Two Aspects of the Therapeutic Alliance:
Differential Relations With Depressive Symptom Change
Christian A. Webb, Robert J. DeRubeis,
and Jay D. Amsterdam
University of Pennsylvania
Richard C. Shelton and Steven D. Hollon
University of Colorado at Boulder
Objective: The therapeutic alliance has been linked to symptom change in numerous investigations.
Although the alliance is commonly conceptualized as a multidimensional construct, few studies have
examined its components separately. The current study explored which components of the alliance are
most highly associated with depressive symptom change in cognitive therapy (CT). Method: Data were
drawn from 2 published randomized, controlled clinical trials of CT for major depressive disorder (n ?
105, mean age ? 40 years, female ? 62%, White ? 82%). We examined the relations of 2 factor-
analytically derived components of the Working Alliance Inventory (WAI; Horvath & Greenberg, 1986,
1989) with symptom change on the Beck Depression Inventory—II (BDI–II; Beck, Steer, & Brown,
1996) that occurred either prior to or subsequent to the examined sessions. WAI ratings were obtained
at an early and a late session for each therapist–patient dyad. Results: Variation in symptom change
subsequent to the early session was significantly related to the WAI factor that assesses therapist–patient
agreement on the goals and tasks of therapy but not to a factor assessing the affective bond between
therapist and patient. In contrast, both factors, when assessed in a late session, were significantly
predicted by prior symptom change. Conclusions: These findings may reflect the importance, in CT, of
therapist–patient agreement on the goals and tasks of therapy. In contrast, the bond between therapist and
patient may be more of a consequence than a cause of symptom change in CT. The implications of these
results and directions for future research are discussed.
Keywords: alliance, cognitive therapy, depression
The therapeutic alliance has been examined in relation to treat-
ment outcome across a variety of treatment modalities and mental
health problems. In meta-analytic reviews, stronger alliances have
been found to be associated with better outcomes (Horvath &
Symonds, 1991; Martin, Garske, & Davis, 2000). Several studies
(e.g., Adler, 1988; Hatcher & Gillaspy, 2006; Horvath & Green-
berg, 1989; Paivio & Bahr, 1998) have reported on the relation
between outcome and the constituent subscales of the Working
Alliance Inventory (WAI; Horvath & Greenberg, 1986, 1989), the
most frequently used alliance measure. The Task subscale of the
WAI has tended to exhibit a stronger association with outcome
than have the Goal or Bond subscales (see Strunk, Brotman, &
DeRubeis, 2010, for an exception). Therapist–patient agreement
on the tasks of therapy, therefore, may play an especially important
role in alliance–outcome associations.
These findings are derived from studies that have employed
theory-derived subscales of the alliance (i.e., the Bond, Goal, and
Task subscales). Findings from factor analytic studies suggest that
this may not be the most appropriate way to partition the WAI. For
example, Andrusyna, Tang, DeRubeis, and Luborsky (2001) con-
ducted an exploratory factor analysis of the WAI and obtained
findings similar to those reported in an earlier factor analysis
(Hatcher & Barends, 1996). Specifically, in the study by An-
drusyna et al., a two-factor structure of the measure emerged,
This article was published Online First April 11, 2011.
Christian A. Webb and Robert J. DeRubeis, Department of Psychology,
University of Pennsylvania; Jay D. Amsterdam, Department of Psychiatry,
University of Pennsylvania; Richard C. Shelton, Department of Psychiatry,
Vanderbilt University; Steven D. Hollon, Department of Psychology, Van-
derbilt University; Sona Dimidjian, Department of Psychology, University
of Colorado at Boulder.
This article is based in part on Christian A. Webb’s doctoral dissertation,
which was supported by a Social Sciences and Humanities Research
Council of Canada doctoral fellowship. The Cognitive Pharmacothera-
py—II trial was supported by Grant MH50129 (R10) to Robert J. DeRubeis
and Grants MH55875 (R10) and MH01697 (K02) to Steven D. Hollon
from the National Institute of Mental Health (NIMH), Bethesda, Maryland.
