Variable outcomes from MET were recently found in a National Institute on Drug Abuse (NIDA) Clinical Trials Network multicenter study that examined the effectiveness of a three-session MET versus counseling as usual (CAU) (Ball et al., 2007). Although the overall results indicated that MET reduced drug use significantly more than CAU, results varied considerably by program site, with MET better than CAU at two sites, little difference between treatments at two sites, and CAU better than MET at one site.

The successful implementation of MET may depend on therapist skill in general, or skill with certain patients, in creating the type of in-session climate that is central to the theory of this form of therapy. Some of the core clinical features of MET are borrowed from client-centered therapy as described by Rogers (1957). These features include a focus on listening to the client and the importance of therapist empathy, acceptance, respect, and positive regard for the client. MET, however, is not identical to Rogerian therapy. Unlike client-centered therapy, MET employs strategies to motivate clients to achieve specific behavior change goals within its overall collaborative and supportive stance (Miller, 1995). For example, therapists actively focus the client's attention on discrepancies between where they are and where they want to be, and to channel these discrepancies toward behavior change (Miller, 1983). In addition, therapists ask questions and reflectively listen to clients to specifically support client statements that favor change (Miller & Rollnick, 2002). Overall, MET is a more directive approach than client-centered therapy.

Although there are several other ways in which MET goes beyond traditional client-centered therapy, the emphasis on therapist empathy and acceptance, respect, and positive regard for the patient capture the essence of the therapeutic climate of the approach. These same features of therapy are highlighted in Orlinsky, Grawe, and Parks’ (1994) empirical analysis of factors that are associated with a positive therapeutic alliance in psychotherapy. The alliance has been defined by Bordin (1979) as composed of three interrelated components: the emotional bond between patient and therapist, agreement on therapy tasks, and agreement on therapy goals. Because of the clear overlap of some MET techniques and factors associated with a positive alliance, it would be expected that the alliance would be one of the central elements of the process of MET. Indeed, one investigation of the relation of therapist techniques in a MI treatment of smokers found that a MI-consistent style was positively related to the alliance (Boardman et al., 2006). Similarly, therapist interpersonal skills (acceptance, egalitarianism, empathy, warmth, spirit) that are consistent with the “spirit” of MI have been found to predict client cooperation and involvement (alliance-related constructs) in the MI treatment of substance abusers (Moyers et al., 2005).

Because the alliance has been extensively researched in diverse psychotherapies, with meta-analyses showing a consistent relation between a positive alliance and relatively more favorable treatment outcomes (Horvath & Symonds, 1991; Martin, Garske, & Davis, 2000), and the close conceptual connection between the alliance and the therapy process involved in MET, it would be expected that the alliance should be associated with treatment outcome within this form of therapy. Despite this close conceptual connection between the alliance and core features of MET and the relatively large number of studies that have been conducted on MET (see bibliography at http://www.motivationalinterview.org/library/biblio.html), few studies have investigated the role of the alliance as a predictor of outcome in this approach. A notable exception is Project MATCH (Connors et al., 1997). In the outpatient arm of this study, ratings on the alliance were positively related to percentage of days abstinent and negatively related to drinks per drinking day for both the 12-week treatment period and the posttreatment follow-up period (Connors et al., 1997). However, the alliance only explained a small percentage of variance in the outcomes (ranging from 0.8% to 1.5% for client alliance ratings and 1.3% to 3.4% for therapist alliance ratings), and there were no significant interactions between alliance and treatment condition (MET, cognitive-behavioral therapy, twelve-step facilitation) in predicting outcome. Another study involving a single-session MI for problem drinking among college students found high alliance ratings, on average, by both clients and therapists, but no significant relations between the alliance and drinking outcomes were apparent (Feldstein & Forcehimes, 2007).

