Whitney Trapp, MS, BCBA, LBA (NE)
University of Nebraska Medical Center, Munroe-Meyer Institute

ASAT's Science CornerResearch has a direct influence on our daily lives. For instance, when you enter your vehicle, you (hopefully) secure your seatbelt before operating the vehicle. A few decades ago, this was not possible because seatbelts were not a vehicle manufacturing requirement in the United States. It was only after the dissemination of seatbelt safety research that vehicle manufacturers were mandated to include seatbelts in all vehicles. However, this research was conducted with crash dummies modeled after adult males around 5’9” and 170 lbs. Findings from seatbelt safety research have been broadly applied to persons of all genders and sizes, but the body composition of the crash dummies was not representative of the public majority. The exclusion of women and individuals of different sizes from this research has led to inequitable safety benefits. Namely, even when wearing seatbelts, females are 73% more likely to be injured in a crash compared to males (Forman et al., 2019).

This example showcases the importance of collecting and reporting participant characteristics in research as part of a broader effort to demonstrate external validity (Barall, 2025; Frampton, 2025). Participant characteristics could include the participant’s age, education level, gender and/or sex, race/ethnicity, socioeconomic status, medical diagnosis, level of functioning, test scores, and language (Jones et al., 2020). Each of these characteristics is simply an umbrella term; the definition for each term includes additional variables to consider. For example, language could be related to the participant’s native language, the participant’s primary language, or the primary language spoken in the participant’s home. As another example, race and ethnicity could be related to the participant’s national origin, sociocultural group identity, or race. Identifying and clearly stating the characteristics of each participant included in a research study helps the scientific community recognize gaps in the literature and identify directions for future research. It also allows consumers of the research to identify with whom the intervention was successful (responders) and for whom the intervention was not successful (non-responders). When considering interventions for a loved one with autism, it is important to find alignment between the characteristics of your loved one and the responders in the study. This would be a minimum indication that the intervention may be appropriate.

Participant Characteristics in Autism Intervention Studies

Evidence-based practices (EBPs) are interventions shown to be effective with a large number of participants. However, the volume of participants does not immediately translate to diversity in participants. In their review of EBPs for children and adolescents with autism, Steinbrenner et al. (2022) found that participants’ characteristics, such as race and ethnicity, were underreported. In articles that did include race and ethnicity, the majority of participants are reported as White across all EBPs.

Diversity in participants is necessary to identify boundary conditions and variables that may influence the success of an intervention. For example, Early Intensive Behavioral Intervention (EIBI) has long been promoted as a leading early intervention approach for young children with autism (Eldevik et al., 2009; Smith et al., 2021). Even with a compelling evidence-base, systematic reviews suggest that there are still gaps in the research regarding the effectiveness of EIBI across the full spectrum of autistic children and their families (Howlin et al., 2009; Spreckley & Boyd, 2009).

EIBI typically involves 20 to 40 hours of therapy each week (Reichow et al., 2018; Spreckley & Boyd, 2009); however, without information about factors like socioeconomic status, we don’t know which families can realistically access this level of support, which families may be more likely to withdraw prematurely, and which families may be left out altogether. Caregiver participation is also considered a key part of EIBI since it helps children use their new skills at home and in the community (Blocher-Rubin & Krabill, 2017). Yet, without data on how caregiver involvement varies across families, it’s difficult to understand who benefits most from the intervention. Another challenge is that most large EIBI studies report only basic participant characteristics, such as age and autism diagnosis (Reichow et al., 2018). Rarely included is information about co-occurring conditions, cultural background, or other differences that can influence how a child responds to intervention. As a result, guidelines for children who do not make progress with standard EIBI have yet to be fully realized (Reichow et al., 2018).

Much like assuming a seat belt works the same for everyone, a “cookie cutter” approach to EIBI may not be the best fit for every autistic child. The effectiveness of these interventions can be hampered by disproportionate representation of participants with a particular set of characteristics within the supporting research. Collecting more thorough information about participant differences could help identify which children are likely to benefit from more traditional EIBI models (e.g., 20-40 hours per week) and for whom modifications would be appropriate. Investigations of modified approaches to EIBI could deepen the research support and lead to greater benefits for more families.

Steps for Caregivers

When exploring an intervention for a loved one with autism and assessing its appropriateness, caregivers should consider reviewing the foundational components of the intervention and its evidence base. Science Corner has published several articles that include questions caregivers may ask when reviewing treatment options, including Mruzek (2014) and Celiberti et al. (2003). The National Autism Center also provides a robust parent guide library with resources related to identifying EBPs. Within the most recently published manual for parents of children with profound autism are steps for how to identify whether an intervention is working for your child (National Autism Center at May Institute, 2025).

