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The most recent report from the Centers for Disease Control estimates that 1 in 59 children have a diagnosis of Autism Spectrum Disorder (Centers for Disease Control, 2018). This is a 15% increase from their last estimation two years ago, which highlights the importance of conducting research in this population. Having a diagnosis of Autism Spectrum Disorder (ASD) has a direct effect on the child given the diagnosis, but it also affects the parents of those children. Parents of children with ASD report lower levels of life satisfaction than parents of children without a disability (Gau et al., 2012; Hoefman et al, 2014). However, certain characteristics of the individual have been shown to improve life satisfaction in parents of children with ASD. Having positive coping strategies, optimistic views, and self-efficacy have been shown to increase overall life satisfaction (Kuhn & Carter, 2006; Ekas, Lickenbrock, & Whitman, 2010; Faso, Neal-Beevers, & Carlson, 2013).
However, there is no research examining the effects of co-parenting on life satisfaction within couples who have a child with ASD. Almost all of the studies examining parenting and life satisfaction focus on mothers, not on both the mother and the father (Hartley et al., 2012; Conti, 2015; Shivers, Leonczyk, & Dykens, 2016). Although research has shown that there is little difference between genders in their rating of life satisfaction, it is possible that different predictors are influencing that rating (Ryff, 1989). With it becoming more and more common for fathers to take on additional roles of parenting, it is imperative to examine how aspects of co-parenting effect their life satisfaction too.
Co-parenting is the way that two adults share the responsibilities of raising a child (Feinberg, 2003). By definition, it includes both the mother and the father (in a heterosexual dyad). According to family systems theory, families are a complex unit of multiple individuals are always responding to each other (Joyce, 2012). This theory states that a family is a single emotional unit, and all members of the family are connected emotionally. If families are a single unit, it is important to examine the co-parenting paradigm between parents, as opposed to looking at parenting in the mother and parenting in the father separately. Fagan and Lee have found that parents who help each other parent have better relationship outcomes (2013). Particularly, they found that lower father perceptions of co-parenting are significantly related to reporting higher levels of stress. Stress leads to a variety of negative mental outcomes, and has been shown to be higher among family members who care for someone with an ASD diagnosis than for the general population (Bonis, 2016; Herrema et al. 2017). This makes it important to examine how a partner views and participates in co-parenting, and how it affects the individuals in the co-parenting relationship.
The purpose of this study is to examine how different aspects of co-parenting a child with ASD influence life satisfaction, and how partner’s perceptions of co-parenting are influencing an individual’s life satisfaction. Based on previous research, I do not expect gender to play a significant role in predicting life satisfaction within couples. I expect that having your partner endorse, support, and approve your parenting more as a will increase your life satisfaction. I also expect that as your own endorsement, support, and approval of your partner’s parenting will increase life satisfaction. I also expect the same bi-directional relationship with parenting closeness, that life satisfaction will increase. However, I expect that believing your partner undermines your parenting will decrease life satisfaction, and that your partner believing you undermine their parenting will decrease your life satisfaction as well.
This study consisted of 33 couples who completed various self-report measures. Two participants were excluded because their partner did not complete the surveys. All couples were either married (n = 32) or living together. All couples had at least one child with a diagnosis of ASD. Parents average age was 37.51 (SD = 5.89), and the average family income ranged from $40,000 to $74,999.
Demographics. Both parents reported on how many children they had, the ages of their children, and about which of their children had a diagnosis of ASD. They also reported on their ethnicity and family income.
Satisfaction with Life Scale. The satisfaction with life scale measure’s an individual’s own perception of their life. It was completed by both parents. Participants rated statements on a scale from 1 to 7, from strongly disagree to strongly agree. The statements they rated included “in most ways, my life is close to ideal” and “if I could live my life over, I would change almost nothing”. Scores were summed to get an overall satisfaction with life score.
Co-parenting Relationship Questionnaire. The co-parenting questionnaire was completed by both parents. Parents rated statements such as “I believe my partner is a good parent”, “my partner undermines my parenting” and “we often discuss the best way to meet our child’s needs” on a scale from 0 (not true of us) to 6 (very true of us). This questionnaire consists of seven subscales: co-parenting support, co-parenting undermining, co-parenting partner endorsement, co-parenting agreement, co-parenting closeness, division of labor, and exposure to conflict. The first six subscales were used in this study.