Baldwin, Wampold, and Imel (2007) recently argued that studies of the relation of the alliance to outcome should conduct separate tests of the potential link between (1) therapist variability in the alliance and outcome, and (2) patient variability in the alliance and outcome. As explained by Baldwin et al. (2007), the within-therapist test examines whether patients with high alliance scores achieve relatively better outcomes than patients, treated by the same therapist, who have low alliance scores. The between-therapist test examines the relation of therapists’ average alliance (averaging over all patients treated by a therapist) to the average outcome achieved by each therapist (again, averaging over patients treated by each therapist). These authors describe how a relation at one level (e.g., therapist) could be positive and at the other level (e.g., patient) could be negative, with such effects canceling out when these sources of variability are incorporated into the statistical model and tested. In their own study, therapist variability in the alliance was found to relate to outcome for students in university counseling centers, but patient variability did not relate to outcome (Baldwin et al., 2007). In a treatment like MET, where there is a high focus on therapist actions that might foster a positive alliance, it would be particularly important to model both patient and therapist variability in alliance in relation to outcome in order to understand whether aspects of the therapist, or patient, are primarily responsible for the relation of the alliance to outcome.

In addition to predicting outcome, it might also be expected that, given the high focus on empathy, acceptance, respect, and positive regard in MET, average levels of alliance in MET would be higher than in therapies that do not emphasize these processes as much. However, in Project MATCH, no differences were found between MET, cognitive-behavioral therapy, and twelve-step facilitation in average alliance scores (Carroll et al., 1998). Similarly, in a study of MET compared to cognitive-behavioral therapy for bulimia nervosa, there was also no mean difference between MET and cognitive-behavioral therapy in mean alliance scores (Treasure et al., 1999).

Although the alliance would be theoretically expected to be especially high in MET, the alliance would also be expected to be high in other types of therapies investigated in randomized clinical trials for which extensive effort has been put into the selection, training, monitoring, and supervision of the therapists implementing the treatments. Thus, not surprisingly, MET has not been found to produce higher alliances than other psychotherapies within the context of studies that carefully select, train, and supervise therapists. A better test of this hypothesis might be to compare MET to a counseling as usual comparison group for which no special efforts at training, supervising, and monitoring have been implemented (although therapist experience should be controlled). In addition, because therapist interpersonal skills have been linked to alliance-like processes in MET, it might be expected that therapists will differ, on average, in their alliances formed with patients based on therapist differences in these interpersonal skills and/or ability to adhere to MET and use it competently. These issues have not been explored empirically to date.

The study protocol and informed consent procedures were approved by the respective Institutional Review Boards affiliated with each site. Recruitment of participants occurred from June 2001 to July 2004.

The fact that MET did not produce higher alliances than CAU was surprising. The extensive focus in MET on empathy, acceptance, and positive regard, as well as clear discussion about goals, would be expected to produce higher alliances in MET compared to CAU. The lack of a treatment difference was especially surprising given that MET adherence ratings were significantly related to the alliance, and MET adherence scores were substantially higher in MET compared to CAU sessions (Martino et al., 2008). Thus, one conclusion is that forming a positive alliance is not unique to MET; very positive average alliance can occur in CAU among therapists never trained in MET.

There are several potential explanations, however, why a treatment difference related to ratings of alliance did not occur. For one, the alliance has been shown to be related to patient pretreatment characteristics, such as expectations for improvement and certain types of interpersonal problems (Gibbons et al., 2003; Muran et al., 1994). To the extent that these patient characteristics are relatively stable over time, the aspect of the alliance that is related to these patient characteristics would not be expected to change depending on type of therapy, particularly when alliance is measured after the second treatment session, as it was here. Studies that have shown that the alliance can change as a function of treatment typically measure alliance multiple times later in treatment (Crits-Christoph et al., 2006; Hilsenroth et al., 2002).

Second, CAU therapists (like the MET therapists) were mostly highly experienced, averaging 8.5 years working with these kinds of patients. Experienced therapists might be expected to typically form relatively high alliances, leaving little room for MET to improve upon CAU. Consistent with this possibility, the average alliance score (dividing the total score by the number of items) was 5.1 on a 1 to 6 scale for both MET and CAU. If MET (adequately implemented) and CAU were compared using inexperienced therapists, the alliance-enhancing potential of training in MET might be more likely to be evident.

