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An examination of the relationships among clients'affect regulation, in-session emotional processing, theworking alliance, and outcomeJeanne C. Watson a , Evelyn J. McMullen a , Meghan C. Prosser b & Danielle L Bedard ca University of Toronto, Ontario Institute for Studies in Education, Department of AdultEducation and Counselling Psychology , Toronto, Ontario, Canadab Private practicec London Health Sciences Centre , London, Ontario, CanadaPublished online: 18 Nov 2010.
To cite this article: Jeanne C. Watson , Evelyn J. McMullen , Meghan C. Prosser & Danielle L Bedard (2011) An examinationof the relationships among clients' affect regulation, in-session emotional processing, the working alliance, and outcome,Psychotherapy Research, 21:1, 86-96, DOI: 10.1080/10503307.2010.518637
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An examination of the relationships among clients’ affect regulation,in-session emotional processing, the working alliance, and outcome
JEANNE C. WATSON1, EVELYN J. McMULLEN1, MEGHAN C. PROSSER2, &
DANIELLE L BEDARD3
1University of Toronto, Ontario Institute for Studies in Education, Department of Adult Education and Counselling
Psychology, Toronto, Ontario, Canada; 2Private practice & 3London Health Sciences Centre, London, Ontario, Canada
(Received 24 August 2009; accepted 9 August 2010)
AbstractThe objectives were to examine the relationships among clients’ affect regulation capacities, in-session emotional processing,outcome, and the working alliance in 66 clients who received either cognitive�behavioral therapy or process-experientialemotion-focused therapy for depression. Clients’ initial level of affect regulation predicted their level of emotionalprocessing during early and working phases of therapy. Clients’ peak emotional processing in the working phase of therapymediated the relationship between their initial level of affect regulation and their level of affect regulation at the end oftherapy; and clients’ level of affect regulation at the end of therapy mediated the relationship between their peak level ofemotional processing in the working phase of therapy and outcome. Clients’ affect regulation at the end of therapy predictedoutcome independently of the working alliance. The findings suggest that clients’ level of affect regulation early in therapyhas a significant impact on the quality of their in-session processing and outcome in short-term therapy. Limitations of thestudy and future directions for research are discussed.
Keywords: cognitive�behavioral therapy; depression; alliance; emotion in therapy; experiential/existential/humanistic
psychotherapy; outcome research; process research; affect regulation
In an effort to better understand the factors that
contribute to positive therapeutic outcomes, re-
searchers have turned their attention to identifying
client characteristics that influence in-session pro-
cesses and outcome (Hardy et al., 2001; Hersoug,
Høglend, Havik, von der Lippe, & Monsen,
2009; Joyce, Piper, Ogrodniczuk, & Klein, 2007;
Ogrodniczuk, Piper, Joyce, McCallum, & Rosie,
2003; Quilty et al., 2008; Zuroff et al., 2000). One
pretherapy characteristic that has not received much
attention in the literature is clients’ capacity to
regulate their affect. Affect regulation, defined as
how people process, modulate, and express their
emotional experience, is viewed as an important
determinant of psychopathology and as a target of
change in psychotherapy (Bradley, 2000; Greenberg
& Watson, 2006; Watson, 2007). Poor affect regula-
tion has been implicated in a number of different
disorders, including chronic fatigue (Godfrey,
Chalder, Ridsdale, Seed, & Ogden, 2007), bulimia
(Stice, 1999), opiate addiction (Giyaur, Sharf, &
Hilsenroth, 2005), complicated grief (Ogrodniczuk
et al., 2003), and depression (Greenberg & Watson,
2006).
Several theorists have suggested that a number of
conditions, including depression, may be character-
ized by emotional and cognitive processing difficul-
ties that interfere with the ability to modulate affect.
On the basis of the finding that depressed people
show more excessive control of emotion than others,
Beutler, Engle, Oro’Beutler, Daldrup, and Meredith
(1986) suggested that they fail to process intense
emotional information, which in turn interferes with
their expression and modulation of emotional exp-
erience. Similarly, Elliott, Watson, Goldman, and
Greenberg (2003) characterized depression as a chr-
onic state of narrowed negative experiencing. Further
evidence of restricted emotional processing in de-
pression has been found with research showing that
depressed people recall more negative memories
and selectively attend to negative stimuli in their
environments, which interferes with their ability to
Correspondence concerning this article should be addressed to Jeanne C. Watson, Department of Adult Education, Community
Development and Counselling Psychology, OISE/UT, 252 Bloor Street West, 7th floor, Toronto, Ontario M5S 1V6, Canada. Email:
Psychotherapy Research, January 2011; 21(1): 86�96
ISSN 1050-3307 print/ISSN 1468-4381 online # 2011 Society for Psychotherapy Research
DOI: 10.1080/10503307.2010.518637
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regulate their affective experience (Kennedy-Moore
& Watson, 1999). More recently, Watson, Goldman,
and Greenberg (2007) observed that clients’ ability
to regulate their affective experience distinguished
good from poor outcome in process-experiential
therapy, an emotion-focused, short-term psychother-
apy for depression.
