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|Title:||Can online support groups address psychological morbidity of cancer patients? An artificial intelligence based investigation of prostate cancer trajectories.||Austin Authors:||Adikari, Achini;de Silva, Daswin;Ranasinghe, Weranja K B;Bandaragoda, Tharindu;Alahakoon, Oshadi;Persad, Raj;Lawrentschuk, Nathan;Alahakoon, Damminda;Bolton, Damien M||Affiliation:||EJ Whitten Prostate Cancer Research Centre at Epworth Healthcare, Melbourne, Australia
Department of Surgery, Austin Health, The University of Melbourne, Heidelberg, Victoria, Australia
Division of Cancer Surgery, Peter MacCallum Cancer Centre, Melbourne, Australia
Olivia Newton-John Cancer Wellness and Research Centre, Austin Health, Heidelberg, Victoria, Australia
Research Centre for Data Analytics and Cognition, La Trobe University, Bundoora, Victoria, Australia
College of Engineering and Science, Victoria University, Heidelberg, Victoria, Australia
MD Anderson Cancer Center, University of Texas, Houston, Texas..
NHS Trust, North Bristol, England, United Kingdom..
|Issue Date:||4-Mar-2020||metadata.dc.date:||2020-03-04||Publication information:||PLoS One 2020; 15(3): e0229361||Abstract:||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. 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. 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<0.01). A comparison of pre-treatment vs post-treatment emotions showed that joining pre-treatment had significantly lower negative emotions after 12-months compared to post-treatment (p<0.05). Long-term deep emotion analysis reveals that all groups except 'recurrence' improved in emotional wellbeing. This is the first empirical study of psychological morbidity and deep emotions expressed by men with a new diagnosis of cancer, using AI. PCa patients joining pre-treatment had improved emotions, and long-term participation in OCSG led to an increase in emotional wellbeing, indicating a decrease in psychological distress. It is opportune to further investigate AI in OCSG for early psychological intervention as an adjunct to conventional intervention programs.||URI:||http://ahro.austin.org.au/austinjspui/handle/1/22753||DOI:||10.1371/journal.pone.0229361||ORCID:||0000-0001-5112-5063
|PubMed URL:||32130256||Type:||Journal Article|
|Appears in Collections:||Journal articles|
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