A third reason may be that the CAU therapists in the current study frequently used open questions and reflections, and were rated close to an average level of MI style in their sessions (Martino et al., 2008). While MET and CAU were discriminable, there may have been enough of the client-centered counseling skills happening in CAU to result in good alliances. Increasing empathy and reflections above a basic level may have little incremental impact on the alliance.

Our study adds to existing findings that report therapist effects on the alliance. Like Baldwin et al. (2007), we found that the therapist variability in the alliance, but not the patient variability, was associated with outcome (reduced drug/alcohol use). This is an important distinction because it suggests that something that therapists are doing in sessions (e.g., differences in interpersonal style, abilities to learn and implement alliance-fostering techniques, or identify and repair alliance ruptures) determines, at least in part, the alliance. As reported in Ball et al. (2007), there were no overall significant therapist effects on outcome in the current study, suggesting that the between-therapist alliance-outcome relation found here is not part of a more general therapist effect for which the alliance is simply a marker. Furthermore, the effect size for the alliance-outcome relationship found in the present study is comparable to that in the literature. The Cohen's d effect size of 0.39 found here converts to an r of 0.191 for the linear between-therapist effect of the alliance on outcome; the d = 0.44 for the quadratic effect converts to an r of 0.215. These effects are similar to the average r of 0.22 reported by Martin et al. (2000) in their meta-analysis of studies examining the relation of the alliance to outcome, despite the fact that, unlike the studies in the meta-analysis, our effect size is specific to the between-therapist relation and controls for improvement up to the assessment of the alliance.

To the extent that the between-therapist component of the alliance is related to treatment outcome, but not the within-therapist component, conceptualizations of the alliance as primarily an interactional variable (e.g., Henry & Strupp, 1994) may need to be modified. If the alliance is primarily a function of interpersonal processes unique to each dyad, then one would expect meaningful variation between patients who are treated by the same therapist, and that this variation between patients should be related to treatment outcome. The fact that the between-therapist variability, but not the between-patient variability, was found to relate to outcome suggests that relative differences between therapists in skill level, or personal qualities, are leading to a tendency for patients within a therapist's caseload to be reacting in a similar and meaningful way to a given therapist. While patient variables also impact the alliance (Gibbons et al., 2003; Muran et al., 1994), the variability between therapists in their ability to form a relatively more positive or negative alliance appears to be a more important determinant of outcome, as least as evidenced from the two studies (the current study and Baldwin et al., 2007) that have examined both patient and therapist variability in the alliance in relation to outcome.

Assuming the alliance plays a direct or indirect causal role in psychotherapy or drug counseling, the current findings suggest that efforts to train therapists in ways that might enhance the alliance are justified. Recent training studies have provided preliminary evidence that such training can be accomplished (Crits-Christoph et al., 2006; Hilsenroth et al., 2005). However, it is also possible that innate personality characteristics of therapists determine the alliance, at least in part, and these characteristics may not be teachable. In addition, treatments that do not have a special, explicit, MET-like focus on empathy and positive affirmations, such as cognitive-behavioral therapy (e.g., Bouchard et al., 2004) or the CAU in the current study, often display very high average alliance scores; therefore, training in the use of MET-like techniques does not appear to be the only vehicle for achieving a positive alliance. Thus, it seems likely that only a subset of therapists, those of any orientation who have a relatively impaired ability to form positive alliances, might benefit from training in how to enhance the alliance.

Furthermore, the relation between the alliance and outcome with alcohol and substance abusing populations may be complicated by the fact that many patients can readily become abstinent from drugs and alcohol early in treatment. Sustaining such abstinence, or reducing the severity and frequency of relapses, is more difficult, and it is in this treatment phase when alliance may most impact treatment outcomes. Many studies, however, measure outcome in a way that confounds reductions in drug use and prevention of slips and relapses. In the current study, assessing outcome in two phases, the first of which largely captured the initial reduction in drug use to near zero (Weeks 1 to 4) and the second that potentially captured slips and relapses (Weeks 4 to 16), revealed that the alliance was primarily related outcomes during the follow-up period.

