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Couple resilience predicted marital satisfaction but not well-being and health for married couples in Bali, Indonesia

Throughout their marriage, couples face numerous adversities, with marital dissolution the ultimate threat. Couple resilience is defined as the process undertaken by couples to manage adversity through positive relationship behaviors. Previous studies on couple resilience have focused on negative relationship behaviors, but have not explored the interaction effect between the dyads. Three hundred couples living in Bali, Indonesia participated in this study by reporting their positive and negative relationship behaviors, and the expected outcomes of these (marital satisfaction, emotional wellbeing, and general health status). Model fit analysis showed that the relationship behaviors did not predict the outcomes, and that there was no interaction effect between couples. Positive behaviors, however, showed a higher probability of predicting marital satisfaction, especially amongst wives. The implication of this finding leads to the practical suggestion for future couple resilience studies to conduct a multiphase longitudinal study with repeated measures of the outcomes.


Introduction
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  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, Wiloughby, & Doherty, 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, Wiloughby, & Doherty, 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.
In the field of relationships, couple resilience is 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, Backer-Fulghum, & Carson, 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, Backer-Fulghum, & Carson, 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, Backer-Fulghum, & Carson, 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 (Peláez-Ballestas, et al., 2015;Rafnsson, Jonsson, & Windle, 2006). Negative coping strategies are Couple resilience predicted marital satisfaction but not well-being and health ….
Psikohumaniora: Jurnal Penelitian Psikologi -Vol 6, No 1 (2021) │ 15 associated with depressive symptoms and poorer emotional regulations (Heffer & Willoughby, 2017). 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, Backer-Fulghum, & Carson, 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, Shen, Sinclair, Grossman, & Klieger, 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, Westphal, & Mancini, 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, Backer-Fulghum, & Carson, 2016). On the other hand, the outcome of similar concepts (e.g., dyadic coping) is relationship quality (Bodenmann, Pihet, & Kayser, 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, Hall, & Murray, 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, Milek, Nussbeck, Davila, & Bodenmann, 2018). A previous study on couple resilience (Sanford, Backer-Fulghum, & Carson, 2016) also found relationships between positive resilience and marital satisfaction (r = .35), and

Figure 1
Working model of the study illustrating couple resilience as a set of positive and negative behaviors 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 that negative resilience was negatively correlated (r = -.10) with wellbeing (Sanford, Backer-Fulghum, & 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, Ghazinour, Nygren, Nojumi, & Richter, 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 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 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.

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, Backer-Fulghum, & 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.
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.

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. 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, Backer-Fulghum, & Carson, 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 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, Backer-Fulghum, & Carson, 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 Couple resilience predicted marital satisfaction but not well-being and health ….
Psikohumaniora: Jurnal Penelitian Psikologi -Vol 6, No 1 (2021) │ 19 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 Chisquare 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.
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, Perwitasari, & Khoirunisa, 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 R 2 ) and p-value, helped the authors to make a precise decision on hypothesis testing.

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. 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. 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, Backer-Fulghum, & Carson, 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.

Based on
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. however, the scatterplots and the rather low effect size prompted us to investigate further the relationship between the variables.

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

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

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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 R 2 = .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, Backer-Fulghum, and Carson (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, Miller, Oka, & Henry, 2014;Rostami, Ghazinour, Nygren, Nojumi, & Richter, 2013). Wives' marital satisfaction correlates more strongly between constructs (Beam, Marcus, Turkheimer, & Emery, 2018). Wives also react to marriage differently than their partners, focusing more on the relationship attunement (Beam, Marcus, Turkheimer, & Emery, 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 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 . 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 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, Lamers, Ten Klooster, Bohlmeijer, & Westerhof, 2018) or contextually appropriate wellbeing scales (Maulana, Khawaja, & Obst, 2019) would be effective tools to measure wellbeing. The changes in the measurements may also strengthen the relationship between positive behaviors and wellbeing.
Couple resilience predicted marital satisfaction but not well-being and health ….

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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.