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. Author manuscript; available in PMC: 2025 Jun 13.
Published in final edited form as: Res Dev Disabil. 2025 Mar 27;161:104999. doi: 10.1016/j.ridd.2025.104999

Quality of life in caregivers of toddlers with autism features

Sarah R Edmunds a,b,*, Daina M Tagavi b,c, Colleen M Harker b,d, Trent DesChamps b, Wendy L Stone b
PMCID: PMC12164539  NIHMSID: NIHMS2076096  PMID: 40154040

Abstract

Understanding factors that contribute to the quality of life (QoL) of primary caregivers of young autistic children can help researchers and clinicians provide high-quality support to caregivers and families. This study examined whether family demographic factors, parenting stress, and caregivers’ perceptions of family-centered healthcare experiences uniquely predict caregivers’ QoL. Participants were caregivers of toddlers with: features of autism (n = 119), other developmental delays (n = 101), and no developmental concerns (n = 264). We hypothesized that higher levels of perceived family-centered care would moderate (ameliorate) the relation between parenting stress and QoL. Higher levels of perceived family-centered care were associated with higher QoL for all groups but did not moderate the negative relation between parenting stress and QoL. Negative effects of parenting stress on QoL were stronger for caregivers of children with autism features compared to other groups. Future research is needed to determine how to provide additional support to caregivers with lower QoL, particularly caregivers who are experiencing income- or parenting-related stress and lower levels of family-centered care. Caregiver QoL is especially important to support across service settings (e.g., primary care, early intervention) during the birth-to-three period, when the process of accessing autism services can be challenging for caregivers.

Keywords: Quality of life, Caregiver, Parenting stress, Family-centered care, Autism

1. Quality of life in caregivers of toddlers with autism features

For caregivers of autistic children, increased levels of caregiver stress, anxiety, depression, poor physical health, and reduced relationship satisfaction (e.g., Cohrs & Leslie, 2017; Ku and Ghim, 2024; Lins-Silva et al., 2024) can make it difficult for both caregivers and their children to engage in intervention supports and effectively cope, problem-solve, and be resilient when facing the myriad barriers to navigating the world as a neurodivergent individual (Black et al., 2024). Many studies examining caregiving in the context of autism have focused on these more negative outcomes; however, examining and promoting overall caregiver quality of life (QoL) may present a more comprehensive and multidimensional picture of caregivers of autistic children.

2. Quality of life (QoL)

Quality of life (QoL) is a broad multidimensional construct defined by the World Health Organization (WHO) as “an individual’s perception about their position in life in the context of the culture and value system they live in and in relation to their objectives, expectations, standards, and concerns” (WHO 1998; p. 11). QoL is recognized as a critical benchmark for evaluating the quality and outcome of healthcare (Moons et al., 2006) and education (Dunst, 2002), such that researchers and health care providers now consider impact on QoL and appropriate measurement of QoL when evaluating the effectiveness of new interventions, rather than only measuring symptom reduction (e.g., Kaplan & Hays, 2022; Oliveira et al., 2016). QoL also has important public health implications; low QoL is associated with high hospitalization rates (e.g., Mathews & May, 2007), lower mortality rates (Phyo et al., 2020), high health care expenditures (Campbell et al., 2017; Himmelstein et al., 2020), and greater mental health challenges. Given this, research is focused on identifying factors that influence QoL to support QoL in high-need clinical populations.

2.1. Caregiver QoL in the context of neurodevelopmental disorders

Findings indicate that caregivers of children with special healthcare needs report lower QoL than caregivers of neurotypical children and adults (e.g., Arora et al., 2020; Dükert et al., 2023; Klassen et al., 2008; Warreman et al., 2023). However, these differences in caregiver QoL are not entirely due to child characteristics themselves. Rather, in these studies, demographic (e.g., low income), psychological (e.g., high levels of parenting stress, maladaptive coping styles), and system-level (e.g., low levels of family-centered care) factors have been identified as determinants of low QoL even when controlling for child symptom severity (e.g., Lowoko & Soares, 2003; Sulaimani et al., 2023).

We know little about the QoL of caregivers of young autistic children (i.e., < 5 years old). As autistic children elicit different caregiving demands across their lifespan, it is important to understand how QoL may be uniquely impacted for caregivers of very young autistic children, as opposed to caregivers of older autistic individuals (Alnahdi, 2024; Russa et al., 2015; Sonido et al., 2022). There is also limited understanding about QoL in caregivers of young children with autism features, but no formal diagnosis. This dearth of research is concerning, given that this period is often a time of great stress for families as they navigate a new service delivery system and tolerate uncertainty about their child’s characteristics (O’Neill & O’Donnell, 2024). To date, only one study has examined QoL in a sample of caregivers of individuals with possible autism, and found that caregivers of adolescents and young adults with autism features but no diagnosis reported lower QoL than caregivers of adolescents and young adults both with and without an autism diagnosis (McKenachie et al., 2017), suggesting that the uncertainty of the presence of autism characteristics without diagnostic confirmation may be particularly frustrating for caregivers.

2.2. Predictors of QoL

Caregivers of autistic children face unique demands at many socio-ecological levels (individual, family, and within the healthcare system). Socio-ecological models to explain the impacts at varied environmental and personal levels on complex psychological outcomes such as quality of life are rarely used in the neurodevelopmental literature (e.g., Dai et al., 2024) but are common when exploring predictors of physical and psychological well-being in neurotypical adults (e.g., Aruta et al., 2021). These demands may differentially impact quality of life (QoL) for caregivers of toddlers with autism features, compared to caregivers of children with other developmental concerns or caregivers of children with no current concerns (Russa et al., 2015). In addition, caregiver QoL may change over time and may be especially impacted during early stages of the diagnostic journey (Dai et al., 2024).

