{"title":"Understanding the Nonmedical Use of Prescription Medications in the U.S. High School Adolescents","authors":"Cynthia G. Ayres, N. M. Pontes, M. Pontes","doi":"10.1177/1059840516677322","DOIUrl":null,"url":null,"abstract":"The purpose of the study was to examine relationships between sleep insufficiency, depressive symptoms, demographic factors, and the nonmedical use of prescription medications (NMUPMs) in the U.S. high school students. Data from the 2013 Youth Risk Behavioral Surveillance System were used (n = 13,570) and analyzed using IBM SPSS 23™ (complex samples). Significant bivariate relationships were found between the NMUPMs and sleep (p < .01), feeling sad (p < .001), grade level (p < .001), and race/ethnicity (p < .01). Logistic regression analyses found that all of the independent variables were significant in predicting the likelihood of the NMUPMs. Findings underscore the potential impact of preventing NMUPMs in high school adolescents by improving their sleep behaviors and assessing adolescents for depressive symptoms.","PeriodicalId":77407,"journal":{"name":"The Academic nurse : the journal of the Columbia University School of Nursing","volume":"8 1","pages":"269 - 276"},"PeriodicalIF":0.0000,"publicationDate":"2016-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The Academic nurse : the journal of the Columbia University School of Nursing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/1059840516677322","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
The purpose of the study was to examine relationships between sleep insufficiency, depressive symptoms, demographic factors, and the nonmedical use of prescription medications (NMUPMs) in the U.S. high school students. Data from the 2013 Youth Risk Behavioral Surveillance System were used (n = 13,570) and analyzed using IBM SPSS 23™ (complex samples). Significant bivariate relationships were found between the NMUPMs and sleep (p < .01), feeling sad (p < .001), grade level (p < .001), and race/ethnicity (p < .01). Logistic regression analyses found that all of the independent variables were significant in predicting the likelihood of the NMUPMs. Findings underscore the potential impact of preventing NMUPMs in high school adolescents by improving their sleep behaviors and assessing adolescents for depressive symptoms.