Personality and prescription drug use/misuse among first year undergraduates.

Addictive behaviors(2018)

引用 37|浏览18
暂无评分
摘要
Emerging adults (18-25 year olds) endorse the highest rates of prescription drug misuse. Attending college or university may confer additional risk. Previous research suggests that personality is an important predictor of many addictive behaviours. Four traits have been consistently implicated: anxiety sensitivity, hopelessness, sensation seeking, and impulsivity. Published studies on personality as a predictor of prescription drug abuse are limited, however, by a primary focus on overall prescription drug use, inconsistent operationalisation of misuse, and failure to control for alcohol use. Sample sizes have been small and non-specific. We sought to better understand how personality predicted the overall use, the medically-sanctioned use, and the misuse of prescription sedatives/tranquilizers, opioids, and stimulants. A large (N = 1755) sample of first year Canadian undergraduate students (mean age = 18.6 years; 68.9% female) was used. We predicted that: anxiety sensitivity would be related to sedatives/tranquilizers, hopelessness to opioids, sensation seeking to stimulants, and impulsivity to all three. Save for the impulsivity to opioid use path, predictions were fully supported in our "any use" model. For medically-sanctioned use: anxiety sensitivity predicted sedative/tranquilizers, hopelessness predicted opioids, and impulsivity predicted stimulants. For misuse: anxiety sensitivity (marginally) predicted sedatives/tranquilizers, sensation seeking predicted stimulants, and impulsivity predicted all three. Our models support using personality-matched interventions. Specifically, results suggest targeting anxiety sensitivity for sedative/tranquilizer misuse, sensation seeking for stimulant misuse, and impulsivity for unconstrained prescription drug misuse. Interventions with early coping skills that pertain to all four traits might be useful for preventing prescription drug uptake and later misuse.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要