Psikohumaniora: Jurnal Penelitian Psikologi, Vol 6, No 1 (2021): 13–32
DOI: https://doi.org/10.21580/pjpp.v6i1.6520
Copyright © 2021 Psikohumaniora: Jurnal Penelitian Psikologi

Couple resilience predicted marital satisfaction but not
well-being and health for married couples in Bali, Indonesia
Edwin Adrianta Surijah,1 ∗ Gaura Hari Prasad,2 Made Rinda Ayu Saraswati2
1

Faculty of Health, School of Psychology and Counselling, Queensland University of Technology (QUT), Brisbane,
QLD – Australia; 2 School of Psychology, Universitas Dhyana Pura, Badung, Bali – Indonesia
Abstract: Married couples face various challenges in their married life, with divorce
being one of the threats to their relationship. Spouse resilience is the process by
which couples manage marital challenges through positive relationship behavior.
This study examines the resilience of partners by including negative behavior in the
relationships and examines the effects of interactions between partners. Three
hundred couples living in Bali, Indonesia (length of marriage of between 1-10 years)
participated by reporting positive and negative behaviors, and the outcomes of their
relationship (marital satisfaction, emotional well-being, and general health status).
The measurement instruments employed were the Couple Resilience Inventory,
Satisfaction with Married Life Scale, and the 36-item Short-Form Health Survey.
Model fit analysis showed that behavior in relationships did not predict the outcomes
referred to above, and that there was no interaction effect between partners.
However, positive behavior showed a higher probability of predicting marital
satisfaction, especially for wives (β = .271; β = .403; p < .001). The implications of
these findings provide practical suggestions for future partner resilience research to
apply a longitudinal approach that repeatedly measures the outcomes of resilience.
Keywords: couple resilience; marriage; resilience
Abstrak: Pasangan yang telah menikah menemui berbagai tantangan dalam
kehidupan pernikahan, dan perceraian menjadi salah satu ancaman jalan akhir suatu
relasi. Resiliensi pasangan adalah proses pasangan mengelola tantangan pernikahan
melalui perilaku positif dalam relasi (positive relationship behavior). Studi ini meneliti
resiliensi pasangan dengan menyertakan perilaku negatif dalam relasi serta melakukan kajian terhadap efek interaksi di antara pasangan. Tiga ratus pasangan yang
tinggal di Bali, Indonesia (usia pernikahan antara 1-10 tahun) menjadi partisipan
dengan melaporkan perilaku positif dan negatif, dan luaran dari relasi pasangan
(kepuasan pernikahan, kesejahteraan emosi, dan status kesehatan secara umum).
Alat ukur dalam penelitian ini adalah Couple Resilience Inventory, Satisfaction with
Married Life Scale, dan 36-item Short-Form Health Survey. Analisis kesesuaian model
menunjukkan bahwa perilaku dalam relasi tidak memprediksi luaran tersebut, dan
tidak ada efek interaksi antar pasangan. Akan tetapi, perilaku positif menunjukkan
tingkat probabilitas yang lebih tinggi dalam memprediksikan kepuasan pernikahan
khususnya pada istri (β = 0,271; β = 0,403; p < 0,001). Implikasi temuan ini adalah
saran praktis bagi penelitian resiliensi pasangan di masa mendatang untuk
menerapkan pendekatan longitudinal yang mengukur luaran dari resiliensi secara
berulang.
Kata Kunci: pernikahan; resiliensi; resiliensi pasangan

__________
Corresponding Author: Edwin Adrianta Surijah (edwin@adrianta.com), Faculty of Health, School of Psychology and Counselling,
Queensland University of Technology (QUT), Brisbane, QLD 4000 – Australia.

∗

ISSN 2502-9363 (print); ISSN 2527-7456 (online)
http://journal.walisongo.ac.id/index.php/Psikohumaniora/
Submitted: 1-10-2020; Received in revised form: 6-3-2021; Accepted: 21-3-2021; Published: 30-5-2021

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E. A. Surijah, G. H. Prasad, M. R. A. Saraswati

