Background
In the United States, there are considerable racial inequities in adverse perinatal outcomes. Exposure to racism, sexism, and other forms of oppression may help explain these inequities.
Objectives
To describe the application of realâtime data collection using ecological momentary assessment (EMA) and smartphone technology to assess exposure to stress, racism, sexism, microaggressions, and other forms of oppression.
Methods
The Postpartum Mothers Mobile Study (PMOMS) is an ongoing longitudinal cohort study that began recruitment in December 2017. Participants delivering at a hospital in Pittsburgh, PA are recruited by 29Â weeks' gestation. Using smartphones and smart scales, participants complete daily surveys related to psychosocial, behavioural, and contextual factors and weigh themselves weekly for approximately 15Â months. We provide a preliminary descriptive analysis of EMA selfâreported measures of stress, racism, sexism, and microaggressions; and nonâEMA measures of stress and major discrimination.
Results
The sample (n = 230) is 63.5% White, 24.8% Black/African American, and 7% Hispanic origin. The most commonly reported item from the Major Discrimination Scale is being unfairly fired (18.1% of the sample). Of those, 31.7% and 17.1% attribute unfair firing to their gender and race, respectively. From the random EMA measures, on average, participants report experiences of racism and sexism at least once daily, in an average 12âhour day over the 4âweek period. Black participants indicate about two experiences per day of racism, and White participants indicate more than 1 per day of sexism. Mean stress levels from the EMA measures were similar to the stress measures collected at baseline.
Conclusions
The methods applied in PMOMS provide realâtime data regarding how participants' daily experiences of stress and discrimination influence their lives. Future work will include understanding if and how these EMA measures may relate to already established measures of racism, sexism, and stress; and ultimately understanding associations with perinatal inequities.