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

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...

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Autores principales: Adikari, Achini, de Silva, Daswin, Ranasinghe, Weranja K. B., Bandaragoda, Tharindu, Alahakoon, Oshadi, Persad, Raj, Lawrentschuk, Nathan, Alahakoon, Damminda, Bolton, Damien
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7055800/
https://www.ncbi.nlm.nih.gov/pubmed/32130256
http://dx.doi.org/10.1371/journal.pone.0229361
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author Adikari, Achini
de Silva, Daswin
Ranasinghe, Weranja K. B.
Bandaragoda, Tharindu
Alahakoon, Oshadi
Persad, Raj
Lawrentschuk, Nathan
Alahakoon, Damminda
Bolton, Damien
author_facet Adikari, Achini
de Silva, Daswin
Ranasinghe, Weranja K. B.
Bandaragoda, Tharindu
Alahakoon, Oshadi
Persad, Raj
Lawrentschuk, Nathan
Alahakoon, Damminda
Bolton, Damien
author_sort Adikari, Achini
collection PubMed
description 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 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. CONCLUSION: 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.
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spelling pubmed-70558002020-03-12 Can online support groups address psychological morbidity of cancer patients? An artificial intelligence based investigation of prostate cancer trajectories Adikari, Achini de Silva, Daswin Ranasinghe, Weranja K. B. Bandaragoda, Tharindu Alahakoon, Oshadi Persad, Raj Lawrentschuk, Nathan Alahakoon, Damminda Bolton, Damien PLoS One Research Article 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 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. CONCLUSION: 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. Public Library of Science 2020-03-04 /pmc/articles/PMC7055800/ /pubmed/32130256 http://dx.doi.org/10.1371/journal.pone.0229361 Text en © 2020 Adikari et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Adikari, Achini
de Silva, Daswin
Ranasinghe, Weranja K. B.
Bandaragoda, Tharindu
Alahakoon, Oshadi
Persad, Raj
Lawrentschuk, Nathan
Alahakoon, Damminda
Bolton, Damien
Can online support groups address psychological morbidity of cancer patients? An artificial intelligence based investigation of prostate cancer trajectories
title Can online support groups address psychological morbidity of cancer patients? An artificial intelligence based investigation of prostate cancer trajectories
title_full Can online support groups address psychological morbidity of cancer patients? An artificial intelligence based investigation of prostate cancer trajectories
title_fullStr Can online support groups address psychological morbidity of cancer patients? An artificial intelligence based investigation of prostate cancer trajectories
title_full_unstemmed Can online support groups address psychological morbidity of cancer patients? An artificial intelligence based investigation of prostate cancer trajectories
title_short Can online support groups address psychological morbidity of cancer patients? An artificial intelligence based investigation of prostate cancer trajectories
title_sort can online support groups address psychological morbidity of cancer patients? an artificial intelligence based investigation of prostate cancer trajectories
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7055800/
https://www.ncbi.nlm.nih.gov/pubmed/32130256
http://dx.doi.org/10.1371/journal.pone.0229361
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