Introduction

In the field of relationships, couple resilience is

One of the endpoints of a failed marriage is
marital dissolution. In the United States, the
percentage of currently separated/divorced
women has increased over the years and reached
21% in 2018 (Schweizer, 2020). In Indonesia,
there were 408,202 divorce cases in 2018 alone,
with 44.85% of the cases due to ongoing disputes
among couples (Jayani, 2020). Unfortunately,
there is a lack of data availability regarding the
marital situation and divorce rate in Indonesia.
For example, Badan Pusat Statistik (BPS-Statistics
Indonesia) does not have data on the marriage
and divorce rates in the Bali region. However,
local news indicates that there is a growing trend
in the divorce rate in the region, primarily due to
the COVID-19 pandemic (Mustofa, 2020). In
Buleleng district in Bali, there were around 50 to
80 divorce cases each month during the COVID19 pandemic (Mustofa, 2020). This situation is of
concern and studies in the field of the family and
marriage are much needed.
Recent evidence suggests that soft reasons
are the main driving factors of divorce. Nonabusive (e.g., physical attacks) and non-adultery
(e.g., extramarital affairs) reasons, such as
‘growing apart’ and ‘not able to talk together’ are
becoming the common reasons for divorce
(Hawkins et al., 2012). While abuse or adultery
are not associated with the intention to reconcile,
these soft reasons are negatively associated with
the interest to resolve the marriage (Hawkins et
al., 2012). This interest is an open opportunity in
family and marriage studies to help couples deal
with adversities in their marriage; resilience may
hold the key for couples to deal with their
challenges.

14 │

a recently developed concept in understanding
how couples adapt to adversities. It is a process
whereby a couple initiates relationship behaviors
which will help them to adapt and maintain
wellbeing in adverse life situations (Sanford, et al.,
2016). Similarly, another study described relational
resilience as couples’ ability to recover after
encountering adverse life events (Aydogan &
Kizildag, 2017). In the face of adversity, couples will
engage in a particular behavior as a response to the
stressor (adversity). Sanford et al. (2016) explains
that couple resilience consists of two components:
positive and negative resilience. Positive resilience
represents the couple’s positive behavior when
they experience adversity, such as helping each
other to remain calm or to maintain a positive
attitude (Sanford et al., 2016). In contrast, negative
resilience is related to their negative behaviors in
the face of adversity, such as withdrawing from
communication and becoming hostile (Sanford et
al., 2016). During or after adverse life events,
couples may engage in positive or negative
behaviors as their response to the stressor.
The global definition of resilience underlines
the capacity of a system to adapt successfully to
adverse life events that threaten the function of
the system (Masten, 2014). Marriage or the
relationship between couples is a system, and
resilience helps them to thrive in the face of
adversity. This proposition is different to other
concepts, such as coping strategy. Coping
strategies can be divided into categories, such as
positive, emotional, evasive, and negative (PeláezBallestas, et al., 2015; Rafnsson et al., 2006).
Negative coping strategies are associated with
depressive symptoms and poorer emotional
regulations (Heffer & Willoughby, 2017).

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Couple resilience predicted marital satisfaction but not well-being and health ….

Contrary to coping strategy, resilience leads to
positive adaptation or outcomes. We believe that
couple resilience would be a useful concept for
couples to deal with adversities. This study aims
to examine the idea of positive and negative
resilience within the concept of couple resilience.
In addition to the concept of couple resilience,
a previous study developed a measurement tool
to estimate couple resilience. The Couple
Resilience Inventory (CRI) is an eighteen-item
self-administered survey that measures couples’
positive and negative resilience (Sanford et al.,
2016). A more detailed description of the
inventory is given in the Methods section.
Resilience studies have underlined that there are
two diverging approaches to understanding
resilience. The first approach views resilience as a
trait or something possessed by an individual
(Britt, et al., 2016), while the second approach
sees resilience as a dynamic process of how a
system deals with adversity (Becker & Ferry,
2016). Viewing resilience as trait has helped
researchers to develop inventories, such as the
Connor Davidson Resilience Scale (Connor &
Davidson, 2003). Resilience as a trait also allows
researchers to measure the characteristics of
resilient individuals; in addition, resilience as a
process helps observe the trajectory of healthy
functioning over time (Bonanno et al., 2011).
Sanford et al. (2016) defined couple resilience as a
process of couples engaging in relationship
behaviors and constructed a Couple Resilience
Inventory (CRI). This study examines the concept
of couple resilience, and also investigates the
association between the CRI and couple’s healthy
functioning or positive outcomes.
The key components of resilience are risks
(adversities) and positive adaptation (positive
outcomes). As such, resilience can be understood