2.2.1. Demographic predictors of QoL

Child age, caregiver employment status, and caregiver marital status have not been linked to caregiver QoL in the context of caring for children with disabilities (Ji et al., 2014; Siah & Tan, 2016), while income and number of children in the home have been inconsistently linked to the various domains of QoL (Ji et al., 2014; Johnson et al., 2011). One study found that increased caregiver education predicted improved QoL (Sulaimani et al., 2023), and another study found that living conditions (e.g., apartment vs. other dwellings) also impacted caregiver QoL (Asahar et al., 2021).

2.2.2. Type of caregiver concern as a predictor of QoL

Many researchers have used child health or disability status as a direct indicator of QoL, when in actuality, it is a potential (but not guaranteed) predictor of QoL (Moons, 2004). Historically, there has been a poor distinction between indicators of QoL and predictors of QoL (Moons et al., 2006). By definition, indicators are representations of a phenomenon, while predictors are contributing factors that may influence a phenomenon. Indeed, empirical evidence also suggests this. For children with autism and other neurodevelopmental disorders, there is mixed evidence as to whether having a child with a disability or neurodevelopmental difference, or the severity of their impairment, is predictive of their caregivers’ QoL. One recent study found that both the presence of a child with a disability and the severity of that disability predicted reduced QoL for caregivers in Saudi Arabia (Sulaimani et al., 2023), while other studies of caregivers of autistic children found that neither child diagnostic status nor degree of impairment impacted their caregivers’ QoL (Cardoso et al., 2023; ten Hoopen et al., 2022). As such, caregivers’ concerns about their child’s development (no matter the type of concern) should be conceptualized as a predictors, rather than an indicator, of their QoL.

2.2.3. Psychological predictors of QoL

Psychological factors, such as stress and depression, often emerge as stronger predictors of QoL than demographic factors (e.g., Simon et al., 2008; Hoopen et al., (2022)), which is encouraging given that psychological variables are often more malleable or responsive to intervention than demographic variables such as income or systemic variables such as service access. Increased parenting self-efficacy has been found to predict greater caregiver QoL for caregivers of autistic children (Dai et al., 2024). With regard to resilience, increased opportunities for leisure activity and personal goals predicted increased QoL in caregivers of autistic children (Davy et al., 2024).

Although parenting stress is one of the most widely examined variables in caregivers of autistic children, its association with QoL is less studied. Of the studies that have been conducted, results indicate that parenting stress is negatively associated with overall QoL (DesChamps et al., 2019; Eapen et al., 2014; McKechanie et al., 2017; ten Hoopen et al., 2022), and that parenting stress is higher in caregivers of children with autism or autism features compared to caregivers of children with other developmental concerns or no concerns (Deschamps et al., 2019). These findings are consistent with studies examining QoL in other caregiver populations, including caregivers of children with other developmental concerns (e.g., Wheeler et al., 2008).

2.2.4. System-level predictors of QoL

Additionally, healthcare system-level factors related to the physical environment (e.g., distance from health services and social environment (e.g., healthcare satisfaction) are increasingly being examined as potential predictors of QoL in both children and adults (Jia et al., 2009; Simon et al., 2008). Understanding whether healthcare system characteristics can improve caregiver QoL, above and beyond demographic or psychological characteristics, is an exciting area for future research.

Low social support has been linked with low QoL (Johnson et al., 2011; Ran et al., 2023; Dai, et al., 2024), and receiving training or education has been linked with higher QoL (Asahar et al., 2021). However, there is a notable lack of research about the influence of one of the most important social relationships in individuals with high healthcare needs – their medical providers. The term ‘family--centered care’ describes a philosophy in which caregivers are recognized as experts on their children’s needs and are included in decision-making processes in partnership with their child’s healthcare providers (Dunst, 2002; King et al., 2004). High levels of family-centered care are associated with important child and family outcomes for children with and without special healthcare needs, such as lower parenting stress (King et al., 1999), higher healthcare satisfaction (Carbone et al., 2013), increased caregiver well-being (King et al., 1999), and improved child heath (McAllister et al., 2009). Having a supportive experience at the system level (e.g., perceiving the care a primary care provider (PCP) provides to be family-centered), may ameliorate individual- or family-level stressors that caregivers experience.

Family-centered care is recognized as an important component of service provision for families of autistic children (Gabovitch & Curtin, 2009), and relates to both caregivers’ parenting stress and QoL (Zeng et al., 2020). Caregivers of autistic children report lower perceived levels of family-centered care compared to caregivers of children with other special health care needs (Kogan et al., 2008). Additionally, though research indicates that increased family-centered care is associated with decreased parenting stress (e.g., Hung et al., 2015; King et al., 2004) and may therefore be associated with increased caregiver QoL, family-centered care may in reality moderate the relation between parenting stress and QoL, especially for caregivers of children with autism features. Improving family-centered care could be an effective point of intervention for primary care providers (PCPs) (King et al., 1999).

2.3. Current study objectives

The goals of this study are to:

  1. Examine the extent to which three levels of predictors predict caregiver QoL: demographic predictors (i.e., child age, family income, caregiver employment status, and number of children residing in the home; caregiver predictors (i.e., parenting-related stress); and system-level predictors (i.e., perceived family-centered care). We hypothesized that parenting stress will be a particularly strong predictor of QoL, given research evidence that psychological variables are stronger predictors of QoL in multivariate models compared to demographic or biological variables (Simon et al., 2008).