The University of Washington trial was supported by NIMH Grant
MH55502 (R01) first to Neil S. Jacobson and, after his death, to David L.
Dunner. GlaxoSmithKline provided medications and pill placebos for both
We are grateful to Dianne L. Chambless and Jacques P. Barber for their
helpful comments on this article. In addition, we thank Robert J. Kohlen-
berg, Keith S. Dobson, Karen B. Schmaling, and David L. Dunner for their
leadership of the University of Washington trial and for making data
available for this project.
Correspondence concerning this article should be addressed to Chris-
tian A. Webb, Department of Psychology, University of Pennsylvania,
3815 Walnut Street, Philadelphia, PA 19104-1696. E-mail: webb@
Journal of Consulting and Clinical Psychology
2011, Vol. 79, No. 3, 279–283
© 2011 American Psychological Association
where the first factor (Agreement) consisted of all of the items
from the Task and Goal subscales and one item from the Bond
subscale. The second factor (Relationship) consisted of the remaining
items from the Bond subscale. This factor structure is not surprising
given the relatively high correlations often reported between the Task
and Goal subscales of the WAI (e.g., Busseri, & Tyler, 2003; Hatcher
& Gillaspy, 2006; Horvath & Greenberg, 1989).
Studies of alliance components and their relation to outcome have
tended to rely on patient- or therapist-rated versions of the WAI. Patient
ratings would seem preferable given that theories of the alliance empha-
size the patient’s experience. However, patients’ ratings of the alliance
can be contaminated by their judgment of the benefits already experi-
enced in therapy, and they are subject to response biases, such as acqui-
escence bias or central tendency bias (Tashakkori & Teddlie, 1998). The
influence of prior symptom change on patients’ ratings can be mitigated
to some degree by procedures that control for temporal confounds, but
response biases can be neither estimated nor controlled for statistically in
investigations of the relation between patient-rated alliance and outcome.
These potential problems also exist for therapist-rated alliance measures.
In contrast, observer-rated methods typically employ evaluators
to the rated session. Moreover, unlike patients’ or therapists’ ratings,
those of observers can be evaluated for interrater reliability, such that
any biases a given rater might display can be addressed with further
training and estimated in a reliability analysis. In addition, studies that
employ the same raters (patients or therapists) to assess both the
alliance and outcome, as is frequently the case, may yield alliance–
outcome correlations that are inflated due to problems related to
problems may be minimized with the use of independent observers
who do not also assess outcome.
The vast majority of studies of the relation between the therapeutic
alliance and outcome have not controlled for temporal confounds
(Barber, 2009), leaving open the possibility that significant alliance–
outcome associations reflect, at least in part, the influence of prior
symptom improvement on the alliance (Stiles, Shapiro, & Elliott,
1986). In the context of a design that minimizes temporal confounds,
our goals were to examine the relation between the WAI, assessed
early in cognitive therapy (CT), and subsequent depressive symptom
change, as well as the association between the WAI, assessed late in
treatment, and prior symptom change. In the event that significant
alliance–outcome relations were obtained, we planned to conduct
exploratory analyses to determine which components of the alliance
may be driving these effects. Of specific interest was the relation
between the empirically derived Agreement and Relationship factors
of the WAI and both subsequent and prior symptom change. In
particular, we were interested in whether the components of the
alliance early in therapy that are associated with subsequent symptom
change might differ from those late in therapy that account for its
relation with prior symptom change.
All patients from the CT conditions of the Cognitive Pharma-
cotherapy—II (CPT–II; N ? 60; DeRubeis et al., 2005) and
University of Washington (UW; N ? 45; Dimidjian et al., 2006)
studies were included. Both studies targeted adults with major
depression, and CT was provided for a total of 16 weeks. (For
more detailed information on each of the studies, see DeRubeis et
al., 2005, CPT–II; Dimidjian et al., 2006, UW). Local institutional
review board approval was obtained for all sites, and all patients
provided written informed consent.
WAI short observer-rated version (WAI–O–S; Tracey &
Kokotovic, 1989; Tichenor & Hill, 1989).
