ArticlePDF Available

Examining US Public Early Intervention for Toddlers With Autism: Characterizing Services and Readiness for Evidence-Based Practice Implementation


Abstract and Figures

As the rates of Autism Spectrum Disorder (ASD) increase and early screening efforts intensify, more toddlers with high likelihood of ASD are entering the United States' (US') publicly funded early intervention system. Early intervention service delivery for toddlers with ASD varies greatly based on state resources and regulations. Research recommends beginning ASD-specific evidence-based practices (EBP), especially caregiver-implemented intervention, as early as possible to facilitate the development of social-communication skills and general learning. Translating EBP into practice has been challenging, especially in low-resourced areas. The main goal of this study was to obtain a more comprehensive understanding of public early intervention system structure, service delivery practices, and factors influencing EBP use for children with ASD in the US. Participants ( N = 133) included 8 early intervention state coordinators in 7 states, 29 agency administrators in those states, 57 early intervention providers from those agencies, and 39 caregivers of children with ASD receiving services from those providers. Online surveys gathered stakeholder and caregiver perspectives on early intervention services as well as organizational factors related to EBP implementation climate and culture. Stakeholders identified key intervention needs for young children with ASD. In general, both agency administrators and direct providers reported feeling somewhat effective or very effective in addressing most needs of children with ASD. They reported the most difficulty addressing eating, sleeping, family stress, and stereotyped behaviors. Data indicate that children from families with higher income received significantly higher service intensity. While administrators and providers reported high rates of high-quality caregiver coaching (>60%), caregivers reported low rates (23%). Direct providers with more favorable attitudes toward EBP had greater EBP use. In turn, provider attitudes toward EBP were significantly associated with implementation leadership and culture at their agency. Results suggest that publicly funded early intervention programs in the US require additional resources and training for providers and leaders to support improved implementation climate and attitudes toward ASD EBPs. Results also suggest that more state system support is needed to increase use of ASD-specific EBP use, including high-quality caregiver coaching, to better serve toddlers with ASD. Recommendations for implementation strategies are addressed.
Content may be subject to copyright.
published: 16 December 2021
doi: 10.3389/fpsyt.2021.786138
Frontiers in Psychiatry | 1December 2021 | Volume 12 | Article 786138
Edited by:
Annarita Contaldo,
University of Pisa, Italy
Reviewed by:
Lobna Abdel Gawad Mansour,
Cairo University, Egypt
Katherine Stavropoulos,
University of California, Riverside,
United States
Aubyn C. Stahmer
Specialty section:
This article was submitted to
a section of the journal
Frontiers in Psychiatry
Received: 29 September 2021
Accepted: 24 November 2021
Published: 16 December 2021
Aranbarri A, Stahmer AC, Talbott MR,
Miller ME, Drahota A, Pellecchia M,
Barber AB, Griffith EM, Morgan EH
and Rogers SJ (2021) Examining US
Public Early Intervention for Toddlers
With Autism: Characterizing Services
and Readiness for Evidence-Based
Practice Implementation.
Front. Psychiatry 12:786138.
doi: 10.3389/fpsyt.2021.786138
Examining US Public Early
Intervention for Toddlers With
Autism: Characterizing Services and
Readiness for Evidence-Based
Practice Implementation
Aritz Aranbarri 1,2,3 , Aubyn C. Stahmer 1
*, Meagan R. Talbott 1, Marykate E. Miller 1,
Amy Drahota 4, Melanie Pellecchia 5, Angela B. Barber 6, Elizabeth McMahon Griffith 7,
Elizabeth H. Morgan 1,8 and Sally J. Rogers 1
1Collaborative START Lab, The MIND Institute, Psychiatry and Behavioral Sciences, University of California, Davis,
Sacramento, CA, United States, 2Child and Adolescent Mental Health Area, Psychiatry and Psychology, Hospital Sant Joan
de Déu Barcelona, Esplugues de Llobregat, Spain, 3Child and Adolescent Mental Health Research Group, Psychiatry and
Psychology, Institut de Recerca Sant Joan de Déu, Esplugues de Llobregat, Spain, 4Department of Psychology, Michigan
State University, East Lansing, MI, United States, 5Center for Mental Health, Psychiatry Department, University of
Pennsylvania, Perelman School of Medicine, Philadelphia, PA, United States, 6Department of Communicative Disorders,
University of Alabama, Tuscaloosa, AL, United States, 7Department of Pediatrics, University of Colorado School of Medicine,
Aurora, CO, United States, 8College of Education, California State University, Sacramento, CA, United States
As the rates of Autism Spectrum Disorder (ASD) increase and early screening efforts
intensify, more toddlers with high likelihood of ASD are entering the United States’
(US’) publicly funded early intervention system. Early intervention service delivery for
toddlers with ASD varies greatly based on state resources and regulations. Research
recommends beginning ASD-specific evidence-based practices (EBP), especially
caregiver-implemented intervention, as early as possible to facilitate the development of
social-communication skills and general learning. Translating EBP into practice has been
challenging, especially in low-resourced areas. The main goal of this study was to obtain a
more comprehensive understanding of public early intervention system structure, service
delivery practices, and factors influencing EBP use for children with ASD in the US.
Participants (N=133) included 8 early intervention state coordinators in 7 states,
29 agency administrators in those states, 57 early intervention providers from those
agencies, and 39 caregivers of children with ASD receiving services from those providers.
Online surveys gathered stakeholder and caregiver perspectives on early intervention
services as well as organizational factors related to EBP implementation climate and
culture. Stakeholders identified key intervention needs for young children with ASD. In
general, both agency administrators and direct providers reported feeling somewhat
effective or very effective in addressing most needs of children with ASD. They reported
the most difficulty addressing eating, sleeping, family stress, and stereotyped behaviors.
Data indicate that children from families with higher income received significantly higher
service intensity. While administrators and providers reported high rates of high-quality
caregiver coaching (>60%), caregivers reported low rates (23%). Direct providers with
more favorable attitudes toward EBP had greater EBP use. In turn, provider attitudes
Aranbarri et al. ASD Early Intervention: Characterizing Services
toward EBP were significantly associated with implementation leadership and culture at
their agency. Results suggest that publicly funded early intervention programs in the US
require additional resources and training for providers and leaders to support improved
implementation climate and attitudes toward ASD EBPs. Results also suggest that more
state system support is needed to increase use of ASD-specific EBP use, including high-
quality caregiver coaching, to better serve toddlers with ASD. Recommendations for
implementation strategies are addressed.
Keywords: ASD, autism, early intervention, community-based research, implementation science, health services
Autism Spectrum Disorder (ASD) is one of the most common
forms of neurodevelopmental disabilities, with a rate of 1 in
every 54 children born in United States (US) (1). Increases in
awareness and screening have led to a higher demand for autism-
specific early intervention services. This has led to a need to better
understand how public service systems address early intervention
for toddlers with ASD who have delays across multiple areas of
development (2).
Research demonstrates that specific early intervention models
can lead to significant gains in social communication, language
development, and adaptative behavior in young children with
ASD (36). Several groups have published recommendations and
quality indicators for best practices in early intervention for ASD
(7) that include using evidence-based approaches, beginning
intervention as early as possible, active involvement of caregivers
as part of the intervention, individualizing treatment based on
child, family, cultural, and contextual needs, using curriculum
content with a focus on child’s social communication, play skills,
cognitive, self-help, and behavioral needs, and providing high
levels of staff education and training. Recent studies strongly
support the role of caregivers’ active involvement in early
intervention for achieving optimal short and long-term outcomes
(8). Toddlers with ASD may also require a higher intensity of
service provision to optimize outcomes (9), although the specific
number of hours per week needed is not clear (10,11).
Despite broad agreement on most of these recommendations,
in practice meeting these standards within the available
publicly funded early intervention community service system
remains very challenging. A recent meta-analysis (12) found
less favorable outcomes when children with ASD received
community intervention compared to hospital/University-based
intervention demonstrating significant differences between the
types of services being tested and recommended by researchers,
and the community services most families receive. Challenges in
community implementation may be related to many variables:
the complexity of ASD-specific evidence-based practices (EBP),
limited opportunities for and variability in staff training, lack
of autism-specific support, large caseloads and high overall
work demands, low-intensity of service delivery, high diversity
both clinically and culturally among clients and areas served,
and low funding rates, among others. However, we have
limited information about the specific barriers that limited
implementation of EBPs in community early intervention
services. To bridge the gap between research and practice,
researchers must first understand the implementation context.
In the US, children under the age of 3 with an ASD diagnosis
or early signs of ASD are typically eligible for public early
intervention services provided by Part C of the Individuals with
Disabilities Education Act (13). Few states have clear policies
or practices in place regarding the type or intensity of Part C
early intervention services for young children with ASD, and
only a quarter of states have specific intervention guidelines (14).
Services may range from simple surveillance, such as a monthly
visit from a social worker to intensive interventions, such as 20 h
a week of intervention involving delivery of EBPs and parent
education. The average service intensity in Part C is 90 min
per week (15). As a result of these variables high-quality ASD-
specific practices are especially difficult to access in low-resource
areas of the US (16). For example, although Part C requirements
prioritize and mandate family involvement in early intervention,
existing data indicate that most community providers have
caregivers playing a passive rather than an active, collaborative
and participatory role in their child’s intervention (1721). This
lack of active capacity building for primary caregivers allows for
little carryover of intervention strategies into daily routines and
does not accomplish the Part C goal of building early intervention
competence in the child’s family (22).
To better understand how to improve translation of EBP,
such as parent coaching, into publicly funded early intervention
services, we must identify the current service landscape at
multiple levels and from varied perspectives (23). Factors
related to organizational leader, direct service provider, and
consumer characteristics, as well as the organizational climate
for innovation, are all related to the quality and use of EBP.
The recent field of implementation science provides guidance
for identifying determinants of high-quality use of EBP to guide
training, adaptation, and implementation of innovative EBP.
For example, direct service providers report that intervention
practices developed in research settings are too rigid and do
not serve the diversity and complexity of day-to-day practices
(24,25). This is concerning as data indicate that providers’
perceptions toward EBPs are linked to uptake and delivery (26).
Thus, practitioner attitudes toward EBPs have been considered
a target mechanism to improve EBP implementation (27,28).
Data from one early study indicated early intervention providers
working with children with ASD had more favorable attitudes
Frontiers in Psychiatry | 2December 2021 | Volume 12 | Article 786138
Aranbarri et al. ASD Early Intervention: Characterizing Services
toward EBPs than mental health professionals generally and
perceived less divergence between their current practice and
EBP (29). However, to the best of our knowledge no recent
studies have specifically examined provider attitudes toward
the use evidence-based early intervention strategies for ASD,
including caregiver involvement in intervention, or whether
direct providers are considering the evidence-base of their
practices when intervening with their clients (14,30).
So far, a majority of implementation work has focused
primarily on direct service providers as the end-users of
EBPs, and less on other individuals involved in community
implementation (31). However, implementation science has
identified leadership as a key component of successful EBP
adoption, implementation, and sustainment in community
services (32). Leadership can drive EBP implementation through
fostering an organizational context in favor of EBP use, for
example, by prioritizing provider access to EBP training.
