IntroductionThe most recent report from the Centers for Disease Control estimates that 1 in 59 children have a diagnosis of the disorder on the autism spectrum (Centers for Disease Control, 2018). This is an increase of 15% from their last estimate two years ago, highlighting the importance of conducting research on 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 these children. Parents of children with ASD report lower levels of life satisfaction than parents of children without disabilities (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 and Carlson, 2013).Say no. to plagiarism. Get a tailor-made essay on “Why Violent Video Games Should Not Be Banned”? Get an original essay However, there is no research examining the effects of co-parenting on life satisfaction among couples who have a child with ASD. Almost all studies examining parenting and life satisfaction focus on mothers, not mothers and fathers (Hartley et al., 2012; Conti, 2015; Shivers, Leonczyk, and Dykens, 2016). Although research has shown that there is little difference between the sexes in their evaluation of life satisfaction, it is possible that different predictors influence this evaluation (Ryff, 1989). As it is increasingly common for fathers to take on additional parenting roles, it is imperative to examine how aspects of co-parenting also affect their life satisfaction. Co-parenting is how two adults share the responsibilities of raising a child. (Feinberg, 2003). By definition, this includes both mother and father (in a heterosexual dyad). According to family systems theory, families are a complex unit made up of multiple individuals who always respond to each other (Joyce, 2012). This theory states that a family is a single emotional unit and that all family members are emotionally connected. If families are a single unit, it is important to examine the co-parenting paradigm between parents, rather than examining mother parenting and father parenting separately. Fagan and Lee found that supportive parents have better relationship outcomes (2013). In particular, they found that fathers' lower perceptions of co-parenting are significantly related to higher levels of stress. Stress leads to a variety of negative mental outcomes and has been shown to be higher among family members caring for someone with an ASD diagnosis than in the general population (Bonis, 2016; Herrema et al. 2017). It is therefore important to examine how one partner perceives and participates in co-parenting, and how this 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 perceptions of co-parenting influence an individual's life satisfaction. According to previous research,I do not expect gender to play a significant role in predicting life satisfaction within couples. I expect that having your partner approve, support, and approve more of your parenting will increase your life satisfaction. I also hope that your own approval, support and approval of your partner's parenting will increase life satisfaction. I also expect the same two-way relationship with parental closeness, increased life satisfaction. However, I expect that believing that your partner is undermining your parenting will decrease life satisfaction and that your partner believing that you are undermining their parenting will also decrease your life satisfaction. Methods Participants This study included 33 couples who completed various self-report measures. Two participants were excluded because their partner did not respond to the surveys. All couples were either married (n = 32) or living together. All couples had at least one child with a diagnosis of ASD. The average parental age was 37.51 years (SD = 5.89) and the average family income ranged from $40,000 to $74,999. Both parents reported how many children they had, the ages of their children, and which of their children had been diagnosed with ASD. They also reported their ethnicity and family income. Satisfaction with life scale. The Life Satisfaction Scale measures an individual's own perception of their life. It was completed by both parents. Participants rated the statements on a scale of 1 to 7, ranging from strongly disagree to strongly agree. The statements they rated included “In many ways, my life is close to ideal” and “If I could live my life again, I would change almost nothing.” Scores were summed to obtain an overall life satisfaction 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 interferes with my parenting,” and “We often discuss how best to meet our child's needs” on a scale of 0 (which is not true for us) to 6. (very true for us). This questionnaire consists of seven subscales: co-parenting support, co-parenting impairment, co-parenting partner approval, co-parenting agreement, co-parenting closeness, division of labor, and exposure to conflict. The first six subscales were used in this study. Analytical PlanThis study examines how individuals within a couple influence their partner's life satisfaction. Due to their relationship status (married or cohabiting), it is reasonable to expect that each individual within the couple will influence the other's life satisfaction. This lack of independence is why a data analysis of the actor-partner interdependence model is necessary. Most statistical methods require data independence, which is not present within couples. To analyze these dyadic data, hierarchical linear modeling was used via 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 partner on actor, as well as of actor on actor. The objective is to examine how the partner's variables impact the actor's outcome, and how the actor's variables simultaneously impact the actor's outcome. HLM allows you to analyzedata at multiple levels. In this study, individuals (level 1) are nested within a couple (level 2). At level 1 of the model, life satisfaction was predicted by an intercept, the sex of the individual (β0; coded 0 = man