journal of social and personal relationships-2014-sanford-0265407513518156
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DOI: 10.1177/0265407513518156
published online 10 January 2014Journal of Social and Personal RelationshipsKeith Sanford
behaviors bad, benign, or beneficial?A latent change score model of conflict resolution in couples: Are negative
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Article
A latent change scoremodel of conflictresolution in couples: Arenegative behaviors bad,benign, or beneficial?
Keith SanfordBaylor University, USA
AbstractThis study used latent change score models to examine how couples make progresstoward resolution when they experience conflicts. It examined why negative conflictengagement might sometimes predict increased resolution, and how this processmight be moderated by relationship satisfaction. A sample of 734 people in hetero-sexual marriages or cohabitation relationships were asked to identify an episode ofrelationship conflict and complete a questionnaire measuring types of negative beha-vior, attributions, anger, and soft emotion as well as measures of current discord,peak discord, positive behavior, and types of conflict disengagement. Negativeengagement predicted peak levels of conflict discord, but for people in satisfyingrelationships, this effect was benign because large conflicts predicted large resolutionsregardless of negative engagement levels.
KeywordsCommunication, conflict resolution, couples, latent change, marriage
When couples experience relationship conflicts, partners are likely to have perceptions
regarding levels of conflict discord. These perceptions may include appraisals regarding
the extent to which a conflict is a cause of personal distress, a source of relationship
Corresponding author:
Keith Sanford, Department of Psychology and Neuroscience, Baylor University, One Bear Place #97334,
Waco, TX 76798, USA.
Email: [email protected]
Journal of Social andPersonal Relationships
1–21ª The Author(s) 2014
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DOI: 10.1177/0265407513518156spr.sagepub.com
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tension, and an issue that is unresolved. A couple, then, could be defined as making
progress toward conflict resolution when partners move from a point of experiencing
high discord on a particular issue of conflict to a new point of low discord (or high
accord) in regard to the same issue of conflict. It is important to note that this type of
progress toward resolution involves experiencing a change in conflict discord, and it is
different from merely experiencing a state of resolution at a single point in time. In and
of itself, a person’s current state of resolution may not be highly informative, because if a
person has a conflict that is small and inconsequential, he or she could easily experience
a state of resolution without any meaningful change taking place. Consequently, a state
of resolution might not tell us anything about the processes a person uses when he or
she experiences a significant conflict and needs to move from a point of discord to a new
point of accord with a partner. To understand how people do this, it may be important to
assess perceived resolution progress. Perceived resolution progress could be defined as
the difference between the level of discord a person recalls experiencing at a previous
point in time when a particular conflict was at its peak and that person’s level of discord
regarding the same issue of conflict at the current point in time.
This definition sets a foundation for addressing a key question. How is perceived
resolution progress influenced by the types of negative behaviors, thoughts, and emo-
tions that often occur during conflict interactions? Although these types of negative
conflict variables logically would be inversely correlated with experiencing a state of
resolution, it is not clear how they will predict progress toward resolution. Just because a
behavior, thought, or emotion occurs during conflict does not mean it hinders progress.
In fact, it is possible that couples might use negative behaviors, think negative thoughts,
and experience negative emotions as part of the natural process of addressing and
resolving conflicts (Fincham & Beach, 1999), and, if so, this raises a possibility that
these negative variables might merely be inconsequential or possibly even adaptive
(McNulty & Russell, 2010). This issue is important because, presumably, a couple’s
relationship health will depend on their ability to make progress toward resolution on
those occasions when they experience significant conflicts (Johnson & Roloff, 1998;
Markman, Stanley, & Blumberg, 2001).
Although there is scant research on the predictors of perceived resolution progress,
clues regarding this process may be drawn from a long line of longitudinal research
investigating change in relationship satisfaction. In this area, research has produced two
contrasting sets of findings. One set of studies has found that negative communication
behaviors and negative attributions during conflict are sometimes associated with
beneficial long-term outcomes (Gottman & Krokoff, 1989; Heavey, Layne, & Christen-
sen, 1993; Karney & Bradbury, 1997; McNulty, O’Mara, & Karney, 2008; McNulty &
Russell, 2010; Overall, Fletcher, Simpson, & Sibley, 2009). In line with this type of
inverse effect, studies have also identified situations where the use of positive commu-
nication is associated with an increased risk of future relationship distress (Baucom,
Hahlweg, Atkins, Engl, & Thurmaier, 2006; Schilling, Baucom, Burnett, Allen, &
Ragland, 2003). This body of research is counterbalanced by another equally persua-
sive body of research that has failed to find such inverse effects and instead has found
that negative conflict variables predict future relationship distress (e.g., Karney &
Bradbury,1995; Lavner & Bradbury, 2012; Markman, Rhoades, Stanley, Ragan, &
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Whitton, 2010). Thus, some studies suggest that negative conflict variables are
sometimes adaptive, whereas other studies suggest that these variables are mostly
detrimental. Notably, all these studies have focused on predictors of change in rela-
tionship satisfaction and not on predictors of perceived conflict resolution progress.
However, a consideration of these contrasting findings can suggest three crucial
issues for research on conflict resolution. First, there is a need to clarify the function
of different negative conflict variables; second, there is a need to consider all rele-
vant pathways when modeling change processes in relationships; and third, there is a
need to investigate possible moderating variables.
The first issue is that it is important to clarify the function of negative conflict
variables. These variables include types of negative behavior, cognition, and emotion
that are commonly observed when couples experience conflict. For example, couples
often use hostile forms of communication behavior that include types of criticism and
defensiveness (Gottman, 1994; Heyman, 2001), they make cognitive attributions in
which they blame each other (Bradbury & Fincham, 1990), and they experience
feelings of anger (Sanford, 2007a). In addition, a slightly different negative variable is
called ‘‘soft’’ emotion, and it includes feelings of sadness, hurt, and concern, which are
associated with expressions of vulnerability (Sanford, 2007a) and which sometimes
predict positive outcomes to relationship therapy (Cordova, Jacobson, & Christensen,
1998; Johnson & Greenberg, 1988). In seeking to understand how all these common
negative conflict variables might predict perceived resolution progress, each variable
could be conceptualized to function in two basic ways. As described below, a negative
variable could function primarily as a type of conflict engagement or as a type of
adversarial interaction.
