Leisure Time and Family Functioning in Families Living with Autism Spectrum Disorder

Abstract

Family leisure can provide opportunities for both enjoyment and family growth. However, families of children with autism spectrum disorder (ASD) experience multiple barriers to engaging in satisfying family leisure activities. This study surveyed parents of children with ASD (n=112) and parents of children with typical development (n=123) to examine relationships among family leisure involvement, leisure satisfaction, family functioning, and satisfaction with family life. Parents of children with ASD reported a similar amount of leisure involvement as families of typically developing children. However, they reported lower leisure satisfaction, poorer family functioning, and less satisfaction with family life. Mediation models suggested that low leisure satisfaction was related to less effective family communication, which in turn led to poorer family functioning and less satisfaction with family life. Amount of time spent in leisure made relatively small contributions to predicting other family variables. These results suggest that leisure-focused interventions for families of children with ASD should focus on improving quality, rather than quantity, of family leisure time.

Leisure time is an important component of family life that provides opportunities for family members to interact, communicate, and learn together during enjoyable family activities. The core and balance model of family leisure (Zabriskie & McCormick, 2001) categorizes family leisure activities into two main types, core activities and balance activities. Core leisure activities are frequent, generally low-cost, and often take place inside the home; they include activities such as family meals, playing catch in the backyard, and going for walks. Balance leisure activities are less frequent, often take place outside the home, and usually involve more planning and/or cost. Balance activities include things such as family vacations, community outings, or having dinner at a restaurant. The core and balance model posits that these different types of leisure serve different functions within a family. Core activities provide opportunities for family members to spend time together during familiar routines. These predictable activities help to meet a family’s needs for structure and predictability, fostering closeness among family members, and therefore promoting family cohesion. On the other hand, balance activities provide opportunities for families to face new experiences and challenges together. These activities are thought to contribute to family flexibility by providing a sense of excitement and shared experience, as well as an opportunity for practicing flexible problem solving strategies while facing new challenges together (Zabriskie & McCormick, 2001). In support of this model, Zabriskie and McCormick (2001) found that both core and balance family leisure patterns were related to family cohesion and flexibility in a sample of college students. Core leisure activities were more strongly related to family cohesion, while core and balance activities correlated equally strongly with family flexibility.

Several researchers have also been interested in how core and balance family leisure activities contribute to family communication, family functioning, and satisfaction with family life. Agate et al. (2009) examined not just involvement in leisure, but also families’ satisfaction with leisure, and how these variables related to satisfaction with family life. They found that leisure satisfaction (rather than leisure involvement) was the single strongest predictor of satisfaction with family life, even after controlling for a number of demographic and personal factors. However, they did acknowledge that some degree of engagement in leisure is a clear prerequisite to leisure satisfaction. Poff, Zabriskie, and Townsend (2010) modeled relationships among these variables in a nationally representative sample of nearly 900 families. They concluded that family leisure involvement was related to satisfaction with family life, and that this relationship was mediated by both family functioning and satisfaction with leisure. Smith, Freeman, and Zabriskie (2009) furthered this model by examining the role of family communication. Family communication is theorized to play a facilitative role in the relationship between family leisure and family functioning; leisure activities provide a forum for practicing family communication in a relatively relaxed and “low-stakes” atmosphere, as well as affording time to engage in conversation and potentially discuss important family matters. In fact, parents report intentionally planning family leisure activities with the goal of enhancing family communication (Shaw & Dawson, 2001). This role for family communication has also gained empirical support; Smith et al. (2009) found that family communication mediated the relationship between family leisure and family functioning variables in a sample of youth (ages 11–17) from the United States. Relationships between family leisure and family functioning variables have also been substantiated across diverse groups of families, including transracial adoptive families (Zabriskie & Freeman, 2004), traditional Turkish families (Aslan, 2009), and single parent families (Hornberger, Zabriskie, & Freeman, 2010).

Leisure in Families Living with Disability

Families living with disability may face barriers to engaging in family leisure. Parents of children with disabilities report facing structural and environmental barriers (e.g., recreation settings not being physically accessible) as well as other accessibility barriers (e.g., lack of appropriate or adapted community leisure opportunities) to finding recreation opportunities for their children (Law, Petrenchik, King, & Hurley, 2007). Families may also perceive disability-related factors as interfering with family leisure. For example, mothers of children with autism spectrum disorder (ASD) describe their children’s need for routine as interfering with and decreasing enjoyment of family events (Larson, 2006). Additional factors that may interfere with leisure participation for children with ASD include sensory processing difficulties (Hochhauser & Engel-Yeger, 2010), lack of play/leisure skills (Lang et al., 2009), and interference of restricted and repetitive behaviors (Leekam, Prior, & Uljarevic, 2011), among others. These types of challenges may contribute to overall stress for family members of children with ASD, as multiple studies have found increased stress (Hayes & Watson, 2013) and depression (Ingersoll, Meyer, & Becker, 2011) among mothers of children with ASD.

Unfortunately, the little research that has explored leisure in families living with disability does not offer a clear picture. Dodd et al. (2009) found no significant differences in family functioning or family leisure involvement between families living with disability and a normative sample of families. In contrast, Settle (2016) found that families of young children with ASD participated in less family leisure and were less satisfied with their leisure time, as compared to families of young children without disabilities. These samples differed in age (mean age of child with disability in the Dodd sample = 11.66 years; in the Settle sample = 3.22 years) and disability type (mixed disabilities in the Dodd sample v. ASD only in the Settle sample). The relationships among family leisure time, leisure satisfaction, family functioning, and satisfaction with family life have also not been explored in detail. Settle (2016) found that amount of time spent in family leisure was correlated with parents’ satisfaction with leisure, but did not examine family functioning or satisfaction with family life. Dodd et al. (2009) found a positive relationship between time spent in core family leisure and several family functioning variables. However, this study did not examine satisfaction with leisure or satisfaction with family life. None of these studies has considered how parent mental health may complicate this picture, despite elevated depression in this population (Ingersoll et al., 2011) and the finding that leisure satisfaction contributes to psychological health (Pearson, 2008). Given the potential importance of leisure for families living with disability, and the challenges faced by these families when attempting to engage in leisure, additional research that more thoroughly explores relationships between leisure time, leisure satisfaction, family functioning, parent mental health, and satisfaction with family life is needed.