Leaders can be instrumental in institutionalizing EBPs, allocating
resources strategically to ensure continuity of implementation,
or by serving as EBP champions (32). Therefore, leaders can
have a profound influence on both the organizational climate
(i.e., staff perception of their work environment) and culture
(i.e., normative beliefs and shared behavioral expectations in an
organizational unit), which in turn can shape the perceptions,
attitudes, and implementation by direct service providers (33).
Overall, there are limited data regarding implementation of
EBP in community-based early intervention settings, particularly
for families in low-resource areas and from historically
marginalized backgrounds. Preliminary data indicate that
providers report implementing broader elements of EBP
strategies rather than the specific techniques that underlie each
EBP, adapting them in various ways to meet child and family
needs as they deem appropriate (34). Thus, there is a need
to describe the early intervention services taking place for
toddlers with an elevated likelihood of ASD, and to examine
the organizational context that could support use of EBP in
low-resourced community settings.
The current study adds to the small body of the literature
in this area by studying the structure and practices involved in
community Part C delivery in the US public early intervention
system focusing on services for children with or at high
likelihood of having ASD living in low-resourced areas.
Specifically, we aimed to: (1) characterize early intervention
services for ASD across seven states serving families in low-
resource areas in the US; (2) examine intervention practices
and strategies and use of EBP in these systems; and (3)
examine organizational and contextual factors influencing
system readiness for EBP implementation.
The survey described in this study was conducted as part
of a larger community-partnered project designed to adapt
an evidence-based early intervention for use in low-resourced
service systems. The study used a community-based participatory
research methodology (35) with partners in seven states. Partner
groups included a mix of representatives including researchers,
early intervention agency administrators and direct service
providers, and caregivers of children with ASD participating
in the early intervention system in their state. The teams met
to identify methods for supporting services in rural and low-
resource communities within their state and to collaborate on
survey development, recruitment, and data interpretation. This
specific study involved surveying early intervention stakeholders
at multiple levels of the Part C delivery structure.
Recruitment and Distribution
Participants included individuals involved in one of four
distinct tiers of the federally funded (Part C of the IDEA)
early intervention delivery structure in the US, specifically
providing services for children with or at high likelihood
of having ASD. Inclusion criteria were as follows: (a)
State Part C Coordinators (coordinator) serving as the
designated state early intervention system leader for each
participating state. (b) Agency administrator (administrator)
participants had to have at least 1 year of experience leading
an agency serving children with ASD under age 3 in a low-
income region of the state, at an agency funded through the
Part C system, and have at least one qualifying direct service
provider also working at that agency. (c) Direct Service Providers
(provider) met the following inclusion criteria: (1) having served
at least 2 toddlers with high likelihood of ASD in the past
year in a participating agency, and (2) having at least 1 year
of experience with the population. (d) Primary Caregivers
(caregiver) had the following inclusion criteria: (1) legal
guardians of a child with or at high likelihood of having ASD
participating in Part C services and (2) receiving services from a
participating provider.
To facilitate a high response rate and obtain a broad view of
publicly funded early intervention services for young children
with ASD and their families in the US, participants were
recruited from two primary sources. First, participants were
recruited from the larger project’s partners in 7 US states
(i.e., Pennsylvania, New Mexico, Montana, Maine, Colorado,
California, and Alabama). Participants originating from referrals
through state partners consisted of approximately 27.4% of
all survey participants. All other participants were recruited
through a nomination system starting with state coordinators
and ending with caregivers. State coordinators nominated at
least two administrators in agencies providing early intervention
services to low-resource and/or low-income families within
their state. Participating administrators nominated at least
three providers in their agency that directly serve young
children with autism or high likelihood of autism. Finally,
participating providers nominated at least one family on their
caseload with a young child in this population. This method
provided 72.5% of our total participant pool. If we did not
get a response from at least one provider or one family, the
study coordinator contacted the referral source to request an
additional nomination.
The study team distributed online surveys via REDCap
between November 2015 and April 2016 through email. To
accommodate any technical or language barriers, arrangements
Frontiers in Psychiatry | 3December 2021 | Volume 12 | Article 786138
Aranbarri et al. ASD Early Intervention: Characterizing Services
TABLE 1 | Participants and agency demographics.
Variable Coordinators Administrators Providers Caregivers Total
Number of participants n=8(6%) n=29 (22%) n=57 (43%) n=39 (29%) n=133 (100%)
Child age (in month) 40.2 (21.2)
Participant’s age (in years) 55.9 (4.5) 51.8 (10) 44.6 (12.5)
% Of children with ASD in agency 6.3 (4.7) 9.7 (9.3) 29.5 (31)
Years of experience with ASD 18.2 (11) 13.9 (9.3)
Female 100% 90% 95% 100% 95%
Non-hispanic* 88% 86% 86% 79% 85%
Hispanic 12% 14% 12% 21% 15%
White 75% 90% 86% 77% 85%
Hawaiian/Pacific Islander 12% 3% 5% 8% 6%
Black/African American 12% 7% 5% 13% 8%
Asian 0% 0% 2% 0% <1%
Amer Indian/Alaskan 0% 0% 2% 3% 1%
Highest education
Some high school/HS/GED 0% 0% 0% 24% 7%
Some college 0% 0% 2% 29% 9%
College degree 25% 28% 32% 24% 28%
Master’s degree 62% 62% 60% 16% 48%
Doctorate 12% 7% 0% 0% 2%
Other 0% 7% 3% 3% 5%
Primary discipline
Psychologist 14% 14% –
Marriage/family therapist 4% 2%
Social worker 25% 11% 7%
Speech therapist 4% 22%
Physical therapist 4%
Educator 63% 50% 31%
Behavior specialist 5%
Others 10% 14% 14%
Marital status
Married – 59%
Divorced – 6%
Cohabiting, no marriage 13%
Single and unmarried 22%
Family annual income
Under $25,000 26%
$25,000–$49,000 – 21%
$50,000–$74,999 – 15%
$75,000–$99,999 – 26%
$100,000 and above 13%
The percentages not reaching 100% are due to minor-missing data.
*The terms Hispanic, Non-hispanic were used in the survey at the time. We use the more appropriate term Latinx in the manuscript.
were made to collect surveys from Spanish-speaking families
over the phone. One survey was collected via postal service.
Each participant received a survey-package specific to their role
(coordinator, administrator, provider, caregiver). Participants
were contacted by both phone and email with reminders
to complete the survey and to answer any questions. Upon
completion of the survey, participants were offered a $20 gift card
for their participation.
Frontiers in Psychiatry | 4December 2021 | Volume 12 | Article 786138
Aranbarri et al. ASD Early Intervention: Characterizing Services
One hundred and eighty one participants across 7 states were
contacted, and 133 participated (73%). Participants included
8 state coordinators (88% response rate; two states had two
coordinators complete the survey and one state did not
complete the survey); 29 administrators (76% response rate),
57 providers (73% response rate), and 39 caregivers of children
with autism (81% response rate). Seventy-three percent of all
participants completed the survey, 29% remained unopened
or unfinished, and 3% formally declined. See Table 1 for
respondents’ demographics.
Surveys were chosen to characterize the early intervention
service system context including service setting, funding, service
intensity, parent/caregiver involvement and child needs, use
and perspectives of EBP, and readiness for EBP implementation.
Surveys asked about the types of intervention practices
being used, including providers’ perceived confidence using
the interventions, and use of caregiver training method
(e.g., psychoeducation/training, caregiver practice with
feedback/coaching, etc.). Surveys included demographic
questions, components of the ACT SMART Agency Assessment
Battery (described below), and questions about implementation
of new practices. Table 2 lists the surveys completed at each
participant level.
Participant Demographics Survey
Participants at each level responded to questions describing
their agency, experience and/or family. All participants
TABLE 2 | Participant survey completion.
Participant Type Survey components
State Part C coordinators Participant demographics
Agency demographics
ASD—Needs, Strategies and Context
Survey (ASD-SIS)
Agency administrators Participant demographics
Agency demographics
ASD—Needs, Strategies and Context
Survey (ASD-SIS)
Modified Practice Attitudes
Scale (MPAS)—adapted
Direct providers Participant demographics
Agency demographics
ASD—Needs, Strategies and Context
Survey (ASD-SIS)
Organizational Readiness to Change
Assessment (ORCA)
Texas Christian University Organizational
Readiness for Change 4-Domain
Assessment (TCU ORC-D4)
Modified Practice Attitudes
Scale (MPAS)—adapted
Caregivers Participant demographics
ASD-needs, strategies and context survey
Caregiver/client survey
provided information about their age, gender, race/ethnicity,
and education. Caregivers responded to questions about
marital status, income, and primary language spoken (one
family completed the survey in Spanish) in the home. State
coordinators, administrators and providers responded to
questions about their primary discipline and years at the agency.
Administrators and providers also indicated their years of
experience working with youth with ASD and responded to
questions about their training.
Agency Demographics Survey
Coordinators, administrators, and providers responded to
questions regarding the percentage of children served in their
agency/state had ASD, the service setting(s) and funding sources.
ACT SMART Agency Assessment Battery
This assessment battery, developed by Drahota et al. (36)
specifically to provide a comprehensive, multi-level assessment
of agencies providing services to children with ASD, compiles
adapted versions of the ASD-Needs, Strategies and Context
Survey (37), the Modified Practice Attitudes Scale [MPAS;
(38)], the Organizational Context subscale of the Organizational
Readiness for Change Assessment [ORCA; (39)], and TCU
Organizational Readiness for Change-D4 [ORC-D4; (40)].
Measures were selected to evaluate the type and quality of
intervention strategies and services being delivered within
participating agencies and the extent to which services were
perceived to be meeting client needs as well as organizational
factors hypothesized to impact the quality and delivery of
ASD services (e.g., communication within agencies; readiness
for change; staff attributes, and attitudes) (41). A caregiver
component was included to obtain perspectives on child and
family needs, service provision and acceptability. Subscales from
the following assessments were used in this study.
ASD-Needs, Strategies, and Context Survey
Participants across levels reported on areas of intervention need
for children with ASD and how well a variety of needs were
being addressed by the current system/agency, service intensity,
and caregiver education and training methods. Administrators,
providers, and caregivers were asked about the typical presenting
problems of children with ASD or high likelihood of ASD.
The specific need areas assessed included: communication,
social interaction, play, learning, sleep, eating, sensory, behavior
challenges, stereotyped behaviors, repetitive and/or restrictive
behaviors, parent-child engagement, and family stress around
the child. Administrators and providers also reported on the
perceived effectiveness in addressing these needs on a Likert scale
from: not being addressed, not effective, somewhat effective, or
very effective (37).
Additionally, participants across levels (including caregivers)
indicated service intensity (number of hours per week), service
location (home, school, community, childcare, clinic) and
caregiver involvement (e.g., participation in goal development,
observation of providers, practice using strategies, feedback on
use, etc.). To better understand parent/caregiver involvement, we
defined caregiver training as observation of providers working
Frontiers in Psychiatry | 5December 2021 | Volume 12 | Article 786138
Aranbarri et al. ASD Early Intervention: Characterizing Services
with the child, reading materials/resources and/or discussing the
intervention with caregivers and caregiver coaching as providing
the parents opportunities to practice a specific strategy with
feedback and specified at-home practices between visits.
