Lennox Richard, Dennis Michael L, Scott Christy K, Funk Rod
Psychometric Technologies, 2404 Western Park Lane, Hillsborough, NC 27278, USA.
Drug Alcohol Depend. 2006 Jun 28;83(2):95-103. doi: 10.1016/j.drugalcdep.2005.10.016. Epub 2005 Dec 20.
This paper examines the need, feasibility, and validity of combining two biometric (urine and saliva) and three self-report (recency, peak quantity, and frequency) measures of substance use for marijuana, cocaine, opioids, and other substances (including alcohol and other drugs). Using data from 337 adults with substance dependence, we used structural equation modeling to demonstrate that these multiple measures are driven by the same underlying factor (substance use) and that no single measure is without error. We then compared the individual measures and several possible combinations of them (including one based on the latent factors and another based on the Global Appraisal of Individual Needs (GAIN) Substance Frequency Scale) to examine how well each predicted a wide range of substance-related problems. The measure with the highest construct validity in these analyses varied by drug and problem. Despite their advantages for detection, biometric measures were frequently less sensitive to the severity of other problems. Composite measures based on the substance-specific latent factors performed better than simple combinations of the biometric and psychometric measures. The Substance Frequency Scale from the GAIN performed as well as or better than all measures across problem areas, including the latent factor for any use. While the research was limited in some ways, it has important implications for the ongoing debate about the proper way to combine biometric and psychometric data.
本文探讨了结合两种生物特征识别（尿液和唾液）以及三种自我报告（近期使用情况、峰值使用量和使用频率）指标来测量大麻、可卡因、阿片类药物及其他物质（包括酒精和其他毒品）使用情况的必要性、可行性和有效性。利用来自337名有物质依赖的成年人的数据，我们通过结构方程模型证明，这些多种测量指标受相同的潜在因素（物质使用）驱动，且没有单一指标是完全无误的。然后，我们比较了各个指标及其几种可能的组合方式（包括一种基于潜在因素的组合和另一种基于个体需求综合评估（GAIN）物质使用频率量表的组合），以检验每种组合对一系列与物质相关问题的预测效果如何。在这些分析中，具有最高建构效度的指标因药物和问题的不同而有所差异。尽管生物特征识别指标在检测方面具有优势，但它们对其他问题的严重程度往往不太敏感。基于特定物质潜在因素的综合指标比生物特征识别指标和心理测量指标的简单组合表现更好。GAIN的物质使用频率量表在各个问题领域的表现与所有指标相当，甚至优于包括任何使用的潜在因素在内的所有指标。虽然这项研究在某些方面存在局限性，但它对正在进行的关于如何正确结合生物特征识别数据和心理测量数据的辩论具有重要意义。
