Vision care among school-aged children with autism spectrum disorder in North America: Findings from the Autism Treatment Network Registry Call-Back Study

Abstract

Children with autism spectrum disorder have a high risk of vision problems yet little is known about their vision care. This cross-sectional survey study, therefore, examined vision care among 351 children with autism spectrum disorder ages 6–17 years in the United States or Canada who were enrolled in the Autism Treatment Network Registry. Vision care variables were vision tested with pictures, shapes, or letters in the past 2 years; vision tested by an eye care practitioner (e.g. ophthalmologist, optometrist) in the past 2 years; prescribed corrective eyeglasses; and wore eyeglasses as recommended. Covariates included sociodemographic, child functioning, and family functioning variables. Multivariable models were fit for each vision care variable. Though 78% of children with autism spectrum disorder had their vision tested, only 57% had an eye care practitioner test their vision in the past 2 years. Among the 30% of children with autism spectrum disorder prescribed corrective eyeglasses, 78% wore their eyeglasses as recommended. Multivariable analysis results demonstrated statistically significant differences in vision care among children with autism spectrum disorder by parent education, household income, communication abilities, intellectual functioning, and caregiver strain. Overall, study results suggest many school-aged children with autism spectrum disorder do not receive recommended vision care and highlight potentially modifiable disparities in vision care.

Lay Abstract

Children with autism are at high risk for vision problems, which may compound core social and behavioral symptoms if untreated. Despite recommendations for school-aged children with autism to receive routine vision testing by an eye care practitioner (ophthalmologist or optometrist), little is known about their vision care. This study, therefore, examined vision care among 351 children with autism ages 6–17 years in the United States or Canada who were enrolled in the Autism Treatment Network Registry. Parents were surveyed using the following vision care measures: (1) child’s vision was tested with pictures, shapes, or letters in the past 2 years; (2) child’s vision was tested by an eye care practitioner in the past 2 years; (3) child was prescribed corrective eyeglasses; and (4) child wore eyeglasses as recommended. Sociodemographic characteristics such as parent education level, child functioning characteristics such as child communication abilities, and family functioning characteristics such as caregiver strain were also assessed in relationship to vision care. Although 78% of children with autism had their vision tested, only 57% had an eye care practitioner test their vision in the past 2 years. Among the 30% of children with autism prescribed corrective eyeglasses, 78% wore their eyeglasses as recommended. Differences in vision care were additionally found among children with autism by parent education, household income, communication abilities, intellectual functioning, and caregiver strain. Overall, study results suggest many school-aged children with autism do not receive recommended vision care and highlight potentially modifiable disparities in vision care.

Keywords

autism spectrum disorder children healthcare disparities preventive care vision tests

Pronounced and persistent health disparities exist for individuals with autism spectrum disorder (ASD) (Guan & Li, 2017; Hirvikoski et al., 2016; Kuhlthau et al., 2010). Drivers of health disparities for individuals with ASD often take hold during childhood and include the healthcare access problems and poor healthcare quality that parents of children with ASD commonly experience (Kogan et al., 2018). In terms of healthcare access problems, children with ASD are most likely to encounter delays accessing needed healthcare (e.g. not getting an appointment soon enough) and difficulty affording needed healthcare (e.g. difficulty affording dental or specialty care) (Lindly et al., 2019). Among children with ASD who have unmet healthcare needs, medical and/or dental care, mental healthcare, and hearing and/or vision care are the most frequently foregone types of healthcare (Kogan et al., 2018; Schieve et al., 2012; Valicenti-McDermott et al., 2019). Children with ASD are also less likely than those without ASD to receive high quality healthcare such as care delivered through the patient-centered medical home model (Kogan et al., 2018).

Beyond core social, communication, and behavioral impairments, children with ASD also often have co-occurring physical health issues such as vision problems that contribute to their need for multiple services across different delivery systems (Schieve et al., 2012). The complexity of ASD core symptoms and co-occurring conditions along with related service needs may, together, collectively contribute to greater healthcare access problems and poorer healthcare quality (Lindly et al., 2016; Schieve et al., 2012). Sociodemographic characteristics (e.g. race, ethnicity, household income) are additionally linked to differences in healthcare access and quality among children with ASD (Blanche et al., 2015; Magaña et al., 2012; Parish et al., 2012). For example, Latino children with ASD are less likely to have a personal doctor (Parish et al., 2012) and have greater difficulty obtaining specialty care referrals than non-Latino children with ASD (Broder-Fingert et al., 2013; Parish et al., 2012). Moreover, children of color with ASD experience disparities in access to needed educational and therapy-based services (Harstad et al., 2013; Irvin et al., 2012; Zuckerman et al., 2017). Yet, limited knowledge exists regarding how these disparities manifest for children with ASD in the context of accessing certain preventive and specialty care services targeting physical health issues such as vision care.

Children with ASD are more likely to have vision problems (e.g. amblyopia, high refractive error, strabismus) or blindness than other children (Little, 2018); therefore, greater understanding of vision care among children with ASD is especially needed. Recent data show that among US school-aged (6–17 years) children approximately 3.9% with ASD are estimated to have blindness or vision problems (even when wearing glasses) compared to 2% without ASD (Child and Adolescent Health Measurement Initiative (CAHMI) et al., 2018). Untreated vision problems, particularly those moderate and severe in nature, may exacerbate core social and behavioral symptoms leading to poor long-term health outcomes in children with ASD. However, if identified early through a vision test, many common vision problems in childhood are treatable with a combination of spectacle correction, occlusion therapy, and/or surgery (American Optometric Association Evidence-Based Optometry Guideline Development Group, 2017). For children with ASD and other developmental disabilities, the treatment of vision problems may have positive effects both on their core ASD symptoms and their overall health (Ozer et al., 2018; Streff, 1975; The Royal College of Ophthalmologists & Royal College of General Practitioners, n.d.).

