Livelli e Modelli di Alleanza Terapeutica in Psicoterapia Breve Stevens et al 2007

Levels and Patterns of the TherapeuticAlliance in Brief Psychotherapy

CHRISTOPHER L. STEVENS*J. CHRISTOPHER MURAN*JEREMY D. SAFRAN#BERNARD S. GORMANH

ARNOLD WINSTON*

We examined the relevance of the level and pattern of the therapeuticalliance in 44 cases of three different, manualized 30–session treatmentsusing patient ratings of the Working Alliance Inventory after each session. Itwas hypothesized that both high–alliance level and either a linear increase inalliance rating or a series of brief rupture–and–repair episodes would befound in successful treatments. We also hypothesized that a more globalhigh–low–high pattern predicted in the literature would not be present.Consistent with the literature, higher alliance levels were found to be relatedto improved outcome. As predicted, we did not find a global, high–low–highpattern. Local rupture–and–repair patterns were found in 50% of the cases;linear trends were found in 66% of the cases. There was no relationshipbetween outcome and either pattern. We found no differences among thetreatments.

LEVEL & PATTERN OF THE THERAPEUTIC ALLIANCE IN BRIEFPSYCHOTHERAPY

Although findings that a strong, positive therapeutic alliance is relatedto positive treatment outcome has been extremely robust, (Horvath andSymonds, 1991; Martin, Garske, & Davis, 2000) the exact nature of thisrelationship has remained less clear. As a result, clinical theorists andresearchers have increasingly turned their attention to determining howthe alliance functions to foster change. For example, some (e.g., Raue &

*Beth Israel Medical Center and Albert Einstein College of Medicine, #New School for SocialResearch and Beth Israel Medical Center, HState University of New York and Beth Israel MedicalCenter. Mailing address: J. Christopher Muran, Beth Israel Medical Center, Department of Psychiatry& Behavioral Sciences, First Avenue at 16th Street, New York, New York 10003. e-mail:[email protected] The research presented in this article was supported in part by Grant R03MH50246 from the National Institute of Mental Health.

AMERICAN JOURNAL OF PSYCHOTHERAPY, Vol. 61, No. 2, 2007

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Goldfried, 1994; Beck, 1995) believe that the alliance serves primarily as astatic foundation for the application of curative techniques, while others(e.g., Bordin, 1979, 1994; Safran & Muran, 2000) believe that the allianceis an active agent of the change process in its own right. Many of theseauthors have theorized that the way in which the alliance develops overtime can give important information about how this takes place. Morespecifically, they hypothesized that working through conflicts or strains inthe alliance leads to positive change and that the variability in the allianceratings, indicating these periods of strain, could be a predictor of improvedoutcome.

Much of this research can be characterized as a search for global shiftsin the alliance over the course of treatment. Researchers, influenced in partby Mann (1973), suggested that alliance development goes through a seriesof changes as patients react to the shifting techniques of the therapist. (e.g.Gelso & Carter 1985, 1994; Horvath & Luborsky, 1993, Kivlighan &Shaughnessy, 1995, 2000). Specifically, researchersposit that the alliancewill proceed through three distinct phases. According to this model, thealliance is characterized by an initial period of high hope fostered bysupportive alliance–building activity by the therapist. During the nextphase of treatment, patient realization that all expectations will not be met,increasingly challenges therapist activity and, this leads to growing ambiv-alence, resistance, and greater strain on the alliance. Finally, in successfultreatment, patients gain a more realistic understanding of the therapist’srole, accept change, and the limitations of therapy, which is brought about(at least in part) by the therapist’s focus on working through termination.This process may be perceived as following a high–low–high pattern ofalliance development.

A number of studies tried to demonstrate this global high–low–highpattern with mixed results (Bernard, Schwartz, Ocaltis & Stiner, 1980;Golden & Robbins, 1990; Horvath & Marx, 1991; Joyce and Piper 1990;Kivlighan & Shaughnessy, 2000; Patton, Kivlighan & Multon, 1997;Schwartz and Bernard, 1981; and Tracey, 1989).

The most compelling case for a high–low–high pattern comes fromKivlighan and Shaughnessy (2000). They noted that as a result of thestatistical procedures used, both their 1995 study and the study by Patton,Kivlighan, and Multon 1997 study were unable to detect possible sub-groups of alliance development. As a result, they switched from thehierarchical linear modeling techniques (used in previous studies) to acluster–analytic model to identify patterns of alliance development (asrated by clients) and to determine if a high–low–high pattern was present

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and related to improved client outcome. They used novice counselors andrecruited subjects for a 4–session, short–term dynamic therapy. Analysis oftheir initial sample of 38 clients showed three distinct patterns of alliancedevelopment, which they identified as stable alliance, linear alliancegrowth, and quadratic alliance growth. A subsequent replication sample of41 clients identified the same three patterns. In addition, this analysis ofthe results of the second sample showed that clients reporting a quadraticpattern of alliance development had greater improvement on outcomemeasures compared to other patterns of development.

