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Analyzing Patient Interactions within Cancer Support Groups

This study examines the effectiveness of online support groups for cancer patients and the potential for predicting health outcomes. Sentiment analysis and topic association reveal key trends in patients' experiences. The study suggests that leveraging online support group data can improve clinical outcomes for cancer patients.

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Analyzing Patient Interactions within Cancer Support Groups

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  1. Analyzing Patient Interactions within Cancer Support Groups Zhenghao Chen, Pang Wei Koh Together with: Marc Rasi, SuchiSaria, Daphne Koller Katy Plant, Philip Ritter and Kate Lorig

  2. Cancer • Leading cause of death in the developed world • Treatment: • Chemotherapy • Surgery • Radiotherapy • Threat of recurrence • Management of cancer survivors is important very debilitating!

  3. Traditional Peer Support Groups

  4. Online Peer Support Groups

  5. Some Questions • Do online support groups work? • Can we discover better clinical practices? • Can we predict health outcomes more accurately?

  6. Sentiment Trends

  7. Sentiment-Topic Association • cancer treatment years year breast chemo back recurrence months treatments pain diagnosis diagnosed oncologist ll finished dx told doctor • side therapy scan don blood scars lymphedema radiation onc scar eects arm surgeon results physical reconstruction follow doctor pain • love kids year mom cat joy dogs years cats husband son home watching funny place sound house christmas watch

  8. Sentiment-Topic Association • sleep bed night work hours sleeping nights stressed trouble earlier early late schedule tired morning ready music problems times • plan action week peggy great days tools plans specific make session exercise walking confidence level completing time good complete

  9. Outcome Prediction

  10. Conclusion • Data from online groups is plentiful and untapped • It seems to work even with a small dataset • Scaling up might help us improve clinical outcomes for cancer patients

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