To address childhood vision problems as early as possible, the American Academy of Pediatrics (AAP) and the American Academy of Ophthalmology (AAO) recommend: (1) an initial assessment of children’s visual systems occur during the newborn period and, if needed, referral to an eye care practitioner (i.e. ophthalmologist, optometrist) for comprehensive evaluation; (2) instrument-based vision screening (e.g. photoscreening devices, traditional optotype-based tools with age-appropriate symbols) be attempted with children ages 12 months to 3 years at well-child visits, until direct visual acuity screening can routinely begin often by age 4 years; and (3) children of any age who fail vision screening be referred to an eye care practitioner for a comprehensive evaluation and annual re-evaluation thereafter (Committee on Practice and Ambulatory Medicine et al., 2016; Donahue et al., 2016). For children ages 3 through 5 years, the American Academy of Optometry recommends that all children regardless of risk for vision problems receive at least one comprehensive evaluation by an eye care practitioner and school-aged children (ages 6–18 years) receive annual evaluation (American Academy of Optometry, 2016). Children with readily recognized ocular abnormalities (e.g. strabismus), known motor or neurodevelopmental disorders, those with a first degree relative with amblyopia or strabismus, those born prematurely (<32 weeks), and those with parents who express concern about potential vision problems are recommended to be directly referred for a comprehensive evaluation by an eye care practitioner with annual examination thereafter (American Academy of Optometry, 2016). In their joint vision screening policy statement, the American Academy of Pediatrics’ American Academy of Pediatrics Committee on Practice and Ambulatory Medicine in conjunction with the American Academy of Ophthalmology, the Association for Pediatric Ophthalmology and Strabismus, and the American Association of Certified Orthoptists make no reference to a special case for children with neurodevelopmental disability (Committee on Practice and Ambulatory Medicine et al., 2016; Donahue et al., 2016).

Despite these national recommendations for pediatric vision testing and mandated school vision screening for children in 40 states (Ruderman, 2016), only half of US school-aged children with ASD received a comprehensive evaluation by an eye care practitioner based on 2011–12 National Survey of Children’s Health data (Swanson, in press). Vision testing for children with ASD may be impeded by unique challenges such as social and behavioral issues (Butchart et al., 2017; Coulter et al., 2015; Ikeda et al., 2013). Indeed, past research suggests poor vision testing adherence among children with ASD due to challenges in communication, sensory processing, motor planning, and diagnostic overshadowing (Ikeda et al., 2013; Kabatas et al., 2015; The Royal College of Ophthalmologists & Royal College of General Practitioners, n.d.). Vision testing for children with ASD may also be impacted by the severity of ASD symptoms and family sociodemographic characteristics such as primary household language (Swanson, in press).

Still, little is presently known about vision care for children with ASD in North America. Prior research on this topic has primarily relied on small samples at single sites or has used a data source with limited ASD-specific measures of child and family functioning that likely contribute to broader healthcare disparities for this population (Coulter et al., 2015; Ikeda et al., 2013; Swanson, in press). This study, therefore, aimed to (1) determine vision care access and (2) examine sociodemographic, child functioning and health, and family functioning correlates of vision care in a well-described sample of school-aged children with ASD. In relationship to our first study aim and based on past research regarding healthcare access for children with ASD (Kogan et al., 2018), we hypothesized that children with ASD would lack access to vision care services, particularly comprehensive evaluation by an eye care practitioner as is recommended. Related to our second study aim and in alignment with prior research on healthcare disparities for children with ASD (Broder-Fingert et al., 2013; Lindly et al., 2019; Zuckerman et al., 2017), we hypothesized that children with ASD in low socioeconomic subgroups and/or with poorer functioning would be most prone to lack vision care access.

Method

Study design

We conducted a secondary analysis of cross-sectional data from the Autism Speaks Autism Treatment Network (ATN) Registry Call-Back Assessment study (RCBA). The ATN RCBA was initiated in 2015 to collect long-term, follow-up data on participants enrolled in the ATN registry (Murray et al., 2016). For the ATN RCBA, a random sample of ATN registry participants was drawn from each of the 12 academic, hospital-affiliated clinics that were active in the ATN from 2015 to 2016 (Supplemental Material). ATN RCBA data were first collected in 2015 and then again in 2016; however, vision care data were only collected at a single time point making this study cross-sectional. The Institutional Review Board at each ATN RCBA site approved this research.

The ATN and ATN registry have both been previously described in greater detail (Murray et al., 2016; Perrin et al., 2016). Briefly, the ATN registry is a multisite database including developmental, behavioral, and health data on a convenience sample of children with ASD who received care at an ATN clinical center in the United States or Canada. Exclusion criteria included a medical condition that precluded valid diagnostic testing (e.g. blindness, deafness), and parents had to be fluent in English or Spanish.

Sample

The study sample included the cohort of families who completed a second annual visit for the ATN RCBA. The ATN RCBA initially enrolled 611 families. The following ATN RCBA inclusion criteria were used to determine eligibility: prior ATN assessment between 2011 and 2016 or current ATN registry enrollment, met Diagnostic and Statistical Manual of Mental Disorders (4th ed.; DSM-IV) criteria for any pervasive developmental disorder or Diagnostic and Statistical Manual of Mental Disorders (5th ed.; DSM-V) criteria for ASD, and provided informed consent. Families participating in the ATN RCBA did not differ substantially from families who were recruited but declined enrollment (Fenning et al., 2020). A second annual ATN RCBA visit was conducted for 407 families. Of these families, 374 families provided data for the questions about their child’s vision care and 351 of these families had children aged 6–17 years. Because only 23 children with ASD were younger than 6 years old and vision care guidelines differ between children less than 6 years old and 6–18 years old, we limited the sample to children ages 6–17 years.

