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Can online support groups address psychological morbidity of cancer patients? An artificial intelligence based investigation of prostate cancer trajectories

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Listed:
  • Achini Adikari
  • Daswin de Silva
  • Weranja K B Ranasinghe
  • Tharindu Bandaragoda
  • Oshadi Alahakoon
  • Raj Persad
  • Nathan Lawrentschuk
  • Damminda Alahakoon
  • Damien Bolton

Abstract

Background: Online Cancer Support Groups (OCSG) are becoming an increasingly vital source of information, experiences and empowerment for patients with cancer. Despite significant contributions to physical, psychological and emotional wellbeing of patients, OCSG are yet to be formally recognised and used in multidisciplinary cancer support programs. This study highlights the opportunity of using Artificial Intelligence (AI) in OCSG to address psychological morbidity, with supporting empirical evidence from prostate cancer (PCa) patients. Methods: A validated framework of AI techniques and Natural Language Processing (NLP) methods, was used to investigate PCa patient activities based on conversations in ten international OCSG (18,496 patients- 277,805 conversations). The specific focus was on activities that indicate psychological morbidity; the reasons for joining OCSG, deep emotions and the variation from joining through to milestones in the cancer trajectory. Comparative analyses were conducted using t-tests, One-way ANOVA and Tukey-Kramer post-hoc analysis. Findings: PCa patients joined OCSG at four key phases of psychological distress; diagnosis, treatment, side-effects, and recurrence, the majority group was ‘treatment’ (61.72%). The four groups varied in expression of the intense emotional burden of cancer. The ‘side-effects’ group expressed increased negative emotions during the first month compared to other groups (p

Suggested Citation

  • Achini Adikari & Daswin de Silva & Weranja K B Ranasinghe & Tharindu Bandaragoda & Oshadi Alahakoon & Raj Persad & Nathan Lawrentschuk & Damminda Alahakoon & Damien Bolton, 2020. "Can online support groups address psychological morbidity of cancer patients? An artificial intelligence based investigation of prostate cancer trajectories," PLOS ONE, Public Library of Science, vol. 15(3), pages 1-14, March.
    • Handle: RePEc:plo:pone00:0229361
    DOI: 10.1371/journal.pone.0229361
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    References listed on IDEAS

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    1. Tharindu Rukshan Bandaragoda & Daswin De Silva & Damminda Alahakoon, 2017. "Automatic event detection in microblogs using incremental machine learning," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 68(10), pages 2394-2411, October.
    2. Tharindu Rukshan Bandaragoda & Daswin De Silva & Damminda Alahakoon & Weranja Ranasinghe & Damien Bolton, 2018. "Text Mining for Personalized Knowledge Extraction From Online Support Groups," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 69(12), pages 1446-1459, December.
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