The important role that clients’ ability to regulate
their affect plays in psychotherapy outcome is con-
sistent with studies that have found that the quality of
clients’ emotional processing in the session has been
linked to positive client outcomes in psychotherapy
(Castonguay, Goldfried, Wiser, Raue, & Hayes,
1996; Pos, Greenberg, Goldman, & Korman, 2003;
Stanton et al., 2000; Watson & Bedard, 2006;
Whelton, 2004). Several studies have revealed sig-
nificant differences in the manner in which good-
and poor-outcome cases process their emotional
experience during the session (Pos et al., 2003;
Watson & Bedard, 2006). Watson and Bedard
(2006) found that good-outcome clients in both
process-experiential therapy, an emotion-focused
approach (PE-EFT), and cognitive�behavioral ther-
apy (CBT) for depression began, continued, and
ended therapy at higher modal and peak experiencing
levels during the session than did clients with poor
outcome. Good-outcome clients in both PE-EFT
and CBT engaged in deeper exploration, referred to
their emotions more frequently, were more internally
focused, and examined and reflected on their experi-
ence to create new meaning and resolve their
problems in personally meaningful ways more than
poor-outcome clients. In contrast, clients with poorer
outcomes were not as engaged in processing their
emotional experience, nor did they reflect on or pose
questions about their experience during the session
to examine it and try to understand the origins and
implications of their experience more fully. As a
result, poor-outcome clients did not report important
shifts in perspective or feeling during the session.
Similarly, Pos et al. (2003) found that clients’ level of
experiencing late in therapy mediated the relation-
ship between their early experiencing and outcome,
and that the working alliance made an independent
contribution to outcome after controlling for clients’
experiencing level in client- centered therapy and PE-
EFT to predict outcome. Moreover, clients’ emo-
tional processing in the session has been found to be
beneficial across a range of therapeutic approaches,
including CBT (Castonguay et al., 1996; Godfrey
et al., 2007; Leahy, 2002; Stanton et al., 2000) and
psychodynamic therapy (Giyaur et al., 2005).
To enhance treatment effectiveness and better
understand the change process, it is important to
establish links between clients’ pretreatment char-
acteristics, psychotherapy process, and outcome.
The goal of the current study was to examine the
relationship between initial level of affect regulation,
in-session emotional processing, the working alli-
ance, and outcome in a group of clients treated for
depression in a randomized clinical trial comparing
the effectiveness of CBT and PE-EFT (Watson,
Gordon, Stermac, Kalogerakos, & Steckley, 2003).
A second objective was to test the convergent and
discriminant validity of the Observer-Rated Measure
of Affect Regulation (O-MAR).
Hypotheses
It was hypothesized, first, that clients’ level of affect
regulation at the beginning of therapy would predict
their level of emotional processing early in therapy;
second, that clients’ level of affect regulation at the
beginning of therapy would predict their level of
emotional processing during the working phase of
therapy; third, that clients’ level of emotional proces-
sing during the working phase of therapy would
mediate the relationship between their level of affect
regulation at the beginning of therapy and their level
of affect regulation at the end of therapy; fourth, that
clients’ level of affect regulation at the end of therapy
would mediate the relationship between their highest
level of emotional processing during the working
phase of therapy and outcome; and fifth, that clients’
level of affect regulation at the end of therapy would
predict outcome over and above the working alliance.
Method
Participants
Clients. The sample comprised 66 clients (67%
female, 33% male) who participated in a randomized
clinical trial comparing PE-EFT and CBT in the
treatment of depression (Watson et al., 2003). All
clients were diagnosed with major depression accord-
ing to DSM-IV criteria using the Structured Clinical
Interview for DSM-IV (Spitzer, Williams, Gibbon, &
First, 1995) and were assigned to either PE-EFT (20
female, 13 male) or CBT (24 female, 9 male). Clients
ranged in age from 21 to 65 years (M�41.52, SD�10.82). Regarding ethnicity, 91% identified them-
selves as European, 6% as Asian, and 3% as Hispanic.
A majority of clients (56%) had a college degree; the
remaining 44% either completed a secondary level of
education or had a graduate degree. In terms of
marital status, 42% were married or living common
law, 42% were single, and 16% were separated,
divorced, or widowed. Thirty-four clients (51%), 17
each in the PE-EFT and CBT groups, were diag-
nosed with Axis II personality disorders: 20 (58%)
Affect regulation, emotional processing, outcome 87
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with obsessive�compulsive, 20 with avoidant, one
with histrionic, one with schizoid, three with narcis-
sistic, two with dependent, and four with paranoid
personality disorder. The Global Assessment of
Functioning scores ranged from 51 to 65 (M�58.17). There were no significant differences be-
tween the groups in terms of demographic variables.
Therapists. A total of 15 therapists participated:
eight CBT (six female, two male) and seven PE-EFT
(six female, one male). Therapists ranged in age
from 26 to 43 years (M�32.73, SD�6.08). Four-
teen identified themselves as European and one as
Asian. The majority of the therapists were master’s/
doctoral candidates in counseling psychology at a
large metropolitan university in southern Ontario,
and two were psychologists. Level of experience
ranged from 1 to 15 years (M�5.23, SD�4.74).
