Health System Integration of Tools to Improve Primary Care for Autistic Adults
Phase: NA
Conditions: Autism Spectrum Disorder
Sponsor: Portland State University

 
Study Title: Health System Integration of Tools to Improve Primary Care for Autistic Adults 
 
File Type: Study Protocol (including Statistical Analysis Plan) 
 
Date: March 10, 2021 
 
 
 
 
 

Health System Integration of Tools to Improve Primary Care for Autistic Adults 
Abstract: 
The health system is ill-equipped to meet the needs of autistic adults. Our prior work has identified significant 
healthcare disparities experienced by autistic adults, including greater unmet healthcare needs, lower use of 
preventive services, and greater use of the Emergency Department (ED). A majority of primary care providers 
(PCPs) lack the skills needed to care for autistic adults, yet competing priorities make it unlikely they will attend 
trainings on autism. The heterogeneity of the autism spectrum may also make it challenging for PCPs to 
understand specific patients’ needs. The Academic Autism Spectrum Partnership in Research and Education 
(AASPIRE), an academic-community partnership comprised of academics, autistic adults, healthcare 
providers, and supporters, has used a community based participatory research (CBPR) approach to develop 
and test an online healthcare toolkit aimed at improving primary care services for autistic adults. It was 
specifically designed as a low-intensity, sustainable intervention that can realistically be used in busy primary 
care practices that do not have a special focus on autism or other developmental disabilities. The toolkit 
includes the Autism Healthcare Accommodations Tool (AHAT)--an automated tool which allows patients and/or 
their supporters to create a personalized accommodations report for their PCP--and other targeted resources, 
worksheets, checklists, and information. Our pilot work has demonstrated that the AHAT has strong construct 
validity and test-retest stability, the toolkit is highly acceptable and accessible, and it has the potential to 
decrease barriers to care and increase patient-provider communication. Our long-term plan is to conduct a 
hybrid effectiveness-implementation trial, using a cluster randomized trial design, both to test the effectiveness 
of the AASPIRE Healthcare Toolkit in improving healthcare quality and utilization and to assess the utility of 
implementation strategies in diverse healthcare systems. The objective of this proposal is to use a CBPR 
approach to understand how to integrate the toolkit into these health systems, collect more robust efficacy 
data, and explore potential mechanisms of action. We will do so by conducting a 6-month pilot study with 
patients assigned to intervention and control clinics in three diverse health systems. We will meet our 
objectives by achieving the following specific aims: 1) to determine how to integrate use of the toolkit within 
diverse health systems; 2) to test the effect of the toolkit on short-term healthcare outcomes; 3) to use a mixed-
methods approach to further explore the toolkit’s mechanisms of action; and 4) to refine our recruitment, 
retention, data collection, and system integration strategies in preparation for the larger cluster-randomized 
trial. Successful integration of this easily scalable and sustainable low-intensity intervention into primary care 
practices within diverse health systems will empower patients and providers to work together to improve health 
outcomes for a large, underserved, and understudied population with great barriers to care. 
 
 

Specific Aims 
Despite growing attention to the needs of autistic children, the health system is ill equipped to meet the needs 
of autistic adults. Our prior work has identified significant healthcare disparities experienced by autistic adults, 
including greater unmet healthcare needs, lower use of preventive services, and greater use of the Emergency 
Department (ED). These disparities likely stem from a complex interaction between patient-, provider-, and 
system-level factors. Autism entails atypical communication and interpersonal relationships, and challenges 
with executive function – factors that are critically important for effective healthcare interactions and health 
system navigation. Moreover, a majority of primary care providers (PCPs) lack the skills needed to care for 
autistic adults, yet competing priorities make it unlikely they will attend trainings on autism. The heterogeneity 
of the autism spectrum may also make it challenging to understand a specific patient’s needs. Finally, autistic 
patients may be disproportionally affected by the complexity of the health system, low socio-economic status, 
and societal biases, yet few systems can afford autism-specific care coordination programs for adults.   
The Academic Autism Spectrum Partnership in Research and Education (AASPIRE), an academic-community 
partnership comprised of academics, autistic adults, healthcare providers, and supporters, has used a 
community based participatory research (CBPR) approach to develop and test an online healthcare toolkit 
aimed at improving primary care services for autistic adults. It was specifically designed as a low-intensity, 
sustainable intervention that can realistically be used in busy primary care practices that do not have a special 
focus on autism or other developmental disabilities. The toolkit includes the Autism Healthcare 
Accommodations Tool (AHAT)--an automated tool which allows patients and/or their supporters to create a 
personalized accommodations report for their PCP--and other targeted resources, worksheets, checklists, and 
information. A series of NIMH-funded studies demonstrated that the AHAT has strong construct validity and 
test-retest stability, and that the toolkit is highly acceptable and accessible. In a 1-month pre-post intervention 
comparison, we found a decrease in barriers to care and increases in patient-provider communication and 
confidence in healthcare. Despite these promising preliminary results, more data is needed to test its 
effectiveness and understand how to best integrate it into diverse primary care practices and health systems.  
Our long-term plan is to conduct a hybrid effectiveness-implementation trial, using a cluster randomized trial 
design, both to test the effectiveness of the AASPIRE Healthcare Toolkit in improving healthcare quality and 
utilization and to determine the potential utility of implementation strategies in diverse healthcare systems. The 
objective of this proposal is to use a CBPR approach to understand how to best integrate the toolkit into these 
health systems, collect more robust efficacy data, and explore potential mechanisms of action. We will do so 
by conducting a 6-month pilot study with patients assigned to intervention and control clinics in three diverse 
health systems. We will meet our objectives by achieving the following specific aims: 
1. To determine how to integrate use of the toolkit within diverse health systems. Our existing CBPR 
partnership will expand to include local patients, providers, staff, and administrators from each system. 
Together, we will decide how to make patients and providers aware of the toolkit, integrate the AHAT 
into the electronic medical record, and respond to recommendations. We will collaboratively develop 
implementation protocols and determine how to track them. We will then conduct a mixed-methods, 
formative process evaluation to optimize the likelihood of success of future implementation efforts. 
2. To test the effect of the toolkit on short-term healthcare outcomes. We hypothesize that, over 6 months, 
the toolkit will increase satisfaction with patient-provider communication and decrease barriers to 
healthcare in patients from intervention clinics as compared to patients from control clinics. 
3. To use a mixed-methods approach to further explore the toolkit’s mechanisms of action. Quantitative 
data will help us refine and psychometrically test our measures of patient self-advocacy and visit 
preparedness; provider/staff use of desired accommodations and strategies; and patient and provider 
self-efficacy. Qualitative data will allow us to obtain a richer understanding of how the toolkit is affecting 
care and potentially suggest additional mechanisms of action.  
4. To refine our recruitment, retention, data collection, and system integration strategies in preparation for 
the larger cluster-randomized trial. We will use this study to confirm or modify our change model, 
choose long-term health utilization outcomes to be further studied in the R01, finalize study protocols 
and data collection instruments, and develop a flexible implementation strategy that can be feasibly 
applied to diverse primary care clinics. 
Successful integration of this scalable and sustainable low-intensity intervention into primary care practices 
within diverse health systems will empower patients and providers to work together to improve health 
outcomes for a large, underserved and understudied population with great barriers to care.

Significance 
This project will result in the preliminary data necessary to inform a large hybrid effectiveness/implementation 
trial of a practical, easily scalable, and sustainable intervention to improve the healthcare of autistica adults. 
Autism is increasingly being recognized in the adult population.  The Center for Disease Control and 
Prevention estimates that 1 in 68 children are identified as having an autism spectrum disorder (ASD).1 
Though the prevalence of autism has appeared to rise dramatically in the last two decades, much of that rise is 
likely due to changes in how diagnostic criteria are being applied.2 A large study found a 1% prevalence of 
ASD, with no change in autism prevalence based on age.3-5 Even if fewer adults currently recognize they are 
on the autism spectrum due to missed diagnoses during childhood, the large cohort of adolescents with known 
ASD are rapidly approaching adulthood and will need to receive healthcare from PCPs who care for adults. 
Autistic adults face significant healthcare disparities. Our prior survey found that autistic adults had a 
greater number of unmet health needs, lower use of preventive services, higher use of the emergency 
department (ED), and lower ratings of patient-provider communication and healthcare self-efficacy than non-
autistic adults.6 Autistic adults also reported a greater overall number of barriers to healthcare and numerous 
autism-specific barriers to care.7 Others have found that total mean ED charges were 2.3 times higher for 
autistic adults than non-autistic adults.8 In our qualitative study, autistic patients and their supporters described 
many problematic healthcare interactions, illuminating a complex interplay between an individual’s autistic 
characteristics, the healthcare provider’s knowledge and attitudes about autism, and the healthcare system.9  
Primary care providers lack the knowledge and skills necessary to care for autistic adults.  PCPs’ lack 
of sufficient knowledge on how to care for adults with developmental disabilities has been identified as a major 
problem.10,11 For example, despite increased attention to developmental disabilities in pediatric residency 
programs,12 there are no training requirements for the care of adults with developmental disabilities for 
residents in internal medicine13 or family medicine.14 In our co-investigator’s study of 922 adult healthcare 
providers, 77% rated their knowledge and skills in providing care to autistic patients as poor or fair.15 The 
problem is compounded by the very nature of the autism spectrum, which includes a great amount of 
heterogeneity. Knowledge related to taking care of one autistic patient may or may not be helpful in the care of 
other autistic patients with different autistic characteristics, strengths, and needs. 
Autism in adults is still a low incidence condition for most PCPs, few of whom are likely to take part in 
time-consuming training efforts. As the cohort of autistic children diagnosed in the last two decades has 
started to age, there has been a growing interest in “transition” to adulthood, with many calls for increased 
training efforts for PCPs who care for adults.16,17 However, autism has not yet risen to an area of concern for 
adult PCPs, a majority of whom have many competing priorities and only a few autistic patients in their panels. 
For example, even though 73% of PCPs in our survey felt uncomfortable in their ability to provide quality care 
for autistic adults, 84% stated that they were unlikely to seek additional training on ASD (see preliminary 
results). Our co-investigators found that a majority of PCPs were not even aware they had adult patients with 
ASD.15 As PCPs ourselves, and as educators of PCPs, we are critically aware of the crowded curriculum in 
residency and continuing education programs and appreciate the need for other types of solutions.   
Health systems face significant challenges to providing quality care to autistic adults. Optimally, health 
systems will develop local care coordination and medical home models, as well as regional consultation 
services with specific expertise in autism.18 Specialized referral sources for autistic adults, however, remain 
scarce.15 Moreover, coordinated care approaches in the adult health care system typically focus on common 
adult conditions such as depression or diabetes that drive adult healthcare costs19 and may not automatically 
meet the needs of autistic adults. Interventions are needed to complement and support primary care 
transformation efforts. In order to ensure maximum scalability and impact, such interventions need to be 
implemented with a relatively low investment from health care systems. 
The AASPIRE Healthcare Toolkit was created, using a CBPR approach, to be an easily scalable, low-
intensity intervention that meets the needs of both patients and PCPs. Our team of autistic adults, family 
members, and PCPs developed this toolkit with the above challenges in mind. The toolkit allows PCPs to 
access information on a “need to know” basis, focusing only on the most important, personalized, and succinct 
 
a We appreciate the perspectives of people on both sides of the debate regarding the use of person-first vs. 
identity-first language in autism. We use identity-first language in this proposal to respect the wishes of our 
autistic partners. All our participant materials use the more neutral term “on the autism spectrum”. 

