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Nevin Manimala Statistics

Google Trends and seasonal patterns of dementia in Taiwan and globally

BMC Psychol. 2025 Dec 18. doi: 10.1186/s40359-025-03849-9. Online ahead of print.

ABSTRACT

BACKGROUND: This study investigates dementia-related search behaviors using Google Trends and national data from Taiwan, examining temporal trends, seasonal patterns with a focus on both Taiwan and global comparisons.

METHODS: We collected Google Trends data for dementia-related search terms from 2014 to 2024 and retrieved official Taiwanese dementia diagnosis data. Analytical approaches included descriptive statistics, Fourier-based regression for seasonal trend analysis, seasonal-trend decomposition, and Pearson correlation to assess the relationship between GT search volume and diagnosed dementia cases.

RESULTS: Search interest in dementia increased both globally and in Taiwan over the study period, with sharper fluctuations and a pronounced surge in Taiwan beginning in 2023. Seasonal trends revealed consistent peaks in certain months. In Taiwan, top and rising queries reflected clinical and caregiving concerns, while global searches were more general. A strong positive correlation was observed between Google Trends scores and diagnosed dementia cases in Taiwan (r ≈ 0.8).

CONCLUSIONS: Google Trends offers valuable insights into public interest in dementia and holds promise as a monitoring tool, particularly in aging societies and during health crises such as the COVID-19 pandemic.

PMID:41408340 | DOI:10.1186/s40359-025-03849-9

By Nevin Manimala

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