Published on in Vol 5, No 2 (2018): Apr-Jun

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/9152, first published .
Diurnal Variations of Depression-Related Health Information Seeking: Case Study in Finland Using Google Trends Data

Diurnal Variations of Depression-Related Health Information Seeking: Case Study in Finland Using Google Trends Data

Diurnal Variations of Depression-Related Health Information Seeking: Case Study in Finland Using Google Trends Data

Journals

  1. Zepecki A, Guendelman S, DeNero J, Prata N. Using Application Programming Interfaces to Access Google Data for Health Research: Protocol for a Methodological Framework. JMIR Research Protocols 2020;9(7):e16543 View
  2. Strzelecki A. Google Medical Update: Why Is the Search Engine Decreasing Visibility of Health and Medical Information Websites?. International Journal of Environmental Research and Public Health 2020;17(4):1160 View
  3. Adler N, Cattuto C, Kalimeri K, Paolotti D, Tizzoni M, Verhulst S, Yom-Tov E, Young A. How Search Engine Data Enhance the Understanding of Determinants of Suicide in India and Inform Prevention: Observational Study. Journal of Medical Internet Research 2019;21(1):e10179 View
  4. Mavragani A. Infodemiology and Infoveillance: Scoping Review. Journal of Medical Internet Research 2020;22(4):e16206 View
  5. Huvila I, Enwald H, Eriksson‐Backa K, Liu Y, Hirvonen N. Information behaviour and practises research informing technology and service design. Proceedings of the Association for Information Science and Technology 2019;56(1):541 View
  6. Mavragani A, Ochoa G. Google Trends in Infodemiology and Infoveillance: Methodology Framework. JMIR Public Health and Surveillance 2019;5(2):e13439 View
  7. Anastasiou M, Pantavou K, Yiallourou A, Bonovas S, Nikolopoulos G. Trends of Online Search of COVID-19 Related Terms in Cyprus. Epidemiologia 2021;2(1):36 View
  8. Yu S, Eisenman D, Han Z. Temporal Dynamics of Public Emotions During the COVID-19 Pandemic at the Epicenter of the Outbreak: Sentiment Analysis of Weibo Posts From Wuhan. Journal of Medical Internet Research 2021;23(3):e27078 View
  9. Mack D, DaSilva A, Rogers C, Hedlund E, Murphy E, Vojdanovski V, Plomp J, Wang W, Nepal S, Holtzheimer P, Wagner D, Jacobson N, Meyer M, Campbell A, Huckins J. Mental Health and Behavior of College Students During the COVID-19 Pandemic: Longitudinal Mobile Smartphone and Ecological Momentary Assessment Study, Part II. Journal of Medical Internet Research 2021;23(6):e28892 View
  10. Becerra-García J, Sánchez-Gutiérrez T, Barbeito S, Calvo A. COVID-19 pandemic and mental health in Spain: An analysis of their relationship using Google Trends. Spanish Journal of Psychiatry and Mental Health 2023;16(4):215 View
  11. Davison-Kerwood M, Jiang S, Gonzalez1 M. Orthopaedic Surgical Demand Index: A Measure of Need in the United States. JAAOS: Global Research and Reviews 2022;6(11) View
  12. Jiang S, Davison-Kerwood M, Gonzalez M. Increased Rate of Fracture Injuries Associated With Alternative Modes of Transportation During COVID-19. JAAOS: Global Research and Reviews 2022;6(9) View
  13. Monzani D, Vergani L, Marton G, Pizzoli S, Pravettoni G. When in doubt, Google it: distress-related information seeking in Italy during the COVID-19 pandemic. BMC Public Health 2021;21(1) View
  14. Deiner M, Kaur G, McLeod S, Schallhorn J, Chodosh J, Hwang D, Lietman T, Porco T. A Google Trends Approach to Identify Distinct Diurnal and Day-of-Week Web-Based Search Patterns Related to Conjunctivitis and Other Common Eye Conditions: Infodemiology Study. Journal of Medical Internet Research 2022;24(7):e27310 View

Books/Policy Documents

  1. Heinz M, Thomas N, Nguyen N, Griffin T, Jacobson N. Comprehensive Clinical Psychology. View
  2. . Dealing With Change Through Information Sculpting. View