Humphreys Keith, Blodgett Janet C, Wagner Todd H
Center for Innovation to Implementation, VA Palo Alto Health Care System, Menlo Park, California; Department of Psychiatry and Behavioral Sciences, Stanford University, Palo Alto, California; Ci2i, VAPAHCS (152-MPD), Menlo Park, California.
Alcohol Clin Exp Res. 2014 Nov;38(11):2688-94. doi: 10.1111/acer.12557.
Observational studies of Alcoholics Anonymous' (AA) effectiveness are vulnerable to self-selection bias because individuals choose whether or not to attend AA. The present study, therefore, employed an innovative statistical technique to derive a selection bias-free estimate of AA's impact.
Six data sets from 5 National Institutes of Health-funded randomized trials (1 with 2 independent parallel arms) of AA facilitation interventions were analyzed using instrumental variables models. Alcohol-dependent individuals in one of the data sets (n = 774) were analyzed separately from the rest of sample (n = 1,582 individuals pooled from 5 data sets) because of heterogeneity in sample parameters. Randomization itself was used as the instrumental variable.
Randomization was a good instrument in both samples, effectively predicting increased AA attendance that could not be attributed to self-selection. In 5 of the 6 data sets, which were pooled for analysis, increased AA attendance that was attributable to randomization (i.e., free of self-selection bias) was effective at increasing days of abstinence at 3-month (B = 0.38, p = 0.001) and 15-month (B = 0.42, p = 0.04) follow-up. However, in the remaining data set, in which preexisting AA attendance was much higher, further increases in AA involvement caused by the randomly assigned facilitation intervention did not affect drinking outcome.
For most individuals seeking help for alcohol problems, increasing AA attendance leads to short- and long-term decreases in alcohol consumption that cannot be attributed to self-selection. However, for populations with high preexisting AA involvement, further increases in AA attendance may have little impact.
对戒酒互助会(AA)成效的观察性研究容易受到自我选择偏差的影响,因为个体自行选择是否参加AA。因此,本研究采用了一种创新的统计技术来得出无选择偏差的AA影响估计值。
使用工具变量模型分析了来自美国国立卫生研究院资助的5项AA促进干预随机试验(1项有2个独立平行组)的6个数据集。由于样本参数存在异质性,其中一个数据集(n = 774)中的酒精依赖个体与样本的其余部分(从5个数据集中汇总的1582名个体)分开进行分析。随机化本身被用作工具变量。
随机化在两个样本中都是一个良好的工具,有效地预测了AA参与度的增加,而这不能归因于自我选择。在合并进行分析的6个数据集中,有5个数据集显示,因随机化导致的AA参与度增加(即无自我选择偏差)在3个月(B = 0.38,p = 0.001)和15个月(B = 0.42,p = 0.04)随访时,对戒酒天数有显著影响。然而,在剩余的数据集中,由于预先存在的AA参与度高得多,随机分配的促进干预导致的AA参与度进一步增加并未影响饮酒结果。
对于大多数寻求酒精问题帮助的个体来说,增加AA参与度会导致酒精消费量在短期和长期内下降,且这不能归因于自我选择。然而,对于预先存在较高AA参与度的人群,AA参与度的进一步增加可能影响甚微。