Skip to Main Content
 

Global Search Box

 
 
 

ETD Abstract Container

Abstract Header

Using Student Risk Factors to Predict Student-School Connectivity

Burke, Mark Edward, Jr.
http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1363272440

Abstract Details

2013, Doctor of Education (Ed.D.), Bowling Green State University, Leadership Studies.
The purpose of this correlational research study was to examine the degree to which five student risk factors (marijuana use, alcohol use, prescription drug use, household composition, and delinquent behavior) predict student-school connectivity. For the study, a secondary data source was used comprising of 557 secondary school students. The data was collected by a small urban/rural north central Ohio school district in May of 2011. Student results were gathered through the use of the Youth Health and Risk Survey. Three research questions guided the study. The study examined gender, grade level, and household composition differences; substance use compared to national norms, and best predictors of student-school connectedness. Results showed females had significantly higher use of alcohol. Results also indicated grade level differences included: higher uses of substance in grades 9-12, higher levels of delinquent behavior in grades 6-8, and the lowest levels of student-school connectedness was in grade 9. Household composition differences were observed when comparing two parent households and households without two parents. Results showed students living with someone other than their parents had significantly higher uses of marijuana, alcohol, and prescription drugs; additionally, students living outside their parents’ home had the lowest levels of student-school connectedness. Results indicated that the studied sample had significantly higher uses of alcohol (28%) and marijuana (12.9%) when compared to national rates of use (alcohol 13.6% and marijuana 7.4%). Lastly, results showed the combination of perceived risk of drug use, delinquent behavior, and alcohol use was significant in predicting student-school connectivity. Several conclusions were drawn from the study results. First, household composition is a critical factor in the development of student-school connectedness. Students living in household that are absent of parents may be at risk for a numerous anti-social behaviors including substance use, delinquent behaviors, and lower levels of academic success. It is vital from school districts to offer programing to engage families within the school. Second, student grade level can impact the development of student-school connectedness. Students entering grade 9 should be systematically targeted with engagement activities to foster a sense of school connectivity. Lastly, low level of perceived substance use risk negatively impacts the development of student-school connectivity. Drug awareness programming and drug education can be used as a protection factor toward student substance use. Health related curriculum focused on the negative side effects of alcohol and drug use may decrease student substance use and subsequently increasing student-school connectedness.
Rachel Reinhart, Ph.D. (Committee Chair)
Wendy Watson, Ph.D. (Committee Member)
Joyce Litten, Ed.D. (Committee Member)
Todd Nichols, Ed.D. (Committee Member)
120 p.
Education; Educational Leadership; Middle School Education; Secondary Education
School connectedness; substance use; risk factors; household composition; adolescent; secondary schools; rural school district; national norms; gender differences; grade differences

Recommended Citations

Citations

  • Burke, Jr., M. E. (2013). Using Student Risk Factors to Predict Student-School Connectivity [Doctoral dissertation, Bowling Green State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1363272440

    APA Style (7th edition)

  • Burke, Jr., Mark. Using Student Risk Factors to Predict Student-School Connectivity. 2013. Bowling Green State University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1363272440.

    MLA Style (8th edition)

  • Burke, Jr., Mark. "Using Student Risk Factors to Predict Student-School Connectivity." Doctoral dissertation, Bowling Green State University, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1363272440

    Chicago Manual of Style (17th edition)

bgsu1363272440
926
© 2013, some rights reserved.Creative Commons License Using Student Risk Factors to Predict Student-School Connectivity by Mark Edward Burke Jr. is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License. Based on a work at etd.ohiolink.edu.
This open access ETD is published by Bowling Green State University and OhioLINK.