Procedures

ATN registry enrollment involved baseline assessments to confirm the child’s ASD diagnosis through clinical best estimate procedures involving the Diagnostic and Statistical Manual of Mental Disorders (4th ed., text rev.; DSM-IV-TR) or DSM-V (American Psychiatric Association, 2000, 2013) and the Autism Diagnostic Observation Schedule (ADOS-2) (Lord et al., 2012). As part of the baseline assessments, parents also reported on sociodemographic characteristics and whether their child had current or past vision problems. The second annual ATN RCBA follow-up protocol involved parent-reported measures of child adaptive behavior, ASD symptoms, problem behaviors, pediatric quality of life, caregiver strain, patient activation, and vision care. When possible, ATN RCBA participants were asked to report data online before their visit and other study assessments were completed in-person during a single clinic encounter. The mean time between the baseline ATN registry visit and the second annual ATN RCBA follow-up visit was 3.87 years (SD = 0.60; range: 2–5 years).

Measures

ATN baseline vision problems

As part of the ATN registry parent baseline assessment, parents were asked to indicate if their child ever or currently had vision problems (yes or no).

Sociodemographic characteristics

Parents reported on their child’s age (years), sex, Hispanic ethnicity, race (White; Black, African American or Black Canadian; Asian, other race or multiracial), and health insurance coverage (private only, public only, public and private, uninsured). Parents also reported their family’s annual household income level in US or Canadian dollars ($0.00–$24,999, $25,000–$49,999, $50,000–$74,999, $75,000–$99,999, ⩾$100,000), and highest parent education level (high school or less versus some college or more). Except for the child’s age, all sociodemographic characteristics were assessed at ATN baseline.

ATN baseline intellectual functioning

Child intellectual functioning, also referred to as intelligence quotient (IQ), was measured at ATN enrollment through administration of a standardized cognitive assessment that yielded an overall summary score with a common metric. ATN cognitive assessments were selected in accordance with child presentation and needs, and included the Mullen Scales of Early Learning (Mullen, 1995), Bayley Scales of Infant Development-Third Edition (Bayley, 2006), Stanford–Binet Intelligence Scales-Fifth Edition (Roid, 2003), Differential Abilities Scales-Second Edition, Wechsler Preschool and Primary Scale of Intelligence-Third Edition (Wechsler, 2002), Wechsler Intelligence Scale for Children-Fourth Edition (Wechsler, 2003), Wechsler Abbreviated Scale of Intelligence (Wechsler, 1999), and the Leiter International Performance Scale-Revised (Roid & Miller, 2002). IQ standard scores below 76 were also used to determine intellectual disability status (American Psychiatric Association, 2013).

ATN baseline adaptive behavior

The Adaptive Behavior Composite score from the Vineland Adaptive Behavior Scales-2 (VABS-2) Survey Interview was used to assess level of adaptive behavior at ATN enrollment and to establish the presence of comorbid intellectual disability (Sparrow et al., 1984, 2005; Sparrow & Cicchetti, 1985). Higher scores indicated greater adaptive functioning.

ATN baseline ASD severity

ADOS-2 Comparison scores, taken at the time of ATN registry enrollment, were used as an indicator of ASD severity. Higher ADOS-2 Comparison scores indicated greater ASD severity.

ATN RCBA ASD symptoms

Parent-reported ASD symptoms were indexed by the Autism Impact Measure (AIM) Total Frequency score (Kanne et al., 2014). The AIM has been used to assess ASD symptoms in recent clinical trials (Frye et al., 2018). Higher AIM scores indicated greater impact.

ATN RCBA communication skills

Given prior evidence linking participation in vision testing to children’s communication skills (Coulter et al., 2015), emphasis was placed on this specific aspect of adaptive behavior at RCBA follow-up. The Communication standard score from the VABS-2 (Sparrow et al., 1984; Sparrow & Cicchetti, 1985, 2005) was used to index children’s everyday communication skills across receptive, expressive, and written language domains.

ATN RCBA child behavior problems

Total level of parent-reported child behavior problems was assessed using the Total Problems T-score from the widely used and validated Child Behavior Checklist (Achenbach & Ruffle, 2000; Cohen et al., 1985). Higher scores indicated more behavior problems.

ATN RCBA pediatric quality of life

Pediatric quality of life was measured by the PedsQL total score, with higher scores indicating better health-related quality of life (Varni et al., 2001).

ATN RCBA attention deficit/hyperactivity disorder

Attention deficit/hyperactivity disorder (ADHD) was based on clinician report of whether the child had ADHD not otherwise specified or attention deficit disorder with hyperactivity.

ATN RCBA prescription medication

Any prescription medication use by the child was based on clinician report of whether the child was prescribed one or more of 28 prescription medications (e.g. mixed amphetamine salts, risperidone, fluoxetine).

ATN RCBA caregiver strain

Caregiver-reported strain related to the target child with ASD was assessed using the Total Score from the 21-item Caregiver Strain Questionnaire, with higher scores indicating greater strain. The Caregiver Strain Questionnaire has been widely used to assess strain among caregivers of children with serious emotional and behavioral disorders and ASD more specifically (Brannan et al., 1997; Khanna et al., 2012).

