Michael C. Frank, PhD


Michael C. Frank, PhD
Recipient of the 2021 MCHRI Structural Racism, Social Injustice and Health Disparities in Maternal and Child Health Pilot Award

Study title: Measuring Children's Early Vocabulary Using Large Scale Data from Diverse Families

Program: Structural Racism, Social Injustice and Health Disparities in Maternal and Child Health Pilot Awards

Research summary: Learning a language is a critical part of a child’s development, and early language learning sets the stage for future academic achievement. Notably, the tools currently used for measuring early language have not been validated with diverse families in the US, leading to problematic mis- or over-identification of children from racial and ethnic groups as having speech and language issues. Michael Frank, PhD, Associate Professor of Psychology, is leading a study to leverage web- and app-based technologies to collect vocabulary data in a representative sample of children from diverse backgrounds. This project will examine novel questions regarding socioeconomic-related effects on early language learning and children’s language outcomes.

Q: What progress have you made to date?
A: With support from MCHRI, we have already collected survey data about early language, literacy, and parenting attitudes from a first pilot sample of families from diverse backgrounds. These data are helping us analyze both the relationships between these variables, and also the suitability of the instruments and our online platform for use with these families. Based on what we’ve learned, we are making some substantial revisions to our materials and will be gathering further data later in the year. 

We use a specific form called the MacArthur-Bates Communicative Development Inventory (or CDI). The CDI measures developmentally appropriate language, including early gestures and the understanding and production of words for younger kids, then the growth of vocabulary and grammar for older kids. Our online platform is called Web-CDI, and it allows us to send CDI surveys to parents. Overall, parents are very good observers of their children's language development and so gathering data from parents is one way that we look at language growth across diverse families. Of course, sometimes parents can be biased observers and so we try to compensate for this bias both in the types of questions we ask and also in our statistical analysis. 

Q: How will this award impact your broader research goals related to healthcare disparities?
A: This award has already helped us to gather important pilot data for a broader proposal that we just submitted. Further, the revisions that we are making to our website and measurement tools will allow us to make more accurate assessments of children's early language across populations. Our ultimate goal is to build predictive models that help us understand how children's home experiences translate into their language outcomes. We can't do this without good measurements of those outcomes.

The project is currently in progress. This story is a complimentary piece to a larger article. To read the article, click here.


Laura Hedli is a writer for the Division of Neonatal and Developmental Medicine in the Department of Pediatrics and contributes stories to the Stanford Maternal and Child Health Research Institute.