and 1 = woman), the score of the actor on the independent variable ( β1), the score of his partner on the independent variable (β0) and the error (r). The two independent variables were centered around the grand mean, to describe what life satisfaction is based on an average of the independent variable. Gender was not centered in any way, as it has a significant zero. Due to the small sample size (33 couples), restricted maximum likelihood was used for all models and all slopes were fixed (β1, β2, and β3). The interception remained random. Coparenting weakening, division of labor, coparenting partner approval, coparenting support, coparenting agreement, and coparenting closeness were used to predict life satisfaction. To examine multiple predictors of life satisfaction, several models were run using HLM. Gender was used as a grouping variable to separate mother and father effects, so it was still present in the model. The first model contained only gender, and subsequent 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 analyzes were conducted to examine whether the interaction of gender and of the predictor was a significant predictor of life satisfaction. For each life satisfaction predictor, number of children was added as a level two predictor. However, each of the final six models ended up having the same equation (see Figure 1 for the model). Model construction First, only the gender of the actor was entered into the equation. Once entered, there was still significant unexplained variance, so additional variables were entered into subsequent models. The first variable, decline in coparenting, was added to the model with gender as a predictor of life satisfaction. Violations of the actor's co-parenting and violations of the partner's co-parenting were added at this stage. Although there was still a significant amount of unexplained variance, some main effects significantly predicted life satisfaction. The addition of the interaction between coparenting and gender was then added to the model. Model fit was not improved with this addition, and the interaction was not a significant predictor of life satisfaction, p ³ 0.500. It was therefore removed and not included in the final model. The same pattern emerged with the other five main effects of coparenting that were tested separately. The interaction between partner and actor score on coparenting deterioration was then added, but this interaction was also nonsignificant, p ³ .500. Again, the same pattern applied to all other coparenting predictors. At level 2 of the model, the number of children in the family was added. Number of children was not a significant predictor of life satisfaction, nor did it significantly interact with partner coparenting or actor coparenting, ps ³ 0.050. The same pattern appeared for all other models, so the Level 2 predictor was not included in any of the final models. InEach subsequent model, the addition of division of labor, co-parenting support, co-parenting partner approval, co-parenting agreement, and co-parenting closeness to the gender-presence model had significant significant main effects. Gender was not a significant predictor of life satisfaction, but it was retained in the model to test for interactions. Interactions between gender and effects were then entered, and not all level 1 interactions were significant for all models, ps ³ 0.050. Adding the number of children in the family at level 2 was also not significant. Due to the lack of explanation of variance and lack of significant prediction of life satisfaction, the final variables included in the model were partner main effects, actor main effects, and gender. DiscussionThe characteristic of coparenting that most improved life satisfaction was partner approval. Partner approval refers to the extent to which you believe your partner supports your parenting decisions. This makes sense, because if you don't have support from your partner, you might not feel like your parenting style is valid. Interestingly, there were no gender differences in how parental approval predicted life satisfaction. Although I didn't expect a difference, it shows that it is important for the father to approve of the mother's parenting, and vice versa. Approving co-parenting improves life satisfaction, so it makes sense that the opposite, undermining your partner's co-parenting, would decrease life satisfaction. Both the actor's report of the extent of impairment and his or her partner's report of the extent of impairment decreased the actor's life satisfaction. The actor's feeling of being weakened reduces their life satisfaction score more than if their partner declares having been weakened. Impairing co-parenting has been shown to decrease parental self-efficacy and competitive parenting, which are linked to lower life satisfaction (Merrifield & Gamble, 2012; Murphy, Jacobvitz, & Hazen, 2015). Like approval, the actor's and partner's reports of coparenting support had a significant impact on the actor's life satisfaction. Partner support and approval are similar in that they help alleviate some of the negative effects of coparenting and conflict (Riina & Feinberg, 2018). To best improve life satisfaction, it seems that both parents should learn not to harm the other's parenting, but rather to support and approve of their partner's parenting. Although the actor's own perceptions of the division of labor impacted their own life satisfaction, their partner's reports only marginally predicted the actor's life satisfaction. Due to the small sample size, it is possible that this marginal effect would have become significant if more couples had completed this study. Previous research has shown that when parents are satisfied with any division of parenting, 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 primarily on women in the relationship and has shown that the division of labor is more important for.