{"id":105,"date":"2018-01-09T16:58:03","date_gmt":"2018-01-09T16:58:03","guid":{"rendered":"http:\/\/labs.la.utexas.edu\/champagne\/?page_id=105"},"modified":"2023-08-28T20:04:01","modified_gmt":"2023-08-28T20:04:01","slug":"research","status":"publish","type":"page","link":"https:\/\/labs.la.utexas.edu\/dailyactivitylab\/research\/","title":{"rendered":"Research"},"content":{"rendered":"
<\/h6>\n
Research in our lab focuses on collecting and analyzing high-density, ecologically valid datasets from parents and children as they interact naturally and in controlled settings.<\/strong><\/span><\/h6>\n

We are interested in children\u2019s early social-emotional development and maternal mental health and well-being. We use sensors worn by mothers and their children to capture the daily behaviors hypothesized to contribute to these outcomes. For example, to learn more about patterns of children’s distress and soothing, infants and toddlers in our studies wear recorders that capture up to 72 hours of audio data over the course of a week. We can combine this data with information about maternal mood, collected via daily surveys, or mother and infant sleep, collected via devices similar to a Fitbit.<\/p>\n

We use these innovative \u201cin the wild\u201d data to characterize daily risk and protective behaviors during the first few years of a child\u2019s life. This time is important because it in these years that patterns of children\u2019s emotion regulation are becoming established. Additionally, the first years of a child\u2019s life also corresponds to the highest risk for mothers\u2019 mental health. Ultimately, we plan to develop interventions embedded in daily life to modify behavioral risks for adverse outcomes – for children and their mothers – while such risks are particularly malleable. We have recently published a paper on the promise of such mobile sensing techniques for developmental science<\/a><\/strong>.<\/p>\n

Learn more about our research areas below.<\/em><\/p>\n

Developing a sensor paradigm for developmental science.<\/strong><\/h6>\n

A main research effort of the lab has been developing and refining a novel sensor paradigm and pipelines to collect, process, and analyze multimodal datasets of 72 hours of natural mother-child activity data.<\/p>\n

Daily activity sensing.<\/strong><\/h6>\n

While sleep deprivation and incessant crying are taken as a given of early childrearing, very few studies have documented caregiving experiences with objective data. Using our multimodal sensor paradigm, we aim to objectively characterize the daily behaviors and interactions of mothers and children in the home and study their impacts across the first years of life. For example,<\/p>\n