Goals of the Current Study

The current study aims to explore family leisure, family functioning, and satisfaction with family life in families that include a child with ASD, as compared to families with only typically developing (TD) children. First, we will compare quantity of leisure time, satisfaction with leisure, family functioning, parent depression, and satisfaction with family life between families with and without a child with ASD. We hypothesize that families of children with ASD will report lower family flexibility and cohesion, less leisure involvement, less satisfaction with leisure, greater depression, and lower satisfaction with family life compared to typical families (Higgins et al., 2005; Settle, 2016; Zablotsky, Anderson, & Law, 2013). Second, we will test the core and balance model of family leisure across families with and without ASD. Based on previous research with non-disability samples, we expect both core and balance leisure to contribute to both dimensions of family functioning (flexibility and cohesion) (Zabriskie & McCormick, 2001). We expect these relationships to be mediated by satisfaction with leisure (Poff et al., 2010) and family communication (Smith, Freeman, & Zabriskie, 2009). We will also explore whether these relationships differ in families living with ASD vs. TD families. Finally, we will examine whether having a child with ASD influences satisfaction with family life indirectly through leisure involvement, satisfaction with leisure, family communication, and family functioning, and whether these relationships are moderated by parent depression. We hypothesize that relationships between each mediator and satisfaction with family life will be weaker when parent mental health is good, suggesting a buffering effect of good mental health on satisfaction with family life.

Methods

Participants and Procedure

Review and approval for this study and all procedures were obtained from the Ohio State University Institutional Review Board. Participants were 112 parents/caregivers of children with ASD aged 4–18, and 123 parents/caregivers of children with typical development (TD) aged 4–18. Participants were recruited through the Research Match database (n=24 ASD, n=42 TD) or through Qualtrics (n=88 ASD, n=81 TD). Research Match is a national health volunteer registry that was created by several academic institutions and supported by the U.S. National Institutes of Health as part of the Clinical Translational Science Award (CTSA) program. Research Match has a large population of volunteers who have consented to be contacted by researchers about health studies for which they may be eligible. Qualtrics recruits individuals from a variety of general and targeted market research panels. Potentially eligible participants from both recruitment sources were invited to participate through e-mail invitation. All data were collected anonymously. A total of 288 participants (n=137 ASD; n=151 TD) began the survey. Thirty two participants (n=20 ASD; n=12 TD) did not complete the survey and were excluded case-wise. ASD group participants were excluded if the child did not score ≥12 on the Social Communication Questionnaire, Lifetime Version (n=5). While a cutoff score of 15 is typically used for this measure in clinical settings, a lower cutoff score of 12 was implemented in this study to maximize sensitivity in younger children as well as children already reported to have an ASD diagnosis, as recommended by Corsello et al. (2007). In order to maximize the likelihood that children included in the TD group were developing “typically” (i.e., did not have a significant developmental, mental health, or behavioral health disability), TD participants were excluded if the parent indicated that the child attended a school for children with developmental disabilities (n=2) or was school-aged (≥6 years) but spent <80% of the school day in a classroom with typical peers (n=14). This yielded a final sample of 235 participants (n=112 ASD; n=123 TD). See Table 1 for demographics.

Table 1.

Participant Characteristics

	Families Living w/ASD				Typical Families
	N	Mean (SD) or %	Range	N	Mean (SD) or %	Range
Caregiver Age (Years)	110	40.02 (9.29)	26–68	119	39.47 (9.13)	21–67
Caregiver Relationship to Child	112			123
Mother		76.8%			86.2%
Father		17.0%			8.9%
Other		6.3%			4.9%
Caregiver Race	112			123
American Indian/Alaskan		3.6%			0%
Asian		2.7%			3.3%
Black or African American		6.3%			4.9%
Native Hawaiian/Pacific Is.		0.9%			0%
White		84.8%			88.6%
Other		1.8%			3.3%
Caregiver Ethnicity (% Hispanic)	112	14.3%		123	8.1%
Caregiver Highest Education**	112			123
Less than High School		0.9%			1.6%
High School Graduate		19.6%			19.5%
Partial College		33.0%			14.6%
College Graduate		32.1%			35.8%
Graduate/Professional		14.3%			28.5%
Child Age (Years)**	112	10.71 (3.80)	4.0–18.83	123	9.08 (4.03)	4.17–18.0
Child Gender (% Male)**	112	78.6%		123	48.8%
SCQ Score	112	21.68 (5.84)	13–34	--	--	--
Child Educational Placement**	112			123
School for Children with DD		23.2%			0%
Homeschooled		9.8%			8.9%
0% of Day with TD Peers		2.7%			1.6%
1–39% of Day with TD Peers		14.3%			7.3%
40–79% of Day with TD Peers		14.3%			0.8%
80–99% of Day with TD Peers		8.0%			5.7%
100% of Day with TD Peers		27.7%			75.6%
Number of Children in Family	112	2.54 (1.23)	1–6	123	2.28 (1.11)	1–6
Number of Adults in Home	112	2.06 (.88)	1–5	123	1.96 (.59)	1–5
Annual Household Income*	110			120
Less than $20,000		11.8%			7.5%
$21,000–$40,000		26.4%			11.7%
$40,001–$60,000		20.9%			20.8%
$60,001–$90,000		17.3%			22.5%
Over $90,000		23.6%			37.5%

^*Significantly different between groups at p<.05

^**p<.01; ASD=Autism Spectrum Disorder

DD=Developmental Disabilities

SCQ=Social Communication Questionnaire

TD=Typically developing

Measures

Family Leisure Activity Profile (FLAP).

