Assessing LEND Trainees' Knowledge of Autism Spectrum Disorder (ASD) Tybytha Ryan1,5, Caitlin Winters2,3, Anna Merrill1, & Maryellen Brunson McClain2,4 1 = Riley Child Development Center, Indianapolis, 2 = Utah Regional LEND, 3 = University of Utah, 4 = Utah State University, 5 = Indiana University Introduction Participant Demographics Results The prevalence of ASD is currently reported as affecting 1 in 68 children (Centers for Disease Control & Prevention, 2016). Due to the high rate of ASD diagnoses and high likelihood of complex, co-occurring medical and mental health problems, an interdisciplinary team is commonly established in order to provide a comprehensive level of care. This project utilizes the Autism Spectrum Knowledge Scale (ASKS; McClain, Harris, & Haverkamp, in review) to investigate the current levels of ASD knowledge across interdisciplinary LEND trainees nationwide. The measure is composed of 33 binary questions (true/false) that examine five areas of ASD knowledge: (1) etiology/prevalence, (2) symptoms/associated behaviors, (3) assessment/diagnosis, (4) treatment, (5) outcomes/prognosis. The overall score upon completion of the ASKS is based on how many questions were answered correctly. Specifically, the current study examines the following research questions: What are the current levels of ASD knowledge across LEND trainees? What are some predictors of ASD knowledge across disciplines?  Using a combination of logistic regression and multivariate analyses, our data showed discipline-specific knowledge of ASD and predictions of ASD knowledge among trainees. Post Hoc analyses revealed clinical and specialized disciplines (e.g. psychology, Speech Language Pathology, Special Education, etc.) showed greater knowledge of ASD compared to non-clinical and specialized disciplines (e.g. family advocates, healthcare administrators, etc.). When clustering disciplines, participants seeking higher and more specialized training (e.g. specialists, doctorate degrees, etc.) exhibited slightly higher overall ASD knowledge compared to participants seeking other degrees and less specialized training (e.g. bachelors degree). Give out sample size, we conclude that knowledge of ASD is highly drive by training exposure that is clinically relevant. Participants were LEND trainees (N = 169) that represented a variety of professional disciplines of individuals that work with ASD. Gender: Our sample for the respondents were primarily females (89.9%) with a small portion of males (9.6%), and the remaining preferred not to respond (.5%). Age: All participants were at least 18 years or older with the majority of participants between 25-34 years (49%). The remaining participants ages included: 18-24 (30%), 35-44 (10%), and 45-54 (12%). Race/Ethnicity: The majority of participants identified their race/ethnicity as White (81%). The remaining participants identified their race/ethnicity as: Latino/a (9%), Asian (5%), Black or African American (4%), Multiracial (1%), or Other (< 1%). LEND Trainees’ Current Knowledge of ASD & Predictors of ASD Knowledge LEND Trainee Disciplines Methods LEND sites’ training directors were contacted via email (N = 29; response rate = 56%). Survey emailed prior to each LEND site’s start date (first survey sent June 30 and last sent September 13). Survey included: demographics, experiences and confidence with ASD, and the ASKS. Compensation: entered for random drawing for a $100 Amazon.com gift card. Conclusion Our preliminary findings showed predictors of ASD knowledge among diverse disciplines to include educational status, discipline, and perceived knowledge of ASD. In the future, we plan to diversify our sample and examine other predictor variables of ASD Knowledge across various trainees. Additionally, we aim to utilize our comprehensive findings to validate a broad measure that professionals can use to assess ASD knowledge across settings and professionals. *Other disciplines included public health, community Fellow, ABA, Neuroscience, Legal, and others. References: Centers for Disease Control and Prevention. (2016). Autism spectrum disorder data and statistics. Retrieved from https://www.cdc.gov/ncbddd/autism/data.html. McClain, M.B., Harris, B., & Haverkamp, C.R. (2017). Development and Validation of the Autism Spectrum Knowledge Scale: Preliminary Analyses, in review.