Although the results offer the strongest support to date of a rupture–and–repair process, there are several significant limitations to this study.The stated goal of the study was to examine patterns of global alliancedevelopment, but such a brief treatment is a significant shortcoming. First,it seems unlikely that any of the stages that Mann described had time todevelop. Similarly, Horvath and Luborsky’s (1993) model also suggestedthat the alliance–building phase of treatment would take place over thefirst five sessions, peaking at session three. With only four sessions oftreatment, it is impossible to determine if the changes observed wererelated to those that might be seen in longer treatment. Second, with onlyfour sessions, there are only 16 potential patterns that could develop,several of which could be interpreted as high–low–high, stable, or linearimprovement. Since Kivlighan and Shaugnessy found three different pat-terns, it might be more important to ask which patterns did not emerge.And finally, it is impossible to distinguish between discrete or transientchanges in alliance and more global dynamics.

Although, taken as a group, these studies seem to provide support forthe notion of a global high–low–high process, all suffered from significantlimitations. Sample sizes were small (Tracy, 1989; Golden & Robbins,1990) or not representative of clinical populations. The training andexperience of the therapists involved has been limited (Kivlighan &Shaughnessy, 1995, 2000; Patton et al., 1997). Treatment length has beeninconsistent (Bernard et al. 1980; Bernard and Schwartz, 1981) or ex-tremely brief (Kivlighan & Shaughnessy, 2000). Additionally, the statisticalmethods used were not appropriate for detecting patterns that might existamong subgroups of patients (Tracy, 1989; Golden & Robbins, 1990;Kivlighan & Shaughnessy, 1995; Patton et al., 1997). These limitationsraise the question of whether a general drop in alliance ratings during themiddle portion of the treatment is the best account of the kind of changestake place in the alliance during this portion of the treatment or if otherpatterns might provide a description.

Alliance Level and Pattern

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A review of the literature to date suggests that there is moderatesupport for the notion that variability increases in the midphase oftreatment (Bernard, Schwartz, Ocaltis and Stiner, 1980; Schwartz andBernard, 1981). Similarly, there is some initial support for the notion thatundergoing a rupture and repair process is related to improved outcome(Forman & Marmar, 1985; Lansford, 1986; Golden & Robbins, 1990;Horvath & Marx, 1991; Kivlighan & Shaughnessy, 2000; Patton, Kivlighan& Multon, 1997). However, Gelso and Carter, as well as Horvath andLuborsky, point out that the strains in the alliance experienced during themiddle phase of treatment often are the result of more focal strains on therelationship, which are brought about by momentary lapses or empathicfailures on the part of the therapist, disagreements on tasks or goals, orstrains on the bond. Both empirical (Forman & Marmar, 1965; Rhodes,Hill, Thompson & Elliott, 1994: Safran, Crocker, McMain & Murray,1990; Muran 2001; Safran & Muran 1996; Safran, Muran & Samstag, 1994;Safran, Muran, Samstag & Stevens, in press) and theoretical (Bordin, 1994;Safran, 1993; Safran & Muran, 1994, 1998, 2000) work suggest that whenstrains in the alliance are not addressed, outcome is negatively impactedand drop out may occur.

If this is true, then the middle phase of treatment might be bettercharacterized by a series of brief ruptures and repairs in which the allianceis strained. In successful treatment, the strain is addressed and the alliancereturns to previously high levels, not during the final stage of treatment,but within a few sessions. Rather than thinking of alliance development interms of curves, with global decrease in patient satisfaction and generalweakening of the alliance in the middle phase, it could be envisioned as aseries of dips and spikes representing, not global shifts in satisfaction, buta kind of session–by–session negotiation process (Safran & Muran, 2000).

The present study attempts to address many of the methodologicalproblems that limited the conclusions drawn from previous studies and totest the idea that the rupture–and–repair process is better described as alocal, rather than global, phenomenon. Consistent with the Bordin’s 1994assertion that different patients work differently in the alliance, twopatterns of alliance development were predicted. The first form is a linearincrease in Working Alliance Inventory (WAI) scores across the course oftreatment. The second follows the suggestion of Safran and Muran (1990,1993, 1994, 1996, 2000), Gelso and Carter (1994), and Horvath andLuborsky (1994). It is characterized by a series of rupture–and–repairepisodes in which patient alliance ratings drop and then return to previ-ously high levels within three to five sessions. A global high–low–high


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pattern was not expected to appear. Additionally, it was predicted thattreatments demonstrating a linear increase or rupture–and–repair episodeswould evidence better outcome than those that did not.

