Research Centre for Data Analytics and Cognition, La Trobe University, Bundoora, Victoria, Australia.
MD Anderson Cancer Center, University of Texas, Houston, Texas.
PLoS One. 2020 Mar 4;15(3):e0229361. doi: 10.1371/journal.pone.0229361. eCollection 2020.
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.
在线癌症支持团体（OCSG）正成为癌症患者获取信息、经验和赋权的日益重要的来源。尽管它们对患者的身心健康有重大贡献，但 OCSG 尚未在多学科癌症支持计划中得到正式认可和应用。本研究强调了在 OCSG 中使用人工智能（AI）来解决心理困扰的机会，并提供了来自前列腺癌（PCa）患者的支持性实证证据。
使用经过验证的 AI 技术和自然语言处理（NLP）方法框架，根据十个国际 OCSG（18496 名患者-277805 次对话）中的对话，研究 PCa 患者的活动。重点关注表明心理困扰的活动；加入 OCSG 的原因、深层情绪以及从加入到癌症轨迹里程碑的变化。使用 t 检验、单向方差分析和 Tukey-Kramer 事后分析进行比较分析。
PCa 患者在四个关键的心理困扰阶段加入 OCSG；诊断、治疗、副作用和复发，大多数患者处于“治疗”（61.72%）阶段。四个组在癌症的强烈情绪负担方面存在差异。“副作用”组在第一个月表达的负面情绪比其他组更高（p<0.01）。治疗前与治疗后情绪的比较表明，治疗前组在 12 个月后与治疗后组相比，负面情绪显著降低（p<0.05）。长期深入的情绪分析表明，除“复发”组外，所有组的情绪健康状况都有所改善。
这是第一项使用人工智能研究新诊断为癌症的男性表达的心理困扰和深层情绪的实证研究。治疗前加入的 PCa 患者情绪有所改善，长期参与 OCSG 导致情绪健康状况增加，表明心理困扰减少。有必要进一步研究 OCSG 中的 AI 作为传统干预计划的辅助手段，进行早期心理干预。
