Dierker Lisa C, Avenevoli Shelli, Goldberg Abbie, Glantz Meyer
Department of Psychology, Wesleyan University, Middletown, Connecticut 06459, USA.
Prev Sci. 2004 Sep;5(3):169-83. doi: 10.1023/b:prev.0000037640.66607.6b.
If multiple etiologies of substance use are truly at work in the population, then further strides in the accurate prediction of smoking and the use of other substances will likely be built on diverse pattern-centered approaches that explore the presence of multiple population subgroups across various substance use stages. The present study aimed to identify population subgroups defined by individual risk factors or risk factor constellations that prospectively predict specific smoking stages. Using data from the National Longitudinal Study of Adolescent Health (Add Health), analyses were conducted on the sample that took part in the baseline and 1 year follow-up assessment between 1994 and 1996. Classification and regression tree procedures were used to investigate the structure of individual risk factors, or constellations of risk, that define population subgroups with high rates of both experimental and established smoking. For each level of smoking, a relatively simple model including two subgroups predicted over half of the smoking cases. Findings also indicated that the two group models identified higher rates of regular smokers compared to experimental smokers. Deviant behaviors and alcohol use without permission independently predicted movement to experimentation at follow-up. Progression to regular smoking from both a nonsmoking and experimental smoking status at baseline were each predicted by smoking friends. Additionally, baseline levels of experimental use predicted movement from experimental to regular smoking, while a relatively low grade point average predicted rapid progression from baseline nonuse to regular use at follow-up. By identifying first approximations of patterns, these analyses may lead to clues regarding the major multiple mechanisms at work for the progression of smoking among adolescents.
如果物质使用的多种病因确实在人群中起作用,那么在准确预测吸烟及其他物质使用方面取得的进一步进展可能将基于多样化的以模式为中心的方法,这些方法会探索在不同物质使用阶段多个亚人群体的存在情况。本研究旨在识别由个体风险因素或风险因素组合所定义的亚人群体,这些因素可前瞻性地预测特定的吸烟阶段。利用青少年健康全国纵向研究(Add Health)的数据,对1994年至1996年间参与基线和1年随访评估的样本进行了分析。采用分类与回归树程序来研究个体风险因素或风险组合的结构,这些因素定义了实验性吸烟和习惯性吸烟发生率都很高的亚人群体。对于每个吸烟水平,一个包含两个亚组的相对简单的模型就能预测超过一半的吸烟案例。研究结果还表明,与实验性吸烟者相比,这两个亚组模型识别出的习惯性吸烟者比例更高。偏差行为和未经许可饮酒分别独立预测了随访时向实验性吸烟的转变。在基线时,无论是从不吸烟状态还是实验性吸烟状态转变为习惯性吸烟,都可由吸烟的朋友预测。此外,基线时的实验性使用水平预测了从实验性吸烟向习惯性吸烟的转变,而相对较低的平均绩点则预测了随访时从基线不使用迅速转变为习惯性使用。通过识别模式的初步近似值,这些分析可能会为青少年吸烟进展过程中起作用的主要多种机制提供线索。