The FLAP (Zabriskie & McCormick, 2001) contains questions regarding sixteen different types of family leisure activities—eight “core” activities (e.g., playing games; participating in home-based outdoor activities) and eight “balance” activities (e.g., community-based special events; tourism activities). For each activity type, respondents are first asked whether they ever engage in this activity with family members. If the respondent indicates “yes,” they are then asked how often, and for about how long per time they typically engage in this activity. Finally, respondents are asked to indicate how satisfied they are with participation in the activity on a 1–5 scale, with 1 indicating “very dissatisfied” and 5 indicating “very satisfied.” This satisfaction question is asked regardless of whether or not the individual indicates that they engage in the activity (as some individuals might not participate in an activity due to lack of interest, and therefore be satisfied despite nonparticipation). In this study, we also added a question inquiring how frequently the target child (child with ASD or TD child) was present during the activity, with 1 indicating “never,” 2 indicating “sometimes,” and 3 indicating “always.”

To obtain scores for level of involvement in core and balance leisure, the frequency and duration scores for each item were combined to create an average weekly duration of participation in hours (e.g., if daily participation for 2–3 hours each time is reported, $\frac{2.5\mathrm{hours}\mathrm{x}365\mathrm{times}\mathrm{per}\mathrm{year}}{52\mathrm{weeks}\mathrm{per}\mathrm{year}}=17.55$ℎ𝑜𝑢𝑟𝑠/𝑤𝑒𝑒𝑘) (Melton, Ellis, & Zabriskie, 2016). For time estimates provided in days or weeks (e.g., vacations), we assumed 12 hours per day of meaningful participation. Scores for the eight core activities and the eight balance activities were summed to obtain scores for overall balance leisure involvement and overall core leisure involvement, and all sixteen items were summed to create a score for total leisure involvement. This time-based scoring method is recommended as having increased face validity, as well as adequate reliability when compared to previously used ordinal scoring methods (Melton et al., 2016). Cronbach’s alphas for leisure involvement scales in this sample were .67 for core leisure involvement, .79 for balance leisure involvement, and .80 for total leisure involvement. To obtain scores for satisfaction with leisure, we averaged the satisfaction score corresponding to each relevant leisure item to create total scores ranging from 1–5 for balance leisure satisfaction (α = .91), core leisure satisfaction (α = .89), and total leisure satisfaction (α = .94). To obtain scores for child involvement in leisure, we averaged the child involvement score corresponding to each relevant leisure item to create total scores ranging from 1–3 for balance leisure child involvement (α = .71), core leisure child involvement (α = .65), and total leisure child involvement (α = .79).

Family Adaptability and Cohesion Evaluation System (FACES-IV).

The FACES-IV (Olson, Gorall, & Tiesel, 2004) is a 62-item questionnaire with subscales measuring family flexibility, cohesion, communication, and satisfaction with family life. Respondents are provided with a series of statements and asked to indicate their agreement with each statement on a 1–5 scale, with 1 indicating “strongly disagree” and 5 indicating “strongly agree.” In the areas of family flexibility and cohesion, several items indicate healthy levels of these constructs (“balanced” cohesion and flexibility), while other items indicate very high levels (i.e., “enmeshed” patterns for cohesion, and “chaotic” patterns for flexibility) or very low levels (i.e., “disengaged” patterns for cohesion, and “rigid” patterns for flexibility) that are considered less healthy family structures. Scores for “balanced cohesion,” “balanced flexibility,” and “total balanced family functioning” are obtained by calculating a ratio in which the level of “balanced” cohesion or flexibility is divided by the score for “unbalanced” patterns in that area. These “balanced” ratio scores were used for all analyses in this study. Scores for family communication and satisfaction with family life are obtained by averaging the raw scores for the ten items in each area, producing a score that ranges from 1–5. In typically developing samples, the FACES-IV has been found to have strong internal consistency, a factor structure consistent with the subscale structure of the measure, and ability to discriminate between “problem” and “non-problem” family systems (Olson, 2011). It has also been used to examine family functioning in families of children with ASD, and shown expected patterns of relationships with children’s developmental functioning (Nuovo & Azzara, 2011) and maternal and child behavioral and mental health problems (Baker et al., 2011) in families living with ASD. In this sample, internal consistencies (Cronbach’s alpha) for these subscales were as follows: .73 for balanced cohesion, .66 for balanced flexibility, .82 for total balanced family functioning, .91 for family communication, and .95 for satisfaction with family life.

Neuro-QOL Item Bank v1.0, Depression Short Form.

The Depression-Short Form from the Neuro-QOL Item Bank v1.0 was used to examine parent depression (Cella et al., 2012). This form includes eight items regarding how often the respondent felt several depressive symptoms during the past seven days, with five answer choices ranging from “never” to “always.” This instrument has demonstrated good evidence of reliability and validity in large samples of adults from the general population, as well as adults experiencing chronic neurological conditions (Cella et al., 2012). Total scores on the measure were used to obtain a T-score indicating level of depression when compared to a general population sample (Gershon et al., 2012). Cronbach’s alpha was .95 for depression.

Data Analysis

Missing Data and Outliers.

Missing values for individual items (n=9) were singly imputed as the individual’s mean for the relevant subscale. Missing FACES-IV subscales (n=1) were excluded pairwise. On the FLAP, eleven caregivers (n=5 TD, n=6 ASD) reported implausible values for total leisure involvement (≥4380 hours, the equivalent of 12 hours/day of leisure every day). Values above 4380 were Winsorized (Reifman & Keyton, 2010) by replacing the total leisure value with 4380, and changing core and balance leisure involvement values to reflect the new total while maintaining the originally reported ratio of core: balance activities¹.

Demographic Analyses and Group Comparisons.

