Text-Mining Open-Ended Survey Responses Using Structural Topic Modeling: A Practical Demonstration to Understand Parents’ Coping Methods During the COVID-19 Pandemic in Singapore

Open-ended survey questions crucially contribute to researchers’ understandings of respondents’ experiences. However, analyzing open-ended responses using human coders is labor-intensive. Structural topic modeling (STM) a text mining method that discover topics from textual data. We demonstrate the use STM analyze understand how parents coped during COVID-19 lock-down in Singapore. administered online surveys 199 Singapore lock-down. To show analysis, we demonstrated workflow includes steps data preprocessing, model estimation, selection, and interpretation. An 18-topic best fit based on diagnostics expertise. Prevalent coping methods described by respondents include “Spousal Support,” “Routines/Schedules,” “Managing Expectations.” Topic prevalence for some varied with levels parenting stress whether were fathers or mothers. offers an efficient, valid, replicable way such as case notes can complement knowledge skills. be used part multistage research process support other analyses clarifying quantitative findings identifying preliminary themes qualitative data.Supplemental this article available at https://doi.org/10.1080/15228835.2022.2036301 .