Accepted for/Published in: JMIR Cancer
Date Submitted: Nov 9, 2021
Open Peer Review Period: Nov 9, 2021 - Jan 4, 2022
Date Accepted: May 1, 2022
(closed for review but you can still tweet)
Identifying themes for assessing cancer-related cognitive impairment identified by topic modeling and qualitative content analysis of public online comments
ABSTRACT
Background:
Cancer-related cognitive impairment is a common and significant adverse effect of cancer and its therapies. However, its definition and assessment remain difficult due to limitations of currently available measurement tools.
Objective:
The aim of this study was to provide proof-of-concept for using natural language to examine cognitive effects of cancer.
Methods:
We applied Latent Dirichlet Allocation, a topic modeling approach, to 145 public online comments related to cognitive effects of cancer. We supplemented this method with a qualitative content analysis.
Results:
Latent Dirichlet Allocation revealed two latent topics that we qualitatively interpreted as representing internal and external factors related to cognitive effects. These findings lead us to hypothesize regarding the potential contribution of locus of control to cancer-related cognitive impairment. Qualitative content analysis suggested several major themes including symptoms, emotional/psychological impacts, coping, “chemobrain” is real, change over time, and function.
Conclusions:
Our findings indicate that topic modeling of free text responses may be a valuable approach for hypothesis generation in the study of cancer-related cognitive impairment. Future directions in this field include prospective acquisition of free text responses for both subjective and objective assessment of cognitive function in patients with cancer.
Citation
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Copyright
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