There were no significant differences between CBT
and PE-EFT therapists in terms of experience level,
age, education, or gender.
Process raters. There were five process raters, all
female and all European. They ranged in age from
24 to 52 years. All were master’s/doctoral candidates
in counseling psychology at a large metropolitan
university in southern Ontario.
Treatments
CBT. The CBT protocol was conducted accord-
ing to cognitive therapy treatment for depression
outlined by Beck, Rush, Shaw, and Emery (1979).
The treatment was primarily a cognitive therapy with
some behavioral components, such as the recording
of daily activities and behavioral experiments.
PE-EFT. This treatment followed the manual
developed by Greenberg, Rice, and Elliott (1993).
PE-EFT integrates client-centered and gestalt tech-
niques, including two-chair, empty-chair, systematic
evocative unfolding, and focusing, to resolve clients’
cognitive-affective problems in therapy. When thera-
pists felt it was most appropriate, they implemented
specific interventions at client markers or statements
that indicated clients were experiencing specific
processing difficulties. There was a general expecta-
tion that therapists would implement a minimum of
one intervention every two to three sessions from
Session 3 through 15.
Process Measures
The Experiencing Scale (EXP; Klein,
Mathieu, Gendlin, & Kiesler, 1969). This pro-
cess measure assesses clients’ moment-to-moment
emotional processing during the therapy hour. Client
statements are rated on a 7-point scale in terms of
the extent to which they talk about or use their
affective experience as a referent during therapy, and
explore and reflect on their inner experience to
achieve self-understanding and problem resolution
(Klein, Mathieu-Coughlan, & Kiesler, 1986). At
Level 1 clients discuss events, ideas, or others without
any reference to the self or their emotions; at Level 2
they refer to the self without expressing emotions; at
Level 3 clients refer to their reactions about external
events; at Level 4 they share their experience and
subjective worldview; at Level 5 clients begin to
purposefully explore and examine their personal
reactions and subjective worldviews; at Level 6 clients
gain awareness of previously tacit feelings and mean-
ings; and at Level 7 they make continuous reference
to their emotions as part of an ongoing process of
understanding and devising ways of being in the
world (Klein et al., 1986). Clients’ experiencing has
been related to good outcome (Klein et al., 1986; Pos
et al., 2003; Watson & Bedard, 2006). Interrater
reliability coefficients have ranged from .76 to .91,
with rating re-rating correlation coefficients of ap-
proximately .80 (Klein et al., 1986).
In the present study, four raters (two primary and
two secondary) were trained to an acceptable level of
agreement with an expert according to the training
manual (Klein et al., 1969) for the EXP (Klein et al.,
1986). The four raters were organized into three
different pairs. One pair rated the middle 20 minutes
of Session 1, overlapping on 69% of the data. All
intraclass correlation coefficients (ICCs) in this
study were a two-way, fixed, single measure, abso-
lute agreement type (McGraw & Wong, 1996;
Shrout & Fleiss, 1979). For Session 1 ratings, the
ICC was .67 (pB.000) for modal ratings and .76
(pB.000) for peak ratings. The ICC is strongly
influenced by variance, and ratings for Session
1 were restricted between 2 and 4, which likely
deflated ICC scores. The coders had 89% agreement
on modal ratings and 87% on peak ratings.
The data for the hypotheses were divided across
the three pairs of raters. ICCs for the modal and
peak ratings, respectively, were as follows: .90 (pB
.001) and .90 (pB.001) for the first pair of raters;
.80 (pB.001) and .81 (pB.001) for the second pair;
and .78 (pB.001) and .78 (pB.001) for the third
pair. Levels greater than .75 can be considered
excellent agreement beyond chance (Cicchetti,
1994; Shrout & Fleiss, 1979).
O-MAR (Watson & Prosser, 2004). The
O-MAR assesses clients’ affect regulation based
on five subscales of emotional processing: (1)
Level of Awareness, (2) Modulation of Arousal, (3)
88 J. C. Watson et al.
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Modulation of Expression, (4) Acceptance of Affec-
tive Experience, and (5) Reflection on Experience.
Each item is rated on a 7-point Likert scale, with
higher scores signifying more optimal levels of func-
tioning. An overall score is calculated as the average of
the five ratings. Preliminary findings in an earlier
study involving 50 participants indicated that the O-
MAR has high internal consistency (early O-MAR�.86; late O-MAR�.93), and there is preliminary
evidence of construct and predictive validity (Prosser
& Watson, 2007). Preliminary data on the construct
validity of the O-MAR were obtained by correlating
the O-MAR full-scale score with the Problem-
Focused Style of Coping subscales, which distinguish
between reflective, suppressive, and reactive coping
styles. As expected, O-MAR scores were positively
correlated with a reflective coping style (r�.40) and
negatively correlated with suppressive (r��.52) and
reactive (r��.51) coping styles. The current study
expanded the data set to 66. Two independent raters
were trained on the O-MAR to an acceptable level of
agreement. They rated the data, overlapping on 70%
of the data set. Interrater reliability for the O-MAR
(N�66) was significant (ICC�.78, pB.001, early
sessions; ICC�.87, pB.001, late sessions). Each
client’s mean scores across the five subscales for early
sessions and again for later sessions were used for the
analyses.