as a positive adaptation despite adversity
(Fleming & Ledogar, 2008). A previous study
highlighted that the positive outcome of couple
resilience is wellbeing or quality of life (Sanford et
al., 2016). On the other hand, the outcome of
similar concepts (e.g., dyadic coping) is
relationship quality (Bodenmann et al., 2006).
This study aims to examine couple resilience, with
the inclusion of diverse domains of positive or
multiple outcomes (Luthar, Cicchetti, & Becker,
2000) being essential to the research. Marital
satisfaction or relationship quality are
indispensable outcome indicators in the field of
couples’ relationships and is closely related to
wellbeing (Schmitt, Kliegel, & Shapiro, 2007). In
addition to wellbeing, resilience is also closely
associated with health status (Bottolfs, et al.,
2020; Zautra et al., 2010). This study focuses on
the three indicators of marital satisfaction,
wellbeing, and health status.
Figure 1 shows the hypothesized working
model of the study. We reviewed previous studies
that have investigated the association between
various relationship-related variables (e.g., dyadic
coping), resilience, and outcomes. Studies have
found that resilience was positively correlated (r
= .52) with relationship satisfaction (Bradley &
Hojjat, 2017), and that dyadic coping was
positively correlated (r = .68) with relationship
satisfaction (Breitenstein et al., 2018). A previous
study on couple resilience (Sanford et al., 2016)
also found relationships between positive
resilience and marital satisfaction (r = .35), and
negative resilience and marital satisfaction (r = .24). In addition, relationship status has been
shown to be positively correlated (r = .23) with
happiness (Lucas & Dyrenforth, 2006). It has also
been found that couples’ positive resilience was
positively correlated (r = .13) with wellbeing, and

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E. A. Surijah, G. H. Prasad, M. R. A. Saraswati

Figure 1
Working model of the study illustrating couple resilience as a set of
positive and negative behaviors

that negative resilience was negatively correlated
(r = -.10) with wellbeing (Sanford, BackerFulghum, & Carson, 2016). In a study investigating
the relationship between marital satisfaction and
various health indicators,

the

correlations

between the variables ranged between .15 and .26
(Rostami et al., 2013). Based on this information,
this study expects: 1) an effect size r > .50 for the
association between positive behaviors and
marital satisfaction; 2) that negative behaviors and
marital satisfaction will a have similar level of
effect in the opposite direction (r > -.50); and 3)
that positive and negative behaviors will have less
effect on their relationship with wellbeing and
health status.
The study highlights the potential role of
couple resilience in helping couples to manage
adversities in their lives. We observed a
theoretical gap between couple resilience and the
general view of resilience as a process. Resilience

16 │

is also tied to positive adaptation, while couple
resilience and the Couple Resilience Inventory
introduced a dimension called ‘negative
resilience.’ To conform with the idea that
resilience is a positive adaptation despite
adversity (Fleming & Ledogar, 2008), we
operationalized positive and negative resilience
as positive and negative relationship behaviors.
The theoretical gap allowed this to become an
exploratory study. An overarching research
question or hypothesis in this study is that the
positive and negative behaviors of couple
resilience predict marital satisfaction, wellbeing,
and health status, with consideration of the
participants’ age, marital duration, and number of
children. This broad hypothesis examines the
working model and determines which variables
are significant for the model. This step helped the
researchers to narrow down the effective
variables for the following hypothesis testing. The
first set of hypotheses is:

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Couple resilience predicted marital satisfaction but not well-being and health ….

1. The model fit shows that positive and
negative behaviors are associated with
marital satisfaction, wellbeing, and health,
considering the participants’ age, marital
duration, and number of children.
2. Positive behaviors predict marital satisfaction
with an effect size of r > .50, and predict
wellbeing and health status with an effect size
of r > .25.
3. Negative behaviors predict the outcome with
a similar effect size but in the opposite or
negative direction.
One previous study did not work with
couples (dyads) as participants and instead used a
Mechanical Turk sample (Sanford, BackerFulghum, & Carson, 2016). This study addresses
this gap by using married couples in Bali as
participants. It explores the dyadic nature of
couple resilience toward the outcomes given the
control variables and the interdependent
relationship between the husband and wife. In
this step, we only select the significant variables
based on the previous hypothesis testing.
Another study investigated the relationship
between marital adjustment, conflict resolution
styles, and marital satisfaction (Ünal & Akgün,
2020). Husbands’ marital adjustment predicted
their own marital satisfaction (β = .79) and that of
their wives predicted theirs (β = .83). However,
only wives’ marital satisfaction experienced an
indirect effect from their partners perceived
problem-solving style; the average effect sizes
explaining the marital satisfaction was R2 > .60
(Ünal & Akgün, 2020). Another study (Conradi, et
al., 2017) found that husbands’ avoidance
attachment could predict their own marital
satisfaction (β = -.66, p = -.62), but that of their
wives did not have an effect on their husbands’