Independent samples t-tests, chi square, and Fisher’s exact tests were used to probe for demographic differences between groups. These analyses revealed that children in the ASD group were slightly older and more likely to be male. Parents in the ASD group were less well educated and reported lower family incomes than TD parents. Bivariate correlations indicated that child age, family income, and parent education (but not child gender) were significantly related to substantive variables of interest. Therefore, child age, family income, and parent education were entered as covariates in ANCOVA analyses examining group differences in leisure, family functioning, and mental health variables. Bivariate correlations (Pearson’s r for continuous variables and Spearman’s rho for ordinal variables) were used to explore relationships between level of functional impairment of the child with ASD (as measured by SCQ score and educational environment) and leisure, family functioning, and satisfaction with family life variables.

Mediation and Moderation Analyses.

Hayes’ (2013) PROCESS SPSS v.3.0 macro supplement was used with SPSS Statistics v.24 to test models examining predictors of family functioning and satisfaction with family life. All models were tested using 5,000 bootstrap samples, constructed using the percentile method. Specifically, we used custom PROCESS models to examine whether core leisure involvement and balance leisure involvement indirectly predicted family flexibility and cohesion, mediated by leisure satisfaction and family communication. We considered group (ASD v. TD) as a potential moderator of the paths in this mediation model (see Figure 1, Panel A for hypothesized model). Then, we used PROCESS model 88 to examine the impact of group (ASD v. TD) on Satisfaction with Family Life (SWFL), with total leisure involvement, total leisure satisfaction, family communication, and total balanced family functioning ratio as serial mediators; parent depression was examined as a potential moderator between each mediator and SWFL (See Figure 2). Nonsignificant moderation paths were dropped from the final models. A random number seed of 62983 was used for all models. All reported model coefficients are unstandardized.

Figure 1.

Hypothesized model for core and balance model of family functioning. Four models were run separately, with core leisure involvement and balance leisure involvement each predicting both family cohesion and family flexibility.

Figure 2.

Model predicting Satisfaction with Family Life. Solid lines indicate significant paths; dotted lines indicate paths dropped from the final model (moderation paths) or non-significant in the final model (mediation paths).

Results

Group Comparisons

Based on a Bonferroni correction for 15 tests, only p-values of <.003 were interpreted as significant. ANCOVA analyses were conducted using a main effects model controlling for child age, family income, and parental education level. No group differences emerged in core (F (1, 219) = 1.21, p =.273), balance (F (1, 219) = 0.38, p =.538), or total (F (1, 219) = 1.30, p =.255) leisure involvement. However, there were significant differences in satisfaction with leisure in the areas of core (F (1, 219) = 20.76, p<.001), balance (F (1, 219) = 18.04, p<.001), and total (F (1, 219) = 22.22, p<.001) leisure; caregivers of children with ASD reported lower satisfaction with leisure compared to caregivers of TD children. Children with ASD were not significantly less likely to be included in core (F (1, 216) = 7.12, p = .008), balance (F (1, 211) = 8.00, p = .005), or total (F (1, 217) = 7.62, p = .006) leisure activities, although there was a trend in this direction.

In the area of family functioning, caregivers of children with ASD reported lower family cohesion (F (1, 219) = 22.00, p<.001) and flexibility (F (1, 219) = 11.97, p=.001), as well as poorer overall family functioning (F (1, 219) = 23.16, p<.001). Family communication was not significantly different between the ASD and TD groups (F (1, 218) = 5.57, p=.019). Caregiver satisfaction with family life was also not significantly different between groups, but showed a trend toward lower satisfaction in the ASD group (F (1, 219) = 7.37, p=.007). Finally, caregivers in the ASD group reported higher levels of depressive symptoms compared to caregivers in the TD group (F (1, 219) = 15.11, p<.001). See Table 2.

Table 2.

Descriptive Statistics for Variables of Interest

	ASD			Typical			Group Comparisons
	N	Mean	SD	N	Mean	SD	p	Partial η2
Total Leisure Involvement (Hours/Week)	112	26.5	21.3	123	29.8	19.8	.255	.006
Core Leisure Involvement	112	21.6	17.2	123	23.3	15.5	.273	.005
Balance Leisure Involvement	112	4.95	7.66	123	6.45	10.1	.538	.002
Total Leisure Satisfactiona	112	3.41	.79	123	3.99	.80	<.001*	.092
Core Leisure Satisfactiona	112	3.43	.84	123	4.02	.81	<.001*	.087
Balance Leisure Satisfactiona	112	3.38	.88	123	3.95	.87	<.001*	.076
Total Leisure Child Involvementb	111	2.49	.37	122	2.66	.32	.006	.034
Core Leisure Child Involvementb	110	2.47	.39	122	2.65	.34	.008	.032
Balance Leisure Child Involvementb	106	2.51	.44	121	2.69	.32	.005	.037
Total Family Functioning Ratio	112	2.11	1.05	123	2.92	1.15	<.001*	.096
Family Cohesion Ratio	112	2.63	1.61	123	3.87	1.82	<.001*	.091
Family Flexibility Ratio	112	1.59	.70	123	1.97	.77	.001*	.052
Family Communicationa	112	3.71	.81	122	3.99	.60	.019	.025
Satisfaction with Family Lifea	112	3.42	.94	123	3.84	.80	.007	.033
Caregiver Depression T-Score	112	51.34	7.90	123	46.75	7.38	<.001*	.065

^*Significantly different from typical group following Bonferroni correction, using an ANCOVA main effects model controlling for parent education, family income, and child age

^aReported on 1–5 Likert-type scale, where higher numbers indicate greater satisfaction/better communication

^bReported on 1–3 Likert-type scale, where higher numbers indicate more frequent involvement of the target child in the activity