This study is examining how individuals within a couple are influencing their partner’s life satisfaction. Due to their relationship status as married or cohabiting, it is reasonable to expect that each individual within the couple will influence the other’s life satisfaction. This absence of independence is why an actor-partner interdependence model data analysis is necessary. Most statistical methods require independence of data, which is not present within couples.
To analyze this dyadic data, Hierarchical Linear Modeling was used through the HLM 7.0 program (HLM; Raudenbush and Bryk, 2002). For dyadic data, the modeling uses an actor-partner paradigm. HLM modeling examines the effect of the partner on the actor, as well as the actor on the actor. The goal is to examine how partner variables impact the outcome of the actor, and how the actor’s variables impact the outcome of the actor at the same time. HLM allows data to be analyzed at multiple levels. In this study, the individuals (level 1) are nested within a couple (level 2).
At level 1 of the model, life satisfaction was predicted by an intercept, the individual’s gender (β0; coded 0 = male and 1 = female), the actor’s score on the independent variable (β1), their partner’s score on the independent variable (β0), and error (r). The two independent variables were centered around the grand mean, to describe what life satisfaction is at an average of the independent variable. Gender was not centered in any way, because it has a meaningful zero. Due to small sample size (33 couples), restricted maximum likelihood was used for all models, and all the slopes were fixed (β1, β2, and β3). The intercept was left random. Co-parenting undermining, division of labor, co-parenting partner endorsement, co-parenting support, co-parenting agreement, and co-parenting closeness were used to predict life satisfaction.
To examine multiple predictors of life satisfaction, multiple models were run using HLM. Gender was used as the grouping variable to separate mother and father effects, so it was always present in the model. The first model only contained gender, and the following models contained both the partner effect and the actor effect. The actor effect and partner effect were included in the first model of each analysis and for significant predictors of life satisfaction, further analyses were run to examine if the interaction of gender and the predictor was a significant predictor of life satisfaction. With each predictor of life satisfaction, number of children was added as a level two predictor. However, each of the six final models ended up having the same equation (see figure 1 for model).
First, just the actor’s gender was entered into the equation. When entered, there was still significant unexplained variance, so other variables were entered into subsequent models. The first variable, co-parenting undermining was added to the model with gender as a predictor of life satisfaction. Both the actor’s co-parenting undermining and the partner’s co-parenting undermining were added in this step. Although there was still a significant amount of unexplained variance, there were main effects that significantly predicted life satisfaction. The addition of the interaction between co-parenting and gender was added to the model next. The model fit was not improved with this addition, and the interaction was not a significant predictor of life satisfaction, p ³ .500. Thus, it was removed and not included in the final model. The same pattern emerged with the other five main effects of co-parenting that were tested separately. The interaction between the partner and actor’s score on co-parenting undermining was added next, however this interaction was also non-significant, p ³ .500. Again, the same pattern followed for all additional co-parenting predictors.
At level 2 of the model, number of children within the family was added. The number of children was not a significant predictor of life satisfaction, nor did it interact significantly with partner co-parenting undermining or actor co-parenting undermining, ps ³ .050. The same pattern emerged for all other models, so the level 2 predictor was not included in any of the final models.
In each subsequent model, the addition of division of labor, co-parenting support, co-parenting partner endorsement, co-parenting agreement, and co-parenting closeness to the model with gender present had significant main effects. Gender was not a significant predictor of life satisfaction, but it was kept in the model to test interactions. The gender and effect interactions were entered next, and all of the level 1 interactions were non-significant for all models, ps ³ .050. The addition of number of children in the family at level 2 was also non-significant. Due to lack of explaining variance and lack of significantly predicting life satisfaction, the final variables that were included in the model were the main effects of the partner, the main effects of the actor, and gender.
The characteristic of co-parenting that most improved life satisfaction is partner endorsement. Partner endorsement refers to how much you feel your partner backs up your parenting decisions. It does make sense, because if you’re not being endorsed by your partner, you may not feel like your parenting style is valid. Interestingly, there was no difference in gender on how parenting endorsement predicts life satisfaction. Although I did not expect a difference, this shows that it is important for both the father to endorse the mother’s parenting, and vice versa.
Endorsing co-parenting improves life satisfaction, so it fits that the opposite, undermining your partner’s co-parenting would decrease life satisfaction. Both the actor’s report of how much they are undermined and their partner’s report of how much they are undermined decreased the actor’s life satisfaction. How much the actor feels like they are being undermined decreases their life satisfaction score more than if their partner reports being undermined. Undermining co-parenting has been shown to lower parenting self-efficacy and competitive parenting, which are related to lower life satisfaction (Merrifield & Gamble, 2012; Murphy, Jacobvitz, & Hazen, 2015). Like endorsement, both actor and partner reports of co-parenting support significantly impacted the actor’s life satisfaction. Support and partner endorsement are similar in that they help buffer some of the negative effects of co-parenting undermining and conflict (Riina & Feinberg, 2018). To best improve life satisfaction, it seems that both parents should be taught how to not undermine each other’s parenting, but instead how to support and endorse their partner’s parenting.
