Asthma is the most prevalent pulmonary chronic disease in the U.S. impacting 11% (or 25 million) people. African Americans experience greater asthma disparities. They are two times more likely to have asthma, five times more likely to be seen in the Emergency Department for asthma related symptoms and three times more likely to die from asthma complications. African American emerging adults (those ages 18 – 29) have the highest prevalence among all ages. Given the wide use of mobile devices in this population and the increasing role of digital technology in healthcare delivery, considerations for mobile health (mHealth) based care management interventions has increased. Mobile health apps can play a significant role in supporting the self-management of chronic conditions; however, these apps have low adoption rates. This cross sectional descriptive study includes correlational analysis to examine the factors impacting mHealth adoption. This study is informed by the NASSS (Non-adoption, Abandonment, Scale-up, Spread, and Sustainability) of healthcare technology framework and was used to better understand the factors impacting mHealth adoption. Data were collected using a survey instrument distributed through Qualtrics software. Survey respondents (N = 52) had a mean age of 22 (SD = 3.54). On average respondents had been managing asthma for 15.9 years (SD = 5.74), however only 19.2 % of respondents had adopted (initial use of) an mHealth app to support their asthma self-management. The NASSS framework patient-level constructs considers predictors of 1) the condition, 2) digital literacy, 3) digital self-efficacy, and 4) value as impacting adoption decisions. The regression model only explained 20% of the impact of these variables with a Nagelkerke R2 of .20. Digital literacy was the only variable that significantly impacted mHealth adoption however that impact was negative; meaning respondents were 92.6% less likely to adopt an mHealth app for every one unit increase in digital literacy (p = .027). Though not statistically significant, independent t - tests resulted in higher asthma self-management (3.48, SD = .995, p > .05) and higher perceived value (3.52, SD = .973, p >.05) for mHealth adopters when compared those that have not adopted (3.32, SD = .575 and 3.38, SD = .593, respectively). Qualitative findings found 1) app features, 2) endorsements and 3) improved asthma symptom control to be factors that would motivate mHealth app adoption while barriers were identified as 1) awareness, 2) low perceived value, and 3) lack of trust as factors that prevent mHealth adoption. While the small sample size impacted the overall model fit and effect size of the predictors, open-ended responses provided valuable insights into the factors impacting mHealth app adoption in African American emerging adults.