Exploratory correlational analyses indicated that, within the ASD group, ASD severity (as measured by the SCQ) was negatively correlated with involvement of the child in core leisure (r(108)=−.253, p=.008), involvement of the child in total leisure (r(109)=−.213, p=.025), and satisfaction with core leisure (r(110)=−.206, p=.029). As expected, among the sub-group of children with ASD attending a regular school (i.e., not homeschooled or attending a special school for children with disabilities), SCQ score and percentage of time spent with typical peers were negatively correlated (r_s (73) =−.242, p=.037), indicating that children with fewer symptoms of ASD were likely to spend a larger proportion of their day in a classroom with typical peers. Proportion of time spent in a typical classroom showed small to medium positive correlations with satisfaction with core, balance, and total leisure (Core r_s(73)=.242, p=.036; Balance r_s(73)=.282, p=.014; Total r_s(73)=.304, p=.008), as well as satisfaction with family life (r_s(73)=.228, p=.049). These results indicate that parents of children with milder ASD presentations (i.e., fewer symptoms of ASD or more ability to participate in typical educational settings) report greater satisfaction with leisure and family life as compared to parents of children with more substantial functional impairments. SCQ score and child educational environment were not correlated with family leisure involvement, family communication, family functioning (flexibility and cohesion), or caregiver depression.

Predictors of Family Functioning

In describing results of all PROCESS models, all coefficients are unstandardized. The notation a will be used to designate the coefficient for the pathway from the predictor variable to the first mediator; b will be used to designate the coefficient from the mediator to the outcome variable in simple mediation models; for serial mediation models, b₁ will be used to designate the coefficient from the first mediator to the second mediator and b₂ will be used to designate the coefficient from the second mediator to the outcome variable. For indirect (mediated) effects, the coefficients of all paths in the mediation model (ab for simple mediation or ab₁b₂ for serial mediation) will be used to designate the coefficient for indirect effect operating through the mediator(s); finally, c’ will be used to designate the coefficient for the direct path from the predictor variable to the outcome variable, when holding all mediators constant. See Figure 1 for a visualization of which paths correspond to each model coefficient. The same coefficient designations also appear in Tables 3 and 4.

Table 3.

Model Coefficients Predicting Family Cohesion and Family Flexibility from Core and Balance Leisure Involvement

Core Leisure Involvement	Family Cohesion			Family Flexibility
Model Coefficients (Predictors in Rows)	Core Leisure Satisfaction	FamilyCommunication	Family Cohesion	Core Leisure Satisfaction	FamilyCommunication	Family Flexibility
	Coefficient (SE)	Coefficient (SE)	Coefficient (SE)	Coefficient (SE)	Coefficient (SE)	Coefficient (SE)
Core Leisure Involvement	a=.0186 (.0033)*	a1=.0058 (.0028)*	c’=−.0113 (.0061)	a=.0186 (.0033)*	a1=.0058 (.0028)*	c’=−.0062 (.0027)*
Core Leisure Satisfaction		b1=.3026 (.0524)*	b3=1438 (.1264)		b1=.3026 (.0524)*	b3=.0126 (.0569)
Family Communication			b2=1.8158 (.2258)*			b2=.7298 (.1016)*
Direct and Indirect Effects	Coefficient	Bootstrap SE	95% CI	Coefficient	Bootstrap SE	95% CI
Direct Effect	c’=−.0113	.0061	−.0233, .0006	c’=−.0062	.0027	−.0116, −.0008*
Indirect Effect (Core Leisure Involvement→Core Leisure Satisfaction→Family Communication→Family Cohesion/Flexibility)
Typical	ab1b2=.0102	.0030	.0052, .0169*	ab1b2=.0041	.0012	.0021, .0069*
ASD	ab1b2=.0065	.0019	.0033, .0109*	ab1b2=.0026	.0008	.0013, .0044*
Index of Moderated Mediation	−.0038	.0018	−.0079, −.0008*	−.0015	.0006	−.0029, −.0004*
Balance Leisure Involvement	Family Cohesion			Family Flexibility
Model Coefficients (Predictors in Rows)	Balance Leisure Satisfaction	FamilyCommunication	Family Cohesion	Balance Leisure Satisfaction	FamilyCommunication	Family Flexibility
	Coefficient (SE)	Coefficient (SE)	Coefficient (SE)	Coefficient (SE)	Coefficient (SE)	Coefficient (SE)
Balance Leisure Involvement	a=.0285 (.0064)*	a1=.0032 (.0051)	c’=−.0557 (.0102)*	a=.0285 (.0064)*	a1=.0032 (.0051)	c’=−.0201 (.0047)*
Balance Leisure Satisfaction		b1=.2816 (.0497)*	b3=.5566 (.1068)*		b1=.2816 (.0497)*	b3=.1108 (.0491)*
Family Communication			b2=1.3466 (.1325)*			b2=.5489 (.0609)*
Direct and Indirect Effects	Coefficient	SE	95% CI	Coefficient	SE	95% CI
Direct Effect	c’=−.0557	.0102	−.0759, −.0356*	c’=−.0201	.0047	−.0293, −.0108*
Indirect Effect (Balance Leisure Involvement→Balance Leisure Satisfaction→Family Communication→Family Cohesion/Flexibility)
	ab1b2=.0108	.0039	.0053, .0204*	ab1b2=.0044	.0016	.0021, .0084*

^*95% Confidence Interval constructed using 5,000 bootstrap samples does not include zero

Table 4.

