Published on in Vol 9 , No 4 (2020) :April

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/15610, first published .
Reducing Drinking Among People Experiencing Homelessness: Protocol for the Development and Testing of a Just-in-Time Adaptive Intervention

Reducing Drinking Among People Experiencing Homelessness: Protocol for the Development and Testing of a Just-in-Time Adaptive Intervention

Reducing Drinking Among People Experiencing Homelessness: Protocol for the Development and Testing of a Just-in-Time Adaptive Intervention

Journals

  1. Reitzel L, Chinamuthevi S, Daundasekara S, Hernandez D, Chen T, Harkara Y, Obasi E, Kendzor D, Businelle M. Association of Problematic Alcohol Use and Food Insecurity among Homeless Men and Women. International Journal of Environmental Research and Public Health 2020;17(10):3631 View
  2. Golbus J, Dempsey W, Jackson E, Nallamothu B, Klasnja P. Microrandomized Trial Design for Evaluating Just-in-Time Adaptive Interventions Through Mobile Health Technologies for Cardiovascular Disease. Circulation: Cardiovascular Quality and Outcomes 2021;14(2) View
  3. Balaskas A, Schueller S, Cox A, Doherty G, Myers B. Ecological momentary interventions for mental health: A scoping review. PLOS ONE 2021;16(3):e0248152 View
  4. Mun E, Li X, Businelle M, Hébert E, Tan Z, Barnett N, Walters S. Ecological Momentary Assessment of Alcohol Consumption and Its Concordance with Transdermal Alcohol Detection and Timeline Follow‐Back Self‐report Among Adults Experiencing Homelessness. Alcoholism: Clinical and Experimental Research 2021;45(4):864 View
  5. Walters S, Businelle M, Suchting R, Li X, Hébert E, Mun E. Using machine learning to identify predictors of imminent drinking and create tailored messages for at-risk drinkers experiencing homelessness. Journal of Substance Abuse Treatment 2021;127:108417 View
  6. Abo-Tabik M, Benn Y, Costen N. Are Machine Learning Methods the Future for Smoking Cessation Apps?. Sensors 2021;21(13):4254 View