satisfaction (β = .09, p = .63). On the contrary,
wives’ avoidance attachment (β = -.35, p = -.67)
and that of their partners (β = -.37, p = -.32)
predicted wives’ own marital satisfaction
(Conradi, et al., 2017). Although we have
attempted to find previous studies to help
estimate our hypotheses, we could not
confidently predict the effect size due to the
differing evidence in these. Therefore, we loosely
articulated the second set of hypotheses as
follows:
1. The husband’s/wife’s couple resilience
predicts their own marital satisfaction with
an effect size of r > .30.
2. The actor’s effect toward the actor’s wellbeing
and health have a smaller effect size of .20 < r
< .30.
3. There is a partner’s effect on the relationship
between the partner’s couple resilience and
the husband’s/wife’s outcome variables.
4. The partner’s effects have a smaller effect size
than the actor’s effects.

Methods
Procedure & Participants
The participants in this study were married
couples. The inclusion criteria were that they
were couples living with their spouse, with or
without children, currently residing in Bali, and
having been married for one to ten years. The
study consisted of scales translation, a pilot trial,
and the main data collection. The Couple
Resilience Inventory (CRI) was translated by a
professional translator and by a researcher fluent
in English and Bahasa Indonesia. Both versions of
the translation were compiled into a single file. A
committee consisting of a psychologist, a lecturer
in psychology, and a psychology researcher made

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E. A. Surijah, G. H. Prasad, M. R. A. Saraswati

comments on the translated scale. We finalized
the translation by accommodating all the input
from the committee. A pilot trial was conducted to
calculate the CRI reliability and to obtain feedback
on the participants’ comprehension of the CRI and
health outcome measures. Fifty couples
participated in the pilot trial, with similar
inclusion criteria. The trial also informed us that
those who had been married longer were more
reluctant to join the study. This finding was the
reason why we limited marital duration to ten
years as one of the inclusion criteria.
The main study data collection involved 300
couples, as we had set quota sampling for the
participants. The survey questionnaire was
printed and contained the informed consent,
information sheet, and all of the proposed
inventories. In the overall the collection, three
couples gave incomplete data. These were
dropped and we looked for substitutes to maintain
the 300 participant couples. The study went
through a faculty examination to ensure the study
design adhered to the Pedoman Nasional Etik
Penelitian Kesehatan 2011 National Statement.
Instrument
Couple resilience was measured by the
Couple Resilience Inventory (Sanford et al., 2016).
In this inventory, it comprised positive and
negative resilience scales. Each aspect had nine
items; for example, for positive behavior ‘you and
your partner work together like a team,’ and for
negative behavior ‘either you or your partner
denied, ignored, or downplayed the seriousness of a
problem.’ Participants were asked to recall
positive and negative behavior examples with the
question ‘Are you able to think of a specific example
of this behavior occurring in your relationship?’ For
positive behavior, participants were given

18 │

memory prompts to recall stressful events in
order to avoid the ceiling effect on the positive
resilience scale. The negative resilience scale did
not include memory prompts. Participants were
then given a 6-point rating scale: 1 = No, this
behavior did NOT happen; 2 = No, although this
behavior might have happened, I could not think of
an example; 3 = No, although this behavior
certainly happened, I could not think of an example;
4 = Yes, I was able to think of a specific example; 5 =
Yes, I was able to think of a specific example, and I
can easily think of one or two more; and 6 = Yes, I
was able to think of a specific example, and I can
easily think of several more. The scale was reliable,
with α = .89 for positive resilience, and α = .93 for
negative resilience (Sanford et al., 2016).
At the top of the questionnaire, we asked the
participants to 1) think about their marital
relationship and the problems they have faced as
a couple; 2) recall how they behaved during
difficult times and how the problems affected
their relationship; and 3) rate their specific
example of behavior occurring in their relationship. Following the translation process, we
conducted a pilot trial to examine the scale
reliability and to obtaining participants’ feedback
on it. The pilot trial suggested that positive
behavior (α = .895) and negative behavior (α =
.828) were reliable. Cronbach’s α was above .70,
so also considered to be reliable.
After the data collection for the main study,
we conducted another reliability and internal
consistency analysis. In this case, positive
behaviors (α = .925) and negative behaviors (α =
.869) of the CRI were also reliable. The
confirmatory factor analysis (CFA) indicated that
the CRI was not orthogonal. The cutoff scores for
the indices were RMSEA close to .06, and CFI and
TLI close to .95 (Hu & Bentler, 1999). The Chi-

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Couple resilience predicted marital satisfaction but not well-being and health ….