12-item observer-rated measure of the quality of the therapeutic
alliance based on Bordin’s (1979) highly cited tripartite concep-
tualization of the construct. Items are rated on a 7-point scale (0 ?
never, 6 ? always). In the current study, we employed the two
factors derived from Andrusyna et al.’s (2001) factor analysis. The
first factor (Agreement) consists of all four of the items from the
Task (1, 2, 8, and 12) and Goal (4, 6, 10, and 11) subscales,
respectively, as well as one item (5) from the Bond subscale. The
second factor (Relationship) consisted of the remaining three items
from the Bond subscale (3, 7, and 9; see Table 3 in Andrusyna et
al., 2001, for a list of all items). The WAI–O–S, henceforth the
WAI, has been rated reliably in prior research (Strunk et al., 2010).
Beck Depression Inventory—2nd Edition (BDI–II; Beck et
The BDI–II, a 21-item self-report measure of depres-
sive symptoms, was administered to all patients in this study prior
to each session. The BDI–II exhibits excellent psychometric prop-
erties (Beck et al., 1996).
The WAI–O–S is a
Therapy sessions were video- and audiotaped. For each therapist–
patient dyad, Session 3 (“early session”) and the third-from-last ses-
sion (“late session”) were rated.1Raters, who took notes while view-
ing each session, provided ratings after the end of the session. If a
videotape was unavailable, we substituted either a videotape from an
adjacent session or an audiotape of the session. Two patients were not
included because they dropped out of treatment prior to Session 2. All
other dropouts (9 CPT–II patients and 5 UW patients) left treatment
between Session 2 and the third-from-last session; these patients were
included in analyses of early, but not late, sessions. In addition,
recordings of early sessions for three patients and late sessions for two
patients were unavailable from the UW study. In total, 100 early
sessions and 87 late sessions were rated.
1Therapist adherence ratings were completed at the third session for
both the UW and CPT–II studies using the observer-rated cognitive be-
havioral subscale of the Collaborative Study Psychotherapy Rating Scale
(CSPRS–CB). We examined the mean of the subset of CSPRS–CB items
assessing therapist adherence to “concrete,” symptom-focused CT tech-
niques (CT-Concrete factor; see DeRubeis & Feeley, 1990), such as
helping patients identify and challenge specific maladaptive cognitions.
The CT-Concrete factor mean (2.83) is similar to that reported in previous
studies (DeRubeis & Feeley, 1990; Feeley et al., 1999) and suggests that
even as early as Session 3, the therapists in the current study were engaging
in concrete, symptom-focused CT techniques. We also examined the
CSPRS–CB items assessing more abstract discussions between the therapist
and patient (CT-Abstract), including psychoeducation about the cognitive
model. The Session 3 CT-Abstract mean of 2.32 suggests that therapists were
also engaging patients in abstract discussion of CT and their treatment.
WEBB ET AL.
Five students from the University of Pennsylvania served as raters.
Each tape was coded by two raters independently according to a
balanced incomplete block design (Fleiss, 1981). Raters were as-
signed no more than one session per therapist–patient dyad. Raters,
who were blind to treatment outcome, site, and the study aims, as well
as to participant and session numbers, received 30 hr of training,
which included didactic instruction on CT for depression and, in
particular, on the construct of the working alliance and the WAI
observer-rated measure. During training, raters practiced coding 12
CT sessions, initially along with the study supervisor (Christian A.
Webb), and later, independently. Subsequent to rating each session,
raters reviewed all of their ratings with the study supervisor to discuss
quality of the working alliance in the session, raters were instructed to
pay attention to any instances in the session during which there
appeared to be shifts in the quality of the working alliance (e.g.,
disagreement about treatment goals or about the usefulness of an
in-session or homework activity). To prevent rater drift, raters met
weekly with the study supervisor to rate a tape independently and to
discuss any discrepancies in ratings.
Means, standard deviations, and correlations for all rated vari-
ables are listed in Table 1. Intraclass correlation coefficients
(ICCs), estimated for the WAI using a random effects model
(Shrout & Fleiss, 1979) for the mean ratings of two raters are also
reported in Table 1. The estimates are in the general range of those
obtained in previous studies using observer-rated alliance scales
(e.g., Strunk et al., 2010; Hanson, Curry, & Bandalos, 2002).