The theoretical rationale for explaining why negative behaviors, thoughts, and
feelings might be beneficial for conflict resolution is that these variables might reflect
types of conflict engagement (Fincham & Beach, 1999), and such engagement may be
necessary for making progress toward resolution. Along this line, studies have found
that withdrawal from conflict is associated with relationship distress (Eldridge, Sevier,
Jones, Atkins, & Christensen, 2007), and researchers have often suggested that neg-
ative conflict processes could be adaptive if they reduce avoidance (Gottman &
Krokoff, 1989; Karney & Bradbury, 1997; McNulty, 2010). If negative conflict
variables reflect types of active conflict engagement, then these variables should have
the opposite function from types of conflict disengagement. For example, their func-
tion would be opposite from disengagement due to withdrawal (including what Wang,
Fink, & Cai, 2012, call ‘‘negative withdrawal’’ and what Gottman, 1994, calls
‘‘stonewalling’’) as well as from disengagement that occurs when one partner passively
hopes the other will take the initiative to address an issue (similar to what Eidelson &
Epstein, 1982, call an ‘‘expectation of mindreading’’).
A contrasting possibility is that negative conflict variables primarily function as types
of adversarial interaction and as such they may produce no direct benefits for resolution
progress. Accordingly, some negative conflict variables have been described as being
‘‘corrosive’’ (Gottman, 1994) or ‘‘hostile’’ (Heyman, 2001). Moreover, behaviors that
involve displays of anger and distress, as well as tactics that involve arguing, comba-
tiveness, yelling, and aggression, may violate people’s standards for ‘‘rationality’’ in
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conflict interaction (Honeycutt & Bryan, 2011). If negative variables are adversarial in
nature, then they are likely to produce conflict escalation (Markman et al., 2001) and
moreover, negative conflict variables would be expected to have the opposite function
from types of collaborative communication. For example, their function would be
opposite from the types of listening and constructive self-expression that are promoted in
educational programs for couples (Markman et al., 2001). In sum, one way to clarify
the function of negative behaviors, thoughts, and emotions is to contrast the function of
these negative variables both with conflict disengagement and with collaborative
communication.
A second issue involves a need to consider all relevant pathways when modeling
change processes. It is especially important to take into account the fact that the ‘‘pre-
change’’ level of a variable will often predict the extent to which that variable changes
(McArdle, 2009). Thus, in considering perceived resolution progress, it is possible that a
person’s level of discord when a conflict is at its peak (the pre-change level of discord)
might predict the total extent of perceived resolution progress (defined as the difference
between peak discord and current discord). In other words, the size of the conflict could
determine the amount of movement toward resolution. This opens a possibility for a
mediated effect pathway in which negative conflict variables predict the level of peak
discord during a conflict, and peak discord in turn predicts the extent of perceived res-
olution progress. This would occur, for example, if negative conflict variables were pri-
marily adversarial in nature, if they consequently produced high levels of peak discord
during conflicts, and if high peak discord was followed by making substantial progress
toward resolution. This would mean that if negative conflict variables predict larger con-
flicts, and if larger conflicts produce larger resolutions, then negative conflict variables
would also predict larger resolutions. An alternate possibility, however, is that there is a
direct effect pathway in which negative conflict variables directly predict the extent of
perceived resolution progress. That is, negative conflict variables may have a direct
effect that remains evident even after controlling for the effects of peak discord. This
type of direct effect would occur, for example, if negative conflict variables were a nat-
ural part of active conflict engagement and if such active engagement was necessary or
beneficial for conflict resolution. In this case, greater engagement would directly predict
greater resolution progress even after accounting for effects pertaining to conflict size.
A crucial feature to notice in these examples is that both a mediated effect (in which
negative conflict variables have an adversarial function) and a direct effect (in which
negative variables function as types of engagement) could potentially produce identical
patterns of results showing that negative conflict variables are positively correlated with
resolution progress. Thus, it is important to use methods that can tease apart distinctions
between direct effects and mediated effects. Notably, this has not always been done in
studies investigating change in relationship satisfaction. Although this issue is arguably
salient to all studies of change processes in couples, studies that have investigated
change across just two time points (e.g., Gottman & Krokoff, 1989) have sometimes
been singled out for criticism in this regard (Cramer, 2003; Woody & Costanzo, 1990).
However, it is possible to address this issue, and to do so even if change is measured
across only two points, by using an approach called a ‘‘latent change score model’’
(McArdle, 2001, 2009). This is a type of structural equation model in which two scores
4 Journal of Social and Personal Relationships
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pertaining to a variable are measured in regard to two different points in time. A latent
change score is created by first accounting for measurement error in the indicators and
then placing constraints on the pair of scores, specifying that the second score (in this
case, current discord) is exactly equal to the first score (in this case, recalled peak dis-
cord) plus change. This approach produces a latent change score (in this case, repre-
senting the extent of perceived resolution progress), which can be used as an outcome
variable in path models. Importantly, these models can include a path from peak discord
to the latent change score, accounting for the fact that that the size of the conflict might
predict the size of the progress toward resolution.
A final issue is that the effects of negative conflict variables may be moderated. Even
if negative conflict variables are associated with resolution progress for some couples,
they may not predict such progress for all couples. For some couples, engagement might
exacerbate conflicts, and large conflicts might fail to produce large resolutions. One
likely possibility is that the direction of effect depends on levels of relationship satis-
faction. According to Karney and Bradbury’s (1995) vulnerability-stress-adaptation
model, a couple’s ability to utilize adaptive processes in their relationship is hindered
when satisfaction is low. Similarly, Gottman (1994) suggests that when satisfaction is
low, conflict interactions often become ‘‘absorbing states,’’ whereby couples are unable
to escape from cycles of negative behavior once those cycles have begun. In this way,
dissatisfied couples might easily become stuck at their peak levels of conflict intensity
and fail to make progress toward resolution. In contrast, when couples are satisfied with
their relationship, the mechanisms of conflict resolution might run more efficiently
(Johnson & Roloff, 1998). This suggests that if negative conflict variables are associated
with greater levels of conflict resolution, either through direct effects or through
mediated effects, these effects may occur primarily when relationship satisfaction is high
and not when satisfaction is low.
