Journal article
Applying novel technologies and methods to inform the ontology of self-regulation
Behaviour research and therapy, Vol.101
Feb 2018
PMCID: PMC5801197
PMID: 29066077
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Self-regulation is a broad construct representing the general ability to recruit cognitive, motivational and emotional resources to achieve long-term goals. This construct has been implicated in a host of health-risk behaviors, and is a promising target for fostering beneficial behavior change. Despite its clear importance, the behavioral, psychological and neural components of self-regulation remain poorly understood, which contributes to theoretical inconsistencies and hinders maximally effective intervention development. We outline a research program that seeks to define a neuropsychological ontology of self-regulation, articulating the cognitive components that compose self-regulation, their relationships, and their associated measurements. The ontology will be informed by two large-scale approaches to assessing individual differences: first purely behaviorally using data collected via Amazon's Mechanical Turk, then coupled with neuroimaging data collected from a separate population. To validate the ontology and demonstrate its utility, we will then use it to contextualize health risk behaviors in two exemplar behavioral groups: overweight/obese adults who binge eat and smokers. After identifying ontological targets that precipitate maladaptive behavior, we will craft interventions that engage these targets. If successful, this work will provide a structured, holistic account of self-regulation in the form of an explicit ontology, which will better clarify the pattern of deficits related to maladaptive health behavior, and provide direction for more effective behavior change interventions.
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Details
- Title
- Applying novel technologies and methods to inform the ontology of self-regulation
- Creators
- Ian W Eisenberg - Department of Psychology, Stanford University, Stanford, CA 94305, USA. Electronic address: ieisenbe@stanford.eduPatrick G Bissett - Department of Psychology, Stanford University, Stanford, CA 94305, USAJessica R Canning - Department of Psychology, Arizona State University, Tempe, AZ 85281, USAJesse Dallery - Department of Psychology, University of Florida, Gainesville, FL 32611, USAA Zeynep Enkavi - Department of Psychology, Stanford University, Stanford, CA 94305, USASusan Whitfield-Gabrieli - Brain and Cognitive Sciences Department, The McGovern Institute for Brain Research, MIT, Cambridge, MA 02139, USAOscar Gonzalez - Department of Psychology, Arizona State University, Tempe, AZ 85281, USAAlan I Green - Department of Psychiatry, Geisel School of Medicine at Dartmouth, Dartmouth College, Lebanon, NH 03766, USAMary Ann Greene - Department of Biomedical Data Science, Geisel School of Medicine at Dartmouth, Dartmouth College, Lebanon, NH 03766, USAMichaela Kiernan - Department of Medicine, Stanford University, Stanford, CA 94305, USASunny Jung Kim - Department of Psychiatry, Geisel School of Medicine at Dartmouth, Dartmouth College, Lebanon, NH 03766, USA; Department of Biomedical Data Science, Geisel School of Medicine at Dartmouth, Dartmouth College, Lebanon, NH 03766, USAJamie Li - Department of Psychology, Stanford University, Stanford, CA 94305, USAMichael R Lowe - Department of Psychology, Drexel University, Philadelphia, PA, USAGina L Mazza - Department of Psychology, Arizona State University, Tempe, AZ 85281, USAStephen A Metcalf - Department of Biomedical Data Science, Geisel School of Medicine at Dartmouth, Dartmouth College, Lebanon, NH 03766, USALisa Onken - National Institute on Aging, National Institutes of Health, Bethesda, MD 20892, USASadev S Parikh - Department of Psychology, Stanford University, Stanford, CA 94305, USAEllen Peters - Department of Psychology, The Ohio State University, Columbus, OH 43206, USAJudith J Prochaska - Department of Medicine, Stanford University, Stanford, CA 94305, USAEmily A Scherer - Department of Psychiatry, Geisel School of Medicine at Dartmouth, Dartmouth College, Lebanon, NH 03766, USALuke E Stoeckel - National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD 20892, USAMatthew J Valente - Department of Psychology, Arizona State University, Tempe, AZ 85281, USAJialing Wu - Department of Biomedical Data Science, Geisel School of Medicine at Dartmouth, Dartmouth College, Lebanon, NH 03766, USAHaiyi Xie - Department of Biomedical Data Science, Geisel School of Medicine at Dartmouth, Dartmouth College, Lebanon, NH 03766, USADavid P MacKinnon - Department of Psychology, Arizona State University, Tempe, AZ 85281, USALisa A Marsch - Department of Psychiatry, Geisel School of Medicine at Dartmouth, Dartmouth College, Lebanon, NH 03766, USA; Department of Biomedical Data Science, Geisel School of Medicine at Dartmouth, Dartmouth College, Lebanon, NH 03766, USARussell A Poldrack - Department of Psychology, Stanford University, Stanford, CA 94305, USA
- Publication Details
- Behaviour research and therapy, Vol.101
- Publisher
- Elsevier; England
- Grant note
- UH2 DA041713 / NIDA NIH HHS F32 DA041773 / NIDA NIH HHS P30 DA029926 / NIDA NIH HHS
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Psychological and Brain Sciences (Psychology)
- Identifiers
- 991014878634904721
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- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Psychology, Clinical