The scope of this page is autism spectrum disorder (ASD) across the lifespan. For more detailed information and resources about social communication disorders across the lifespan, see the Social Communication Disorder Practice Portal page.
In support of critical considerations for neurodiversity and neurodiversity-affirming care, ASHA encourages providers to be familiar with Communication About Autism: Terminology Considerations.
This Practice Portal page will use the terms “person with autism,” “person with ASD,” “autistic person,” and “person on the autism spectrum,” reflecting diverse identities within the autism community. The term “autism” is generally used in this document, and the term “autism spectrum disorder (ASD)” is used when referring specifically to the diagnosis defined in the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, Text Revision (DSM-5-TR; American Psychiatric Association [APA], 2022). The terminology on this page is monitored on an ongoing basis. Clinicians are advised to use the terminology that their client identifies with best.
See the Autism Evidence Map for summaries of the available research on this topic.
The DSM-5-TR (APA, 2022) defines autism spectrum disorder (ASD) as a neurodevelopmental disorder characterized by deficits in social communication and social interaction and the presence of restricted, repetitive behaviors.
Clinicians consider the various models of disability that may impact service delivery and clinical decisions. Clinicians’ understanding of different models of disability may inform their clinical philosophies. There are several models of disability, but two types are the most well-known.
The medical model of disability views disability through a deficit- or disorder-based lens, where “typical” or “normal” bodies and neurotypes are the end goal of interventions and services (Gaddy & Crow, 2023). Under this model, ASD is a medical diagnosis (as defined above by the DSM-5-TR [APA, 2022] diagnostic criteria). Many service funding sources, such as medical insurance, use a medical model of disability when determining clients’ services and funding eligibility. As such, the medical model of disability can inform the following outcomes and decisions:
Clinicians use codes from the International Classification of Diseases and Related Health Problems, 10th Revision, Clinical Modification (ICD-10-CM; World Health Organization, 2001) and from Current Procedural Terminology® (CPT) on claims and in documentation for reimbursement. For more information about coding, see The ASHA Leader article, “The Right Codes for ASD-Related Services” (Swanson, 2019).
The social model of disability views disability as a natural part of life, in which a person is not disabled by an inherent “defect”; rather, a person is disabled by societal attitudes toward their difference(s), lack of effective accessibility and supports, and lack of inclusion by people and groups in the social majority (Gaddy & Crow, 2023). Autism is part of a person’s identity. Disability is a part of the person’s lived experience. This lived experience informs clinical practice and how it is carried out—such as using strengths-based approaches, providing accommodations, and providing person-centered care. Neurodiversity-affirming clinicians consider the social model of disability in their practice. It is important for clinicians to understand the different models of disability when providing individualized care.
The criteria specified in the DSM-5-TR (APA, 2022) reflect several changes from those in the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision (DSM-IV-TR; APA, 2000). The most notable change eliminated the Pervasive Developmental Disorder (PDD) category, which included diagnoses of Autistic Disorder, Asperger’s Disorder, Childhood Disintegrative Disorder, Rett’s Disorder, and Pervasive Developmental Disorder Not Otherwise Specified.
The DSM-5-TR (APA, 2022) criteria for ASD (the term used in place of PDD) encompass the social and behavioral deficits typically associated with these populations but no longer specify subtypes. Although subtypes are no longer specified, the DSM-5-TR notes, “Individuals with a well-established DSM-IV diagnosis of autistic disorder, Asperger’s disorder, or pervasive developmental disorder not otherwise specified should be given the diagnosis of autism spectrum disorder” (APA, 2022, p. 57). The DSM-5-TR lists Rett syndrome, a genetic disorder, as a separate diagnosis in which disruptions of social interaction may be observed during the regressive phase.
According to the DSM-5-TR, individuals who meet the specified criteria are given the diagnosis of “autism spectrum disorder” with one of three severity levels of support. Each severity level specifies the amount of support needed for the individual’s social communication skills and degree of restricted, repetitive behaviors. Levels of support may vary by context and may fluctuate over time.
The incidence of autism spectrum disorder (ASD) refers to the number of new cases identified in a specified time period. The prevalence of ASD refers to the number of individuals who are living with ASD in a given time period.
In 2020, the estimated ASD prevalence was 2.76% (1 in 36) of children 8 years of age (Maenner et al., 2023). The 2021 National Survey of Children’s Health (NSCH; Maternal and Child Health Bureau, 2022) estimated the parent-reported ASD prevalence to be 3.1% of children aged 3–17 years (Wang et al., 2023).
The percentage of the population ages 5–21 years served under Part B of the Individuals with Disabilities Education Improvement Act of 2004 under the category of autism was 1.2% (U.S. Department of Education, 2023).
The prevalence of autism among Medicaid-enrolled adults was 0.95% in 2019 (Rubenstein et al., 2023).
According to data from the Centers for Disease Control and Prevention, ASD prevalence was significantly higher in boys (4.3%) than in girls (1.14%), with an overall prevalence ratio of 3:8 (male:female). Results were reported based on gender; however, there were no indications as to whether the data collected were based on sex assigned at birth and/or gender identity (Maenner et al., 2023). The pooled prevalence of autism in gender-diverse individuals was 11% (Kallitsounaki & Williams, 2023).
The estimated ASD prevalence for non-Hispanic White children (24.3 per 1,000) and children of two or more races (22.9 per 1,000) was lower than that for non-Hispanic Black children (29.3 per 1,000); Hispanic children (31.6 per 1,000); and non-Hispanic Asian/Pacific Islander children (33.4 per 1,000). The prevalence of ASD among non-Hispanic American Indian or Alaska Native children (26.5 per 1,000) was similar to that of other racial and ethnic groups. This report found no consistent association between ASD and socioeconomic status (Maenner et al., 2023).
The prevalence of autism among individuals diagnosed with a variety of conditions was as follows (Richards et al., 2015):
The estimated global prevalence of autism by region was as follows (Olusanya et al., 2023):
Views of neurodivergence influence motivation to seek services. Some autistic people may not wish to pursue diagnosis and/or treatment, whereas some seek support. Completely accurate numbers are difficult to obtain due to possible under- or overidentification, lack of a biological marker, variations in the quality and quantity of behavioral information in records, and other factors (Mulvihill et al., 2009). Individuals with autism and other co-occurring developmental conditions may be underdiagnosed, as having multiple conditions may lead to a misdiagnosis or delay in autism diagnosis. There is also a need to improve diagnostic tools to recognize autism in adults who may have been misdiagnosed or previously unidentified (Interagency Autism Coordinating Committee, 2023).
To date, diagnostic tools have typically been developed in studies where the participants were predominantly assigned male at birth, leading to underdiagnosis in individuals assigned female at birth. Diagnostic bias may account for the variations in reported incidence and prevalence pertaining to sex assigned at birth (McCrossin, 2022). Significant variations exist in social communication norms across cultures in the United States. These social norms may not be reflected in screening and diagnostic tools, potentially resulting in over- and underidentification in marginalized groups.
In addition, access to services influences disparities. A cross-sectional study mapped resource allocation to marginalized populations along with prevalence data to analyze access to services as a factor in prevalence. Findings revealed that Black and Hispanic children experienced more disparities in access to services as compared to White children (Liu et al., 2023).
The core features of autism spectrum disorder (ASD) are observed in the areas of
These core features are significantly influenced by (a) the developmental level of language acquisition (e.g., pre-symbolic language, emerging language, and conversational language) and (b) the severity level of the disorder. In addition to these core features, sensory and feeding challenges may also be present.
People with autism have a wide range of abilities and experiences. Abilities range from significant cognitive and language impairments to above-average cognitive and language abilities. However, regardless of these differences, the core characteristics and challenges associated with autism will have an impact on the development of social communication skills. The lack of community awareness of autism and the absence of opportunities to interact with people on the autism spectrum may result in miscommunication and misperceptions of behaviors. Misperceptions of behaviors, misdiagnosis, and lack of proper supports for children might place them at risk for becoming part of the “school-to-confinement pipeline” population (Stanford, 2020).
Below are common characteristics based on domain. Specific areas of deficit will vary. No one person will be the same. Skilled interventions may require adaptations to the environment, accommodations to make activities accessible, and/or the development of treatment goals.
Social communication includes joint attention, social reciprocity, and social cognition.
Joint attention is the shared focus of two or more individuals on the same object or event.
People with ASD and their neurotypical communication partners frequently experience social communication breakdowns due to what Milton (2012) describes as the double empathy problem— framed as the neurotypical person and the autistic person communicating from different perspectives, world views, and social perceptions. Society misunderstands autistic behavior and continues the stereotype which asserts that autistic people lack empathy. Autistic people do have empathy but may show unconventional ways of caring (DeThorne, 2020). Autistic communication is more apparent to other people when interacting with a non-autistic person than with an autistic person (Crompton et al., 2020). Non-autistic peers may avoid that person or may react to social overtures in a negative way (e.g., by teasing or bullying).
Joint attention might look like
Joint attention deficits that could require skilled services include the following:
Social reciprocity is the back-and-forth interaction between people, during which the behavior of each person influences the behavior of the other person.
Social reciprocity might look like
Social reciprocity deficits that might require skilled services include the following:
Social cognition refers to the mental processes involved in perceiving, attending to, remembering, thinking about, and making sense of the people in our social world (Moskowitz, 2005).
Social cognition might look like
Social cognition deficits that might require skilled services include the following:
Language and related cognitive skills might look like
Language and related cognitive skills that might require skilled services in one or more of the following seven areas:
Behaviors and emotions might look like
Behavioral and emotional challenges that might require skilled services include the following:
Sensory and feeding may look like
Sensory and feeding challenges that might require skilled services include the following:
Diagnostic features of ASD are present in very young children. Most families and caregivers report observing symptoms within the first 2 years of life and typically express concern by the time the child reaches 18 months of age.
Studies of children with ASD found the following:
It is well documented that more boys than girls are diagnosed with ASD (e.g., Baio et al., 2018). A diagnostic bias toward characteristic ASD traits as they present in boys makes it easy to miss ASD traits as they present in girls (Dworzynski et al., 2012). Autistic girls demonstrate more neurotypical social interaction and communication skills compared to autistic boys (Wood-Downie et al., 2021). In addition, girls also tend to have fewer and less unusual repetitive, stereotyped behaviors than boys (Mandy et al., 2012). Gender stereotypes and expectation bias may also add to the underdiagnosis of girls (Whitlock et al., 2020). Girls who do meet the diagnostic criteria for ASD during early childhood tend to have additional challenges (lower cognitive ability and/or additional behavioral problems). This is not the case for boys (e.g., Dworzynski et al., 2012; Lord & Schopler, 1985). See the Assessment section for information about autism in transgender and gender-non binary people.
Autistic people and people with a medical diagnosis of autism frequently have co-occurring conditions. For example, 97% of children with public health insurance and autism, or ASD, were reported to have at least one co-occurring health condition (Center for Medicaid and CHIP Services, 2024). Such co-occurring conditions are not necessarily present in every person.
These co-occurring conditions could include
Speech- and language-related disorders can also co-occur with ASD. These disorders include the following:
Autism spectrum disorder (ASD) is medically diagnosed based on differences in communication development and other signs and symptoms resulting from differences in brain structure. Researchers have devoted considerable efforts to investigating etiological factors. Understanding the biomarkers of autism can lead to more efficient screening and diagnosis/identification, which would then connect people to services sooner (Interagency Autism Coordinating Committee [IACC], 2023). Although no single cause has been identified, the available data suggest that autism results from different sets of causal factors—including genetic, neurobiological, and environmental factors.
Researchers largely agree that ASD is the result of hereditable genetic differences and/or mutations. For example, ASD is most likely linked to genetic differences associated with the X chromosome (Chakrabarti & Fombonne, 2005). People with a medical diagnosis of autism may also be more likely to have a younger sibling with an autism diagnosis (Ozonoff et al., 2011).
A genetic code may result in different brain development—which can lead to differences in structure and function, cognition and neurobiology, and behaviors (D. Williams, 2012). These behaviors demonstrate how the brain may respond differently to the environment, such as a different neural response to eye gaze (Elsabbagh et al., 2012).
Researchers have begun to investigate how pre- and postnatal environmental factors (e.g., dietary factors, exposure to drugs, environmental toxicants, parental factors) might influence autism.
More research is needed to fully understand potential environmental factors, including specific exposures and gene–environment interactions (IACC, 2023).
For more information on the potential causes of autism, see Question 2 and Question 3 of the 2021–2023 IACC Strategic Plan for Autism Research, Services, and Policy (IACC, 2023).
Speech-language pathologists (SLPs) play a central role in the screening, assessment, diagnosis, and treatment of persons with autism spectrum disorder (ASD). The professional roles and activities in speech-language pathology include clinical/educational services (diagnosis, assessment, planning, and treatment); prevention and advocacy; and education, administration, and research. See ASHA’s Scope of Practice in Speech-Language Pathology (ASHA, 2016).
The role of the SLP, often on an interprofessional team, is to provide skilled services to people who have been diagnosed with ASD and are developing communication skills based on their unique needs. There are autistic traits that may help with diagnosis but that do not require intervention or change.
SLPs provide skilled interventions that are either medically necessary or educationally necessary to support a person with a diagnosis of ASD in achieving their communication or feeding goals. The Code of Ethics (ASHA, 2023) states that the clinician must serve the best needs of the client using evidence-based practices.
The combination of (a) evidence-based, peer-reviewed research, (b) clinical experience, and (c) autistic voices can help clinicians determine how to develop and implement culturally responsive and neurodiversity-affirming treatment plans.
Appropriate roles for SLPs are as follows.
As indicated in the Code of Ethics (ASHA, 2023), SLPs who serve this population should be specifically educated and appropriately trained to do so.