Prediction of Subsequent Symptom Change
Multiple regression analyses were performed to examine the
relation between alliance variables (i.e., WAI, WAI-Agreement,
WAI-Relationship), assessed at the early session, and subsequent
change in the BDI–II.2End of treatment (i.e., Week 16) BDI–II
scores were used as the dependent variable (DV), adjusting for
BDI–II scores obtained just prior to the rated session (i.e., Session
3). Following DeRubeis et al. (2005) and Dimidjian et al. (2006),
we used the last observation carried forward as the DV for patients
who dropped out or failed to complete the final assessment. In all
cases, positive standardized betas (?s) indicate that higher ratings
on the given alliance variable were associated with greater symp-
tom reduction. We performed all analyses using SAS Version 9.2
PROC REG/GLM (SAS Institute, Cary, NC).
The WAI, assessed early in treatment, was a significant predic-
tor of subsequent symptom change, ? ? .23, t(97) ? 2.84, p ? .01.
Agreement, on its own, predicted subsequent symptom change,
? ? .25, t(97) ? 3.02, p ? .01, whereas a nonsignificant trend was
obtained for Relationship, ? ? .15, t(97) ? 1.80, p ? .07. When
both WAI factors were included as predictors and subsequent
symptom change was the criterion, after accounting for Relation-
ship, Agreement was a significant predictor of subsequent symp-
tom change, ? ? .27, t(96) ? 2.39, p ? .02. However, after
controlling for Agreement, the association between Relationship
and subsequent symptom change was no longer significant, ? ?
?.03, t(96) ? ?0.24, p ? .81.3
Prediction of the Alliance From Prior Symptom Change
Following Feeley, DeRubeis, and Gelfand (1999), we computed
a residualized “prior change” score to examine the relation be-
tween alliance variables, assessed at the late session, and prior
change in BDI–II. For each patient, a prior change score was
calculated as the difference between pretreatment BDI–II and late
session BDI–II, adjusting for pretreatment BDI–II. This residual-
ized change score served as the independent variable in the regres-
sion analyses, and the late session alliance variables (WAI, WAI-
Agreement, WAI-Relationship) served as the dependent variables.
The late session WAI was predicted by prior symptom change,
? ? .40, t(85) ? 4.00, p ? .001, as were each of the factors:
Agreement, ? ? .41, t(85) ? 4.11, p ? .0001; Relationship, ? ?
.29, t(85) ? 2.82, p ? .01.4
Consistent with findings from numerous studies of the thera-
peutic alliance (Martin et al., 2000) we found, in a sample of
2There was no evidence of any Study (CPT–II and UW) ? Measure
interaction in any of the analyses reported. Thus, results were reported
using the pooled sample of the two studies. Several outliers were identified.
With respect to the early session, one outlier for both the WAI (z ? ?3.92)
and WAI-Agreement factor (z ? ?3.92) was detected. Similarly, for the
late session, an outlier for the WAI (z ? ?4.22), WAI-Agreement factor
(z ? ?3.88), and WAI-Relationship factor (z ? ?4.63) was identified.
Each of these scores was replaced with the next most extreme nonoutlier
value in the dataset for that variable.
3It is in principle possible that the difference in the strength of the
relation of the Agreement and Relationship factors to subsequent symptom
change could be accounted for by differences in their interrater reliabilities.
When we tested these relations when each was corrected for attenuation
due to unreliability, the same pattern of findings resulted. In addition, we
reran the analyses after degrading the Agreement factor (to reduce its
reliability), such that its ICC matched that of the Relationship factor (i.e.,
ICC .56). The same pattern was observed. The analyses were also rerun
using residualized change scores (see Feeley et al., 1999); they yielded the
same pattern of findings we report in the Results section.