data needed to care for a particular patient. Additional information is available online for providers who desire 
more extensive resources. Patient resources are tailored to autistic patients, who generally prefer very detailed 
information in accessible language, along with practical worksheets and checklists. The toolkit is free to use 
and does not require specialized trainings, costly implementation strategies, or additional personnel. 
Preliminary studies suggest the toolkit is highly acceptable and has the potential to improve the care 
of autistic adults. We evaluated the toolkit with a national convenience sample of 170 autistic adults with 
diverse disability-related characteristics.20 Almost all (>94%) felt that the AHAT and the toolkit were easy to 
use, important, and useful. In a single arm, 1 month, pre-post intervention comparison, we found significant 
decreases in patient-reported barriers to healthcare and increases in satisfaction with patient-provider 
communication. (See preliminary results). However, our study was not designed to promote or assess 
integration of the toolkit into specific primary care practices, nor did it assess provider impressions in-depth. 
A large, multi-site, hybrid effectiveness/implementation trial will have the greatest possible impact on 
improving the way healthcare is delivered to autistic adults. We had initially anticipated following our pilot 
work with a traditional, large effectiveness trial, which could later be followed by implementation and 
dissemination efforts. However, we have come to realize that that may not be an optimal strategy in this 
situation. Though we were pleased with our pilot results, we were concerned that the toolkit’s potential utility 
was lessened by its lack of integration into the work-flow of primary care practices. In order to integrate the 
toolkit into clinical care, one would have to conduct the effectiveness trial within specific practices. Between the 
low number of autistic adult patients per site and the threat of contamination if the unit of randomization is the 
patient or the provider, such a study would need to include a large number of practices. It would be 
conceivable to conduct such a trial in a very large, integrated system such as Kaiser Permanente, but 
generalizing that experience to other primary care practices may then be challenging. Integration of the toolkit 
into the clinic operations of different sites requires attention to implementation issues from the outset. As such, 
our long-term goal is to conduct a large, cluster-randomized controlled trial using a hybrid effectiveness/ 
implementation approach, as outlined by Curran et al.21 To prepare for such a trial, more data is needed on 
ways to integrate the healthcare toolkit and the research study into varied health systems. This project will 
allow us to obtain the data necessary to successfully prepare for the larger effectiveness/implementation trial. 
Innovation 
Little is known about how to improve healthcare services for autistic adults.  Improving access to quality 
healthcare is a high priority for the Interagency Autism Coordinating Committee22, the community of autistic 
adults,23,24 and people who support autistic adults,24,25 but rarely have research studies focused on this 
important issue. To our knowledge, our AASPIRE work6,7,9,20,26 and that of our co-investigators at Kaiser15,27 
constitute a majority of literature on the primary care services of autistic adults. This study will provide critical 
information that can further our understanding of how to improve healthcare services for autistic adults. 
Autism research rarely includes autistic adults in the research process in an authentic and meaningful 
way.  Our project greatly benefits from the strengths, insights, and experiences of autistic adults and their 
supporters, both as research participants and collaborators. CBPR and other participatory approaches may 
strengthen scientific and ethical practices to improve the quality of the science.28-33 Our group has been 
working together for almost a decade, during which time we have developed a strong infrastructure and 
processes to enable true participation in the research process by members of the autistic self-advocacy 
community, as well as by other stakeholders, including family members, healthcare providers, and disability 
professionals.34 Despite a large increase in the use of CBPR in health services research, its use with autistic 
adults remains uncommon. Several reviews by authors unaffiliated with our team have pointed to AASPIRE as 
the only participatory research group in the published literature authentically including autistic individuals 
throughout the research process.35-37 We do see gradual but steady uptake in participatory approaches in the 
autism field and have offered a number of consultations in recent years to autism researchers wishing to 
incorporate input from autistic individuals. Lessons from this project may encourage other autism researchers 
to authentically include autistic individuals on their team. 
Few health services instruments have been adapted or tested for use with autistic adults. A common 
limitation in studies using autistic participants is the use of standardized instruments developed in general 
populations, without attention to language pragmatics issues or other challenges experienced by autistic 
individuals. Our experience with autistic participants and community partners, including those with high 
educational attainment, is that trying to answer surveys using un-adapted instruments often causes confusion, 
frustration, and anxiety, and may lead to incomplete or inaccurate data. We have used our CBPR approach to 

adapt numerous health and health services instruments to be accessible to autistic individuals.6,34,38 We have 
done so by rewording confusing items, adding hotlinks to define difficult or vague terms or offer examples, 
including graphics for response options using Likert scales, changing prefaces to make instructions more clear, 
and/or adding autism-specific items, each time reassessing psychometric properties. We also have begun to 
create and validate a number of new instruments to specifically address autism-specific services issues.7,20 
This project will allow us to further refine and validate these instruments. Our instruments can advance the field 
by helping others more accurately study autism services. Moreover, our processes can serve as an example 
for those wishing to adapt other surveys.  
Our project may provide insight into the types of interventions and implementation strategies that can 
address important but uncommon conditions or topics not yet considered high priority areas by 
primary care providers. Our intervention approach, which provides patient-specific information on a need-to-
know basis to busy PCPs, may be useful in other complex, low-incidence conditions. 
Approach 
Preliminary Studies 
The Academic Autistic Spectrum Partnership in Research and Education (AASPIRE):  AASPIRE is an 
academic-community partnership comprised of autistic adults, academic researchers, healthcare providers, 
and family members. Community partners serve as equal partners in every stage of each project, ensuring that 
research questions are relevant to the community, that methods and instruments are accessible, and that 
findings result in social change. We have created a strong infrastructure for equal and effective partnership and 
to develop communication and work strategies that capitalize on members’ strengths and accommodate their 
needs.34 One of AASPIRE’s main areas of interest has been the healthcare of autistic adults. We have 
collaboratively conducted a series of studies (funded via a CTSA pilot grant and an NIMH R34) to inform, 
develop, and test the AASPIRE Healthcare Toolkit, as shown in Figure 1. These studies directly lead to the 
current proposed project, which will in turn result in the necessary data for the future R01. 
Figure 1: AASPIRE Healthcare Studies 
Healthcare Disparities Survey  
We conducted an online survey to compare the healthcare experiences of autistic and non-autistic adults6. We 
adapted commonly used survey instruments to be accessible to autistic adults and assessed preliminary 
psychometric data on the adapted scales. 437 participants completed the survey (209 autistic, 228 non-
autistic, with or without other disabilities). All adapted scales had good to excellent internal consistency 
reliability (alpha 0.82–0.92) and strong construct validity. In multivariate analyses, after adjustment for 
demographic characteristics, health insurance, and overall health status, autistic adults reported lower 
satisfaction with patient-provider communication (beta coefficient −1.9, CI −2.9 to −0.9), general healthcare 
self-efficacy (beta coefficient −11.9, CI −14.0 to −8.6), and chronic condition self-efficacy (beta coefficient −4.5, 
CI −7.5 to −1.6); higher odds of unmet healthcare needs related to physical health (OR 1.9 CI 1.1–3.4), mental 
health (OR 2.2, CI 1.3–3.7), and prescription medications (OR 2.8, CI 2.2–7.5); lower self-reported rates of 
tetanus vaccination (OR 0.5, CI 0.3–0.9) and Papanicolaou smears (OR 0.5, CI 0.2–0.9); and greater odds of 
using the ED (OR 2.1, CI 1.8–3.8). These findings informed our choices regarding which healthcare outcomes 
to study as well as our hypotheses about which mechanisms of action to target with the toolkit. 
Barriers to Healthcare Study 
We also used our online survey to better understand barriers to healthcare for autistic adults. As no instrument 
existed to measure autism-specific barriers to care, we adapted the "Access Barriers Checklist" instrument, 

created by our colleagues from a literature review.39 To make it more accessible to autistic participants, we 
clarified language and sentence structure, added pop-up definitions for difficult words, and removed redundant 
items. We added autism-related items such as sensory discomforts, difficulty identifying symptoms, and 
concerns about meltdowns. We also replaced the single item on communication with a section of 
communication-related barriers. The final survey included an item pool of 60 barriers. We reduced the 
instrument to the 41 items endorsed by 10% or more of participants and sorted them into semantically related 
categories to create the "Barriers to Healthcare Checklist: Long Form." We created a shorter version that 
would be more practical in clinical or research settings by combining functionally redundant items, collapsing 
lower-granularity items into single higher-granularity items, and verifying that pair-wise correlations were high 
between combined items. We used this 16-item "Barriers to Healthcare Checklist: Short Form" instrument in 
our Toolkit Evaluation Study, and will use it in this proposed project. 
We compared responses to the Barriers to Healthcare Checklist: Long Form between 1) autistic participants 
and participants without disabilities, and 2) autistic participants and participants who had other disabilities. A 
significantly higher proportion of autistic than non-disabled participants endorsed all barriers except lack of 
insurance. Autistic participants were significantly more likely than those with other disabilities to endorse items 
related to emotional stress, trouble following medical instructions, difficulty understanding the healthcare 
system or seeking care or follow-up, having behavior misinterpreted, communication, sensory barriers, and 
handling the waiting room. As expected, items about patient-provider communication and sensory processing 
were among those most selected by the autistic participants; for example, difficulty processing information fast 
enough to participate in real-time healthcare discussions (32%), sensory distress caused by facilities (30%), 
and capacity to tolerate exams and tests (24%). We built many aspects of the toolkit to target these barriers. 
Qualitative study of healthcare experiences of autistic adults 
We conducted a qualitative study to obtain a rich understanding of autistic adults’ experiences with healthcare 
and their ideas for improving their care.9 We completed semi-structured, open-ended interviews with 39 autistic 
adults, and 16 family members and disability services professionals who have supported autistic adults in 
healthcare settings. Autistic participants had a wide range of disability-related characteristics (e.g., 13% 
primarily communicated by methods other than speech, and over half lived in group homes or with family.) 
Participants expressed a range of satisfaction with healthcare, but what differentiated positive and negative 
experiences almost always related to the interplay among patient-, provider-, and system-level factors.  
Participants identified numerous patient-level, autism-related factors that impact healthcare interactions, 
including verbal communication skills, atypical non-verbal communication, sensory sensitivities, challenges 
with body awareness (e.g., differentiating pain or other sensations), slow processing speed, and challenges 
with organization. These patient-level factors interacted with provider-level factors such as providers’ 
knowledge about autism in adults, incorrect 
assumptions about individual patients, 
willingness to allow written communication, 
use of accessible language, openness to 
providing other accommodations (e.g., 
turning off fluorescent lights), and skill in 
appropriately incorporating supporters. 
Finally, participants’ healthcare experiences 
could not be separated from the larger 
context in which they lived and received 
care. System-level factors included the 
availability of supporters, complexity of the 
healthcare system, accessibility of 
healthcare facilities, and stigma about 
autism. We used these findings to build a 
conceptual model that has guided the rest of 
our work (Figure 2), to identify potential 
leverage points that could be targeted with our intervention, and to inform the types of tools and resources to 
include in the toolkit. 
PCP Needs Assessment: We conducted a needs assessment survey with 129 PCPs who regularly care for 
adult patients. The majority, 88%, of the providers had cared for 3 or fewer autistic adults in the past year. 
Figure 2: Conceptual Model 