To investigate these issues, it is first necessary to develop a valid method for assessing
peak discord and current discord to provide a measure of perceived resolution progress.
Because perceived conflict discord involves personal perceptions of an episode of
conflict, assessments may best be obtained via self-report. In addition, ratings specifi-
cally pertaining to peak discord may need to be obtained retrospectively. This is because
it would be difficult to arrange for participants in a study to provide ratings of peak
discord during actual conflict interactions at the precise moments, on the particular
days, when those conflicts were reaching their peaks. The convergent validity of both
peak discord and current discord could be tested, in part, by examining cross-spouse cor-
relations. Because personal perceptions of conflict discord arise out of a common con-
flict experience that is shared by two partners, it is likely that ratings from two
partners will be at least moderately correlated.
It is important to note that because perceptions of conflict discord are at the core a
type of relationship sentiment, ratings of discord are likely to be highly correlated with
ratings of relationship satisfaction. However, a distinct feature of conflict discord is that
it should pertain to a single issue of conflict, and, thus, ratings of discord should be more
specific than general ratings of global relationship sentiment. This means that if two
partners make ratings of conflict discord for the same issue of conflict, their ratings
should share a context-specific similarity that cannot be explained by partners’ ratings of
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global relationship satisfaction. In other words, the cross-partner correlation for conflict
discord should remain significant after controlling for relationship satisfaction. Another
unique feature of conflict discord is that it should often show substantial change over the
course of a single conflict, and this would contrast with global measures of relationship
satisfaction that often remain relatively stable even over the course of several years.
Overview
This study began with an examination of validity data for a measure of conflict discord,
and then it focused on testing a latent change model of perceived conflict resolution. The
study included four key independent variables: negative communication behavior,
blaming attributions, anger, and soft emotion. Results from these negative conflict
variables were contrasted with collaborative communication behavior and two types of
disengagement: withdrawal and passive immobility (the latter being a type of conflict
disengagement in which a person desires to address an issue but passively waits for a
partner to initiate engagement). To the extent that negative conflict variables might
produce direct effects, the effects were expected to be positive, to be strongest when
satisfaction was high, and to be the opposite of the effects for withdrawal and passive
immobility. To the extent that mediated effects might be present, it was expected that
negative conflict variables would predict high peak discord, that collaborative engage-
ment would have the opposite effect, that peak discord would positively predict reso-
lution progress, and that this effect would be the strongest when satisfaction was high.
Method
Participants
Participants included 734 people in heterosexual marriages or cohabitation relationships.
A total of 687 were married and the remaining 47 were cohabitating (because a majority
were married, the terms ‘‘wife’’ and ‘‘husband’’ will be used throughout). Age of
participants ranged from 18 to 82 years (M ¼ 40.20, SD ¼ 13.15); and of the
married participants, length of marriages ranged from less than 1 to 51 years (M¼ 13.36,
SD ¼ 12.38). The sample comprised 64% female, 11% Asian, 7% Black or African
American, 10% Hispanic, 69% White (non-Hispanic), and 3% other races. Annual
family income ranged from less than US$10,000 to more than US$500,000 (median
¼ US$78,000, M ¼ US$102,000, SD ¼ US$85,000).
The total sample was divided into two overlapping subsamples. First, a paired-data
subsample included 117 couples with two participating partners, with both partners com-
pleting an assessment pertaining to the same issue of relationship conflict. Second, an
independent-cases subsample had 617 participants. These included (a) 1 randomly
selected member from each of the 117 couples in the paired-data subsample, (b) 1 ran-
domly selected member from each of 28 couples where partners completed assessments
pertaining to different issues of conflict, and (c) 472 married or cohabitating individuals
participating without their partners.
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Procedure
An interactive Web site was created, which allowed participants to create an anonymous
account, complete an assessment, submit responses, receive personalized feedback, and
view a resource bank of information for couples. On the first page of the assessment,
participants were instructed to ‘‘Think about a single, specific episode of conflict in your
relationship,’’ and they were given a text box in which they were asked to write a brief
conflict description that would be acceptable to be viewed by their partners (if partici-
pating). When both members of a couple participated, the first partners’ incident
description was automatically displayed on the first page of the questionnaire for the
second partner, and the second partner was asked to indicate whether they had both
identified the same incident. When the incident was reported to be the same for both
partners, the couple was included in the first subsample of paired partners. No other parts
of the assessment were shared between partners, and partners were instructed to com-
plete their assessments independently.
After identifying an episode of conflict, participants then completed several ques-
tionnaire scales regarding that conflict. Participants were included in the data set only if
they completed the entire questionnaire and responded affirmatively to a question about
providing valid answers. A portion of the sample was recruited using procedures outlined
by Feeney (1999) in which students from upper level undergraduate psychology courses
invited their married parents, relatives, and acquaintances to complete the Web ques-
tionnaire. Drawing from student recruitment records, it is estimated that approximately
60% of the couples were recruited by students and that the remaining 40% simply dis-
covered the questionnaire while searching the Internet or via links from other Web sites.
Compared with other nonclinical samples of couples (e.g., Funk & Rogge, 2007), the
participants in the present study had a lower mean and a wider spread of relationship
satisfaction scores (Couples Satisfaction Inventory M ¼ 49.44, SD ¼ 21.54), and there
was a significant gender difference, d ¼ .32, t(615) ¼ 3.70, p < .001, with women
reporting lower satisfaction than men. There is a possibility that the recruitment methods
inadvertently oversampled distressed women compared with distressed men, and, thus,
any gender differences in this study should be interpreted with caution.