  2. Examine the extent to which perceived family-centered care moderates (ameliorates) the relation between parenting stress and QoL. We hypothesized that caregivers’ reports of family-centered care will moderate the relation between parenting stress and caregiver QoL, such that for caregivers who experience higher (compared to lower) degrees of family-centered care, the negative relation between high parenting stress and low QoL will be weaker. It is further hypothesized that this moderation (i.e., the ameliorating effect of perceived family-centered care) will be stronger for caregivers of children with autism features (AF), relative to caregivers of children with developmental delays (DD) or no concerns (NC).

3. Method

3.1. Participants

Participants were drawn from a larger NIH-funded pragmatic trial that examined the implementation of a model to increase autism-specific screening and early supports in nine early intervention (EI) agencies and ten primary care provider (PCP) practices across four geographically and ethnically diverse counties (see (Ibañez et al., 2019) for full study protocol; (Deschamps et al., 2019)). Caregivers of children with autism features and other possible developmental delay were recruited from both PCP practices and EI agencies, while children with no developmental concerns were recruited from PCP practices only. PCPs and EI providers assisted with recruitment for the larger study. Research team members then completed phone screenings with caregivers in order to determine eligibility. Families recruited through their child’s PCP were eligible for the study if their child was between 16 and 20 months old at the time of enrollment. Families recruited through their child’s EI provider were eligible if their child was between 16 and 36 months old at the time of enrollment. Children with severe medical conditions were excluded from the study.

The present study included a subsample of participants (n = 484) from the larger study, collected from 2016 to 2019. Children were classified into one of three groups based on information that caregivers provided during the eligibility screening process for the larger study: Autism Features (AF; n = 119), Developmental Delays (DD; n = 101), or No Concerns (NC; n = 264). Children were classified in the AF group for one of three reasons: (1) their caregiver indicated that they had an existing diagnosis of ASD; (2) they screened at-risk on an autism screening tool in the past, their caregiver explicitly endorsed suspecting autism, and/or their caregiver reported that a provider or another family member suspected autism; or (3) their caregiver reported concerns about how their child interacted with adults and/or peers and endorsed a concern about language or communication, unusual toy play, unusual body movements, and/or sensory issues. Children with autism features (n = 99) were combined with the children with confirmed autism diagnoses (n = 20), given the long waits for diagnostic assessments. Children were classified in the DD group if their caregiver expressed concerns about general development (e.g., delayed language or motor development), but did not endorse any of the aforementioned criteria for the AF group. Caregivers of children in the NC group reported having no concerns about their child’s development during eligibility screening.

Table 1 provides the demographic characteristics for caregivers and children in the three groups. One-way ANOVAs were used to examine group differences in caregiver age, child age, number of children residing in the home, family income, and caregiver employment status. Chi-square independence tests were used to examine group differences in child sex, caregiver race (collapsed into White vs. Non-White), and caregiver ethnicity (Hispanic vs. Non-Hispanic). Children in the NC group were significantly younger than children in the AF (p < .001) and the DD groups (p < .001); children in the DD group were significantly younger than children in the AF group (p < .001). Caregivers of children in the AF group reported significantly lower yearly family income than caregivers of children in the DD group and the NC group, X2 (16, 488) = 62.16, p < .001. Caregivers of children in the AF group were less likely to be employed than caregivers of children in the DD group (p = .02) and caregivers of children in the NC group, (p = .04). The relation between child natal sex and concern group was significant, X2 (2, 484) = 17.04, p < .001; there was a greater proportion of males to females in each of the concerns groups (AF and DD) compared to the No Concerns (NC) group. Similarly, there was a higher proportion of Hispanic/Latinx caregivers in the AF and DD groups compared to the NC group, X2 (2, 484) = 31.70, p < .001. There was a higher proportion of multiracial caregivers in the AF group compared to the DD and NC groups, X2 (12, 481) = 24.22, p < .02. There were no group differences in the number of children in the home (Table 2)

Table 1.

Demographic Characteristics of the Sample.

Variable Autism Features Developmental Delay No Concerns p
n = 119 n = 101 n = 264
Child age M (SD) 26 (5.5) 21.7 (4.3) 19.9 (1.2) < .001υ
Number of children residing in the home M (SD) 2.6 (1.6) 2.1 (1) 2.1 (1) .12
Child sex # (%) < .001t
  Male 92 (61) 71 (61) 129 (45)
  Female 51 (34) 39 (33) 148 (52)
Caregiver race # (%) .02∧
  American Indian or Alaskan Native 3 (2) 1 (1) 1 (.4)
  Native Hawaiian or Other Pacific Islander 0 (0) 1 (1) 1 (.4)
  Asian 1 (1) 0 (0) 2 (1)
  Black or African American 0 (0) 0 (0) 0 (0)
  White 96 (75) 88 (83) 244 (92)
  Other 5 (4) 3 (3) 7 (3)
  More than One Race 12 (10) 5 (5) 6 (2)
  Unknown 3 (2) 2 (2) 1 (1)
Caregiver ethnicity # (%) < .001t
  Hispanic/Latine 45 (30) 20 (17) 28 (10)
  Non-Hispanic/Latine 96 (63) 87 (74) 243 (85)
  Unknown 1 (1) 2 (2) 1 (.3)
Family income # (%) < .001υ
  $20,000 or less 39 (26) 20 (17) 27 (9)
  $20,001 – 40,000 39 (26) 25 (21) 39 (14)
  $40,001 – 60,000 20 (13) 10 (9) 53 (19)
  $60,001 – 80,000 11 (7) 17 (15) 38 (13)
  $80,001 – 100,000 9 (6) 13 (11) 39 (14)
  $100,001 or greater 7 (5) 23 (19) 58 (20)
Caregiver employment status # (%) .01∧
  Unemployed 86 (57) 53 (45) 130 (45)
  Part-time 22 (15) 12 (10) 54 (19)
  Full-time 33 (22) 45 (39) 89 (31)
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Note.

