Abstract
BackgroundCurrent qualitative literature about the experiences of women dealing with urinary tract infections (UTIs) is limited to patients recruited from tertiary centers and medical clinics. However, traditional focus groups and interviews may limit what patients share. Using digital ethnography, we analyzed free-range conversations of an online community.ObjectiveThis study aimed to investigate and characterize the patient perspectives of women dealing with UTIs using digital ethnography.MethodsA data-mining service was used to identify online posts. A thematic analysis was conducted on a subset of the identified posts. Additionally, a latent Dirichlet allocation (LDA) probabilistic topic modeling method was applied to review the entire data set using a semiautomatic approach. Each identified topic was generated as a discrete distribution over the words in the collection, which can be thought of as a word cloud. We also performed a thematic analysis of the word cloud topic model results.ResultsA total of 83,589 posts by 53,460 users from 859 websites were identified. Our hand-coding inductive analysis yielded the following 7 themes: quality-of-life impact, knowledge acquisition, support of the online community, health care utilization, risk factors and prevention, antibiotic treatment, and alternative therapies. Using the LDA topic model method, 105 themes were identified and consolidated into 9 categories. Of the LDA-derived themes, 25.7% (27/105) were related to online community support, and 22% (23/105) focused on UTI risk factors and prevention strategies.ConclusionsOur large-scale social media analysis supports the importance and reproducibility of using online data to comprehend women’s UTI experience. This inductive thematic analysis highlights patient behavior, self-empowerment, and online media utilization by women to address their health concerns in a safe, anonymous way.
Highlights
Symptomatic acute bacterial cystitis, often used interchangeably with the term urinary tract infection (UTI), affects 60% of women once in their lifetime [1,2]
latent Dirichlet allocation (LDA) Topic Modeling Themes We identified a total of 105 themes using LDA, which were grouped into 9 categories to avoid redundancy and provide an overview of the topics represented online (Table 2)
Digital ethnography combining qualitative analysis and LDA allowed us to analyze free-range patient perspectives, which are currently not found in the UTI literature
Summary
Symptomatic acute bacterial cystitis, often used interchangeably with the term urinary tract infection (UTI), affects 60% of women once in their lifetime [1,2]. Current qualitative studies among women with UTIs focus on prescription practice patterns, self-management strategies, and UTIs during pregnancy [5,6,7]. These studies are usually conducted in the clinical setting. Conclusions: Our large-scale social media analysis supports the importance and reproducibility of using online data to comprehend women’s UTI experience. This inductive thematic analysis highlights patient behavior, self-empowerment, and online media utilization by women to address their health concerns in a safe, anonymous way
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