Even though 73% stated they felt uncomfortable in their ability to provide quality care for autistic adults, 84% 
stated that they were unlikely to seek additional training on ASD within the next year. Nonetheless, 88% stated 
they would accept an autistic patient into their practice if they presented for care. Even under those 
circumstances, less than half stated that they were likely to attend a CME event on ASD, but 82% stated that 
they were likely to search the Internet for information on ASD. We then asked respondents to imagine that an 
autistic patient brought them a brief customized report (like the AHAT) from a reputable source, and explained 
what would be included in such a report. Virtually all of the providers, 98-99%, stated they would read such a 
report, consider following its recommendations, and appreciate the patient’s effort. Finally, we conducted in-
depth interviews with 10 PCPs to better understand their experiences and recommendations. 
Development and psychometric testing of the AHAT 
Recognizing the substantial heterogeneity of autistic individuals, our research participants and team members 
felt that communicating personalized information about individual patients was essential.9 The toolkit’s 
centerpiece is thus the Autism Healthcare Accommodations Tool (AHAT), which allows patients to create a 
personalized accommodations report for their healthcare provider.  A patient or his/her supporter completes 
the AHAT survey to automatically generate a customized cover letter and AHAT report for the provider.  
We used the recommendations elicited in our qualitative studies, and the lived and professional experience of 
the community and academic partners on our team, to create the AHAT survey items. There are two versions, 
one for autistic adults and one for supporters. The AHAT survey includes 5 multiple-choice items about the 
patient’s spoken and written communication abilities and use of alternatives to speech, and 12 items about 
areas where autistic adults may need strategies and accommodations to facilitate care, or where providers 
may need to be aware of autism-related characteristics. Each of these items uses a check-all response format 
and lists five to fourteen potential accommodations, strategies, or characteristics, an option indicating that no 
accommodations are needed, and one indicating that accommodations are needed, but not listed.  There are 
also open-ended items related to patients’ strengths, special interests, and strategies to recognize and address 
anxiety in healthcare settings, and a section eliciting information about supporters. AHAT reports translate this 
information into a clinically useful format, with separate sections for providers, front office and back office staff. 
The AHAT survey and samples of AHAT reports are provided in Appendix A.  
We assessed content validity of the AHAT survey and reports by conducting cognitive interviews with autistic 
adults, supporters, and PCPs and reviewed the AHAT with local groups of PCPs and autism experts. Autistic 
participants consistently indicated that the AHAT was important and easy to understand. Most felt that all their 
necessary accommodations were included in the options. All PCPs indicated the content of the report was very 
helpful, but some PCPs looking at earlier versions felt it would be difficult to access the information. We altered 
the AHAT report format multiple times until we found one that maximized ease of use for PCPs. 
We then conducted a two-week test-retest reliability study with autistic participants and supporters to test the 
stability of the tool over time. Taking each response option for the check-all items as a separate dichotomous 
variable, the original AHAT included 132 variables. We calculated the percent of the time participants gave the 
same response on the two versions of the survey, as well as a kappa and a phi statistic for each variable. In 
test-retest comparisons, participants answered AHAT items similarly 80% of the time (mean .803, std 0.08). 
Evaluation of the Healthcare Toolkit 
We housed the AHAT within an online Toolkit now available at www.autismandhealth.org. Our team of 
academic and community partners jointly created and edited materials to ensure their relevance, utility, and 
accessibility. In general, we found that our autistic participants and team members desired a high degree of 
detail and examples, especially on topics related to navigating the healthcare system. The resulting AASPIRE 
Healthcare Toolkit has a section for patients and supporters and another for healthcare providers. It includes 
general healthcare and autism-related information, checklists, worksheets, and other resources. See 
Appendix B for sample screenshots of the toolkit and a print-out of the patient and provider resources.  
We evaluated the full toolkit using a mixed-methods, single arm, pre-post intervention study design. We used a 
convenience sample of autistic adults recruited nationally and locally via disability-oriented organizations and 
forums. After completing a baseline survey, autistic participants (or their supporters) used the AHAT tool to 
create a personalized report and decided whether to have it sent to their PCP. They then gained access to the 
remainder of the online toolkit. One month after using the toolkit, participants completed a post-intervention 
survey. In cases where participants asked us to send the AHAT report to their provider, we surveyed PCPs 
approximately one month after the intervention to assess whether they found the report useful. 

170 autistic adults participated in the study, either independently or with support. Participants had a wide range 
of disability-related characteristics (e.g. approximately 1/3 required assistance to receive healthcare always or 
often, 1/3 required it sometimes, and 1/3 rarely or never; approximately half lived in their own place and half 
with family or in a group home). Almost all patient participants (>94%) felt that the AHAT and the toolkit were 
easy to use, important, and useful. A majority (65%) of participants gave permission for us to mail their AHAT 
report to their PCP. Of the thirty-five participants who answered an open-ended item about why they chose not 
to have their report sent, a majority indicating that they planned on bringing the report to the PCP themselves 
(N=8), were in the process of changing or did not have PCP (N=8), or did not need it (N=6). A small number 
did not wish to disclose their ASD to their PCP (N=4), had privacy concerns (N=2), didn’t like the report (N=1) 
or worried that their PCP would not react well to it (N=2). We were able to send AHAT reports to 88 PCPs, 41 
(47%) of whom completed the survey. Most of the PCPs surveyed read the AHAT (97%), rated it as 
moderately or very useful (82%), and would recommend it to other patients (87%). 
In pre-post intervention comparisons, the mean number of barriers decreased significantly (4.07 to 2.82, 
p<0.0001, effect size -0.55). For the 43 participants who saw their PCP during the one month follow-up period, 
satisfaction with PCP communication improved significantly (mean 30.9 to 32.6, p=0.03, effect size 0.26). Of 
note, we also found small but significant increases (mean 37.9 to 39.4, p=0.02, effect size 0.12) in a 21-item 
scale that we created de novo to capture potential toolkit-specific changes in patients’ confidence in 
healthcare. While the scale had demonstrated strong internal consistency (alpha 0.92), additional work is 
needed to refine this scale and better target it to the toolkit’s potential mechanisms of action. 
Responses to open-ended survey questions have started to help us understand how the toolkit may be 
affecting change. Patients stated the toolkit helped clarify their needs, enabled them to self-advocate and 
prepare for visits more effectively, and positively influenced provider’s willingness to offer accommodations. 
For example, one participant wrote “It takes away a lot of my uncertainty about the appointments. Whether I'll 
bring up everything I want to bring up, whether I asked the right questions about follow up care, and being 
prepared for talking to new doctors. It's a game changer for me.” Another wrote “<My provider> went over it 
with me and did what had been recommended….I felt like some of the difficulties I experience were addressed 
and that they wouldn't have been had I not made use of the Healthcare Toolkit.” Most answers from PCPs to 
open-ended questions were positive and provided examples of the tool's utility (e.g. “Extremely helpful. What I 
needed were specific, but concise suggestions regarding how to make my patient more comfortable. The 
report will be in her chart and I will use it at each visit.”) 
Research Design and Methods 
Community Academic Partnership 
The Co-Directors of AASPIRE, Drs. Nicolaidis and Raymaker, will serve as PI and Co-I, respectively. Both 
bring dual perspectives as academic researchers and members of the larger autism community. Dr. Nicolaidis 
is a health services researcher, PCP, and parent of an autistic teenager. Dr. Raymaker is an autistic individual 
who co-founded AASPIRE as the Community PI, but who has since earned her PhD in systems science, in 
part thanks to AASPIRE’s strong emphasis on community capacitation.40 Our full team of academic and 
community partners (including additional autistic adults, family members, and PCPs) works closely together to 
guide all aspects of the project. A Steering Committee with representatives from each community helps resolve 
conflicts, as needed. Team members communicate on a very active list-serve. Meetings occur in a variety of 
ways (e.g., in-person, text-based chat, video-conferencing, telephone) to accommodate the social and 
communication needs of autistic partners as well as the geographic dispersion of our team. We break up into 
smaller workgroups, as needed, to accomplish specific tasks, but always make sure to have adequate 
representation from community partners and buy-in from the full team. Careful attention is given to making 
feasible accommodations to support active participation by all members. We have written memoranda of 
understanding guiding our collaboration, including a formal consensus-building process, and authorship and 
presentation guidelines. One of the main principles of CPPR is that projects should have a transparent and 
iterative process for evaluating progress and impact.41 AASPIRE uses double-loop learning42 in its standard 
operating procedures by doing regular "CBPR check-ins" to critically examine both our processes and our 
underlying understanding of who we are and what we are doing and then adjusting our processes and/or our 
underlying assumptions about our goals, values, or mental models to improve our operations. Additional 
information about our collaboration processes is described in our CBPR-focused publications.34,43,44 In this 
project, our team will expand to include a new academic partner (Dr. Lisa Coen of Kaiser Permanente) and 
several new community partners from our partnering health care systems. These new team members will 

represent local PCPs, primary care office staff, administrators, patients, and supporters. As we have done in 
the past, we will have meetings specifically focused on welcoming new members to the team and integrating 
them into the CBPR process. These new members will be critical to helping us ensure the most feasible and 
effective strategies for integrating the AASPIRE Healthcare Toolkit into their local health systems. 
Setting: 
We will conduct the study within clinics from three diverse systems. A majority of participants will be recruited 
from Kaiser Permanente Northern California (KPNC), an integrated healthcare delivery system with more than 
3.5 million members, 20 hospitals, and over 50 outpatient clinics. KPNC has over 6600 adult members with 
diagnoses of Autism Spectrum Disorder (ASD). The KPNC team will select 4 intervention clinics and 4 
matched control clinics to participate in the study and can select additional clinics if we do not meet anticipated 
recruitment goals. Seventeen KPNC clinics each have >100 adult patients with diagnosed ASD. Kaiser’s great 
resources and commitment make it an optimal site both for this pilot study and for a future large RCT. 
However, we recognize that Kaiser’s strengths as an integrated health system can limit generalizability. As 
such, we will also study a variety of additional clinics in Oregon to proactively develop an implementation plan 
that can be effective in diverse practices. We will work with two clinics from Legacy Health System, a private, 
non-profit hospital system with 6 hospitals and 26 primary care clinics. Though each of the Legacy primary 
care clinics has only about two-dozen adult patients with diagnosed ASD, we feel it’s important to study the 
implementation of the toolkit in a private health system with low prevalence of diagnosed ASD, as that may be 
more typical. Finally we will use two of the four primary care clinics run by the Oregon Health and Science 
University (OHSU) Department of Family Medicine. We chose these two clinics because they represent 
diverse practices – the Gabriel Park Clinic is in an urban area and the Scappoose Clinic is a rural health center 
in a town of under 7000 people. The two clinics have a total of approximately 200 adult autistic patients. 
Though the two sites are so different that they cannot serve as controls for one another, they each consist of 4 
“pods” that function independently, with their own group of providers, front and back office staff, and patient 
panels. As such, we will use two pods as the intervention site and two pods as the control site for each of the 
OHSU clinics. All three participating health systems use Epic as their electronic medical record (EMR).  
Overview, Study Design and Change Model: 
We will conduct a mixed-methods study (concurrent QUANT-qual), using a CBPR approach, in preparation for 
a future cluster randomized hybrid effectiveness/implementation trial. Qualitative data will supplement 
quantitative data to obtain a deeper understanding of implementation issues and patient and provider 
experiences, to further explore potential mechanisms of action, and to help interpret quantitative findings. We 
will start by working with representatives from each intervention site to determine how to integrate the toolkit 
into their practices and track implementation efforts. We will pay attention to what might be done similarly 
across systems and what has to differ to accommodate practice needs. We will then conduct a 6-month, non-
randomized, controlled, pilot study in 5 intervention sites and 5 control sites. Though control sites are 
sometimes considered an unnecessary use of resources in pilot-studies, in this case, it is important to collect 
data from control sites to 1) ensure that we can obtain adequate recruitment and retention rates, even without 
offering an intervention, 2) to assess for potential contamination being that patients and providers are free to 
use the publicly available toolkit, and 3) to obtain more robust efficacy data on the toolkit’s short-term 
outcomes and potential mechanisms of action than we could in our prior 1-month, single-arm trial.  
 Figure 2: Change Model 
Our study is based on the conceptual model we developed from our qualitative work (see Preliminary Results). 
This model views successful healthcare outcomes as being dependent on the interaction between patient- and 
provider-level factors within a larger context of system-level factors. We developed the toolkit to target potential 
leverage points within this model. Specifically, it is meant to give patients and providers the tools they need to 
improve their self-efficacy while encouraging providers and staff to use desired, patient-specific 
accommodations and recommended strategies. We hypothesize that doing so will improve patient-provider 