In the current study, a more positive alliance was not necessarily a good thing: A curvilinear (quadratic) relation between the alliance (between-therapist component) and rate of change in primary drug/alcohol use during Weeks 4 and 16 was found. This indicates that deviations from the average alliance in both directions (relatively low and relatively higher than the average) were associated with relatively poorer outcomes. This type of finding was reported early in the history of alliance research by Saunders, Howard, and Orlinsky (1989), but has largely been overlooked since then, with investigators assuming a linear relation of the alliance to outcome. Further research is needed to understand the basis of this quadratic effect of alliance and outcome, and whether such an effect is evident across different types of therapies, patients, and settings.

High levels of therapist use of both MET fundamental techniques and MET advanced techniques were associated with high levels of alliance. Caution is warranted in interpreting the adherence data given the relatively high correlation between the fundamental and advanced adherence subscales, incomplete data (not all sessions were rated), and the standard limitations of correlational findings (i.e., reverse causation, influence of third variables). Within the constraints of these limitations, we can speculate that both fundamental techniques (e.g., positive affirmations, use of open-ended questions, use of reflective statements) and advanced techniques (e.g., problem discussion and feedback, exploring pros/cons/ambivalence, heightening discrepancies, discussing a plan for change) contribute to the fostering of the alliance. It may be that fundamental techniques are useful for strengthening the bond component of the alliance while advanced techniques help move the dyad towards greater agreement on goals and tasks. The findings with the adherence scale also suggest that the negative impact of high alliance on outcome is not a function of high levels of use of MET fundamental or advanced techniques. When these variables were included in the statistical model predicting substance use from the alliance, the curvilinear relation did not change, suggesting that some other factors are likely to be producing the finding of very high alliances being associated with relatively poorer drug use outcomes. Therapists implementing MET should therefore not be concerned that high use of these techniques has a detrimental effect on outcome by fostering an overly positive alliance. The MET adherence scale, however, was not designed to measure all alliance-fostering techniques. Thus, other alliance-fostering techniques not measured in the MET adherence scale may be responsible for the curvilinear relation that we found.

Several other limitations are important to consider in understanding this study's results. First, alliance was measured only after Session 2. This was done because the treatment was only three sessions long and it was important to assess the alliance early in treatment before most clinical improvement had occurred. Some previous studies of the alliance, however, have measured it later in treatment, giving more time for a bond to develop or for alliance ruptures and repairs to occur. It is possible that different results would be obtained if alliance was assessed after Session 3 or if treatment had been longer. Second, restricting CAU to three sessions limits the generalizabilty of the results to clinical settings where CAU is typically longer. Third, the fact that patients across conditions also participated in group counseling sessions, potentially led by MET or CAU counselors, is a limitation that may have attenuated our findings. Fourth, a substantial portion of patients randomized did not have alliance scores or did not have outcome measures. The lack of data on some randomized patients may have introduced bias in the comparison of treatments. Fifth, the time spent in training was not balanced across treatment conditions. Therapists assigned to MET received regular supervision based on tape reviews throughout the trial. This supervision difference between the treatments may have impacted the results in unknown ways. Sixth, although therapists were randomly assigned to treatment conditions, random assignment of patients to therapists was not performed. If systematic biases existed at clinics in regard to which therapists received which patients, such biases could create the therapist differences in the alliance that were found, and also be responsible for the between-therapist effect for the alliance in relation to outcome (assuming patient factors are related to the alliance and outcome). Seventh, both the predictor variable (alliance) and outcome measure (drug use) were self-report measures. The study's findings should be confirmed using an observer measure of the alliance. Finally, during this period of time in which alliance predicted drug use (Weeks 4 to 16), patients may have been receiving additional non-study treatment services at the original clinic or another clinic, with patients who were increasing their drug use being more likely to receive such services. Increased additional services during follow-up is associated with drug use outcomes (Worley et al., 2008), and this might have attenuated the relation of the alliance to outcome during Weeks 4 to 16.