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J Korean Med Assoc. 2011 Nov;54(11):1209-1227. Korean. Original Article. https://doi.org/10.5124/jkma.2011.54.11.1209
Lee MS .
Department of Social and Preventive Medicine, Sungkyunkwan University School of Medicine, Seoul, Korea. msnlee@skku.edu
Abstract

This study assessed the extent to which developmental assets predict or contribute to the reduction of health risk behaviors among Korean adolescents. The concept of developmental assets was introduced by Benson and his colleagues as building blocks for healthy child and adolescent's development. Their framework of 40 developmental assets encompasses positive external environmental factors and internal personal qualities which strongly influence adolescents' quality of life. We analyzed data from our 'Korean Youth Health Related Behaviors and Developmental Assets Survey.' The survey was based on self-reported questionnaires we distributed to 3,739 grade 9 students at eight schools across two cities in South Korea in 2001. The 40 developmental assets were measured by using 5-point Likert scales, and health risk behaviors were measured in terms of the prevalence or the experience rate. We identified the predictors of each health risk behavior among the 40 developmental assets using multiple logistic regression analyses. We found that the assets of 'restraint', 'positive peer influence', and 'time at home' were commonly the most important predictors associated with decreased reports of most health risk behaviors except depression. 'Self-esteem' was the most important predictor of decreased reports of depression and suicide. Other internal and external developmental assets were identified as important predictors to specific behaviors. We concluded that the positive asset promotion approach would be more effective and important than the risk factor approach in preventing effectively health risk behaviors among adolescents, and that intervention programs should include more comprehensive and adolescent-based strategies to promote adolescents' health and quality of life by a multi-level multi-dimensional approach.

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