Interdisciplinary collaboration in assessing and diagnosing ASD is important due to the complexity of the disorder, the varied aspects of functioning affected, and the need to distinguish ASD from other disorders or medical conditions (Hyman et al., 2020). Timely diagnosis allows for timely supports and skilled services, both of which facilitate positive outcomes (IACC, 2023).
Ideally, the SLP is a key member of an interdisciplinary team with expertise in diagnosing ASD. When there is no appropriate team available, an SLP—who has been trained in the clinical criteria for ASD and who is experienced in diagnosing developmental disorders—may be qualified to diagnose these disorders as an independent professional.
State speech-language pathology licensing boards do not always specify whether the diagnosis of ASD and other conditions is expressly within a licensee’s scope of practice. Moreover, licensing agencies—such as a state medical board—for other health professions may set rules that prohibit SLPs from diagnosing ASD independently.
School districts and employers in other settings may also have policies regarding the professionals who can establish the diagnosis. In addition, payers (Medicare, Medicaid, commercial, or private insurers) typically require a diagnosis by a physician, a psychiatrist, or another medical professional for coverage of services.
SLPs are responsible for understanding the requirements in place in their state, in their setting, and by payer so that appropriate services are not delayed. Please see ASHA’s state-by-state resources for state licensing requirements and contact information. ASHA also provides tracking of state insurance mandates for ASD. For questions regarding specific payer requirements, please contact reimbursement@asha.org.
See the Assessment section of the Autism Evidence Map for pertinent scientific evidence, expert opinion, and client/care partner perspective.
Interdisciplinary collaboration and family involvement are essential in assessing and identifying autism. The speech-language pathologist (SLP) is a key member of an interdisciplinary team that includes the child’s pediatrician, a pediatric neurologist, a psychologist, and a developmental pediatrician. Several available algorithms and tools are available to help physicians develop a strategy for early identification of children with autism spectrum disorder (ASD; Plauché Johnson & Myers, 2007).
Consistent with the World Health Organization’s (WHO) International Classification of Functioning, Disability and Health (ICF) framework (ASHA, 2023; WHO, 2001), assessment is conducted to identify and describe functioning, disability, and contextual factors.
See ASHA’s resource on the International Classification of Functioning, Disability, and Health (ICF) and examples of the ICF framework specific to selected disorders.
The benefits of early, accurate diagnosis of ASD are as follows:
Any diagnosis of ASD—particularly of young children—is periodically reviewed by members of the interdisciplinary team because diagnostic categories and conclusions may change as the child develops.
The identification of early behavioral indicators can help families and caregivers obtain appropriate diagnostic referrals and access early intervention services, even before a definitive diagnosis is made (Woods & Wetherby, 2003). Early intervention may improve long-term outcomes for many children (Dawson & Osterling, 1997; Dawson et al., 2010; Harris & Handleman, 2000; Landa & Kalb, 2012). There also may be benefits of providing intervention that targets prelinguistic communication to infants who may be autistic (Bradshaw et al., 2015; L. K. Koegel et al., 2014).
A diagnosis guides the team to focus supports and services that may facilitate options for functional communication development, inform social and psychosocial accommodation recommendations, and identify opportunities to connect with the autistic community to learn more about the lived experiences of autistic self-advocates. While severity rating is included in the diagnosis, it should not be used to determine eligibility for any service.
The diagnosis describes the features of autism and identifies common traits of the autistic community. Seeking a diagnosis may help an individual determine what interventions might support personal goals that improve independence and employability. Skilled services can be recommended to improve health and educational outcomes.
Some autistic people are not diagnosed until later school age, adolescence, or even adulthood. This can happen because they appear to succeed in some or most academic subjects, particularly in their early school years. However, those who are identified later in life show challenges with social engagement and social communication. This can significantly affect their ability to adjust to social demands in later academic and community settings and in the workplace (Gilchrist et al., 2001; Mueller et al., 2003; Tsatsanis et al., 2004). Interventions may need to address the gap between cognitive potential and social adaptive functioning.
Camouflaging may be another potential reason why people are diagnosed with autism later in life. Camouflaging, including masking, is a learned coping strategy that autistic people use to (a) hide their autistic behavior that might be deemed socially unacceptable or (b) “perform” neurotypical social behavior (Lai et al., 2017; Willey, 1999). Autistic people may camouflage but may not realize that they are doing it. Here are some examples of camouflaging and masking (Cook et al., 2022):
All genders can camouflage, but autistic females are more likely to camouflage and mask their autistic traits (Alaghband-rad et al., 2023; Lai et al., 2017). Camouflaging and masking takes a lot of cognitive energy. Higher camouflaging has been associated with excessive stress, anxiety, and depression (Adams et al., 2023; Alaghband-rad et al., 2023; Lai et al., 2017).
Some adults have lived with undiagnosed ASD and seek services only when they start experiencing challenges at work, in social relationships, or in academic settings (Brugha et al., 2011). Some people may find a diagnosis of ASD in adulthood as a relief. But for many, it can come as a surprise and may be difficult to accept, even if it helps explain some of the challenges that they have been experiencing. Therefore, it is essential to give the diagnosis with utmost sensitivity. See ASHA’s Practice Portal page on Counseling in Audiology and Speech-Language Pathology.
Adult diagnosis is complicated by the fact that (a) there is limited information about the developmental trajectory of adults with autism and (b) there are no standard screening and diagnostic tools for ASD in adults (Interagency Autism Coordinating Committee [IACC], 2023). There is also a lack of services and supports for adults with autism. The importance of involving professionals from multiple disciplines cannot be overstated, especially because many adults receiving an ASD diagnosis for the first time can have other related concerns (e.g., mental health; Geurts & Jansen, 2012). SLPs with expertise in assessing social communication, higher level language, conversation, and discourse are integral members of this team.
For a comprehensive discussion on autism across the lifespan, see Question 6 of the 2021–2023 IACC Strategic Plan for Autism Research, Services, and Policy (IACC, 2023).
Social communication is influenced by the core characteristics of autism. Variations in norms for social communication exist within and across cultures. The core characteristics of ASD may be viewed through a cultural lens leading to under-, over-, or misdiagnosis (Taylor Dyches et al., 2001; Tek & Landa, 2012). Patient- and family-centered care is essential to providing culturally responsive care. Ethnographic interviewing during a case history provides an opportunity for patients, families, caregivers, and care partners to describe their daily communication and the communication norms that exist in the home. When examining the patient’s social communication, the clinician compares it to the expectations and norms that exist in the home for the family and/or caregiver. For example, direct eye contact with an adult may be considered respectful or disrespectful—depending on one’s culture. If clinicians note variations in eye contact—without knowing how the family views eye contact culturally—then the clinician would not be able to make conclusions.
Lack of familiarity with cultural influences may contribute to the disparity in the diagnosis of ASD among some racial and ethnic groups (Begeer et al., 2009; Taylor Dyches, 2011). In studies examining the length of time that it takes a clinician to diagnose ASD in African American children, parents indicated that they shared concerns with professionals nearly 3 years prior to diagnosis (Constantino et al., 2020). African American children with ASD were more likely than Hispanic and White children to be classified with a co-occurring intellectual disability (Maenner et al., 2023). It took Latino/a/x children an average of eight visits to receive a diagnosis (Iland et al., 2012). Researchers suggested, in part, that disparities may be due to a lack of health care provider training in recognizing ASD in children of color (Aylward et al., 2021).
According to a study of children in which researchers examined self-report and parent report, there are more nonbinary and trans people who are autistic than who are not autistic (Corbett et al., 2023; Warrier et al., 2020). Most diagnostic tools were developed on the basis of cisgender norms that were determined by sex assigned at birth. This suggests that transgender and gender-nonconforming people may be more likely to have undiagnosed autism (Warrier et al., 2020).
Core values and beliefs can affect the family’s views of autism and their decisions regarding services (Burkett et al., 2015; Wilder et al., 2004). For example, autism may be viewed in a negative light, and the family feels that it needs to be hidden from others. This, in turn, may influence the type of care that the family seeks. Signs and symptoms that are clearly “red flags” in the U.S. health care or educational system may not be viewed in the same way by someone from a culture that does not formally define the disorder.
See ASHA’s Practice Portal page on Cultural Responsiveness. See also Taylor Dyches (2011) for a discussion of diverse perspectives on symptoms of autism.
The goal of screening is to detect developmental delays and other factors that might signal ASD—such as a child being referred to the early intervention system or a child who is the younger sibling of someone with autism. See ASHA’s Practice Portal page on Early Intervention.
Screening tools for early identification are available. One screening tool identifies prelinguistic behavioral vulnerabilities in infants 6–18 months of age (Bryson et al., 2008). Another tool—a broadband screener—identifies communication delays (including ASD) in children 9–24 months of age (Pierce et al., 2011; Wetherby et al., 2008). Also available are questionnaire-based tools that can screen children who may have ASD as early as 12 months of age (Turner-Brown et al., 2012). Any screening tool should be culturally and linguistically appropriate and have strong psychometric features to support its accuracy.
Screening typically includes
Screening procedures evaluate the main characteristics that differentiate ASD from other developmental disorders, including difficulties in
Social communication norms vary across cultures. When screening is conducted for nonlinguistic aspects of communication, it is important to recognize when differences are related to cultural variances rather than to a communication disorder. See ASHA’s Practice Portal page on Cultural Responsiveness.
Loss of language or social skills at any age should be considered grounds for screening. In cases where children are being raised in a bilingual environment, consider whether language loss is attributable to language attrition. See ASHA’s Practice Portal page on Multilingual Service Delivery in Audiology and Speech-Language Pathology.
Because children with ASD are often initially suspected of having a hearing problem, audiologists play a critical role in (a) recognizing the possible signs of ASD in children whose hearing they test and (b) making appropriate referrals for screening.
Individuals who may have ASD based on screening results are referred to an SLP and other professionals, as needed, for a comprehensive assessment. A comprehensive assessment is functional and is sensitive to the wide range of acceptable social norms within and across communities and cultures. It involves the collaborative efforts of families, caregivers, care partners, classroom teachers, SLPs, special educators, and psychologists, as needed.
A culturally responsive partnership between the SLP and the family facilitates the assessment process and acknowledges the diverse needs of the individual and their family and/or care partners (Pearson et al., 2018). See ASHA’s Practice Portal page on Cultural Responsiveness.
The comprehensive assessment typically includes the following components:
The comprehensive assessment may also include two additional testing components:
The comprehensive assessment may result in
Individuals with hearing loss may present with symptoms similar to those of ASD, particularly in the areas of communication and socialization. For example, children with hearing loss might display the following autistic-like behaviors:
But, it is also possible that a deaf and hard of hearing person is also autistic (Easterbrooks & Handley, 2005; Malandraki & Okalidou, 2007; Szymanski & Brice, 2008). Knowing a child’s hearing acuity prior to an ASD assessment is a fundamental step in ensuring a reliable diagnosis and in further understanding if a child has hearing loss, has ASD, or has both conditions concurrently.
The potential similarities in presentation between hearing loss and ASD (e.g., a lack of response when someone calls their name)—and the possibility that both conditions might be co-occurring—can make diagnosis challenging. Currently, no ASD screening and assessment measures are validated for use with children who have hearing loss (Szarkowski, Mood, et al., 2014). Often, there is a delay in ASD diagnosis in individuals with both ASD and hearing loss (Szarkowski, Flynn, & Clark, 2014). More research is needed on the assessment of ASD for those who use American Sign Language (ASL) as their primary language (Szarkowski, Mood, et al., 2014).
Some characteristic behaviors associated with ASD can make it challenging to obtain valid and reliable hearing assessment results. These behaviors include (a) comfort with “sameness” and an aversion to novel situations; (b) hypersensitivity and negative responses to sensory input; and (c) communication differences, such as receptive language deficits and unreliable pointing gestures (Davis & Stiegler, 2005; Stiegler & Davis, 2010).
Suggestions for assessing hearing in individuals with these and other challenging behaviors are as follows:
See Scope of Practice in Audiology (ASHA, 2018c).
To obtain the most true and accurate assessment results, the clinician confirms a person’s hearing status before assessing them. SLPs can use both formal and informal assessment approaches. Formal testing may be required if a diagnosis or eligibility for services has yet to be determined. Informal testing may be most useful for determining whether the person has met specific communication milestones or for assessing communication skills in everyday settings. See ASHA’s resource on assessment tools, techniques, and data sources, which SLPs can use in a comprehensive communication assessment.
The SLP might use dynamic assessment to identify nonsymbolic and symbolic communication behaviors and to evaluate individual learning potential (Pea, 1996; Snell, 2002). Conversation analysis (Yu & Sterponi, 2022) is an additional option for dynamic assessment. It is a form of spontaneous language sampling that provides a realistic picture of an autistic person’s language—including echolalia—and social communication without the assumptions that come with structured questionnaires, interviews, and tests (Yu & Sterponi, 2022).
A comprehensive speech and language assessment includes testing of skills in language, speech, feeding and swallowing, and AAC.
Expressive language. Assessment of spoken language includes language expression and language comprehension (see ASHA’s Practice Portal page on Spoken Language Disorders). The clinician assesses all means of expressive language—verbal (including echolalia) and nonverbal (including gestures)—for communicative function and intent (see, e.g., Cohn et al., 2022; Watson et al., 2013). Language sampling and narrative analysis are essential pieces to the comprehensive assessment, especially if the child uses forms of echolalia.
Communicative functions of echolalia. Historically, echolalia has been described as meaningless and without communicative function. However, a growing body of research has identified various communicative functions of echolalia (e.g., turn-taking, labeling, requesting, affirming, and protesting) and has suggested its role in gestalt language acquisition (Prizant, 1982, 1983; Prizant & Duchan, 1981; Prizant & Rydell, 1984; Stiegler, 2015). SLPs can consider the theory of gestalt language acquisition and the role of echolalia in assessment procedures (e.g., assessing communicative function of echolalia) and treatment approaches to language intervention (see, e.g., Blanc et al., 2023; Luyster et al., 2022). However, clinicians may need to be cautious of overgeneralizing gestalt language acquisition to autistic language development (Hutchins et al., 2024).
