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DYADIC ATTACHMENT DETERMINANTS OF SESSION QUALITY
IN EARLY PSYCHOTHERAPY
João Francisco BARRETO1,2
(FCT Individual Doctoral Grant SFRH/96922/2013 –jfbarreto@fpce.up.pt)
Paula MENA MATOS1
1Faculty of Psychology and Sciences of Education, Center for Psychology at University of Porto, Portugal
2Polytechnic Institute of Porto, Portugal
INTRODUCTION
It is sometimes assumed that a counter-complementary stance towards the relational pull exerted by clients
plays an important role in the change process (Bernier & Dozier, 2002; Mallinckrodt, 2000). Initial evidence
suggests that this can be facilitated by a dissimilar or non-complementary match between relational
preferences within the therapeutic dyad and by attachment security in therapists (see Daniel, 2006). In both
cases, ‘out of style’/’against type’ responses are more likely to occur, which may help disconfirm clients’
problematic working models of relationships and thus facilitate change (Bowlby, 1988). Presumably, client
and therapist attachment dimensions and their combinations will have an effect on session quality
(Goodman, 2000). Research in the field is scarce, but tends to support this hypothesis (Bruck et al., 2006;
Mohr et al., 2005; Romano et al., 2008). Meanwhile, even less is known concerning the variation of session
evaluation over time.
OBJECTIVE
In this paper, we study the impact of patient and therapist attachment dimensions on the evolution of
therapist and client-rated session evaluation in initial stages of psychotherapy.
METHOD
Participants
•12 independent therapeutic dyads in adult psychotherapy working in different community contexts
•Clients (C): 9 women and 3 men, ages from 19 to 58 years-old (M = 29.0, SD = 14.1)
•Therapists (T): 9 women and 3 men, ages from 28 to 55 years-old (M = 42.8, SD = 7.1), 5 to 23 years of
experience (M = 14.3, SD = 5.9); predominant theoretical orientation: 5 psychoanalytic/dynamic, 2
humanistic/experiential, 3 cognitive-behavioral, 3 eclectic/integrative (1 assimilated cognitive-behavioral
and eclectic/integrative)
Instruments
•Experiences in Close Relationships –Relationship Structures (ECR-RS; Fraley et al., 2011; Portuguese version
by Moreira et al., 2014): Self-report designed to assess attachment patterns in different relationships (9
items), scoring for attachment-related Avoidance and Anxiety. In this study, 3 targets were included
(mother, father, and romantic partner or best friend), originating global Avoidance and Anxiety scores
(Cronbach’s alphas in Table 1), to which we added a measure of attachment Security as total scale’s mean
reversed score. Match coefficients in Avoidance and Anxiety were calculated as the absolute difference
between T and C scores on each of these dimensions, higher values meaning increased dissimilarity (as in
Bruck et al., 2005; Bucci et al., 2015)
•Session Evaluation Questionnaire, Form 5 (SEQ; Stiles et al., 2002; Portuguese version by Ribeiro &
Gonçalves, 2009): 21-item semantic differential scale used to assess therapist and client reactions to
specific sessions with a 7-point bipolar adjective format. The scale assesses 4 dimensions, referring to
session perception (Depth and Smoothness) and post-session mood (Arousal and Positivity). In this study,
Depth and Smoothness were selected. In each of these we dropped 1 item to improve internal consistency
(item 3 for Depth and item 2 for Smoothness –see Cronbach’s alphas in Table 1). Evolution in Depth and
Smoothness from 2nd to 5th session (or t1 to t2) was computed as the difference between t2 and t1
respective scores
Procedure
As part of an ongoing study (BINOCULAR –www.fpce.up.pt/binocular/), therapists of different orientations
were invited to participate in a longitudinal study on therapeutic process. All data were collected on-line
(LimeSurvey 1.87®). Regarding the variables reported in this study, T and C attachment (ECR-RS) and socio-
demographic data were assessed prior to 2nd session. T and C session evaluation (SEQ) was measured after
the 2nd session (t1) and after 5th session (t2)
Data Analysis
Aside from the correlational analyses, linear regressions and path analyses were performed using only
manifest variables due to the small sample size. When possible, we used the Actor–Partner Interdependence
Model (APIM) (Kenny, Kashy, & Cook, 2006) to account for the non-independence of the dyadic data and
integrate both actor and partner effects in the same analyses. Variables were centered whenever interaction
effects were tested (Maroco, 2014). Analyses were run with IBM SPSS Statistics 22 and IBM SPSS Amos 23.
RESULTS
For initial data exploration, we performed a series of correlations between the attachment predictors and the
session evaluation outcomes. Table 1 shows the most relevant results. Given the small sample size, we
decided to report non-significant correlations with p<.10, signaling possible tendencies.