The measure also assessed which, if any, autism-specific
practices were being used within the agency as perceived by
administrators and providers. The listed items included evidence
and non-evidence-based practices including 26 therapeutic
strategies or interventions specific to ASD services for early
intervention. Strategies were adapted slightly to include only
those strategies appropriate for early intervention settings (e.g.,
intervention packages such as cognitive behavioral therapy and
social skills training and treatment strategies such as cognitive
restructuring were removed). Strategies and packages were listed
by name in alphabetical order with no definition or information
about their evidence base. Direct providers were further asked
to rate their level of confidence in delivering any treatment
strategies they said they reported utilizing on a Likert Scale (“I feel
confident in my delivery of this practice”: 1–Disagree Strongly;
5–Agree Strongly).
Organizational Readiness to Change Assessment
(ORCA)–Organizational Context
The ORCA-Organizational Context Scale (39) assessed
organizational culture, defined as “normative beliefs and
shared behavioral expectations in an organizational unit” (43
p. 770). Specifically, the ORCA measures staff perceptions of
the quality of the organizational context to support practice
change and innovation. The scale is comprised of six subscales:
leadership culture (i.e., norms and expectations regarding how
leaders behave and how things are done at the agency), staff
culture (i.e., norms and expectations regarding how staff behave
and how things are done at the agency), leadership practices (i.e.,
staff perception of leadership behaviors), measurement (i.e., staff
perception of supervisor feedback), readiness to change among
opinion leaders (i.e., performance measures and procedures for
feedback and accountability), and resources to support practice
change. Subscales consists of three to six items and all items
are scored on a 5-point Likert scale from 1 (strongly disagree)
to 5 (strongly agree). Scale and subscale scores are calculated
by dividing the total score by the number of items on the scale
resulting in scale score values of 1–5. Average scores below 3.8
are considered areas in need growth, while scores between 4
and 5 are considered areas of strength (i.e., 3.8–3.9 indicate an
average score). Reliability tests indicate that the ORCA context
subscale tool meets standard requirements of 0.80. Cronbach’s
alpha for reliability at 0.85.
Texas Christian University Organizational Readiness for
Change 4-Domain Assessment
The ORC-D4 (40,42) measures organizational climate, defined
as the “way people perceive their work environment” across four
major domains comprised of 21 scales and 125 items and [(43). p.
769]. Specifically, this measure assessed staff perceptions of their
role in the organization. This project used the Staff Attributes
(Growth, Efficacy, Influence, Adaptability, Satisfaction) Scale.
For Staff Attributes, growth measures the extent to which
staff value and perceive opportunities for professional growth;
efficacy measures staff confidence in their own intervention
skills; influence is the willingness and ability of staff to influence
coworkers (be an opinion leader); adaptability is the ability
for staff to adapt to a changing environment, and satisfaction
examine overall job satisfaction. ORC-D4 scores have been
associated with higher satisfaction with training, greater openness
to innovations (44,45), and better client functioning (42,46).
Response categories for the items on the ORC-D4 are on a
5-point Likert scale from 1 (strongly disagree) to 5 (strongly
agree). Scale scores are computed by averaging scale items and
multiplying by 10 to obtain a range of 10–50. A score of 30
indicates the scale’s mid-point (neither agreeing nor disagreeing).
Thus, scale scores above 30 indicate greater agreement and scale
scores below 30 indicate greater disagreement with the construct.
For Staff Attributes, scores above 40 are in the 75th %tile and
considered a strength, excepting the efficacy scale which requires
a score of 44.
Modified Practice Attitudes Scale
Adapted from the longer Evidence-Based Practices Attitude
Scale (EBPAS) measure, the MPAS assessed attitudes toward
treatment manuals specifically (47). The 8-item MPAS assessed
both direct provider (consistent with original measure) and
administrators (e.g., items were modified to reflect administrator
attitudes toward providers use of EBP) attitudes toward EBP. A
sample item includes: “[I am willing to OR I am willing to have
clinical staff] use new and different types of interventions if they
have evidence of it being effective.” Participants indicated their
agreement with each item from 0 (not at all) to 5 (to a very great
extent). The total score ranges from 0 to 40, and higher scores
reflect more favorable attitudes toward use of EBP with scores
above 32 indicating this as an area of strength. Scores below 22.5
indicate an area for growth in an organization. The cronbach’s
alpha for the MPAS was 0.80 in the original measure development
study (27). For the current survey responses, the MPAS alpha
coefficient maintained an 0.80 (38).
Data Analysis
Data analyses were conducted using the SPSS 23.0 statistical
software program. The characterization of early intervention
services in the US was examined using descriptive statistics
and mean difference analyses (i.e., Chi-square tests and
independent samples t-test). Concretely, Chi-square tests
(through contingency tables based on Bonferroni post-hoc
method) were conducted to identify the discrepancies across
the participant groups (i.e., administrators, providers, and
caregivers) on intervention intensity, type of parent/caregiver
training, coaching given and received, and the presenting
needs of children with ASD. Two-tailed independent sample
t-tests were used to detect discrepancies between administrators
and providers on the perceived effectiveness of their team at
addressing child’s needs. To examine intervention practices and
strategies used, and organizational variables associated with
readiness to implement evidence-based practices, we conducted
descriptive statistics, Pearson correlational analyses, and multiple
Frontiers in Psychiatry | 6December 2021 | Volume 12 | Article 786138
Aranbarri et al. ASD Early Intervention: Characterizing Services
TABLE 3 | Intervention intensity reported by each participant.
Intensity per month Administrator % Provider % Caregiver %
(n=28) (n=48) (n=35)
Fewer than 6 h 50 50 43
From 6 to 15h 32 25 14
More than 15 h 18 25 43
linear regression analysis (i.e., using a backward elimination
method to determine best model fit).
Early Intervention Services in the US:
Characterizing Services for ASD
Service Setting
The most frequent early intervention setting was the home (over
85% of all participants). The second most common setting was
the community (coordinator =37.5%, administrator =67.9%,
provider =58.6%). Very few children received services in a
clinic (<15%), and 25% received services in school or daycare
settings. We did not collect information about specific type
of school or daycare setting or opportunities to interact with
typically developing peers.
Methods Used for Therapeutic Goals
The most frequent method to establish intervention goals was
through collaboration with caregivers. Respondents across levels
similarly reported that early intervention goals were based
on child and family needs (72.3%). Other methods included
observing the child’s behaviors and skills (53.6%) and using a
specific assessment (44.1%).
Private vs. Public Funding Source
Based on agency report, 96.4% of the interventions provided to
children with ASD were publicly funded (Part C), with a smaller
percentage of interventions paid for privately (i.e., insurance,
private pay, employer supported).
All groups of participants agreed that about half of the
children received fewer than 6 h of intervention per month.
Administrators reported that only 18% of children received
more than fifteen hours a month, while direct providers
reported 25%, and caregivers reported that 43% received more
intensive services (see Table 3). Because most services were
provided in home (85%) it is likely these were provided
using a one-to-one provider/child ratio. Surveys did not ask
about caseloads. Although caregivers descriptively reported
higher-intensity services, a Chi-square test showed that the
differences reported by the three groups (i.e., administrators,
providers, and caregivers) were not significant [χ2
(4) =6.27,
When stratifying caregivers’ report by family income, children
from lower income families (<$50,000/year) were most likely
TABLE 4 | Intervention intensity by income (caregivers).
Intensity per month Lower income % Higher income %
(n=18) (n=17)
Fewer than 6 h 56 29
From 6 to 15h 17 12
More than 15 h 28 59
Under $50,000 is referred to as low income, while $50,000 and above is referred to as
high income based on median income in the US in 2016 being $59,039 (48).
to receive fewer than 6 h of intervention per month (n=
10, 56%). Children from families with higher income (>
$50,000/year), were more likely to receive more than fifteen hours
per month of intervention (n=10, 59%). For more detailed
information see Table 4. A Chi-square test analysis stratifying
intensity of intervention by those families getting fifteen or
less hours per month and those getting more than fifteen
hours per month [χ2
(1) =3.44, p=0.064] revealed marginally
significant differences.
Caregiver Training and Coaching
We asked participants about the use of caregiver training
and caregiver coaching in early intervention. All participants
reported high rates of caregiver training (68–97%; see Figure 1)
while reported rates of coaching varied (23–75%). Chi-square
test showed significant differences [χ2
(3) =20.95, p<0.001]
between groups of participants with regards to the reported
frequency of caregiver training and caregiver coaching usage.
While coordinators, administrators, and providers reported
a high use of caregiver coaching strategies (over 60%),
caregivers reported very low rates (23%). Providers indicate
high rates of caregiver education and lower rates of caregiver
coaching. However, caregivers did not report receiving training
and coaching as often as the program staff reported (see
Figure 1).
Presenting Needs of Children With ASD in Early
Administrators, providers, and caregivers were asked about
the typical presenting problems for children with or at high
likelihood of having ASD. All participant groups agreed
the most frequently identified needs were addressing
the development of communication, social interaction,
play skills, concerns related to sensory differences, and
behavioral challenges. All these areas were reported as key
areas of need by over 80% of participants, regardless of
participant role.
Chi-square tests were conducted to examine differences
between the three groups (i.e., administrators, providers,
and caregivers) in the reported areas of need. Results
showed an overall agreement among the three participant
groups in the reported areas of needs for young children
with ASD. However, significant differences were found
(2) =11.97, p=0.003] between the caregivers and
both administrators and providers. Caregivers reported
Frontiers in Psychiatry | 7December 2021 | Volume 12 | Article 786138
Aranbarri et al. ASD Early Intervention: Characterizing Services
FIGURE 1 | Parent coaching and parent training usages reported by all participants. Parents coaching refers to at-home practice together with feedback on parents
use of strategies.
significantly higher levels of concern about learning differences
(91%) compared to both professional groups (i.e., 50%
administrators and 70% direct providers). See Table 5 for
more details.
Perceived Effectiveness of the Interventions
Addressing Client Needs
Overall, descriptive analyses showed that administrators
and direct providers reported feeling somewhat effective
or very effective in addressing the needs of children with
ASD. Communication skills were the only area where both
administrators and direct providers reported the highest
effectiveness (i.e., over 50% of both groups reported feeling very
effective). There were four areas in which both groups felt less
effective. More concretely, <25% reported feeling very effective,
addressing sleeping, eating,stereotyped/repetitive behaviors, or
family stress.
Comparing Agency Administrators’ and Direct
Providers’ Perceptions of Early Intervention
A Student Ttest was conducted to identify differences between
administrator and provider perceptions of effectiveness in
addressing the developmental needs of children with ASD.
TABLE 5 | Presenting client needs: children with ASD in early intervention.
Needs Administrators %Providers %Caregiver %
(n=28) (n=54) (n=32)
Communication skills 100 90 100
Social interaction skills 100 90 100
Play skills 93 92 100
Learning differences 50a70a91a,b
Parent-child engagement 75 52 47
Sleep challenges 68 60 66
Eating differences 71 75 94
Sensory differences 89 83 88
Behavior challenges 86 80 84
Stereotyped behavior 75 65 69
Family stress 75 72 84
Variable in italics had significant differences across groups.
The different subscripts (a,b) refer to significant differences across those specific groups.
