INTRODUCTION: Smoking is a risk factor in at least 18 cancers, and approximately two-thirds of cancer survivors continue smoking following diagnosis. Text mining of survivors' online posts related to smoking and quitting could inform strategies to reduce smoking in this vulnerable population. METHODS: We identified posts containing smoking/cessation-related keywords from the Cancer Survivors Network (CSN), an online cancer survivor community of 166 000 members and over 468 000 posts since inception. Unsupervised topic model analysis of posts since 2000 using Latent Dirichlet Allocation extracted 70 latent topics which two subject experts inspected for themes based on representative terms. Posterior analysis assessed the distribution of topics within posts, and the range of themes discussed across posts. RESULTS: Less than 1% of posts (n = 3998) contained smoking/cessation-related terms, and covered topics related to cancer diagnoses, treatments, and coping. The most frequent smoking-related topics were quit smoking methods (5.4% of posts), and the environment for quitters (2.9% of posts), such as the stigma associated with being a smoker diagnosed with cancer and lack of empathy experienced compared to nonsmokers. Smoking as a risk factor for one's diagnosis was a primary topic in only 1.7% of smoking/cessation-related posts. CONCLUSIONS: The low frequency of smoking/cessation-related posts may be due to expected criticism/stigma for smoking but may also suggests a need for health care providers to address smoking and assist with quitting in the diagnostic and treatment process. Topic model analysis revealed potential barriers that should be addressed in devising clinical or population-level interventions for cancer survivors who smoke. IMPLICATIONS: Although smoking is a major risk factor for cancer, little is known about cancer patients' or survivors' views or concerns about smoking and quitting. This study used text mining of posts to an online community of cancer patients and survivors to investigate contexts in which smoking or quitting is discussed. Results indicated that smoking and quitting discussions were relatively rare, but nevertheless provide insight into barriers that may need to be addressed in cessation interventions for survivors.
INTRODUCTION: Smoking is a risk factor in at least 18 cancers, and approximately two-thirds of cancer survivors continue smoking following diagnosis. Text mining of survivors' online posts related to smoking and quitting could inform strategies to reduce smoking in this vulnerable population. METHODS: We identified posts containing smoking/cessation-related keywords from the Cancer Survivors Network (CSN), an online cancer survivor community of 166 000 members and over 468 000 posts since inception. Unsupervised topic model analysis of posts since 2000 using Latent Dirichlet Allocation extracted 70 latent topics which two subject experts inspected for themes based on representative terms. Posterior analysis assessed the distribution of topics within posts, and the range of themes discussed across posts. RESULTS: Less than 1% of posts (n = 3998) contained smoking/cessation-related terms, and covered topics related to cancer diagnoses, treatments, and coping. The most frequent smoking-related topics were quit smoking methods (5.4% of posts), and the environment for quitters (2.9% of posts), such as the stigma associated with being a smoker diagnosed with cancer and lack of empathy experienced compared to nonsmokers. Smoking as a risk factor for one's diagnosis was a primary topic in only 1.7% of smoking/cessation-related posts. CONCLUSIONS: The low frequency of smoking/cessation-related posts may be due to expected criticism/stigma for smoking but may also suggests a need for health care providers to address smoking and assist with quitting in the diagnostic and treatment process. Topic model analysis revealed potential barriers that should be addressed in devising clinical or population-level interventions for cancer survivors who smoke. IMPLICATIONS: Although smoking is a major risk factor for cancer, little is known about cancer patients' or survivors' views or concerns about smoking and quitting. This study used text mining of posts to an online community of cancer patients and survivors to investigate contexts in which smoking or quitting is discussed. Results indicated that smoking and quitting discussions were relatively rare, but nevertheless provide insight into barriers that may need to be addressed in cessation interventions for survivors.
Authors: Bach Xuan Tran; Carl A Latkin; Noha Sharafeldin; Katherina Nguyen; Giang Thu Vu; Wilson W S Tam; Ngai-Man Cheung; Huong Lan Thi Nguyen; Cyrus S H Ho; Roger C M Ho Journal: JMIR Med Inform Date: 2019-09-15