Postsession Outcome Measure
Working Alliance Inventory�Short Form
(WAI-S; Horvath & Greenberg, 1989). The
WAI-S is a 12-item self-report questionnaire derived
from Bordin’s (1979) conceptualization of the work-
ing alliance. It measures the agreement between the
participants on the goals and tasks of therapy and
the quality of the bond. Each item is rated on a
7-point Likert scale ranging from never (1) to always
(7). This instrument possesses high internal consis-
tency (.93 for the client-rated scale) and good
construct validity. Furthermore, the WAI has been
shown to have good concurrent and predictive
validity through its correlations with other measures
of the therapeutic relationship and with outcome
measures (Horvath & Greenberg, 1986).
Outcome Measures
Beck Depression Inventory (BDI; Beck,
Ward, Mendelson, Mock, & Erbaugh, 1961).
The BDI is a 21-item inventory for assessing
depression. Scores of 10 and higher are regarded as
symptomatic of depression. Test�retest reliability has
been reported at .65 (Ogles, Lambert, & Sawyer,
1995). The BDI has been shown to have good
concurrent validity and internal consistency reported
at .86 (Beck & Steer, 1984). Test�retest reliability
has been reported at .65 (Ogles et al., 1995).
Inventory of Interpersonal Problems (IIP;
Horowitz, Rosenberg, Baer, Ureno, &
Villasenor, 1988). This 127-item self-report instru-
ment measures distress arising from interpersonal
sources. Responses are scored according to a cir-
cumplex model divided into eight octants corre-
sponding to eight subscales: Domineering/
Controlling, Vindictive/Self-Centered, Cold/Dis-
tant, Socially Inhibited, Nonassertive, Overly Ac-
commodating, Self-Sacrificing, and Intrusive/Needy.
The IIP has been shown to possess high internal
consistency, reliability, and validity (Horowitz et al.,
1988) and high test�retest reliability (r�.90; Hansen
& Lambert, 1996).
Rosenberg Self-Esteem Inventory (RSE;
Rosenberg, 1965). A 10-item version of the RSE
(Bachman & O’Malley, 1977) was used to assess
clients’ levels of self-esteem. This instrument has
shown good internal consistency and validity. High
internal reliability (.89�.94), high test�retest relia-
bility (.80�.90), and adequate sensitivity to change
have been reported.
Symptom Checklist-90-Revised (SCL-90-R;
Derogatis, Rickels, & Roch, 1976). This 90-item
self-report questionnaire measures general psycho-
logical distress. Derogatis et al. (1976) reported
internal consistency ranging from .77 to .90 and
test�retest reliability between .80 and .90 over a 1-
week interval.
Dysfunctional Attitudes Scale (DAS;
Weissman & Beck, 1978). The DAS is a 40-item
inventory of dysfunctional attitudes measuring
vulnerability to depression. It has high internal
reliability coefficients and test�retest reliability coef-
ficients (Kuiper & Olinger, 1989).
Procedure
The BDI, RSE, DAS, IIP, and SCL-90-R are all
client self-report instruments and were completed
posttherapy. The WAI-S was completed after every
session, and mean scores were used for the analyses
in the current study. Clients’ level of affect regulation
was rated at the beginning (Session 1 or 2) and at the
end (Session 15 or 16) of therapy using videotaped
segments and transcripts when available, consisting
of the middle 20 minutes of each session. To
demonstrate O-MAR and client EXP as distinct
Affect regulation, emotional processing, outcome 89
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constructs, the same middle-20-minute portion of
the session was also coded on EXP.
Clients’ level of experiencing over the course of
therapy was rated using transcripts of three sessions.
One session was chosen from early in therapy (Ses-
sions 2�4) and the other two were chosen from the
later working phase of therapy (Sessions 5�15).
Sessions were chosen based on clients’ levels of
observed emotional expression, for example, when
clients’ speech was ragged or there were other changes
in vocal quality, such as crying, voice cracking,
volume fluctuations (e.g., rising as a result of anger
or softening as a result of tearfulness or the expression
of some other emotion). Choosing sessions in which
clients were emotional was an attempt to address the
uniformity myth, which assumes that client process is
the same within sessions and across therapy (Elliot
et al., 2004; Greenberg & Safran, 1987; Greenberg,
Watson, & Goldman 1998; Pos et al., 2003). The
identification of sessions in which clients were
aroused ensured that clients’ emotions were activated,
and that meaningful and relevant excerpts of clients’
in-session emotional processing were being ade-
quately tested in the study. Segments of the sessions
began 5 minutes before the onset of emotional
expression and continued until the end of the session
or until the subject matter about which clients had
expressed emotion ended and it was clear that their
emotion had subsided. A change in subject matter
occurred for six of the 198 sessions that were
transcribed and rated on experiencing, and in these
cases the segment ended 5 minutes after the deviation.
Results
Prior to analyses, the variables were screened for
accuracy of data entry, missing values, and potential
univariate outliers and to test for univariate normal-
ity. To determine the internal consistency of the O-
MAR for the present sample (N�66), Cronbach’s
alpha was calculated. Consistent with Prosser and
Watson (2007), the O-MAR showed high internal
consistency: early O-MAR a�.86 and late O-MAR
a�.93. The interitem correlations for each of the
subscales ranged from r�.36 to r�.86. The correla-
tions are presented in Table I.