ATN RCBA parent activation

Level of parent skills, knowledge, and motivation as related to child health and disability status was measured with the total raw score from the Parent Activation Measure for Developmental Disabilities (Ruble et al., 2018). Higher scores indicated greater parent activation.

ATN RCBA vision care

Four items were used to examine vision care. Several ATN RCBA questionnaire items on parents’ experiences regarding their child’s vision care were adapted from questionnaire items in the 2011–2012 National Survey of Children’s Health (Centers for Disease Control, 2012). The first item asked parents: “During the past 2 years, has your child had his or her vision tested with pictures, shapes, or letters?” If the parent answered “Yes” to this question, the parent was then asked: “What kind of place or places did your child have his or her vision tested?” Parents were asked to mark all of the following response options that applied: eye doctor or eye specialist (ophthalmologist, optometrist) office, pediatrician or other general doctor’s office, school, clinic or health center, or other (specify). Because children who receive vision testing at an ophthalmologist or optometrist office are likely to receive a comprehensive evaluation, we used this item to assess vision evaluation versus screening. All parents were additionally asked: “Does your child require corrective eyeglasses, based on evaluation?” If parents responded “Yes” to this item, they were next asked, “Does your child wear glasses as recommended?” The response options to this item were yes or no.

Statistical analysis

Descriptive univariate statistics including frequencies, percentages with 95% confidence intervals (CIs) for categorical variables, and means and standard deviations for continuous variables were initially computed for all variables of interest among the study sample. Bivariate statistics were next computed to examine associations of each vision care variable of interest and the sociodemographic, child functioning, and family functioning variables. Multivariable mixed effects logistic regression models with a random intercept for site were then fit for each vision care variable. Covariates for each multivariable model were determined according to statistically significant bivariate analysis results, as well as clinical interest. Parent-reported child vision problems at the ATN registry baseline assessment was controlled for in all multivariable models, except in the model for children having worn corrective eyeglasses as prescribed. All analyses were performed in SAS 9.4 (SAS Institute Inc., 2013).

Results

Sample characteristics

The study sample’s sociodemographic, child functioning and health, and family functioning characteristics are shown in Table 1. Approximately 17% of children in the study sample were reported by a parent to have vision problems at ATN registry enrollment. Regarding the sample’s sociodemographic characteristics, a plurality of children with ASD were primary school aged (6–11 years), male, non-Hispanic, White, privately insured, from a household with one or more parent that had more than a high school education, and from a household with an annual income of $50,000 or more. In addition, slightly more than half of the children met DSM-V criteria for comorbid intellectual disability, as defined by measured intellectual functioning and adaptive behavior standard scores below 76 at the time of ATN enrollment (American Psychiatric Association, 2013). Approximately 43% of the sample had co-occurring ADHD, and more than half (60.4%) used one or more prescription medication.

Table 1.

Sample characteristics (N = 351).

	n	M (SD) or %
Vision problems (past or present)	52	17.1
Sociodemographics
Age, years	351	10.0 (3.0)
6–11	267	76.1
12–17	84	23.9
Sex	351
Female	66	18.8
Male	285	81.2
Hispanic ethnicity	336
Hispanic	24	7.1
Non-Hispanic	312	92.9
Race	341
White	280	82.1
Black, African American, Black Canadian	17	5.0
Asian	16	4.7
Other or Multiracial	28	8.2
Insurance coverage	351
Private Insurance Only	173	49.3
Public Insurance Only	107	30.5
Public and Private Insurance	57	16.2
Uninsured	14	4.0
Highest parent education level	339
High school or less	35	10.3
More than high school	304	89.7
Annual household income	282
$0–$24,999	42	14.9
$25,000–$49,000	70	24.8
$50,000–$74,999	53	18.8
$75,000–$99,999	39	13.8
⩾$100,000	78	27.7
Child Functioning and Health
DSM-IV diagnosis	351
Autism	248	70.7
Asperger’s	33	9.4
Pervasive Developmental Disorder-Not Otherwise Specified	70	19.9
Autism Diagnostic Observation Schedule Score	332	7.0 (2.1)
Autism Impact Measure Total Frequency Score	342	105.7 (27.9)
Intellectual Functioning	291	76.6 (23.3)
Intellectual Disability	327
No	157	48.0
Yes	170	52.0
Vineland Composite Score	330	72.1 (11.9)
Communication Standard Score (Vineland)	338	73.3 (16.5)
Total Problems Child Behavior Checklist Score	340	61.1 (9.1)
Pediatric Quality of Life Total Scale Score	342	62.8 (16.0)
Attention Deficit/Hyperactivity Disorder
No	201	57.3
Yes	150	42.7
Prescription Medication Use
No	139	39.6
Yes	212	60.4
Family Functioning
Patient Activation Measure Total Score	307	69.3 (15.6)
Caregiver Strain Questionnaire Global Score	341	7.4 (2.2)

Vision care among children in the ATN RCBA

Among school-aged children in the ATN RCBA, 77.8% (95% CI: 73.5%–82.1%) reported vision testing in the past 2 years. Of those with vision testing, 26.4% (95% CI: 21.2%–31.6%) reported vision testing at two or more places in the past 2 years. In the full study sample during the past 2 years 57.0% (95% CI: 51.8%–62.1%) reported vision testing at an ophthalmologist or optometrist office, 24.5% (95% CI: 20.0%–29.0%) reported vision testing at a pediatrician or general doctor’s office, 19.9% (95% CI: 15.8%–24.1%) reported vision testing at school, 1.4% (95% CI: 0.2%–2.7%) reported vision testing at a clinic or health center, and 0.9% (0%–1.8%) reported vision testing at another setting. Overall, 30.2% (95% CI: 25.4%–35.0%) of children were prescribed corrective eyeglasses. Among them, 78.3% (70.6%–86.0%) wore their corrective eyeglasses as recommended.