Results indicated significant differences between administrators
and direct providers in two areas: social interaction [t(78) =
2.21, p=0.03] and stereotyped behaviors [t(67) = −2.27,
Frontiers in Psychiatry | 8December 2021 | Volume 12 | Article 786138
Aranbarri et al. ASD Early Intervention: Characterizing Services
TABLE 6 | Percentage of leaders and providers who report using practices/strategies in early intervention and provider’s reported competence.
Practice/strategy Administrator strategy
use %
strategy use %
Provider reported high
competence %
(n=28) (n=65) (n=65)
Evidence-based practice
Reinforcement/rewards 75 75.4 95.9
Modeling 89.3 73.8 89.6
Visual supports (schedules) 82.1 69.2 86.6
Prompting 67.9 63.1 92.7
Alternative communication systems (e.g., PECS, sign, devices) 89.3 63.1 70.7
Parent-implemented intervention 60.7 53.8 73.5
Responsive teaching DIR/Floortime 35.7 46.2 96.5
Functional behavior assessment 39.3 46.2 65.5
Pivotal response training—naturalistic 53.6 44.6 82.8
Differential reinforcement 17.9 41.5 74.1
Positive behavior support (PBS) 35.7 41.5 92.6
Task analysis 14.3 41.5 76
Discrete trial teaching 28.6 40.0 73.1
Antecedent-based Intervention 25.0 40.0 84.6
Extinction 14.3 35.4 65.2
Social-communication intervention (e.g., SCERTS, Project ImPACT)—parent implemented 21.4 33.8 63.6
Early start denver model 35.7 32.3 33.3
Emerging evidence
Sensory diet* 46.4 49.2 65.7
Expressive language-based therapy (e.g., HANEN) 32.1 47.7 87.1
Sensory integration* 75.0 47.7 48.4
Imitation-based intervention/reciprocal imitation training 28.6 41.5 74.1
Joint-attention intervention/instruction (e.g., JASPER)—naturalistic* 25.0 35.4 56.5
Music therapy 17.9 21.5 57.1
No evidence to support
Play therapy 35.7 49.2 83.9
Dietary changes 28.6 33.8 54.5
Massage/touch therapy 35.7 24.6 56.3
*Considered emerging evidence at the time of the survey by the NAEYC report.
Competence’s columns indicate percentage of providers indicating feeling competent on this particular practice/strategy.
p=0.04]. More specifically, providers reported better skills in
addressing social skills than was perceived by administrators. The
opposite views were reported regarding stereotyped behaviors.
That is, administrators perceived higher effectiveness of early
intervention for addressing stereotyped behavior than providers.
Association Between Client Needs and Effectiveness
Addressing Those Needs
When we combine these two sources of information, the
presenting needs, and the effectiveness of the interventions
addressing those specific needs, results showed that most
administrators and direct providers reported feeling somewhat
effective or very effective addressing client’s highest needs (i.e.,
communication skills, social interaction, play skills, sensory
differences, and behavior challenges). Administrators and direct
providers disagreed about the effectiveness of intervention
for social interaction. While over 50% of direct providers
reported feeling very effective in supporting development of social
interaction, only 28% of the administrators felt that way.
Intervention Practices and Strategies for
ASD utilized in Early Intervention
Administrators and providers reported on the practices
used in their programs. Table 6 shows the proportion of
participants reporting the use of a particular practice or strategy.
Determination of the level of evidence for each strategy was
based on the Evidence Based Practices for Children, Youth, and
Young Adults with Autism Spectrum Disorders Report (2014) and
the group’s review of comprehensive treatment models (49). The
2014 review was used, rather than the 2020 update, to examine
provider use of EBP identified at the time of the survey.
Most administrators and providers endorsed many different
practices. A similar proportion of providers reported using
evidence-based practices, practices with emerging evidence, and
those with no/limited evidence (i.e., EBP =58.1%, emerging
Frontiers in Psychiatry | 9December 2021 | Volume 12 | Article 786138
Aranbarri et al. ASD Early Intervention: Characterizing Services
evidence =55.4% and no evidence =48.1% based on the
2014 report). All providers endorsed using at least 3 (out
of seventeen) EBP. Providers tended to endorse strategies
that addressed specific behaviors rather than comprehensive
interventions addressing multiple areas of development.
Provider Competencies
Over 75% of providers agreed or strongly agreed that they felt
competent delivering the following evidence-based practices and
strategies: reinforcement/rewards (95.9%), modeling (89.6%),
visual supports like schedules (86.6%), prompting (92.7%),
responsive teaching DIR/Floortime (96.5%), pivotal response
training—naturalistic (82.8%), positive behavior support
(92.6%), task analyses (76%) and antecedent-based intervention
(84.6%), see more details in Table 6.
Provider Training
The majority (76.3%) of providers indicated they received
training through their school and/or educational coursework.
However, over 50% of providers reported a need for more
training in the following areas of competency: (a) ASD-related
training (70.1%); (b) improving behavioral management of
clients (59.7%); (c) improving engagement of caregivers during
the session (56.1%); (d) increasing participation in interventions
by clients with ASD or their families (54.4%); and (e) caregiver
coaching strategies or methods (50.9%).
Provider Readiness to Implement EBP in
Early Intervention Programs
Attitudes Toward EBPs
MPAS scores did not differ by respondent type. Administrators,
overall, had an MPAS mean score of 31.53 (SD =4.90) and
providers had a mean score of 30.79 (SD =5.08) indicating this
is an area that could benefit from additional growth and training
across administrator and provider levels.
Organizational Context
Providers indicated that their early intervention agencies had
average leadership culture (as indicated by ORCA scores;
Table 7) for innovation implementation. They considered
leadership practices, staff culture, and opinion leaders (at the staff
level) as strengths in their organizations in terms of readiness to
support the use of new practices. Measurement (i.e., leadership
feedback on the use of intervention practices) and having
resources to support practice change were both areas of need in
early intervention agencies.
Provider Attributes
Providers in early intervention agencies considered the attributes
of staff in their agencies as strengths on two ORC-D4 staff
attribute subscales (see Table 8): influence (i.e., staff interaction
based on sharing and mutual support) and satisfaction (i.e.,
general satisfaction with one’s job and work environment).
They rated staff as average in the areas of growth, efficacy,
and adaptability which may indicate that staff do not highly
value or make use of opportunities to advance their own
professional growth, may have poor confidence in their ability to
TABLE 7 | Organization readiness to change (ORCA)—context scale.
Subscale (n=52 providers) Mean (SD) Rating
Leadership culture 3.96 (0.79) Average
Staff culture 4.27 (0.59) Strength
Leadership practices 4.00 (0.82) Strength
Measurement (leadership feedback) 3.75 (0.79) Growth/Need
Readiness to change (opinion leaders) 4.42 (0.63) Strength
Resources to support practice change 3.64 (0.86) Growth/Need
deliver interventions or conduct their work well, and feel they
have limited ability to effectively integrate new innovations at
their agency.
Organizational Factors Associated With Attitudes
Toward EBPs by Providers
Results showed a moderate positive association between provider
attitudes toward EBPs and EBP usage (r=0.39, p=0.01).
However, there was no association between attitudes toward
EBPs and the provider’s perceived competence using the EBP
(r=0.07, p=0.61).
Regarding organizational factors, correlation analyses showed
that provider attitudes toward EBPs were significantly associated
with three of the organizational scales, leadership culture (r=
0.38, p=0.01), staff culture (r=0.28, p=0.04), and growth
(r=0.39, p=0.01), with low-to-moderate positive associations.
That is, higher leadership culture, staff culture, and growth
were related to more favorable attitudes toward EBP practices
and strategies.
A linear regression analysis (i.e., backward elimination
method) was conducted to assess whether organizational factors
were related to the attitudes toward EBPs. Results of the linear
regression model were significant, showing that 31% of the
variance in attitudes toward EBP was explainable by readiness to
change,leadership culture,resources to support practice change,
and growth, [F(4,47) =5.40, p=0.001, R2=0.31]. Leadership
culture was significantly associated with attitudes toward EBPs,
B=2.70, t(47) =3.17, p=0.003. This indicates that on average,
a one-unit increase of leadership culture (as measured by the
ORCA) was associated with increased attitude toward EBPs
(MPAS) by 2.70 units. Growth (measured by the ORC-D4) was
significantly associated with attitudes toward EBPs, B=0.43,
t(47) =3.29, p=0.002. This indicates that on average, a one-
unit increase of growth was associated with an increased attitude
toward EBPs (MPAS) of 0.43 units. Table 9 summarizes the
results of the regression model with the best model fit.
This study examined three aspects of current early intervention
practices for ASD to identify routes to improve translation
and implementation of EBP in US publicly funded community
early intervention settings. First, we sought to characterize the
services delivered across seven states serving families in low-
resource areas of the US. We found high levels of agreement
Frontiers in Psychiatry | 10 December 2021 | Volume 12 | Article 786138
Aranbarri et al. ASD Early Intervention: Characterizing Services
across stakeholders in terms of the service setting, intensity, and
needs of children entering the community early intervention
system. Agency stakeholders and caregivers reported contrasting
information about the extent of caregiver coaching delivery,
with few caregivers reporting receipt of high-quality in-person
coaching with their child. Interestingly, caregiver report of
psychoeducation closely aligned with providers’ rates of reported
caregiver coaching. Over 50% of participating providers reported
the need for more training in caregiver coaching strategies.
Second, we specifically examined the current use of EBP in
the system. The vast majority of providers reported using
multiple strategies, about half of which could be considered
evidence-based. While many providers felt competent in their
delivery of several EBPs, endorsed strategies were specific
rather than comprehensive, and 70% indicated the need for
additional training in specific EBPs for ASD. Third, we
examined organizational and contextual factors influencing
system readiness for EBP implementation. Our data support
a positive link between attitudes toward EBPs and EBP usage.
Leadership culture and staff attribute growth were positively
associated with providers’ attitudes toward EBPs, pointing to
contextual factors as potential leverage points to intervene upon
to increase EBP use in community early intervention settings.
The US regulations for Individuals with Disabilities Education
Improvement Act of 2004 (13) include several guidelines for Part
C that support a “natural environment” for intervention, often
interpreted as being the child’s home for very young children,
the use of scientifically-based interventions, and building early
intervention competence within the child’s family, including
family involvement in goal setting and intervention delivery. No
specific recommendations are provided for service intensity.
Our data indicate that a vast majority of children receive
Part C services in the home or another community setting
TABLE 8 | TCU Organization Readiness for Change (ORC-D4)—staff attributes
scale (n=52 providers).
Subscale M(SD) Rating
Growth 39.90 (0.50) Average
Efficacy 41.79 (0.44) Average
Influence 40.12 (0.59) Strength
Adaptability 39.13 (0.48) Average
Satisfaction 44.82 (0.57) Strength
and very few are going to a clinic for services. This is very
consistent with Part C regulations. Although no clear data exist
to determine the specific intensity needed for early ASD services
(11), general consensus in the field recommends at least ten hours
of comprehensive treatment per week (10). Our data indicate that
most children with ASD residing in low-resourced areas of the
US receive 6 h of intervention per month (i.e., fewer than 2 h
per week) through publicly funded early intervention services.
