Several theoretical risk models were proposed previously regarding the prediction of child maltreatment. Although child maltreatment was predicted individually in these models by such variables as parent temperament, emotional and behavioral regulation, stress, coping, and child temperament, these variables were not yet examined collectively. As such, a new transactional theory was proposed for the current study. As part of this study, a national community sample of 158 culturally diverse mothers of young children who were between the ages of 1½- to 5-years rated their own temperament, emotional and behavioral regulation abilities, parenting stress, daily hassles, and coping behaviors as well as their young children's temperament. Correlational analyses demonstrated many significant relationships among the variables of interest. In addition, hierarchical regression analyses suggested that several parent (i.e., mother mood quality, mother flexibility/rigidity, emotion dysregulation, parenting stress, cumulated severity of stress, and emotion-focused coping) and child characteristics (i.e., young child mood quality) added unique incremental variance to the prediction of child maltreatment potential. Finally, mediation analyses indicated that mothers' emotion dysregulation mediated the relationship between mothers' flexibility/rigidity and child maltreatment potential. Overall, this study contributed information regarding the importance of emotion dysregulation as a mechanism through which difficult mother temperament may be related to increased child maltreatment potential. Accordingly, these findings suggested that emotion regulation skills may serve as a potential point of intervention for mothers who are at increased risk for child maltreatment due to difficult temperament characteristics.
| Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd-2278 |
| Date | 01 January 2015 |
| Creators | Lowell, Amanda |
| Publisher | STARS |
| Source Sets | University of Central Florida |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Electronic Theses and Dissertations |
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