Intercorrelations Among Affect Regulation,
Experiencing, Alliance, and Outcome
To establish affect regulation, as measured by the O-
MAR, and emotional processing, as measured by the
EXP, as distinct constructs, Pearson product�moment correlation coefficients were calculated for
data rated on the middle 20 minutes of Session 1.
No significant relationship was found between these
variables for modal (r�.07; range, �.02 to .21) and
peak (r�.19; range, �.03 to .19) scores, providing
support that these two constructs are independent.
The intercorrelations among affect regulation, ex-
periencing, alliance, and the outcome variables used
in the analyses that follow are presented in Table II.
Early Affect Regulation Predicting Emotional
Processing Early in Therapy
To determine whether clients’ level of affect regula-
tion at the beginning of therapy was related to their
emotional processing early in therapy, linear regres-
sion analyses were performed, with clients’ O-MAR
scores from the beginning of therapy as the inde-
pendent variable and clients’ mean modal rating and
peak level of experiencing early in therapy as
the dependent variables. Clients’ O-MAR scores
significantly predicted their mean modal rating,
F(1, 64)�14.999, pB.000 (�.44, R2�.19, ad-
justed R2�.18), and peak level of experiencing,
F(1, 64)�15.053, pB.000 (�.44, R2�.19, ad-
justed R2�.18), as early as Sessions 2 to 4.
Early Affect Regulation Predicting Emotional
Processing in Midtherapy
To determine whether clients’ level of affect regula-
tion at the beginning of therapy predicted their level
of emotional processing during the working phase of
therapy, a linear regression analysis was performed
with clients’ O-MAR scores from the beginning of
therapy as the independent variable and mean modal
rating and peak level of experiencing (highest rating
of the two sessions from the working phase of
therapy) at midtherapy as the dependent variables.
Clients’ O-MAR scores significantly predicted their
mean modal rating, F(1, 64)�6.46, pB.01 (�.30,
Table I. Internal Consistency Reliability Analyses for Observer-Rated Measure of Affect Regulation (O-MAR) Subscales (N�66)
Item�total correlations Range of interitem correlations
Variable Early O-MAR Late O-MAR Early O-MAR Late O-MAR
1. Awareness and Labeling of Experience .68 .60 .37�.78 .36�.70
2. Modulation of Arousal .61 .75 .38�.61 .36�.82
3. Modulation of Expression .56 .86 .37�.58 .51�.86
4. Acceptance of Experience .76 .92 .57�.65 .63�.86
5. Reflective of Experience .76 .85 .40�.78 .66�.82
90 J. C. Watson et al.
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Table II. Intercorrelations Among Affect Regulation, Experiencing, Alliance, and Outcome (N�66)
Variable 1 2 3 4 5 6 7 8 9 10 11 12
1. Early O-MAR *2. Late O-MAR .38*** *3. Early modal EXP .44**** .32*** *4. Early peak EXP .44**** .36*** .75**** *5. Mid modal EXP .30** .43**** .66**** .45*** *6. Mid peak EXP .32*** .56**** .52**** .52**** .64**** *7. Mean WAI-S .05 .31** .13 .13 .15 .29** *8. Post BDI �.20 �.50**** �.12 �.37*** �.13 �.39**** �.49**** *9. Post RSE .19 .54**** .29** .42**** .18 .38*** .35*** �.64**** *
10. Post DAS �.11 �.47**** �.18 �.32** �.09 �.27** �.36*** .46**** �.71**** *11. Post IIP �.26** �.39*** �.19 �.25* �.07 �.30** �.45**** .68**** �.60**** .67**** *12. Post SCL�GSI �.23 �.37*** �.15 �.40**** �.03 �.34*** �.36*** .72**** �.57**** .50**** .58**** *
Note. O-MAR, Observer-Rated Measure of Affect Regulation; EXP, Experiencing Scale; WAI-S, Working Alliance Inventory� Short Form; BDI, Beck Depression Inventory; RSE, Rosenberg
Self-Esteem Inventory; DAS, Dysfunctional Attitudes Scale; IIP, Inventory of Interpersonal Problems; SCL�GSI, Symptom Checklist-90-Revised, Global Symptom Index.
*p�.051. **pB.05. ***pB.01. ****pB.001.
Affect
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R2�.09, adjusted R2�.08), and peak level of
experiencing, F(1, 64)�7.187, pB.01 (�.32,
R2�.10, adjusted R2�.09), during the working
phase of treatment.
Hierarchical Regression of Early�Late Affect
Regulation Mediated by Peak Experiencing
To determine whether clients’ level of emotional
processing during the working phase of therapy
mediated the relationship between level of affect
regulation at the beginning of therapy and level of
affect regulation at the end of therapy, the proce-
dures outlined by Baron and Kenny (1986) were
followed. Three different regression analyses were
performed to test mediation. Table III presents
the results of the regression analyses.