Providers responses indicated these services were predominantly
a mix of individual strategies, rather than comprehensive,
integrated programs. Moreover, low-income families reported
receiving fewer service hours per month overall than higher-
income families and the number of hours reported by low-
income families aligned with Part C providers’ overall report
of service intensity. This suggests that higher-income families
may be supplementing public early intervention services with
additional intervention hours funded through insurance or
self-pay methods. Higher-income families may also be able to
use advocacy to garner more hours from the public system.
To improve equity in provision of care, identifying equity-
focused implementation strategies and allocation of services
will be key to prevent widening disparities in access to needed
services. However, ensuring the use of high-quality intervention
in community programs may be even more critical given that
poorly implemented interventions are not likely to improve child
outcomes regardless of intensity.
Understanding the use of EBP in early intervention may
provide some information regarding quality. Although to
date, no specific intervention model or method has been
established as the general standard for early intervention for
ASD, many EBPs leading to gains in social communication,
language, adaptative behavior, and learning have been
identified (36,49,50). Some EBPs focus on specific
skills and behaviors while others are applied across a
range of skills and behaviors (50,51). Both targeted and
comprehensive strategies may need to be adapted to work
within various public early intervention delivery systems (e.g.,
increased feasibility).
According to our results, most administrators and providers
endorsed delivering multiple practices to youth with ASD, some
with evidence and some with no/limited evidence. These results
are consistent with prior studies in which providers report
using an eclectic approach, combining different practices and
strategies according to their personal criteria, typically in an
TABLE 9 | Results for linear regression for attitudes toward EBPs.
Variable B SE 95% CI βt p
(Intercept) 14.95 6.13 [2.61, 27.29] 0.00 2.44 0.019
Readiness to change 1.86 1.09 [4.05, 0.33] 0.23 1.71 0.094
Leadership culture 2.70 0.85 [0.98, 4.41] 0.42 3.17 0.003
Resources to support practice change 1.09 0.76 [2.61, 0.44] 0.18 1.44 0.158
Staff attributes growth 0.43 0.13 [0.17, 0.70] 0.43 3.29 0.002
Results: F(4,47)=5.40, p =0.001, R2=0.31.
Frontiers in Psychiatry | 11 December 2021 | Volume 12 | Article 786138
Aranbarri et al. ASD Early Intervention: Characterizing Services
unsystematic manner (25,34). Providers reported competence
in delivering several focused EBPs such as using rewards,
modeling, prompting, and using visual supports. While they
reported some confidence using a few complex EBPs (e.g.,
pivotal response training), fewer providers reported skills
to deliver comprehensive interventions. This is consistent
with observational studies indicating more accurate use of
more structured, less complex interventions (52). However,
comprehensive interventions may result in stronger outcomes
(10,52). Additionally, consistent with reports of limited
coaching by caregivers, fewer providers reported confidence
in their ability to effectively use caregiver coaching strategies
or caregiver-implemented interventions, indicating a need
for additional training or EBP adaptation to fit the system
of care.
This lack of confidence in caregiver coaching may be a
primary reason most caregivers in our sample reported receiving
psycho-education rather than active, direct coaching with
feedback, even though providers reported providing coaching.
This discrepancy in reported use of caregiver coaching and
training between administrators, providers, and caregivers is
a common finding in publicly funded service provisions. For
example, Straiton et al. (53) found a similar discrepancy
between early intervention providers and caregivers in Michigan;
providers who reported utilizing caregiver training were not
typically endorsing EBP that aligned with caregiver training but
rather psychoeducation and parental check-in strategies. Several
factors could explain the discrepancy between caregivers and
providers, including pre-service exposure to child and family-
guided interventions (30). Some providers may use these terms
and approaches synonymously. There may also be discipline-
specific differences among coaching techniques where some
may be more educational/structural than family-centered (54).
Finally, caregiver expectations of intervention structure could
also play a role in how they perceived coaching within the early
intervention system.
Interestingly, another area of agreement among stakeholders
included providers and administrators reporting challenges
related to addressing eating, sleeping, family stress, and
stereotyped behaviors presented by children with ASD in the
early intervention setting. Other than stereotypy, these challenges
involve associated but not ASD-specific behaviors, linked to
higher levels of parenting stress, suggesting the need for targeted
trainings in these areas. However, consistent with other studies,
administrators and providers differed in reports of client needs,
practice use and effectiveness of practices (34,55). These
discrepancies may imply a mismatch between provider training
needs and training opportunities provided by administrators.
Further, since providers are unlikely to communicate directly
with state autism coordinators, it may be that individuals who
can facilitate policy or funding for training are not aware of the
support needed for providers to be able to meet the needs of
their clients.
Organizational readiness to adopt and utilize new practices
is critical for successful implementation of EBPs within
an organization (56). Organizational readiness consists of
motivation to try new practices, general capacity within an
organization to support new practices, and necessary innovation-
specific capacities, such as knowledge, skills, and resources. Both
individual perspectives on the organizational climate as well
as perspectives about the organizational norms are necessary
to evaluate the capacity of an organization to deliver a new
EBP at both the leader and provider levels (42). Organizational
culture is a complex and dynamic set of constructs that coalesce
to form an overall culture of readiness to implement an
EBP (33).
Consistent with our finding that leadership characteristics
relate to provider attitudes toward EBP, the implementation
literature has established leadership as a key component for the
successful adoption, implementation, and sustainment of EBP
(57). Rather than considering only how we can provide adequate
professional development to providers, we must also consider
how to train leaders who support and recognize providers in their
pursuit of improving high quality services (58).
In general, our data suggest that early intervention agencies
could benefit from improved leadership climate and culture
for innovation. While providers indicated some organizational
strengths, such as the influence of opinion leaders, satisfaction
with their work environment and culture for innovation at the
provider level, they also reported challenges with consistent
measurement of practice use, obtaining resources and feelings
of efficacy and adaptability. Additionally, both administrators
or providers reported relatively average or neutral attitudes
toward EBP in general. The fact that attitudes toward EBP were
associated with greater use of EBP highlights the importance
of a focus on agency and provider buy-in to improve research-
based early intervention services. Organizational context, in turn,
explained much of the variance in EBP attitudes, indicating that a
multi-level intervention addressing implementation readiness at
the system, agency, and provider levels may be key to improving
the quality of public early intervention programs (28,58).
Our study has several limitations that should be noted when
interpreting the results. First, although we sought diverse,
representative stakeholders by focusing recruitment in states
serving low-resourced areas (e.g., rural) which resulted in
our caregiver sample having a range of incomes represented
and 21% of caregivers identified as Latinx, a majority of
our sample identified as white and non-Latinx. Additionally,
most of the caregivers were married, with little representation
of unmarried and single parents (i.e., 22%). Further, the
administrator and provider samples are reflective of the limited
diversity of the population. For instance, the American Speech-
Language-Hearing Association (ASHA), the major professional
organization for speech-language pathologists, reported that in
2020 96.3% of SLP members were female and 81.0% were
white (59). Second, although we used a nomination system to
connect the different participating layers to allow us greater
consistency in understanding agreements and disagreements
Frontiers in Psychiatry | 12 December 2021 | Volume 12 | Article 786138
Aranbarri et al. ASD Early Intervention: Characterizing Services
between participants, this complex recruitment method resulted
in a small total sample size, limiting our statistical power and
resulting in a less diverse sample overall.
Recommendations for Practice
Our findings describe the early intervention features in low-
resourced areas of the US, which could help future research
translating EBPs into community programs to improve access to
effective intervention for toddlers with ASD and their families.
Given the limited resources of the system and low intensity
of services, ensuring high-quality and model-adherent EBPs is
especially important for families who cannot afford to pay for
hours over and above what the public system provides.
The early intervention system itself and the agencies that
provide early intervention services funded through the US Part
C system would benefit from leadership training that supports
implementation and sustainment of EBP, including caregiver
coaching. Scientists have developed leadership training specific
to supporting high-quality use of EBP (28,58); testing these
training programs in early intervention settings has the potential
to increase access to quality care. Understanding how to create
an organizational context and culture that values, supports, and
rewards EBP use could drive low-resourced community services
toward a general and effective use of EBPs, even in low-intensity
services. Changing organizational culture is likely to influence
provider attitudes toward EBPs, which in turn may additionally
promote use of these EBPs and increase access to scientifically-
supported interventions for more children and families.
Attitudes and practice can also improve through professional
training. Professional training facilitates the use of caregiver
training and coaching (53). Our results clearly suggest a majority
of providers would welcome training in caregiver coaching as
well as other specific EBP for autism symptoms and related
concerns (e.g., sleep, feeding).
The best treatment response for young children occurs
when early intervention combines both clinician- and caregiver-
implemented components (60). Therefore, training in EBP
and caregiver coaching designed to fit the early intervention
context could boost providers’ general capacity to implement best
practices, including increased use of collaborative interventions
involving primary caregivers. Long-term outcomes are stronger
when there is an active participation of caregivers in the early
intervention program (8). In low-resourced environments where
low-intensity treatment hours are more likely to be delivered, a
child’s day-to-day learning opportunities rely more on caregiver
use of EBP than children receiving high-intensity treatment.
Thus, caregiver active involvement in intervention delivery is
crucial to optimize learning opportunities and facilitate positive
child outcomes (61). To meet this goal, providers need specific
training in how to engage and coach caregivers successfully, how
to support caregivers in integrating EBP into daily routines and
activities, and how to adapt strategies to meet the individual
needs of the family and child with ASD (62).
The raw data supporting the conclusions of this article will be
made available by the authors, without undue reservation.
The studies involving human participants were reviewed
and approved by Institutional Review Board (IRB) for the
University of California, Davis, project ID: 780328-22. The
patients/participants provided their electronic informed consent
to participate in this study.
AA: contributed to study conceptualization, methodology,
fieldwork, and leading statistical analyses and interpretations
of results, writing the original text, and contributing my own
postdoctoral funding. AS: contributed to conceptualization,
methodology, project multisite administration and supervision,
obtaining project funding, and completing original writing.
MT: contributed to the field work management, project
administration, supervision, and significant review and editing
of the manuscript. MM: contributed to project administration
and fieldwork as well as manuscript editing. AD: provided
study measures, contributed to results interpretation, provided
original text, and edited manuscript content. MP: facilitated
recruitment and project administration at one site, provided
original text, and contributed to reviewing and editing the
manuscript. AB: contributed to recruitment and project
administration at one site, reviewed and edited the manuscript.
EG: contributed by overseeing the fieldwork, local recruitment
and administration of the project at one, and grant/manuscript
editing. EM: contributed to recruitment at one site, survey
development, and manuscript editing. SR: contributed to
the study conceptualization, methodology, obtaining project
funding, administering and supervising the project, and editing
the document. All authors contributed to the article and
approved the submitted version.
This project was primarily funded through a U.S. Department
of Education Research and Development Award (R324A150211).
We received infrastructure support through the MIND Institute
Intellectual and Developmental Disabilities Research Center
(P50HD103526). Additionally, AA received funding for his
work on the project through a Postdoctoral Fellowship
of the Mas Casadevall-La Caixa Foundation for Autism
Research ID20140714S7. MT’s time was funded by the National
Center for Advancing Translational Sciences, National Institutes
of Health, through grant number UL1 TR001860 and linked
award KL2 TR001859.
