Evidence map›Paper›PMID 41607399›Full record

ArticleFrontiers in big data2025

Dynamic patterns of healthy lifestyle awareness after COVID-19: a study using Google Trends and joinpoint regression.

Zahroh Shaluhiyah, Shabrina Arifia Qatrannada, Roshan Kumar Mahato, Farid Agushybana, Sri Handayani, Dzul Fahmi Afriyanto, Usha Rani, Dewie Sulistyorini

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Article in Frontiers in big data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Zahroh ShaluhiyahDepartment of Health Promotion, Faculty of Public Health, Diponegoro University, Semarang, Indonesia.
Shabrina Arifia QatrannadaDepartment of Health Promotion, Faculty of Public Health, Diponegoro University, Semarang, Indonesia.
Roshan Kumar MahatoDepartment of Health Management Innovative Technology, Faculty of Public Health, Khon Kaen University, Khon Kaen, Thailand.
Farid AgushybanaDepartment of Biostatistics and Demography, Faculty of Public Health, Diponegoro University, Semarang, Indonesia.
Sri HandayaniDepartment of Epidemiology, Faculty of Public Health, Dian Nuswantoro University, Semarang, Indonesia.
Dzul Fahmi AfriyantoDepartment of Health Promotion, Faculty of Public Health, Diponegoro University, Semarang, Indonesia.
Usha RaniDepartment of Health Care and Hospital Management, Prasanna School of Public Health, Manipal, India.
Dewie SulistyoriniInstitute of Biomedical and Health Sciences, Hiroshima University, Higashihiroshima, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: The COVID-19 pandemic has significantly influenced public interest in health-related behaviors, as reflected in online search trends. Analyzing these trends provides insights into shifting health concerns and informing future public health strategies. This study examined Google Trends data to assess the changes in public interest in mental health, healthy diet, sleep, screen time, physical activity, and tobacco smoking before, during, and after the COVID-19 pandemic. Methods: Google Trends data (2019-2023) were analyzed using joinpoint regression to identify statistically significant shifts in relative search volume (RSV) over time. Additionally, the Mann-Whitney U test was conducted to examine differences in mean RSV across time period. Results: Awareness that consistently increased during and after the pandemic was observed in mental health, particularly anxiety, and sleep patterns. These topics showed significant positive trends in joinpoint regression and higher mean RSVs, with statistically significant differences across time periods ( Conclusion: Digital interest in health behaviors varied during and after COVID-19, with only mental health and sleep showing sustained concern. However, spikes in awareness often reflected personally relevant issues, highlighting Google Trends' potential as an early signal for health promotion efforts.

Indexed as

digital health surveillanceGoogle Trendsinformation seeking behaviorjoinpoint regressionpublic health awareness

Identifiers

PMID41607399
PMCPMC12834755

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.