Trajectories of Nonmedical Prescription Drug Misuse

项目总结/摘要 为了响应PAR-18-062：利用现有数据加快药物滥用研究的步伐， 竞争更新“非医疗处方药滥用的轨迹”建立在我们的父R 01和 建议使用国家数据来评估医疗和保健轨迹之间的纵向关系， 处方药的非医疗使用、功能结局和不良后果 青春期（18岁）至中年期（50岁）。拟议的研究将集中在处方阿片类药物， 镇静剂/安定剂和兴奋剂，因为这些药物的医疗和非医疗用途， 在过去的三十年里，美国的相关后果有所增加。 在纵向研究中，研究了损耗对医疗和非医疗使用估计的影响。 此外，国家研究未能检查长期功能结果或与之相关的不良结果。 处方药的医疗和非医疗使用的不同轨迹。更多的纵向研究 需要跟踪到中年的青少年，因为成年人更有可能被处方 定期服药，并经常承担更大的生活/工作责任。因此，我们建议， 分析主要集中在MTF纵向面板样本，其中包括11个独立的队列， 大约26，400名高中毕业生（标准年龄18岁），他们被随访1-2年（19-20岁），3-4年 (ages 21-22岁）、5-6岁（23-24岁）、7-8岁（25-26岁）、9-10岁（27-28岁）、11-12岁（29- 29岁） 30岁）、17岁（35岁）、22岁（40岁）、27岁（45岁）和32岁后（50岁），导致总体11例 数据波。MTF数据提供了一个独特的机会，具有足够的测量和样本量， 研究32年来的关系，并满足我们研究的目标，其目的是：1）估计 处方阿片类药物、镇静剂/安定剂的医疗和非医疗使用估计率的偏差，以及 兴奋剂在不同的发展阶段和估计的变化率随着时间的推移，在医疗和 通过比较和评价替代加权和插补， 方法; 2）确定处方阿片类药物的医疗和非医疗使用轨迹， 镇静剂/安定剂和兴奋剂，基于青春期（18岁）的多波纵向数据 到成年中期（50岁）; 3）使用生长混合模型来评估特定对象的轨迹是否 非医疗和医疗使用的处方阿片类药物，镇静剂/安定剂和兴奋剂， 青春期到45岁是功能结果的预测（例如，教育程度）和不利 后果（例如，SUD症状）;以及4）检查青少年的风险和保护因素， 处方药的医疗和非医疗使用轨迹与不良功能相关， 结果和不良后果在中年使用基于理论的发展模型。

PROJECT SUMMARY/ABSTRACT In response to PAR-18-062: Accelerating the Pace of Drug Abuse Research Using Existing Data, this competing renewal “Trajectories of Nonmedical Prescription Drug Misuse” builds on our parent R01 and proposes to use national data to assess the longitudinal relationships among trajectories of medical and nonmedical use of prescription medications, functional outcomes and adverse consequences from adolescence (age 18) to middle adulthood (age 50). The proposed research will focus on prescription opioids, sedatives/tranquilizers, and stimulants because the medical and nonmedical use of these medications and related consequences have increased over the past three decades in the U.S. To date, no national studies have examined the impact of attrition on medical and nonmedical use estimates in longitudinal studies. Moreover, national studies fail to examine long-term functional outcomes or adverse outcomes associated with different trajectories of medical and nonmedical use of prescription medications. More longitudinal studies of adolescents followed into middle adulthood are needed because adults are more likely to be prescribed scheduled medications and often assume greater life/work responsibilities. As a result, we propose secondary analyses focusing primarily on the MTF longitudinal panel sample, which features 11 separate cohorts of approximately 26,400 high school seniors (modal age 18) who were followed 1-2 years (ages 19-20), 3-4 years (ages 21-22), 5-6 years (ages 23-24), 7-8 years (ages 25-26), 9-10 years (ages 27-28), 11-12 years (ages 29- 30), 17 years (age 35), 22 years (age 40), 27 years (age 45), and 32 years later (age 50) resulting in 11 overall waves of data. The MTF data provide a unique opportunity with sufficient measures and sample sizes for examining relationships over 32 years and to meet the objectives of our study, which aims to: 1) estimate the bias in estimated rates of medical and nonmedical use of prescription opioids, sedatives/tranquilizers, and stimulants at different developmental periods and in estimated rates of change over time in medical and nonmedical use due to differential attrition, by comparing and evaluating alternative weighting and imputation approaches; 2) identify the trajectories of medical and nonmedical use of prescription opioids, sedatives/tranquilizers, and stimulants based on multiple waves of longitudinal data from adolescence (age 18) to middle adulthood (age 50); 3) use growth mixture modeling to evaluate whether subject-specific trajectories of nonmedical and medical use of prescription opioids, sedatives/tranquilizers, and stimulants from adolescence to age 45 are predictive of functional outcomes (e.g., educational attainment) and adverse consequences (e.g., SUD symptoms) at age 50; and 4) examine the adolescent risk and protective factors for trajectories of medical and nonmedical use of prescription medications that are associated with poor functional outcomes and adverse consequences in middle adulthood using a theory-based developmental model.