The results indicated that clients’ affect regulation
(independent variable) at the beginning of therapy
significantly predicted the mediator, clients’ peak
level of emotional processing from the working phase
of therapy (Equation 1.1 in Table III), and the
dependent variable, clients’ level of affect regulation
at the end of therapy (Equation 1.2). In the final
equation (1.3), the relationship between the inde-
pendent and dependent variables remained signifi-
cant, and peak emotional processing score from the
working phase of therapy also predicted the depen-
dent variable while controlling for the independent
variable. However, as predicted, the weight for
clients’ affect regulation scores at the beginning of
therapy dropped from .38 to .22 when clients’ peak
level of emotional processing was entered into the
regression model, indicating that clients’ emotional
processing partially mediates the relationship be-
tween their early and later affect regulation scores.
Last, results from the Sobel test confirmed the
statistical significance of the mediational pathway
found through regression analysis.
Hierarchical Regression of Experiencing�Outcome Mediated by Affect Regulation
To determine whether clients’ level of affect regula-
tion at the end of therapy mediated the relationship
between level of emotional processing during the
working phase of therapy and outcome, the proce-
dures outlined by Baron and Kenny (1986) were
again followed. Results of the regression analyses
(Table IV) revealed that clients’ peak level of emo-
tional processing during the working phase of
therapy significantly predicted the mediator, clients’
O-MAR scores at the end of therapy (Equation 1.1).
In the second step, five linear regression analyses
were conducted to determine whether the indepen-
dent variable, clients’ peak level of emotional proces-
sing during the working phase of therapy, predicted
the dependent variable, clients’ outcome scores on
the BDI, RSE, DAS, IIP, and SCL-90-R at the end
of therapy (Equations 1.2 to 5.2, respectively, in
Table IV). Clients’ peak level of emotional processing
during the working phase of therapy significantly
predicted outcome on all five outcome measures.
In the third step, five hierarchical linear regression
analyses were performed to test whether the med-
iator, clients’ affect regulation at the end of therapy,
predicted the dependent variable, clients’ outcome
scores on the BDI, RSE, DAS, IIP, and SCL-90-R at
the end of therapy, while controlling for the inde-
pendent variable. The model significantly predicted
outcome on the five outcome measures at the end of
therapy. Clients’ O-MAR scores at the end of
therapy significantly predicted outcome, after con-
trolling for clients’ peak experiencing scores on the
BDI, RSE, DAS, and IIP and approached signifi-
cance for the SCL-90-R (Equations 1.1 to 5.3). As
predicted, the weight for clients’ peak level of
emotional processing dropped from �.39 to �.16
on the BDI, from .38 to .11 on the RSE, from �.27
to �.00 on the DAS, from �.30 to �.12 on the IIP,
and from �.34 to �.20 on the SCL-90-R, and
became nonsignificant as a predictor in each of the
models, indicating that clients’ affect regulation at
the end of therapy fully mediates the relationship
between their level of experiencing midtherapy and
outcome on four of the five indices. Last, results
from the Sobel tests confirmed the statistical
significance of the mediational pathways found
through regression analyses.
Table III. Hierarchical Regression of Early�Late Affect Regulation Mediated by Peak Experiencing (N�66)
Equation IV DV b t p R2 F (df) Sobel test (p): ratio PM
1.1 Early O-MAR Peak EXP .318 2.681 .009 .10 7.187(1, 64)***
1.2 Early O-MAR Late O-MAR .375 3.238 .002 .14 10.484(1, 64)***
1.3 Early O-MAR Late O-MAR .220 2.064 .043
Peak EXP .487 4.564 .000 .35 17.280(2, 63)**** 2.304 (.021) .41
Note. IV, independent variable; DV, dependent variable; O-MAR, Observer-Rated Measure of Affect Regulation; peak EXP, highest peak
score for the working phase of therapy as measured by the Experiencing Scale; Ratio PM, proportion of total effect mediated.
***pB.01. ****pB.001.
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Hierarchical Regression of Affect Regulation
and Alliance Predicting Outcome
Finally, to determine whether level of affect regula-
tion at the end of therapy predicted outcome over
and above the working alliance, clients’ mean work-
ing alliance score was entered into the regression for
each of the five outcome measures. Table V presents
the results of the regression analyses. The model
significantly predicted outcome on each outcome
measure at the end of therapy, including the BDI,
RSE, DAS, IIP, and SCL-90-R (Equations 1.1�5.3, respectively). Clients’ affect regulation score
late in therapy remained a significant predictor of
outcome on all the measures, and their mean work-
ing alliance scores significantly predicted outcome
independently on three of the outcome measures,
including the BDI, IIP, and SCL-90-R (Equations
1.3, 4.3, and 5.3, respectively) but was not a
significant predictor of RSE (Equation 2.3) and
DAS (Equation 3.3).