Measures
Conflict resolution. A new instrument called the conflict resolution questionnaire was
created for this study. This questionnaire asked participants to rate 10 pairs of items
pertaining to the specific episode of conflict they identified at the beginning of the
assessment protocol. The first item of each pair was used to assess peak discord, and each
of these items asked respondents to make a rating based on the conflict when it was at its
peak. The second item of each pair was used to assess current discord, and each of these
items asked participants to rate the same characteristic as the first item but to base the
rating on the conflict at the current moment in time. A list of items is provided in
Appendix 1. A confirmatory factor analysis of this questionnaire was conducted, and,
specifically, a model was tested with (a) six-item parcels, (b) two latent state factors, and
also (c) two indicator-specific factors accounting for variance shared by pairs of
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questions that were repeated in regard to two different time points (Geiser, 2013). This
model produced a good fit, w2(df ¼ 6) ¼ 41.64, comparative fit index (CFI) ¼ .99, stan-
dardized root mean square residual (SRMR)¼ .04; further details regarding this analysis
are available from the author. Cronbach’s as were .87 and .94 for peak discord and cur-
rent discord, respectively.
Communication behavior. The Conflict Communication Inventory (Sanford, 2010a) was
used to assess both adversarial (negative) communication and collaborative (positive)
communication during the specific episode of conflict that participants identified at the
beginning of the assessment protocol. The adversarial communication scale includes
seven items that ask participants to rate their use of negative communication (e.g.,
‘‘I said something mean’’ and ‘‘I defended my position’’). The collaborative commu-
nication scale includes seven items that ask participants to rate their use of positive
communication (e.g., ‘‘I politely talked about my feelings,’’ and ‘‘I carefully listened so
I could understand my partner’’). Previous research has found that scores on these scales
are highly correlated with observer ratings and, moreover, that the scores predict future
observed behavior nearly as well as do ratings that are obtained from trained observers
(Sanford, 2010a). In the present study, a was .85 for adversarial communication and
.86 for collaborative communication.
Negative attributions. Participants used a negative attribution scale (Sanford, 2010b) to
rate their appraisals during the episode of conflict that they identified at the beginning of
the assessment protocol. On this scale, participants rated the extent to which they agreed
with eight different attribution statements, such as ‘‘My partner deserves to be blamed’’
and ‘‘My partner did something on purpose that caused this problem.’’ Previous research
has found that scores on this scale correlate with observer ratings of verbalized attri-
butions (Sanford, 2010b) and, in the present sample, a was .89.
Emotion. Two scales from the Couples Emotion Rating Form (CERF; Sanford, 2007a)
were used to obtain ratings of negative emotion during the episode of conflict that
participants identified at the beginning of the assessment protocol. Anger was assessed
with a four-item ‘‘hard emotion’’ scale measuring feelings of anger, annoyance, irrita-
tion, and aggravation. Participants also completed a 4-item ‘‘soft emotion’’ scale measur-
ing feelings of sadness, hurt, concern, and disappointment. This instrument was
developed and validated in a series of studies (Sanford, 2007a, 2007b, 2012) demonstrat-
ing that (a) the CERF fits an expected factor structure, (b) scores on the CERF corre-
spond to observer ratings of expressed emotion, and (c) changes in emotion predict
corresponding changes in communication behavior and cognition. In the present study,
as were .85 for anger and .83 for soft emotion.
Conflict disengagement. A new instrument called the Conflict Disengagement Inventory
was created. This instrument contains two 7-item scales specifically pertaining to the
episode of conflict participants identified at the beginning of the assessment protocol.
One scale measures withdrawal and the other measures passive immobility. A list of
items is provided in Appendix 2. The instrument was developed through a series of four
8 Journal of Social and Personal Relationships
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studies (total n ¼ 3,715) conducted by this author (Sanford) in which pools of potential
items were factor analyzed, and items were selected and revised to produce an instru-
ment with two distinct factors. A subsequent validation study (n ¼ 297) comparing the
two scales found that the withdrawal scale had significantly stronger correlations with
other existing measures of withdrawal (measuring patterns of withdrawal rather than
withdrawal in a specific conflict interaction), avoidant attachment, and low relationship
commitment. In contrast, passive immobility had significantly stronger correlations with
having standards that a partner should be able to ‘‘mind read’’ one’s own desires and with
anxious attachment. In the present study, as were .85 for withdrawal and .88 for passive
immobility.
Relationship satisfaction. Participants completed the 16-item version of the Couples Satis-
faction Index (Funk & Rogge, 2007). This measure was developed using item response
theory analysis to select highly discriminating items from a pool of items drawn from
several existing measures. In the present study, a was .97.
Results
The first step in data analysis was to conduct a test of the convergent validity for the
ratings of peak discord and current discord. Using only the paired data set of 117 couples,
correlations were computed between wives and husbands. These cross-spouse correla-
tions were .60 (p < .001) for peak discord and .76 (p < .001) for current discord. Next,
partial correlations were computed after controlling for both wife relationship satisfac-
tion and husband relationship satisfaction. The partial correlations were .59 (p < .001)
for peak discord and .61 (p < .001) for current discord. Thus, the strong correlation
between partners in their ratings of conflict discord was more specific than merely shar-
ing perspectives that matched their overall relationship satisfaction. This provides initial
support for the convergent validity of the resolution scales.
The remaining analyses all used the nonpaired data set of 617 independent cases.
First, means, SDs, and correlations were computed for all the variables, and these are
listed in Table 1. Correlations between the various independent variables ranged from
being small and nonsignificant to large. Consistent with the fact that both conflict dis-
cord and relationship satisfaction tap aspects of relationship sentiment, the correlation
between relationship satisfaction and current discord was large. However, as reported
earlier, the correlation between partners in their ratings of current discord could not be
explained by their ratings of satisfaction, suggesting that discord scores are also distinct
from satisfaction. Notably, correlations between adversarial communication, anger, and
negative attributions were all .50 or greater. Along this line, a confirmatory factor
analysis demonstrated a good fit for a model in which these three variables were all
indicators of a single factor, and each of the other four variables were sole indicators of
separate factors, w2(df ¼ 8) ¼ 45.06, CFI ¼ .98, SRMR ¼ .03. Thus, to reduce the
number of equations tested in subsequent analyses, adversarial communication, anger,
and negative attributions were each standardized and then summed together to create a
composite variable called ‘‘negative process’’.
