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

Special Issue on Computing and Mental Health (2018) (33) Peer-to-Peer Support and Online Communities (636) Natural Language Processing (692) Substance Abuse (419) Machine Learning (1465) Linguistics, Comprehension, and Learning (52)

Published on in Vol 20, No 6 (2018): June

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/10136, first published .
Detecting Recovery Problems Just in Time: Application of Automated Linguistic Analysis and Supervised Machine Learning to an Online Substance Abuse Forum

Detecting Recovery Problems Just in Time: Application of Automated Linguistic Analysis and Supervised Machine Learning to an Online Substance Abuse Forum

Detecting Recovery Problems Just in Time: Application of Automated Linguistic Analysis and Supervised Machine Learning to an Online Substance Abuse Forum

Authors of this article:

Rachel Kornfield1 Author Orcid Image ;   Prathusha K Sarma2 Author Orcid Image ;   Dhavan V Shah1 Author Orcid Image ;   Fiona McTavish3 Author Orcid Image ;   Gina Landucci3 Author Orcid Image ;   Klaren Pe-Romashko3 Author Orcid Image ;   David H Gustafson3 Author Orcid Image
Article Authors Cited by (26) Tweetations (9) Metrics

Journals

  1. Bergman B, Wu W, Marsch L, Crosier B, DeLise T, Hassanpour S. Associations Between Substance Use and Instagram Participation to Inform Social Network–Based Screening Models: Multimodal Cross-Sectional Study. Journal of Medical Internet Research 2020;22(9):e21916 View
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  8. Bergman B, Kelly J. Online digital recovery support services: An overview of the science and their potential to help individuals with substance use disorder during COVID-19 and beyond. Journal of Substance Abuse Treatment 2021;120:108152 View
  9. Aggarwal N, Ahmed M, Basu S, Curtin J, Evans B, Matheny M, Nundy S, Sendak M, Shachar C, Shah R, Thadaney-Israni S. Advancing Artificial Intelligence in Health Settings Outside the Hospital and Clinic. NAM Perspectives 2020 View
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  11. Davis-Martin R, Alessi S, Boudreaux E. Alcohol Use Disorder in the Age of Technology: A Review of Wearable Biosensors in Alcohol Use Disorder Treatment. Frontiers in Psychiatry 2021;12 View
  12. Klingemann J, Wieczorek Ł. Mobile application recovery support for patients with an alcohol use disorder. Acceptance, usability, and perceived helpfulness. Journal of Addictive Diseases 2022;40(4):559 View
  13. Cresta Morgado P, Carusso M, Alonso Alemany L, Acion L. Practical foundations of machine learning for addiction research. Part I. Methods and techniques. The American Journal of Drug and Alcohol Abuse 2022;48(3):260 View
  14. Chia A, Zhang M. Digital phenotyping in psychiatry: A scoping review. Technology and Health Care 2022;30(6):1331 View
  15. Yang F, Shah D, Tahk A, Vjorn O, Dietz S, Pe-Romashko K, Bailey E, Gicquelais R, Hwang J, Gustafson D, Westergaard R. mHealth and social mediation: Mobile support among stigmatized people living with HIV and substance use disorder. New Media & Society 2023;25(4):702 View
  16. Guasti M, Alexiadou A, Sauerland U. Undercompression errors as evidence for conceptual primitives. Frontiers in Psychology 2023;14 View
  17. Yang E, Kornfield R, Liu Y, Chih M, Sarma P, Gustafson D, Curtin J, Shah D. Using Machine Learning of Online Expression to Explain Recovery Trajectories: Content Analytic Approach to Studying a Substance Use Disorder Forum. Journal of Medical Internet Research 2023;25:e45589 View
  18. Yang Q, Ledbetter A, Zhuang J, Richards A. Theme and sentiment of posts in a weight loss subreddit predict popularity, engagement, and users’ weight loss: a computational approach. Human Communication Research 2023;49(4):452 View
  19. Belanger M, Sondhi A, Mericle A, Leidi A, Klein M, Collinson B, Patton D, White W, Chen H, Grimes A, Conner M, De Triquet B, Best D. Assessing a pilot scheme of intensive support and assertive linkage in levels of engagement, retention, and recovery capital for people in recovery housing using quasi-experimental methods. Journal of Substance Use and Addiction Treatment 2024;158:209283 View

Books/Policy Documents

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