Bivariate associations of vision care with sociodemographic, child functioning and health, and family functioning characteristics

Vision problems were more common for children reported to have had their vision tested in the past 2 years, children who had their vision tested at an ophthalmologist or optometrist office in the past 2 years, and children who were prescribed corrective eyeglasses. Children reported to have had their vision tested in the past 2 years were older, had parents with more education, had less historical ASD symptom severity (ADOS-2) and less frequent current ASD symptoms (AIM frequency), had higher intellectual functioning, had higher adaptive functioning including communication ability, and had less caregiver strain. Children reported to have had their vision tested at an ophthalmologist or optometrist office in the past 2 years had parents with more education, had higher annual household income, had higher intellectual functioning, and had higher communication ability. Children who were prescribed corrective eyeglasses were older, had higher intellectual functioning, and had higher adaptive functioning including communication ability. Among children who were prescribed corrective eyeglasses, those who wore their corrective eyeglasses as prescribed were reported to have less frequent current ASD symptoms, fewer behavior problems, higher pediatric quality of life, and less caregiver strain. Table 2 shows all bivariate analysis results.

Table 2.

Bivariate associations of vision care with sociodemographic, child functioning, and family functioning characteristics among school-aged children with autism in the ATN RCBA..

	Vision tested in the past 2 years		Vision tested at an ophthalmologist or optometrist office in the past 2 years		Prescribed corrective eyeglasses		Corrective eyeglasses worn as recommended
	Yes (n = 273)	No (n = 78)	Yes (n = 200)	No (n = 151)	Yes (n = 106)	No (n = 245)	Yes (n = 83)	No (n = 23)
Vision problems (past or present)	90.4%	9.6%	78.8%	21.2%	65.4%	34.6%	85.3%	14.7%
No vision problems	77.0%	23.0%	52.4%	47.6%	21.4%	78.6%	79.6%	20.4%
p-value	0.037		<0.001		<0.001		0.58
Sociodemographics
Age, years	10.2 (3.0)	9.4 (3.0)	10.2 (3.0)	9.7 (3.0)	10.7 (3.2)	9.7 (2.9)	10.4 (3.1)	11.6 (3.4)
p-value	0.019		0.063		0.009		0.12
Sex
Female	80.3%	19.7%	65.2%	34.8%	34.8%	65.2%	82.6%	17.4%
Male	77.2%	22.8%	55.1%	44.9%	29.1%	70.9%	77.1%	22.9%
p-value	0.63		0.17		0.37		0.78
Hispanic ethnicity
Hispanic	66.7%	33.3%	41.7%	58.3%	12.5%	87.5%	33.3%	66.7%
Non-Hispanic	78.5%	21.5%	57.7%	42.3%	30.4%	69.6%	80.0%	20.0%
p-value	0.20		0.14		0.07		0.12
Race
White	79.6%	20.4%	57.9%	42.1%	32.9%	67.1%	80.4%	19.6%
Black, African American, Black Canadian	70.6%	29.4%	41.2%	58.8%	11.8%	88.2%	50.0%	50.0%
Asian	68.8%	31.3%	62.5%	37.5%	25.0%	75.0%	50.0%	50.0%
Other or Multiracial	71.4%	28.6%	50.0%	50.0%	17.9%	82.1%	80.0%	20.0%
p-value	0.39		0.47		0.13		0.21
Insurance coverage
Private insurance	78.0%	22.0%	53.2%	46.8%	30.6%	69.4%	81.1%	18.9%
Public insurance	75.7%	24.3%	56.1%	43.9%	30.8%	69.2%	78.8%	21.2%
Public and private insurance	84.2%	15.8%	70.2%	29.8%	31.6%	68.4%	72.2%	27.8%
Uninsured	64.3%	35.7%	57.1%	42.9%	14.3%	85.7%	50.0%	50.0%
p-value	0.35		0.16		0.66		0.50
Highest Parent Education Level
High school or less	60.0%	40.0%	37.1%	62.9%	40.0%	60.0%	78.6%	21.4%
More than high school	80.3%	19.7%	59.2%	40.8%	29.6%	70.4%	78.9%	21.1%
p-value	0.009		0.018		0.25		0.99
Annual household income
$0–$24,999	69.0%	31.0%	31.0%	69.0%	26.2%	73.8%	81.8%	18.2%
$25,000–$49,000	82.9%	17.1%	52.9%	47.1%	31.4%	68.6%	90.9%	9.1%
$50,000–$74,999	79.2%	20.8%	58.5%	41.5%	26.4%	73.6%	71.4%	28.6%
$75,000–$99,999	74.4%	25.6%	53.8%	46.2%	28.2%	71.8%	81.8%	18.2%
⩾$100,000	82.1%	17.9%	70.5%	29.5%	37.2%	62.8%	86.2%	13.8%
p-value	0.40		0.001		0.66		0.61
Child Functioning and Health
Autism Diagnostic Observation Schedule Score	6.9 (2.1)	7.4 (2.2)	6.8 (2.2)	7.2 (2.0)	6.7 (2.2)	7.1 (2.1)	6.6 (2.3)	6.9 (2.2)
p-value	0.041		0.12		0.16		0.72
Autism Impact Measure Total Frequency Score	103.6 (27.3)	113.1 (28.7)	103.5 (27.5)	108.5 (28.2)	102.1 (27.4)	107.2 (28.0)	98.3 (25.0)	115.3 (31.4)
p-value	0.009		0.07		0.13		0.014
Intellectual functioning	78.9 (22.8)	68.4 (23.5)	79.5 (23.1)	72.6 (23.1)	84.4 (23.0)	72.9 (22.6)	83.8 (22.5)	86.4 (25.3)
p-value	<0.001		0.013		<0.001		0.60
Intellectual disability
No	82.8%	17.2%	59.9%	40.1%	36.9%	63.1%	79.3%	20.7%
Yes	71.2%	28.8%	53.5%	46.5%	21.8%	78.2%	78.4%	21.6%
p-value	0.013		0.27		0.003		0.99
Vineland Composite Score	73.3 (11.5)	68.1 (12.7)	73.2 (11.5)	70.8 (12.3)	74.8 (12.2)	71.1 (11.7)	75.3 (12.0)	72.7 (13.5)
p-value	0.005		0.20		0.02		0.48
Communication Standard Score (Vineland)	75.0 (16.4)	67.1 (15.5)	75.7 (16.7)	70.0 (15.8)	77.9 (16.9)	71.3 (16.0)	79.7 (16.2)	71.2 (18.0)
p-value	0.001		0.004		0.002		0.05
Total Problems Child Behavior Checklist T Score	60.6 (9.4)	63.0 (7.5)	60.7 (8.6)	61.7 (9.7)	61.2 (8.7)	61.1 (9.3)	59.9 (8.7)	65.6 (7.7)
p-value	0.057		0.19		0.99		0.007
Pediatric Quality of Life Total Scale Score	62.9 (16.2)	62.5 (15.1)	63.2 (16.5)	62.3 (15.2)	63.9 (17.4)	62.4 (15.3)	66.0 (16.5)	56.5 (18.9)
p-value	0.80		0.42		0.38		0.049
Attention Deficit/Hyperactivity Disorder
No	76.6%	23.4%	57.2%	42.8%	29.9%	70.1%	78.3%	21.7%
Yes	79.3%	20.7%	56.7%	43.3%	30.7%	69.3%	78.3%	21.7%
p-value	0.60		>0.99		0.91		>0.99
Prescription Medication Use
No	77.0%	23.0%	57.6%	42.4%	26.6%	73.4%	78.4%	21.6%
Yes	78.3%	21.7%	56.6%	43.4%	32.5%	67.5%	78.3%	21.7%
p-value	0.79		0.91		0.29		>0.99
Family Functioning
Patient Activation Measure Total Score	69.7 (15.4)	67.8 (16.2)	68.9 (15.8)	69.9 (15.3)	71.4 (17.3)	68.4 (14.7)	72.7 (16.4)	67.4 (19.7)
p-value	0.16		0.73		0.20		0.36
Caregiver Strain Questionnaire Global Score	7.2 (2.1)	7.9 (2.4)	7.2 (2.1)	7.6 (2.4)	7.1 (2.1)	7.5 (2.3)	6.7 (1.9)	8.3 (2.4)
p-value	0.026		0.14		0.23		0.003