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Tab
le1.
Mea
ns,
SDs,
and
corr
elat
ions
bet
wee
nva
riab
les
usi
ng
617
indep
enden
tca
ses.
Satisf
action
Adve
rsar
ial
com
.N
egat
ive
attr
ibutions
Ange
rSo
ftem
otion
Colla
bora
tive
com
.W
ithdra
wal
Pas
sive
imm
obili
tyPea
kdis
cord
Curr
ent
dis
cord
Mea
n49.4
43.2
72.9
33.6
63.6
02.5
72.4
02.8
23.6
02.5
2SD
21.5
4.8
8.9
5.9
91.0
7.7
3.8
7.9
3.7
61.0
3A
dve
rsar
ialco
m.
�.2
6**
Att
ributions
�.5
0**
.53**
Ange
r�
.26**
.58**
.50**
Soft
emotion
�.4
0**
.44**
.50**
.42**
Colla
bora
tive
com
..1
7**
�.3
0**
�.3
0**
�.3
1**
.00
Withdra
wal
�.1
8**
�.0
9*
.09*
.02
.04
�.0
6Pas
sive
imm
obili
ty�
.18**
.28**
.34**
.23**
.34**
�.0
1.3
0**
Pea
kdis
cord
�.5
3**
.55**
.58**
.48**
.59**
�.3
7**
.10*
.21**
Curr
ent
dis
cord
�.8
1**
.34**
.51**
.28**
.45**
�.1
7**
.17**
�.2
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.58**
Not
e.Sa
tisf
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score
sra
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from
0to
81.Sc
ore
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alloth
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ales
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1to
5.co
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munic
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*p<
.05;**
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.01.
10
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Latent change score models
A series of five latent change score models were estimated, one for each of five conflict
process variables: negative process (which was a composite of adversarial communication,
anger, and negative attributions), soft emotion, collaborative engagement, withdrawal, and
passive immobility. These models were analyzed following procedures described by
McArdle (2001, 2009) using LISREL 8.80 software (Scientific Software International,
Lincolnwood, Illinois, USA; Joreskog & Sorbom, 2007). Figure 1 provides a depiction of
the basic model. This figure includes all components of the model except for variables
pertaining to gender, which were entered as covariates in all analysis but omitted from the
1 1
Satisfaction×
Conflict Process
Satisfaction×
PeakDiscord
SatisfactionConflictProcessVariable
Constant
CurrentDiscord
Change(PerceivedResolutionProgress)
Peak Discord
e e e e
e
C
A
B
eIndi-cator
Indi-cator
Indi-cator
Indi-cator
Indi-cator
Indi-cator
1
1
1 1 1 1
Figure 1. Latent change score model of conflict resolution. Each ‘‘e’’ indicates measurement errorvariance, which is fixed to equal an indicator’s variance times 1 minus its reliability. Each ‘‘1’’indicates a pathway fixed to equal one. Current discord is fixed to equal peak discord plus changewith no residual variance. Pathways A and B are the mediated effect pathways. Pathway C is thedirect effect pathway. To simplify presentation, covariates and interactions involving gender arenot depicted in the figure.
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figure to simplify the presentation. As seen in the figure, the model includes variables
representing peak discord and current discord and also an unobserved variable called
‘‘change.’’ Both peak discord and change have arrows pointing to current discord, and both
of these pathways are constrained to equal one. This means that current discord is equal to
the sum of peak discord plus change, and hence, change is a latent difference score equal to
current discord minus peak discord (if current¼ peakþ change, then change¼ current�peak). In other words, change is a measure of perceived resolution progress. The model
also includes a constant, depicted as a triangle and set equal to one for all participants,
which makes it possible to estimate intercepts. For example, the arrow from the
constant to change estimates the intercept for change, which is the average amount of
change after controlling for other predictors. In each model, peak discord was pre-
dicted by (a) one of the conflict process variables, (b) relationship satisfaction, and
(c) the interaction between the conflict process variable and relationship satisfaction.
Although not depicted in the figure, peak discord was also predicted by (d) gender,
(e) the interaction between gender and the conflict process variable, and (f) the
interaction between gender and relationship satisfaction. Change was predicted by
(a) peak discord (b) one of the conflict process variables, (c) relationship satisfaction,
(d) the interaction between the conflict process variable and relationship satisfaction,
and (e) the interaction between peak discord and relationship satisfaction. Although
not depicted in the figure, change was also predicted by (f) gender, (g) the interaction
between gender and peak discord, (h) the interaction between gender and the conflict
process variable, and (i) the interaction between gender and relationship satisfaction.
In Figure 1, the direct effect of the negative process variable on conflict resolution is
labeled as Path C, and the mediated effect is the product of the Paths labeled A and B.
As depicted in Figure 1, each latent variable has a single indicator (or observed
variable), and each indicator is constrained to have a unit loading on its target latent
variable. In line with McArdle (2001), the error variance for each indicator was set to
equal the observed variables’ variance times 1 minus its reliability. Prior to analysis,
and prior to calculating products for the interaction terms, scores for peak discord,
satisfaction, and the conflict process variable were all converted to z scores. Gender
was coded so that 0 ¼ wives and 1 ¼ husbands. Scores for current discord were
standardized using the mean and SD for peak discord. This means, for example, that a
change score of �1 indicates a decrease in conflict discord that is equal to a 1 SD drop
on the peak discord scale.
