Towards an Unbiased Estimate of the Effectiveness of Alcoholics Anonymous
Towards an Unbiased Estimate of the Effectiveness of Alcoholics Anonymous
批准号:
8530119
负责人:
Keith N. Humphreys
金额:
$12.29万
依托单位国家:
美国
项目类别:
财政年份:
2012
资助国家:
美国
项目状态:
已结题
起止时间:
2012-08-15 至 2015-07-31
关键词:
AccountingAlcohol abuseAlcohol consumptionAlcohol dependenceAlcoholics AnonymousAlcoholsApplications GrantsClinical TrialsCounselingCross-Sectional StudiesDataData SetEconomicsEffectivenessEndogenous FactorsEnrollmentEquationEvaluationExploratory/Developmental GrantFundingIndividualInterventionLiteratureMeasuresMethodsMetricMinorityModelingObservational StudyOutcomeOutcomes ResearchPatientsPrincipal InvestigatorProceduresRandomizedRandomized Clinical TrialsReadingResearchResearch PersonnelResearch SubjectsReview LiteratureSelection BiasSourceStatistical MethodsSubstance Use DisorderSymptomsTechniquesUnited StatesWomanWorkalcohol related consequencescomparison groupeffectiveness researchimprovedinstrumentinterestmeetingsmemberpeerprospectivepsychosocialrandomized trialsatisfactiontherapy design
中文摘要
描述(由申请人提供):“12步”互助组织匿名酗酒者(AA)是美国最常见的酒精问题帮助来源。因此,研究人员致力于评估参与AA的结果。虽然AA研究多年来在方法质量方面有了显着提高,但对AA的影响进行无偏估计仍然是一个挑战。从根本上说,作为一个同行对照和广泛使用的组织,AA很难在随机试验中进行研究,这意味着对其影响的估计往往会受到自我选择的影响。然而,现在一些联邦政府资助的随机临床试验(例如,项目匹配)研究了旨在促进AA参与的干预措施(例如,12-步骤促进咨询),一个前所未有的机会存在,以产生一个公正的估计AA的有效性。具体来说,这些临床试验的数据可以使用工具变量模型进行重新分析,这是一种广泛用于经济学的技术,用于消除结果估计的偏倚。这项R21发展/探索性资助计划使用随机化到12步促进干预作为工具,在之前进行的6项试验中评估AA的影响,这些试验总共招募了3,000多名患者(其中女性和少数族裔的代表性很好)。这种无偏的AA有效性估计不仅本身令人感兴趣,而且还提供了一个有用的度量标准,用于判断先前的AA结果研究(即,确定AA影响的无偏工具变量估计值是否与观察性研究中使用其他统计程序产生的估计值相似)。 六项试验的数据将由其主要研究者提供,他们都参与了拟议的项目小组。关键结果将是酒精消费、酒精依赖和酒精相关后果,所有这些都在六项随机试验中使用经验证的测量方法进行评估。AA的无偏影响将通过简单的会议出席率测量和更全面的AA参与测量(例如,阅读文献,赞助其他成员)。每一个要分析的试验都包括一个随机分配的干预措施,旨在促进AA参与。因此,随机化条件将作为一个优秀的工具变量,因为它是完全观察到的,并强烈预测AA参与。将对每项单独试验和包括所有试验的堆叠数据集中的模型进行估计。次要分析将侧重于酒精以外的结果(例如,婚姻满意度,精神症状),并将工具变量模型的结果与使用不同方法减少AA有效性估计偏差的先前AA研究的结果进行比较(例如,MANCOVA,倾向评分)。
英文摘要
DESCRIPTION (provided by applicant): The "12-step" mutual help organization Alcoholics Anonymous (AA) is the most commonly sought source of help for alcohol problems in the United States. Researchers have therefore worked to assess the outcomes of participation in AA. Although AA research has improved dramatically in methodological quality over the years, generating an unbiased estimate of AA's impact remains a challenge. Fundamentally, as a peer-controlled and widely available organization, AA is difficult to study in randomized trials, meaning that estimates of its impact tend to be biased by self-selection. However, now that a number of federally-funded randomized clinical trials (e.g., Project MATCH) have studied interventions designed to facilitate AA participation (e.g., 12-step facilitation counseling), an unprecedented opportunity exists to generate an unbiased estimate of AA's effectiveness. Specifically, the data from these clinical trials can be re-analyzed using instrumental variables modeling, a technique widely employed in economics to remove bias from outcome estimates. Using randomization to a 12-step facilitating intervention as an instrument, this R21 developmental/exploratory grant proposes to assess the impact of AA in 6 previously conducted trials enrolling a total of over 3,000 patients (with excellent representation of women and minorities). This unbiased AA effectiveness estimate will not only be of interest in itself, but wil also provide a useful metric against which to judge prior AA outcome research (i.e., to determine if the unbiased instrumental variables estimate of AA's impact resembles those estimates generated using other statistical procedures in observational studies). Data from the six trials will be contributed by their principal investigators, all of whom are involved in the proposed project team. The key outcomes will be alcohol consumption, alcohol dependence, and alcohol- related consequences, all of which were assessed in the six randomized trials using validated measures. The unbiased effect of AA will be assessed both for a simple measure of meeting attendance and for more encompassing measures of AA participation (e.g., reading literature, sponsoring other members). Every trial to be analyzed included a randomly assigned intervention designed to promote AA involvement. Randomization condition will therefore serve as an excellent instrumental variable because it is fully observed and strongly predicts AA involvement. Models will be estimated for each individual trial and in a stacked dataset including all trials. Secondary analyses will focus on outcomes other than alcohol (e.g., marital satisfaction, psychiatric symptoms) and on comparing the results of the instrumental variables models with those of prior AA studies that used different methods to reduce bias in AA effectiveness estimates (e.g., MANCOVA, propensity scores).
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