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.

Agency
National Institute of Health (NIH)
Institute
Eunice Kennedy Shriver National Institute of Child Health & Human Development (NICHD)
Type
Research Project (R01)
Project #
5R01HD076994-05
Application #
9497496
Study Section
Psychosocial Development, Risk and Prevention Study Section (PDRP)
Program Officer
Esposito, Layla E
Project Start
2014-07-01
Project End
2020-05-31
Budget Start
2019-06-01
Budget End
2020-05-31
Support Year
5
Fiscal Year
2019
Total Cost
Indirect Cost
Name
Pennsylvania State University
Department
Psychology
Type
Schools of Arts and Sciences
DUNS #
003403953
City
University Park
State
PA
Country
United States
Zip Code
16802
Gatzke-Kopp, Lisa M; Ram, Nilam; Lydon-Staley, David M et al. (2018) Children's Sensitivity to Cost and Reward in Decision Making Across Distinct Domains of Probability, Effort, and Delay. J Behav Decis Mak 31:12-24
Buss, Kristin A; Davis, Elizabeth L; Ram, Nilam et al. (2018) Dysregulated Fear, Social Inhibition, and Respiratory Sinus Arrhythmia: A Replication and Extension. Child Dev 89:e214-e228
Ong, Anthony D; Benson, Lizbeth; Zautra, Alex J et al. (2018) Emodiversity and biomarkers of inflammation. Emotion 18:3-14
Benson, Lizbeth; Ram, Nilam; Almeida, David M et al. (2017) Fusing Biodiversity Metrics into Investigations of Daily Life: Illustrations and Recommendations With Emodiversity. J Gerontol B Psychol Sci Soc Sci 73:75-86
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
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
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
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
Koffer, Rachel E; Ram, Nilam; Almeida, David M (2017) More than Counting: An Intraindividual Variability Approach to Categorical Repeated Measures. J Gerontol B Psychol Sci Soc Sci 73:87-99

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