METHODSPARTICIPANTS

TherapistsThis study was conducted as part of a psychotherapy research project

at a major medical center in New York City (see Muran, 2002, for anoverview). The therapists were drawn from the department of psychiatryand included attending psychiatrists, clinical psychologists, social workers,psychiatry residents, psychology interns and externs. To assure consistencyof treatment, all of the therapists, regardless of their background andexperience, received similar training and evaluation in the therapeuticmodel they practice. To assure treatment adherence, trained observersrated videotapes of a randomly selected session in each treatment third(beginning, middle and end), using an instrument developed by theproject, which has demonstrated adequate psychometric properties (Pat-ton, Muran, Safran, Wachtel, & Winston, 1996). Licensed cliniciansparticipated in one–hour weekly supervision until they met acceptablestandards for treatment adherence (1–2 cases), while unlicensed therapistscontinued to receive individual supervision for all of their cases. Alltherapists participated in a weekly 90–minute group supervision.

Patients were randomly assigned to one of three manualized, 30–session, once–per–week treatment conditions designed to treat personality–disordered patients. All the therapy sessions were videotaped. The threedifferent conditions were Brief Relational Therapy ([BRT] Safran, 2002;Safran & Muran, 2000; Muran & Safran, 2002), Cognitive–BehavioralTherapy ([CBT] Turner & Muran, 1992) and Brief Adaptive Psychother-apy ([BAP]; Pollack, Flegenheirmer & Kaufman, 1988). Brief RelationalTherapy is an integrative model that combines the principles of relationalpsychoanalysis and humanistic psychotherapy. It focuses on detection andresolution of alliance ruptures and has an explicit emphasis on processrather than content. The CBT condition is a fairly traditional, schema–focused model aimed at constructing differential learning experiences andchallenging maladaptive schemas. Brief Adaptive Psychotherapy is a dy-namic model in the tradition Strupp’s and Luborsky’s work. It posits thatby making unconscious, irrational material conscious, the reality orienta-tion of the ego will enable the patient to adapt to the environment in a


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more adaptive fashion. Of the 128 cases reviewed for inclusion in this theproject, 44 fit the specific inclusion criteria (presented below). Of the 44patients, eighteen were seen in CBT, 14 in BRT and 12 in BAP.

PatientsPatients were recruited using advertisements in local newspapers,

inviting adults suffering from long–standing depression, anxiety, orinterpersonal problems to participate in a program to investigateshort–term psychotherapy. The principal inclusion criterion was thatthey met criteria for diagnosis of Personality Disorder (PD) cluster C orNOS on axis II. Exclusion Criteria was evidence of schizophrenia orother psychoses, organic brain syndrome or mental retardation, maniaor bipolar disorder, severe obsessive compulsive disorder or seriouseating disorder, serious dissociative disorders, a current substance usedisorder, active para–suicidal or suicidal behavior, a history of violentbehavior or severe impulse control problems, psychotropic medicationuse within the past six months.

Patient demographics. There were an equal number of male and femalepatients. They ranged in age from 25 to 63 years (M � 40, SD �10). Allwere educated at or above the high school level, and 75% had a collegedegree or at least some graduate level education. More than 75% wereemployed. Eighty percent were Caucasian.

Patient diagnostic characteristics. All of the patients in this study metthe criteria for an Axis II diagnosis, and all but two met criteria for an AxisI diagnosis in the Diagnostic Systems Manual Fourth Edition (AmericanPsychiatric Association, 1994). All patients with an Axis I diagnosis werein the mood or anxiety disorder spectrum. All 44 patients met criteria foran Axis II diagnosis, and 14 also met criteria for a secondary Axis IIdiagnosis based on the SCID–II. More than half (23) had a personalitydisorder NOS, with the remainder diagnosed as falling into Cluster C (14avoidant, 7 obsessive compulsive, [2?] aggressive).

CodersWe had four coders classify alliance development curves and identify

rupture–and–repair cycles. Each of the coders was a Ph.D.–level graduatestudent who was familiar with Regression Curve Analysis. They receivedapproximately 4 hours of training involving examination of sample curvesand rupture patterns. Raters were highly reliable on the example curvesand ruptures (Kappa � 1.0)


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MEASURES

AllianceAlliance was assessed using the short form of the WAI (Horvath &

Greenberg, 1989, Tracey & Kokotovic, 1989).The WAI was administeredat the end of each session as part of a postsession questionnaire (PSQ)designed to assess the therapeutic relationship (Muran et. al. 1991).

The WAI (Horvath, 1989) was created to assess the working allianceindependent of a therapist’s theoretical orientation while simultaneouslyproviding a clear description of what constitutes a working alliance andhow the alliance functions to promote positive change. Items for the WAIwere generated in a unique multi–step process to insure content validity.Items were created initially to reflect the three different dimensions (tasks,goals and bond) of Bordin’s model (Bordin 1974, 1979, 1980) and wererated by psychologists from different theoretical backgrounds. Experts onthe working alliance reviewed each item, rating it for relevance. Theremaining items were reviewed a second time from randomly selectedpracticing psychologists and separated into clusters corresponding to eachof the three dimensions (tasks, goals and bond). The top–rated 12 items ineach group were chosen to form the WAI. There has been good empiricalsupport both for the overall scale and the subscales.