Model Coefficients Predicting Family Cohesion and Family Flexibility from Leisure Satisfaction

Core Leisure Satisfaction	Family Cohesion		Family Flexibility
Model Coefficients	FamilyCommunication	Family Cohesion	FamilyCommunication	Family Flexibility
	Coefficient (SE)	Coefficient (SE)	Coefficient (SE)	Coefficient (SE)
Core Leisure Satisfaction	a=.3403 (.0495)*	c’=0784 (.1221)	a=.3403 (.0495)*	c’=−.0231 (.0551)
Family Communication		b=1.7655 (.2254)*		b=.7024 (.1018)*
Direct and Indirect Effects	Coefficient (SE)	95% CI	Coefficient (SE)	95% CI
Direct Effect	c’=.0784 (.1221)	−.1622, .3191	c’=−.0231 (.0551)	−.1318, .0855
Indirect Effect (Core Leisure Satisfaction →Family Communication →Family Cohesion/Flexibility)
Typical	ab=.6008 (.1221)	.3796, .8614*	ab=.2390 (.0513)	.1480, .3451*
ASD	ab=.3793 (.0765)	.2385, .5387*	ab=.1523 (.0334)	.0903, .2216*
Index of Moderated Mediation	−.2215 (.0970)	−.4258, −.0415*	−.0867 (.0356)	−.1591, −.0230*
Balance Leisure Satisfaction	Family Cohesion		Family Flexibility
Model Coefficients	FamilyCommunication	Family Cohesion	FamilyCommunication	Family Flexibility
	Coefficient (SE)	Coefficient (SE)	Coefficient (SE)	Coefficient (SE)
Balance Leisure Satisfaction	a=.2903 (.0477)*	c’= 2659 (.1117)*	a=.2903 (.0477)*	c’=0086 (.0510)
Family Communication		b=1.6384 (.2220)*		b=.6819 (.1014)*
Direct and Indirect Effects	Coefficient (SE)	95% CI	Coefficient (SE)	95% CI
Direct Effect	c’= 2659 (.1117)	.0458, .4860*	c’=0086 (.0510)	−.0919, .1092
Indirect Effect (Balance Leisure Satisfaction →Family Communication →Family Cohesion/Flexibility)
Typical	ab=.4757 (.1058)	.2872, .6927*	ab=.1980 (.0432)	.1197, .2933*
ASD	ab=.3109 (.0688)	.1846, .4580*	ab=.1272 (.0292)	.0733, .1887*
Index of Moderated Mediation	−.1648 (.0819)	−.3372, −.0155*	−.0707 (.0301)	−.1339, −.0156*

^*95% Confidence Interval constructed using 5,000 bootstrap samples does not include zero

Four separate PROCESS models were used to examine the impact of (1) core leisure involvement on family cohesion, (2) core leisure involvement on family flexibility, (3) balance leisure involvement on family cohesion, and (4) balance leisure involvement on family flexibility. For each model, satisfaction with leisure and family communication were included as serial mediators, and ASD status was tested as a moderator of each serial mediation or direct path in the model. In the initial models examining the effect of core leisure involvement on family cohesion and flexibility, ASD status significantly moderated only one path in each model (between communication and family cohesion/flexibility). Therefore, all other moderation paths were dropped.

The final models supported indirect effects of core leisure involvement on both family cohesion and family flexibility, mediated through core leisure satisfaction and family communication. For both cohesion and flexibility, greater core leisure involvement was related to greater core leisure satisfaction (a=.0186), which was in turn related to better family communication (b₁=.3026); better family communication was then associated with more positive family cohesion and flexibility (Cohesion b₂=1.8158; Flexibility b₂=.7298). Confidence intervals constructed using 5,000 bootstrap samples for the index of moderated mediation were entirely below zero in both models (Cohesion=−.0079, −.0008; Flexibility=−.0029, −.0004), indicating that the mediation models differed between the ASD group and the TD group. While the indirect effects of core leisure involvement on cohesion and flexibility through core leisure satisfaction and family communication were positive in both the ASD and TD groups, this relationship was more pronounced in the TD group (Cohesion ab₁b₂=.0102; Flexibility ab₁b₂=.0041) as compared to the ASD group (Cohesion ab₁b₂=.0065; Flexibility ab₁b₂=.0026). When holding the mediators constant, there was no direct effect of core leisure involvement on family cohesion, but there was a small negative direct effect on family flexibility (c’=−.0062, 95% CI=−.0116, −.0008). See Table 3.

We next examined the indirect effect of balance leisure involvement on family cohesion and flexibility. The initial models indicated that none of the paths were significantly moderated by group (ASD v. TD), so all moderators were dropped from the final models. The final models indicated that balance leisure involvement had indirect effects on both family cohesion and family flexibility, mediated through balance leisure satisfaction and family communication (Cohesion ab₁b₂=.0108; Flexibility ab₁b₂=.0044). After accounting for indirect effects, balance leisure involvement had a small but significant negative direct effect on both family cohesion (c’=−.0557) and family flexibility (c’=−.0201). See Table 3.

Examining the coefficients for these models indicated that, for every one hour per week increase in leisure involvement, increases in family cohesion and flexibility that could be attributed to the mediation models ranged from .007 points to .031 points. For example (using the largest coefficient of .031), to move family cohesion score by 1 SD (1.83 points) through all indirect effects combined, balance family leisure involvement would have to increase by 59 hours per week (a clearly implausible value, as this amounts to more than 8 hours per day of additional leisure). Moreover, these small positive indirect effects were largely “canceled out” by small negative direct effects. This suggests that while these mediation models were statistically significant, the size of these effects is likely not clinically meaningful. Closer examination of the models suggested that these small effects were driven by weak relationships between leisure involvement and leisure satisfaction across all models. Therefore, to further probe these relationships, we dropped core/balance leisure involvement from the models, and examined each mediation model with core/balance leisure satisfaction as the focal predictor.