∧

Autism Features group significantly different than Developmental Delay and No Concerns groups.

t

Autism Features group significantly different than No Concerns group.

υ

Autism Features group significantly different than Developmental Delay group.

Table 2.

Group differences on psychosocial measures.

M (SD)
Variable Cronbach’s alpha Total Sample
n = 494		 Autism Features
n = 119		 Develop-mental Delay
n = 101		 No Concerns
n = 264		 F p ηp2
PSI-SF Total Scorea .96 67.21 (24.95) 89.42 (25.43) 64.72 (21.25) 57.41 (18.55) 72.40 < .001 .24
MPOC–20 Total Scorea .97 5.55 (1.18) 5.56 (1.23) 5.52 (1.16) 5.56 (1.17) .20 .82 .001
Overall QoLa .89 3.65 (0.54) 3.39 (0.64) 3.64 (0.48) 3.65 (0.54) 14.18 < .001 .06
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Note. PSI-SF = Parenting Stress Index- Short Form; MPOC-20 = Measure of Processes of Care;

a

Controlling for income

3.2. Procedure

The present study is based on select questionnaires that caregivers completed at their time of entry into the study. Caregivers completed all questionnaires online via REDCap (Research Electronic Data Capture). Paper versions were available to families upon request.

3.3. Measures

3.3.1. Predictors of QoL

Demographic predictors.

Demographic predictors were measured using the Family Demographic Information Form, which is completed by caregivers. This form assesses demographic characteristics including child age, family income, number of children residing in the home, and caregiver employment status.

Psychological predictor: parenting stress.

The psychological predictor was operationalized as parenting-related stress, which was measured using the Parenting Stress Index-Short Form (PSI-SF; Abidin, 1990). The PSI-SF is a self-report measure designed to assess the amount of stress that caregivers of children between one month to twelve years of age experience in their caregiving role. PSI-SF items are rated on a five-point Likert scale ranging from “Strongly Disagree” (1) to “Strongly Agree” (5). Items in each subscale are summed to produce three subscale scores that range from 12 to 60. Scores for each of the three subscales (parent distress, difficult child, and parent-child dysfunctional interaction) were summed to obtain a total parenting stress score ranging from 36 to 180, with higher scores indicating higher levels of parenting stress. Prior work suggests that the PSI-SF has an average Cronbach’s alpha of 0.85 (Abidin, 1995).

System-level predictor: perceived family-centered care.

The healthcare system-level predictor was operationalized as family-centered care and measured using the Measure of Processes of Care (MPOC-20; King et al., 2004). The MPOC-20 is a 20-item self-report measure designed to evaluate caregiver perceptions of the degree of family-centered care delivered by their child’s primary health care providers (e.g., doctors, nurses). The MPOC-20 was specifically designed to measure perceived family-centered care for children with special health care needs. MPOC-20 items are rated on a seven-point scale ranging from “Never” (1) to “To a Great Extent” (7) (Cronbach’s alpha =.77 – .88). In the current study, an overall MPOC-20 score was calculated by averaging the mean score across all items in accord with prior work (Carbone et al., 2013).

Outcome measure: quality of life (QoL).

QoL was measured using the World Health Organization’s Quality of Life Questionnaire (WHOQOL-BREF; WHO, 1996). The WHOQOL-BREF is a 26-item caregiver report measure that has been validated cross-culturally in an international field trial, and has demonstrated adequate internal consistency in the U.S. in a sample of healthy adults and adults with physical and mental health issues (Cronbach’s α =.69 – .87; Skevington et al., 2004).

The WHOQOL-BREF comprises four domains: Environmental (8 items), Physical (7 items), Psychological (6 items), and Social (3 items). Items assess general living conditions; health services; access to transportation; satisfaction with physical capacities, satisfaction with mental health, and satisfaction with social connectedness, such as personal relationships, friendships, and sex. WHOQOL-BREF items are rated on a five-point scale ranging from “Very Dissatisfied” (1) to “Very Satisfied” (5). The mean score of items within each domain was used to calculate each domain score. Higher values indicate higher levels of quality of life. In the current study, the four WHOQOL-BREF domains were averaged together to examine overall QoL.

3.4. Analytic approach

3.4.1. Preliminary analyses: differences by caregiver group

Group differences on all predictors of interest were examined using ANCOVA. Between-groups ANCOVAs were conducted to investigate the effect of group status on caregiver parenting stress, perceived family-centered care, and QoL, controlling for income. Post-hoc analyses were performed with Bonferroni corrections.