Tracey and Kokotovic (1989) used a hierarchical bilevel model torepresent the factor structure of the WAI, and they concluded that theWAI assesses both the individual aspects of the alliance represented by thesubscales and the overall alliance dimension. Based on their findings, theyselected the four items that best defined each of the unique aspects of thealliance (i.e. the three subscales) and constructed a 12–item short form ofthe WAI. It is this shortened version that is used as a part of the PSQ andprovides the alliance ratings used in this study.

Outcome measuresOutcome for this study was measured using two factors established by

calculating the standardized residual gains for each of six outcome mea-sures, the

● Global Assessment Scale ([GAS] Endicott, Spitzer, Fleiss, & Cohen1976),

● Global Symptom Index (GSI) of the Symptom Checklist 90–Revised● ([SCL—90—R] Derogatis, 1983),● Inventory of Interpersonal Problems● ([IIP], Horowitz, Rosenberg, Baer, Ureno & Villasenor, 1988),● Wisconsin Personality Disorder Inventory


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● ([WISPI] Klein, Benjamin, Treece, Rosenfeld, Greist, 1990),● Patient Target Complaints (PTC), and● Therapist Target Complaints (TTC).

The residual gains scores were then submitted to principal componentanalysis with Varimax rotation. Two factors were extracted with eigenval-ues exceeding 1.00 and with 59.11% of the variance accounted. Twooutcome composites were calculated by averaging the standardized scoresof the measures that loaded � .45 on the respective factors and byapplying the yielded factor scores as weights. Factor one, which is consid-ered a measure of symptom reduction, is a composite that included GAS(factor loading � –.78, factor score � –.36), PTC (.83, .41), TRC (.81, .40)and the GSI (.45, .12). Factor two, a measure of patients interpersonalfunctioning, is a composite that included the IIP (.82,), WIPSI (.89, .61)and GSI (.50, .23).

STATISTICAL METHODOLOGY

Data selectionSince patterns of alliance development were the focus of this study,

gaps in PSQ reporting could have been problematic. As a result, [weincluded] only cases in which the patient had completed treatment, andreturned a minimum of 66% of the PSQs, with no gaps of no more thanthree consecutive sessions. Of the 128 original cases, 44 met all of thesecriteria and were included in the analysis. The largest gap in consecutivesessions was three, with an average of one missed session. To allow for theconsistent analysis of patterns across the length of therapy, all gaps in psqscores were filled in with the average of scores from the sessions before andafter the skipped session (s). For example, if a PSQ from session 14 weremissing, the average WAI values for sessions 13 and 15 were substitutedfor session 14.

As it seemed possible that large gaps in the PSQ reporting might beindicative of ruptures, and because cases with large numbers of missingPSQs could not be included in the analysis, it is possible that the remainingcases might be representative of only “good cases”. To help control forthis, the data was analyzed in several ways. First, we conducted a T–test tocompare the percentage of PSQs returned for clients who completedtreatment with those who dropped out of treatment. The test results werenot statistically significant (t � .423, p. � .673). Next, all cases of patientswho completed treatment were examined for a correlation between thepercentage of PSQs returned and outcome. Outcome for symptom reduc-tion and interpersonal functioning both at termination and follow–up was


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compared to percentage of missing PSQs, but no significant relationshipwas discovered. Finally, regression curves for the relationship betweenoutcome and percentage of PSQs returned were examined to determine ifthere was a nonlinear relationship. No significant quadratic or linearrelationship was found for either symptom reduction or interpersonalfunctioning at termination or follow–up. Although the precise meaning ofmissing PSQs cannot be determined, the percentage of PSQs returneddoes not appear to be predictive either of length of treatment or ofoutcome.

Data AnalysisBefore analyzing the impact of different patterns of alliance develop-

ment on outcome, we needed to determine first if alliance level for thissample correlated with outcome. The treatment was first divided intophases, as suggested by the literature (eg., Mann 1973; Gelso and Carter,1994; and Horvath and Luborsky, 1993). Using bivariate Pearson corre-lations with a Spearman two–tailed test of significance, we compared

● alliance levels at the third, fifteenth, thirtieth session;● average alliance levels for phase one (sessions one to five),● phase two (sessions six to twenty–five), and phase three (twenty six

through thirty); and● overall WAI mean

with outcomes for symptom reduction (factor one) and interpersonalfunctioning (factor two) at termination. As can be seen in Table 1, themean WAI ratings for both factors were correlated significantly withoutcome. With the exception of the ratings in phase one for interpersonalfunctioning, all of the mean ratings for the phases were correlated signif-icantly to outcome. Ratings taken from individual sessions showed aweaker relationship with outcome, with only sessions 15 and 30 beingsignificant. Interestingly, correlations were highest for phase two andsession fifteen, indicating the closest relationship between values taken