The initial models again suggested that only the pathway between family communication and family cohesion was significantly moderated (for both core and balance leisure satisfaction), so this moderation was considered in the final models. The final models indicated that core leisure satisfaction (a = .3403, b = 1.7655) and balance leisure satisfaction (a = .2903, b = 1.6384) were indirectly related to family cohesion, through family communication. Confidence intervals constructed with 5,000 bootstrap samples for the index of moderated mediation indicated that the indirect effects of leisure satisfaction on cohesion were conditional on group for both core (95% CI=−.4258, −.0415) and balance leisure satisfaction (95% CI=−.3372, −.0155), such that the relationship between leisure satisfaction and family cohesion through family communication was more strongly positive in the TD group than the ASD group. Results were similar when examining effects of core and balance leisure satisfaction on family flexibility, with significant indirect effects of both leisure satisfaction types on flexibility (Core a=.3403, b=.7024; Balance a=.2903, b=.6819), significantly moderated by group status such that the effect was more strongly positive for the TD group (Core ab=.2390; Balance ab=.1980) than the ASD group (Core ab=.1523; Balance ab=.1272). An examination of these coefficients reveals that, in the TD group, for every one point increase in leisure satisfaction, there was a resulting .60 point increase (core)/.48 point increase (balance) in family cohesion (~ ¼ to ⅓ of a standard deviation in this sample) that could be attributed to the mediation pathway through family communication. For families in the ASD group, a one point increase in leisure satisfaction was associated with a .38 point increase and a .31 point increase in balanced cohesion for core and balance satisfaction, respectively, that could be accounted for by this mediation model. Leisure satisfaction exerted a somewhat less strong influence on family flexibility across both groups (ASD and TD). There was also a significant positive direct effect of balance leisure satisfaction on family cohesion (c’=.2659, 95% CI=.0458, .4860). See Table 4.

Predictors of Satisfaction with Family Life.

Next, we examined the effect of group (ASD v. TD) on satisfaction with family life (SWFL), with total leisure involvement, total leisure satisfaction, family communication, and overall balanced family functioning entered as serial mediators. Caregiver depression was tested as a moderator of the paths between each mediator and SWFL. See Figure 2. In initial analyses, caregiver depression did not significantly moderate any of these paths; therefore, the proposed moderation analyses were trimmed from the model. The final analysis supported a serial mediation model in which having a child with ASD was associated with less leisure satisfaction, which in turn was related to poorer family communication and poorer overall family functioning. These variables were then associated with lower satisfaction with family life. However, group (ASD v. TD) was not significantly related to family leisure involvement, nor did it have any direct effect on satisfaction with family life, after accounting for the mediators. Examination of the coefficients indicated that for families in the ASD group, a .42 point decrease in satisfaction with family life (~½ a standard deviation in this sample, and approximately equal to the group difference in SWFL in this sample) can be attributed to the overall mediation model. See Table 5.

Table 5.

Model Coefficients Predicting Satisfaction with Family Life

Model coeffcients	Total Leisure Involvement	Total Leisure Satisfaction	FamilyFunctioning Communication	Total Family Functioning	Satisfaction with Family Life
	Coefficient (SE)	Coefficient (SE)	Coefficient (SE)	Coefficient (SE)	Coefficient (SE)
Group (ASD v. TD)	−3.4262 (2.6885)	−.5378 (.0976)*	−.1037 (.0913)	−.4430 (.1156)*	−.0019 (.0611)
Total Leisure Involvement		.0142 (.0024)*	.0047 (.0022)*	−.0136 (.0029)*	.0042 (.0015)*
Total Leisure Satisfaction			.2883 (.0578)*	.2449 (.0769)*	.1224 (.0402)*
Family Communication				.9619 (.0833)*	.8571 (.0537)*
Total Family Functioning					.1107 (.0339)*
Direct and Indirect Effects		Coefficient	SE	95% CI-Lower	95% CI-Upper
Total Direct Effect		−.0019	.0611	−.1223	.1184
Total Indirect Effect		−.4244*	.1034	−.6305	−.2227
Group→Total Leisure Satisfaction→Satisfaction with Family Life
		−.0659*	.0293	−.1357	−.0190
Group→Total Family Functioning→Satisfaction with Family Life
		−.0490*	.0211	−.0957	−.0134
Group→Total Leisure Satisfaction→Family Communication→Satisfaction with Family Life
		−.1329*	.0399	−.2189	−.0638
Group→Total Leisure Satisfaction→Total Family Functioning→Satisfaction with Family Life
		−.0146*	.0079	−.0336	−.0025
Group→Total Leisure Satisfaction→Family Communication→Total Family Functioning→Satisfaction with Family Life
		−.0165*	.0072	−.0328	−.0047

^*95% Confidence Interval constructed using 5,000 bootstrap samples does not include zero; All indirect effects were tested, but only significant indirect effects are included in table. In top half of table, predictor variables appear in rows, while predicted variables appear in columns.

Discussion

These findings suggest that many families living with ASD struggle to engage in fulfilling family leisure, and that these difficulties may relate to negative outcomes such as poorer family functioning and lower satisfaction with family life. Interestingly, few differences emerged in patterns of leisure involvement between families living with ASD and TD families. Caregivers of children with ASD reported equally frequent family participation in both core and balance leisure compared to TD caregivers. Moreover, they indicated that the child with ASD was usually included in family leisure (although there was a trend toward children with ASD being less frequently included than TD children, and children with more symptoms of ASD were less likely to be included that those with fewer symptoms). These findings contrast with those of Settle (2016), who found that families of young children with ASD engage in less frequent leisure compared to families of TD children. However, children in the Settle study were younger than the current sample (ages 2–7, as compared to 4–18 in the current study) and were currently in the process of receiving an ASD diagnosis; these sample differences could account for the differences in findings. On the surface, reports of equal leisure involvement across groups also appear to contrast with qualitative accounts from families of children with ASD reporting substantial challenges in leisure participation, particularly in non-routine (balance) leisure activities (DeGrace, 2004; Larson, 2006). However, observed patterns of leisure satisfaction are firmly in line with families’ descriptions of these challenges. Nearly a quarter (23.3%) of caregivers in the ASD group reported overall satisfaction with leisure below the mid-point on a 5-point scale, as compared to just 8.9% of caregivers of TD children. This pattern was equally pronounced across both core and balance activities, suggesting that a substantial minority of families living with ASD are dissatisfied with their leisure activities. Moreover, families of children with more substantial functional impairment (as measured by SCQ score and more restrictive school placement) reported lower satisfaction compared to families of less severely impacted children. Despite these challenges, families of children with ASD continue to attempt engagement in leisure, both at home and in their communities, making these activities a potentially fruitful setting for family-based intervention.