4In an effort to replicate the findings from previous studies, we also
performed analyses using the three WAI theory-derived subscales. First, three
multiple regressions were performed to examine the relation between the three
subscales of the WAI and subsequent symptom change (adjusting for Session
3 BDI–II). The Task (? ? .26, p ? .01), Goal (? ? .21, p ? .02), and Bond
(? ? .17, p ? .04) subscales each significantly predicted subsequent depres-
sive symptom change, with the Task subscale displaying the strongest relation
with symptom change. After we accounted for the other two subscales, the
Task subscale (? ? .30, p ? .08) was associated with subsequent symptom
change at the level of a nonsignificant trend. In contrast, in parallel analyses,
and when the other two subscales were statistically controlled, the Bond (? ?
?.01, p ? .92) and Goal (?? ?.04, p ? .80) subscales bore virtually no
relation to subsequent symptom change. Finally, with respect to the WAI
assessed at the late session, each of the three subscales exhibited similar
relations to prior symptom change (Task: ? ? .40, p ? .001; Goal: ? ? .39,
p ? .001; Bond: ? ? .33, p ? .01).
The correlation between the Agreement and Relationship factors in the late
session was particularly high (r ? .76). It was therefore not surprising that,
while controlling for the other factor, the standardized betas were reduced
substantially in each case (Agreement factor: ? ? .41 3 .20; Relationship
factor: ? ? .29 3 ?.02); the effect remained significant only for the Agree-
ment factor (p ? .01).
TWO ASPECTS OF THE THERAPEUTIC ALLIANCE
depressed patients in CT, that stronger alliances were associated
with greater symptom reduction. Of the few studies that have
included a control for temporal confounds (see Barber, 2009), only
two (Barber, Connolly, Crits-Christoph, Gladis, & Siqueland,
2000; Klein et al., 2003) have reported a significant association
between alliance and subsequent outcome. To our knowledge, this
is the first study of CT to find that subsequent symptom change is
predicted by the alliance.
When we examined the relation between subsequent symptom
change and the two factor-analytically derived components of the
early WAI, Agreement and Relationship, Agreement appeared to
account for most of the predictive variance. In contrast, both
components of the late WAI were associated with prior symptom
change. This pattern of findings may reflect the importance of
therapist–patient agreement on the tasks and goals of CT and
suggests that variation in the bond between therapist and patient
may play a less prominent role in contributing to symptom im-
provement in CT. The bond did vary as a function of prior
symptom change, consistent with the view that it may strengthen
as a consequence of symptom improvement. It is important to note,
however, that at the early session the Relationship factor was
associated with subsequent symptom change at the level of a
nonsignificant trend when the Agreement factor was not included
as a covariate. And although the standardized regression coeffi-
cient (.15) from the latter analysis may be considered small, it is by
no means negligible and is not much smaller than the mean
alliance–outcome correlation of .22 reported in Martin et al.’s
In the current study we examined only the relation between the
alliance assessed at the third session and subsequent outcome. It is
possible that a significant relation between the therapist–patient
bond and subsequent symptom change would have emerged if the
alliance had been assessed earlier or later in treatment. On average,
approximately one third of the symptom change occurred prior to
the early session and, thus, before our alliance assessment. It may
be that a different pattern of results would have emerged if the
alliance had been assessed even earlier in treatment (see also Gelso
& Carter, 1985; Horvath & Greenberg, 1989).
We examined a relatively highly structured form of therapy. It
is unclear to what extent these findings would be replicated in
studies of other treatment modalities, such as dynamic therapy
(Summers & Barber, 2010). It may be that the symptom improve-
ment observed in the current study is at least in part a result of the
particular goals and tasks that are emphasized and pursued in CT
(e.g., those related to identifying, challenging, and modifying
negative cognitions). Motivational interviewing (Miller, & Roll-
nick, 2002), with its empathic, client-centered approach, may offer
helpful tools for therapists to enhance their alliances (including
agreement on the goals and tasks of treatment) with their patients,
particularly those who are especially ambivalent about changing.
