Self-regulation is a key aspect of healthy development and impairments in self-regulation are associated with many poor health outcomes. This application addresses the NIH's call for greater consistency and integration in research on self-regulation. Building from a core framework, wherein self-regulation is defined as the recruitment of executive processes (e.g. attention control) to alter prepotent responses (e.g. emotion) we develop a set of mathematical models that aim to unify theoretical perspectives, and to capture the dynamic nature of self-regulation using intensive time-series data. Models are developed and tested using intensive time-series data archived in 5 independent studies of early childhood self-regulation and parent-directed regulation of infant state. In each, behaviors and/or physiology indexing prepotent and executive processes were coded on a second-by-second time scale. Knowledge gained from the unified framework is then used to design and collect new data that provides for tests of predictive validity, developmental differences, and generalization across multiple manifestations of both young children's and parents'self-regulation.

Public Health Relevance

Self-regulation plays an important role in many health problems, such as mental disorders, obesity, and heart disease. This study integrates the diversity of research into a unified model that describes development of self- regulation in young children and in their parents, and identifies potential areas for intervention.

National Institute of Health (NIH)
Eunice Kennedy Shriver National Institute of Child Health & Human Development (NICHD)
Research Project (R01)
Project #
Application #
Study Section
Psychosocial Development, Risk and Prevention Study Section (PDRP)
Program Officer
Esposito, Layla E
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
Pennsylvania State University
Schools of Arts and Sciences
University Park
United States
Zip Code
Tuarob, Suppawong; Tucker, Conrad S; Kumara, Soundar et al. (2017) How are you feeling?: A personalized methodology for predicting mental states from temporally observable physical and behavioral information. J Biomed Inform 68:1-19
Ong, Anthony D; Benson, Lizbeth; Zautra, Alex J et al. (2017) Emodiversity and Biomarkers of Inflammation. Emotion :
Ram, Nilam; Benson, Lizbeth; Brick, Timothy R et al. (2017) Behavioral Landscapes and Earth Mover's Distance: A New Approach for Studying Individual Differences in Density Distributions. J Res Pers 69:191-205
Lydon-Staley, David M; Ram, Nilam; Brose, Annette et al. (2017) Reduced impact of alcohol use on next-day tiredness in older relative to younger adults: A role for sleep duration. Psychol Aging 32:642-653
Brinberg, Miriam; Fosco, Gregory M; Ram, Nilam (2017) Examining inter-family differences in intra-family (parent-adolescent) dynamics using grid-sequence analysis. J Fam Psychol 31:994-1004
Ong, Anthony D; Ram, Nilam (2017) Fragile and Enduring Positive Affect: Implications for Adaptive Aging. Gerontology 63:263-269
Buss, Kristin A; Davis, Elizabeth L; Ram, Nilam et al. (2017) Dysregulated Fear, Social Inhibition, and Respiratory Sinus Arrhythmia: A Replication and Extension. Child Dev :
Cole, Pamela M; Bendez├║, Jason J; Ram, Nilam et al. (2017) Dynamical systems modeling of early childhood self-regulation. Emotion 17:684-699
Lydon, David M; Ram, Nilam; Conroy, David E et al. (2016) The within-person association between alcohol use and sleep duration and quality in situ: An experience sampling study. Addict Behav 61:68-73
Gershon, Anda; Ram, Nilam; Johnson, Sheri L et al. (2016) Daily Actigraphy Profiles Distinguish Depressive and Interepisode States in Bipolar Disorder. Clin Psychol Sci 4:641-650

Showing the most recent 10 out of 24 publications