3.4.2. Primary analyses

To examine the relative influence of family demographic, caregiver psychological, and healthcare system-level predictors on caregiver QoL, multiple linear regression models were fitted using a hierarchical, theory-driven, stepwise process (Zhang, 2016; Table 3). First, a block of four demographic variables was entered (child age, family income, caregiver employment status, and the number of children residing in the home). Next, the caregiver psychological variable (parenting stress) and an interaction term (group* stress) were entered, controlling for all variables from the second stage. Then, the healthcare system variable (perceived family-centered care) and an interaction term (group* perceived family centered care) were entered, controlling for all variables from the third model. Group status was then entered, after controlling for all variables from previous models. Lastly, two interaction terms (stress*family-centered care; group*stress*family-centered care) were entered to examine whether perceived family-centered care moderated the relation between parenting stress and QoL and whether it differed by group (Table 3; Table 5). The final model is also presented in Table 4.

Table 3.

Correlation matrix for continuous variables of interest by caregiver concerns group.

Perceived Family-Centered Care Parenting Stress Quality of Life (QoL)
Perceived Family-Centered Care:
  Overall - − .225 * ** .372 * **
  Autism Features (AF) - − .228 * .304 * **
  Developmental Delays (DD) - − .221 * .372 * **
  No Concerns (NC) - − .225 * ** .372 * **
Parenting Stress
  Overall - − .563 * **
  AF - − .699 * **
  DD - − .556 * **
  NC - − .563 * **
Quality of Life
  Overall -
  AF -
  DD -
  NC -
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Notes:

*

p < .05;

* *

p < .01;

* **

p < .001

Table 5.

Final hierarchical regression model for overall quality of life (Model 6).

Predictors B (SE) β t (p)
Intercept 3.63 (0.07) 50.97 (<.001)
Step 1: Family Demographic
  Caregiver Employment Status − 0.04 (0.02) − .06 − 1.87 (.06)
  Household Income 0.06 (0.01) .23 6.34 (<.001) *
  Number of Children in the Household − 0.01 (0.02) − .02 − 0.54 (.59)
  Age of Primary Child (in Months) 0.02 (0.03) .03 0.77 (.44)
Step 2: Caregiver Psychological
  Parenting Stress − .44 (.04) − .80 − 11.87 (<.001)* *
Step 3: Health Care System
  Perceived Family-Centered Care .12 (.02) .22 6.55 (<.001)* *
Step 4: Parenting Stress by Family-Centered Care .02 (.02) .05 1.36 (.18)
Step 5: Groupψ
  DD − .16 (.07) − .12 − 2.32 (.02)*
  NC − .14 (.07) − .12 − 1.97 (.049)*
Step 6: Group by Parenting Stress
  DD*Parenting Stress .22 (.06) .16 3.79 (<.001)* *
  NC*Parenting Stress .14 (.05) .15 2.75 (.006)*
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*

p < .05;

* *

p < .001.

ψ

Reference group is the Autism Features Group. DD = Developmental Delays group; NC = No Concerns Group.

Table 4.

Model Summary Statistics for Hierarchical Models.

Model R Adjusted R2 R2 Change F Change (p)
1 (Family Demographics) .37 .13 .13 17.11 < .001
2 (Caregiver Psychological) .69 .47 .34 287.40 < .001
3 (Health Care System) .73 .52 .05 45.10 < .001
4 (Parenting Stress by Perceived Family Centered Care) .73 .52 .002 2.10 .15
5 (Group) .73 .54 .001 0.52 .56
6 (Group by Parenting Stress) (final model) .74 .54 .02 7.28 < .001
7 (Group by Family Centered Care) .74 .54 .003 1.63 .20
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Caregiver group was dummy coded as two variables (i.e., NC as compared to an AF reference group [AF = 0; NC = 1], and DD as compared to the AF reference group [AF = 0; DD = 1]), which produced two different regression coefficients for each interaction. An interaction involving group was determined to be significant if there was significant R2 change between a model without the two interaction terms and a model that included the two interaction terms.

4. Results

4.1. Preliminary analyses: differences by caregiver group

All analyses controlled for caregiver income, the only demographic predictor with significant differences by caregiver group. There were significant group differences in parenting stress, F(2, 457) = 72.40, p < .001, such that caregivers of children in the Autism Features (AF) group reported significantly higher levels of parenting stress than caregivers in the Developmental Delay (DD), marginal mean difference (Δ_mm) = 24.05, p < .001, and the No Concerns (NC) groups, Δ_mm = 30.60, p < .001 (Table 2). Further, in this larger sample, we found that caregivers of children with DD reported higher parenting stress than those in the NC groups, Δ_mm = 6.54, p = .029. Caregiver ratings of family-centered care did not significantly differ between groups. With regard to overall quality of life (QoL), there was a significant main effect of group, F(2, 455) = 14.18, p < .001, such that caregivers of children with AF reported lower QoL than caregivers of children with DD, Δ_mm = −.21, p = .01, and those with NC, Δ_mm = −.32, p < .001. There was no significant difference in QoL between caregivers of children with developmental and no concerns, Δ_mm = −.12, p = .16. Table 2 also presents Cronbach’s alpha for each measure within our sample. Bivariate correlations between continuous variables of interest are reported in Table 3 (Table 5).

4.2. Primary analysis: predictors of quality of life (QoL)

The results of the hierarchical model fitting process are presented in Table 4 and Table 6. Assumptions of multiple linear regression for all models were met (a linear relationship between the independent variables and the dependent variable; no perfect multicollinearity; multivariate normality; and homoscedasticity) by assessing the distribution of the residuals from each model and examining multicollinearity statistics (e.g., variance inflation factor) for each predictor. Despite highly significant correlations (Table 3), effect sizes were moderate, and predictors of QoL all had VIFs under 5 (Shrestha, 2020). The addition of parenting stress (model 2), family-centered care (model 3), and the group by parenting stress interaction (Model 6) all resulted in a better fitting model of QoL (ΔR2, Table 4). The final model (Model 6) is presented in Table 5 and described in detail below.