The substantive parameters of interest in the latent change score analysis pertain to
the predictors of peak discord and the predictors of change (i.e., perceived resolution
progress). The results regarding predictors of peak discord are listed in Table 2. Both
negative process and soft emotion strongly predicted higher peak discord, whereas
collaborative communication predicted lower peak discord. The two disengagement
variables had small effects, with withdrawal being nonsignificant. As might be expected,
the level of peak discord was inversely related to relationship satisfaction, and it was also
inversely related to being a husband (which is consistent with the gender difference in
this sample). Importantly, the effects for negative process, soft emotion, and colla-
borative communication were all moderated by relationship satisfaction. The direction of
these interactions indicated that the effects were stronger when satisfaction was high.
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The results regarding predictors of change are listed in Table 3. Note that change is
scored so that negative values indicate conflict resolution progress (i.e., a decrease in
discord), whereas positive values indicate conflict escalation. Because units of change
were scaled to the SD of peak discord, the change variable itself was not a z score, and,
therefore, path loadings near one do not indicate a near perfect correspondence. The
intercepts in Table 3 indicate that participants reported average reductions in conflict
discord that were approximately equal to 1.55 SDs on the peak discord scale. This is
consistent with the expectations that scores regarding conflict discord should have the
potential for changing substantially over the course of a single conflict. Importantly,
both peak discord and relationship satisfaction were strong predictors of greater per-
ceived resolution progress (predicting greater reductions in discord). In addition, peak
discord was moderated by satisfaction. The direction of the interaction indicated that
peak discord predicted the most resolution when satisfaction was high. In contrast to
the robust effects for peak discord, the direct effects for the conflict process variables
were generally small, and the only significant direct effects pertained to negative
process, soft emotion, and passive immobility. Each of these variables was associated
with reduced progress toward resolution. Thus, the results for passive immobility were
consistent with the idea that disengagement might hinder resolution, whereas the
results for negative process and soft emotion were opposite from expectations that
these variables might be adaptive and might facilitate resolution. Notably, there was an
interaction between soft emotion and satisfaction, suggesting that this direct effect for
soft emotion was weaker when satisfaction was high. Incidentally, there were also
some gender effects in that men reported slightly less progress toward resolution, and
in the equation testing effects of soft emotion, the interaction between gender and peak
discord fell in the significant range.
Table 2. Coefficients for pathways predicting peak discord.
Equation parameters
Name of conflict process variable used in the model
Negativeprocess
Softemotion
Collaborativecommunication Withdrawal
Passiveimmobility
Intercept .11 .11 .12 .15 .13Conflict process variable (Path A) .49* .50* �.34* .02 .11*Relationship satisfaction
Main effect �.41* �.40* �.51* �.54* �.53*Interaction with conflict
process.13* .09* �.14* .07 .05
GenderMain effect �.22* �.27* �.33* �.43* �.38*Interaction with conflict
process.10 �.04 .08 .09 .00
Satisfaction by gender interaction .32* .12 .13 .07 .09
Note. Each column contains parameter estimates obtained from a single model and all parameters pertain topathways predicting peak discord.*p < .05.
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To assist in interpreting the significant interactions in Tables 2 and 3, conditional
effects were computed for all variables. Specifically, mediated effects, direct effects, and
total effects were calculated for both: (a) people 1 SD above the mean on relationship
satisfaction and (b) people 1 SD below the mean. Because there was a significant gender
interaction in one of the equations pertaining to soft emotion (Path B), results for this
particular variable were calculated separately for wives and husbands. All conditional
effects are reported in Table 4. The results indicate that the mediated effects are both
robust and strongly moderated by satisfaction. Compared to people with low satisfaction,
the results for highly satisfied people show that negative process and soft emotion both
predicted comparatively greater increases in peak discord, but this was offset by the fact
that peak discord predicted comparatively greater levels of resolution progress. Taken
together, these mediated effects were substantial for people with high satisfaction (e.g.,
negative process-mediated effect was �.56), but small for people with low satisfaction
(e.g., negative process-mediated effect was �.22). The total effects listed at the bottom
of Table 4 show that these mediated effects were reduced, albeit only slightly, by small
direct effects in the opposite direction. Notably, the results for collaborative communi-
cation were mostly a mirror image of the results for negative process, suggesting that
these variables have opposite functions. In contrast, the two disengagement variables had
Table 3. Coefficients for pathways predicting change (perceived resolution progress).
Name of conflict process variable used in the model
Equation parametersNegativeprocess
Softemotion
Collaborativecommunication Withdrawal
Passiveimmobility
Intercept �1.55* �1.56* �1.55* �1.54* �1.55*Peak dissonance (Path B) �.74* �.76* �.66* �.68* �.69*Direct effects of conflict
process (Path C).09* .13* .03 .02 .08*
Relationship satisfactionMain effect �.98* �.97* �.97* �.97* �.97*Interaction with peak
dissonance�.14* �.09* �.12* �.13* �.12*
Interaction with conflictprocess
.01 �.07* .02 .02 �.05
GenderMain effect .14* .13* .13* .11 .14*Interaction with peak
dissonance.09 .13* .08 .06 .07
Interaction with conflictprocess
�.03 �.09 .01 .12 .02
Satisfaction by genderinteraction
.13 .10 .11 .13 .13
Note. Each column contains parameter estimates obtained from a single model and all parameters pertain topathways predicting perceived resolution progress. Negative values indicate greater perceived resolutionprogress (i.e., greater reductions in discord).*p < .05.
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small effects that were, if anything, in the same direction as negative process rather than
opposite.
Discussion
Perceived conflict resolution progress in couples is a process that involves moving from
a point of high discord on a conflict to a new point of low discord. The present study
demonstrated how this process can be examined using latent change score models, and it
investigated the extent to which perceived resolution progress was associated with a set
of three negative process variables (including adversarial communication, blaming
attributions, and anger) and also a measure of soft emotion. The results were consistent
with a mediated pathway in which negative process variables predicted greater peak
discord during conflicts and where greater peak discord in turn predicted greater reso-
lution progress. In other words, large conflicts were offset by large resolutions.
