Defining Prescription Drug Misuse: A Naturalistic Evaluation of National Survey on Drug Use and Health Data From 2012-2014 to 2015-2017.
Defining Prescription Drug Misuse: A Naturalistic Evaluation of National Survey on Drug Use and Health Data From 2012-2014 to 2015-2017.
复制标题
定义处方药滥用:对 2012-2014 年至 2015-2017 年全国药物使用和健康数据调查的自然评价。
DOI:
10.1097/adm.0000000000001115
复制
发表时间:
2023
影响因子:
5.5
通讯作者:
Fitzmaurice,GarrettM
中科院分区:
文献类型:
--
作者:
McHugh,RKathryn;Votaw,VictoriaR;McCarthy,MeganD;Bichon,JulietteA;Bailey,AllenJ;Fitzmaurice,GarrettM
ObjectivesPrescription drug misuse (PDM) is a significant public health problem. As research has evolved, the definitions of misuse have varied over time, yet the implications of this variability have not been systematically studied. The objective of this study was to leverage a change in the measurement of PDM in a large population survey to identify its impact on the prevalence and correlates of this behavior.MethodsData from the National Survey on Drug Use and Health were compared before and after a change in the definition of PDM from one that restricted the source and motive for use to one that captured any misuse other than directed by a prescriber. Three-year cohorts were constructed, representing a restricted definition of PDM (2012–2014) and a broad definition of PDM (2015–2017).ResultsSegmented logistic regression models indicated a significant increase in PDM prevalence for all 3 drug types examined (opioids, tranquilizers, and sedatives). Although the magnitude of differences varied somewhat based on drug type, the broader definition was generally associated with older age, higher prevalence of health insurance, and higher odds of misusing one's own prescription. Some worsening of mental health indicators was observed, but results indicated few other clinical or substance use differences.ConclusionsDefinitions of prescription drug misuse have a substantial impact on the prevalence of misuse and some impact on the characteristics of the population. Further research is needed to understand the optimal strategy for measuring this behavior, based on the scientific or public health question or interest.