Table 1
+p<.10; *p<.05; **p<.01
We further explored the data testing direct and interaction effects of Tand C attachment on t1 and t2
session-specific and t1-t2 evolution SEQ ratings. When performing successive APIMs with session-specific SEQ
dimensions as dependent variables, we found several significant interaction effects, namely: T x C avoidance
on C depth t1 (β=-.54,p= .030); T x C avoidance on C depth t2 (β=-.66,p= .001) and T depth t2 (β=-.58,p=
.002); T anxiety x C avoidance on C depth t1 (β=-.84,p= .008) and t2 (β=-.89,p= .001); and T avoidance x C
anxiety on T depth t2 (β=-.59,p= .017). Figure 1 presents these models, including explained variances for
each dependent variable and attesting that, in most cases, only the interaction effects were significant. In
Figure 2,an example of a significant interaction was investigated by plotting C depth scores predicted by C
avoidance as a function of low (one SD below M), mean (M), and high (one SD above M) values of T
avoidance. The figure indicates that higher C avoidance predicts lower session depth (rated by therapists after
5th session) with Ts higher in avoidance, but predicts greater depth in the case of less avoidant Ts.
Figure 1
Figure 2
Finally, results regarding the same combinations of predictors with t1-t2 evolution of session ratings yielded
only one interaction effect, concerning the impact of T x C avoidance on T-rated depth evolution (β=-.48,p=
.029). Figure 3 shows the models in which significant effects were found, along with explained variances. In
Figure 4, the interaction effect found in this series of analyses is represented.
Figure 3
Figure 4
DISCUSSION / CONCLUSIONS
•Overall, results tend to confirm the impact of Tand C attachment on session quality, particularly concerning
the depth component, which represents the perception of sessions as powerful and valuable (Stiles et al.,
2002)
•Associations seem especially relevant considering that they occur across raters, as with the actual or
tendency for correlations between C anxiety/security and T ratings at t2; and the correlations between the
evolution of depth rated by Cs and Ts attachment anxiety and security. Through this lens, Ts feel they work
at deeper levels with more insecure Cs after initial sessions, and Cs perception of session depth decreases
from 2nd to 5th session with more anxious Ts. This is further confirmed by the partner effects found
regarding T attachment dimensions’ impact on C rated depth evolution
•Taken together, the results involving T anxiety support the findings of Sauer et al. (2003) indicating a
positive effect on C-rated alliance after 1st session and a negative effect over time. This may be interpreted
as a consequence of T’s effort to make Cs feel good about the relationship (Daniel, 2006)
•Non-complementary hypothesis was supported by several results, namely: positive associations of both
anxiety and avoidance dissimilar match with dimensions of session evolution and depth at t2; interaction
effects of Tand C attachment dimensions, suggesting a positive impact of avoidance dissimilarity in session
depth at t1 and t2 and t1-t2 evolution rated by Ts; T anxiety moderating the impact of C avoidance on C-
rated t1 and t2 depth, such that more avoidant Cs do better with more anxious Ts; and C anxiety
moderating the impact of T avoidance on t2 session depth, with more avoidant Ts doing better with more
anxious Cs
•Overall, the combination of attachment avoidance within the dyad seems particularly important for depth
and depth evolution. Figure 4 suggests that a positive evolution requires a combination of low-avoidant Ts
with Cs above a certain level of avoidance. An interpretation for this may be that, on one hand, less
avoidant Ts seeing less avoidant Cs reach higher initial depth levels, making it more likely to evolve
negatively or closer to 0; on the other hand, more avoidant Ts will tend to decrease in session depth,
especially with more avoidant Cs
•Main limitations of the study: small sample, possible common method biases, internal consistency in some
SEQ subscales, measurement error may distort results (structural equation modeling with latent variables
desirable), lack of qualitative data –ongoing longitudinal study may help overcome some of these
difficulties
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processes of therapeutic change. Lanham, MD: Jason Aronson. |Kenny, D. A., Kashy, D. A., & Cook, W. L. (2006). Dyadic data analysis. New York: The Guilford Press. |
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Avoid C Anx C Sec C Avoid T Anx T Sec T Avoid Match Anx Match α
Depth C t1 .-66* .87
Smooth C t1 .75
Depth C t2 .90
Smooth C t2 .80
Depth T t1 .71
Smooth T t1 .70
Depth T t2
.57+.-61* .72** .67* .88
Smooth T t2
.57+.59
Evol Depth C .-73**
.58+
Evol Smooth C .68*
Evol Depth T
.51+.52+
Evol Smooth T
α.79 .88 .81 .93 .90 .95
0
1
2
3
4
5
6
0123456
Depth C t2
Avoid C
Avoid T low
Avoid T high
-1,5
-1
-0,5
0
0,5
1
1,5
0,00 1,00 2,00 3,00 4,00 5,00 6,00
Evol Depth T
Avoid C
Avoid T low
Avoid T high