communication and decrease barriers to healthcare, with possible long-term impacts on unmet healthcare 
needs and healthcare utilization. Figure 2 shows our proposed change model.  
Our study will use multiple data sources: 1) process information from research records, EMR, and clinic 
protocols, 2) baseline and follow-up surveys of autistic participants in intervention and control clinics, 3) brief 
baseline and follow-up surveys of providers in intervention and control clinics, 4) qualitative interviews with a 
subset of patients, providers, staff, and administrators from intervention clinics, and 5) administrative data on 
healthcare utilization. Table 1 depicts how constructs from each data source will be used to meet our aims. We 
intend to survey all autistic adults in the 10 participating sites, along with their PCPs, with the goal of including 
a minimum of 250 autistic adults. We will also obtain in-depth, qualitative data from 30 autistic adults, 15 PCPs, 
and 15 support staff/administrators from the five intervention sites. 
Table 1: Data Sources, Constructs, Measures, and Aims 
Data Source 
Construct(s) 
Measure(s) 
Function(s) 
Aims 
Process data 
Recruitment, retention, 
toolkit utilization, 
protocol adherence 
Process information from research 
records, EMR, clinic protocols, other 
process / implementation checklists 
Feasibility, fidelity, 
implementation 
strategy refinement 
1,4 
Patient surveys 
Patient-provider 
communication 
Adapted for ASD from 2007 Health 
Information National Trends Survey  
Short-term outcome 
2 
Barriers to healthcare 
Barriers to Healthcare Checklist: Short 
(developed for ASD) 
Short-term outcome 
2 
Unmet healthcare 
needs and healthcare 
utilization 
Adapted for ASD from 2002/2003 Joint 
US Canada Survey and 2007 National 
Health Interview Survey Questionnaire 
- Adult Access to Health Care & 
Utilization  
Long-term outcome 
4 
Chronic illness self-
efficacy 
Adapted for ASD from Self-Efficacy for 
Managing Chronic Disease Scale  
Mechanism of 
action 
3 
General healthcare self-
efficacy 
Adapted for ASD from Chronic Disease 
Self-Management (long version) 
Mechanism of 
action 
3 
Patient self-advocacy 
and visit preparedness 
Confidence in Healthcare Scale 
(developed for ASD; to be further 
modified in proposed study) 
Mechanism of 
action 
3 
Provider/staff use of 
accommodations 
To be developed de novo for this study 
Mechanism of 
action 
3 
Toolkit acceptability 
Healthcare Toolkit evaluation items 
Evaluation / fidelity 
1, 4 
Provider surveys 
Provider self-efficacy 
Items on self-efficacy, attitudes, and 
satisfaction with the toolkit 
Mechanism of 
action 
3 
Qualitative 
interviews with 
patients, providers, 
and staff 
Better understanding of 
toolkit impact 
Semi-structured questions reflecting on 
experience with toolkit 
Mechanisms of 
action 
3 
Better understanding of 
implementation process 
Semi-structured questions around the 
implementation 
Implementation 
strategy refinement 
1, 4 
Administrative data 
Healthcare utilization 
Primary care, ED, and preventive care 
Long-term outcome 
4 
Toolkit integration and process evaluation: 
During the start-up phase, we will meet with providers, administrators, and staff from each intervention clinic to 
create a plan for how best to integrate the toolkit into clinical practice. For example, the clinic may choose to 
set up a protocol for scanning AHAT reports into the EMR, flagging patient charts to alert providers to the 
existence of the AHAT, communicating relevant recommendations to front office and back office staff, setting 
up follow-up appointments, if needed, creating EMR templates to help providers document discussions or 
changes, and responding to challenges implementing requested accommodations.  

We will then conduct a process evaluation spanning the duration of the project. Using Stetler’s classification 
system,45 this assessment would be considered a formative implementation-focused evaluation. The purpose 
is to resolve actionable barriers, enhance identified levers of change, and refine future implementation efforts 
by analyzing discrepancies between the implementation plan and its operationalization. As part of this 
evaluation, we will measure a variety of quantitative process measures including: 1) recruitment and retention 
rates; 2) completion of AHAT reports; 3) use of other portions of the toolkit site; and 4) proportion of AHAT 
reports scanned into the EMR. We will collaboratively determine how to feasibly collect additional process 
information to track fidelity with the implementation protocols the clinics developed. We will use qualitative data 
to more fully understand the implementation experience (see below). Such data will focus on patient, provider, 
staff, and administrator perceptions of the Toolkit’s utility, how the toolkit was used, barriers and facilitators to 
successful uptake and integration, and recommendations for change to the implementation plan. 
Survey and Administrative Data Collection: 
Participants, recruitment, and screening: Participants will be adults (age 18 and up) who have ever had ICD-9 
or ICD-10 codes consistent with autism spectrum disorder (including autistic disorder, Asperger’s disorder, and 
Pervasive Developmental Disorder Not Otherwise Specified) and who obtain primary care from the 
participating clinics. Of note, we will not be confirming autism spectrum diagnoses. Given the significant 
challenges with autism diagnoses in adults and the wide variation in care, we expect that a proportion of these 
ICD codes were entered into the record in error or may have changed upon further testing. However, we feel 
that in a real-world setting, it would be unfeasible for PCPs to confirm ASD diagnoses prior to using tools to 
facilitate care. Moreover, it is likely that the tools may be of benefit to other people with communication 
disorders. Finally, we do not want participation in the study to denote that a patient has a particular medical 
diagnosis. As such, on all publicly facing materials, we will be describing the tools and the study as relating 
“autism and other communication disabilities.” (Note, the protocol continues to refer to “autistic participants” in 
multiple areas for the sake of conciseness.) 
In cases where patients cannot participate directly, even with appropriate accommodations and supports, we 
will ask a supporter to participate as a proxy with as much input as possible from the autistic patient. 
Supporters must also be age 18 or older, must speak (or read) English, and must have experience supporting 
the autistic patient in healthcare settings. Participants also include primary care providers, staff, and 
administrators who work in the participating sites. 
Each health system will identify all adult patients assigned to the participating practices who have had an ICD-
9 or 10 code consistent with ASD (299.00, 299.8, and 299.9 or F84.0, F84.5, and F84.9). Staff from the 
partnering health systems will send a letter (via mail or Epic MyChart message) to all potential participants 
explaining the study. The letter will include information on how to participate and information for how to opt out 
of future calls. Staff will then make recruitment telephone calls to patients who did not reply to the letter. Clinic 
personnel can also inform patients about the study when patients come into the clinic for an appointment. 
Personnel will give patients a recruitment flyer and direct them to contact the study website or contact the 
Program Manager to learn more about the study. They will also ask participants if they would rather clinic 
personnel pass along their contact information to the Program Manager so that she can contact them directly. 
Potentially interested participants will take a screening questionnaire to assess eligibility. As in our prior 
studies, the screening questionnaire can be done via telephone or Internet, independently or via a supporter. 
Eligible participants will be asked for informed consent. In cases where a participant cannot offer informed 
consent, we will ask for consent from a legally authorized representative.  
Recruitment materials will include information for how participants can participate online (a URL just for this 
study). When participants take the online screener, the program will automatically direct them to the correct 
consent form (based on whether it is the patient, supporter, or an LAR, if they are in an intervention or control 
clinic, and so forth). At the end of the consent form, if the person has checked yes (and we have the correct 
supporter/LAR combination for those who need a supporter or LAR), the computer will assign them a study 
number and pass that number along to the registration system. They will then be asked to create a login and 
password. After they have set up their login/password, they will get directed into the survey using a specialized 
link based on the participant ID. (Our database stores the participant ID in 3 places: the screening/consent 
database, the registration system, and the survey database). The participant will then take the survey, and 
after they are done, they will be directed to the AHAT / toolkit. Six months later, we will send them a reminder 
(with the login name, but not the password), so they can continue to the 6-month follow-up survey. The 
registration system we use offers a reset for their password if they have forgotten it (as long as they still have 

