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虚幻预测因素:可卡因治疗留存率研究结果的可推广性

Illusory predictors: Generalizability of findings in cocaine treatment retention research.

作者信息

Stotts Angela L, Mooney Marc E, Sayre Shelly L, Novy Meredith, Schmitz Joy M, Grabowski John

机构信息

University of Texas Medical School at Houston, USA.

出版信息

Addict Behav. 2007 Dec;32(12):2819-36. doi: 10.1016/j.addbeh.2007.04.020. Epub 2007 May 3.

Abstract

Treatment retention is of paramount importance in cocaine treatment research as treatment completion rates are often 50% or less. Failure to retain cocaine patients in treatment has both significant research and clinical implications. In this paper we qualitatively and quantitatively demonstrate the inconsistency found across analyses of retention predictors in order to highlight the problem. First, a qualitative review of the published literature was undertaken to identify the frequency of predictors studied and their relations to treatment retention. Second, an empirical demonstration of predictor stability was conducted by testing a common set of variables across three similar 12-week cocaine clinical trials conducted by the same investigators in the same research clinic within a five-year period. Results of the literature review indicated inconsistently selected variables of convenience, widely varying statistical procedures, and discrepant findings of significance. Further, quantitative analyses resulted in discrepancies in variables identified as significant predictors of retention among the three studies. Potential sources of heterogeneity affecting the consistency of findings across studies and recommendations to improve the validity and generalizability of predictor findings in future studies are proposed.

摘要

在可卡因治疗研究中,治疗保持率至关重要,因为治疗完成率通常为50%或更低。未能使可卡因患者坚持治疗具有重大的研究和临床意义。在本文中,我们通过定性和定量分析,展示了在治疗保持率预测因素分析中发现的不一致性,以突出这一问题。首先,对已发表的文献进行定性综述,以确定所研究的预测因素的频率及其与治疗保持率的关系。其次,通过在五年内由同一研究人员在同一研究诊所进行的三项类似的为期12周的可卡因临床试验中测试一组常见变量,对预测因素的稳定性进行实证论证。文献综述结果表明,所选变量存在随意性、统计程序差异很大,以及显著性结果不一致。此外,定量分析导致三项研究中被确定为治疗保持率显著预测因素的变量存在差异。本文提出了影响各项研究结果一致性的潜在异质性来源,以及在未来研究中提高预测因素结果的有效性和普遍性的建议。

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