Written language. This includes reading decoding, reading comprehension, written expression, and writing for varied audiences. See ASHA’s Practice Portal page on Written Language Disorders.
Social communication. Assessment of social communication may vary based on familial and cultural norms. Components of social communication assessment may include the following:
Speech. A speech sound disorder, including a motor speech disorder, can result in a person having significant difficulty producing speech or, possibly, an inability to speak. Motor speech disorder in autistic people who use part-time oral speech can be characterized by reduced intelligibility, decreased precision, and difficulty with speech coordination (Maffei et al., 2024).
Speech difficulties are not the same as language and social communication problems. For example, when a speech sound disorder results in lack of speech or highly unintelligible speech, someone might assume that the individual is nonverbal. However, they may have average to above-average language and communication abilities (see, e.g., Tierney et al., 2015). See ASHA’s Practice Portal pages on Speech Sound Disorders: Articulation and Phonology and Childhood Apraxia of Speech.
Feeding and swallowing. See ASHA’s Practice Portal page on Pediatric Feeding and Swallowing.
AAC. See ASHA’s Practice Portal page on Augmentative and Alternative Communication (AAC).
Following a diagnosis of ASD, clinicians conduct ongoing assessments. Reasons may include, but are not limited to, the following:
As part of the ongoing assessment process, clinicians can use alternative approaches such as dynamic assessment to identify skills that an individual has achieved, skills that may be emerging, and the contextual supports that enhance communication skills (e.g., AAC or modeling). The dynamic assessment framework uses a test–teach–retest model. This allows the clinician the opportunity to observe how quickly new skills are learned.
Within a public school setting, eligibility for services under the disability category of autism is based on the definition of autism provided in the Individuals with Disabilities Education Improvement Act of 2004 (IDEA, 2004):
Autism means a developmental disability significantly affecting verbal and nonverbal communication and social interaction, generally evident before age three, that adversely affects a child’s educational performance. Other characteristics often associated with autism are engagement in repetitive activities and stereotyped movements, resistance to environmental change or change in daily routines, and unusual responses to sensory experiences . . . . Autism does not apply if a child’s educational performance is adversely affected primarily because the child has an emotional disturbance, as defined by IDEA . . . . a child who manifests the characteristics of autism after age three could be identified as having autism if the criteria in 300.8(c)(1) are satisfied.
Social communication challenges affect participation and progress in the general education curriculum. The pervasive nature of social communication challenges in individuals with ASD supports the eligibility criteria for services in schools.
Individuals who have been diagnosed with ASD via other sources of clinical criteria—such as the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, Text Revision (DSM-5-TR; American Psychiatric Association, 2022)—are likely to be eligible for special education services under the autism category, as defined above, due to (a) deficits in social communication functioning across severity levels and (b) the determination of educational benefit.
To determine a person’s eligibility for educational services, the clinician uses a variety of strategies for gathering information, including
Regardless of the assessment measures or tools that they use, the clinician needs to be aware of any subtle signs and symptoms consistent with a diagnosis of ASD.
IDEA (2004) requires an initial determination as outlined in Section 300.301 to inform the decision-making process regarding eligibility for special education and related services. Some possible criteria to consider are listed below, with reference to ASD as relevant.
Cognitive referencing. This practice of comparing IQ scores and language scores to determine eligibility for speech-language intervention assumes that language functioning cannot surpass cognitive levels. Consequently, if language functioning is commensurate or consistent with cognitive skills, no further gains can be made through intervention. Research had demonstrated that children with disabilities whose language and cognitive levels were commensurate nonetheless benefit from language intervention (Cole et al., 1990). See ASHA’s resource on cognitive referencing.
Chronological age. This argument suggests that individuals with disabilities are either “too young” or “too old” to benefit from communication services. However, research shows that infants, toddlers, and preschoolers with ASD do benefit from communication services and supports (Garfinkle & Schwartz, 2002; L. K. Koegel et al., 2014; Lawton & Kasari, 2012; Pierce et al., 2011). In addition, individuals with ASD can continue to develop communication abilities across their lifespan (Hamilton & Snell, 1993; Pickett et al., 2009; Watanabe & Sturmey, 2003).
Diagnostic label. The term “severe disability” is used to describe a variety of diagnostic labels that identify a significant communication impairment. However, research shows that individuals with severe disabilities—regardless of the underlying diagnosis—can learn to communicate effectively. In the case of ASD, social communication impairment is a core feature (Baron-Cohen et al., 1992; DiLavore et al., 1995; Lord & Corsello, 2005). Therefore, a diagnosis of ASD indicates the inclusion of communication services. Research has indeed demonstrated the benefits of instruction and support for individuals with ASD (Hamilton & Snell, 1993; Mirenda et al., 2000; Wetherby et al., 2000).
Absence of cognitive or other prerequisite skills. This practice presumes that certain skills and performance criteria are necessary to benefit from communication services and supports, based on the interpretation shared by some research findings (Miller & Chapman, 1980; Shane & Bashir, 1980). However, subsequent research shows that individuals (including those with ASD) who do not demonstrate supposed prerequisites can benefit from appropriate communication services and supports (Amato et al., 1999; Bondy & Frost, 1998; Moes & Frea, 2002).
Failure to benefit from previous communication services. Lack of progress in therapy is often attributed to a lack of “potential” to benefit from services. But lack of progress can be tied to other factors—including inappropriate goals, unsuitable intervention methods, failure to incorporate assistive technology, or insufficient methods in measuring outcomes (National Joint Committee for the Communication Needs of Persons With Severe Disabilities, 2003). Access to communication services and supports should not be denied because of failure to progress as a function of these other factors. Rather, previously unsuccessful therapy experiences should be examined to help determine ways in which communication services and supports can be better tailored to meet the individual’s unique communication needs.
Lack of funding or adequately trained professionals. A lack of funding and expertise often fuels exclusionary practices. If trained professionals are not available, then there is an obligation either to find trained professionals or to train existing professionals (Timothy W. v. Rochester, New Hampshire School District, 1989). Similarly, lack of funding does not constitute a reason for exclusion from communication services and supports. IDEA (2004) mandates that identified needs must be met.
SLPs are instrumental in differentiating between autism, social communication disorder, and other neurodevelopmental disorders or conditions. Accurate diagnosis ensures that individuals with ASD and those with social communication disorder gain access to services. See ASHA’s Practice Portal page on Social Communication Disorder.
Diagnostic features also differ by gender. Differences in the social landscape of girls may make it easier for them to camouflage or mask their social differences. For example, the social groups that girls form on the playground are “fluid.” Girls with autism stay near peer groups and, to an observer, look similar to non-autistic girls. Most boys, on the other hand, usually play structured games on the playground. Boys with ASD tend to spend more time wandering and, therefore, do not appear similar to their peers who are not on the spectrum (Dean et al., 2017).
Whether or not they have had difficulties with language acquisition, all people with an ASD diagnosis are eligible for speech-language services due to the pervasive nature of the social communication impairment. Therefore, SLPs advocate for inclusion of language intervention for individuals diagnosed with ASD and ensure that individuals with ASD also receive a diagnosis of a language disorder when they meet the criteria. See ASHA’s Practice Portal pages on Spoken Language Disorders and Written Language Disorders.
At its core, communication is a social process. People with ASD and their neurotypical communication partners frequently experience social communication breakdowns. These communication breakdowns are usually due to the double empathy problem (Milton, 2012). The double empathy problem is framed as the neurotypical person and the autistic person communicating from different experiences, world views, and social perceptions. Communication breakdowns occur because the neurotypical person and the autistic person have trouble with cognitively and emotionally empathizing with each other (Gaddy & Crow, 2023).
Individuals with ASD report a desire to have friendships and relationships despite their social communication challenges. However, due to the double empathy problem, peers often feel ineffective in social exchanges with an individual with ASD. Non-autistic peers may avoid that person or may react to social overtures in a negative way (e.g., by teasing or bullying).
Family members, friends, teachers, and coworkers face the challenge of learning to recognize and respond to subtle bids for communication and to interpret the communication functions of challenging behaviors. See the National Joint Committee for the Communication Needs of Persons With Severe Disability’s resource on challenging behavior as communication.
See the Treatment section of the Autism Evidence Map for pertinent scientific evidence, expert opinion, and client/caregiver perspective.
Speech-language pathologists (SLPs) provide skilled services for people with autism spectrum disorder (ASD) across the lifespan. They work with people on the autism spectrum and their families to develop and meet their personal goals throughout their life. The goal of skilled services is to promote positive outcomes—not to force people with ASD to mask their autistic traits or to lose their identity (Interagency Autism Coordinating Committee [IACC], 2023).
SLPs also observe and document the skills of people with ASD—skills that might look different from those of their non-autistic peers. SLPs help the person build new skills using strengths to improve areas that negatively impact the autistic person’s daily functioning. Neurodiversity-affirming care, integrated with skilled services, develops skills that support the autistic child’s identity while helping them learn and develop. See Crow’s (2024) neurodiversity-affirming flowchart [PDF]. This flowchart was originally published as part of the ASHA Professional Development course, “Neurodiversity-Affirming Speech-Language Services and Early Intervention” (Crow, 2024).
Not all people will want to seek skilled services. Those who do require speech and language services aim to improve their language and social communication skills. People on the autism spectrum can learn and apply skills needed to better develop relationships, navigate and function independently in educational and work settings, and actively participate in everyday life. SLPs often collaborate with other professionals to design and implement effective treatment plans.
The mode of communication used during treatment can vary. Mode of communication can include
More than one mode of communication can be used, such as part-time use of AAC systems (Koerner et al., 2023). Different types of AAC may be necessary in differing environments. Low-tech supports may enable quick access or assist unfamiliar communication partners. High-tech assistive technologies or SGDs allow the user to communicate more detailed ideas and offer auditory features. Multimodal communication systems are individualized according to the person’s preferences and abilities and according to the context of communication.
The goal of family-centered practice is to create a partnership so that the family fully participates in all aspects of the individual’s care. Participation of families in services for people with autism can help reduce the stress experienced by family members (National Research Council, 2001).
Support may take different forms at different times and may include the following:
See ASHA’s resources on person- and family-centered care and family-centered practice.
Patient-centered care encompasses gender- and neurodiversity-affirming care. It is culturally responsive and relevant. It ensures that identified goals embrace the priorities and preferences of the individual and family. Cultural, linguistic, and personal values should be incorporated into therapeutic activities. Clinicians also need to recognize that cultural, linguistic, and socioeconomic factors can affect a family’s access to—as well as selection and use of—services (Yu, 2013). Surveillance data reveal persistent disparities across demographic categories. Limitations in studies, most specifically considering the intersectionality of demographic categories, make it difficult to draw conclusions (Hotez & Shea, 2023). Screening for social determinants provides a framework for allowing considerations in access to services. See ASHA’s Practice Portal page on Cultural Responsiveness and ASHA’s resource on social determinants of health.
Advancements have been made in research on bilingual individuals with ASD. Research indicates that children with ASD who are being raised in bilingual language environments are not more likely to have language delays than their monolingual counterparts (Drysdale et al., 2015; Gilhuber et al., 2023; Hambly & Fombonne, 2012). Multilingual autistic children experience the same benefits of being multilingual as their multilingual non-autistic peers.
When determining the language of treatment for a child with ASD, SLPs carefully consider the child’s linguistic environments. Treatment is provided either by a multilingual SLP or by working with trained interpreters, when necessary. See ASHA’s Practice Portal pages on Multilingual Service Delivery in Audiology and Speech-Language Pathology and Collaborating With Interpreters, Transliterators, and Translators.
Treatment approaches differ in the method used to address goals. They range from discrete trial, traditional behavioral approaches to social-pragmatic, naturalistic developmental behavioral approaches (Prizant & Wetherby, 1998).
Approaches also differ in how goals are prioritized and addressed. Focused interventions rely heavily on individual strategies—used alone or in combination—to target specific skills or behaviors (e.g., to increase verbalization). Comprehensive interventions use multiple strategies to target a broad range of skills or behaviors (e.g., to enhance learning).
The selection of specific approaches takes the following factors into consideration:
Below are brief descriptions of general and specific treatment options for addressing ASD. The options are organized into broader categories; however, many options can fit into more than one broad category. For example, many options combine developmental approaches and behavioral teaching strategies.
SLPs who engage in neurodiversity-affirming behavioral interventions work on identifying environmental impacts that may affect the autistic person’s successful communication. SLPs create skilled, therapeutic opportunities for meaningful engagement with the autistic person to develop autonomy, teach self-regulation strategies, promote independence, and consider the person’s autistic identity.
This list is not exhaustive, and the inclusion of any specific treatment approach does not imply endorsement from ASHA. Many approaches have different available commercial programs. Some approaches and programs may require additional training and/or certification. This section will share general descriptions of treatment options that can support people on the spectrum. As autistic children become autistic adults, their needs change and so do the treatment approaches. For a more comprehensive list of treatment options, see the Treatment section of the Autism Evidence Map.
Behavioral interventions and techniques are designed to reduce behaviors that impact effective communication or nutrition and teach functional alternative behaviors using the basic principles of behavior change. These methods are based on behavioral/operant principles of learning. They involve examining the antecedents that elicit a certain behavior, along with the consequences that follow that behavior. Clinicians then adjust in this chain to increase desired behaviors and/or decrease inappropriate ones.
SLPs might apply behavior approaches to interventions. Many treatment approaches that target specific behaviors can fall into either traditional approaches or more contemporary behavior approaches. Intervention is customized based on the person’s needs, interests, and family situation.