Multivariable associations of vision care with sociodemographic, child functioning and health, and family functioning characteristics

As shown in Table 3, multivariable analysis results showed that only highest parent education level (more than high school versus high school or less) had a statistically significant association with the child having had his or her vision tested in the past 2 years (adjusted odds ratio (aOR): 6.48, 95% CI: 1.81–23.24, p-value = 0.004) after adjusting for child vision problems, age, ASD symptoms, intellectual functioning, communication ability, behavior problems, and caregiver strain among school-aged children in the ATN RCBA. Multivariable analysis results also showed that compared to low household income ($0–$24,999), higher annual household income ($50,000–$74,999: aOR: 4.17, 95% CI: 1.20–14.42, p-value = 0.025; ⩾$100,000: aOR: 6.39, 95% CI: 1.88–21.69, p-value = 0.003) had a statistically significant association with the child’s vision being tested at an ophthalmologist or optometrist office in the past 2 years after adjusting for child vision problems, age, highest parent education level, and intellectual functioning. Higher child communication ability (aOR: 1.03, 95% CI: 1.00–1.05, p-value = 0.035) also had a statistically significant association with the child’s vision being tested at an ophthalmologist or optometrist office in the past 2 years after adjusting for child vision problems, age, highest parent education level, and intellectual functioning. Higher intellectual functioning (aOR: 1.02, 95% CI: 1.00–1.03, p-value = 0.027) and communication ability (aOR: 1.04, 95% CI: 1.01–1.06, p-value = 0.002) were each associated with higher adjusted odds of children being prescribed corrective eyeglasses after adjusting for child vision problems and age. Among children prescribed corrective eyeglasses, higher caregiver strain had a statistically significant association with the lower odds of the child having worn his or her corrective eyeglasses as recommended (aOR: 0.71, 95% CI: 0.52–0.98, p-value = 0.036) after adjusting for ASD symptoms, pediatric quality of life, and behavior problems.

Table 3.