Importantly, this mediated pathway was strong for people with high relationship satis-
faction, but weak for people with low satisfaction. These results help answer a key
question. Are negative process variables sometimes beneficial for resolution progress?
Results of the present study suggest that negative process variables do, indeed, predict
positive change. However, the reason is not because these variables directly serve a
beneficial function, but rather, because when people are in satisfying relationships,
Table 4. Conditional effects of conflict process variables predicting change (perceived resolutionprogress) at levels of relationship satisfaction.
Name of conflict process variable
Negativeprocess
Soft emotion
Collaborativecommunication Withdrawal
Passiveimmobility
Name of conditionaleffect pathway Wives Husbands
Path A: Conflict process predicting peak discordSatisfaction Z ¼ þ1 .65 .59 .55 �.45 .12 .16Satisfaction Z ¼ �1 .39 .41 .37 �.17 �.02 .06
Path B: Peak discord predicting changeSatisfaction Z ¼ þ1 �.85 �.85 �.72 �.75 �.79 �.79Satisfaction Z ¼ �1 �.57 �.67 �.54 .51 �.53 �.55
Path C: Direct effects of conflict processSatisfaction Z ¼ þ1 .09 .06 �.03 .05 .08 .04Satisfaction Z ¼ �1 .07 .20 .11 .01 .04 .14
Path AB: Mediated effects of conflict processSatisfaction Z ¼ þ1 �.56 �.50 �.40 .34 �.09 �.13Satisfaction Z ¼ �1 �.22 �.27 �.20 .09 .01 �.03
Total effects of conflict process (AB þ C)Satisfaction Z ¼ þ1 �.47 �.44 �.43 .40 �.01 �.09Satisfaction Z ¼ �1 �.15 �.07 �.09 .10 .05 .10
Note. Negative values indicate greater perceived resolution progress (i.e., greater reductions in discord).
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perturbations away from a norm are followed by a return to the status quo. After con-
trolling for this robust effect, the remaining direct effect of negative process variables on
resolution progress was quite small in magnitude and in the direction of predicting
decreased, not increased, resolution.
The results help clarify the extent to which negative process variables function pri-
marily as types of adversarial interaction versus types of conflict engagement. If these
variables are adversarial in nature, they should function as the opposite of collaborative
engagement. They should violate what Honeycutt and Bryan (2011) call ‘‘rules for
positive understanding,’’ and they should be associated with conflict escalation
(Markman et al., 2001). In line with this assumption, the present study not only found
that negative process variables were correlated with higher peak discord but also that
these variables had the opposite effect from collaborative engagement, which predicted
reduced levels of peak discord. A contrasting (albeit not incompatible) theoretical per-
spective is that negative process variables are best conceptualized as types of conflict
engagement and that resolution will be facilitated by engagement and hindered by dis-
engagement (Gottman & Krokoff, 1989; Karney & Bradbury, 1997; McNulty, 2010).
The results of the present study were mixed regarding the overall salience of variables
pertaining to disengagement. One type of disengagement called ‘‘passive immobility’’
had a small but significant direct effect predicting lower perceived resolution progress,
but the direct effects for another type of disengagement, called ‘‘withdrawal,’’ were not
significant. Importantly, results regarding the two disengagement variables were, if
anything, similar in direction (rather than opposite in direction) from the effects for the
negative process variables. Thus, the pattern of results provided the strongest support for
conceptualizing negative process variables as being primarily adversarial in function.
In the present study, peak discord predicted the extent of perceived resolution
progress. These results followed a general pattern in which a pre-change condition of
having problems (high peak discord) predicted making subsequent improvements (per-
ceived resolution progress), and, thus, the variables that predicted having problems were
also variables that predicted making improvements. A similar pattern of results is evident
in longitudinal research on relationship satisfaction. For example, some previous studies
have found that forms of negative communication are associated with having initially
low levels of satisfaction and also with experiencing future improvements (Gottman
& Krokoff, 1989; Heavey et al., 1993). This type of pattern is also found in growth curve
modeling studies where the rate of improvement is assessed across multiple time points.
These studies have found that, when newly married couples report experiencing marital
problems, they tend to have low immediate relationship satisfaction but also a trajectory
of improvement over time; and moreover, when these couples with problems use nega-
tive communication and make negative attributions, it again predicts low immediate
satisfaction, but a trajectory of improvement (McNulty et al., 2008; McNulty & Russell,
2010). Similarly, Karney and Bradbury (1997) found that wives’ negative behavior was
inversely related to pre-change satisfaction levels (albeit with most effects falling short
of significance in this study), but it had a beneficial effect on that rate of change over
time. A mirror image of this effect was also observed in a study of couples attending
a premarriage education program where high satisfaction scores at the beginning of the
program predicted subsequent declines in satisfaction (Baucom et al., 2006). In sum,
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several longitudinal studies of satisfaction in couples have produced a pattern of findings
that is consistent with a possibility that pre-change levels of satisfaction predict the sub-
sequent direction and rate of change. The findings from these studies are strikingly sim-
ilar to the total effects in the present study, in which the negative conflict variables were
associated with greater perceived improvement. Importantly, the present study also con-
trolled for the extent to which pre-change problems (peak discord) predicted subsequent
improvement (perceived resolution progress), and the results indicated that the negative
conflict variables were not directly beneficial, but instead they predicted improvement
merely because they predicted the extent of pre-change problems. This raises questions
about whether this same type of effect might also explain results in longitudinal studies
of relationship satisfaction.
Perhaps the most striking results in the present study were the extent to which the
mediated effects were moderated by relationship satisfaction. A purview of the condi-
tional effects listed in Table 4 reveals that the total mediated effects were, on average,
more than twice as large for satisfied people than for unsatisfied people. These results are
consistent with theories suggesting that conflict can be an absorbing state for distressed
couples (Gottman, 1994). Not only were the mediation effects moderated by satisfaction,
but satisfaction also strongly predicted both peak discord and conflict resolution. This
pattern suggests that, for distressed couples, conflicts might often escalate to high levels
of peak discord regardless of the presence or absence of negative process variables and
that large conflicts often fail to produce large resolutions. In contrast, for satisfied
couples, the level of escalation may be commensurate with the level of negative process
and the size of the conflict may determine the size of the resolution. If this is true, then it
would seem that conflict resolution is more dependent on levels of relationship satis-
faction than on other aspects of conflict process.