Traditional Behavioral Approaches
Applied Behavior Analysis (ABA)—a behavioral intervention that focuses on bringing about meaningful and positive change in behavior. ABA techniques have been developed for individuals with autism to help build a variety of skills (e.g., communication, social skills, self-control, and self-monitoring) and to help generalize these skills to other situations. Providers use techniques in one-on-one or group instruction, structured settings (e.g., classroom), and everyday settings (e.g., family dinnertime). Supporters of traditional ABA may believe that highly structured approaches should be used as the main service for people with autism. Some people who oppose traditional ABA may believe that focusing on behavior correction removes autonomy and, thus, they support more child-led treatment approaches.
Intervention is customized based on the person’s needs, interests, and family situation. ABA techniques are often used in intensive, early intervention programs (with children younger than age 4 years) to address a full range of life skills. Intensive programs total 25–40 hours per week for 1–3 years. SLPs might collaborate with Board Certified Behavioral Analysts to maximize resources and promote optimal outcomes. See ASHA’s advocacy resource about ABA and Autism Evidence Map. See also the Resources section on this page for articles about SLPs working with ABA professionals.
Discrete Trial Training (DTT)—a one-on-one instructional approach using behavioral methods to teach skills in small, incremental steps in a systematic, controlled fashion. The teaching opportunity is a discrete trial consisting of an antecedent (such as an instruction from the teacher), a response from the learner, and a consequence or feedback regarding the response. DTT is most often used for skills that (a) learners are not initiating on their own; (b) have a clear, correct procedure; and (c) can be taught in a one-to-one setting.
Functional Communication Training (FCT)—a behavioral intervention program that combines the assessment of the communicative functions of maladaptive behavior with the use of ABA procedures to teach alternative responses. Problem behaviors can be eliminated through extinction and replaced with alternate, more appropriate ways of communicating needs or wants. FCT can be used with children with ASD across a range of ages and regardless of cognitive level or expressive communication abilities (Carr & Durand, 1985).
Naturalistic Developmental Behavioral Interventions (NDBI)
Activities and treatment targets are child-led, are presented in natural settings, and use developmental and spontaneous modeling. NDBI includes play-based behavioral approaches. A wide range of acceptable antecedents exist, as do a variety of acceptable responses. See ASHA’s Autism Evidence Map for summaries on NDBI.
Incidental Teaching—a teaching technique that uses behavioral procedures. The clinician provides naturally occurring teaching opportunities that are based on the child’s interests. The clinician follows the child’s lead and reinforces communication attempts as these attempts get closer to the desired communication behavior (G. G. McGee et al., 1999).
Examples of traditional and naturalistic behavioral programs are as follows:
Educational and School-Based Behavior Interventions
Positive Behavior Support (PBS)—an approach that uses positive (nonpunitive) interventions for decreasing challenging behaviors. A commonly used strategy focuses on two aspects:
Multicomponent intervention plans often include prevention strategies (i.e., antecedent packages). PBS integrates principles of behavioral analysis with person-centered values to foster skills that replace challenging behaviors. PBS can be used to support children and adults with autism who demonstrate problem behaviors (Carr et al., 2002).
Examples of educational and school-based programs are as follows:
Cognitive behavioral therapy (CBT) is an intervention approach that combines cognitive and behavioral learning principles to shape and encourage desired behaviors. The underlying assumptions of CBT are that an individual’s behavior is mediated by maladaptive patterns of thought or understanding and that changes in thinking or cognitive patterns can lead to changes in behavior. CBT is used primarily to help people with ASD improve behavior by learning to regulate emotions and control impulses.
The most effective CBT programs for ASD tend to include a parent education component (Scarpa & Reyes, 2011). Effective interventions often include intervention in natural settings (school, home, community; Wood et al., 2009). Because the intervention generally involves developing hierarchies and training individuals to change thought processes, the procedures are generally used with individuals who have reliable oral speech and who experience fewer core ASD characteristics.
There are additional considerations for professionals implementing CBT principles or other traditional psychotherapeutic approaches to nonspeakers or people who use AAC (Noyes & Wilkinson, 2022). SLPs may need to provide communication partner training to mental health professionals. SLPs can help mental health professionals work with AAC users, such as identifying and repairing communication breakdowns.
Milieu Therapy—a range of methods (including incidental teaching) that are integrated into a child’s natural environment. Milieu therapy includes training in everyday environments and during activities that take place throughout the day rather than only at “therapy time” (Kaiser et al., 1992).
Caregiver-mediated or relationship-based interventions consist of strategies that caregivers, care partners, or peers use to facilitate communication or social interaction. The caregiver can be involved in interventions even after early intervention. Relationship-based interventions can include romantic partners, family members, and friends. The SLP trains and coaches the caregiver to implement these interventions in natural settings. See ASHA’s Autism Evidence Map for summaries on caregiver-, peer-, or sibling-mediated interventions and on relationship-based interventions.
Examples of programs that include caregiver-mediated and relationship-based interventions are as follows:
Social skills training approaches and frameworks are designed to increase social skills, using social group settings and other platforms to teach peer interaction skills and promote effective communication. Social skills may be trained individually or in groups using a variety of intervention techniques, including social scripts (Nelson, 1978). See ASHA’s Practice Portal page on Social Communication Disorder and ASHA’s Autism Evidence Map for summaries on social communication interventions.
Examples of programs that focus on social skills are as follows:
Augmentative and Alternative Communication (AAC)
An AAC system is an integrated group of components used to enhance communication. AAC uses a variety of techniques and tools to help the individual express thoughts, ideas, wants, needs, and feelings. Examples of treatment techniques include the following:
AAC can supplement existing expressive spoken communication or can be an alternative to spoken language. Although people with autism, especially autistic adults, may have functional speech, they may also need AAC to fully meet their communication needs (Zisk & Dalton, 2019).
For more information about AAC interventions and communicative competence, see ASHA’s Practice Portal page on Augmentative and Alternative Communication (AAC). See ASHA’s Autism Evidence Map for summaries on AAC.
Executive Function
People with autism may have trouble with executive functioning. Speech-language pathology services might address executive functioning skills and/or recommend strategies and accommodations. See ASHA’s Practice Portal page on Executive Function Deficits.
Feeding and Swallowing
Feeding and swallowing interventions may address sensory difficulties and food acceptance. See ASHA’s Practice Portal page on Pediatric Feeding and Swallowing.
Fluency
Autistic adults may demonstrate more typical disfluencies (e.g., revisions, multisyllable word repetitions), stuttering-like disfluencies (e.g., prolongations, blocks), and atypical disfluencies (e.g., repetition of a final sound or syllable) than non-autistic peers (Pirinen et al., 2023). See ASHA’s Practice Portal page on Fluency Disorders.
Language Interventions for Deaf and Hard of Hearing Individuals
People diagnosed with ASD may also be deaf and hard of hearing. Clinicians may need to account for additional considerations for language interventions, such as nonspoken language models or referrals to audiologists and other medical professionals for hearing management options (e.g., hearing aids, cochlear implants, or other hearing assistive technology). See ASHA’s Practice Portal page on Language and Communication of Deaf and Hard of Hearing Children.
Literacy (Written Language) Intervention
Reading comprehension is a common academic struggle for people on the autism spectrum with low support needs (McIntyre et al., 2017). Literacy intervention approaches incorporate a variety of instructional strategies to improve phonological awareness, word decoding, word identification, reading fluency, reading vocabulary, and reading comprehension. Older children with autism may also have difficulty with higher level literacy skills that require theory of mind.
For a review of strategies for promoting literacy, see Lanter and Watson (2008). See also ASHA’s Practice Portal page on Written Language Disorders and ASHA’s Autism Evidence Map for summaries on literacy interventions.
Spoken Language Intervention
The goal of spoken language intervention is to facilitate overall language development and functional, everyday communication. The selection of treatment options and approaches is based on the person’s current level of language skills. See also ASHA’s Practice Portal page on Spoken Language Disorders for descriptions of various treatment options and approaches. Interventions may also reflect views on natural language acquisition patterns in children with ASD and the role of echolalia and gestalt language processing (see, e.g., Blanc et al., 2023).
Natural language acquisition (Blanc et al., 2023) is an example of a protocol to describe gestalt language. At first, children produce “chunks” or “gestalt forms” (e.g., echolalic utterances), without distinction between individual words and without appreciation for internal syntactic structure. These gestalt forms are considered units of communication (Peters, 1983).
Children begin to recognize similarities and patterns between these gestalt forms. They begin to combine different segments and words into new forms. Eventually, the child can formulate creative, spontaneous utterances for communication purposes. As such, using a strengths-based approach, gestalts are used to promote language development and progress. Clinicians use modeling and utilize a framework of development to coach a child through language stages in child-led activities. No current efficacy studies are available. See Blanc et al. (2023) and Hutchins et al. (2024) for further discussion of natural language acquisition and gestalt language processing.
Speech Sound Intervention
Speech sound intervention addresses functional disorders such as articulation and phonology and motor speech disorders such as apraxia of speech and dysarthria. See ASHA’s Practice Portal pages on Speech Sound Disorders: Articulation and Phonology and Childhood Apraxia of Speech for relevant treatment options.
Activity Schedule and Visual Supports
Activity schedules and visual supports include objects, photographs, drawings, or written words that act as cues or prompts. They help individuals complete a sequence of tasks or activities, attend to tasks, transition from one task to another, or maintain emotional regulation in various settings. Written and/or visual prompts that initiate or sustain interaction are called scripts. Scripts are often used to promote social interaction but can also be used in a classroom setting to facilitate academic interactions and to promote academic engagement (Hart & Whalon, 2008). See ASHA’s Autism Evidence Map for summaries on visual supports and activity schedules.
Assistive Technology
AAC is considered a form of assistive technology. Additional assistive technology can include hearing technology, FM systems, and text-to-speech readers. This technology can further support the person with autism’s participation in daily activities.
Self-Management
Self-management is an approach aimed at helping individuals learn to independently regulate their behaviors and behave appropriately in a variety of contexts. Individuals are taught to discriminate the difference between appropriate and inappropriate behaviors, evaluate and record their behaviors, and (when possible and appropriate) reward themselves for using appropriate behaviors. Self-management interventions can be used across a wide range of ages from early childhood through adulthood. See ASHA’s Autism Evidence Map for summaries on self-management.
The treatment options and approaches below are not endorsed by ASHA. ASHA stands firmly behind its members in support of effective services leading to independent communication for those they serve. See ASHA’s position on each. Click on the hyperlinks provided to read ASHA’s full position statements.
Auditory Integration Training (AIT)
According to ASHA’s position statement titled Auditory Integration Training, “The 2002 ASHA Work Group on AIT, after reviewing empirical research in the area to date, concludes that AIT has not met scientific standards for efficacy that would justify its practice by audiologists and speech-language pathologists” (ASHA, 2004, para. 1).
Facilitated Communication
According to ASHA’s position statement titled Facilitated Communication, “It is the position of the American Speech-Language-Hearing Association (ASHA) that Facilitated Communication (FC) is a discredited technique that should not be used. There is no scientific evidence of the validity of FC, and there is extensive scientific evidence—produced over several decades and across several countries—that messages are authored by the ‘facilitator’ rather than the person with a disability. Furthermore, there is extensive evidence of harms related to the use of FC. Information obtained through the use of FC should not be considered as the communication of the person with a disability” (ASHA, 2018a, para. 1).
Rapid Prompting Method
According to ASHA’s position statement titled Rapid Prompting Method, “use of the Rapid Prompting Method (RPM) is not recommended because of prompt dependency and the lack of scientific validity. Furthermore, information obtained through the use of RPM should not be assumed to be the communication of the person with a disability” (ASHA, 2018b, para. 1).
Young adults with autism experience high rates of unemployment and underemployment (Lounds Taylor & Seltzer, 2011; Shattuck et al., 2012). They may have difficulty maintaining employment once they have the job (Lounds Taylor et al., 2015; Wei et al., 2015). Socially, they may discontinue friendships, participate in fewer social activities (Orsmond et al., 2013), and experience social isolation (Lounds Taylor et al., 2017; Myers et al., 2015).
These findings highlight the need for continued support to facilitate a successful transition to adulthood. SLPs are involved in transition planning in high school and may be involved, to varying degrees, in other support services beyond high school. For example, job-related support from an SLP could include improving interview skills (Morgan et al., 2014; Smith et al., 2014). Transition goals focus on facilitating self-determination and self-advocacy (Perryman et al., 2020).
See ASHA’s resource on postsecondary transition planning for more information about postsecondary supports and services. See also ASHA’s Autism Evidence Map for summaries on employment and vocational skills of people with autism.
Access to state-funded ASD programs may be limited for adults who are newly diagnosed because documentation of a developmental disability prior to the age of 22 years is typically required. However, some funding for services may be available; services include counseling, vocational supports, and speech-language services to address core social communication challenges. Community support programs and various online support groups are also available.
For a comprehensive discussion about supporting the needs of people on the autism spectrum, see Question 6 of the 2021–2023 IACC Strategic Plan for Autism Research, Services, and Policy (IACC, 2023). For a review and discussion of research on environmental supports and barriers to participation in adolescents with ASD, see Krieger et al. (2018).
See the Service Delivery section of the Autism Evidence Map for pertinent scientific evidence, expert opinion, and client/caregiver perspective.
In addition to determining the type of speech and language treatment that is optimal for children with social communication disorders, SLPs consider other service delivery variables—including format, provider, dosage, and timing—that may impact treatment outcomes.
Format refers to the structure of the treatment session. In-person formats can include individual sessions or small groups. Telepractice may be a usable and versatile format for people with autism. However, each state’s requirements for telepractice vary. See ASHA’s state-by-state resource for specific state rules and ASHA’s Practice Portal page on Telepractice. Payer coverage for telepractice also varies widely, even when states allow telepractice. See ASHA’s telepractice payment and coverage resource for more information. Trained individuals may need to be available to help the person receiving telepractice services (Edwards-Gaither et al., 2023).
