Published on in Vol 24, No 12 (2022): December

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/41527, first published .
Characterizing Help-Seeking Searches for Substance Use Treatment From Google Trends and Assessing Their Use for Infoveillance: Longitudinal Descriptive and Validation Statistical Analysis

Characterizing Help-Seeking Searches for Substance Use Treatment From Google Trends and Assessing Their Use for Infoveillance: Longitudinal Descriptive and Validation Statistical Analysis

Characterizing Help-Seeking Searches for Substance Use Treatment From Google Trends and Assessing Their Use for Infoveillance: Longitudinal Descriptive and Validation Statistical Analysis

Journals

  1. Severson M, Onanong S, Dolezal A, Bartelt-Hunt S, Snow D, McFadden L. Analysis of Wastewater Samples to Explore Community Substance Use in the United States: Pilot Correlative and Machine Learning Study. JMIR Formative Research 2023;7:e45353 View
  2. Russell A, Acuff S, Kelly J, Allem J, Bergman B. ChatGPT‐4: Alcohol use disorder responses. Addiction 2024;119(12):2205 View
  3. Nicholls M, Almeida A, Castello J, Grelotti D, Daugherty B, Gann Jr D, Lenyoun K, Trillo-Park S, Borquez A. Assessing the Safety, User Acceptability, Dissemination, and Reach of a Comprehensive Web-Based Resource on Medications for Opioid Use Disorder (MOUD Hub): Protocol for a Development and Usability Study. JMIR Research Protocols 2024;13:e57065 View