square test result was χ2 = 1489.520; df = 134;
and p = .000, with the other indices RMSEA = .130;
CFI = .808; and TLI = .781. These results did not
support the two-factor structure of the construct.
We conducted a separate CFA for each aspect of
the scale. For positive behaviors, the Chi-square
test result was χ2 = 10.787; df = 4; and p = .029,
while for other indices RMSEA = .053; CFI = .998;
and TLI = .984. The negative behaviors Chisquared test result was χ2 = 29.227; df = 9; and p
= .001, and for the other indices RMSEA = .061;
CFI = .993; and TLI = .971. We concluded that in
this study, the CRI was composed of two
independent sets of positive and negative
relationship behaviors.
Marital satisfaction was measured with the
Satisfaction with Married Life Scale (SWML),
which is a modification of the Satisfaction with
Life Scale (Diener, Emmons, Larsen, & Griffin,
1985). SWML has five items, with each item
scored on a 7-point Likert scale from 1 (Strongly
Disagree) to 7 (Strongly Agree). An item example
is ‘I am satisfied with my married life.’ A previous
study showed that the scale was reliable with α =
.92 (Johnson, Zabriskie, & Hill, 2006). The scale
was previously translated, and the Bahasa
Indonesia version was reliable with α = .82
(Surijah & Prakasa, 2020). In this particular study,
we retested the reliability and factor structure of
the scale. Satisfaction with married life was
reliable (α = .870). The CFA also indicated the
unidimensionality of the scale, with Chi-squared
test result being χ2 = 22.440; df = 5; and p = .000.
The other indices were RMSEA = .076; CFI = .989;
and TLI = .978.
A full mental health framework comprised of
emotional wellbeing, social wellbeing, and
psychological wellbeing (Keyes, 2002). The
emotional aspect, such as positive affect, has often

been used to estimate individuals’ wellbeing
(Salsman et al., 2013; Medvedev & Landhuis,
2018). A previous study utilized a multidimensional health questionnaire to measure wellbeing
(Nath & Pradhan, 2012), while this study used the
36-item Short-Form Health Survey (SF-36) to
measure perceived health status and emotional
wellbeing (Ware & Sherbourne, 1992). SF-36
includes several aspects, such as physical
functioning, role limitations, pain, and health
change. In this study, we utilized the five items of
the Emotional Wellbeing (EWB) aspect to
measure emotional wellbeing, and the five
General Health (GH) items to measure participants’ perceived health condition. An example of
an EWB item was ‘Have you been a happy person?’
and the participants had to respond from 1 (all of
the time) to 6 (none of the time). A GH item
example was ‘I am as healthy as anybody I know’,
with the responses ranging from 1 (definitely
true) to 5 (definitely false). As SF-36 is a widely
popular (Lins & Carvalho, 2016) and established
health measurement survey, including a Bahasa
Indonesia version, we did not reevaluate it in our
pilot trial, as it was previously validated in Bahasa
Indonesia (Novitasari, Perwitasari, & Khoirunisa,
2016), The EWB and GH aspects were reliable (α
> .70) in the Bahasa Indonesia version (Novitasari
et al., 2016).
Data Analysis
This is an exploratory study which influenced
the flow of the data analysis. The descriptive
statistics were obtained with the basic feature of
Microsoft Excel, and we used R (version 4.0.2) to
create box plots and scatterplots using the
‘ggplot2’ package. The scatterplots, along with the
effect size (bivariate correlation, intercepts, or R2)
and p-value, helped the authors to make a precise
decision on hypothesis testing.

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E. A. Surijah, G. H. Prasad, M. R. A. Saraswati

To test the model fit, a Structural Equation
Model with IBM SPSS 26 AMOS as the statistical
tool was employed. The general model is shown in
Figure 1. This initial model fit would determine the
components of the dyadic model, and the dyadic
analysis would then examine the actor partner
interdependence model of couple resilience. A
robust estimation with maximum likelihood
(Phillips, 2015) in R was also conducted as a
comparison to support our findings and to
anticipate highly skewed data distribution. We
explain the analysis further in the Results section.

Results
Table 2 and Figure 2 outline the descriptive
characteristics of the participants and the raw
data distribution of the study. The majority of the
participants were newlyweds (n = 141 couples,
47%), while 67 couples had been married for 4-6
years and 92 couples for more than seven years.
More than half of the couples (73%) had one or
two offspring, while 47 couples did not have any
children, and 35 had three or four children.
Based on Figure 2, it can be observed that the
participants’ positive behavior was mostly
distributed within the range of 40 to 50 and did
not reach the ceiling, as also demonstrated in the
previous study (Sanford et al., 2016). It can also be
seen that the data distribution for each variable is
skewed.
The next part of the visual-based analysis
comprised the scatterplots, as shown in Figure 3,
which give a visualization of the relationship
between the variables. The slope and the
confidence interval support the statistical analysis
given the p-value and effect size. The scatterplots
give initial evidence that positive behaviors would
have the strongest association with marital
satisfaction.