Clinicians might also consider incorporating additional technology into service delivery. Computer-based instruction involves the use of computer technology (e.g., iPads) and/or computerized programs for teaching language skills, including vocabulary, social skills, social understanding, and social problem-solving (see, e.g., Khowaja & Salim, 2013; Weng et al., 2014).
Video-based instruction (also called “video modeling”) uses video recordings to provide a model of the target behavior or skill. Video modeling procedures can be implemented in following three ways:
In all cases, the clinician works with the learner to provide practice and feedback. Video-based techniques are more frequently being used in treatment (see, e.g., Wilson, 2013). Video visual screen displays can support social interactions of people with autism who have complex communication needs (Babb et al., 2021).
The provider is the person offering the treatment, such as the SLP or caregiver. The SLP provides training and coaching to caregivers, peers, or other professionals involved in the interventions. Coaching strategies can include direct teaching, guided practice, reflection, and feedback (Brown, 2016). These trained individuals can help support the communication of people with autism in more natural settings.
Dosage refers to the frequency, intensity, and duration of service. Dosage varies based on the person’s needs and desired goals. Some people may make significant gains from intensive programs that are multiple times per week, for many hours. Some people may respond to less intensive programs that are only once per week.
Timing refers to the start of intervention relative to the diagnosis. The earlier the diagnosis or identification, the sooner services can begin. Early intervention can maximize the positive outcomes for children with autism (IACC, 2023).
The setting is the location of treatment. Interventions can take place in the home, community, and school. School-based services can take place in the SLP’s resource room or in the student’s classroom. Supporting communication in natural settings can promote generalization of skills.
This list of resources is not exhaustive, and the inclusion of any specific resource does not imply endorsement from ASHA.
Adams, D., Ambrose, K., Simpson, K., Malone, S., & Dargue, N. (2023). The relationship between anxiety and social outcomes in autistic children and adolescents: A meta-analysis. Clinical Child and Family Psychology Review, 26, 706–720. https://doi.org/10.1007/s10567-023-00450-7
Alaghband-rad, J., Hajikarim-Hamedani, A., & Motamed, M. (2023). Camouflage and masking behavior in adult autism. Frontiers in Psychiatry, 14. https://doi.org/10.3389/fpsyt.2023.1108110
Amato, J., Jr., Barrow, M., & Domingo, R. (1999). Symbolic play behavior in very young verbal and nonverbal children with autism. Infant–Toddler Intervention: The Transdisciplinary Journal, 9(2), 185–194.
American Psychiatric Association. (2000). Diagnostic and statistical manual of mental disorders (4th ed., text rev.).
American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.).
American Psychiatric Association. (2022). Diagnostic and statistical manual of mental disorders (5th ed., text rev.).
American Speech-Language-Hearing Association. (2004). Auditory integration training [Position statement]. https://www.asha.org/policy/
American Speech-Language-Hearing Association. (2016). Scope of practice in speech-language pathology [Scope of practice]. https://www.asha.org/policy/
American Speech-Language-Hearing Association. (2018a). Facilitated communication [Position statement]. https://www.asha.org/policy/
American Speech-Language-Hearing Association. (2018b). Rapid prompting method [Position statement]. https://www.asha.org/policy/
American Speech-Language-Hearing Association. (2018c). Scope of practice in audiology [Scope of practice]. https://www.asha.org/policy/
American Speech-Language-Hearing Association. (2023). Code of ethics [Ethics]. https://www.asha.org/policy/
Aylward, B. S., Gal-Szabo, D. E., & Taraman, S. (2021). Racial, ethnic, and sociodemographic disparities in diagnosis of children with autism spectrum disorder. Journal of Developmental & Behavioral Pediatrics, 42(8), 682–689. https://doi.org/10.1097/DBP.0000000000000996
Babb, S., McNaughton, D., Light, J., & Caron, J. (2021). “Two friends spending time together”: The impact of video visual scene displays on peer social interaction for adolescents with autism spectrum disorder. Language, Speech, and Hearing Services in Schools, 52(4), 1095–1108. https://doi.org/10.1044/2021_LSHSS-21-00016
Babinska, K., Celusakova, H., Belica, I., Szapuova, Z., Waczulikova, I., Nemcsicsova, D., Tomova, A., & Ostatnikova, D. (2020). Gastrointestinal symptoms and feeding problems and their associations with dietary interventions, food supplement use, and behavioral characteristics in a sample of children and adolescents with autism spectrum disorders. International Journal of Environmental Research and Public Health, 17(17), Article 6372. https://doi.org/10.3390/ijerph17176372
Baio, J., Wiggins, L., Christensen, D. L., Maenner, M. J., Daniels, J., Warren, Z., Kurzius-Spencer, M., Zahorodny, W., Robinson Rosenberg, C., White, T., Durkin, M. S., Imm, P., Nikolaou, L., Yeargin-Allsopp, M., Lee, L.-C., Harrington, R., Lopez, M., Fitzgerald, R. T., Hewitt, A., . . . Dowling, N. F. (2018). Prevalence of autism spectrum disorder among children aged 8 years—Autism and Developmental Disabilities Monitoring Network, 11 sites, United States, 2014. MMWR Surveillance Summaries, 67(6), 1–23. https://dx.doi.org/10.15585/mmwr.ss6706a1
Baranek, G. T. (1999). Autism during infancy: A retrospective video analysis of sensory-motor and social behaviors at 9–12 months of age. Journal of Autism and Developmental Disorders, 29(3), 213–224. https://doi.org/10.1023/A:1023080005650
Baron-Cohen, S., Allen, J., & Gillberg, C. (1992). Can autism be detected at 18 months? The needle, the haystack, and the CHAT. The British Journal of Psychiatry, 161(6), 839–843. https://doi.org/10.1192/bjp.161.6.839
Begeer, S., El Bouk, S., Boussaid, W., Terwogt, M. M., & Koot, H. M. (2009). Underdiagnosis and referral bias of autism in ethnic minorities. Journal of Autism and Developmental Disorders, 39(1), 142–148. https://doi.org/10.1007/s10803-008-0611-5
Berard, G. (1993). Hearing equals behavior. Keats.
Blanc, M., Blackwell, A., & Elias, P. (2023). Using the natural language acquisition protocol to support gestalt language development. Perspectives of the ASHA Special Interest Groups, 8(6), 1279–1286. https://doi.org/10.1044/2023_PERSP-23-00098
Bondy, A. S., & Frost, L. A. (1998). Picture Exchange Communication System. Topics in Language Disorders, 19(4), 373–390. https://doi.org/10.1055/s-2008-1064055
Bradshaw, J., Steiner, A. M., Gengoux, G., & Koegel, L. K. (2015). Feasibility and effectiveness of very early intervention for infants at-risk for autism spectrum disorder: A systematic review. Journal of Autism and Developmental Disorders, 45(3), 778–794. https://doi.org/10.1007/s10803-014-2235-2
Brown, J. A. (2016). Coaching in parent-implemented early communication interventions: Understanding and overcoming individual-level implementation barriers. Perspectives of the ASHA Special Interest Groups, 1(1), 144–153. https://doi.org/10.1044/persp1.SIG1.144
Brueggeman, P. M. (2012). 10 tips for testing hearing in children with autism. The ASHA Leader, 17(1), 5–7. https://doi.org/10.1044/leader.FTR3.17012012.5
Brugha, T. S., McManus, S., Bankart, J., Scott, F., Purdon, S., Smith, J., Bebbington, P., Jenkins, R., & Meltzer H. (2011). Epidemiology of autism spectrum disorders in adults in the community in England. Archives of General Psychiatry, 68(5), 459–465. https://doi.org/10.1001/archgenpsychiatry.2011.38
Bryson, S. E., Zwaigenbaum, L., McDermott, C., Rombough, V., & Brian, J. (2008). The Autism Observation Scale for Infants: Scale development and reliability data. Journal of Autism and Developmental Disorders, 38(4), 731–738. https://doi.org/10.1007/s10803-007-0440-y
Burkett, K., Morris, E., Manning-Courtney, P., Anthony, J. C., & Shambley-Ebron, D. (2015). African American families on autism diagnosis and treatment: The influence of culture. Journal of Autism and Developmental Disorders, 45(10), 3244–3254. https://doi.org/10.1007/s10803-015-2482-x
Carr, E. G., Dunlap, G., Horner, R. H., Koegel, R. L., Turnbull, A. P., Sailor, W., Anderson, J. L., Albin, R. W., Koegel, L. K., & Fox, L. (2002). Positive behavior support: Evolution of an applied science. Journal of Positive Behavior Interventions, 4(1), 4–16. https://doi.org/10.1177/109830070200400102
Carr, E. G., & Durand, V. M. (1985). Reducing behavior problems through functional communication training. Journal of Applied Behavioral Analysis, 18(2), 111–126. https://doi.org/10.1901/jaba.1985.18-111
Center for Medicaid and CHIP Services. (2024). 2024 Medicaid and CHIP beneficiaries at a glance: Autism. Centers for Medicare & Medicaid Services.
Chakrabarti, S., & Fombonne, E. (2005). Pervasive developmental disorders in preschool children: Confirmation of high prevalence. American Journal of Psychiatry, 162(6), 1133–1141. https://doi.org/10.1176/appi.ajp.162.6.1133
Chawarska, K., Paul, R., Klin, A., Hannigen, S., Dichtel, L. E., & Volkmar, F. (2007). Parental recognition of developmental problems in toddlers with autism spectrum disorders. Journal of Autism and Developmental Disorders, 37(1), 62–72. https://doi.org/10.1007/s10803-006-0330-8
Cohn, E. G., McVilly, K. R., Harrison, M. J., & Stiegler, L. N. (2022). Repeating purposefully: Empowering educators with functional communication models of echolalia in autism. Autism & Developmental Language Impairments, 7, 1–16. https://doi.org/10.1177/23969415221091928
Cole, K. N., Dale, P. S., & Mills, P. E. (1990). Defining language delay in young children by cognitive referencing: Are we saying more than we know? Applied Psycholinguistics, 11(3), 291–302. https://doi.org/10.1017/S0142716400008900
Constantino, J. N., Abbacchi, A. M., Saulnier, C., Klaiman, C., Mandell, D. S., Zhang, Y., Hawks, Z., Bates, J., Klin, A., Shattuck, P., Molholm, S., Fitzgerald, R., Roux, A., Lowe, J. K., & Geschwind, D. H. (2020). Timing of the diagnosis of autism in African American children. Pediatrics, 146(3), e20193629. https://doi.org/10.1542/peds.2019-3629
Cook, J., Crane, L., Hull, L., Bourne, L., & Mandy, W. (2022). Self-reported camouflaging behaviours used by autistic adults during everyday social interactions. Autism, 26(2), 406–421. https://doi.org/10.1177/13623613211026754
Corbett, B. A., Muscatello, R. A., Klemencic, M. E., West, M., Kim, A., & Strang, J. F. (2023). Greater gender diversity among autistic children by self-report and parent-report. Autism, 27(1), 158–172. https://doi.org/10.1177/13623613221085337
Crompton, C. J., Ropar, D., Evans-Williams, C. V., Flynn, E. G., & Fletcher-Watson, S. (2020). Autistic peer-to-peer information transfer is highly effective. Autism, 24(7), 1704–1712. https://doi.org/10.1177/1362361320919286
Crooke, P. J., Hendrix, R. E., & Rachman, J. Y. (2008). Brief report: Measuring the effectiveness of teaching social thinking to children with Asperger syndrome and high-functioning autism. Journal of Autism and Developmental Disorders, 38(3), 581–591. https://doi.org/10.1007/s10803-007-0466-1
Crow, H. (2024, April). Neurodiversity-affirming speech-language services and early intervention [On-demand webinar]. ASHA Professional Development. https://apps.asha.org/eweb/olsdynamicpage.aspx?title=neurodiversity-affirming+speech-language+services+and+early+intervention+(on+demand+webinar)&webcode=olsdetails
Davis, R., & Stiegler, L. N. (2005). Toward more effective audiological assessment of children with autism spectrum disorders. Seminars in Hearing, 26(4), 241–252. https://doi.org/10.1055/s-2005-922446
Dawson, G., & Osterling, J. (1997). Early intervention in autism. In M. Guralnick (Ed.), The effectiveness of early intervention (pp. 307–326). Brookes.