Table 6.

Hierarchical model-building (All Models).

Model (β)
1 2 3 4 5 6 7
Predictors
Model 1: Family Demographic
  Caregiver Employment Status − .04 − .07 − .07 − .07 − .07 − .06 − .06
  Household Income .30 * * .19 * * .20 * * .21 * * .21 * * .23 * * .23 * *
  Number of Children in the Household − .02 − .03 − .03 − .04 − .03 − .02 − .02
  Age of Primary Child (in Months) − .16 * * .07 .04 .05 .03 .03 .04
  Adjusted R2 .13
  F 17.11
Model 2: Caregiver Psychological
  Parenting stress − .65 * * − .59 * * − .59 * * − .61 * * − .80 * * − .84 * *
  Adjusted R2 .47
  ΔR2 .34
  ΔF 287.4 * *
Model 3: Health Care System Perceived Family-centered care .23 * * .22 * * .22 * * .22 * * .09
  Adjusted R2 .52
  ΔR2 .05
  ΔF 45.10 * *
Model 4: Parenting Stress by Family-Centered Care
  Parenting stress*Family-centered care .05 .05 .05 .09 *
  Adjusted R2 .52
  ΔR2 .002
  ΔF 2.10
Model 5: Group ψ
  DD − .05 − .12 * − .13 *
NC − .04 − .12 * − .14 *
  Adjusted R2 .52
  ΔR2 .001
  ΔF 0.52
Model 6: Group by Parenting Stress
  DD*Parenting stress .16 * * .18 * *
  NC*Parenting stress .15 * * .17 * *
  Adjusted R2 .54
  ΔR2 .02
  ΔF 7.73 * *
Model 7: Group by Family-Centered Care (FFC) .07
  DD*FCC .13
  NC*FCC
  Adjusted R2 .54
  ΔR2 .003
  ΔF 1.63
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Note.

*

< .05

* *

<.01. FCC = perceived family-centered care.

ψ

Reference group is the Autism Features (AF) Group. DD = Developmental Delays group; NC = No Concerns group. Model 6 was determined to be the final model, and coefficients for Model 6 are bolded. See Fig. 1 for a graphical depiction of Model 6. See Fig. 2 for a graphical depiction of Model 3/7.

4.2.1. Family demographics

Having a higher annual household income predicted higher caregiver QoL regardless of caregiver concerns group, β = .23, p < .001 (Model 1, Table 6), an effect which held throughout all subsequent models. While child age was a significant predictor of QoL in a model with only demographic predictors added (Model 1, Table 6), it became a non-significant predictor in the final model, β = .03, p = .44 (Model 6, Table 5). Employment status and number of children in the household were not significantly related to caregiver QoL in any model (Tables 5, 6).

4.2.2. Parenting stress

Lower levels of parenting stress predicted higher QoL, β = −.59, p < .001 (Model 2, Table 6). The addition of parenting stress to the model with family demographics predictors only (Model 2 vs. 3) significantly improved model fit, ΔR2 = .34 (Table 4). In fact, the addition of parenting stress produced the greatest change in variance explained of all the models (Table 4). Further, there was significant moderation by concerns group, ΔR2 for Model 6 = .02, p < .001, such that the negative effect of parenting stress on QoL was significantly stronger for caregivers of children in the AF group, β = −.80, than for caregivers of children in the DD group, β = .16, or NC group, β = .15 (Table 5; Fig. 1). Computing estimated slopes (i.e., r values) for the relation between parenting stress on QoL for the DD and NC groups by adding their beta values to the reference group beta, we see that the DD (r = −.64), and NC (r = −.65) slopes are less negative than the AF slope (Table 5, Fig. 1).

Fig. 1.

Fig. 1.

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Parenting stress predicts lower quality of life more strongly for caregivers of children with Autism features than other groups.

4.2.3. Family-centered care

Higher levels of perceived family-centered care predicted greater caregiver QoL across all groups, β = .23, p < .001 (Model 3, Table 6). The addition of perceived family-centered care to a model with family demographics and parenting stress as predictors of QoL (Model 3) significantly improved model fit, ΔR2 = .05 (Table 4).

4.2.4. Does family-centered care attenuate the relation between parenting stress and quality of life (QoL)?

The negative relation between parenting stress and quality of life was not ameliorated by receiving better what caregivers perceived to be better family-centered care, β = .05, p = .15 (Model 4, Table 5), and the addition of this moderation term did not increase model fit, ΔR2 = .002 (Table 4). Better perceived family-centered care therefore predicts greater caregiver QoL equally strongly for all concerns groups (Fig. 2).

Fig. 2.

Fig. 2.

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Perceived family centered care predicts greater quality of life equally well for all groups.

5. Discussion

The purpose of this study was to understand the unique topography of quality of life (QoL) in caregivers of very young children with autism features, compared to children with other developmental delays or no concerns. Previous research has focused primarily on QoL in caregivers of school-aged autistic children and/or adolescents. This study is the first to include caregivers of young children with autism features (before potential diagnosis), providing insight into how autism features may impact caregiver QoL prior to diagnostic confirmation— a period of uncertainty for many families as they navigate the service delivery system to seek diagnostic clarity (Crane et al., 2016; O’Neill & O’Donnell, 2024). While previous research has examined differences in QoL between caregivers of autistic children and other caregiver groups (e.g., Arora et al., 2020; Dükert et al., 2023; Klassen et al., 2008; Warreman et al., 2023), this is one of the first to utilize multivariate analyses when considering multiple, nested socio-ecological levels of predictors of QoL, which consider the impact of family demographic, caregiver psychological, and healthcare system-level factors on families, individually and as a whole.