Discussion
The objectives of the current study were to examine
the relationships among clients’ capacity for affect
regulation at the beginning of therapy, their in-session
emotional processing, the working alliance, and their
affect regulation skills at the end of therapy as well as
changes on other outcome measures. Affect regula-
tion was defined as clients’ level of awareness of their
emotional experience, their capacity to modulate
both arousal and expression, their acceptance of their
emotional experience, and their capacity to reflect on
that experience. The results show that clients’ early
level of affect regulation predicted their level of
emotional processing during the early and working
phases of therapy. In addition, the quality and depth
of clients’ emotional processing in the session
mediated the relationship between their early level
of affect regulation and their level of affect regulation
at the end of therapy; and clients’ level of affect
regulation at the end of therapy mediated the relation-
ship between their peak level of emotional processing
in the working phase of therapy and outcome on all
the measures. In addition, clients’ level of affect
regulation at the end of therapy predicted outcome
independently of the working alliance. This highlights
the importance of specific change processes that are
independent of the quality of the working alliance that
develops between client and therapist to resolve
specific issues in therapy.
The findings suggest that clients’ initial capacity for
affect regulation influences how they engage with
their emotional experience in the session, and that the
quality of their emotional processing or engagement
in the session, particularly their capacity to reflect on
their emotional experience to resolve issues, predicts
changes in their capacity to regulate their affect at the
end of therapy as well as improvement in depression,
self-esteem, dysfunctional thoughts, interpersonal
problems, and the number of complaints and symp-
toms at the end of a short-term therapy for depres-
sion. These findings support those of a number of
studies showing that the depth of clients’ emotional
processing in session is related to positive outcome
(Castonguay et al., 1996; Pos et al., 2003; Watson &
Bedard, 2006). Recently, in a series of case studies
Table IV. Hierarchical Regression of Experiencing�Outcome Mediated by Affect Regulation (N�66)
Equation IV DV b t p R2 F (df) Sobel test (p): ratio PM
1.1 Peak EXP Late O-MAR .557 5.370 .000 .31 28.834(1, 64)****
1.2 Peak EXP BDI �.385 �3.334 .001 .15 11.118(1, 64)****
1.3 Peak EXP BDI �.155 �1.194 ns
Late O-MAR �.412 �3.163 .002 .27 11.345(2, 63)**** �2.725 (.006) .60
2.2 Peak EXP RSE .379 3.229 .002 .14 10.430(1, 62)***
2.3 Peak EXP RSE .106 0.819 ns
Late O-MAR .484 3.738 .000 .30 13.293(2, 61)**** 3.068 (.002) .72
3.2 Peak EXP DAS �.265 �2.150 .036 .07 4.622(1, 61)**
3.3 Peak EXP DAS �.004 �0.028 ns
Late O-MAR �.463 �3.342 .001 .22 8.282(2, 60)**** �2.837 (.005) .99
4.2 Peak EXP IIP �.299 �2.450 .017 .09 6.003(1, 61)**
4.3 Peak EXP IIP �.116 �0.806 ns
Late O-MAR �.324 �2.262 .027 .16 5.763(2, 60)**** �2.072 (.038) .61
5.2 Peak EXP SCL-90-R �.344 �2.885 .005 .12 8.322(1, 62)***
5.3 Peak EXP SCL-90-R �.201 �1.415 ns
Late O-MAR �.253 �1.782 ns (.08) .16 5.896(2, 61)*** �1.693 (.090) .42
Note. IV, independent variable; DV, dependent variable; peak EXP, highest peak score for the working phase of therapy as measured by the
Experiencing Scale; O-MAR, Observer-Rated Measure of Affect Regulation; BDI, Beck Depression Inventory; RSE, Rosenberg Self-
Esteem Inventory; DAS, Dysfunction Attitudes Scale; IIP, Inventory of Interpersonal Problems; SCL-90-R, Symptom Checklist-90-
Revised; Ratio PM, proportion of total effect mediated.
**pB.05. ***pB.01. ****pB.001.
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that examined good and poor outcome in PE-EFT,
Watson et al. (2007) observed that clients who did
not improve in short-term therapy had difficulty
becoming aware of, labeling, and modulating their
feelings. In contrast, good-outcome clients valued
their emotional experience and were able to reflect on
it and use it to resolve problematic issues in therapy.
Similarly, Quilty et al. (2008) found that openness to
experience as well as being innovative, curious, and
less neurotic were patient characteristics associated
with better treatment outcomes.
The findings suggest that clients who do well in
short-term treatments come into therapy with certain
emotional processing skills and capacities that are then
potentiated in the work that they do with their
therapists, resulting in significant changes. However,
it is important to attend to those clients who do not
enter therapy with the capacity to regulate their affect
as well or engage in deep emotional processing in order
to modify our treatment packages to take account of
their different needs and respond appropriately. If we
are able to identify clients’ difficulties early, then we
may be in a position to develop interventions that can
be implemented early in therapy to assist clients with
their emotional processing. For example, it may be
possible to teach clients emotional processing skills,
such as helping them become aware of their emotional
experience, and develop labels for it so that they can
then reflect on it to better modulate their arousal and
expression of emotion. One such task in PE-EFT is
focusing (Gendlin 1981, 1996). This was initially
developed by Gendlin (1964, 1974) to help clients
engage effectively in client-centered therapy. Helping
clients to become aware of and label their feelings is
important if they are to be able to reflect on them to
resolve problematic issues, identify hot cognitions, or
engage in certain interventions like two-chair or empty-
chair tasks in PE-EFT (Safran & Greenberg, 1982;
Watson et al., 2007). Other tasks like chair work help
clients develop skills related to emotional expression.