Dawson, G., Rogers, S., Munson, J., Smith, M., Winter, J., Greenson, J., Donaldson, A., & Varley, J. (2010). Randomized, controlled trial of an intervention for toddlers with autism: The Early Start Denver Model. Pediatrics, 125(1), e17–e23. https://doi.org/10.1542/peds.2009-0958
Dean, M., Harwood, R., & Kasari, C. (2017). The art of camouflage: Gender differences in the social behaviors of girls and boys with autism spectrum disorder. Autism, 21(6), 678–689. https://doi.org/10.1177/1362361316671845
DeThorne, L. S. (2020, April). Revealing the double empathy problem. The ASHA Leader Archive, 25(3). https://doi.org/10.1044/leader.FTR2.25042020.58
DiLavore, P., Lord, C., & Rutter, M. (1995). The Prelinguistic Autism Diagnostic Observation Schedule. Journal of Autism and Developmental Disorders, 25(4), 355–379. https://doi.org/10.1007/bf02179373
Drysdale, H., van der Meer, L., & Kagohara, D. (2015). Children with autism spectrum disorder from bilingual families: A systematic review. Review Journal of Autism and Developmental Disorders, 2, 26–38. https://doi.org/10.1007/s40489-014-0032-7
Dworzynski, K., Ronald, A., Bolton, P., & Happé, F. (2012). How different are girls and boys above and below the diagnostic threshold for autism spectrum disorders? Journal of the American Academy of Child & Adolescent Psychiatry, 51(8), 788–797. https://doi.org/10.1016/j.jaac.2012.05.018
Easterbrooks, S. R., & Handley, C. M. (2005). Behavior change in a student with a dual diagnosis of deafness and pervasive development disorder: A case study. American Annals of the Deaf, 150(5), 401–407. https://doi.org/10.1353/aad.2006.0001
Edwards-Gaither, L., Harris, O., & Perry, V. (2023). Viewpoint telepractice 2025: Exploring telepractice service delivery during COVID-19 and beyond. Perspectives of the ASHA Special Interest Groups, 8(2), 412–417. https://doi.org/10.1044/2022_PERSP-22-00095
Elsabbagh, M., Mercure, E., Hudry, K., Chandler, S., Pasco, G., Charman, T., Pickles, A., Baron-Cohen, S., Bolton, P., & Johnson, M. H. (2012). Infant neural sensitivity to dynamic eye gaze is associated with later emerging autism. Current Biology, 22(4), 338–342. https://doi.org/10.1016/j.cub.2011.12.056
Fay, W. H. (1969). On the basis of autistic echolalia. Journal of Communication Disorders, 2(1), 38–47. https://doi.org/10.1016/0021-9924(69)90053-7
Forbes, H. J., Travers, J. C., & Vickers Johnson, J. (2020). A systematic review of linguistic and verbal behavior outcomes of pivotal response treatment. Journal of Autism and Developmental Disorders, 50, 766–778. https://doi.org/10.1007/s10803-019-04307-3
Forbes, H. J., Travers, J. C., & Vickers Johnson, J. (2024). A systematic review of acquisition and mastery of skills taught using the Picture Exchange Communication System. Augmentative and Alternative Communication, 40(2), 100–114. https://doi.org/10.1080/07434618.2024.2302154
Frith, U., & Happé, F. (1994). Autism: Beyond “theory of mind.” Cognition, 50(1–3), 115–132. https://doi.org/10.1016/0010-0277(94)90024-8
Gaddy, C., & Crow, H. (2023). A primer on neurodiversity-affirming speech and language services for autistic individuals. Perspectives of the ASHA Special Interest Groups, 8, 1220–1237. https://doi.org/10.1044/2023_PERSP-23-00106
Garcia Winner, M., & Crooke, P. J. (2009). Social thinking: A training paradigm for professionals and treatment approach for individuals with social learning/social pragmatic challenges. Perspectives on Language Learning and Education, 16(2), 62–69. https://doi.org/10.1044/lle16.2.62
Garcia Winner, M., & Crooke, P. J. (2011). Social communication strategies for adolescents with autism. The ASHA Leader, 16(1), 8–11. https://doi.org/10.1044/leader.FTR1.16012011.8
Garfinkle, A. N., & Schwartz, I. S. (2002). Peer imitation: Increasing social interactions in children with autism and other developmental disabilities in inclusive preschool classrooms. Topics in Early Childhood Special Education, 22(1), 26–38. https://doi.org/10.1177/027112140202200103
Geurts, H. M., & Jansen, M. D. (2012). A retrospective chart study: The pathway to a diagnosis for adults referred for ASD assessment. Autism, 16(3), 299–305. https://doi.org/10.1177/1362361311421775
Gilchrist, A., Green, J., Cox, A., Burton, D., Rutter, M., & Le Couteur, A. (2001). Development and current functioning in adolescents with Asperger syndrome: A comparative study. The Journal of Child Psychology and Psychiatry, 42(2), 227–240. https://doi.org/10.1017/S0021963001006631
Gilhuber, C. S., Raulston, T. J., & Galley, K. (2023). Language and communication skills in multilingual children on the autism spectrum: A systematic review. Autism, 27(6), 1516–1531. https://doi.org/10.1177/13623613221147780
Gray, C., White, A. L., & McAndrew, S. (2002). My social stories book. Jessica Kingsley Publishers.
Greenspan, S. I., & Wieder, S. (2007). The developmental individual-difference, relationship-based (DIR/Floortime) model approach to autism spectrum disorders. In E. Hollander & E. Anagnostou (Eds.), Clinical manual for the treatment of autism (pp. 179–209). American Psychiatric Publishing.
Gutstein, S. E., & Gutstein, H. R. (2009). The RDI book: Forging new pathways for autism, Asperger's and PDD with the relationship development intervention program. Connections Center Publications.
Hambly, C., & Fombonne, E. (2012). The impact of bilingual environments on language development in children with autism spectrum disorders. Journal of Autism and Developmental Disorders, 42(7), 1342–1352. https://doi.org/10.1007/s10803-011-1365-z
Hamilton, B., & Snell, M. (1993). Using the milieu approach to increase spontaneous communication book use across environments by an adolescent with autism. Augmentative and Alternative Communication, 9(4), 259–272. https://doi.org/10.1080/07434619312331276681
Harris, S. L., & Handleman, J. S. (2000). Age and IQ at intake as predictors of placement for young children with autism: A four- to six-year follow-up. Journal of Autism and Developmental Disorders, 30(2), 137–142. https://doi.org/10.1023/a:1005459606120
Hart, J. E., & Whalon, K. J. (2008). Promote academic engagement and communication of students with autism spectrum disorder in inclusive settings. Intervention in School and Clinic, 44(2), 116–120. https://doi.org/10.1177/1053451207310346
Hutchins, T. L., Knox, S. E., & Fletcher, E. C. (2024). Natural language acquisition and gestalt language processing: A critical analysis of their application to autism and speech language therapy. Autism and Developmental Language Impairments, 9. https://doi.org/10.1177/23969415241249944
Iland, E. D., Weiner, I., & Murawski, W. W. (2012). Obstacles faced by Latina mothers of children with autism. Californian Journal of Health Promotion, 10(SI-Latino), 25–36.
Maternal and Child Health Bureau. (2022). National Survey of Children’s Health. Health Resources and Services Administration. https://mchb.hrsa.gov/data-research/national-survey-childrens-health
Hotez, E., & Shea, L. (2023). Prioritizing social determinants of health in public health surveillance for autism. Pediatrics, 151(2), e2022059541. https://doi.org/10.1542/peds.2022-059541
Hoyson, M., Jamieson, B., & Strain, P. S. (1984). Individualized group instruction of normally developing and autistic-like children: The LEAP curriculum model. Journal of Early Intervention, 8(2), 157–172. https://doi.org/10.1177/105381518400800209
Hyman, S. L., Levy, S. E., Myers, S. M., & Council on Children with Disabilities, Section on Developmental and Behavioral Pediatrics. (2020). Identification, evaluation, and management of children with autism spectrum disorder. Pediatrics, 145(1), e20193447. https://doi.org/10.1542/peds.2019-3447
Individuals with Disabilities Education Improvement Act of 2004, P. L. 108-446, 20 U.S.C. §§ 1501 et seq. (2004). https://www.congress.gov/bill/108th-congress/house-bill/1350
Interagency Autism Coordinating Committee. (2023, September). 2021–2023 IACC strategic plan for autism research, services, and policy. U.S. Department of Health and Human Services. https://iacc.hhs.gov/publications/strategic-plan/2023/
Jones, W., & Klin, A. (2013). Attention to eyes is present but in decline in 2–6-month-old infants later diagnosed with autism. Nature, 504(7480), 427–431. https://doi.org/10.1038/nature12715
Kaiser, A. P., Yoder, P. J., & Keetz, A. (1992). Evaluating milieu teaching. In S. F. Warren & J. Reichle (Eds.), Causes and effects in communication and language intervention (pp. 9–47). Brookes.
Kallitsounaki, A., & Williams, D. M. (2023). Autism spectrum disorder and gender dysphoria/incongruence. A systematic literature review and meta-analysis. Journal of Autism and Developmental Disorders, 53(8), 3103–3117. https://doi.org/10.1007/s10803-022-05517-y
Kapp, S., Steward, R., Crane, L., Elliott, D., Elphick, C., Pellicano, E., & Russell, G. (2019). “People should be allowed to do what they like”: Autistic adults’ views and experiences of stimming. Autism, 23(7), 1782–1792. https://doi.org/10.1177/1362361319829628
Kasari, C., Paparella, T., Freeman, S., & Jahromi, L. B. (2008). Language outcome in autism: Randomized comparison of joint attention and play interventions. Journal of Consulting and Clinical Psychology, 76(1), 125–137. https://doi.org/10.1037/0022-006X.76.1.125
Khowaja, K., & Salim, S. S. (2013). A systematic review of strategies and computer-based intervention (CBI) for reading comprehension of children with autism. Research in Autism Spectrum Disorders, 7(9), 1111–1121. https://doi.org/10.1016/j.rasd.2013.05.009
Koegel, L. K., Singh, A. K., Koegel, R. L., Hollingsworth, J. R., & Bradshaw, J. (2014). Assessing and improving early social engagement in infants. Journal of Positive Behavior Interventions, 16(2), 69–80. https://doi.org/10.1177/1098300713482977
Koegel, R. L., & Koegel, L. K. (2019). Pivotal response treatment for autism spectrum disorders. Brookes.
Koerner, S. M., Glaser, S., & Kropkowski, K. (2023). Perspectives of part-time augmentative and alternative communication use in adults and implications for pediatric service delivery. Perspectives of the ASHA Special Interest Groups, 8(4), 747–760. https://doi.org/10.1044/2023_PERSP-22-00200
Krieger, B., Piškur, B., Schulze, C., Jakobs, U., Beurskens, A., & Moser, A. (2018). Supporting and hindering environments for participation of adolescents diagnosed with autism spectrum disorder: A scoping review. PLOS ONE, 13(8), Article e0202071. https://doi.org/10.1371/journal.pone.0202071
Lai, M.-C., Lombardo, M. V., Ruigrok, A. N. V., Chakrabarti, B., Auyeng, B., Szatmari, P., Happé, F., Baron-Cohen, S., & MRC AIMS Consortium. (2017). Quantifying and exploring camouflaging in men and women with autism. Autism, 21(6), 690–702. https://doi.org/10.1177/1362361316671012
Landa, R. J., & Kalb, L. G. (2012). Long-term outcomes of toddlers with autism spectrum disorders exposed to short-term intervention. Pediatrics, 130(Suppl. 2), S186–S190. https://doi.org/10.1542/peds.2012-0900Q
Lanter, E., & Watson, L. R. (2008). Promoting literacy in students with ASD: The basics for the SLP. Language, Speech, and Hearing Services in Schools, 39(1), 33–43. https://doi.org/10.1044/0161-1461(2008/004)
Laugeson, E. A., Frankel, F., Gantman, A., Dillon, A. R., & Mogil, C. (2011). Evidence-based social skills training for adolescents with autism spectrum disorders: The UCLA PEERS program. Journal of Autism and Developmental Disorders, 42, 1025–1036. https://doi.org/10.1007/s10803-011-1339-1
Lawton, K., & Kasari, C. (2012). Teacher-implemented joint attention intervention: Pilot randomized controlled study for preschoolers with autism. Journal of Consulting and Clinical Psychology, 80(4), 687–693. https://doi.org/10.1037/a0028506
Levy, S. E., Giarelli, E., Lee, L.-C., Schieve, L. A., Kirby, R. S., Cunniff, C., Nicholas, J., Reaven, J., & Rice, C. E. (2010). Autism spectrum disorder and co-occurring developmental, psychiatric, and medical conditions among children in multiple populations of the United States. Journal of Developmental & Behavioral Pediatrics, 31(4), 267–275. https://doi.org/10.1097/DBP.0b013e3181d5d03b
Liu, B. M., Paskov, K., Kent, J., McNealis, M., Sutaria, S., Dods, O., Harjadi, C., Stockham, N., Ostrovsky, A., & Wall, D. P. (2023). Racial and ethnic disparities in geographic access to autism resources across the US. JAMA Network Open, 6(1), e2251182. https://doi.org/10.1001/jamanetworkopen.2022.51182
Lord, C., & Corsello, C. (2005). Diagnostic instruments in autistic spectrum disorders. In F. R. Volkmar, R. Paul, A. Klin, & D. Cohen (Eds.), Handbook of autism and pervasive developmental disorders: Volume 2: Assessment, interventions, and policy (pp. 730–771). Wiley.
