rate?

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