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The Ecological Cumulative Risk Model

dc.contributor.authorWhipple, Saraen_US
dc.contributor.chairEvans, Gary Williamen_US
dc.contributor.committeeMemberDunifon, Rachel E.en_US
dc.contributor.committeeMemberCasasola, Marianellaen_US
dc.date.accessioned2012-06-28T20:57:35Z
dc.date.available2017-06-01T06:00:35Z
dc.date.issued2012-01-31en_US
dc.description.abstractThis paper provides a theoretical and empirical introduction to the Ecological Cumulative Risk Model, an alternative to traditional additive models of cumulative risk (CR). The model is based upon Bronfenbrenner‟s Ecological Systems Theory (Bronfenbrenner, 1979) which posits that development occurs across a number of settings, each with varying proximity to the child. The model is intended as a compromise between additive and multiplicative measurement models of risk. Using the NICHD Study of Early Child Care and Youth Development I categorize a number of risk factors into one of six settings (i.e. demographic, parenting, neighborhood). Factor analysis is used to validate the underlying structure of these groupings. All risk factors were determined from 3rd grade measures and prior while all outcome variables (academic skills, externalizing behaviors, internalizing behaviors, and social skills) were measured at 4th grade. The predictive power of these settings/domains was contrasted against the predictive power of a traditional cumulative risk model. Thus, a total CR score within each setting was calculated as well as an overall CR score. Results indicate that the Ecological CR Model explains approximately 1% more variance across dependent variables compared to the traditional/overall approach. An advantage of dividing risk factors into domains is the ability to model interaction effects, even when using a cumulative risk measurement model. Of the thirty interaction effects that were tested, only two were statistically significant. Finally, structural equation modeling was used to validate the Ecological Domains Model. SEM analyses confirmed that the Ecological Cumulative Risk Model fit the data better than a lump sum approach. Furthermore, evidence of mediation through risk domains is provided; parenting risk partially mediates the effects of demographic risk on all outcome variables. I conclude that the Ecological Cumulative Risk Model is valuable for examining the processes through which risk operates (i.e. proximal domains mediate the impact of more distal risk domains). On the other hand, lack of interaction effects suggests that an additive approach is more viable than a multiplicative model. More research, particularly with a higher risk sample, is needed to further understand the utility of this measurement model.en_US
dc.identifier.otherbibid: 7745398
dc.identifier.urihttps://hdl.handle.net/1813/29482
dc.language.isoen_USen_US
dc.subjectcumulative risken_US
dc.subjectecological domainsen_US
dc.subjectmultiple risken_US
dc.titleThe Ecological Cumulative Risk Modelen_US
dc.typedissertation or thesisen_US
thesis.degree.disciplineDevelopmental Psychology
thesis.degree.grantorCornell Universityen_US
thesis.degree.levelDoctor of Philosophy
thesis.degree.namePh. D., Developmental Psychology

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