Caregivers of children with ASD also reported poorer family functioning and lower satisfaction with family life, compared to caregivers of TD children. This finding is in line with previous work suggesting less adaptive family functioning in families of children with ASD (Higgins et al., 2005), although it should be considered in light of findings that some family patterns typically labeled “dysfunctional” (in particular, enmeshment), may actually be adaptive for families living with ASD (Altiere & von Kluge, 2009). In addition, previous research regarding siblings and parents of children with ASD suggests that multiple elements such as demographic factors, child with ASD behavior problems, broader autism phenotype in family members, and coping style all influence stress, mental health, and psychosocial adjustment in parents and siblings (Ingersoll & Hambrick, 2011; Ingersoll, Meyer, & Becker, 2011; Meyer, Ingersoll, & Hambrick, 2011; Walton, 2016; Walton & Ingersoll, 2015). It is likely that these factors also influence family functioning, and they should be explored in more detail in future research.

Mediation analyses suggested that relationships between family leisure involvement and satisfaction, family functioning, and satisfaction with family life were largely similar in families with and without ASD. In both groups, satisfaction with leisure was significantly related to better family communication, which in turn was related to healthier family functioning (although in some cases this relationship was weaker for families living with ASD). A second mediation model indicated that having a child with ASD was related to poorer satisfaction with leisure, which was in turn related to poorer family communication and family functioning, and ultimately lower caregiver satisfaction with family life. Previous research has found that involvement in leisure may promote better family communication, which in turn leads to better family functioning (Smith et al., 2009). However, results of the current study suggest that leisure satisfaction (rather than leisure involvement) is associated with positive family communication (and in turn, better family functioning). This makes intuitive sense, as forcing oneself (or one’s family members) to struggle through unfulfilling family “leisure” could potentially lead to increased family resentment and poorer communication, rather than promoting healthy communication as intended. The finding that the relationship between family communication and family functioning is somewhat weaker for families living with ASD warrants further exploration. Several questions on the family communication scale are likely to tap into ASD-specific deficits in communication and theory of mind (e.g., understanding one another’s feelings, family members asking one another for what they want). Therefore, it is likely that low family communication scores may be driven, at least in part, by different factors in families with vs. without a child with ASD. It is possible that poor family communication that is driven by ASD-specific communication deficits may be less detrimental for family functioning, as compared to poor family communication that is driven by other types of compromised family interaction patterns, such as hesitance to communicate due to lack of trust or closeness.

These findings have several important clinical and research implications. First, leisure satisfaction was much more impactful in models of family functioning and satisfaction with family life, as compared to leisure involvement. This suggests that interventions aiming to support leisure participation for families of children with ASD should focus on quality, rather than quantity. Interventions that help families identify mutually pleasurable family activities, address behavioral difficulties that might arise during leisure, and increase overall satisfaction with leisure are likely to be more beneficial that interventions that simply aim to increase time spent in leisure. Leisure satisfaction (as well as satisfaction with family life) was particularly low in families of children with ASD who have more substantial functional impairment, suggesting that these families may be in particular need of support for engaging in satisfying family leisure. Second, while there were group differences in several family leisure and functioning variables, the overall relationships among these variables were generally similar across families with and without ASD. This suggests that existing models of family leisure involvement, such as the core and balance model, can be fruitfully applied to families with ASD. Similar to previous studies examining the core and balance model in non-ASD populations (Agate, Zabriskie, Agate, & Poff, 2009; Poff et al., 2010; Zabriskie & McCormick, 2001, 2003), this study found that leisure involvement and satisfaction were related to several other important family variables (i.e., communication, family functioning, satisfaction with family life), and that both dimensions of leisure activity (core and balance) were related to both measured dimensions of family functioning (flexibility and cohesion) (Zabriskie & McCormick, 2001). This suggests general rather than specific benefits for family leisure, and suggests that supporting families to engage in any leisure activity of their choosing may be more effective than pushing families to engage in any specific type of leisure with the expectation of activity-specific benefits.

Limitations and Future Directions

Findings from this study should be considered in light of several limitations. First and most importantly, all data in this study are correlational, and were collected from a single rater at a single time point, which limits any causal conclusions. While the mediation models tested in this study are theory-driven, it is possible that the observed relationships among these variables follow different causal pathways or are influenced by additional unmeasured variables. Further, data were collected from only one parent; future studies should consider perspectives of other family members. Second, the sample in this study was relatively small and homogenous; moreover, ASD status was not independently verified aside from use of the SCQ (which is a screening, rather that diagnostic instrument), and limited information about child variables such as IQ and behavioral/mental health comorbidities was collected. Future work should examine patterns of family leisure and family functioning in larger, more diverse, and more well-characterized samples to increase generalizability of these results, and identify which families may be in particular need of supports for leisure participation. In particular, information about child IQ, behavioral/mental health comorbidities, and timing of measurement in relation to ASD diagnosis (e.g., examining functioning before, during, and after the diagnostic process) may reveal important patterns. Third, this study compared functioning across families with the assumption that similar family functioning patterns would be “healthy” across families with and without a child with ASD. Future studies must test this assumption to determine which family functioning patterns may be most adaptive in families facing different types of challenges.

Conclusions

This study found that, although families living with ASD spent just as much time engaging in leisure as TD families, caregivers of children with ASD reported less satisfaction with leisure, poorer family functioning, and lower satisfaction with family life. Patterns of lower leisure satisfaction and satisfaction with family life were particularly pronounced in families of children with ASD who had more severe functional impairments. Mediation models suggested that lower leisure satisfaction was associated with poorer family communication, which is in turn was related to less optimal family flexibility and cohesion and lower satisfaction with family life. Interventions aiming to improve leisure experiences for families living with ASD should focus on leisure quality rather than quantity in order to most effectively influence family functioning and satisfaction.