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Prior to the model examination, we
conducted a bivariate correlation. This correlation
matrix intended to inform the authors on
selecting the control variables (e.g., age, marital
duration), and supporting the inferences from the
hypothesis testing.
In addition, we also added a bivariate
correlation for the separate husband and wife
data (Table 2).
Previously, we stated that the overarching
hypothesis in the study was that the positive and
negative behaviors of couple resilience predict
marital satisfaction, general health, and emotional
wellbeing, considering the participants’ age,
marital duration, and number of children. We
conducted a structural equation model analysis to
test the model fit of the proposed hypothesis. The
data analysis showed that it was not supported.
The Chi-square test result was χ2 = 108.065; df =
3; and p = .000, with other indices being RMSEA =
.242; CFI = .895; and TLI = .020.
Upon closer examination, the regression
estimate rejected the null-hypothesis of the
coefficients of positive behavior towards marital
satisfaction (β = .385, p < .001, r = .368), the
coefficients of positive behavior towards
emotional wellbeing (β = .170, p < .001, r = .180),
and the coefficients of positive behavior towards
general health (β = .112; p < .01; r = .160). The
regression estimates also rejected the coefficients
of the number of children as a control variable
towards general health (β = .224; p < .001; r =
.650). This finding shows that the general model
of couple resilience and the underlying hypothesis
were not supported. Positive behavior may have a
significant relationship with the outcomes;
however, the scatterplots and the rather low
effect size prompted us to investigate further the
relationship between the variables.

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Figure 2
Univariate Box Plots of Each Variable

Note: The raw data distributions overlaid on the box plots give a visual cue; for example,
the data distribution between husband and wife differs little for each variable.

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E. A. Surijah, G. H. Prasad, M. R. A. Saraswati

Table 1
Simple Correlation between Variables

1. SWML
2. PR

1

2

3

4

1

.368**

-.093*

.083*

.121**

.021

1

-.362**

.160**

.180**

.127**

1

-.127*

-.090*

-.153*

-.024

.019

-.090*

1

.413**

.135*

-.033

-.030

.110**

1

.378**

.037

.005

.023

1

.011

.007

.020

1

.647**

.448**

1

.650**

3. NR
4. GenHealth

5

5. EWB

6

6. SocFunc

7

7. Age

8

9

-.048

-.148**

-.081*

.004

-.037

.102*

8. Duration
9. Child

1

Note: SWML (Satisfaction with Married Life); PR and NR (Positive and Negative Behavior
aspects of Couple Resilience); GenHealth (General Health); EWB (Emotional Wellbeing);
SocFunc (Social Functioning); Duration (Marital Duration); and Child (Number of Children); **
Correlation is significant at the 0.01 level (2-tailed), and *Correlation is significant at the 0.05
level (2-tailed).

Table 2
Simple Correlation between Variables among Husbands and Wives
M (SD)
1. SWML
Husband

29.64
(3.66)

2. PR
Husband

44.83
(7.02)

3. EWB
Husband

94.16
(18.03)

4. SWML
Wife

29.16
(3.73)

5. PR
Wife

45.19
(7.09)

6. EWB
Wife

93.50
(19.59)

7. Children

1

2

3

4

5

6

7

8

1

.345**

.095

.481**

.292**

.062

-.060

-.128*

1

.207**

.235**

.585**

.071

.103

-.052

1

.035

.124*

.280**

.053

-.005

1

.396**

.150**

-.098

-.168**

1

.151**

.104

-.021

1

.005

.017

1

8. Duration

.646**
1

Note: SWML (Satisfaction with Married Life); PR and NR (Positive and Negative Behavior
aspects of Couple Resilience); EWB (Emotional Wellbeing); Duration (Marital Duration); and
Child (Number of Children); ** Correlation is significant at the 0.01 level (2-tailed), and *
Correlation is significant at the 0.05 level (2-tailed).

22 │

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Couple resilience predicted marital satisfaction but not well-being and health ….

Figure 3
Scatterplots

Note: Scatterplots showing that positive behaviors and marital satisfaction have the strongest
association. The data analysis show that these two variables would have the highest correlation
coefficient when compared to other pairings.

