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Modeling abstinence education effectiveness

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Summary:Background: Controversy about the effectiveness of abstinence education has posed troubling dilemmas for everyone involved in this area of study. Strident statements about the lack of efficacy of abstinence education have approached the level of bitter ideology. One remedy to lessen this focus on ideology is to provide a broader analysis of program efforts. Method: This paper provides an innovative analysis of a community-based abstinence education program that encompassed multiple schools across several counties that includes thousands of students. The design addressed many deficits in published studies; it used hierarchical linear modeling to remedy the design flaws of a simple pretest-posttest analysis. Results: Pretests were the principal predictors of posttest scores. Gender was also a significant predictor of posttest scores. Age however was not a significant predictor. An interaction between gender and age was a significant predictor although a three-way interaction of gender x age x race was not. Conclusion: Implications for the findings are stated with recommendations for further research.
Main Authors:​Smith, Thomas E.
Other Authors:Atar, Burcu; Ferreira, Teresa; Valentine, Pamela; Pereira, M. Graça
Subject:Abstinence education HLM Outcome studies Modeling
Year:2015
Country:Portugal
Document type:article
Access type:open access
Associated institution:Universidade do Minho
Language:English
Origin:RepositóriUM - Universidade do Minho
Description
Summary:Background: Controversy about the effectiveness of abstinence education has posed troubling dilemmas for everyone involved in this area of study. Strident statements about the lack of efficacy of abstinence education have approached the level of bitter ideology. One remedy to lessen this focus on ideology is to provide a broader analysis of program efforts. Method: This paper provides an innovative analysis of a community-based abstinence education program that encompassed multiple schools across several counties that includes thousands of students. The design addressed many deficits in published studies; it used hierarchical linear modeling to remedy the design flaws of a simple pretest-posttest analysis. Results: Pretests were the principal predictors of posttest scores. Gender was also a significant predictor of posttest scores. Age however was not a significant predictor. An interaction between gender and age was a significant predictor although a three-way interaction of gender x age x race was not. Conclusion: Implications for the findings are stated with recommendations for further research.