The Seasonal Periodicity of Healthy Contemplations About Exercise and Weight Loss: Ecological Correlational Study

Journals

1. Madden K, Feldman B. Weekly, Seasonal, and Geographic Patterns in Health Contemplations About Sundown Syndrome: An Ecological Correlational Study. JMIR Aging 2019;2(1):e13302 View
2. Teng Y, Huang S, Li Z, Xie Q, Zhang M, Lou Q, Wang F, Zou Y. Seasonal variation and trends in the Internet searches for losing weight: An infodemiological study. Obesity Research & Clinical Practice 2020;14(3):225 View
3. Ganasegeran K, Ch’ng A, Aziz Z, Looi I. Population’s health information-seeking behaviors and geographic variations of stroke in Malaysia: an ecological correlation and time series study. Scientific Reports 2020;10(1) View
4. Cavazzotto T, Ronque E, Vieira E, Queiroga M, Serassuelo Junior H. Social-Ecological Correlates of Regular Leisure-Time Physical Activity Practice among Adults. International Journal of Environmental Research and Public Health 2020;17(10):3619 View
5. Mavragani A. Infodemiology and Infoveillance: Scoping Review. Journal of Medical Internet Research 2020;22(4):e16206 View
6. Waring M, Jake-Schoffman D, Holovatska M, Mejia C, Williams J, Pagoto S. Social Media and Obesity in Adults: a Review of Recent Research and Future Directions. Current Diabetes Reports 2018;18(6) View
7. Kumar N, Pandey A, Garg N, Sampene E, Lavie C. Seasonal and Geographic Patterns in Seeking Cardiovascular Health Information: An Analysis of the Online Search Trends. Mayo Clinic Proceedings 2018;93(9):1185 View
8. Almenara C, Machackova H, Smahel D. Sociodemographic, Attitudinal, and Behavioral Correlates of Using Nutrition, Weight Loss, and Fitness Websites: An Online Survey. Journal of Medical Internet Research 2019;21(4):e10189 View
9. Dzaye O, Adelhoefer S, Boakye E, Blaha M. Cardiovascular-related health behaviors and lifestyle during the COVID-19 pandemic: An infodemiology study. American Journal of Preventive Cardiology 2021;5:100148 View
10. Park M, Wang J, Bulwer B. Global Dieting Trends and Seasonality: Social Big-Data Analysis May Be a Useful Tool. Nutrients 2021;13(4):1069 View
11. Fabbian F, Rodríguez-Muñoz P, López-Carrasco J, Cappadona R, Rodríguez-Borrego M, López-Soto P. Google Trends on Obesity, Smoking and Alcoholism: Global and Country-Specific Interest. Healthcare 2021;9(2):190 View
12. Frazer J, Frazer G. Analysis of primary care prescription trends in England during the COVID-19 pandemic compared against a predictive model. Family Medicine and Community Health 2021;9(3):e001143 View
13. Kamiński M, Kręgielska-Narożna M, Bogdański P. Seasonal variation in lifestyle behavior in Poland: Google searches and market sales analysis. BMC Public Health 2021;21(1) View
14. Madden K, Feldman B. Anosmia-related internet search and the course of the first wave of the COVID-19 pandemic in the United States. Heliyon 2021;7(12):e08499 View
15. Kim J, Park M. A New Body Weight Lifelog Outliers Generation Method: Reflecting Characteristics of Body Weight Data. Applied Sciences 2022;12(9):4726 View
16. Murakami K, Shinozaki N, Okuhara T, McCaffrey T, Livingstone M. Prevalence and Correlates of Dietary and Nutrition Information Seeking Through Various Web-Based and Offline Media Sources Among Japanese Adults: Web-Based Cross-Sectional Study. JMIR Public Health and Surveillance 2024;10:e54805 View
17. Almenara C, Gulec H. Uncovering the Top Nonadvertising Weight Loss Websites on Google: A Data-Mining Approach. JMIR Infodemiology 2024;4:e51701 View