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

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<0.01). A comparison of pre-treatment vs post-treatment emotions showed that

Cancer in Lockdown: Impact of the COVID-19 Pandemic on Patients with Cancer

“…All data sources are publicly available, and the entire data extraction process was anonymized. We applied a validated artificial intelligence framework, the Patient‐Reported Information Multidimensional Exploration (PRIME) framework [5, 6] on both data sets. The PRIME framework has been effectively used for the extraction, analysis and synthesis of patient‐reported information on physical and mental well‐being, such as symptoms, side effects, treatment decisions, real‐life experiences, mental health issues, and emotional burden of patients with cancer, cancer survivors, and caregivers [7].…”

“…All data sources are publicly available, and the entire data extraction process was anonymized. We applied a validated artificial intelligence framework, the Patient-Reported Information Multidimensional Exploration (PRIME) framework [5,6]…”

Prostate Cancer Support Groups: The Unadvertised Camaraderie

“…Men have been found to join PCSG at specific points in their disease process. Adikari, et al showed PCa patients join online support groups at four specific psychological phases: diagnosis, treatment, side-effects, and recurrence, with 67% of patients joining at the time of treatment initiation [25]. Carter, et al (2011) reported patients with advanced PCa are more likely to seek PCSGs and desire stage-specific information to address concerns about the diagnosis [26].…”

Emotions of COVID-19: Content Analysis of Self-Reported Information Using Artificial Intelligence

“…Given the volume and variety of content being shared on social media, online behaviors have been investigated as a proxy for offline human behaviors, with several studies reporting conclusive results and outcomes [16][17][18]. A massive number of social media conversations represents a cross-section of society that encompasses people's opinions across different demographic dimensions.…”

“…In this study, we focus on the application of artificial intelligence (AI) approaches that have been validated across several studies [18,27,38] to analyze human emotions. The algorithms are used to quantify emotion intensities, detect emotion state transitions, and identify profiles of impacted individuals based on the concerns they have expressed on social media to provide a holistic view of people's mental health.…”