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Natural Language Processing-Based Virtual Cofacilitator for Online Cancer Support Groups: Protocol for an Algorithm

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An AI cofacilitator prototype was developed to monitor online cancer support group participants for distress in real time. This tool analyzes text messages to alert therapists, enhancing patient care and support group effectiveness.

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Area of Science:

  • Oncology
  • Psychology
  • Computer Science
  • Artificial Intelligence

Background:

  • Cancer and its treatments significantly impact patient and family psychological well-being.
  • Online support groups offer accessible alternatives to in-person meetings, but therapists face challenges in monitoring distress via text.
  • Artificial intelligence (AI) and natural language processing (NLP) present potential solutions for real-time distress detection in online support settings.

Purpose of the Study:

  • To develop and evaluate an AI-based cofacilitator prototype.
  • To track and monitor distress in online support group participants through real-time text message analysis.
  • To enhance therapist's ability to identify and respond to participant distress during synchronous sessions.

Main Methods:

  • Development of an AI cofacilitator using NLP.
  • Identification of participants at risk for emotional distress.
  • Tracking participant engagement and group cohesion with real-time alerts.
  • Generation of post-session participant profiles and resource suggestions.
  • Phased study including development, performance evaluation, beta testing, and user experience evaluation.

Main Results:

  • Phase 1 (development) was completed in January 2020.
  • Phase 2 (performance evaluation) was underway as of December 2020.
  • The study is anticipated to conclude by September 2021.

Conclusions:

  • An AI-based cofacilitator shows promise for delivering personalized online support groups.
  • This technology can tailor support to individual patient needs.
  • AI offers a novel approach to enhance the effectiveness and reach of online cancer support.