Although the actor’s own perceptions of division of labor impacted their own life satisfaction, their partner’s reports only marginally predicted the actor’s life satisfaction. Due to a small sample size, it is possible that this marginal effect would have become significant had more couples completed this study. Previous research has shown that when parents are satisfied with the division of parenting, whatever that may be, they are generally happier and have better relationship satisfaction (Pina & Bengtson, 1993; Lavee & Katz, 2002). Interestingly, in this study no differences were found between men and women. Previous research has focused mainly on the women in the relationship and have found that the division of labor is more important to the wife than the husband (Kawamura & Brown, 2010). As marriages become more egalitarian, this lack of a gender effect might become more common. Future research is needed within opposite sex couples to examine if gender is still an important factor in determining happiness with parenting division of labor.
The two constructs of co-parenting that did not have a significant partner effect were co-parenting agreement and co-parenting closeness. However, the actor’s own perception of co-parenting agreement and closeness were significant predictors of their life satisfaction. This may be because it does not matter as much if parents have similar styles of parenting, but what really matters is how they support and endorse each other’s parenting. Further research is needed to examine why the partner’s perceptions are not significant predictors of the actor’s life satisfaction, only the actor’s perceptions are.
Although there were significant predictors of life satisfaction, none of the predictors significantly reduced unexplained variance. This is probably due to the fact that things other than parenting and how you and your partner split parenting duties influence your overall life satisfaction. Life satisfaction is a very broad construct, and theoretically everything that happens in one’s life influences it.
Future research should include not only co-parenting, but other measures that can predict life satisfaction. It is probable that many other factors are influencing parent’s life satisfaction, like the quality of their marriage, the relationships they have with friends, their socio-economic status (SES), and so on.
It would also be beneficial to examine couples who have a child with ASD, and couples who only have typically developing children. It has been shown that compared to parents of typically developing children, parents of children with ASD tend to have lower well-being, higher levels of anxiety and depression, and lower satisfaction overall (Faso, Neel-Beevers, & Carlson, 2013). Comparing these parents would show if there was a difference between parenting children with and without an ASD in terms of life satisfaction, and how important co-parenting is in different types of families. Although we can say that efficient co-parenting is beneficial for parents of children with ASD, this study cannot compare the effects of co-parenting on life satisfaction across different types of parents.
Another future direction would be to examine co-parenting longitudinally. Research has shown that co-parenting behaviors vary daily (McDaniel, Teti, & Feinberg, 2017). This variance between days may be important in predicting life satisfaction. Future research should examine if a more consistent report of co-parenting is more beneficial for life satisfaction compared to co-parents who vary widely day-to-day on how they agree and disagree on parenting decisions. Longitudinal research has shown that daily relationship satisfaction relies on co-parenting satisfaction, which suggests that it may have an effect on life satisfaction too (McDaniel, Teti, & Feinberg, 2017).
One of the major limitations in this study was small sample size. Other models that have looked at how parenting impacts a couple’s relationship have had upwards of 200 couples participate (Ponnet et al., 2012). Kashy, Bolger, and Kenny recommend at least 35 dyads to conduct this actor-partner paradigm, and the current study only had 33 (1998). Unfortunately, two participants had to be kicked out of the current study because their partner did not complete any measures. If they had, this study would have had enough dyads to meet the minimum power requirements. With more participants, there would have been higher power, which could lead to more significant main effects and interactions.
Another limitation is the lack of diversity of the participants in this study. Most of the parents who participated in this study were upper middle-class families. Although not tested directly in this study, it is possible that co-parenting may have a larger impact on life satisfaction if there are fewer stressors in the family, like money problems. We may not see the same main effects present in families whose SES fall in the lower to lower middle-class range.
Finally, the lack of different variables being used to predict life satisfaction was a limitation of this study. Life satisfaction is defined as one’s evaluation of life as a whole (Prasoon & Chaturvedi, 2016). Because it is such a broad measure, it is to be expected that many other factors influence it, other than parenting. As discussed in the future research section, this study may have been able to account for more of the unexplained variance had it contained more predictors.
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