In the United States, motor vehicle crashes are one of the leading causes of unintentional injury death and disability for children ages 1'15 years. Despite local, state, and federal legislative and educational efforts, children continue to be restrained improperly and thus face harm. Identifying behaviors and barriers that place child occupants at risk is crucial for implementing focused, injury-prevention programs and policies. The purpose of this study was to evaluate the effectiveness of Connecticut's child passenger safety law that was strengthened in 2005. This study involved a multifactorial approach to predicting child seat use, guided by Roger's diffusion of innovations as the theoretical framework. The analysis determined if there was a difference in the prevalence of car seat use before as compared to after law implementation and identified variables that best predicted the use of car seats and premature transition to a seat belt. Using Connecticut's Crash Data Repository, a logistic regression analysis indicated that car seat use was 1.3 times more likely post law (OR 0.75; 95% CI: 0.65-0.86) and that in particular, children ages 4, 5, and 6 (combined) were most positively affected by the law (OR 0.67; 95% CI 0.54-0.82). Driver sex, crash time of day, child age, and child seating position were all determined to be significant predictors of whether or not a child was in a child safety seat. Additionally, these variables were also determined to be predictors of early transition to use of a lap/shoulder belt (versus child seat). The social change implication of this study is that identifying predictors of car seat use and early transition helps to formulate and implement injury prevention measures that could in turn help to decrease medical costs, save lives, and prevent injuries.
Identifer | oai:union.ndltd.org:waldenu.edu/oai:scholarworks.waldenu.edu:dissertations-1769 |
Date | 01 January 2015 |
Creators | Violano, Giuseppina Mendillo |
Publisher | ScholarWorks |
Source Sets | Walden University |
Language | English |
Detected Language | English |
Type | text |
Format | application/pdf |
Source | Walden Dissertations and Doctoral Studies |
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