access to their email address. We can change the email address manually if need be.) For those people who 
choose to go directly online, there is no need to interact with a RA.  
For those people who choose to go directly online, there is no need to interact with a RA. Those who prefer to 
contact us by phone or email will be given a link to a special starter page (based on which survey version they 
need) where they enter the patient name. The program will generate the ID number and they will then proceed 
like anyone who did the consent online.   
Providers and staff from the intervention and control clinics will also be included as participants.  
Patient Survey:  All patient participants will be asked to take surveys at baseline and at six months. After 
logging into their secure account, participants complete surveys online (independently or with help from a 
supporter) using our Audio Computer Assisted Survey Instrument (ACASI), a highly accessible system with a 
read-aloud option and other features designed to meet the needs of people with disabilities.46 Participants 
without Internet access can take the survey at their primary care clinic or the PSU or Kaiser research offices. 
After completing the baseline survey, participants from intervention sites will be automatically directed to use 
the AHAT to create a personalized report. After reviewing the report, they will be asked permission to have the 
report sent directly to their PCP. Participants will then be directed to the remainder of the toolkit (on a 
password-protected research site), where they can read information about health and healthcare and 
download worksheets and checklists. The research version of the toolkit will be accessible through participants’ 
personal accounts to better track participants’ use of components of the toolkit. Clinics will be expected to use 
the implementation protocol they developed to ensure the AHAT report reaches appropriate staff and that 
recommended strategies and accommodations are incorporated into the patient’s care. Six months later, all 
participants will be re-contacted and asked to participate in the follow-up assessment. To increase retention, 
we will collect various types of contact information and will request permission to use updated information from 
clinical records, if needed. Participants will receive $30 for completing both surveys.  
We will collect data on patient provider communication using items we previously adapted6 from 2007 Health 
Information National Trends Survey (HINTS).47-50 We clarified wording and added two new items on expressive 
and receptive comprehension as community partners felt this was not adequately addressed in the initial scale. 
The scale asks patients about their last visit with their PCP. Responses use a 4-point Likert scale with anchors 
of “Never” to “Always”. The scale is scored by summing the responses. In the post-test, participants will only be 
asked this scale if they have seen their PCP during the 6-month study. The original HINTS patient-provider 
communication scale and our adapted version both had a Cronbach’s alpha of >=0.9.6,51 
We will assess barriers to healthcare using our Barriers to Healthcare: Short scale7. The scale includes 16 
barriers commonly experienced by autistic patients. It was found to be responsive to change in our prior Toolkit 
evaluation. Items can either be analyzed separately or as a count of the total number of barriers endorsed.  
We will assess healthcare self-efficacy using a measure we previously adapted for use with autistic adults6 
from the Chronic Disease Self-Management Studies by Lorig et al.52,53 Participants with at least one chronic 
medical condition complete the Self-Efficacy for Managing Chronic Disease 6-Item Scale.52 All participants are 
also asked to complete 9 additional items about healthcare self-efficacy, selected from Lorig’s original longer 
instrument,53 but adapted to be applicable to individuals whether or not they have any chronic illnesses.  All 
items are rated on a scale of 1-10 with anchors of “not at all confident” and “totally confident” and summed into 
a composite score (range 9-90 for general healthcare self-efficacy, 6-60 for chronic condition self-efficacy; 
higher values indicate greater self-efficacy). Both subscales had good internal consistency reliability (alpha 
0.82 and 0.88) and strong convergent validity, with a strong correlation between general healthcare and 
chronic condition self-efficacy, and between both measures of self-efficacy and unmet healthcare needs.   
We will explore other potential mechanisms of action by modifying a 21-item Confidence in Healthcare Scale 
we previously developed to capture potential toolkit-specific changes in patients’ confidence in their ability to 
navigate the healthcare system and the systems’ responsiveness to their needs. Response options use a 4-
point Likert scale with anchors of “0 - Not at all confident” to “3 - Totally confident”. The scale was originally 
scored by summing responses from the 21 items, resulting in a possible range of 0 to 63, with higher scores 
corresponding to higher self-efficacy. In our Toolkit Evaluation study, the scale had a Cronbach’s alpha of 0.92 
and was responsive to change. However, we feel that it would be useful to further develop this measure to 
more clearly target our proposed mechanisms of action, including self-advocacy and visit preparedness. We 
will use our prior data and our community partners’ insights to modify this scale. We will then use our new data 

to do a confirmatory factor analysis and re-test its psychometric properties in preparation for the larger RCT. 
We will also create and test a new measure on satisfaction with provider/staff use of desired accommodations. 
We will assess unmet healthcare needs and healthcare utilization, using items we previously adapted6 from the 
2002/2003 Joint US Canada Survey54,55 and the 2007 National Health Interview Survey (NHIS) Questionnaire - 
Adult Access to Health Care & Utilization.56,57 We will measure unmet healthcare needs using the item “During 
the past 6 months, there was a time when I felt that I needed the following type of healthcare, but did not 
receive it. (Check all that apply).”  Response options include six types of healthcare (e.g., “medical care for a 
physical health problem,” “mental healthcare or counseling”). As in the past, we will ask a variety of questions 
about outpatient, ED, and hospital visits and use of preventive services, however we will also obtain EMR and 
claims data from each health system about participant use of these services and compare results.  
In the baseline survey, we will collect data on demographic and disability-related characteristics. In the 6-
month follow-up participants in the intervention arm will answer a set of close- and open-ended evaluation 
questions about their satisfaction with the toolkit, which parts they found most useful, why they did not give 
permission to share their AHAT report, whether they discussed the report with the PCP, and what changes, if 
any, they felt occurred in response to the toolkit. To assess for contamination, the 6-month follow-up survey will 
include an item asking participants if they have used the public version of the toolkit. Patients in the control 
clinics will be given a link to the public site at the end of the study. 
Provider Surveys: We are acutely aware of the importance of minimizing the burden of this study on PCPs, 
both in the current study and in the future R01. As such, we will use patient surveys and administrative data to 
answer most of our research questions, and will only conduct in-depth interviews with 3 providers from each 
intervention site (N=15). However, we believe that provider self-efficacy may be an important mechanism of 
action that needs to be assessed directly from all providers. We will conduct an extremely brief survey (<5 
minutes) at baseline and at the end of the study with all providers who have autistic patients in their panels (N 
50-80). Providers may participate via email, fax, telephone, or online. The survey will include items on self-
efficacy and attitudes toward autistic adults. Follow-up surveys will also include an item about whether they are 
aware of the AASPIRE Healthcare Toolkit and, if so, a few items about their satisfaction with the toolkit.  
Administrative Data: We will use administrative data from each health system to assess healthcare utilization. 
Obtaining such information is relatively straightforward for a closed healthcare system such as Kaiser. 
However, it is more complex in non-integrated systems. We will explore how well we can capture data from the 
OHSU and Legacy Systems using EMR data, including Care Everywhere (an Epic System that links EMR 
visits from most local health systems) and claims data from Health Share (the Medicaid managed care 
coordinated care plan for our county). Though this study will not be powered to show a difference in unmet 
needs or healthcare utilization, these data can help inform the future R01. It will also give us experience 
working with this type of administrative data from each health system. 
Quantitative Data Analysis 
Our quantitative analysis plan includes descriptive and psychometric analyses, assessment of missing data 
and attrition, and a mixed effects regression analysis to compare results from intervention and control sites 
while adjusting for demographic and disability-related characteristics. We will conduct analyses using STATA 
14 (Statacorp, College Station, Texas). We will use an intention-to-treat approach for all analyses. 
Preliminary analyses will include careful examination of descriptive statistics and distribution for each of the 
study variables at baseline and the 6-month follow-up. This will include stratified analyses within the 
intervention and control groups. For variables measured with multiple items, psychometric analyses 
(Cronbach's alpha, confirmatory factor analysis) will be conducted to instigate internal reliability, and, when 
necessary, measurement modifications will be made to improve reliability.   
We will use two independent sample T-tests to test bivariate differences between the main independent 
variable (intervention vs control clinic) and baseline continuous variable subject characteristics and Chi-
square/Fisher-Exact test to assess differences between the main independent variable and categorical 
variables. We will apply similar tests to primary outcomes and secondary outcomes at each time point.   
We will test Aim 2 hypotheses using multivariate regression models. The dependent variable in each of our 
primary analyses will be the 6-month change in short-term outcomes (patient-provider communication score 
and number of barriers). We will calculate change by subtracting the baseline score from the score at 6 
months. We will also conduct exploratory analyses using the 6-month change in scores for the potential 

mechanisms of action (e.g., self-efficacy, use of accommodations) and long-term outcomes (e.g., unmet 
needs, emergency department use) as the dependent variable. Analyses will use linear vs logistic models 
depending on whether the outcome is continuous (e.g., patient-provider communication score) or binary (e.g., 
ED use, unmet needs). The predictor will be study arm (intervention vs control). We will adjust for potential 
confounders including data source (direct report vs proxy), age, gender, race/ethnicity, residence (own home 
vs with family of origin); need for support to communicate with providers; health status, and unmet needs at 
baseline.  
Power Considerations: We plan to enroll 250 participants to have complete follow-up data on at least 200 (100 
intervention;100 control), which will allow us to detect an effect size of 0.4 with a power of 80% using an 
independent sample t-test test with a two-tailed hypothesis and an alpha of 0.05. It would provide 97% power 
to detect an effect size of 0.5. Though one must use caution in deriving effect sizes from small pilots, based on 
our preliminary results, we feel it is reasonable to expect this level of change in our short-term outcomes. For 
example, we noted a 0.55 effect size in the number of barriers to healthcare. We are using a conservative 
estimation to compensate for the complex multivariate analyses proposed in Aims 2 and 3.   
Qualitative Interviews with Patients, Providers, Staff, and Administrators 
Participants and Sampling: We will collect qualitative data from 30 patients, 15 providers, and 15 
administrators/staff selected from the 5 intervention sites to better understand the implementation process and 
the tool’s potential impact. We will use maximum variation sampling,58 a purposive sampling strategy which 
increases depth of understanding by selecting a diverse group of individuals who are expected to have 
different perspectives. We will use data from our quantitative surveys to identify which patient and supporter 
participants to invite to the qualitative study. The goal will be to create a patient sample that has wide 
distribution of the following characteristics: 1) gender; 2) age, 3) race/ethnicity, 4) living situation, 5) need for 
assistance to receive healthcare, 6) use of alternative and augmentative communication (AAC), 7) permission 
(yes/no) to share AHAT report with provider, and 8) clinic site. We will primarily recruit participants who have 
seen their PCP after using the Toolkit, as they are the ones most likely to provide rich, interesting information. 
However, we will intentionally sample 5 participants who did not see their PCP to try to understand potential 
barriers to care that were not addressed by the toolkit. We will recruit patient participants for an interview 
between 4-8 months after they complete the baseline survey. We will use a similar strategy to obtain a varied 
sample of providers and administrators/staff from each of the clinics, purposely sampling people who serve in a 
variety of roles in each clinic. Participants will receive an additional $50 stipend for participating in an interview. 
Data Collection: We have found that offering a choice of participation modes is key to being able to collect rich 
data from autistic participants, many of whom prefer written or asynchronous communication. As in our prior 
work, a research assistant, under the supervision of Dr. Nicolaidis, will conduct interviews in person or via 
telephone, email, or instant messenger, and will individually work with participants to offer accommodations. 
We will work with our community partners to create an interview guide with clear, concrete, specific, and easy-
to-understand questions and enough framing to facilitate rich responses. Interview topics for autistic adults and 
supporters include impressions of the toolkit, experience using it, impressions of how it affected their 
healthcare interactions, and recommendations for addressing barriers to use. Interviews with providers, staff, 
and administrators will focus on their experience using the toolkit with patients, changes that they may have 
made due to AHAT reports, how the tools were (or were not) integrated into the clinic’s practices, and 
recommendations for changes to the implementation strategy.  
Qualitative Data Analysis: We will analyze data using thematic analysis59 with an inductive approach (as is 
used with Grounded Theory), at a semantic level, using a constructionist paradigm. Drs. Nicolaidis and 
Raymaker and a research assistant will read each of the transcripts in their entirety, discuss general 
impressions and insights, and develop a set of preliminary codes. Dr. Raymaker and the research assistant will 
apply the codes to the transcripts. The three investigators will use an iterative process, meeting regularly to 
review the coding and generate preliminary themes and sub-themes. Disagreements will be resolved by re-
reading the original transcripts until the investigators agree. Preliminary results will be discussed with the 
community partners, who will offer feedback on the interpretation of data. The three investigators will then meet 
to review and refine the final themes. We will use Atlas-TI for qualitative data management. 
Anticipated Difficulties and Next Steps 
We expect that we will meet recruitment targets with the initial set of clinics, but can add additional sites from 
each of the three health systems if needed. We also expect an adequate response rate from PCPs, but we will 

work with clinic leadership, as needed, to reduce barriers and increase incentives to participation. We will use 
our findings to create a flexible implementation strategy that can be used by diverse practices to incorporate 
the toolkit into clinical care. We will also use findings to refine our change model, outcome measures, study 
protocols, data collection strategies, and power estimations in preparation for the R01.  
Timeline 
Activity 
Year 1 
Year 2 
Ongoing use, assessment, and refinement of CBPR collaboration processes 
x 
x 
x 
x 
x 
x 
x 
x 
Project start-up; decisions re clinic integration protocols; finalization of instruments 
x 
x 
 