Several limitations of the present study should be noted. First,
although it is fundamental to the concept of causal modeling, the
“no omitted variables” assumption is impossible to verify with
observational data. Thus, unmeasured third variable confounds
could have influenced the results. Second, scores on the Agree-
ment and Relationship factors were highly correlated, especially at
the late session, posing problems for the multivariate approach we
took to these data. We attempted to minimize problems that result
from multicollinearity by using two factor-analytically derived
components of the WAI, rather than the three theory-derived
Findings from the present study raise several issues that should
be addressed in future research. First, it will be important to
examine whether the current findings can be replicated in other
samples of depressed patients treated with CT, as well as samples
comprising patients with conditions other than depression and
studies of treatment modalities other than CT. Tests of the robust-
ness of the present findings should also examine alliance–outcome
relations at different assessment points as well as with alternative
methods of assessing the alliance. The results of such future
investigations may lead to the specification of variables that play
especially important roles in therapeutic improvement.
Adler, J. V. (1988). A study of the working alliance in psychotherapy
(Unpublished doctoral dissertation). University of British Columbia,
Andrusyna, T. P., Tang, T. Z., DeRubeis, R. J., & Luborsky, L. (2001). The
factor structure of the Working Alliance Inventory in cognitive-
behavioral therapy. Journal of Psychotherapy Practice and Research,
Barber, J. P. (2009). Toward a working through of some core conflicts in
psychotherapy research. Psychotherapy Research, 19, 1–12. doi:
Barber, J. P., Connolly, M. B., Crits-Christoph, P., Gladis, M., &
Siqueland, L. (2000). Alliance predicts patients’ outcome beyond in-
treatment change in symptoms. Journal of Consulting and Clinical
Psychology, 68, 1027–1032. doi:10.1037/0022-006X.68.6.1027
Means, Standard Deviations, Intraclass Correlation Coefficients, and Correlations for Alliance Variables
agreement factor; Rel ? WAI relationship factor; T1 ? variables assessed at the 3rd session; T2 ? variables assessed at the 3rd-from-last session.
?p ? .01.
N ? 100 for T1 variables; N ? 87 for T2 variables. ICC ? intraclass correlation coefficients; WAI ? Working Alliance Inventory; Agr ? WAI
WEBB ET AL.
Beck, A. T., Steer, R. A., & Brown, G. K. (1996). Manual for the BDI-II. Download full-text
San Antonio, TX: Psychological Corporation.
Bordin, E. S. (1979). The generalizability of the psychoanalytic concept of
the working alliance. Psychotherapy: Theory, Research and Practice,
16, 252–260. doi:10.1037/h0085885
Busseri, M. A., & Tyler, J. D. (2003). Interchangeability of the Working
Alliance Inventory and Working Alliance Inventory, Short Form. Psy-
chological Assessment, 15, 193–197. doi:10.1037/1040-35184.108.40.206
DeRubeis, R. J., & Feeley, M. (1990). Determinants of change in cognitive
therapy for depression. Cognitive Therapy and Research, 14, 469–482.
DeRubeis, R. J., Hollon, S. D., Amsterdam, J. D., Shelton, R. C., Young,
P. R., Salomon, R. M., . . . Gallop, R. (2005). Cognitive therapy vs
medications in the treatment of moderate to severe depression. Archives
of General Psychiatry, 62, 409–416. doi:10.1001/archpsyc.62.4.409
Dimidjian, S., Hollon, S. D., Dobson, K. S., Schmaling, K. B., Kohlenberg,
R. J., Addis, M. E., . . . Jacobson, N. S. (2006). Randomized trial of
behavioral activation, cognitive therapy, and antidepressant medication
in the acute treatment of adults with major depression. Journal of
Consulting and Clinical Psychology, 74, 658–670. doi:10.1037/0022-
Elvins, R., & Green, J. (2008). The conceptualization and measurement of
therapeutic alliance: An empirical review. Clinical Psychology Review,
28, 1167–1187. doi:10.1016/j.cpr.2008.04.002
Feeley, M., DeRubeis, R. J., & Gelfand, L. (1999). The temporal relation
of adherence and alliance to symptom change in cognitive therapy for
depression. Journal of Consulting and Clinical Psychology, 67, 578–
Fleiss, J. L. (1981). Balanced incomplete block designs for inter-rater
reliability studies. Applied Psychological Measurement, 5, 105–112.
