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Publication

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

Rachel Kornfield | Prathusha K Sarma | Dhavan V Shah | Fiona McTavish | Gina Landucci | Klaren Pe-Romashko | David H Gustafson
Journal of medical Internet research | 2018

Online discussion forums allow those in addiction recovery to seek help through text-based messages, including when facing triggers to drink or use drugs. Trained staff (or "moderators") may participate within these forums to offer guidance and support when participants are struggling but must expend considerable effort to continually review new content. Demands on moderators limit the scalability of evidence-based digital health interventions.

Pubmed ID: 29895517

Research resources used in this publication

None found

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Antibodies used in this publication

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Associated grants

  • Agency: NIDA NIH HHS, United States
    Id: DP2 DA042424
  • Agency: NIAAA NIH HHS, United States
    Id: R01 AA017192
  • Agency: NIDA NIH HHS, United States
    Id: R01 DA034279
  • Agency: NIDA NIH HHS, United States
    Id: R01 DA040449

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scikit-learn (tool)

RRID:SCR_002577

scikit-learn: machine learning in Python

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The Stimulating Peripheral Activity to Relieve Conditions (SPARC) effort is the result of National Institutes of Health’s (NIH) drive to map out the neural circuitry responsible for visceral control in higher vertebrates. The SPARC Anatomy Working Group (SAWG) is responsible for the integrity of anatomical knowledge in SPARC

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