Using Large Language Models to Examine Family Stresses During Pandemic

The COVID-19 pandemic has exposed families with young children to various difficulties and challenges, significantly affecting children’s early experiences and overall development. Despite numerous studies investigating the pandemic's impact through quantitative measures, they potentially overlook the dynamic, evolving experiences, perspectives, and challenges families confront. To address the research gap, the current study utilizes a dataset from the Rapid Assessment of Pandemic Impact on Development (RAPID) project. I leverage OpenAI's GPT-3, a state-of-the-art NLP model, to examine open-ended responses to the question “What is challenging during the pandemic for your family”. This approach not only offers a richer and more dynamic understanding of the pandemic's impacts but also uncovers disparities in challenges across different racial and income demographics. By identifying challenge categories and analyzing their prevalence, the study would further provide actionable insights for stakeholders, facilitating corresponding support for diverse caregiver groups and aiding long-term early childhood program and policy development.