This paper is in the following e-collection/theme issue:

Depression and Mood Disorders; Suicide Prevention (1392) Big Data (245) Infodemiology and Infoveillance (1369) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1050) Digital Mental Health Interventions, e-Mental Health and Cyberpsychology (1565) GIS (Geographic Information Systems) Applications in Public Health and Spatial Epidemiology (113) Mental Health Surveillance and Epidemiology (64) Innovative Methods in Public Health and Surveillance (336) Surveillance Systems (466)

Published on in Vol 9, No 3 (2022): March

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/35253, first published .
Utilizing Big Data From Google Trends to Map Population Depression in the United States: Exploratory Infodemiology Study

Utilizing Big Data From Google Trends to Map Population Depression in the United States: Exploratory Infodemiology Study

Utilizing Big Data From Google Trends to Map Population Depression in the United States: Exploratory Infodemiology Study

Authors of this article:

Alex Wang1 Author Orcid Image ;   Robert McCarron1 Author Orcid Image ;   Daniel Azzam1 Author Orcid Image ;   Annamarie Stehli1 Author Orcid Image ;   Glen Xiong2 Author Orcid Image ;   Jeremy DeMartini2 Author Orcid Image
Article Authors Cited by (15) Tweetations (5) Metrics

Journals

  1. Gilbert B, Lu C, Yom-Tov E. Tracking Population-Level Anxiety Using Search Engine Data: Ecological Study. JMIR Formative Research 2023;7:e44055 View
  2. Díaz F, Henríquez P, Winkelried D. Heterogeneous responses in Google Trends measures of well-being to the COVID-19 dynamic quarantines in Chile. Scientific Reports 2022;12(1) View
  3. 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
  4. Zhou W, Zhang X, Zheng Y, Gao T, Liu X, Liang H. Psychological Impact of COVID-19 Lockdown and Its Evolution: A Case Study Based on Internet Searching Data during the Lockdown of Wuhan 2020 and Shanghai 2022. Healthcare 2023;11(3):289 View
  5. Dzaye O, Berning P, Razavi A, Adhikari R, Jha K, Nasir K, Ayers J, Mortensen M, Blaha M. Online searches for SGLT-2 inhibitors and GLP-1 receptor agonists correlate with prescription rates in the United States: An infodemiological study. Frontiers in Cardiovascular Medicine 2022;9 View
  6. Alibudbud R. Google Trends for health research: Its advantages, application, methodological considerations, and limitations in psychiatric and mental health infodemiology. Frontiers in Big Data 2023;6 View
  7. Kohlmann S, Stielow L, Löwe B. Did online information seeking for depression increase during COVID-19 lockdown times? A google trend analysis on data from Germany and the UK. Journal of Affective Disorders Reports 2023;13:100587 View
  8. Díaz F, Henríquez P, Hardy N, Ponce D. Population well-being and the COVID-19 vaccination program in Chile: evidence from Google Trends. Public Health 2023;219:22 View
  9. Gupta B, Mufti T, Sohail S, Madsen D. ChatGPT: A brief narrative review. Cogent Business & Management 2023;10(3) View
  10. Li Z, Fan Y, Su H, Xu Z, Ho H, Zheng H, Tao J, Zhang Y, Hu K, Hossain M, Zhao Q, Huang C, Cheng J. The 2022 Summer record-breaking heatwave and health information-seeking behaviours: an infodemiology study in Mainland China. BMJ Global Health 2023;8(9):e013231 View
  11. Berning P, Schroer A, Adhikari R, Razavi A, Cornelis F, Erinjeri J, Solomon S, Sarkar D, Vargas H, Schöder H, Fox J, Dzaye O. Online searches for hepatocellular carcinoma drugs mirror prescription trends across specialties and changes in guideline recommendations. Frontiers in Oncology 2024;14 View
  12. Díaz F, Henríquez P. Assessing the impact of small firm dynamics on public mental health amid the pandemic in Latin America. BMC Public Health 2024;24(1) View
  13. Pérez Rave J, Fernández Guerrero R, Salas Vallina A. Validation of a dispositional critical thinking scale using an original analytical methodology for addressing data from Google Trends. Baltic Journal of Management 2024;19(5):512 View
  14. Scherbakov D, Hubig N, Lenert L, Alekseyenko A, Obeid J. Natural Language Processing and Social Determinants of Health in Mental Health Research: An Artificial Intelligence-Assisted Scoping Review (Preprint). JMIR Mental Health 2024 View

Books/Policy Documents

  1. Polekhina S, Sinyavskaya Y. Digital Geography. View