Multivariable associations for vision care variables among school-aged children with autism from the ATN RCBA.

	aOR (95% CI)	p-value
Model 1. Vision tested past 2 years
Child age, years	1.13 (0.97–1.32)	0.11
Highest parent education level
High school or less	1.00
More than high school	6.48 (1.81–23.24)	0.004
Autism Impact Measure Total Frequency Score	1.00 (0.98–1.02)	0.70
Intellectual functioning	1.01 (0.99–1.03)	0.45
Communication Standard Score (Vineland)	1.04 (1.00–1.07)	0.06
Total Problems Child Behavior Checklist T Score	0.98 (0.92–1.04)	0.48
Caregiver Strain Global Scale Score	1.01 (0.82–1.23)	0.96
Model 2. Vision tested at an ophthalmologist or optometrist office in the past 2 years
Child age, years	1.08 (0.95–1.22)	0.23
Highest parent education level
High school or less	1.00
More than high school	1.72 (0.49–5.96)	0.39
Annual household income
<$25,000	1.00
$25,000–$49,999	2.80 (0.86–9.13)	0.086
$50,000–$74,999	4.17 (1.20–14.42)	0.025
$75,000–$99,999	2.52 (0.66–9.71)	0.18
⩾$100,000	6.39 (1.88–21.69)	0.003
Intellectual functioning	1.00 (0.99–1.02)	0.73
Communication Standard Score (Vineland)	1.03 (1.00–1.05)	0.035
Model 3. Child prescribed corrective eyeglasses
Child age, years	1.06 (0.95–1.19)	0.29
Intellectual functioning	1.02 (1.00–1.03)	0.027
Communication Standard Score (Vineland)	1.04 (1.01–1.06)	0.002
Model 4. Corrective eyeglasses worn as recommended
Autism Impact Measure Total Frequency Score	0.99 (0.97–1.01)	0.42
Total Problems Child Behavior Checklist Score	0.96 (0.88–1.04)	0.34
Pediatric Quality of Life Total Score	0.99 (0.95–1.04)	0.75
Caregiver Strain Questionnaire Global Scale Score	0.71 (0.52–0.98)	0.036

aOR: adjusted odds ratio; ATN: Autism Treatment Network; CI: confidence interval; RCBA: Registry Call-Back Assessment.

All models included a random intercept for site. Models 1–3 controlled for child vision problems reported by the parent at registry baseline; however, model 4 did not include vision problems at baseline because the model was only fit for children prescribed corrective glasses.

Discussion

This study is one of the first to examine vision care among school-aged children with ASD across multiple sites in North America. Study findings demonstrate that many (78%) school-aged children with ASD participating in the ATN have routine vision testing; however, only 57% including those with parent-reported vision problems routinely received more comprehensive evaluation by an ophthalmologist or optometrist. These results are somewhat consistent with the overall percentage of school-aged children who receive vision testing in any setting and those who receive vision testing by an eye care practitioner, based on 2016 and 2017 National Survey of Children’s Health data. That is, an estimated 86% of US children ages 6–11 years had routine vision testing including 44% who had vision testing by an eye care practitioner, and an estimated 83% of US children ages 12–17 years had vision testing including 59% who had vision testing by an eye care practitioner (CAHMI et al., 2018).

This study’s results additionally showed that nearly 3 in 10 school-aged children with ASD were prescribed corrective eyeglasses, but among them approximately 1 in 5 did not wear their corrective eyeglasses as recommended. Although the percentage of children with ASD in this study who were prescribed corrective glasses was similar to the percentage of US children overall who wear corrective eyeglasses in other studies (Kemper et al., 2007; National Center for Health Statistics, 2017), little remains known about rates of corrective eyeglass adherence among children more generally. This study’s findings further highlight differences in vision care among school-aged children with ASD by sociodemographic characteristics, such as parent education level, and child functioning characteristics, such as intellectual functioning and communication skills, suggesting healthcare disparities and improvement areas.

Differences in routine vision testing generally (regardless of setting) and at an ophthalmologist or optometrist office more specifically among school-aged children with ASD from the ATN RCBA suggest that children whose parents are less educated and/or have a low household income may be falling through the cracks. These findings are aligned with past research on disparities in specialty care services access more broadly among children with ASD, which show families of color and/or low socioeconomic status are less likely to access these services (Broder-Fingert et al., 2013; Lin & Yu, 2015; Liptak et al., 2008). Family-, provider-, and systems-level intervention may, however, be employed to reduce this type of inequality in vision care. For example, intervention targeting parents with limited health literacy (i.e. the ability to access, process, and use health information and services for their child) in primary care settings to increase awareness and knowledge about the importance of vision screening for children with ASD may make parents more conscious of potential vision problems that their child may be experiencing and encourage parents to ask about vision screening during their child’s visits. Visit-based planning tools for parents and/or low-literacy, pictogram-based educational materials could be used for such interventions. On the provider side, further training employing innovative practice-based approaches adapted for pediatric ASD care (e.g. Project Extension for Community Healthcare Outcomes) may also help providers to meet national guidelines on vision screening and referral for children with ASD (Mazurek et al., 2019). Provider prompts in electronic health record systems along with the use of tools or eye examination methods (e.g. photoscreening) that better account for the unique social profile of children with ASD may, together, result in increased and more accurate vision testing (Coulter et al., 2015; Singman et al., 2013). Increased school-based vision testing for children, including vision testing for younger children in early intervention and Head Start programs, could also help to improve screening and referral rates for children with ASD, especially for those in low-income families. Still, school-based testing may also need to be tailored for children with ASD (e.g. use of photoscreening) to ensure assessment is feasible and accurate.