Lord, C., & Schopler, E. (1985). Brief report: Differences in sex ratios in autism as a function of measured intelligence. Journal of Autism and Developmental Disorders, 15, 185–193. https://doi.org/10.1007/BF01531604
Lounds Taylor, J., Adams, R. A., & Bishop, S. L. (2017). Social participation and its relation to internalizing symptoms among youth with autism spectrum disorder as they transition from high school. Autism Research, 10(4), 663–672. https://doi.org/10.1002/aur.1709
Lounds Taylor, J., Henninger, N. A., & Mailick, M. R. (2015). Longitudinal patterns of employment and postsecondary education for adults with autism and average-range IQ. Autism, 19(7), 785–793. https://doi.org/10.1177/1362361315585643
Lounds Taylor, J. L., & Seltzer, M. M. (2011). Employment and post-secondary educational activities for young adults with autism spectrum disorders during the transition to adulthood. Journal of Autism and Developmental Disorders, 41(5), 566–574. https://doi.org/10.1007/s10803-010-1070-3
Luyster, R. J., Zane, E., & Wisman Weil, L. (2022). Conventions for unconventional language: Revisiting a framework for spoken language features in autism. Autism & Developmental Language Impairments, 7, 1–19. https://doi.org/10.1177/23969415221105472
Maenner, M. J., Warren, Z., Williams, A. R., Amoakohene, E., Bakian, A. V., Bilder, D. A., Durkin, M. S., Fitzgerald, R. T., Furnier, S. M., Hughes, M. M., Ladd-Acosta, C. M., McArthur, D., Pas, E. T., Salinas, A., Vehorn, A., Williams, S., Esler, A., Grzybowski, A., Hall-Lande, J., . . . Shaw, K. A. (2023). Prevalence and characteristics of autism spectrum disorder among children aged 8 years—Autism and Developmental Disabilities Monitoring Network, 11 sites, United States, 2020. MMWR Surveillance Summaries, 72(2), 1–14. http://dx.doi.org/10.15585/mmwr.ss7202a1
Maffei, M. F., Chenausky, K. V., Haenssler, A., Abbiati, C., Tager-Flusberg, H., & Green, J. R. (2024). Exploring motor speech disorders in low and minimally verbal autistic individuals: An auditory-perceptual analysis. American Journal of Speech-Language Pathology, 33(3), 1485–1503. https://doi.org/10.1044/2024_AJSLP-23-00237
Malandraki, G. A., & Okalidou, A. (2007). The application of PECS in a deaf child with autism: A case study. Focus on Autism and Other Developmental Disabilities, 22(1), 23–32. https://doi.org/10.1177/10883576070220010301
Mandy, W., Chilvers, R., Chowdhury, U., Salter, G., Seigal, A., & Skuse, D. (2012). Sex differences in autism spectrum disorder: Evidence from a large sample of children and adolescents. Journal of Autism and Developmental Disorders, 42(7), 1304–1313. https://doi.org/10.1007/s10803-011-1356-0
McCrossin, R. (2022). Finding the true number of females with autistic spectrum disorder by estimating the biases in initial recognition and clinical diagnosis. Children, 9(2), 272. https://doi.org/10.3390/children9020272
McGee, G. G., Morrier, M. J., & Daly, T. (1999). An incidental teaching approach to early intervention for toddlers with autism. Journal of the Association for Persons With Severe Handicaps, 24, 133–146. https://doi.org/10.2511/rpsd.24.3.133
McGee, J. J. (1990). Mental handicap nursing. Gentle teaching: The basic tenet. Nursing Times, 86(32), 68–72.
McIntyre, N. S., Solari, E. J., Gonzales, J. E., Solomon, M., Lerro, L. E., Novotny, S., Oswald, T. M., & Mundy, P. C. (2017). The scope and nature of reading comprehension impairments in school-aged children with higher-functioning autism spectrum disorder. Journal of Autism and Developmental Disorders, 47, 2838–2860. https://doi.org/10.1007/s10803-017-3209-y
McTee, H. M., Mood, D., Fredrickson, T., Thrasher, A., & Bonino, A. Y. (2019). Using visual supports to facilitate audiological testing for children with autism spectrum disorder. American Journal of Audiology, 28(4), 823–833. https://doi.org/10.1044/2019_AJA-19-0047
Mesibov, G. B., Shea, V., & Schopler, E. (2007). The TEACCH approach to autism spectrum disorders. Springer.
Miller, J., & Chapman, R. (1980). Analyzing language and communication in the child. In R. Schiefelbusch (Ed.), Nonspeech language and communication: Acquisition and intervention (pp. 159–196). University Park Press.
Milton, D. E. M. (2012). On the ontological status of autism: The ‘double empathy problem’. Disability & Society, 27(6), 883–887. https://doi.org/10.1080/09687599.2012.710008
Mirenda, P., Wilk, D., & Carson, P. (2000). A retrospective analysis of technology use patterns of students with autism over a five-year period. Journal of Special Education Technology, 15(3), 5–16. https://doi.org/10.1177/016264340001500301
Moes, D. R., & Frea, W. D. (2002). Contextualized behavioral support in early intervention for children with autism and their families. Journal of Autism and Developmental Disorders, 32(6), 519–533. https://doi.org/10.1023/A:1021298729297
Morgan, L., Leatzow, A., Clark, S., & Siller, M. (2014). Interview skills for adults with autism spectrum disorder: A pilot randomized controlled trial. Journal of Autism and Developmental Disorders, 44(9), 2290–2300. https://doi.org/10.1007/s10803-014-2100-3
Moskowitz, G. B. (2005). Social cognition: Understanding self and others. Guilford Press.
Mueller, E., Schuler, A. L., Burton, B., & Yates, G. (2003). Meeting the vocational support needs of individuals with Asperger’s syndrome and other autism spectrum disabilities. Journal of Vocational Rehabilitation, 18(3), 163–176.
Mulvihill, B., Wingate, M., Kirby, R. S., Pettygrove, S., Cunniff, C., Meaney, F. J., Miller, L., Robinson, C., Quintana, G., Kaiser, M. Y., Lee, L. C., Landa, R., Newschaffer, C., Constantino, J., Fitzgerald, R., Daniels, J., Giarelli, E., Pinto-Martin, J., Levy, S. E., . . . Doernberg, N. (2009). Prevalence of autism spectrum disorders—Autism and Developmental Disabilities Monitoring Network, United States, 2006. MMWR Surveillance Summaries, 58(10), 1–20.
Myers, E., Davis, B. E., Stobbe, G., & Bjornson, K. (2015). Community and social participation among individuals with autism spectrum disorder transitioning to adulthood. Journal of Autism and Developmental Disorders, 45(8), 2373–2381. https://doi.org/10.1007/s10803-015-2403-z
National Joint Committee for the Communication Needs of Persons With Severe Disabilities. (2003). Position statement on access to communication services and supports: Concerns regarding the application of restrictive “eligibility” policies [Position statement]. https://www.asha.org/policy/
National Research Council. (2001). Educating children with autism. National Academy Press.
Nelson, K. (1978). How children represent knowledge of their world in and out of language: A preliminary report. In R. S. Siegler (Ed.), Children’s thinking: What develops? (pp. 255–273). Erlbaum.
Noyes, A. M., & Wilkinson, K. M. (2022). Supporting access to mental health services for patients who use augmentative and alternative communication: A proposed framework and suggestions for future directions. American Journal of Speech-Language Pathology, 31(5), 2268–2282. https://doi.org/10.1044/2022_AJSLP-22-00089
Olusanya, B. O., Smythe, T., Ogbo, F. A., Nair, M. K. C., Scher, M., & Davis, A. C. (2023). Global prevalence of developmental disabilities in children and adolescents: A systematic umbrella review. Frontiers in Public Health, 11, 1122009. https://doi.org/10.3389/fpubh.2023.1122009
Orsmond, G. I., Shattuck, P. T., Cooper, B. P., Sterzing, P. R., & Anderson, K. A. (2013). Social participation among young adults with an autism spectrum disorder. Journal of Autism and Developmental Disorders, 43(11), 2710–2719. https://doi.org/10.1007/s10803-013-1833-8
Ozonoff, S., Young, G. S., Carter, A., Messinger, D., Yirmiya, N., Zwaigenbaum, L., Bryson, S., Carver, L. J., Constantino, J. N., Dobkins, K., Hutman, T., Iverson, J. M., Landa, R., Rogers, S. J., Sigman, M., & Stone, W. L. (2011). Recurrence risk for autism spectrum disorders: A Baby Siblings Research Consortium study. Pediatrics, 128(3), e448–e495. https://doi.org/10.1542/peds.2010-2825
Patten, E., Belardi, K., Baranek, G. T., Watson, L. R., Labban, J. D., & Oller, D. K. (2014). Vocal patterns in infants with autism spectrum disorder: Canonical babbling status and vocalization frequency. Journal of Autism and Developmental Disorders, 44(10), 2413–2428. https://doi.org/10.1007/s10803-014-2047-4
Payton, J. W., Wardlaw, D. M., Graczyk, P. A., Bloodworth, M. R., Tompsett, C. J., & Weissberg, R. P. (2000). Social and emotional learning: A framework for promoting mental health and reducing risk behavior in children and youth. Journal of School Health, 70(5), 179–185. https://doi.org/10.1111/j.1746-1561.2000.tb06468.x
Pea, E. D. (1996). Dynamic assessment: The model and its language applications. In K. N. Cole, P. S. Dale, & D. J. Thal (Eds.), Communication and language intervention series: Vol. 6. Advances in assessment of communication and language (pp. 281–307). Brookes.
Pearson, J. N., Hamilton, M.-B., & Meadan, H. (2018). “We saw our son blossom”: A guide for fostering culturally responsive partnerships to support African American autistic children and their families. Perspectives of the ASHA Special Interest Groups, 3(1), 84–97. https://doi.org/10.1044/persp3.SIG1.84
Perryman, T., Ricks, L., & Cash-Baskett, L. (2020). Meaningful transitions: Enhancing clinician roles in transition planning for adolescents with autism spectrum disorders. Language, Speech, and Hearing Services in Schools, 51(4), 899–913. https://doi.org/10.1044/2020_LSHSS-19-00048
Peters, A. (1983). The units of language acquisition. Cambridge University Press.
Pickett, E., Pullara, O., O’Grady, J., & Gordon, B. (2009). Speech acquisition in older nonverbal individuals with autism: A review of features, methods, and prognosis. Cognitive and Behavioral Neurology, 22(1), 1–21. https://doi.org/10.1097/WNN.0b013e318190d185
Pierce, K., Carter, C., Weinfeld, M., Desmond, J., Hazin, R., Bjork, R., & Gallagher, N. (2011). Detecting, studying, and treating autism early: The one-year well-baby check-up approach. The Journal of Pediatrics, 159(3), 458–465. https://doi.org/10.1016/j.jpeds.2011.02.036
Pirinen, V., Loukusa, S., Dindar, K., Mäkinen, L., Hurtig, T., Jussila, K., Mattila, M. L., & Eggers, K. (2023). A comprehensive analysis of speech disfluencies in autistic young adults and control young adults: Group differences in typical, stuttering-like, and atypical disfluencies. Journal of Speech, Language, and Hearing Research, 66(3), 832–848. https://doi.org/10.1044/2022_JSLHR-22-00265
Plauché Johnson, C., & Myers, S. M. (2007). Identification and evaluation of children with autism spectrum disorders. Pediatrics, 120(5), 1183–1215. https://doi.org/10.1542/peds.2007-2361
Plumb, A. M., & Wetherby, A. M. (2013). Vocalization development in toddlers with autism spectrum disorder. Journal of Speech, Language, and Hearing Research, 56(2), 721–734. https://doi.org/10.1044/1092-4388(2012/11-0104)
Polirstok, S. R., Dana, L., Buono, S., Mongelli, V., & Trubia, G. (2003). Improving functional communication skills in adolescents and young adults with severe autism using gentle teaching and positive approaches. Topics in Language Disorders, 23(2), 146–153. https://doi.org/10.1097/00011363-200304000-00007
Prizant, B. M. (1982). Gestalt language and gestalt processing in autism. Topics in Language Disorders, 3(1), 16–23.
Prizant, B. M. (1983). Language acquisition and communicative behavior in autism: Toward an understanding of the “whole” of it. Journal of Speech and Hearing Disorders, 48(3), 296–307. https://doi.org/10.1044/jshd.4803.296
Prizant, B. M., & Duchan, J. F. (1981). The functions of immediate echolalia in autistic children. Journal of Speech and Hearing Disorders, 46(3), 241–249. https://doi.org/10.1044/jshd.4603.241
Prizant, B. M., & Rydell, P. J. (1984). Analysis of functions of delayed echolalia in autistic children. Journal of Speech and Hearing Research, 27(2), 183–192. https://doi.org/10.1044/jshr.2702.183
Prizant, B. M., & Wetherby, A. M. (1998). Understanding the continuum of discrete-trial traditional behavioral to social-pragmatic developmental approaches in communication enhancement for young children with autism/PDD. Seminars in Speech and Language, 19(4), 329–353. https://doi.org/10.1055/s-2008-1064053
Prizant, B. M., Wetherby, A. M., Rubin, E., Laurent, A. C., & Rydell, P. J. (2006). The SCERTS Model: Comprehensive educational approach for children with autism spectrum disorders. Brookes.
Rau, S., Skapek, M. F., Tiplady, K., Seese, S., Burns, A., Armour, A. C., & Kenworthy, L. (2020). Identifying comorbid ADHD in autism: Attending to the inattentive presentation. Research in Autism Spectrum Disorders, 69, 101468. https://doi.org/10.1016/j.rasd.2019.101468
Richards, C., Jones, C., Groves, L., Moss, J., & Oliver, C. (2015). Prevalence of autism spectrum disorder phenomenology in genetic disorders: A systematic review and meta-analysis. The Lancet Psychiatry, 2(10), 909–916. https://doi.org/10.1016/S2215-0366(15)00376-4
Rogers, S. J., & Dawson, G. (2009). Play and engagement in early autism: The Early Start Denver Model. Volume I: The Treatment. Guilford.
Rogers, S. J., & Dawson, G. (2010). Early Start Denver Model for young children with autism: Promoting language, learning, and engagement. Guilford.
Rosenhall, U., Nordin, V., Sandström, M., Ahlsén, G., & Gillberg, C. (1999). Autism and hearing loss. Journal of Autism and Developmental Disorders, 29(5), 349–357. https://doi.org/10.1023/a:1023022709710
Rubenstein, E., Schieve, L., Wiggins, L., Rice, C., Van Naarden Braun, K., Christensen, D., Durkin, M., Daniels, J., & Lee, L.-C. (2018). Trends in documented co-occurring conditions in children with autism spectrum disorder, 2002–2010. Research in Developmental Disabilities, 83, 168–178. https://doi.org/10.1016/j.ridd.2018.08.015
Rubenstein, E., Tewolde, S., Michals, A., Fox, M., & Wang, N. (2023). Prevalence of autism among Medicaid-enrolled adults. JAMA Psychiatry, 80(12), 1284–1287. https://doi.org/10.1001/jamapsychiatry.2023.3708
Rydell, P. (2012). Learning Style Profile for Children with Autism Spectrum Disorder. Rocky Mountain Autism Center.