Table I. OVERALL WAI MEAN AND STANDARD DEVIATION SCORES

WAI

Phase Session Overall

One Two Three Three Fifteen Thirty Treatment

Mean 5.24 5.58 5.95 5.39 5.55 6.0 5.59Standard

Deviation 0.75 0.72 0.69 0.86 0.85 0.75 0.66Range 3.6–6.7 3.7–7.0 4.6–7.0 3.0–7.0 3.5–7.0 4.3–7.0 4.1–7.0


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at midtreatment for symptom reduction and interpersonal problems—contrary to what would be expected if a high–low–high pattern existed.Symptom reduction, factor one, was more highly related to outcome withcorrelations in the moderate–to–high range, while all of the correlationsfor factor two, interpersonal functioning, were somewhat lower. Lowscores for either factor indicate improvement, so that a negative correlationindicates that higher WAI scores are related to decreased patient symp-toms or decreased interpersonal problems.

Identification of CurvesTo test the hypothesis that both a linear trend and a series of ruptures

and repairs are predictive of improved outcome, we examined each of the44 cases to determine if either of these two definitions described thepattern of alliance development, or if they were better described ashigh–low–high or other patterns. Testing was done in several ways. First,we used the mean WAI scores for each of the 44 cases to construct aChance–corrected Coefficient of Proportionality Matrix. This correlationmatrix allows cases to be examined for shifts across a series of cases,regardless of their absolute value. This means that the shape of the alliancedevelopment may be examined independently of the level of the alliancescores. We used Ward’s method to see if the cases would cluster by patternof development. Ward’s method is a fairly conservative method, whichconstructs fairly compact (minimum variance) clusters.

Large breaks in similarity occurred to produce two clusters, eachconsisting of four highly similar cases. Examination of the two clustersindicated that both were forms of linear increase, with the first (r � .46 to.87) cluster characterized by a steady, but gradual, increase across thelength of treatment with little variation, and we called this pattern linear–stable.

Table II. WORKING ALLIANCE BY OUTCOME CORRELATIONS

Phase Session Treatment

One Two Three Three Fifteen Thirty Mean

FactorOne

PearsonCorrelation �.444 �.516 �.364 �.277 �.479 �.327 �.524

Sig. (2–tailed) .006 .000 .024 .092 .002 .044 .000Factor

TwoPearson

Correlation �.167 �.329 �.325 �.063 �.281 �.255 �.325Sig. (2–tailed) .280 .030 .032 .682 .064 .094 .032


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The second cluster (r � .24 to .67) was distinguished by a an initialdrop in alliance scores followed by a relatively slow development with peaklevels not being reached until the seventh to ninth session followed bystable scores, and we labeled this late–linear. No other patterns of alliancedevelopment were identified using the cluster analytic technique.

Identification of Alliance CurvesWe then employed a second method to determine if linear or quadratic

patterns were present. Both linear and quadratic patterns can be detectedusing ANOVAs to describe regression curves. ANOVAs generated foreach model were examined to determine if adding a quadratic term betterdescribed the shape of the alliance over time compared to a simple linearrelationship.

Since many potential curves could be associated with a positive findingfor a quadratic relationship, the coders were asked to examine each of thecurves and to determine if the curves were best described by a high–low–high, linear, or stable pattern.

Four coders examined each of the curves and classified each as beinghigh–low–high, linear increase, or other (Kappa � .90). To determine if acase could be categorized as having undergone a local period of ruptureand repair as measured by the WAI, the same four coders were givengraphs of each of the 44 cases and asked to identify rupture and repaircycles.

A total of 29 cases (66%) were identified as having a linear trend byregression analysis with ANOVA (significant at the .05 level or better),indicating that WAI scores improved over the course of treatment. Afterexamining each of the regression curves, coders identified 13 cases (30%)as being best categorized as having a linear trend. All of the cases identifiedby the coders, and all of the cases in each of the two clusters, wereidentified as having a linear trend in the ANOVA analysis.

Identification of Rupture–and–Repair EventsRupture–and–repair patterns were identified differently from more

global trends (e.g., linear, high–low–high, etc.). Cases that demonstratedmicrorupture–and–repair events are not easily detected by statistical pro-cedures. Although these patterns have a distinctive shape, consisting of adrop in alliance scores with a subsequent return, the length, severity, andtiming of these episodes may be different in each case. It was, therefore,necessary to use coders to identify these rupture–and–repair episodes.

If we define ruptures in the therapeutic alliance as “disagreementsabout tasks or goals or problems with the relational bond” (Safran et al.,


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in press, manuscript p. 6), and if it is true that when ruptures areaddressed, the alliance improves (Forman & Marmar, 1985; Lansford,1986; Safran & Muran, 2000), then we hypothesized that periods ofdecreased alliance levels, with a subsequent return to predrop levels,would reflect this process. We defined a complete rupture–and–repairevent as a downward shift in WAI ratings from stable (consistent ordropping no more than .25 point, or an increase in the previous session),with a drop of one WAI point in one session (moderate) or more than onepoint (serious) in one or more consecutive sessions (starting with an initialdrop of 1 or more points), with a subsequent return to within .25 point ofthe predrop level or higher within 3 to 5 sessions.