A strength of this study is that client self-report
measures of outcome and observer-rated measures
of affect regulation and emotional processing were
used to investigate the relationship between in-
session process, outcome, and the working alliance,
thereby limiting monomethod variance. Moreover,
the findings provide support that the O-MAR is
psychometrically sound, with adequate overall relia-
bility and excellent convergent, divergent, and pre-
dictive validity. As expected, facets of emotional
processing as measured by the O-MAR were corre-
lated with a measure of clients’ in-session emotional
processing. These findings speak to the robust
nature of both constructs and provide preliminary
construct validity for both measures. The findings
provide support for the divergent validity of the O-
MAR given that it is not related to the WAI. A
strength of the O-MAR is that it is rated by third-
party observers and thus allows research clinicians to
limit monomethod variance. Most of the measures
that have been developed to date to assess clients’
affect regulation are based on clients’ self-report,
Table V. Hierarchical Regression of Affect Regulation and Alliance Predicting Outcome (N�66)
Equation IV DV b t p R2 F (df)
1.1 O-MAR BDI �.498 �4.596 .000 .25 21.124(1, 64)****
1.2 WAI-S BDI �.491 �4.503 .000 .24 20.278(1, 64)****
1.3 O-MAR BDI �.384 �3.663 .001
WAI-S �.373 �3.558 .001 .37 18.816(2, 63)****
2.1 O-MAR RSE .554 5.104 .000 .30 26.054(1, 62)****
2.2 WAI-S RSE .352 2.906 .004 .12 8.763(1, 62)***
2.3 O-MAR RSE .480 4.194 .000
WAI-S .168 1.468 ns .32 14.348(2, 61)****
3.1 O-MAR DAS �.465 �4.104 .000 .22 16.839(1, 61)****
3.2 WAI-S DAS �.361 �3.024 .004 .13 9.146(1, 61)***
3.3 O-MAR DAS �.383 �3.176 .002
WAI-S �.214 �1.777 ns .26 10.297(2, 60)****
4.1 O-MAR IIP �.390 �3.307 .002 .15 10.938(1, 61)***
4.2 WAI-S IIP �.448 �3.917 .000 .20 15.344(1, 61)****
4.3 O-MAR IIP �.251 �2.058 .044
WAI-S �.348 �2.858 .006 .25 10.197 (2, 60)****
5.1 O-MAR SCL�90-R �.367 �3.104 .003 .13 9.364(1, 62)***
5.2 WAI-S SCL-90-R �.357 �3.010 .004 .13 9.061(1, 62)***
5.3 O-MAR SCL-90-R �.269 �2.158 .035
WAI-S �.254 �2.032 .046 .19 7.126(2, 61)***
Note. IV, independent variable; DV, dependent variable; WAI-S, Working Alliance Inventory; O-MAR, Observer-Rated Measure of Affect
Regulation; BDI, Beck Depression Inventory; RSE, Rosenberg Self-Esteem Inventory; DAS, Dysfunction Attitudes Scale; IIP, Inventory of
Interpersonal Problems; SCL-90-R, Symptom Checklist-90-Revised.
***pB.01. ****pB.001.
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including the Scales for Experiencing Emotion (Behr
& Becker, 2002), the Trait Meta Mood Scale
(Salovey, Mayer, Goldman, Turvey, & Palfai,
1995), and the Difficulties in Emotion Regulation
Scale (Gratz & Roemer, 2004).
The development of process measures is useful and
necessary in psychotherapy research because they not
only provide a way of assessing clients’ characteristics
to establish their relationship with outcome but also are
excellent teaching tools and are clinically valuable in
assessing treatment interventions moment to moment
in therapy. Process measures can be used to identify
treatment markers, which can help clinicians tailor
their treatments to different clients so that they can be
optimally responsive to their clients moment to mo-
ment in the session. However, more work is required to
investigate the relevance of the O-MAR with different
client groups and to see whether the current findings
can be replicated. In future work it will be important to
investigate whether clients’ affect regulation capacities
continue to differentiate good from poor outcome and
to see whether people who enter therapy with lower
levels of affect regulation can improve with different
treatments or longer term therapy.
There are several limitations with the present study.
First, it is based on a small sample size. The findings
need to be replicated with a larger sample to see
whether the findings are generalizable. Second, the
present sample consisted of a depressed population
and was relatively homogenous; thus, the results may
not be generalizable to other populations (e.g., clients
suffering form anxiety or addictive behaviors). Third,
it was only possible to rate a limited number of sessions
for each client, so the picture that emerges may not be
representative of each client’s performance in every
session. Fourth, it would be important given the ratio
of women to men (2:1) to try to increase the number of
men in future samples to see whether there are
differences between men and women in terms of their
capacities to regulate their affect overall and whether
there are differences in terms of the quality of their
emotional processing during in the session.
Acknowledgements
This research was supported by Social Sciences and
Humanities Research Council of Canada Research
Grant 410-2005-0222 to Jeanne C. Watson. The
authors thank the reviewers for their comments on
an earlier draft of this article.
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