These outcome data support both experimental hypotheses: 1. Both groups reduced their consumption and alcohol-related problems relative to baseline levels at follow-up; and 2. The experimental group showed a greater reduction in consumption and a trend towards a greater reduction in alcohol-related problems relative to the control group at follow-up. The magnitude of the reductions in the drinking measures corresponded to medium-to-large effect sizes. In addition the experimental group, compared to the control group, showed even greater reductions in consumption as measured by PDA and log Mean peak BAC per Drinking Day.
These results provide the first scientific evidence from a randomized clinical trial of the potential benefits of the effectiveness of our new web application, Moderate Drinking, when used in conjunction with MM and the resources available online at Moderation Management. It also provides evidence for the effectiveness of the resources MM offers online.
We did not see a clear, positive dose-response relationship between the use of the MD program and outcomes. An analysis of outcomes in the experimental group based on the frequency of logging into the program was non-significant. At one end of the spectrum, some participants who logged in only once or twice had positive outcomes while others did not benefit from their minimal use of the program. Others used the program frequently and had positive outcomes but not all frequent users of the program were successful in reducing their drinking.
The highly varied patterns of use of the MD protocol are to be expected of any self-directed intervention, especially one designed for a clinical issue that may present in such a variety of ways. Unfortunately, this makes it difficult to identify specific mechanisms of change in the application. In order to better understand the pattern of participant use of the MD program, we analyzed outcomes in the experimental group in relation to their use of the various components of the protocol. Within MD, there are 21 modules with material representing the basic components of the BSCT protocol: goal setting, self-monitoring and rate control, as well as some motivational components. Of the 38 participants in the experimental group, 29 actually used the MD application. The average number of modules tapped by those participants who used the site was 8.9, with a trend towards higher number of modules used correlating with better outcomes. The most commonly engaged module involved setting drinking goals (used 22 times), and the next most frequently used components involved gauging one’s chance for success at moderation, and considering “Doing a 30” (used 16 times). In general, motivational components were used relatively frequently, as were components focusing on rate control. Eleven participants entered their self-monitoring of their drinking and received feedback relative to their goals. We will examine these data in more detail once we’ve completed the 12 month follow-ups.
Participant use of Moderation Management resources was not directly monitored during the study. We consciously did this to minimize the assessment burden and to avoid altering what would otherwise be a typical pattern of use. Unfortunately, this makes it difficult to assess precisely which participants in the experimental group benefited more from MM, and which from MD or some combination of the two. Using both monthly email surveys that queried participants about their use of the materials, as well as a structured exit interview at the 12 month follow-up (in progress), we are attempting to further parse the differential use and effects of the two interventions. We will report those findings with the 12 month follow-up results. While this is a limitation of the study, it stems from our choice to maximize external validity. An integration of the two protocols was how we envisioned they would be used in practice.
Another factor that likely affected outcomes was additional assistance participants may have been receiving outside of the study. Twenty-six participants (11 experimental, 15 control) reported seeking help in addition to the interventions in the study: in the experimental group one participant reported attending one Alcoholic Anonymous meeting, eight sought help from some other self-help group, seven went to their doctor about their drinking, six sought help in their social support group and five reported going to their doctor for some other reason. Of the 15 control participants who sought additional help, seven reported attending a self help meeting, two went to their doctors about their drinking, one sought help in their social support network, one entered a RCT of a pharmacological intervention and seven saw their doctor for some other reason.
An unanticipated result emerged from the interaction between participants’ baseline levels of drinking and outcomes in the experimental group. Participants whose drinking, on average, did not meet NIAAA’s definition of binge drinking (5 or more for men, 4 or more for women), had better outcomes in the experimental group which had access to more resources and more opportunities to learn moderate drinking skills. Furthermore, within the experimental group, non-bingers were more likely (7 of 11 or 70%) to participate in 3 or more sessions than were bingers, of whom only 40% (11 of 27) logged into the site 3 or more times.
A consistent finding in the moderate drinking research literature is that those with greater symptoms of dependence benefit less from moderation protocols than do problem drinkers with lower levels of dependence (see Hester, 2003
for a review). This may be the case in our study. Examination of the baseline characteristics of these two groups indicates that the heavier drinking sub-group (that we have labeled Binge Drinkers) had higher mean MAST scores (14.8 vs 11.2, p
), and higher scores on the SADQ which measures dependence (4.9 vs. 3.1, p
) when compared to the problem drinkers who did not, on average
, meet NIAAA’s definition of binge drinking.
Another explanation for this interaction is that there may be a “sleeper” effect in the heavier drinkers that manifests itself in later follow-ups. It may take them longer to acquire the necessary skills to change their drinking. Our 6 and 12 month follow-up data will shed light on this question.
There is a third possible explanation of this interaction between treatment groups and heavy drinking status. As discussed in the Participant flow and follow-up section above, we did see a trend toward better retention in the MD condition, and those lost to follow-up overall tended to be heavier drinkers. Perhaps the interactive nature of the MD program provided more motivation for the less dependent participants who may not think they have as serious a drinking problem as some who are contributing to the MM listserv.
We expect the results of this study to have high external validity for three reasons. First, the intervention given here will be the same intervention that will be available to future users of both Moderation Management and the Moderate Drinking protocols. Second, a computer-based treatment, by its nature, interacts with users in the same way over time. There is no “drift” from the protocol. From the perspective of this trial, there was no therapist variability in the delivery of the intervention. Third, the study sample was representative of non-treatment seeking and non-dependent, but problematic drinkers based on the baseline measures. This increases the generalizability of our findings. The study sample was diverse, including a large proportion of women (50%) and Hispanics (19%). The study participants were representative of ‘at-risk’ drinkers in that they reported medical conditions and psychological symptoms frequently observed among problem drinking populations.
Our study has several limitations. First, it is difficult to determine whether future users of these protocols will have the same level of motivation or commitment that is required of participants entering and following through with a clinical trial. Some future users will come upon the interventions in a more casual fashion, perhaps with as little difficulty as a Google search requires, and may not have the same level of motivation as participants in this clinical trial. In addition, our anecdotal evidence suggested that participating in study follow-ups had some degree of intervention effect. However, since we had neither a delayed assessment nor a no-intervention control group, our conclusions about the effectiveness of MM alone are tempered. These limitations, however, would still not account for the better outcomes in the experimental group.
Another limitation to the generalizability of these results pertains to the general make-up of the study sample. The participants were, on average not only less alcohol dependent, but also somewhat older (M= 50 years) and better educated (M= 15 years of education) than one might expect from a typical sample of problem drinkers. They were also all relatively computer literate. Still, this is the population that has been drawn to MM in the past, and the population we expect to achieve the most benefit from the MD web application in the future.
A fourth limitation of this report is that the data are based on self-report. However, analyses of the collateral data from significant others were correlated and consistent with the findings of overall pre-post changes, and between group differences over time. A final caveat with regards to the current findings is that they are as short-term (3 month) outcomes. It remains to be seen if the significant reductions in drinking and alcohol-related problems, as well as the difference between the groups, persist for the long term. Our expectation, based on past results, is that some drinkers will relapse to heavier drinking, but while others will continue to decrease drinking further and some will become abstinent. We will report these and related outcomes once our 12 month follow-ups are completed.