 
 
 
 
 
Participant recruitment and baseline data collection 
 
 
x 
 
 
 
 
 
6 month follow-up surveys and qualitative data collection 
 
 
 
 
x 
x 
 
 
Process evaluation / refinement of implementation strategies for future trial 
 
x 
x 
x 
x 
x 
x 
 
Data analysis, writing of manuscripts, preparation for R01 proposal 
 
 
 
 
x 
x 
x 
x 
 
 
 

Protection of Human Participants  
The study will be carried out in primary care practices from the KPNC, OHSU, and Legacy Health Systems. 
We will start recruiting participants from 8 KPNC clinics, 2 OHSU clinics, and 2 Legacy clinics. If we have 
difficulty meeting recruitment goals, we may add additional practices as needed. Half the clinics from KPNC 
and Legacy will be designated as intervention sites and half will be designated as control sites. The two OHSU 
clinics do not serve comparable populations, but they each consist of 4 separate pods with distinct providers, 
patients, and staff. As such, two pods from each OHSU clinic will serve as an intervention site and two pods 
from each clinic will serve as a control site. There will thus be a total of 7 intervention sites and 7 control sites. 
1. Risks to the Participants  
1a. Human Participant Involvement and Characteristics  
The goal of this proposal is to use a CBPR approach to understand how to best integrate the toolkit into 
diverse health systems as we prepare for a larger effectiveness-implementation trial. To achieve this goal, we 
will conduct a series of studies with autistic adults (who participate either independently or with the help of a 
supporter), primary care providers, and other primary care office staff.  Studies include a combination of 
qualitative interviews and surveys. We will also access existing data from patients’ electronic medical records 
to assess healthcare utilization (e.g. use of the emergency department, receipt of preventive care services). 
Human Participant Involvement 
Participants will be in the study a total of 6 months. Potentially eligible autistic participants will take a short 
screening survey to assess eligibility. Autistic participants will complete two online surveys, one at baseline and 
another at 6 month. Participants from intervention clinics will also complete an Autism Healthcare 
Accommodation Tool (AHAT) survey and be directed to use the online tools and resources available in the 
AASPIRE Healthcare Toolkit. Each baseline and follow-up survey should take approximately 30 minutes. The 
AHAT survey will take approximately 20 minutes. Participants can spend as much time as they wish using the 
resources on the online toolkit.  
Primary care providers will complete a very brief survey either online, or via fax, telephone or in-person, at 
baseline and at the end of the study. Surveys should take less than 5 minutes to complete.  
A subset of autistic participants, PCPs, and office staff who work in the intervention clinics will take part in 
semi-structured, open-ended interviews. Interviews will last 30-90 minutes.  
Participant Characteristics / Inclusion Criteria  
1) Patients: Participants will be adults (age 18 and up) who have ever had ICD-9 or ICD-10 codes consistent 
with autism spectrum disorder (including autistic disorder, Asperger’s disorder, and Pervasive Developmental 
Disorder Not Otherwise Specified) and who obtain primary care from the participating clinics. Of note, we will 
not be confirming autism spectrum diagnoses. Given the significant challenges with autism diagnoses in adults 
and the wide variation in care, we expect that a proportion of these ICD codes were entered into the record in 
error or may have changed upon further testing. However, we feel that in a real-world setting, it would be 
unfeasible for PCPs to confirm ASD diagnoses prior to using tools to facilitate care. Moreover, it is likely that 
the tools may be of benefit to other people with communication disorders. Finally, we do not want participation 
in the study to denote that a patient has a particular medical diagnosis. As such, on all publicly facing 
materials, we will be describing the tools and the study as relating “autism and other communication 
disabilities.” (Note, the protocol continues to refer to “autistic participants” in multiple areas for the sake of 
conciseness.)   
In cases where patients cannot participate directly, even with appropriate accommodations and supports, we 
will ask a supporter to participate as a proxy with as much input as possible from the patient.  Supporters must 
also be age 18 and older, must speak (or read) English, and must have experience supporting the patient in 
healthcare settings. We expect to screen up to 500 participants to obtain an initial sample of 250 participants, 
with complete 6-month data for 200 participants. We will purposely sample 30 of these participants to take part 
in the qualitative interviews. 
2) Primary Care Providers: We will include all primary care providers who practice in the intervention clinics. 
PCPs, by definition, are over 18 and speak English. They typically have MD, DO, NP, or PA degrees and 
practice primary care. We expect approximately 75 PCPs to take part in the survey. We will purposefully 
sample 15 of these PCPs to take part in the qualitative interviews. 

3) Support staff: We will include an additional 15 clinic employees in the qualitative interviews. Employees will 
include front office staff (e.g. receptionists), back office staff such as medical assistants or nurses, and 
administrators (e.g. clinic managers). Again, by definition, they will be over age 18 and speak English.  
Sampling plan  
We will attempt to enroll all patients, age 18 or over, who have medical diagnoses of autism spectrum disorder, 
and are receiving primary care in the participating sites. We also will attempt to survey all primary care 
providers who have autistic adults on their panels in each clinic. We will work with clinic champions from each 
clinic to purposefully select which additional employees to invite to the qualitative study. 
1b. Sources of Materials  
Data will come from surveys, semi-structured open-ended interviews, and review of exiting data available in 
the patients’ electronic medical records (EMR).  
Survey data will be collected from patient participants or supporters via an Audio-Computer Assisted Self-
Interview (ACASI). A-CASI is a secure, web-based, and highly accessible tool that offers participants additional 
privacy by allowing them to enter data themselves. The ACASI electronic database is stored behind the PSU 
firewall. It will be password-protected and only the PI and specific PI-designees will have access to participant 
information.  
The AHAT report, which serves to communicate personalized data about a specific patient to his or her PCP 
and other primary care clinic staff, needs to include the patient’s name and date of birth in order to serve its 
clinical function. As such, the initial AHAT database on the ACASI system and stored copies of the AHAT 
reports will remain identified. We will regularly transfer data from the ACASI database into a master database 
for data analysis purposes. This database will be stripped of identifying information and coded with the unique 
participant IDs. Of note, while the surveys collected via the ACASI system include identified information, they 
do not include health information.  
Participants will have a choice of a variety of modes in which to participate in the qualitative interviews and the 
PCP survey. Options include email, telephone, instant messenger, and in-person. Initial email messages and 
chat logs will be, by definition, identified and identifiers cannot be reliably erased from all records. Participants 
will be alerted to that fact in the consent materials. We will copy data from such sources into word processing 
files and strip them of identifying data prior to conducting any analyses, again coding them with the unique 
participant ID. Similarly, recordings of interviews conducted over the telephone or in-person may be 
recognizable, but transcripts will be stripped of identifying data and coded with a unique identifier.  
Paper records will be kept in a locked cabinet in the PSU or KPNC research offices. Electronic files (including 
databases, transcripts of interviews, and audio-recordings of interviews will be kept on a secure, password 
protected computer account. Only study personnel will have access to the data. All reports will describe results 
in aggregate form. Data will be destroyed at the end of the study. 
All three systems will share EMR data from consented participants. Data from the 3 health systems will include 
PHI. We will send survey data collected at PSU on patients from the OHSU and Legacy Health Systems to 
OHSU. We will send survey data collected at PSU on patients from the Kaiser Health System to Kaiser. OHSU 
and Kaiser study personnel will link the survey data to data from the EMR. They will then deidentify data and 
send a deidentified version of the full database to OHSU and PSU. The coded database, which does not 
include PHI, will be shared back to PSU to be further analyzed by PSU investigators.    
All data with PHI will be stored on OHSU or Kaiser computers or on Box, a fully HIPPA compliant cloud storage 
and communication system with added protections in place for confidential and restricted data or protected 
health information. OHSU and Box have entered into a Business Associate Agreement that meets all policy 
compliance requirements. Dr. Nicolaidis can grant access to specific files to collaborators at other institutions. 
She will create one folder for each institution. OHSU and Legacy collaborators can then safely and securely 
place files in these folders on Box. For Kaiser, all data with PHI will be stored on Accellion Solution, a secure 
web user interface that has protections in place for confidential data.  
KPNC staff will also conduct some of the qualitative interviews of KPNC patients and employees. They will de-
identify transcripts and share with PSU investigators. 
 

1c. Potential Risks  
We believe that each of the three studies poses minimal harm to participants. Potential risks include: (1) 
possible discomfort due to recollecting memories related to negative experiences with healthcare, (2) possible 
violation of confidentiality if someone were to intercept, see or overhear participant’s answers or the data are 
accessed by someone outside of the research team, (3) possible frustration if the participant experiences 
hardware or internet problems during participation, (4) possible frustration or fatigue if participant has a difficult 
time understanding specific questions or gets tired, (5) concern among professionals that their responses are 
wrong, and (6) the possibility that interview participants report abuse that is mandated as reportable under 
Oregon law.  We will emphasize to participants that data transmitted over email or instant messenger chat is 
not secure and carries a greater risk of loss of confidentiality than other modalities. Participants may choose 
not to participate in the study. 
2. Adequacy of Protection against Risks  
2a. Recruitment and Informed Consent  
1) Patients 
Each health system will identify all adult patients assigned to the participating practices who have had an ICD-
9 or 10 code consistent with ASD (299.00, 299.8, and 299.9 or F84.0, F84.5, and F84.9). Staff from the 
partnering health systems will send a letter (via mail or Epic MyChart) to potentially eligible patients explaining 
the study. The letter will include information for how to participate, as well as a post-card to indicate that a 
patient is not interested. Staff will then make recruitment telephone calls to patients who did not reply to the 
letter. Potentially interested participants will take a screening questionnaire to assess eligibility. As in our prior 
studies, the screening questionnaire can be done in person, over the telephone, or via the Internet, 
independently or via a supporter. We will confirm with the participant that the patient continues to receive 
primary care in the study clinic.  
Optimally, we would be able to assess the autistic adult’s decisional impairment and determine his or her ability 
to consent/assent.  However, doing so is not feasible in an online survey where we will have no contact with 
the autistic adult that the supporter is supporting. We will first ask if a patient is participating themselves 
(Patient Participant), if a supporter is helping a patient participate themselves (Supported Patient Participant), 
or if a supporter is participating on behalf of a patient who cannot participate by themselves, even with help 
from a supporter (Proxy Participant). 
1a. Patients who participate directly in the surveys (Patient Participants) 
Due to the low risk nature of the study and the constraints of Internet data collection, we will use a modified 
informed consent process. Similarly, since the level of risk and participation in our study is no greater than 
what an autistic adult would normally do if he or she is using the Internet independently, we feel that 
participants who are accessing the study independently would not be considered to have a decisional 
impairment for the level of risk involved in this study. Participants who are consenting online will be shown an 
on-line Information Sheet, which they can print out if desired. As we have done in prior studies we will work 
with community partners to create an Information Sheet that they feel is easy to comprehend.  After reading 
the Information Sheet, they will be asked to check a box if they agree to proceed. Because collecting 
signatures is not feasible in our online studies, will ask for a waiver for HIPPAA authorizations. Participants will 
also be given the opportunity to contact the researchers to ask any questions they may have.  
During all interactions with participants, we will emphasize that no one will be upset if they decide not to 
participate and that they should speak to anyone in their network that they would like to as they make a 
decision. Consented participants will receive a unique login and password to participate in the remainder of the 
study.  
1b. Patient who is participating with help from a supporter (Supported Patient Participant).  
We will describe what is needed for a participant to take part in the study and will ask the supporter if they feel 
they can provide enough support for a patient to make this type of decision and answer these types of 
questions. If they feel that they can, then we will use the patient version of the information sheet and the 
patient version of the surveys. We will instruct the support to relay the information to the patient and enter the 
patient’s answers into the online system. In this case, only the patient is a participant. If the supporter does not 

