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

Prevention and Health Promotion (1428) Crowdsourcing and Mechanical Turks (103) Substance Abuse (547) Alcohol Abuse, Alcoholism Prevention and Recovery (348)

Published on in Vol 7, No 4 (2021): April

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/23872, first published .
The Psychosocial Predictors and Day-Level Correlates of Substance Use Among Participants Recruited via an Online Crowdsourcing Platform in the United States: Daily Diary Study

The Psychosocial Predictors and Day-Level Correlates of Substance Use Among Participants Recruited via an Online Crowdsourcing Platform in the United States: Daily Diary Study

The Psychosocial Predictors and Day-Level Correlates of Substance Use Among Participants Recruited via an Online Crowdsourcing Platform in the United States: Daily Diary Study

Authors of this article:

Jennifer Payaal Jain1 Author Orcid Image ;   Claudine Offer1 Author Orcid Image ;   Christopher Rowe2 Author Orcid Image ;   Caitlin Turner3 Author Orcid Image ;   Carol Dawson-Rose1 Author Orcid Image ;   Thomas Hoffmann3 Author Orcid Image ;   Glenn-Milo Santos1 Author Orcid Image
Article Authors Cited by (5) Tweetations (4) Metrics

Journals

  1. Agley J, Xiao Y, Nolan R, Golzarri-Arroyo L. Quality control questions on Amazon’s Mechanical Turk (MTurk): A randomized trial of impact on the USAUDIT, PHQ-9, and GAD-7. Behavior Research Methods 2022;54(2):885 View
  2. Sinclair E, Punia K, Tabri N, Balodis I, Kim H. Who Engages in Simultaneous Gambling and Alcohol Use, and Why? A Mixed-Method Study. Journal of Gambling Studies 2025;41(2):857 View
  3. Sun Y, Mo P. Depression, positive affect, and sexual behavior: a moderated mediation model of drug use among men who have sex with men in Hong Kong. Journal of Affective Disorders 2025;382:107 View
  4. Deng H, Kandt J, Signorelli V, Shelton N. Daily mobility, greenspace exposure and affective states: A systematic review of studies that use mobile methods. Landscape and Urban Planning 2025;262:105407 View
  5. Zamora G, Gunawan T, Zhao Q, Meruelo A. Comparing random forest and elastic net models to predict substance use disorder transitions in participants with cannabis and stimulant use: Evidence from the All of Us cohort. Drug and Alcohol Dependence 2026;278:113012 View