The same four coders who classified regression curves also identifiedrupture events. They were able to reliably identify cases as being rupturefree, having only moderate ruptures, or serious ruptures (Kappa � .91). Atotal of 22 cases (50%) were coded as having ruptures. Thirteen (30%) ofthese were classified as having serious events. See figure I for an example

Figure 1LINE GRAPH OF WORKING ALLIANCE RATINGS (MEAN) BY SESSION.


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of a case with a single rupture–repair episode, which starts in session 16and ends in session 18.

CategorizationCases were categorized in several ways. Those cases that formed a

coherent cluster after applying Wards method formed a category. Thosefor which a linear trend was detected by the initial ANOVAs werecategorized as “significant linear”. Those for which a linear trend wasidentified by the coders were categorized as “coder–rated linear”. Becausecoders agreed about only two cases as being best described by a globalhigh–low–high pattern, this category was not included in the final analysis.Cases identified as having local rupture patterns were categorized as “anyruptures”. Those with only moderate ruptures were categorized as “onlymoderate ruptures” and those with patterns of only serious ruptureswereclassified as “only serious ruptures”.

We ran ANOVAs, using the General Linear Model of SPSS (9.0), foreach category to test the degree to which they related to outcome for factorone or factor two. Treatments categorized as linear by ANOVA and coderswere not found to be related significantly to outcome on factor one.However, cluster 1 (the stable linear group) showed a relationship toimproved outcome on factor one (symptom reduction) with a low–leveleffect size and good power (F (2, 44) � 4.497 p � .045 r � .31). Similarly,there was no significant relationship between linear development patternsas defined by ANOVA, coder or cluster analysis and factor two (interper-sonal functioning). There also was no relationship between the presence ofrupture–and–repair episodes and outcome on factor two.

Since rupture–and–repair cycles, as operationalized here, were notsignificantly related to outcome, a secondary analysis was run to determineif variability in the alliance was predictive of outcome. To do this, thestandard deviation for each patient’s WAI scores was correlated withoutcome for each factor. A moderately strong relationship was foundbetween the standard deviation of the WAI scores and factor one (r �.345, p � .042), indicating that a patient’s improvement on factor one(symptom reduction) is negatively correlated with variability on alliance.Factor two (interpersonal functioning) was not found to be significantlycorrelated with variability in WAI scores (r � .028). Additionally, toexplore the different findings between this study and Kivlighan andShaugnessy (2000) , an additional analysis was conducted. The Kivlighanand Shaughnessy (2000) study found that treatments with brief high–low–high patterns were positively correlated with outcome. This study found


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no such relationship. We conjectured that this discrepancy might beexplained by the brevity of the treatment in all of Kivlighan and Shaugh-nessy’s cases. In this study, because of the greater length of treatment, thealliance continued to change and develop after rupture–and–repair events.As a result, there was no guarantee that cases including rupture–and–repair events would end on a “terminal high” as did those in the Kivlighanand Shaughnessy study. To determine if this difference in treatment lengthhad an effect on the relationship between pattern development andoutcome, the WAI scores for session 3 were subtracted from those ofsession 30. Eighteen of the 22 cases containing rupture–and–repair eventshad higher scores at session thirty than at session three, indicating that amajority of cases (81%) with rupture–and–repair episodes ended withalliance scores as high or higher than hose with which they began.

Treatment ConditionsIn addition to looking for an overall relationship among alliance level,

pattern of alliance development, and outcome, the data was also analyzedfor relationships among the three treatment conditions and patterns ofalliance development. No significant relationship was found betweenalliance levels and treatment group. A series of Chi–Square tests were runto test for relationships between type of alliance pattern developed withtreatment group. The percentage of cases with ruptures was higher in theBRT group (a total of 10 ruptures in a total of 66% of the cases) than ineither CBT or BAP condition (with nine ruptures in 53% of the cases and3 ruptures in 33% of the cases respectively. The relationship approachedsignificance (�2 � 4.725, p � .094).

There also was no significant relationship found between linear in-crease and treatment condition (�2 � .625, p � .732). There was amoderately significant relationship (r (2, 44) � .38, p � .042) betweentreatment condition and variability. The BRT condition was found to havesignificantly greater variability (M � .66) than BAP (M � .51) and CBT(M � .49). One additional finding is that the linear stable cluster of fourcases found to be related to improved outcome was made up of three CBTand one BAP case.