Frontiers in Psychiatry | 13 December 2021 | Volume 12 | Article 786138
Aranbarri et al. ASD Early Intervention: Characterizing Services
1. Maenner MJ, Shaw KA, Baio J, Washington A, Patrick M,
DiRienzo M, et al. Prevalence of autism spectrum disorder
among children aged 8 years — autism and developmental
disabilities monitoring network, 11 sites, United States, 2016.
MMWR Surveill Summ. (2020) 69:1–12. doi: 10.15585/
2. Landa RJ, Holman KC, Garrett-Mayer E. Social and communication
development in toddlers with early and later diagnosis of
autism spectrum disorders. Arch Gen Psychiatry. (2007) 64:853–
64. doi: 10.1001/archpsyc.64.7.853
3. Fuller EA, Oliver K, Vejnoska SF, Rogers SJ. The effects of the early
start denver model for children with autism spectrum disorder:
a meta-analysis. Brain Sci. (2020) 10:368. doi: 10.3390/brainsci100
4. Fuller EA, Kaiser AP. The effects of early intervention on social
communication outcomes for children with autism spectrum
disorder: a meta-analysis. J Autism Dev Disord. (2019) 50:1683–
700. doi: 10.1007/s10803-019-03927-z
5. Hampton LH, Kaiser AP. Intervention effects on spoken-language outcomes
for children with autism: a systematic review and meta-analysis. J Intellect
Disabil Res. (2016) 60:444–63. doi: 10.1111/jir.12283
6. Sandbank M, Bottema-Beutel K, Crowley S, Cassidy M, Dunham K, Feldman
JI, et al. Project AIM: autism intervention meta-analysis for studies of young
children. Psychol Bull. (2020) 146:1–29. doi: 10.1037/bul0000215
7. Zwaigenbaum L, Bauman ML, Choueiri R, Kasari C, Carter A, Granpeesheh
D, et al. Early intervention for children with autism spectrum disorder under
3 years of age: recommendations for practice and research. Pediatrics. (2015)
136:S60–81. doi: 10.1542/peds.2014-3667E
8. Kim SH, Bal VH, Lord C. Longitudinal follow-up of academic achievement
in children with autism from age 2 to 18. J Child Psychol Psychiatry. (2018)
59:258–67. doi: 10.1111/jcpp.12808
9. Baghdadli A, Assouline B, Sonié S, Pernon E, Darrou C, Michelon C, et al.
Developmental trajectories of adaptive behaviors from early childhood to
adolescence in a cohort of 152 children with autism spectrum disorders. J
Autism Dev Disord. (2011) 42:1314–25. doi: 10.1007/s10803-011-1357-z
10. Rogers SJ, Yoder P, Estes A, Warren Z, McEachin J, Munson J, et al. A multisite
randomized controlled trial comparing the effects of intervention intensity
and intervention style on outcomes for young children with autism. J Am Acad
Child Adolesc Psychiatry. (2021) 60:710–22. doi: 10.1016/j.jaac.2020.06.013
11. Pellecchia M, Iadarola S, Stahmer AC. How meaningful is more?
Considerations regarding intensity in early intensive behavioral intervention.
Autism. (2019) 23:1075–8. doi: 10.1177/1362361319854844
12. Nahmias AS, Pellecchia M, Stahmer AC, Mandell DS. Effectiveness of
community-based early intervention for children with autism spectrum
disorder: a meta-analysis. J Child Psychol Psychiatry. (2019) 60:1200–
9. doi: 10.1111/jcpp.13073
13. Individuals with Disabilities Education Act (IDEA). 104 Stat. (2004).
14. Stahmer AC, Mandell DS. State infant/toddler program policies for eligibility
and services provision for young children with autism. Adm Policy Ment
Health. (2007) 34:29–37. doi: 10.1007/s10488-006-0060-4
15. Hebbeler K, Spiker D, Bailey D, Scarborough A, Mallik S, Simeonsson R, et
al. Early Intervention for Infants and Toddlers With Disabilities and Their
Families: Participants, Services, and. (2007). Available from: http://www.seels.
(accessed: Sep 20, 2021)
16. Drahota A, Sadler R, Hippensteel C, Ingersoll B, Bishop L. Service deserts
and service oases: utilizing geographic information systems to evaluate service
availability for individuals with autism spectrum disorder. Autism. (2020)
24:2008–20. doi: 10.1177/1362361320931265
17. Campbell PH, Sawyer LB. Supporting learning opportunities in natural
settings through participation-based services. J Early Intervent. (2016) 29:287–
305. doi: 10.1177/105381510702900402
18. Fleming JL, Sawyer LB, Campbell PH. Early intervention providers’
perspectives about implementing participation-based practices. Top
Early Childhood Special Educ. (2010) 30:233–44. doi: 10.1177/0271121410
19. Ingersoll B, Meyer K, Bonter N, Jelinek S. A comparison of developmental
social-pragmatic and naturalistic behavioral interventions on language
use and social engagement in children with autsim. J Speech,
Lang Hear Res. (2012) 55:1301–13. doi: 10.1044/1092-4388(2012/1
20. Vincent LJ, Salisbury CL, Strain PS, McCormick C, Tessier A. A Behavioral-
Ecological Approach to Early Intervention: Focus on Cultural Diversity. 173–91.
21. Salisbury C, Cambray-Engstrom E, Woods J. Providers’ reported and actual
use of coaching strategies in natural environments. Top Early Childhood
Special Educ. (2010) 32:88–98. doi: 10.1177/0271121410392802
22. Stahmer AC, Aranbarri A, Drahota A, Rieth S. Toward a more collaborative
research culture: extending translational science from research to community
and back again. Autism. (2017) 21:259–61. doi: 10.1177/1362361317692950
23. Wainer A, Drahota A, Cohn E, Kerns C, Lerner M, Marro B, et
al. Understanding the landscape of psychological intervention practices
for social, emotional, and behavioral challenges in youth with ASD:
a study protocol. J Ment Health Res Intellect Disabil. (2017) 10:178–
97. doi: 10.1080/19315864.2017.1284289
24. Cochran-Smith M, Lytle S. Relationships of knowledge and
practice: teacher learning in communities. Rev Res Educ. (1999)
24:249–305. doi: 10.2307/1167272
25. Stahmer A, Collings NM, Palinkas LA. Early intervention practices for
children with autism: descriptions from community providers. Focus Autism
Other Dev Disabil. (2005) 20:66–79. doi: 10.1177/10883576050200020301
26. Aarons GA, Fettes DL, Flores LE Jr, Sommerfeld DH. Evidence-based practice
implementation and staff emotional exhaustion in children’s services. Behav
Res Ther. (2009) 47:954–60. doi: 10.1016/j.brat.2009.07.006
27. Borntrager C, Chorpita B, Higa-McMillan C, Weisz J. Provider attitudes
toward evidence-based practices: are the concerns with the evidence or with
the manuals? Psychiatr Serv. (2009) 60:677–81. doi: 10.1176/ps.2009.60.5.677
28. Brookman-Frazee L, Stahmer AC. Effectiveness of a multi-level
implementation strategy for ASD interventions: study protocol
for two linked cluster randomized trials. Implement Sci. (2018)
13:66. doi: 10.1186/s13012-018-0757-2
29. Stahmer AC, Aarons GA. Attitudes toward adoption of evidence-based
practices: a comparison of autism early intervention providers and children’s
mental health providers. Psychol Serv. (2009) 6:223–34. doi: 10.1037/a00
30. Douglas SN, Meadan H, Kammes R. Early interventionists’
caregiver coaching: a mixed methods approach exploring
experiences and practices. Topics Early Child Spec Educ. (2020)
40:84–96. doi: 10.1177/0271121419829899
31. Stadnick NA, Lau AS, Barnett M, Regan J, Aarons GA, Brookman-Frazee
L. Comparing agency leader and therapist perspectives on evidence-based
practices: associations with individual and organizational factors in a mental
health system-driven implementation effort. Adm Policy Ment Health. (2017)
45:447–61. doi: 10.1007/s10488-017-0835-9
32. Aarons, Gregory A, Ehrhart MG, Torres E. Linking team level implementation
leadership and implementation climate to individual level provider
attitudes, behaviors, and implementation outcomes. Implement Sci. (2016)
11:100. doi: 10.1186/s13012-016-0452-0
33. Aarons GA, Ehrhart MG, Farahnak LR, Sklar M. Aligning leadership across
systems and organizations to develop a strategic climate for evidence-
based practice implementation. Annu Rev Public Health. (2014) 35:255–
74. doi: 10.1146/annurev-publhealth-032013-182447
34. Pickard K, Mellman H, Frost K, Reaven J, Ingersoll B. Balancing fidelity and
flexibility: usual care for young children with an increased likelihood of having
autism spectrum disorder within an early intervention system. J Autism Dev
Disord. (2021) 1–13. doi: 10.1007/s10803-021-04882-4
35. Jones L, Wells K. Strategies for academic and clinician engagement
in community-participatory partnered research. JAMA. (2007) 297:407–
10. doi: 10.1001/jama.297.4.407
36. Drahota A, Aarons GA, Stahmer AC. Developing the autism model of
implementation for autism spectrum disorder community providers:
study protocol. Implement Sci. (2012) 7:85. doi: 10.1186/1748-
37. Pickard KE, Kilgore AN, Ingersoll BR. Using community partnerships to
better understand the barriers to using an evidence-based, parent-mediated
Frontiers in Psychiatry | 14 December 2021 | Volume 12 | Article 786138
Aranbarri et al. ASD Early Intervention: Characterizing Services
intervention for autism spectrum disorder in a medicaid system. Am J
Community Psychol. (2016) 57:391–403. doi: 10.1002/ajcp.12050
38. Chorpita BF, Weisz JR, Higa C, et al. Modified Practice Attitudes Scale (MPAS)
Unpublished Measure (2004).
39. Helfrich CD, Li Y-F, Sharp ND, Sales AE. Organizational readiness to change
assessment (ORCA): development of an instrument based on the Promoting
Action on Research in Health Services (PARIHS) framework. Implement Sci.
(2009) 4:38. doi: 10.1186/1748-5908-4-38
40. Lehman WEK, Greener JM, Simpson DD. Assessing organizational
readiness for change. J Subst Abuse Treat. (2002) 22:197–
209. doi: 10.1016/S0740-5472(02)00233-7
41. Simpson DD, Dansereau DF. Assessing organizational functioning as a step
toward innovation. Sci Pr Perspect. (2007) 3:20–8. doi: 10.1151/spp073220
42. Greener JM, Joe GW, Simpson DD, Rowan-Szal GA, Lehman WEK. Influence
of organizational functioning on client engagement in treatment. J Subst Abuse
Treat. (2007) 33:139–47. doi: 10.1016/j.jsat.2006.12.025
43. Glisson C, James LR. The cross-level effects of culture and climate in human
service teams. J Organ Behav. (2002) 23:767–94. doi: 10.1002/job.162
44. Fuller BE, Rieckmann T, Nunes EV, Miller M, Arfken C, Edmundson E,
et al. Organizational readiness for change and opinions toward treatment
innovations. J Subst Abuse Treat.(2007) 33:183. doi: 10.1016/j.jsat.2006.12.026
45. Saldana L, Chapman JE, Henggeler SW, Rowland MD. The organizational
readiness for change scale in adolescent programs: criterion validity. J Subst
Abuse Treat. (2007) 33:159–69. doi: 10.1016/j.jsat.2006.12.029
46. Broome KM, Flynn PM, Knight DK, Simpson DD. Program structure, staff
perceptions, and client engagement in treatment. J Subst Abuse Treat. (2007)
33:149–58. doi: 10.1016/j.jsat.2006.12.030
47. Aarons G. Mental health provider attitudes toward adoption of evidence-
based practice: the Evidence-Based Practice Attitude Scale (EPBAS). Ment
Health Serv Res. (2004) 6:61–74. doi: 10.1023/B:MHSR.0000024351.12294.65
48. Semega JL, Fonteno KR, Kollar MA. Income and Poverty in the United States:
2016. Current Populations Reports, P60-259 2017 US Government Printing
Office, Washington DC (2017).