This does not mean, however, that negative process variables are entirely inert. After
controlling for the large effects produced by peak discord and relationship satisfaction,
there was still a small direct effect indicating that negative process during conflict
predicted reduced progress toward resolution. In addition, the soft emotion variable had a
similar direct effect predicting reduced progress toward resolution; however, this effect
applied primarily to people with low relationship satisfaction and not people with high
satisfaction. Importantly, the direction of these direct effects was opposite from the
direction of the mediated effects. When the direct effects were isolated, the negative
process variables (including soft emotion for people in unsatisfying relationships)
appeared to be more harmful than beneficial for perceived resolution progress. In this
respect, the findings of this study are consistent with those longitudinal studies that have
shown that negative process variables predict future relationship distress (e.g., Karney &
Bradbury,1995; Lavner & Bradbury, 2012; Markman et al., 2010).
There were several gender differences in the results, with women reporting less
satisfaction, greater peak dissonance, and greater perceived resolution progress. How-
ever, it is not clear if this indicates a genuine difference between women and men or if
the recruitment techniques in this study inadvertently oversampled distressed women
relative to distressed men. It is possible that men in distressed relationships are disin-
clined to complete relationship questionnaires on the Internet. Other limitations of the
present study include the fact that all variables were assessed via self-report, and data
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were collected over the Internet without control over the assessment environment. In
addition, ratings for peak discord were collected retrospectively (in part, because it did
not seem feasible to collect assessments of peak discord at the actual moments when con-
flicts were reaching their peaks), and there is some risk that participants may have failed
to remember their previous conflict experiences accurately. Also, because this study was
correlational, it could not address issues regarding direction of effects. For example, are
couples able to resolve big conflicts because they are satisfied? Or conversely, does the
process of having big conflicts and then resolving those big conflicts produce relation-
ship satisfaction?
Notwithstanding the limitations discussed above, the results of this study are valuable
for two key reasons. First, they provide preliminary evidence for a model of conflict
resolution in couples. According to this model, the primary function of negative process
variables is that they predict peak levels of conflict discord, but at least for people in
satisfying relationships, this effect is benign because large conflicts predict large reso-
lutions. Negative process variables may also have a direct effect predicting reduced
resolution progress, although this appears to be small in magnitude. Second, the results
demonstrate how latent change score models might be especially useful for research with
couples, and it highlights the importance of distinguishing between direct and mediated
effects. In the present study, scores from a pre-change point in time (peak discord)
strongly predicted the extent of subsequent change (perceived conflict resolution). These
results suggest that it is crucial for researchers to model this pathway when investigating
aspects of change in relationships.
Appendix 1
List of items for the conflict resolution questionnaire
(1) Think about the point during this particular conflict when you felt the most upset.
How upset did you feel at that point? (2) How upset do you feel right now? (3) Think
about the point during this particular conflict when it was the hardest to understand your
partner. How well did you understand your partner at that point? (4) How well do you
understand your partner right now? (5) Think about the point during this particular con-
flict when your partner showed the worst understanding of you. How well did your part-
ner understand you at that point? (6) How well does your partner understand you right
now? (7) Think about the point during this particular conflict when there was the most
tension between you and your partner. How much tension was there at that point? (8)
How much tension is there between you and your partner right now? (9) Think about the
point during this particular conflict when there was the most disagreement between you
and your partner. How much did you and your partner disagree with each other at that
point? (10) How much do you and your partner disagree with each other right now?
(11) Think about the point during this particular conflict when it was the furthest away
from being resolved. How much was there to be resolved at that point? (12) How much is
there that still needs to be resolved right now? (13) Think about the point during this par-
ticular conflict when you felt as if there was the most distance between you and your
partner. How distant did you feel from your partner at that point? (14) How distant do
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you feel from your partner right now? (15) Think about the point during this particular
conflict when it was most difficult to be accepting of your partner. How accepting did
you feel at that point? (16) How accepting do you feel right now? (17) Think about the
point during this particular conflict when you were the most worried about your relation-
ship. How worried did you feel at that point? (18) How worried are you right now?
(19) Think about the point during this particular conflict when it was most difficult to
feel friendly toward your partner. How friendly did you feel at that point? (20) How
friendly do you feel toward your partner right now?
Note. Each item is rated on a 5-point scale: 1¼ Not at all (Zero), 2¼ A small amount,
3 ¼ A medium amount, 4 ¼ A large amount, and 5 ¼ An extreme amount (Completely).
Appendix 2
List of items for the Conflict Disengagement Inventory
(1) I avoided discussing the conflict. (2) I wanted my partner to be faster at recognizing
when I am upset. (3) I silently refused to say anything. (4) I decided to remain silent until
my partner stopped nagging. (5) I quietly waited, hoping my partner would notice I was
upset. (6) I wanted my partner to drop the issue. (7) I decided it was useless to reply to my
partner. (8) I wanted my partner to notice my feelings without me having to say anything.
(9) I withdrew from my partner. (10) I wanted my partner to take responsibility for find-
ing out how I felt. (11) I wanted my partner to figure something out without me having to
say it. (12) I chose not to respond to my partner. (13) I silently wished my partner would
ask about my feelings. (14) I wanted my partner to notice something was wrong without
me having to point it out.
Note. The Withdrawal Scale includes items 1, 3, 4, 6, 7, 9, and 12. The Passive Immo-
bility Scale includes items 2, 5, 8, 10, 11, 13, and 14. Each item is rated on a 5-point
scale: 1 ¼ Disagree strongly, 2 ¼ Disagree, 3 ¼ Agree somewhat, 4 ¼ Agree, and
5 ¼ Agree Strongly.
Funding
This study was supported in part by a grant from the Baylor University Research Committee.
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