DISCUSSION

The hypothesis that alliance development would be characterized by alinear increasing pattern and treatments demonstrating localized (three tofive session) rupture–and–repair episodes was supported. As predicted,there was no evidence of a global high–low–high pattern of alliance


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development and decay. Rather, alliance development was characterized inhalf of the cases observed by local rupture–and repair–episodes. While thefinding supports the notion that many treatments will undergo a series ofstrains in the relationship that must be repaired if the treatment is to besuccessful, it appears that these strains are more localized than had beenpreviously predicted. Additionally, more–rupture and–repair events wereseen in BRT than in BAP or CBT, indicating that rupture–and–repairevents may occur differently in different types of treatment.

The hypothesis that treatments demonstrating a linear trend or rup-ture–and–repair episodes would be related to improved outcome, receivedlimited support. No relationship between the presence of rupture–and–repair episodes and outcome was found. There also was no relationshipfound between a statistically significant linear trend or coder rated lineartrend and outcome, but one cluster of four cases classified as stable–linearwas found to have a significant relationship to improved outcome on factorone (symptomatology). Finally, variance in WAI ratings was found to benegatively correlated with outcome on factor one (symptomatology).

There are a number of possible explanations for the failure to find anysignificant relationship between the presence of rupture–and–repair epi-sodes and outcome. First, the way in which ruptures in the alliance wereoperationalized in this study may not accurately reflect actual ruptureevents. Working from a definition that ruptures in the alliance are char-acterized by disagreements about tasks or goals, or problems with therelational bond, we hypothesized the WAI scores, which dropped andthen returned to pre–drop levels, would reflect this process. Although theclassifications of moderate and serious rupture events were made todiscriminate levels of disagreement, we did not consider the number orseverity of rupture events in this analysis. Currently, there has been notheoretical prediction about the pattern alliance ruptures make. Safran andMuran (2000) state that the process of resolving ruptures may, in fact, leadto further ruptures. In describing the BRT model, Safran wrote, “In thisapproach, the treatment process is conceptualized as ongoing cycles oftherapeutic enactment, disembedding and understanding, enactment anddisembedding” (Safran, 2002, p. 171).

Nevertheless, there is no clear notion of how many (or few) ruptureevents lead to improvement. It is possible to imagine cases in which patientand therapist encounter, and work through, a significant rupture around acore maladaptive interpersonal issue and then move on to other topics.Perhaps being able to survive this one conflict, or feel understood, just thisonce, is enough to lead to significant improvement. It is just as easy to


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imagine, however, that a patient may need to work through a particularconflict several times with a therapist before being able to experience it ina new way. The current study did not set out to determine how suchrupture events lead to change, but rather to determine if the absence orpresence of rupture events (as defined by drops and returns on the WAI)were related to outcome. A more nuanced exploration of the depth,timing, and number of these events, based on a more detailed model,might yield a better understanding of how the pattern of ruptures may berelated to outcome.

The additional findings, variance in WAI ratings was negatively corre-lated with outcome, and that only the most stable cluster of cases display-ing a linear pattern was correlated with improved outcome, make inter-pretation more difficult. Regardless of the specific pattern that alliancedevelopment had been expected to take, be it the global high–low–highpattern or the more local, rupture–and– repair events predicted here, thereis broad consensus among theorists that fluctuations in the therapeuticrelationship are both unavoidable and form an important component ofthe change process. These theorists (e.g. Bordin, 1994; Forman & Marmar,1965; Horvath and Luborsky,1993; Muran 2001; Rhodes, Hill, Thompson& Elliott, 1994; Safran, Crocker, McMain & Murray, 1990; Safran &Muran 1994, 1998, 2000; Tracey, 1989) suggest that it is through thesedisagreements, misunderstandings, and conflicts, that patients learn criticallessons about how to balance the needs of the self and the needs of others.Tracey (1989), and Horvath and Luborsky (1993) suggest that whentherapists do not notice periods of tension or disagreement, they shouldbegin to question if the treatment needs to be changed, noting that it isimportant to be aware that during periods when therapy goes “toosmoothly” might represent a problem in the therapeutic work.

The belief that having the experience of working through conflicts withan empathic and responsive listener is an essential part of therapeuticchange, reflects years of clinical theory and experience backed by compel-ling anecdotal evidence. This has lead researchers to attempt to discoverthe way therapeutic technique interacts with the alliance and shapes itsdevelopment.

Finding patterns of alliance development consistent with the belief thata degree of conflict is an essential element of change has proven to be adifficult task. Studies that found these patterns (e.g. Bernard et al., 1980;Bernard & Schwartz, 1981; Patton et al., 1997; Kivlighan & Shaughnessy,2000) have been hampered by methodological problems. Conversely, thefinding that a strong, stable alliance is related to improved outcome has


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been highly consistent (Joyce & Piper, 1990; Kivlighan & Shaughnessy,1995; Krupnick et al., 1996) findings of this study, that higher alliancelevels were strongly and fits well with the related to improved outcome andthat increased variability between sessions was related to poorer outcome.The small cluster of stable linear cases, which were positively related withsymptom reduction, also suggest that a steadily increasing alliance withlittle between–session variation is more conducive to improvement than amore dramatically fluctuating alliance.