feel they can provide adequate support for the patient to participate themselves, then they will be treated as a 
proxy participant (as below.) 
1c. Supporter who is participating on behalf of a patient who cannot participate themselves (Proxy Participant).  
If a patient cannot participate themselves, even with help from a supporter, then we will assume that the 
patient has a decisional impairment. In this case, we will need to obtain study data from a supporter who has 
experience supporting the patient in healthcare settings. This person may or may not be the patient’s legally 
authorized representative (LAR). In cases where it is not the same person, then we will obtain consent both 
from the LAR (e.g. to allow us to use data from the patient’s medical record) and from the Supporter (since 
they will be taking part in the study themselves).   
2. PCPs and office staff 
Health systems will provide a list of primary care providers who work in each clinic, including contact 
information to be used to invite them to the survey. We will attempt to contact PCPs via email, telephone, fax, 
or in-person to complete the survey. The survey will begin with a brief statement explaining the study and 
stating that the research in voluntary.  
3. Qualitative interviews.  
We will purposefully sample patients and PCPs to invite to the interview study based on their survey data. 
Clinic champions from each clinic will help purposefully select which other employees to invite to the qualitative 
study. For those participating over the telephone, we will use a modified consent process, which involves the 
interviewer reading a script and answering any questions and the participant voicing his or her consent.  For 
those participating in an interview over email or IM, we will show participants an Information sheet and ask 
them to indicate their consent online. Those participating in person will sign written informed consent. 
2b. Protection against risk 
We will proactively take several steps to prevent risks and/or minimize the consequences of the risks identified 
above.  
First, although participants may be asked questions that remind them of negative experiences accessing 
healthcare, our experience is that participants actually derive benefit from sharing negative experiences 
through being able to relate their perspective and perhaps make sense out of the experience in a novel way. 
Moreover, participants may receive comfort that their negative experiences are being used to inform empirical-
based practices to improve healthcare for autistic adults. All researchers will also be trained in providing 
emotional comfort to participants who become upset during qualitative interviews.  
Second, though we cannot eliminate the risk of violations of confidentiality, we are taking a variety of steps as 
is appropriate for the nature of participation in each study.  
For individuals participating remotely via Internet survey, text-based chat, email, or telephone, we will 
encourage participants to engage in the research from a location where they feel adequately protected from 
invasions of privacy. For those participants who participate in person, we will identify places in our offices 
where they can complete the research measures in private. For individuals who participate via telephone, we 
will ask participants whether they are in a place where they feel comfortable responding to our questions.  
We will also take steps to handle the data in ways that will minimize breaches of confidentiality. Participants 
will take baseline, AHAT, and 6-month follow-up surveys online via our ACASI system. Confidentiality will be 
maintained using the following safeguards: 1) All data provided will be stored on a password protected 
computer and only the investigators and other key personnel will have access to the data; 2) Data collected via 
ACASI is collected and stored behind a firewall.  Research personnel need a password to access that site. 3) 
Project staff will directly download information from the ACASI site to a password protected account. 4) Copies 
of AHAT reports will need to remain identified. However, databases used for analysis purposes will be stripped 
of identifying information and coded with a unique identifier. 5) Contact information will be stored separately 
from survey data.  6) PHI will only be stored on OHSU or Kaiser computers. 7) No identifying information will 
be used in publications or other reports.  
For those individuals participating in interviews via email, text-based chat, or telephone, we will clearly state in 
the informed consent materials that email, text-based chat, and telephone communications are not secure. 
That is, we cannot guarantee that participants’ responses will not be intercepted, overheard or accessed 

without participants’ permission. We will encourage participants to consider other options for participation or to 
not participate at all if they do not feel comfortable with the level of risk inherent in using these media. Project 
staff will promptly compile these communications, strip all email and text-based chat data of identifying 
information and not make these data available to other members of the team until we have done so. We will 
strip identifying information from transcripts of telephone or in-person interviews.  
Third, we will prepare individuals for the possibility that they may experience hardware or internet problems as 
they participate in the research and encourage them to participate in the study where they have a reliable 
computer and Internet connection. 
Fourth, we will work intensively with members of our research team, including the community partners, to 
create questions that are understood. We will inform participants during consent procedures that they may take 
breaks as needed.  
Fifth, to avoid coercion, we will emphasize participants’ rights as a research participant, including their right to 
decline to participate. All of our research materials and interactions with participants will include important 
information about the study and their rights. We will not inform employers, supervisors, or others whether an 
individual participated.  
Sixth, questions ask participants about their beliefs and experiences - questions to which there are no right or 
wrong answers. We emphasize to all participants that we are interested in hearing their opinions and 
experiences.  
Lastly, although participants will not be directly asked questions that might lead them to report abuse, there is a 
small chance that participants may disclose information about abuse during qualitative interviews. Oregon law 
requires that researchers report abuse of children, elders, and individuals with developmental disabilities.  We 
will clearly state in all consent materials that the researchers must report such instances of abuse. We will 
describe to participants the type of information that would lead to a mandatory report and describe to them 
what would happen when we were required to do that.  
 
3. Potential Benefits of the Proposed Research to Participants and Others  
We do not anticipate any guaranteed direct benefit to participants. However, we do believe that participants 
may derive substantial benefit from the research by having the opportunity to share their experience and 
opinion. Some participant groups included herein have few opportunities to make such a contribution and have 
research be inclusive of their perspectives. We believe that providing the opportunity to contribute valuable 
information to science will be positively experienced by participants. There is the possibility that participants 
may gain important insights and knowledge as part of their participation. It is also possible that participants in 
the intervention clinics may benefit from using the tools with their primary care providers or patients. 
We do anticipate several indirect benefits. We believe the instruments and tools developed herein and the 
findings will provide empirically-based mechanisms that may improve autistic adults’ healthcare. 
 
4. Importance of the Knowledge Gained  
The AASPIRE Healthcare Toolkit is a scalable, sustainable, low-intensity intervention that has the potential to 
greatly improve healthcare services for autistic adults. This project will provide critically important data to 
inform a larger hybrid effectiveness/implementation trial testing the AASPIRE Healthcare Toolkit in diverse 
health systems. Ultimately, the project can impact how care is given to this growing population that 
experiences significant healthcare disparities and has large unmet healthcare needs. 
 
5. Data Safety and Monitoring Plan 
Data and Safety Monitoring Plan 
This non-randomized, controlled pilot intervention assesses the potential effectiveness of an online toolkit and 
its integration into primary care practices. It does not involve pharmaceuticals or medical devices. Data 
collection relies on administrative data, self-report data, and interview-based data; no invasive testing or 
procedures are involved. The risks related to participation are likely much lower than those of a trial involving 

pharmaceuticals, medical devices, or somatic interventions or procedures. Nonetheless, we will very carefully 
monitor the progress of the study and any potential risks or adverse events. 
Our data and safety monitoring plan includes real-time adverse event (AE) monitoring by Dr. Nicolaidis as well 
as AE monitoring by all staff working on the project. AEs will be identified by spontaneous reports to any study 
staff member, and all staff will be trained to be receptive to subject complaints and concerns about the study. 
Any complaints about the research process will be considered AEs. Further, any breach of confidentiality will 
be considered an AE.  
We will classify an AE as: 
0 - No AE 
1 - Mild - no treatment needed 
2 - Moderate - resolved with treatment 
3 - Severe - inability to carry on normal activities, required professional medical attention 
4 - Life-threatening or disabling 
5 - Fatal 
The PI will review all adverse events in real-time to determine if they meet the definition of an Unanticipated 
Problem (UP). The PSU IRB defines UPs as events that are not expected given the nature of the research 
procedures and the subject population being studied and suggest that the research places subjects or others 
at a greater harm or discomfort related to the research than was previously known or recognized. All 
Unanticipated Problems, including AEs that meet the definition of a UP as determined by Dr. Nicolaidis, 
including breaches of confidentiality and subject complaints, will be reported to the IRB as soon as possible 
and within the following time frames: 
• 
Deaths and potentially life-threatening events within 7 days of the PI learning of the event days.  
• 
All other unanticipated problems will be reported within 15 days of the PI learning of the event. 
 
If any AEs or UPs requires a change to the protocol or consent form (as determined by the PI or IRB) the PI 
will submit the revised protocol for review and approval by the PSU IRB promptly. A brief summary of UPs and 
all adverse events will be submitted to the IRB at the time of annual continuing review. Adverse events, 
enrollment, and data collection problems will be reviewed every 3 months by the PI. In addition, dropouts and 
AEs will be reviewed for patterns indicating problems with the study procedures. Any protocol deviation 
identified during the quarterly reviews will be reported per PSU IRB policy. 
 
 

