sample
(n = 1582)
Notes . PDA=Percent days abstinent from alcohol; PDMT=Percent days attending an Alcoholics Anonymous meeting. For categorical measures, table shows the proportion of participants and p -value for Pearson Chi 2 test. For continuous measures, table shows mean (standard deviation) and p -value for t-test.
As expected from the Chow test, the Project MATCH aftercare sample (which was the only sample to be drawn from an inpatient setting) differed in numerous respects from the subjects in the pooled datasets. Relative to the pooled sample, the MATCH aftercare participants were older, more likely to be male, more likely to be Black or Hispanic and more likely to be formerly married. At baseline, they had higher prior AA involvement and a lower percentage of days abstinent.
The logic behind the instrumental variables model is to estimate two regression models to account for the fact that PDMT is chosen by the person (and subject to selection bias). In the first model, PDMT is regressed on demographic variables and the instrumental variable (randomization to AA facilitation), yielding the predicted value of PDMT. This prediction represents the change in PDMT as a function of being randomized to AA facilitation or not, and thus excludes any inherent selection bias. In the second regression equation, PDA is regressed on predicted PDMT to provide an unbiased estimate on the link between AA attendance, as influenced by randomization, and abstinence.
An important assumption of instrumental variables is that the instrument is a strong predictor of the first stage outcome. A common rule of thumb requires a partial F statistic greater than 10 ( Stock et al., 2002 ). We tested this assumption by regressing randomization on PDMT with the demographic variables and randomization. In all cases, randomization proved to be a strong predictor of PDMT at three months ( F = 139.24 for the pooled sample and 23.24 for MATCH aftercare) and at 15 months ( F = 20.24 for the pooled sample and 12.47 for MATCH aftercare).
An instrumental variables model assesses the impact of additional AA (i.e., beyond what the person would have chosen to seek out in the absence of intervention) attributable directly to the randomly assigned condition. Our first step therefore was to calculate the differences between the two conditions. As shown in Figure 2 , in the pooled model, the comparison is between individuals with little or no AA attendance versus moderate, experimentally induced attendance, whereas for the MATCH aftercare sample, the comparison is between moderate attendance and extremely high attendance.
Percent Days Attending an Alcoholics Anonymous Meeting, Based on Randomization to an AAFI.
Notes. AAFI=Alcoholics Anonymous Facilitation Intervention; BL=baseline.
Pooled sample includes MATCH outpatient, Walitzer, McCrady (15 months only), Crits-Christoph (3 months only), and Litt. At baseline, meeting attendance was assessed for 3 months (MATCH), 6 months (Walitzer), or 1 year (Litt) prior to study participation. At 15 month follow up, meeting attendance was measured for the 15 months since the start of treatment, except “last 3 months” in Litt and McCrady.
In the instrumental variables model, an increase in PDMT was significantly associated with increased PDA at both 3 and 15 months in the pooled sample (see Table 3 ). The 3 month model showed that an increase in attendance of 1% (i.e., one absolute percentage point, not 1% of prior attendance) predicted an increase in PDA of about a third of a percentage point ( B = 0.38, p = .001). 1 To put these results in context, consider that the average PDA in the pooled sample was 77% at 3 months and 74% at 15 months, which places some limits on potential amount of benefit. That said, the results imply that an increase in PDMT of 28.6 absolute percentage points (i.e., going to an additional 2 AA meetings each week), would be associated with an increase in PDA of 10.9 percentage points, or an additional 3.3 days of abstinence per month. Surprisingly, for the 15 month follow-up point, the effect of PDMT on PDA was not attenuated and indeed was modestly higher ( B = 0.42, p = .04).
Instrumental variable regression estimates for PDA in the pooled sample of 1,582 alcohol use disordered individuals participating in clinical trials.
3 months (SE) | 15 months (SE) | |
---|---|---|
0.382 (0.112) | 0.415 (0.207) | |
0.327 (0.025) | 0.340 (0.027) | |
−0.008 (0.018) | −0.020 (0.019) | |
−0.012 (0.028) | −0.020 (0.028) | |
0.023 (0.017) | 0.017 (0.017) | |
0.052 (0.028) | 0.120 (0.032) | |
0.022 (0.027) | 0.033 (0.027) | |
−0.002 (0.049) | 0.022 (0.047) | |
−0.009 (0.026) | −0.007 (0.026) | |
−0.049 (0.019) | −0.031 (0.019) | |
−0.077 (0.019) | −0.044 (0.019) | |
−0.005 (0.024) | 0.004 (0.024) | |
−0.043 (0.020) | −0.002 (0.018) | |
0.686 (0.035) | 0.617 (0.035) | |
1,291 | 1,178 |
PDA = Percent days abstinent from alcohol; AA = Alcoholics Anonymous.
The models also included dummy variables for each study (including MATCH outpatient, Walitzer, McCrady [15 month model only], Crits-Christoph [3 month model only], and Litt).
In contrast, for the Project MATCH Aftercare sample, there was no evidence that the additional AA meetings prompted by the AA facilitation intervention were beneficial. The weight for the relationship of PDMT to PDA was not significantly different than zero at 3 months ( B = −0.122, p = .43) or 15 months ( B = −0.076, p = .79).
