Drawing on UTAUT2, this study examines the number of causal recipes that foster mHealth adoption, using a mixed approach combining Partial Least Squares (PLS-SEM) and fuzzy-set qualitative comparative analysis. Two general research propositions are assessed using data collected through a survey administered to 120 mHealth users. The findings point that PLS-SEM and fsQCA are complementary analytical approaches providing comparable results. PLS-SEM indicates that performance expectancy, hedonic motivation, and habit have the ability to predict mHealth adoption, while fsQCA reveals six configurations including the factors identified by PLS-SEM. The findings suggest that several conditions that were not significant in PLS-SEM are in fact sufficient conditions when combined with other conditions. For practitioners concerned with fostering mHealth adoption, the findings stress the importance of adopting an integrated approach centered on performance expectancy, facilitating conditions, and habit, targeting well-educated young women. The existence of multiple solutions also points to the presence of equifinality.