References 
 
1. 
Baio J. Prevalence of Autism Spectrum Disorders: Autism and Developmental Disabilities Monitoring Network, 
14 Sites, United States, 2008. Morbidity and Mortality Weekly Report. Surveillance Summaries. Volume 61, 
Number 3. Centers for Disease Control and Prevention. 2012. 
2. 
Newschaffer CJ, Croen LA, Daniels J, et al. The Epidemiology of Autism Spectrum Disorders. Annual Review of 
Public Health. 2007;28(1):235-258. 
3. 
Fombonne E. The Prevalence of Autism. JAMA.289(1):87-89. 
4. 
Lorna W, David P. The epidemiology of autistic spectrum disorders: is the prevalence rising? Mental Retardation 
and Developmental Disabilities Research Reviews. 2002;8(3):151-161. 
5. 
Brugha T MS, Meltzer H, Smith J, Scott FJ, Purdon S, Harris J, Bankart J. Autism Spectrum Disorders in adults 
living in households throughout England: Report from the Adult Psychiatric Morbidity Survey 2007. In: 
Information Centre for Health and Social Care; 2009. 
6. 
Nicolaidis C, Raymaker D, McDonald K, et al. Comparison of healthcare experiences in autistic and non-autistic 
adults: A cross-sectional online survey facilitated by an academic-community partnership. Journal of General 
Internal Medicine. 2013;28(6):761-769. 
7. 
Raymaker D, Nicolaidis C, McDonald K, et al. Barriers to Healthcare: Instrument Development and Comparison 
Between Adults on the Autism Spectrum and Adults With and Without Other Disabilities. Under review. 
8. 
Vohra R, Madhavan S, Sambamoorthi U. Emergency Department Use Among Adults with Autism Spectrum 
Disorders (ASD). Journal of autism and developmental disorders. 2016:1-14. 
9. 
Nicolaidis C, Raymaker DM, Ashkenazy E, et al. “Respect the way I need to communicate with you”: Healthcare 
experiences of adults on the autism spectrum. Autism. 2015;19(7):824-831. 
10. 
Nichols AD, Ward RL, Freedman RI. Left Out in the Cold:  Health care experiences of adults with intellectual and 
developmental disabilities in Massachusetts. Boston, MA: Arc of Massachusetts; December 2008. 
11. 
Zerbo O, Massolo ML, Qian Y, Croen LA. A Study of Physician Knowledge and Experience with Autism in Adults in 
a Large Integrated Healthcare System. Journal of autism and developmental disorders. 2015:1-13. 
12. 
Accredidation Council for Graduate Medical Education. ACGME Program Requirements for Graduate Medical 
Education in Pediatrics. http://www.acgme.org/acWebsite/RRC_320/320_prIndex.asp. Published 2007. 
Accessed May 8, 2009. 
13. 
Accredidation Council for Graduate Medical Education. ACGME Program Requirements for Residency Education 
in Internal Medicine. http://www.acgme.org/acWebsite/RRC_140/140_prIndex.asp. Published 2007. Accessed 
May 9, 2009. 
14. 
Accredidation Council for Graduate Medical Education. ACGME Program Requirements for Graduate Medical 
Education in Family Medicine. http://www.acgme.org/acWebsite/RRC_120/120_prIndex.asp. Published 2007. 
Accessed May 9, 2009. 
15. 
Zerbo O, Massolo ML, Qian Y, Croen LA. A Study of Physician Knowledge and Experience with Autism in Adults in 
a Large Integrated Healthcare System. Journal of autism and developmental disorders. 2015;45(12):4002-4014. 
16. 
Bruder MB, Kerins G, Mazzarella C, Sims J, Stein N. Brief report: the medical care of adults with autism spectrum 
disorders: identifying the needs. Journal of autism and developmental disorders. 2012;42(11):2498-2504. 
17. 
Kuhlthau KA, Warfield ME, Hurson J, Delahaye J, Crossman MK. Pediatric provider’s perspectives on the 
transition to adult health care for youth with autism spectrum disorder: Current strategies and promising new 
directions. Autism. 2014:1362361313518125. 
18. 
Cooley WC, Sagerman PJ. Supporting the health care transition from adolescence to adulthood in the medical 
home. Pediatrics. 2011;128(1):182-200. 
19. 
Bitton A, Martin C, Landon BE. A nationwide survey of patient centered medical home demonstration projects. 
Journal of General Internal Medicine. 2010;25(6):584-592. 
20. 
Nicolaidis C, Raymaker D, McDonald K, et al. The Development and Evaluation of an Online Healthcare Toolkit 
for Autistic Adults and their Primary Care Providers. Journal of General Internal Medicine. Under review. 
21. 
Curran GM, Bauer M, Mittman B, Pyne JM, Stetler C. Effectiveness-implementation hybrid designs: combining 
elements of clinical effectiveness and implementation research to enhance public health impact. Medical care. 
2012;50(3):217. 

22. 
(IACC) IACC. IACC Strategic Plan for Autism Spectrum Disorder (ASD) Research —2013 Update. . U.S. Department 
of Health and Human Services Interagency Autism Coordinating Committee http://iacc.hhs.gov/strategic-
plan/2013/index.shtml. Published 2014. Accessed2016. 
23. 
Smith J. Do We Get Medical Care. NTs Are Weird.  An Autistic's View of the World Web site. 
http://thiswayoflife.org/blog/?p=270. Published 2007. Accessed April 27, 2009, . 
24. 
Aspitude! World Autism Interviews: Amanda Baggs/Access to Quality Healthcare in an Autistic World. 
http://aspitude.blogspot.com/2010/01/world-autism-interviews-amanda.html. Published 2009. 
Accessed02/15/2010. 
25. 
The ARC: Public Policy -- Health Care. http://www.thearc.org/NetCommunity/Page.aspx?pid=370. Accessed 
02/15/2010. 
26. 
Nicolaidis C, Kripke CC, Raymaker D. Primary care for adults on the autism spectrum. Medical Clinics of North 
America. 2014;98(5):1169-1191. 
27. 
Croen LA, Zerbo O, Qian Y, et al. The health status of adults on the autism spectrum. Autism. 
2015:1362361315577517. 
28. 
Viswanathan M, Ammerman A, Eng E, et al. Community-based Participatory Research: Assessing the Evidence. 
Rockville, MD: Agency for Healthcare Research and Quality July 2004. Evidence Report / Technology Assessment 
Number 99. 
29. 
Balcazar FE, Taylor R, & Kielhofner GW. Participatory Action Research (PAR): General principles and a case study 
with Chronic Fatigue Syndrome. In: L. Jason L, Keys CBS-B, Y., Taylor R, Davis M, Durlag J, Isenberg D, eds. 
Community Research: Theories and Methods in Action. Washington, DC: American Psychological Association; 
2004. 
30. 
Brugge D, Kapunan P, Babcock-Dunning L, et al. Developing Methods to Compare Low-Education Community-
Based and University-Based Survey Teams. Health Promotion Practice. 2009:15-24. 
31. 
Israel BA, Schulz AJ, Parker EA, Becker AB. Review of community-based research: assessing partnership 
approaches to improve public health. Annual Review Of Public Health. 1998;19:173-202. 
32. 
Israel BA, Schulz AJ, Parker EP, Becker AB. Community-based participatory research: policy recommendations for 
promoting a partnership approach in health research. Education for Health: Change in Learning & Practice. 
2001;14(2):182-197. 
33. 
Trickett EJ, Espino SLR. Collaboration and Social Inquiry: Multiple Meanings of a Construct and Its Role in 
Creating Useful and Valid Knowledge. American Journal of Community Psychology. 2004;34(1):1-69. 
34. 
Nicolaidis C, Raymaker D, McDonald K, et al. Collaboration strategies in non-traditional CBPR partnerships: 
lessons from an academic-community partnership with autistic self-advocates. Progress in Community Health 
Partnerships: Research, Education, and Action. 2011;011:5(2):143-150. 
35. 
Jivraj J, Sacrey L-A, Newton A, Nicholas D, Zwaigenbaum L. Assessing the influence of researcher–partner 
involvement on the process and outcomes of participatory research in autism spectrum disorder and 
neurodevelopmental disorders: A scoping review. Autism. 2014;18(7):782-793. 
36. 
Wright CA, Wright SD, Diener ML, Eaton J. Autism spectrum disorder and the applied collaborative approach: a 
review of community based participatory research and participatory action research. Journal of Autism. 
2014;1(1):1. 
37. 
Pellicano E, Dinsmore A, Charman T. Views on Researcher-Community Engagement in Autism Research in the 
United Kingdom: A Mixed-Methods Study. 2014. 
38. 
Nicolaidis C, Raymaker, D.M., Katz, M., Oshwald, M., Goe, R., Leotti, S., Grantham, L., Plourde, E., Salomon, J. 
Hughes, L., Powers, L. Participatory research to adapt measures of health and interpersonal violence for use by 
people with developmental disabilities. Progress in Community Health Partnerships: Research, Education, and 
Action. 2015;9(2):in press. 
39. 
Krahn GL, Hammond L, Turner A. A cascade of disparities: Health and health care access for people with 
intellectual disabilities. Mental Retardation & Developmental Disabilities Research Reviews. 2006;12(1):70-82. 
40. 
Raymaker D. Reflections of a community based participatory researcher from the intersection of disability 
advocacy, engineering, and the academy. Action Research. In press. 
41. 
Jones L, Wells K. Strategies for academic and clinician engagement in community-participatory partnered 
research.[see comment]. JAMA. 2007;297(4):407-410. 
42. 
Argyris C. Double loop learning in organizations. Harvard business review. 1977;55(5):115-125. 

43. 
Raymaker D, Nicolaidis C. Participatory research with autistic communities: Shifting the system (Ch 7). In: 
Davidson J, Orsini M, eds. Worlds of Autism. Minneapolis: University of Minnesota Press; 2013:169-188. 
44. 
Raymaker D, Nicolaidis C, Boisclair WC, et al. Community Based Participatory Research Methods in Co-
Developing an Accessible Web Site for End Users on the Autism Spectrum. Under review. 
45. 
Stetler CB, Legro MW, Wallace CM, et al. The role of formative evaluation in implementation research and the 
QUERI experience. Journal of General Internal Medicine. 2006;21(S2):S1-S8. 
46. 
Oschwald M, Leotti S, Raymaker DM, et al. Development of an Audio-Computer Assisted Self-Interview to 
investigate violence and health in the lives of people with developmental disabilities. Disabil Health J. 
2014;7(3):292-301. 
47. 
Cantor D, Covell, J., Davis, T., Park, I., & Rizzo, L. . Health Information National Trends Survey (HINTS). 
http://hints.cancer.gov/docs/HINTS2007FinalReport.pdf. Published 2009. Accessed October 10, 2012. 
48. 
Hong T. Internet Health Information in the Patient-Provider Dialogue. CyberPsychology & Behavior. 2008(5):587-
589. 
49. 
Marks R, Ok H, Joung H, Allegrante JP. Perceptions about collaborative decisions: perceived provider 
effectiveness among 2003 and 2007 Health Information National Trends Survey (HINTS) respondents. Journal of 
Health Communication. 2010;15 Suppl 3:135-146. 
50. 
Ok H, Marks R, Allegrante JP. Perceptions of health care provider communication activity among American 
cancer survivors and Adults Without Cancer Histories: an analysis of the 2003 Health Information Trends Survey 
(HINTS) Data. Journal of Health Communication. 2008;13(7):637-653. 
51. 
Smith SG, Wolf MS, von Wagner C. Socioeconomic status, statistical confidence, and patient-provider 
communication: an analysis of the Health Information National Trends Survey (HINTS 2007). Journal of Health 
Communication.15 Suppl 3:169-185. 
52. 
Lorig KR, Sobel DS, Ritter PL, Laurent D, Hobbs M. Effect of a self-management program on patients with chronic 
disease. Effective Clinical Practice. 2001;4(6):256-262. 
53. 
Lorig K, Stewart A, Ritter P, Gonzalez V, Laurent D, Lynch J. Outcome Measures for Health Education and Other 
Health Care Interventions. Thousand Oaks, CA: Sage Publications; 1996. 
54. 
Blackwell D, Gentleman, J., Martin, M., Ng, E.,Sanmartin, C., Simile, C. Joint Canada/United States Survey of 
Health: Findings and Public-use Microdata File. 
http://www.statcan.gc.ca/pub/82m0022x/2003001/pdf/4228656-eng.pdf. Published 2004. Accessed 
02/25/2009. 
55. 
Sanmartin C, Berthelot J-M, Ng E, et al. Comparing Health And Health Care Use In Canada And The United States. 
Health Aff. 2006;25(4):1133-1142. 
56. 
Pleis JR, Lucas JW. Summary health statistics for U.S. adults: National Health Interview Survey, 2007. Vital & 
Health Statistics - Series 10: Data From the National Health Survey. 2009(240):1-159. 
57. 
CDC. National Health Interview Survey (NHIS) -- Adult Access to Health Care & Utilization. 
http://www.ihis.us/ihis/resources/surveys_pdf/survey_form_ih2007_fam.pdf. Published 2007. Accessed 
October 10, 2012. 
58. 
Creswell JW, Clark VLP. Collecting data in mixed methods research. In: Creswell JW, Clark VLP, eds. Designing 
and conducting mixed methods research. Thousand Oaks, CA: Sage Publications; 2011:171-202. 
59. 
Braun V, Clarke V. Using thematic analysis in psychology. Qualitative research in psychology. 2006;3:77-101.