Scarpa, A., & Reyes, N. M. (2011). Improving emotion regulation with CBT in young children with high functioning autism spectrum disorders: A pilot study. Behavioural and Cognitive Psychotherapy, 39(4), 495–500. https://doi.org/10.1017/S1352465811000063
Shane, H. C., & Bashir, A. S. (1980). Election criteria for the adoption of an augmentative communication system: Preliminary considerations. Journal of Speech and Hearing Disorders, 45(3), 408–414. https://doi.org/10.1044/jshd.4503.408
Shattuck, P. T., Carter Narendorf, S., Cooper, B., Sterzing, P. R., Wagner, M., & Lounds Taylor, J. (2012). Postsecondary education and employment among youth with an autism spectrum disorder. Pediatrics, 129(6), 1042–1049. https://doi.org/10.1542/peds.2011-2864
Shield, A., Cooley, F., & Meier, R. P. (2017). Sign language echolalia in deaf children with autism spectrum disorder. Journal of Speech, Language, and Hearing Research, 60(6), 1622–1634. https://doi.org/10.1044/2016_JSLHR-L-16-0292
Smith, M. J., Ginger, E. J., Wright, K., Wright, M. A., Lounds Taylor, J., Humm, L. B., Olsen, D. E., Bell, M. D., & Fleming, M. F. (2014). Virtual reality job interview training in adults with autism spectrum disorder. Journal of Autism and Developmental Disorders, 44(10), 2450–2463. https://doi.org/10.1007/s10803-014-2113-y
Snell, M. E. (2002). Using dynamic assessment with learners who communicate nonsymbolically. Augmentative and Alternative Communication, 18(3), 163–176. https://doi.org/10.1080/07434610212331281251
Solomon, R., Van Egeren, L. A., Mahoney, G., Quon Huber, M. S., & Zimmerman, P. (2014). PLAY Project Home Consultation intervention program for young children with autism spectrum disorders: A randomized controlled trial. Journal of Developmental & Behavioral Pediatrics, 35(5), 475–485. https://doi.org/10.1097/DBP.0000000000000096
Stanford, S. (2020). The school-based speech-language pathologist's role in diverting the school-to-confinement pipeline for youth with communication disorders. Perspectives of the ASHA Special Interest Groups, 5(4), 1057–1066. https://doi.org/10.1044/2020_PERSP-20-0002
Stiegler, L. N. (2015). Examining the echolalia literature: Where do speech-language pathologists stand? American Journal of Speech-Language Pathology, 24(4), 750–762. https://doi.org/10.1044/2015_AJSLP-14-0166
Stiegler, L. N., & Davis, R. (2010). Understanding sound sensitivity in individuals with autism spectrum disorders. Focus on Autism and Other Developmental Disabilities, 25(2), 67–75. https://doi.org/10.1177/1088357610364530
Sussman, F. (1999). More Than Words: Helping parents promote communication and social skills in children with autism spectrum disorder. The Hanen Centre.
Sussman, F. (2006). TalkAbility: People skills for verbal children on the autism spectrum: A guide for parents. The Hanen Centre.
Swanson, N. (2019). The right codes for ASD-related services. The ASHA Leader, 24(5), 32–34. https://doi.org/10.1044/leader.BML.24052019.3
Szarkowski, A., Flynn, S., & Clark, T. (2014). Dually diagnosed: A retrospective study of the process of diagnosing autism spectrum disorders in children who are deaf and hard of hearing. Seminars in Speech and Language, 35(4), 301–308. https://doi.org/10.1055/s-0034-1389102
Szarkowski, A., Mood, D., Shield, A., Wiley, S., & Yoshinaga-Itano, C. (2014). A summary of current understanding regarding children with autism spectrum disorder who are deaf or hard of hearing. Seminars in Speech and Language, 35, 241–259. https://doi.org/10.1055/s-0034-1389097
Szymanski, C., & Brice, P. J. (2008). When autism and deafness coexist in children: What we know now. Odyssey: New Directions in Deaf Education, 9(1), 10–15.
Taylor Dyches, T. (2011). Assessing diverse students with autism spectrum disorders. The ASHA Leader, 16(1), 12–15. https://doi.org/10.1044/leader.FTR2.16012011.12
Taylor Dyches, T., Wilder, L., & Obiakor, F. (2001). Autism: Multicultural perspectives. In T. Wahlberg, F. Obiakor, S. Burkhardt, & A. F. Rotatori (Eds.), Autistic spectrum disorders: Educational and clinical interventions: Vol. 14. Advances in special education (pp. 151–177). Emerald Group Publishing. https://doi.org/10.1016/S0270-4013(01)80012-X
Tek, S., & Landa, R. J. (2012). Differences in autism symptoms between minority and non-minority toddlers. Journal of Autism and Developmental Disorders, 42(9), 1967–1973. https://doi.org/10.1007/s10803-012-1445-8
Tierney, C., Mayes, S., Lohs, S. R., Black, A., Gisin, E., & Veglia, M. (2015). How valid is the checklist for autism spectrum disorder when a child has apraxia of speech? Journal of Developmental & Behavioral Pediatrics, 36(8), 569–574. https://doi.org/10.1097/DBP.0000000000000189
Timothy W. v. Rochester, New Hampshire School District, 875 F.2d 954 (1st Cir.) cert. denied, 493 U.S. 983 (1989).
Trudeau, S., Anne, S., Otteson, T., Hopkins, B., Georgopoulos, R., & Wentland, C. (2021). Diagnosis and patterns of hearing loss in children with severe developmental delay. American Journal of Otolaryngology, 42(3), 102923. https://doi.org/10.1016/j.amjoto.2021.102923
Tsatsanis, K. D., Foley, C., & Donehower, C. (2004). Contemporary outcome research and programming guidelines for Asperger syndrome and high-functioning autism. Topics in Language Disorders, 24(4), 249–259. https://doi.org/10.1097/00011363-200410000-00003
Turner-Brown, L. M., Baranek, G. T., Reznick, J. S., Watson, L. R., & Crais, E. R. (2012). The First Year Inventory: A longitudinal follow-up of 12-month-old to 3-year-old children. Autism, 17(5), 527–540. https://doi.org/10.1177/1362361312439633
U.S. Department of Education. (2023). 44th annual report to congress on the implementation of the Individuals with Disabilities Education Act, 2022. https://sites.ed.gov/idea/44th-annual-report-to-congress-on-idea
Wang, X., Weng, X., Pan, N., Li, X., Lin, L., & Jing, J. (2023). Prevalence of autism spectrum disorder in the United States is stable in the COVID-19 era. Journal of Autism and Developmental Disorders, 53(8), 3309–3312. https://doi.org/10.1007/s10803-023-05915-w
Warrier, V., Greenberg, D. M., Weir, E., Buckingham, C., Smith, P., Lai, M. C., Allison, C., & Baron-Cohen, S. (2020). Elevated rates of autism, other neurodevelopmental and psychiatric diagnoses, and autistic traits in transgender and gender-diverse individuals. Nature Communications, 11, 3959. https://doi.org/10.1038/s41467-020-17794-1
Watanabe, M., & Sturmey, P. (2003). The effect of choice-making opportunities during activity schedules on task engagement of adults with autism. Journal of Autism and Developmental Disorders, 33(5), 535–538. https://doi.org/10.1023/a:1025835729718
Watson, L. R., Crais, E. R., Baranek, G. T., Dykstra, J. R., Wilson, K. P., Hammer, C. S., & Woods, J. (2013). Communicative gesture use in infants with and without autism: A retrospective home video study. American Journal of Speech-Language Pathology, 22(1), 25–39. https://doi.org/10.1044/1058-0360(2012/11-0145)
Wei, X., Wagner, M., Hudson, L., Yu, J. W., & Shattuck, P. (2015). Transition to adulthood: Employment, education, and disengagement in individuals with autism spectrum disorder. Emerging Adulthood, 3(1), 37–45. https://doi.org/10.1177/2167696814534417
Weng, P. L., Maeda, Y., & Bouck, E. C. (2014). Effectiveness of cognitive skills–based computer-assisted instruction for students with disabilities: A synthesis. Remedial and Special Education, 35(3), 167–180. https://doi.org/10.1177/0741932513514858
Werner, E., & Dawson, G. (2005). Validation of the phenomenon of autistic regression using home videotapes. Archives of General Psychiatry, 62(8), 889–895. https://doi.org/10.1001/archpsyc.62.8.889
Wetherby, A. M., Brosnan-Maddox, S., Peace, V., & Newton, L. (2008). Validation of the Infant–Toddler Checklist as a broadband screener for autism spectrum disorders from 9 to 24 months of age. Autism, 12(5), 487–511. https://doi.org/10.1177/1362361308094501
Wetherby, A. M., Prizant, B. M., & Schuler, A. L. (2000). Understanding the nature of communication and language impairments. In A. M. Wetherby & B. M. Prizant (Eds.), Autism spectrum disorders: A transactional developmental perspective: Vol. 9 (pp. 109–141). Brookes.
Whitlock, A., Fulton, K., Lai, M. C., Pellicano, E., & Mandy, W. (2020). Recognition of girls on the autism spectrum by primary school educators: An experimental study. Autism Research, 13(8), 1358–1372. https://doi.org/10.1002/aur.2316
Wilder, L. K., Taylor Dyches, T., Obiakor, F. E., & Algozzine, B. (2004). Multicultural perspectives on teaching students with autism. Focus on Autism and Other Developmental Disabilities, 19(2), 105–113. https://doi.org/10.1177/10883576040190020601
Willey, L. H. (1999). Pretending to be normal: Living with Asperger’s syndrome. Jessica Kingsley Publishers.
Williams, D. (2012, March). Neurological basis for autism: Implications for speech-language pathologists [Mini-seminar]. Annual Ohio Speech-Language-Hearing Association Convention, Columbus, OH, United States.
Williams, Z. J., Suzman, E., & Woynaroski, T. G. (2021). Prevalence of decreased sound tolerance (hyperacusis) in individuals with autism spectrum disorder: A meta-analysis. Ear and Hearing, 42(5), 1137–1150. https://doi.org/10.1097/AUD.0000000000001005
Wilson, K. P. (2013). Incorporating video modeling into a school-based intervention for students with autism spectrum disorders. Language, Speech, and Hearing Services in Schools, 44(1), 105–117. https://doi.org/10.1044/0161-1461(2012/11-0098)
Wolfberg, P. J., & Schuler, A. L. (1993). Integrated play groups: A model for promoting the social and cognitive dimensions of play in children with autism. Journal of Autism and Developmental Disorders, 23(3), 467–489. https://doi.org/10.1007/BF01046051
Wood, J. J., Drahota, A., Sze, K., Van Dyke, M., Decker, K., Fujii, C., Bahng, C., Renno, P., Hwang, W.-C., & Spiker, M. (2009). Brief report: Effects of cognitive behavioral therapy on parent-reported autism symptoms in school-age children with high-functioning autism. Journal of Autism and Developmental Disorders, 39(11), 1608–1612. https://doi.org/10.1007/s10803-009-0791-7
Woods, J. J., & Wetherby, A. M. (2003). Early identification of and intervention for infants and toddlers who are at risk for autism spectrum disorder. Language, Speech, and Hearing Services in Schools, 34(3), 180–193. https://doi.org/10.1044/0161-1461(2003/015)
Wood-Downie, H., Wong, B., Kovshoff, H., Cortese, S., & Hadwin, J. A. (2021). Research review: A systematic review and meta-analysis of sex/gender differences in social interaction and communication in autistic and nonautistic children and adolescents. The Journal of Child Psychology and Psychiatry, 62(8), 922–936. https://doi.org/10.1111/jcpp.13337
World Health Organization. (2001). International classification of functioning, disability and health (ICF).
Yu, B. (2013). Issues in bilingualism and heritage language maintenance: Perspectives of minority-language mothers of children with autism spectrum disorders. American Journal of Speech-Language Pathology, 22(1), 10–24. https://doi.org/10.1044/1058-0360(2012/10-0078)
Yu, B., & Sterponi, L. (2022). Toward neurodiversity: How conversation analysis can contribute to a new approach to social communication assessment. Language, Speech, and Hearing Services in Schools, 54, 27–41. https://doi.org/10.1044/2022_LSHSS-22-00041
Zisk, A. H., & Dalton, E. (2019). Augmentative and alternative communication for speaking autistic adults: Overview and recommendations. Autism in Adulthood, 1(2), 93–100. https://doi.org/10.1089/aut.2018.0007
Zwaigenbaum, L., Bryson, S., Rogers, T., Roberts, W., Brian, J., & Szatmari, P. (2005). Behavioral manifestations of autism in the first year of life. International Journal of Developmental Neuroscience, 23(2–3), 143–152. https://doi.org/10.1016/j.ijdevneu.2004.05.001
Content for ASHA’s Practice Portal is developed through a comprehensive process that includes multiple rounds of subject matter expert input and review. ASHA extends its gratitude to the following subject matter experts who were involved in the development of the Autism and Autism Spectrum Disorder page.
In addition, ASHA thanks the members of the Ad Hoc Committee on Autism Spectrum Disorders whose work was foundational to the development of this content. Members of the committee were Amy Wetherby (chair), Sylvia Diehl, Emily Rubin, Adriana Schuler, Linda Watson, Jane Wegner, and Ann-Mari Pierotti (ex officio). Celia Hooper, vice president for professional practices in speech-language pathology, 2003–2005, served as monitoring officer.
The recommended citation for this Practice Portal page is:
American Speech-Language-Hearing Association. (n.d.). Autism and autism spectrum disorder [Practice portal]. https://www.asha.org/Practice-Portal/Clinical-Topics/Autism/
Content Disclaimer: The Practice Portal, ASHA policy documents, and guidelines contain information for use in all settings; however, members must consider all applicable local, state and federal requirements when applying the information in their specific work setting.