For all caregivers, those who had higher income, lower parenting stress, and more experiences of family-centered care with their primary care provider (PCP) reported a higher quality of life. When examining interactions between these predictors (controlling for income; no other demographic predictors were significant), as well as differences by type of caregivers’ concerns, a more nuanced picture emerges. For caregivers, greater parenting stress predicts lower quality of life more strongly for caregivers of children with autism features (AF) than for caregivers of children with developmental delays (DD) or no concerns (NC) (Fig. 1). This effect was not ameliorated by their reported levels of perceived family-centered care. Instead, higher subjective levels of family-centered care predicted higher quality of life equally well for all caregiver groups (Fig. 2).

These results are consistent with previous research for caregivers of autistic children (ten Eapen et al., 2014; Hoopen et al., 2022; Johnson et al., 2011; Lee et al., 2009, Simon et. al, 2008) in finding that parenting stress (i.e., a psychological factor) was the strongest predictor of caregiver QoL, above and beyond demographic or healthcare-system factors. These results suggest that when considering interventions for caregivers, psychological supports should be prioritized. It may also be important to determine the relative influence of formal social supports (e.g., programs, support groups) on caregiver quality of life, compared to informal supports (e.g., friends, family). In terms of formal supports, there is emerging evidence that mindfulness-based stress reduction (MBSR) interventions (either paired with early intervention for ASD or alone) lead to decreased depression and increased life satisfaction in caregivers of autistic children (Kuhlthau et al., 2020; Neece, 2014; Rayan & Ahmad, 2017; Singh et al., 2020; Weitlauf et al., 2020). In addition to MBSR, a narrative review by Da Paz and Wallander (2017) found support for stress management and relaxation techniques, expressive writing, and Acceptance and Commitment Therapy (ACT). Experts have suggested that ACT might be a beneficial long-term therapy for targeting stress and QoL in caregivers of autistic children because they are particularly susceptible to continuing to experience elevated stress levels over time, which can affect caregivers’ ability to engage in behaviors based on personal values (a major goal of ACT), which are most likely to be a source of long-term well-being.

To our knowledge, no previous studies have examined and found that the relation between parenting stress and QoL is stronger for caregivers of children with autism features compared to other developmental delays or no concerns. It is important to compare the relative contributions of parenting stress to QoL for caregivers of children with autism features compared to caregivers with no particular concerns about their children, given that parenting stress is experienced by all caregivers at various times (Abidin, 1990; Deschamps et al., 2019). High levels of parenting stress may be uniquely associated with certain aspects of QoL for caregivers of children with autism features due to the unique challenges presented, such as intervention costs and uncertainty about navigating the service delivery system.

The finding that greater caregiver income was associated with greater QoL is consistent with research on caregivers of children with intellectual disabilities (e.g., Lin et al., 2009). However, in contrast to prior work, we did not find that other caregiver demographic variables that were available to include (e.g., number of children in the home, child age, caregiver employment status) were predictive of QoL. This may be because we were not able to measure specific demographic characteristics that have been found to impact QoL (e.g., living situation, caregiver education status; Sulaimani et al., 2023; Asahar et al., 2021). In caregivers of autistic children, research overwhelmingly indicates that income is positively associated with environmental, but not physical or psychological QoL (e.g., Piovesan et al., 2015). We found that caregiver income impacted both overall QoL and, in a post-hoc analysis, each individual domain of QoL. The fact that caregiver income was still a significant predictor in our final model speaks to the unique impact it plays in QoL for caregivers and speaks to the importance of social safety net programs for these populations. Indeed, caregivers’ QoL needs are likely not only related to their possibly autistic child. Future research is needed to determine how to provide additional support to caregivers with lower QoL, particularly caregivers who are experiencing both income- or parenting-related stress in combination with low levels of family-centered care.

Results from the current study indicated that perceived family-centered care was a significant predictor of QoL for all caregivers. To our knowledge, no studies have directly measured the degree to which receiving or having perceived receiving better family centered care improves quality of life for caregivers of autistic children. Improving family-centered care may improve QoL for all caregivers, not just those who are wondering whether their child is autistic. However, we did not find significant evidence that more robust levels of perceived family-centered care ameliorated the negative association between parenting stress and quality of life for any group. Future research should further explore and potentially confirm this lack of moderation. Family-centered care may directly influence certain aspects of QoL itself (e.g., environmental quality of life, or health and social care accessibility and quality, opportunities for acquiring new information or skills, and freedom or security) rather than stress. Moreover, the experience of family-centered care during brief PCP visits may be less impactful for caregivers’ QoL than their interactions with any early interventionists with whom the family might work; early interventionists within federally-funded systems often work with families weekly from the moment a delay is recognized until a child turns three. System-level concerns may be a more salient contributor to stress and/or QoL for caregivers of autistic children compared with caregivers of children with other developmental concerns. This has implications for the types of interventions that may need to be offered to these groups. It is important to provide robust family-centered care for all caregivers of children with autism features, not just those experiencing high levels of stress.