49. Wong C, Odom SL, Hume K, Cox AW, Fettig A, Kucharcyzk S, et al.
Evidence-Based Practices for Children, Youth, and Young Adults With Autism
Spectrum Disorder. Chapel Hill: The University of North Carolina, Frank
Porter Graham Child Development Institute, Autism Evidence-Based Practice
Review Group (2014). doi: 10.1007/s10803-014-2351-z
50. Hume K, Steinbrenner JR, Odom SL, Morin KL, Nowell SW, Tomaszewski
B, et al. Evidence-based practices for children, youth, and young adults
with autism: third generation review. J Autism Dev Disord. (2021) 51:4013–
32. doi: 10.1007/s10803-020-04844-2
51. Odom SL, Boyd BA. Evaluation of comprehensive treatment models for
individuals with Autism Spectrum Disorders. J Autism Dev Disord. (2010)
40:425–36. doi: 10.1007/s10803-009-0825-1
52. Pellecchia M, Connell JE, Beidas RS, Xie M, Marcus SC, Mandell DS.
Dismantling the active ingredients of an intervention for children with autism.
J Autism Dev Disord. (2015) 45:2917–27. doi: 10.1007/s10803-015-2455-0
53. Straiton D, Groom B, Ingersoll B. Parent training for youth with autism
served in community settings: a mixed-methods investigation within a
community mental health system. J Autism Dev Disord. (2020) 51:1983–
94. doi: 10.1007/s10803-020-04679-x
54. McManus BM, Murphy NJ, Richardson Z, Khetani MA, Schenkman M,
Morrato EH. Family-centred care in early intervention: examining caregiver
perceptions of family-centred care and early intervention service use intensity.
Child Care Health Dev. (2020) 46:1–8. doi: 10.1111/cch.12724
55. Bustos TE, Sridhar A, Drahota A. Implementation evaluation of an early
intensive behavioral intervention program across three agencies serving
young children with Autism: a mixed methods study. Child Youth Serv Rev.
(2021) 122:105871. doi: 10.1016/j.childyouth.2020.105871
56. Scaccia JP, Cook BS, Lamont A, Wandersman A, Castellow J, Katz J, et al. A
practical implementation science heuristic for organizational readiness: R =
MC 2. J Community Psychol. (2015) 43:484–501. doi: 10.1002/jcop.21698
57. Aarons GA, Green AE, Trott E, Willging CE, Torres EM, Ehrhart MG,
et al. The roles of system and organizational leadership in system-
wide evidence-based intervention sustainment: a mixed-method study.
Adm Policy Ment Health. (2016) 43:991–1008. doi: 10.1007/s10488-016-
58. Aarons GA, Ehrhart MG, Farahnak LR, Hurlburt MS. Leadership and
organizational change for implementation (LOCI): a randomized mixed
method pilot study of a leadership and organization development
intervention for evidence-based practice implementation. Implement
Sci. (2015) 10:11. doi: 10.1186/s13012-014-0192-y
59. American Speech-Language Hearing Association. Profile of ASHA Members
and Affilitats, Year End (2021).
60. Landa RJ. Efficacy of early interventions for infants and young children
with, and at risk for, autism spectrum disorders. Int Rev Psychiatry. (2018)
30:25–39. doi: 10.1080/09540261.2018.1432574
61. Stahmer A, Pellecchia M. Moving towards a more ecologically valid model
of parent-implemented interventions in autism. Autism. (2015) 19:259–
61. doi: 10.1177/1362361314566739
62. Pellecchia M, Beidas RS, Mandell DS, Cannuscio CC, Dunst CJ,
Stahmer AC. Parent empowerment and coaching in early intervention:
study protocol for a feasibility study. Pilot Feasibility Stud. (2020)
6:22. doi: 10.1186/s40814-020-00568-3
Conflict of Interest: The authors declare that the research was conducted in the
absence of any commercial or financial relationships that could be construed as a
potential conflict of interest.
Publisher’s Note: All claims expressed in this article are solely those of the authors
and do not necessarily represent those of their affiliated organizations, or those of
the publisher, the editors and the reviewers. Any product that may be evaluated in
this article, or claim that may be made by its manufacturer, is not guaranteed or
endorsed by the publisher.
Copyright © 2021 Aranbarri, Stahmer, Talbott, Miller, Drahota, Pellecchia, Barber,
Griffith, Morgan and Rogers. This is an open-access article distributed under the
terms of the Creative Commons Attribution License (CC BY). The use, distribution
or reproduction in other forums is permitted, provided the original author(s) and
the copyright owner(s) are credited and that the original publication in this journal
is cited, in accordance with accepted academic practice. No use, distribution or
reproduction is permitted which does not comply with these terms.
Frontiers in Psychiatry | 15 December 2021 | Volume 12 | Article 786138
Purpose Naturalistic developmental behavioral interventions (NDBIs) have demonstrated initial promise in facilitating social communication development for autistic toddlers, but their highly structured protocols may be a barrier toward their use by early intervention (EI) providers who must individualize intervention according to family-centered principles. This study aimed to characterize the extent to which EI speech-language pathologists (SLPs) use NDBI strategies, and the range of skills and behaviors addressed during their EI sessions, to contextualize the role of NDBIs within the scope of needs of families with autistic children in EI. Method This observational study included 25 families with an autistic toddler and their EI SLP. One home-based session was recorded for each family, and an observational measure was used to describe SLPs' NDBI strategy use. Qualitative content analyses were also used to characterize the strategies SLPs recommended to families, and the child skills and behaviors they discussed. Results SLPs did not implement NDBI strategies with high quality, but they implemented developmental NDBI strategies with significantly higher quality than behavioral NDBI strategies. SLPs discussed many strategies and skills across disciplines within the session. Conclusions SLPs may require further training to implement NDBI strategies, but given the breadth and depth of skills addressed during sessions, researchers should investigate and report on the impact of NDBIs on a wider range of communication skills and developmental domains. This will facilitate clinical decision making and make these interventions better aligned with family-centered EI principles. Supplemental Material
Lay abstract: Early Intervention systems provide therapeutic services to families of young children birth to 3 years with developmental delays and are considered a natural access point to services for young children and their families. Research studies in the autism field have been interested in training providers to deliver evidence-based practices in Early Intervention systems to increase access to services for young children with an increased likelihood of being autistic. However, research has often overlooked that Early Intervention systems prioritize family-centered care, an approach to working with families that honors and respects their values and choices and that provides supports to strengthen family functioning. This commentary points out that family-centered care deserves greater attention in research being done in Early Intervention systems. We describe how family-centered care may shape how interventions are delivered, and discuss directions for future research to evaluate the impact of family-centered care alongside intervention delivery.
Purpose Family-centered practice (FCP) is a core component of early intervention (EI) associated with improved child and family outcomes, but little is known about community-based speech-language pathologists' (SLPs') inclusion of families in EI. Many caregivers of autistic children experience caregiving-related stress, making these intervention principles especially critical to the provision of optimal services. This study aimed to characterize EI SLPs' use of FCP coaching strategies and the quality of caregiver–SLP relationships. Method Participants included 25 families with an autistic toddler and their EI SLP. One intervention session for each SLP–family dyad was recorded and coded for the SLP's use of FCP coaching strategies. Caregivers and SLPs completed surveys about their working alliance, caregiver perceptions of family-centered care, and SLPs' approach to FCP. Results SLPs primarily use child-directed strategies without caregiver involvement. When involving caregivers, SLPs infrequently use coaching strategies that are important for caregiver learning and collaboration (e.g., joint planning and guided practice with feedback). However, caregivers perceived their child's services to be highly family-centered, and caregivers and SLPs rated their working alliance to be of high quality. Conclusions The presence of strong caregiver–SLP working alliances alongside infrequent usage of effective coaching strategies indicates that SLPs may engage caregivers in ways that are perceived to be highly collaborative but are not optimal for caregiver involvement in all aspects of their child's services (goal setting and implementation of intervention). Consideration of family preferences and SLP beliefs about FCP will inform ways to disseminate FCPs needed to optimize families' capacities to support their child's development. Supplemental Material
Full-text available
Naturalistic developmental behavioral interventions (NDBIs) are evidence-based interventions for young children with autism spectrum disorder. There has been growing interest in implementing manualized NDBIs within the early intervention (EI) system without a clear understanding of how these programs and the broader strategies encompassed within them are already used by EI providers. This study examined the use of manualized NDBI programs and broader NDBI strategies within an EI system and factors that impacted their use. Eighty-eight EI providers completed a measure of NDBI program and strategy use. Thirty-three providers participated in a supplemental focus group or interview. Overall, providers described using broader NDBI strategies and the need to adapt manualized NDBI programs. Provider-, intervention-, and organization-level factors impacted their use of NDBI programs and strategies.
Full-text available
This systematic review describes a set of practices that have evidence of positive effects with autistic children and youth. This is the third iteration of a review of the intervention literature (Odom et al. in J Autism Dev Disorders 40(4):425-436, 2010a; Prevent School Fail 54(4):275-282, 2010b; Wong et al. in https ://autis /autis /imce/docum ents/2014-EBP-Repor t.pdf; J Autism Dev Disorders 45(7):1951-1966, 2015), extending coverage to articles published between 1990 and 2017. A search initially yielded 31,779 articles, and the subsequent screening and evaluation process found 567 studies to include. Combined with the previous review, 972 articles were synthesized, from which the authors found 28 focused intervention practices that met the criteria for evidence-based practice (EBP). Former EBPs were recategorized and some manualized interventions were distinguished as meeting EBP criteria. The authors discuss implications for current practices and future research.
Full-text available
Parent training programs focus on parent knowledge and/or skill development regarding strategies to improve child outcomes. Parent training programs are considered evidenced-based treatments for autism spectrum disorder (ASD). Yet little is known about parent training use for youth with ASD served in community settings. This mixed methods project examined parent training for Medicaid-enrolled youth with ASD under age 21. Data were obtained from Medicaid claims for 879 youth and surveys from 97 applied behavior analysis (ABA) providers. Open-ended survey items were analyzed with content analysis. Results demonstrated that the frequency of parent training was low and providers’ conceptualization of parent training was inconsistent with evidence-based models. Providers are largely unaware of evidence-based components (i.e., modeling, caregiver practice with feedback) and use them infrequently. Implications for increasing parent training in community settings are discussed.