There are several possible explanations for this contradiction betweenthe theory and the findings. First, the shape of the alliance may meandifferent things for different patients. As Bordin (1994) suggests, for somepatients, good outcome will be associated with a stable alliance. For others,as Tracey (1989) suggests, an overly stable alliance represents collusionbetween patient and therapist to avoid difficult topics or over complianceby the patient. Similarly, the presence of rupture–and–repair events maymean different things in different treatments. For some patients, theseevents may represent the uncovering and working through of maladaptiveinterpersonal cycles, for others it may be more indicative of an inability toform or maintain a consistent relationship or engage in therapeutic work.If this is true, than rather than looking for globally generalizable patterns,investigators need to focus on factors that might cause particular dyads towork in the alliance in a particular way.

Just as alliance patterns vary depending on the particular treatmentdyad, there is some evidence in this study that the shape the alliance takesrelates to treatment condition. There were marginally more cases withrupture events in the BRT than in BAP and CBT conditions. There wasgreater variability in BRT than CBT or BAP cases, and three of the fourmembers of the stable, high–alliance cluster, which was found to besignificantly related to improved outcome on factor one (symptom reduc-tion), were seen in the CBT condition. While these findings are certainlysuggestive, the effect sizes were small and the relationships marginal.Caution should be taken in interpreting these results. Bordin (1994)contends that different treatments will produce different forms of alliance,and presumably, different patterns of alliance development. It may be thatBRT therapists are taught to focus on rupture events while CBT therapistsare more likely to smooth over misunderstandings that may alter thepattern of alliance development. While the findings of this study indicatean area that should be investigated in further detail, there is not currentlyenough information to draw any real conclusions.

It is possible that the way alliance and outcome were measured in this


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study was not sensitive to the kind of changes that come from workingthrough conflicts in the therapeutic relationship. Most significantly, theWAI may not be able to detect some of the most important kinds ofrupture events. Since the WAI is given at the end of the session and askspatients questions about how they are feeling at that moment, it cannotcapture misunderstandings or strains that took place and were resolvedwithin the session. Since the WAI can only look at shifts between sessions,rather than within them, it is possible that it is missing a critical part of thenegotiation and change process. Researchers, such as Forman and Marmar(1985), Lansford (1986), and Safran, Muran and Samstag (1994), whofound that directly addressing strains, misunderstandings, and ruptures ledto improvement in alliance scores and predicted improved outcome,looked at events that took place and were addressed within a given session.

The WAI may not measure the kinds of relational factors central to thenegotiating process. The WAI focuses on agreement between patient andtherapist. It is clearly vital for patient and therapist to agree on what theyare trying to accomplish and how. This basic agreement on the centralgoals of a treatment—and the methods used to achieve them—maybe afairly stable core of the therapeutic relationship. Shifts in this basicagreement may reflect an inability to establish a firm foundation fortreatment. What may be more important for some patients, however, is tolearn that they can disagree with their therapists without disrupting therelationship. The elements of the therapeutic relationship that may becentral to change may have much more to do with patients feeling theirtherapist is willing to listen, understand and respect them, even whenexpressing anger, anxiety, disappointment, hopelessness, etc. It may, there-fore, be less important that the patient and therapist work throughconflicts about a particular task, than it is that the patient feel free toexpress his or her doubt, discomfort, or skepticism and believe that thetherapist is taking him or her seriously. In these instances, a therapist’swillingness to explain a task, or change it, may be the curative factor.Negotiations can take place in very brief moments, and may never beexplicitly stated, and thus, could not be reflected by an instrument thatmeasures problems lasting more than one session.

Similarly, the outcome measures, which reflect standard measures ofsymptomatology and interpersonal functioning, may not reflect the kind ofchanges that would be brought about by working through alliance rup-tures. Safran and Muran (2000) suggest that working through ruptures,whether explicitly or implicitly, “. . . can have an impact on the fundamen-tal way in which patients construe self–other interactions” (p. 16). Muran


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(2002) refers to the process of measuring this particular type of shift astheory–specific change, and suggests that this process of rupture repairmight lead to changes in self–relations centered on “dimensions such asawareness, nurturance, expansion and agency” (p. 123). It may be possiblethat focusing on, and working with, ruptures not only keeps patients intreatment, but provides opportunities for a unique kind of growth that isnot reflected by standard measures.

Results from this study seem to suggest that the level of the alliance, asmeasured by the WAI, rather than the shape of its development, ispredictive of outcome. Given the limitations of the WAI in trackinginterpersonal process, however, it may be more a function of the way inwhich alliance is defined. The WAI has clearly demonstrated that thealliance, defined by agreement on tasks, goals and bond, is a powerfulcomponent of change in therapy. It may be necessary to develop othertools to determine, with greater precision, how that change takes place.

Acknowledgements: The research presented in this article was supported in part by GrantMH50246 from the National Institute of Mental Health.

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