Because higher income was associated with higher odds of vision testing by an ophthalmologist or optometrist, families of children with ASD who have fewer financial resources may need additional support to overcome the financial barriers often associated with specialty care services such as a comprehensive eye evaluation (Lindly et al., 2019). Co-pays for specialty versus preventive care services are typically higher and may vary between public and private insurance plans, potentially impeding low-income families of children with ASD from obtaining vision care (National Academies of Sciences, Engineering, and Medicine et al., 2016). In addition, it may be difficult for families to find an ophthalmologist or optometrist accepting pediatric patients—particularly those with ASD—and then make the time to go to such appointments given the other, complex service needs children with ASD commonly have. Further research to understand barriers to specialty vision care for children with ASD is needed; however, care integration and navigation models through a patient-centered medical home or ASD clinic could potentially help low-income families of children with ASD to overcome some of these plausible barriers to accessing specialty vision care (e.g. connection to financial assistance resources, increasing a family’s health insurance literacy about their child’s plan coverage).

Study results further suggest that children with ASD with greater communication skills were more likely to have their vision tested at an ophthalmologist or optometrist office and also to be prescribed corrective eyeglasses. Similarly, higher intellectual functioning was associated with higher odds of the child being prescribed eyeglasses. Together, these results reinforce that vision testing protocols tailored for children with ASD, particularly those with cognitive and language delays who may have difficulty understanding and communicating about visit procedures and expectations, may increase rates of comprehensive evaluation. More specifically, promising eye examination protocols tailored for individuals with ASD have incorporated communication supports (e.g. simplification of traditional instruction sets, additional time to process and respond to directions), vision supports (e.g. use of a social story), supports and modifications for planning challenges (e.g. acceptance of motor approximations for nonverbal individuals in visual acuity testing), supports for sensory processing challenges (e.g. selection of tests least likely to elicit tactile defensiveness), and behavioral strategies (e.g. use of shaping and high-probability request/low probability test) (Coulter et al., 2015).

Limitations

This study has important limitations. The ATN RCBA data used in this study were primarily cross-sectional, limiting our ability to draw inferences about the temporal nature of vision care including the relationships examined. The generalizability of study findings is, additionally, limited by the clinical sample drawn for the ATN RCBA. That is, children in the ATN RCBA had a clinically confirmed ASD diagnosis, were seen at a large academic medical center in the United States or Canada, had at least one parent proficient in English or Spanish, and were not blind or deaf. A majority of the children were also identified as being White and non-Hispanic. For this reason, certain subgroups of children with ASD who are especially likely to experience healthcare disparities (e.g. children of color, children living in rural areas) are not well-represented in this study. Study findings may, therefore, be more favorable in terms of vision care access than they might otherwise be in a more demographically and geographically diverse sample of children with ASD. Because children with ASD and blindness and/or deafness were initially excluded from the ATN registry, additional research to understand vision care in these subgroups is especially needed. Similarly, this study was unable to examine how certain co-occurring conditions (e.g. hearing impairment, epilepsy) may affect vision care for children with ASD in terms of both the child’s ability to complete vision testing and diagnostic overshadowing. Additional research in these areas is, therefore, warranted.

To more comprehensively understand vision care—including how practice guidelines are followed—for children with ASD, longitudinal research using more robust vision care measures (i.e. the timing, frequency, and quality of vision screening and evaluation) would also be beneficial. This study only used parent-reported measures of visual impairment and vision care. For this reason, integration of more specific visual impairment (i.e. beyond refractive errors) measures and more extensive vision care measures reported by providers would also strengthen future study. Given this study’s focus on the treatment of refractive errors with corrective eyeglasses, further information regarding the treatment (e.g. surgery, eye drops, medication) of visual impairment more broadly in children with ASD would be another helpful future research direction.

Conclusion

Even in this highly engaged, clinic-based sample of school-aged children with ASD, many children did not meet some of the national guidelines for visual examination by an ophthalmologist or optometrist in the past 2 years. Linkages between vision testing and certain sociodemographic characteristics (e.g. parent education level) further highlight specific subgroups of children with ASD that should be targeted to improve vision care. Associations of child and family functioning characteristics with corrective eyeglasses being prescribed and worn as recommended additionally suggest that children with ASD who present with greater impairment and/or those whose families report high caregiving burden may be at the greatest risk for disparities in vision treatment. Family, provider, and delivery system-oriented intervention strategies (e.g. ASD tailored vision examination protocols, direct intervention to support highly stressed families in adhering to care recommendations) should be adapted and disseminated to reduce vision care disparities and help optimize health for children with ASD.

Supplemental Material

VisionRCBA_Supplemental_Final – Supplemental material for Vision care among school-aged children with autism spectrum disorder in North America: Findings from the Autism Treatment Network Registry Call-Back Study

Supplemental material, VisionRCBA_Supplemental_Final for Vision care among school-aged children with autism spectrum disorder in North America: Findings from the Autism Treatment Network Registry Call-Back Study by Olivia J Lindly, James Chan, Rachel M Fenning, Justin G Farmer, Ann M Neumeyer, Paul Wang, Mark Swanson, Robert A Parker and Karen A Kuhlthau in Autism

Footnotes

Acknowledgements

This work was conducted through the Autism Speaks Autism Treatment Network. This information or content and conclusions are those of the author and should not be construed as the official position or policy of, nor should any endorsements be inferred by HRSA, HHS, the US Government, or Autism Speaks. This work was conducted through the Autism Speaks Autism Treatment Network serving as the Autism Intervention Research Network on Physical Health.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This Network activity was supported by Autism Speaks and cooperative agreement UA3 MC11054 through the US Department of Health and Human Services, Health Resources and Services Administration, Maternal and Child Health Research Program to Massachusetts General Hospital.

ORCID iDs

Olivia J Lindly

Ann M Neumeyer

Paul Wang

Mark Swanson

Supplemental material

Supplemental material for this article is available online.

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