Full-text available
Objective This randomized, multisite, intent-to-treat study tested the effects of two levels of treatment intensity (number of hours) and two treatment styles on progress of young children with autism spectrum disorder (ASD). We predicted that initial severity of developmental delay or autism symptoms would moderate the effects of intensity and style on progress in four domains: autism symptom severity, expressive communication, receptive language, and nonverbal ability. Method Eighty-seven children with ASD, mean age 23.4 months, were assigned to one of two intervention styles (naturalistic developmental-behavioral or discrete trial teaching), each delivered for either 15 or 25 hours per week of 1:1 intervention for 12 months by trained research staff. All caregivers received coaching twice monthly. Children were assessed at four timepoints. Examiners and coders were naive to treatment assignment. Results Neither style nor intensity had main effects on the four outcome variables. In terms of moderating effects of initial severity of developmental delay and of autism symptom severity, neither moderated the effects of treatment style on progress in any of the four domains. In terms of treatment intensity, initial severity moderated effect of treatment intensity on only one domain - change in autism symptom severity, and in a secondary analysis, this effect was found in only one site. Conclusion Neither treatment style or intensity had overall effects on child outcomes in the four domains examined. Initial severity did not predict better response to one intervention style than another. We found very limited evidence that initial severity predicted better response to 25 versus 15 hours per week of intervention in the domains studied.
Full-text available
This meta-analysis examined the effects of the Early Start Denver Model (ESDM) for young children with autism on developmental outcome measures. The 12 included studies reported results from 640 children with autism across 44 unique effect sizes. The aggregated effect size, calculated using a robust variance estimation meta-analysis, was 0.357 (p = 0.024), which is a moderate effect size with a statistically significant overall weighted averaged that favored participants who received the ESDM compared to children in control groups, with moderate heterogeneity across studies. This result was largely driven by improvements in cognition (g = 0.412) and language (g = 0.408). There were no significant effects observed for measures of autism symptomology, adaptive behavior, social communication, or restrictive and repetitive behaviors.
Full-text available
Problem/condition: Autism spectrum disorder (ASD). Period covered: 2016. Description of system: The Autism and Developmental Disabilities Monitoring (ADDM) Network is an active surveillance program that provides estimates of the prevalence of ASD among children aged 8 years whose parents or guardians live in 11 ADDM Network sites in the United States (Arizona, Arkansas, Colorado, Georgia, Maryland, Minnesota, Missouri, New Jersey, North Carolina, Tennessee, and Wisconsin). Surveillance is conducted in two phases. The first phase involves review and abstraction of comprehensive evaluations that were completed by medical and educational service providers in the community. In the second phase, experienced clinicians who systematically review all abstracted information determine ASD case status. The case definition is based on ASD criteria described in the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition. Results: For 2016, across all 11 sites, ASD prevalence was 18.5 per 1,000 (one in 54) children aged 8 years, and ASD was 4.3 times as prevalent among boys as among girls. ASD prevalence varied by site, ranging from 13.1 (Colorado) to 31.4 (New Jersey). Prevalence estimates were approximately identical for non-Hispanic white (white), non-Hispanic black (black), and Asian/Pacific Islander children (18.5, 18.3, and 17.9, respectively) but lower for Hispanic children (15.4). Among children with ASD for whom data on intellectual or cognitive functioning were available, 33% were classified as having intellectual disability (intelligence quotient [IQ] ≤70); this percentage was higher among girls than boys (40% versus 32%) and among black and Hispanic than white children (47%, 36%, and 27%, respectively). Black children with ASD were less likely to have a first evaluation by age 36 months than were white children with ASD (40% versus 45%). The overall median age at earliest known ASD diagnosis (51 months) was similar by sex and racial and ethnic groups; however, black children with IQ ≤70 had a later median age at ASD diagnosis than white children with IQ ≤70 (48 months versus 42 months). Interpretation: The prevalence of ASD varied considerably across sites and was higher than previous estimates since 2014. Although no overall difference in ASD prevalence between black and white children aged 8 years was observed, the disparities for black children persisted in early evaluation and diagnosis of ASD. Hispanic children also continue to be identified as having ASD less frequently than white or black children. Public health action: These findings highlight the variability in the evaluation and detection of ASD across communities and between sociodemographic groups. Continued efforts are needed for early and equitable identification of ASD and timely enrollment in services.
Full-text available
Background: Parent-mediated early interventions (EI) for children with autism spectrum disorder (ASD) can result in significant improvements in children's cognitive ability, social functioning, behavior, and adaptive skills, as well as improvements in parental self-efficacy and treatment engagement. The common component to efficacious parent-mediated early interventions for ASD is clinician use of parent coaching and occurs when a clinician actively teaches the parent techniques to improve their child's functioning. Available evidence suggests that community-based EI clinicians rarely coach parents when working with families of these children, although specific barriers to coaching are unknown. This consistent finding points to the need to develop strategies to improve the use of parent coaching in community EI programs. The purpose of this community-partnered study is to iteratively develop and pilot test a toolkit of implementation strategies designed to increase EI clinicians' use of parent coaching. Methods: This study has four related phases. Phase 1: examine how EI clinicians trained in Project ImPACT, an evidence-based parent-mediated intervention, coach parents of children with ASD. Phase 2: identify barriers and facilitators to clinician implementation of parent coaching by administering validated questionnaires to, and conducting semi-structured interviews with, clinicians, parents, and agency leaders. Phase 3: partner with a community advisory board to iteratively develop a toolkit of implementation strategies that addresses identified barriers and capitalizes on facilitators to improve clinician implementation of evidence-based parent coaching. Phase 4: pilot test the feasibility and effectiveness of the implementation strategy toolkit in improving EI clinicians' use of parent coaching with nine EI clinicians and parent-child dyads using a multiple-baseline-across-participants single-case design. Discussion: Completion of these activities will lead to an in-depth understanding of EI clinicians' implementation of parent coaching in usual practice following training in an evidence-based parent-mediated intervention, barriers to their implementation of parent coaching, a toolkit of implementation strategies developed through an iterative community-partnered process, and preliminary evidence regarding the potential for this toolkit to improve EI clinicians' implementation of parent coaching. These pilot data will offer important direction for a larger evaluation of strategies to improve the use of parent coaching for young children with ASD.
Introduction Autism evidence-based practices (EBPs), including early intensive behavioral interventions (EIBIs), are associated with improved and sustained positive outcomes for children with autism spectrum disorder (ASD). However, little is known about the quality of EIBIs delivered within community-based behavioral health systems, where many children with ASD receive services. These systems vary in their use and delivery of EBPs. Barriers and facilitators play a role in EIBI implementation within these settings. Therefore, this study sought to examine the naturally occurring implementation of the ELI program across three sites over a one-year period, in order to understand the implementation processes, identify barriers and facilitators to implementation, and explore staff perspectives of implementation outcomes. Methods A multi-phase mixed methods (QUAN→QUAL) mixed methods design was utilized to: (1) examine implementation outcomes of acceptability, appropriateness, and feasibility of the EIBI; (2) explore staff perspectives of implementation strategy use; and (3) identify areas of strength and areas for growth to deliver EIBIs in community-based settings. Direct providers (n = 24) and directors/supervisors (n = 6) from three implementation sites participated in the study. All participants completed the Acceptability of Intervention, Intervention Appropriateness, Feasibility of Intervention measures,³ and Organizational Readiness for Change Context Subscale,⁵ at two time-points. Informed by QUAN findings at time-point 1, semi-structured interviews were conducted with a sub-sample of participants (n = 13) who completed the surveys at time-point 1. Thematic analysis was completed with a comparison and consensus methodology. Quantitative and qualitative data were then integrated using a joint display to provide an in-depth assessment of implementation outcomes. Results Quantitative results indicated positive endorsements of implementation outcomes over time; notably, these results aligned with the qualitative data suggesting that the majority of staff shared positive attitudes about the implementation of this EIBI within their organizations. Qualitative results also highlighted key facilitators and barriers to implementation that fell within two major themes: inner contextual factors and innovation factors. Conclusions Findings highlighted several determinants to the naturally occurring implementation of ELI across three settings. These findings may be generalized to inform the implementation processes of EIBIs in usual-care settings thereby facilitating uptake in organizations providing services to children with ASD.
Lay abstract: Autism spectrum disorder and co-occurring symptoms often require lifelong services. However, access to autism spectrum disorder services is hindered by a lack of available autism spectrum disorder providers. We utilized geographic information systems methods to map autism spectrum disorder provider locations in Michigan. We hypothesized that (1) fewer providers would be located in less versus more populated areas; (2) neighborhoods with low versus high socioeconomic status would have fewer autism spectrum disorder providers; and (3) an interaction would be found between population and socioeconomic status such that neighborhoods with low socioeconomic status and high population would have few available autism spectrum disorder providers. We compiled a list of autism spectrum disorder providers in Michigan, geocoded the location of providers, and used network analysis to assess autism spectrum disorder service availability in relation to population distribution, socioeconomic disadvantage, urbanicity, and immobility. Individuals in rural neighborhoods had fewer available autism spectrum disorder providers than individuals in suburban and urban neighborhoods. In addition, neighborhoods with greater socioeconomic status disadvantage had fewer autism spectrum disorder providers available. Finally, wealthier suburbs had good provider availability while few providers were available in poorer, urban neighborhoods. Knowing autism spectrum disorder providers' availability, and neighborhoods that are particularly poorly serviced, presents the opportunity to utilize evidence-based dissemination and implementation strategies that promote increased autism spectrum disorder providers for underserved individuals.
Background: Family Centered Care (FCC) is an approach to pediatric rehabilitation service delivery endorsing shared decision-making and effective communication with families. There is great need to understand how early intervention (EI) programs implement these processes, how EI caregivers perceive them, and how they relate to EI service use. Therefore, the purpose of this study is to examine 1) parent- and provider-perceptions about EI FCC processes and 2) the association between FCC perceptions and EI service intensity. Methods: In this cross-sectional study, parent perceptions of EI FCC were measured using the electronically administered Measures of Processes of Care (MPOC-56 and MPOC-SP; using 7-point scales). Participants included EI parents (n=29) and providers (n=9) from one urban EI program (1/1/18-6/1/18). We linked survey responses with child characteristics and service use ascertained through EI records. We estimated parent-provider MPOC score correlations and the association between EI service intensity (hours/month) and parent MPOC scores using adjusted linear regression accounting for child characteristics. Results: Parents [M=4.2, SD=1.1] and providers [M=5.8, SD=1.3] reported low involvement related to general information exchange. Parent and provider sub-scale scores were not correlated except that parent-reported receipt of specific information was inversely associated with provider-reported provision of general information (r=-0.4, p<.05). In adjusted models, parent perceptions related to respectful and supportive (b=1.57, SE=0.56) and enabling (b=1.42, SE=0.67) care were positively associated with EI intensity, whereas specific information exchange and general information exchange were not associated with intensity. Conclusion: We found that EI parents and providers reported high levels of investment in the family-centeredness of their EI care, with the exception of information sharing. Greater EI service intensity was associated with higher perception of involvement with some metrics of family-centeredness.