When sifting through the various EBPs available, caregivers should also consider reviewing the inclusion and exclusion criteria listed within the research study. The inclusion and exclusion criteria will provide the reader with information about the characteristics the researchers sought to include, and thus, which characteristics are likely and unlikely to be represented in the research. If your child’s characteristics differ significantly from those described in the research, this should prompt a discussion with your provider about potential adjustments, including referrals or consultation to better address your child’s unique needs. Alternatively, it may be the case that other interventions that align with your child’s characteristics may be worth exploring.

Conclusion

As a caregiver, teacher, or clinician, when consuming the literature to identify interventions that you would consider, you should investigate whether the participant characteristics listed resemble those of your autistic loved one. Along that same line, you may want to highlight who is missing, is it a particular age range, level of functioning (e.g., language ability), or racial group? By identifying who is missing, we can better inform research practices by diligently advocating for the inclusion of said group. This will result in more equitable outcomes for all families. Though this type of advocacy takes time, there is hope. Circling back to the analogy offered at the beginning, if the She DRIVES Act is passed, gender disparities in vehicular safety tests will be addressed through the inclusion of crash test dummies modeled after females (She DRIVES Act, 2025). Research has the power to improve our lives, but we must take thoughtful steps to ensure those benefits are accessed by all members of our community.

References

Barall, R. J. (2026). Science Corner: Who is missing from autism research – and why it matters. Science in Autism Treatment, 23(1).

Blocher-Rubin, A., & Krabill, P. (2017). Initial development of the early intensive behavioral intervention parental self‐efficacy scale: A pilot study. Autism Research and Treatment, 2017, 9512180. https://doi.org/10.1155/2017/9512180

Celiberti, D., Buchanan, S., Bleecker, F., Kress, D., & Rosenfeld, D. (2003). The road less traveled: Charting a clearer course in autism treatment. Science in Autism Treatment, 20(1).

Eldevik, S., Hastings, R. P., Hughes, J. C., Jahr, E., Eikeseth, S., & Cross, S. (2009). Meta-analysis of early intensive behavioral intervention for children with autism. Journal of Clinical Child & Adolescent Psychology, 38(3), 439-450. https://doi.org/10.1080/15374410902851739

Forman, J., Poplin, G. S., Shaw, C. G., McMurry, T. L., Schmidt, K., Ash, J., & Sunnevang, C. (2019). Automobile injury trends in the contemporary fleet: Belted occupants in frontal collisions. Traffic Injury Prevention, 20(6), 607-612. https://doi.org/10.1080/15389588.2019.1630825

Frampton, S. (2025). Science Corner: An overview of external validity. Science in Autism Treatment, 22(7).

Howlin, P., Magiati, I., & Charman, T. (2009). Systematic review of early intensive behavioral interventions for children with autism. American Journal on Intellectual and Developmental Disabilities, 114(1), 23-41. https://doi.org/10.1352/2009.114:23-41

Jones, S. H., St. Peter, C. C., & Ruckle, M. M. (2020). Reporting of demographic variables in the Journal of Applied Behavior Analysis. Journal of Applied Behavior Analysis, 53(3), 1304-1315. https://doi.org/10.1002/jaba.722

Mruzek, D. (2013). Questions to ask marketers of autism interventions. Science in Autism Treatment, 10(4), 12-13.

National Autism Center at May Institute. (2025). Profound Autism: A parent’s guide. National Autism Center at May Institute. https://nationalautismcenter.org/resource-library/parent-guide/

Reichow B., Hume K., Barton, E. E., & Boyd, B. A. (2018). Early intensive behavioral intervention (EIBI) for young children with autism spectrum disorders (ASD). Cochrane Database of Systematic Reviews, 5, 1465-1858. http://doi.org/10.1002/14651858.CD009260.pub3

She DRIVES Act, S. 161, 119th Cong. (2025). https://www.congress.gov/bill/119th-congress/senate-bill/161

Smith, D. P., Hayward, D. W., Gale, C. M., Eikeseth, S., & Klintwall, L. (2021). Treatment gains from early and intensive behavioral intervention (EIBI) are maintained 10 years later. Behavior Modification, 45(4), 581-601. https://doi.org/10.1177/0145445519882895

Spreckley, M., & Boyd, R. (2009). Efficacy of applied behavioral intervention in preschool children with autism for improving cognitive, language, and adaptive behavior: A systematic review and meta-analysis. The Journal of Pediatrics, 154(3), 338-344. https://doi.org/10.1016/j.jpeds.2008.09.012

Steinbrenner, J. R., McIntyre, N., Rentschler, L. F., Pearson, J. N., Luelmo, P., Jaramillo, M. E., Boy, B. A., Wong, C., Nowell, S.W., Odom, S.L., & Hume, K. A. (2022). Patterns in reporting and participant inclusion related to race and ethnicity in autism intervention literature: Data from a large-scale systematic review of evidence-based practices. Autism, 26(8), 2026-2040. https://doi.org/10.1177/1362361321107259

Reference for this Article:

Trapp, W. (2026). Science Corner: The importance of participant characteristics when determining the external validity of a research line. Science in Autism Treatment, 23(2).

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