The data analysis was investigated further by
computing the dyadic data on positive behavior
and the outcomes based on the number of
children, as shown in Figure 4. Based on the

previous model fit analysis, positive behavior was
the only significant predictor of the outcomes
(marital satisfaction, emotional wellbeing, and
general health). We computed the number of

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E. A. Surijah, G. H. Prasad, M. R. A. Saraswati

children as a control variable as the previous
analysis showed that this contributed significantly
to the participants’ general health. The dyadic
model fit obtained a Chi-square test result of χ2 =
18.101; df = 9; and p = .034, and the other indices
were RMSEA = .058; CFI = .982; and TLI = .928.
The regression estimate shows that husbands’
positive behavior increased their marital
satisfaction (β = .271; p < .001; r = .345), and
emotional wellbeing (β = .202; p < .01; r = .207).
Similarly, wives’ positive behavior leveraged their

own marital satisfaction (β = .403; p < .001; r =
.396). However, the data analysis also showed
that there was no interaction effect between the
dyads. The second hypothesis focuses on the
dyadic relationship of the married couples. It
predicts that the positive behavior of an actor will
influence their own outcomes and those of their
partner. The results suggest differing support for
the second hypothesis, as there were small effect
sizes on the actors’ effects on marital satisfaction,
and no interaction effect between the couples.

Figure 4
Relationship between Variables

Note: Positive relationship behaviors only predicted the actor effect given the number of
children. The lines and numbers in bold show the significant effects. All the numbers show
standardized regression weights except for the covariance between a husband’s and wife’s
positive relationship behaviors. The number of children as a covariate is not shown to simplify
the illustration.

24 │

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Couple resilience predicted marital satisfaction but not well-being and health ….

The general conclusion from the data analysis
is that positive behavior predicts marital
satisfaction; however, the effect size was smaller
than expected. This finding was supported by the
scatterplots shown in Figure 3. Due to the nonnormal data distribution shown in Figure 2, we
compared the results of the simple linear
regression and the linear regression with
maximum likelihood fitting. The simple linear
regression was calculated with function ‘lm’ in R.
The analysis showed that positive behavior
contributed to the marital satisfaction variability
with an intercept coefficient = 20.70, β = .19, p <
.01, and adjusted R2 = .134. The maximum
likelihood fitting was computed by minimizing
the deviance and estimating the parameters, that
would minimize the loss function (Phillips, 2015).
We used the ‘optim’ function in R to calculate the
parameters. The optimisation converged in a
single value and the intercept coefficient = 20.69,
β = .19, and error standard deviation = 3.44. The
population value of slope β is within the range
with 95% CI [.16, .22] This evidence shows that
there were no significant differences between the
two analyses. This study demonstrates that a
single unit increase in positive behavior will
increase marital satisfaction by .20.

Discussion
The first part of this study examined the
general model of couple resilience, as the model fit
analysis did not support the proposed working
model. Positive behavior, despite significantly
rejecting the null hypothesis, had smaller effect
sizes than expected. However, its current size for
marital satisfaction is similar to the previous study
of Sanford et al. (2016). This finding shows that
individuals who perceive themselves as having
more positive behavior in their relationship will

have a higher chance of being more satisfied with
their marriage. The previous study by Willoughby
et al. (2020) found that married couples and
individuals who had a positive belief in their
marriage would increase their commitment and
this positive belief was indirectly related to a
higher level of relationship satisfaction. Wives who
had a positive body image were associated with a
higher level of their own and their partner’s
marital satisfaction (Meltzer & McNulty, 2010).
Developing self-esteem also contributed to a
subsequent growth in marital satisfaction (Erol &
Orth, 2014). This study has highlighted the
potential of positive self-evaluation in contributing
to a higher level of marital satisfaction.
The second part of the analysis also
highlighted the importance of personal evaluation
within marriage relationships. Although the
expected interaction effect on the second
hypothesis was not supported, the data analysis
showed that wives’ positive behavior positively
predicted their own marital satisfaction, with a
medium effect size. Gender difference studies
indicate that there are differences in marital
satisfaction between husbands and wives
(Jackson et al., 2014; Rostami et al., 2013). Wives’
marital satisfaction correlates more strongly
between constructs (Beam et al., 2018). Wives
also react to marriage differently than their
partners, focusing more on the relationship
attunement (Beam et al., 2018). The different
responses between husbands and wives may
explain the absence of interaction effects in this
study. Wives’ stronger relationship between
positive relationship behaviors and marital
satisfaction reflects their predisposition to work
on relationship attunement.
Additionally, negative behavior did not
predict all the outcomes. The confirmatory factor