Gelso, C. J., & Carter, J. A. (1985). The relationship in counseling and
psychotherapy: Components, consequences, and theoretical antecedents.
Hanson, W. E., Curry, K. T., & Bandalos, D. L. (2002). Reliability
generalization of Working Alliance Inventory scale scores. Educational
and Psychological Measurement, 62, 659–673. doi:10.1177/
Hatcher, R. L., & Barends, A. W. (1996). Patients’ view of the alliance in
psychotherapy: Exploratory factor analysis of three alliance measures.
Journal of Consulting and Clinical Psychology, 64, 1326–1336. doi:
Hatcher, R. L., & Gillaspy, J. A. (2006). Development and validation of a
revised short version of the Working Alliance Inventory. Psychotherapy
Research, 16, 12–25. doi:10.1080/10503300500352500
Horvath, A. O. (2001). The alliance. Psychotherapy: Theory, Research,
Practice, Training, 38, 365–372. doi:10.1037/0033-3220.127.116.115
Horvath, A. O., & Greenberg, L. S. (1986). The development of the
Working Alliance Inventory. In L. S. Greenberg & W. M. Pinsoff (Eds.),
The psychotherapeutic process: A research handbook (pp. 529–556.)
New York, NY: Guilford Press.
Horvath, A. O., & Greenberg, L. S. (1989). Development and validation of
the Working Alliance Inventory. Journal of Counseling Psychology, 36,
Horvath, A. O., & Symonds, B. D. (1991). Relation between working
alliance and outcome in psychotherapy: A meta-analysis. Journal of
Counseling Psychology, 38, 139–149. doi:10.1037/0022-018.104.22.168
Klein, D. N., Schwartz, J. E., Santiago, N. J., Vivian, D., Vocisano, C.,
Castonguay, L. C., . . . Keller, M. B. (2003). Therapeutic alliance in
depression treatment: Controlling for prior change and patient charac-
teristics. Journal of Consulting and Clinical Psychology, 71, 997–1006.
Martin, D. J., Garske, J. P., & Davis, M. K. (2000). Relation of the
therapeutic alliance with outcome and other variables: A meta-analytic
review. Journal of Consulting and Clinical Psychology, 68, 438–450.
Miller, W. R., & Rollnick, S. (2002). Motivational interviewing: Preparing
people for change (Vol. 2). New York, NY: Guilford Press.
Paivio, S. C., & Bahr, L. B. (1998). Interpersonal problems, working
alliance, and outcome in short-term experiential therapy. Psychotherapy
Research, 8, 392–407.
Shrout, P. E., & Fleiss, J. L. (1979). Intraclass correlations: Uses in
assessing rater reliability. Psychological Bulletin, 86, 420–428. doi:
Stiles, W. B., Shapiro, D. A., & Elliott, R. (1986). Are all psychotherapies
equivalent? American Psychologist, 41, 165–180. doi:10.1037/0003-
Strunk, D. R., Brotman, M. A., & DeRubeis, R. J. (2010). The process of
change in cognitive therapy for depression: Predictors of early inter-
session symptom gains. Behaviour Research and Therapy, 48, 599–606.
Summers, R. J., & Barber, J. P. (2010). Psychodynamic therapy: A guide
to evidence-based practice. New York, NY: Guilford Press.
Tashakkori, A., & Teddlie, C. (1998). Mixed methodology: Combining
qualitative and quantitative approaches. Thousand Oaks, CA: Sage.
Tichenor, V., & Hill, C. E. (1989). A comparison of six measures of
working alliance. Psychotherapy: Theory, Research, Practice, Training,
26, 195–199. doi:10.1037/h0085419
Tracey, T. J., & Kokotovic, A. M. (1989). Factor structure of the Working
Alliance Inventory. Psychological Assessment, 1, 207–210. doi:10.1037/
Received March 17, 2010
Revision received December 27, 2010
Accepted December 27, 2010 ?
TWO ASPECTS OF THE THERAPEUTIC ALLIANCE