 Machine-assisted topic analysis, MOTA, uses artificial intelligence methods to help qualitative researchers analyze large datasets and rapidly update healthcare interventions during changing healthcare contexts. The study compared MOTA with human-only thematic analysis techniques on the same dataset, of 1,472 user responses from a COVID-19 behavioral intervention. Results showed that both methods identified key themes about what users found helpful and unhelpful, with substantial time savings for MOTA. The approach can support intervention development and implementation during public health emergencies. This article was authored by Lauren Towler, Lauren Towler, Polina Bondaronek, and others.