As any introductory research methods book will teach, correlation does not equal causation. The long-established positive association between AA involvement and better outcomes was therefore consistent with, but did not prove, causation. Determining whether this association truly reflected AA’s effectiveness or was merely an artifact of the most motivated, less troubled or most socially stable alcohol dependent individuals attending the organization has been a goal of researchers for decades. Using multiple regression techniques ( Morgenstern et al., 1997 ), structural equation models ( McKellar et al., 2003 ; Pisani et al., 1993 ), quasi-experiments ( Humphreys and Moos, 2001 ; 2007 ), and propensity scoring methods (e.g., Magura et al., 2013 ; Ye and Kaskutas, 2009 ) evaluators mounted progressively more sophisticated efforts to separate self-selection bias from outcome estimates and thereby obtain an accurate estimate of AA’s effectiveness (or lack thereof). We believe the present study is a qualitative step forward in this direction that became possible only recently in light of developments in statistics (Nobel Prize Winner James Heckman’s work on instrumental variables) and alcohol research (the emergence of randomized clinical trials of AA facilitation interventions).
That said, there are still possibilities for estimation errors in the results. Instrumental variables analysis does not resolve the problem of some individuals not being followed up, and follow-up rates being different across studies and conditions within studies. Neither can the approach used here correct for the fact that counts of AA meetings (they only variable in all the datasets analyzed here) tend to have weaker relationships to outcomes than do multi-component AA involvement measures ( Humphreys, 2004 ). Despite those weaknesses, it is encouraging that the results here are broadly consistent with what prior research has found: AA appears to actually benefit people with drinking problems rather than simply cobbling together individuals who would have improved without it.
In the Crits-Christoph, Litt, McCrady, Walitzer, and Project MATCH outpatient datasets, AA involvement was effective at increasing days of abstinence. These benefits were in addition to those of the core AA facilitation intervention itself. Even more impressively in a field where intervention effects are often evanescent, the benefits persisted to 15 month follow-up. These findings should be carefully considered in ongoing efforts to re-orient the addiction treatment system away from acute care services and into long-term chronic care ( Kelly and White, 2011 ).
The exception to the main findings was the Project MATCH aftercare sample, in which increases in AA involvement caused by the AA facilitation condition did not lead to any significant increase in days of abstinence. We cannot directly test for why there was no benefit evident, but suspect it had to do with a ceiling effect. The instrumental variables method estimated the impact of the AA participation that was added by the exogenous mechanism (random assignment to 12-step facilitation). Even prior to entering inpatient treatment (which is when prior AA involvement was measured), the Project MATCH aftercare sample had extensive AA involvement. They then participated in 12-step oriented inpatient or day treatment programs with regular 12-step meetings on site ( Babor and Del Boca, 2010 ) followed by sessions of 12-step facilitation counselling. At that high level of pre-existing AA involvement, the addition of still further AA may have had no value. That is, those who were abstinent due to AA could not became any more abstinent with yet more meetings, and those who were not benefiting from AA after such extensive exposure were not likely to start doing so given the addition of even more exposure.
We can only speculate regarding this explanation because there was not enough variance in prior AA attendance to have power to run a reliable interaction model, and because the measurement of prior AA in the Project MATCH aftercare study was at a different time point than all the other datasets (i.e., prior to an AA-heavy inpatient or day treatment episode rather than being made at the start of a new outpatient treatment episode). That said, it seems logical to propose that, as with other health promoting behaviors (e.g., exercise), the greatest gains of AA attendance may occur when someone moves from non-attendance to some attendance, or from light attendance to steady attendance, rather than from heavy attendance to even more heavy attendance.
In any event, the major result of this study is that in 5 of 6 randomized trial datasets, AA participation had a genuine benefit that was not attributable to self-selection bias. This is believable given that AA meetings are characterized by many processes generally found to be therapeutic, including social support for health behavior change, dry friendship networks, opportunities for altruism, the availability role models, instillation of hope and practical skill teaching ( Moos, 2007 ; 2008 ).
For some long-term members of AA, this study may have seemed unnecessary because their own experience convinces them of the organization’s effectiveness. But part of protecting and promoting public health involves subjecting all interventions that serve vulnerable people to careful evaluation. In this case, using what we believe is the most rigorous assessment yet of a 70 year old mutual help organization, the evaluation yielded positive results that will resonate with the experience of people who have become sober in AA. Our findings should also increase the confidence of clinicians, researchers, families and people with current drinking problems of the therapeutic value of Alcoholics Anonymous, even for those individuals who are not initially inclined to attend.
We are greatly indebted to Paul Crits-Christoph, Mark Litt, Barbara McCrady, Scott Tonigan and Kim Walitzer for sharing their trial data are for providing comments on a draft of this manuscript.
1 In order to see if these results were sensitive to the inclusion of the 218 CCTS participants, all of whom were both alcohol and cocaine dependent, we recalculated the 3-month model without them. The result was virtually identical ( B = .36, p =.002). We did not repeat this sensitivity analysis at 15 months because we did not have data from the CCTS at that wave.
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Alcoholics Anonymous, the worldwide fellowship of sobriety seekers, is the most effective path to abstinence, according to a comprehensive analysis conducted by a Stanford School of Medicine researcher and his collaborators.
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Research on the effectiveness of Alcoholics Anonymous (AA) is controversial and subject to widely divergent interpretations. The goal of this article is to provide a focused review of the literature on AA effectiveness that will allow readers to judge the evidence effectiveness of AA for themselves. …
Research on the effectiveness of Alcoholics Anonymous (AA) is controversial and subject to widely divergent interpretations. The goal of this article is to provide a focused review of the literature on AA effectiveness that will allow readers to judge the evidence effectiveness of AA for themselves. The review organizes the research on AA effectiveness according to six criterion required for ...
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