5.1. Limitations and future directions

This study is not without limitations. With a cross-sectional design, it was not possible to determine the directionality of the findings. For example, though low levels of perceived family-centered care may negatively impact caregiver QoL, caregivers who report low QoL may also be more likely to interpret their relationship with their child’s primary care provider more negatively. All data utilized were gathered via self-report, which may result in biased or socially desirable responding. However, many constructs (e.g., parenting stress, quality of life) are inherently subjective. Future research could incorporate additional informants or forms of measurement (e.g., ecological momentary assessment), especially for family-centered care, to further validate and corroborate self-report responses.

The current sample is notably non-diverse in terms of race and socioeconomic status. More work is needed to examine stress and quality of life in marginalized populations, given that the intersectionality of neurodiversity with one or more other marginalized identities may have an outsized effect on quality of life for these families. Future work should examine whether parenting stress plays such a strong role in QoL for minoritized caregivers. Other factors such as demographic and structural factors (e.g., experiences of prejudice, lower perceived or objectively rated family-centered care) should be carefully explored as predictors and possible intervention points for improving QoL for minoritized caregivers.

Another limitation is that the caregiver groups were defined by the features they noticed their child had, rather than by children’s diagnostic status. However, the reality is that resource issues prevent many children from receiving diagnostic evaluations in the birth-to-three range. Observational data about specific child behaviors were not collected (only caregiver report). At the same time, by demonstrating that there are differences in quality of life for caregivers depending on the specific type of concern they have for their children, this study points to a need for individualized supports for caregivers (regardless of children’s developmental status).

An additional limitation is that parenting stress was the only caregiver psychological variable examined as a predictor of QoL in our study. Previous research has linked other factors, such as caregiver burnout, to QoL as well (Aktan et al., 2020). It was not possible to control for or examine all possible constructs that may explain the relation we found between parental stress and QoL Future research might examine the relation between parenting burnout, as well as other parenting factors, on QoL and family-centered care received from both PCPs (as examined in this study) and other professionals that are part of children and caregivers’ care teams.

These limitations notwithstanding, the present study provides an initial step in understanding QoL in caregivers of children with autism features. Given that our group was overwhelmingly comprised of caregivers of children with possible, but not yet confirmed autism, our results emphasize the point that caregivers of children with autism features may specifically benefit from interventions or support services that target their stress and quality of life. As the vast majority of children in the autism features group did not yet have an official diagnosis of ASD, these results indicate that QoL may be particularly negatively impacted in caregivers even prior to diagnostic confirmation of ASD, highlighting a potentially critical period in which parenting stress could be particularly salient and additional support could be provided (Deschamps et al., 2019).

It may be especially important to support caregiver QoL across service settings (e.g., medical, early intervention) during the birth-to-three period, when the identification of autism and the process of accessing many new services and systems of care are new experiences for caregivers. Early interventionists may monitor and intervene on parenting stress, which may also influence individualized family support plan goals. Previous research has demonstrated that participation in autism-specific early intervention, especially early interventions that include a parent training component, can help improve parenting stress overall and even maintain stress immediately following an ASD diagnosis (Brian et al., 2017, Gengoux et al., 2019; Jurek et al., 2023). Similar patterns have also been seen when brief early interventions are accessed by caregivers through primary care (Tellegen & Sanders, 2014). These results are magnified when providers incorporate caregiver input, provide caregivers with choice about target behaviors, and follow the caregivers’ lead (Brookman-Frazee & Koegel, 2004) or when training is provided in a group setting, leading to increased caregiver support (Akhani et al., 2021; Minjarez et al., 2013). In terms of informal supports, Parent to Parent (P2P) is a social support program that matches caregivers of children with disabilities with peer mentors. Research indicates P2P has been found to decrease stress (Lee et al., 2023).

Other research has found that even less formal day-to-day support by people such as partners and other family members can help lower any potential autism-related stress (Goedeke et al., 2019). It may be beneficial to provide caregivers with referrals or recommendations for these types of programs and supports when questions about autism are brought and throughout the diagnostic process. Future work is needed to more systematically test the effect of both formal and informal practices on stress, and thereby overall quality of life, for caregivers of autistic children and also those with autism features to help set them up for success throughout their child’s development, which will hopefully have downstream impacts on their child’s outcomes, as well.

What this paper adds.

This is one of the first studies on quality of life (QoL) to include caregivers of young children with autism features (before potential diagnosis), providing insight on caregiver QoL prior to diagnostic confirmation— a period of uncertainty for many families. For all caregivers, higher income, lower parenting stress, and more experiences of family-centered care with their primary care provider (PCP) related to higher quality of life. To our knowledge, this is the first study to have found that the relation between parenting stress and QoL is stronger for caregivers of children with autism features compared to other developmental delays or no concerns.

Footnotes

Declaration of Competing Interest

The authors have no conflicts of interest to disclose. This study was approved by the University of Washington Institutional Review Board. This study was funded by R01 MH104302 to W.L. Stone. S. R. Edmunds was funded by F31 DC015696 during a portion of her effort on this study.

CRediT authorship contribution statement

Stone Wendy L.: Writing – review & editing, Supervision, Resources, Funding acquisition, Conceptualization. DesChamps Trent: Writing – review & editing, Investigation, Data curation. Harker Colleen M.: Writing – original draft, Investigation, Conceptualization. Tagavi Daina M.: Writing – original draft, Data curation, Conceptualization. Edmunds Sarah R.: Writing – original draft, Visualization, Methodology, Formal analysis, Conceptualization.

Data availability

Data will be made available on request.

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