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E. A. Surijah, G. H. Prasad, M. R. A. Saraswati

analysis also showed that positive and negative
behavior were not adjacent in constructing the
CRI. This evidence supported our initial critics as
we believed that resilience is tied to positive
adaptation (Luthar & Cicchetti, 2000). The
implication of the findings of our study indicates a
new direction in understanding the construct.
Couple resilience may not comprise positive and
negative resilience. The positive adaptation of
couples dealing with adversity will be achieved
through positive relationship behaviors.
Another gap that this study aimed to address
was related to the theoretical perspective of
couple resilience. Measuring resilience with a
single inventory (Maltby, Day, & Hall, 2015; Lock,
Rees, & Heritage, 2020) reinforced the view that
couple resilience is a trait. Resilient couples will
exhibit positive behaviors in maintaining their
relationship or resolving adversities. This notion
reinforces the view of couple resilience being a set
of positive behaviors and that married individuals
engage to maintain or regain their relationship.
Negative behaviors are not the other side of the
coin, and engaging in them would be something
out of character.
Couple resilience was initially defined as the
process by which couples participate in
relationship behaviors to handle adversity
(Sanford, Backer-Fulghum, & Carson, 2016). This
study’s findings pose the question of whether
couple resilience is a resource (trait) or a dynamic
process in the face of stressful life events.
Bonanno (2005) stated that there is no single
resilient type, and people will behave in
unforeseen ways in order to be resilient. Previous
studies have shown that resilience as a process
will allow individuals to learn and develop skills
or capabilities to attain positive adaptation

26 │

through the interaction with multiple systems
(Foster et al., 2018; Foster, 2020; Masten &
Barnes, 2018). Therefore, this study proposes the
idea that couple resilience is a dynamic process
through which couples achieve positive adaptation despite adversity.
The proposed idea of couple resilience as a
process reveals a limitation of this study. We
observed positive relationship behaviors in a
single cross-sectional design, an approach which
was not able to unfold the dynamic process of
couple resilience. Future studies should not rely on
a single inventory and a single cross-sectional
research design. A longitudinal method is a
suitable approach to operationalizing couple
resilience. A systematic review (Cosco et al., 2015)
found that longitudinal studies on resilience
conducted repeated applications of psychometrically established resilience scales, repeated
measures of the criteria, and calculation of the
latent variables. In the context of couple resilience
studies, a longitudinal study design would observe
marital satisfaction, wellbeing, and the other
resilience outcomes in a multiphase repeated
measure design.
In relation to the measurement of the
outcome criteria, the second limitation of this
study is the measurement validity. The study used
the SF-36 health survey to estimate the
participants’ wellbeing and health status. Future
studies should employ a specific wellbeing
measure to gauge this wellbeing accurately. The
Mental Health Continuum-Short Form (Franken et
al., 2018) or contextually appropriate wellbeing
scales (Maulana et al., 2019) would be effective
tools to measure wellbeing. The changes in the
measurements may also strengthen the
relationship between positive behaviors and
wellbeing.

Psikohumaniora: Jurnal Penelitian Psikologi — Vol 6, No 1 (2021)

Couple resilience predicted marital satisfaction but not well-being and health ….

As the study was conducted in Bali, Indonesia,
the researchers should have considered the
cultural and contextual appropriateness. Ungar
(2008) mentions that there are globally- and
culturally specific aspects of people’s lives that
contribute to resilience. For example, in the
context of African families, social justice is the
prominent factor that should precede the efforts in
promoting resilience (Anderson, 2019). Therefore,
future studies should also pay attention to the
cultural context of marital relationships and its
related challenges in Bali, Indonesia.

Conclusion
The current study concluded that couple
resilience refers to the positive relationship
behaviors that help couples to obtain positive
outcomes or adaptation. These behaviors
specifically lead to a higher probability of couples
reaching a higher level of marital satisfaction,

especially in relation to wives or females.
However, the crucial issue for the future
development of couple resilience is to observe
couples’ dynamic over time.
Acknowledgment
We thank Kris Pradnya Swari and Meriska
Lesmana for helping the authors to collect the
data. We also thank Prof. Ian Shochet
(Queensland University of Technology, Australia)
and Dr. Kate Murray (Queensland University of
Technology, Australia) for giving us valuable
insights throughout the conceptual developments
of this manuscript. We thank Listiyani Dewi
Hartika, M. Psi., psikolog (Universitas Dhyana
Pura), Agnes Utari Hanum Ayuningtyas, M. Psi.,
psikolog (Universitas Dhyana Pura), Rai Hardika,
M. Psi., psikolog (Universitas Dhyana Pura) for the
constructive feedbacks for the authors.[]

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