Highly favorable results from our newest research study!

Key Points

  • “The rate of autism spectrum disorder (ASD) diagnosis continues to increase in the United States, with a recent estimate indicating 1 in 59 children receive the diagnosis (Baio et al., 2018). This increase in prevalence has not been matched with increases in the speed of the clinical diagnosis process, and families often wait from 1 to 2 years for an evaluation after reporting concerns to their pediatrician (e.g., Austin, et al., 2016). “
  • “The current diagnostic assessment process overburdens families and fails to provide children with ready opportunities to improve their outcomes. Moreover, the burden of waiting impacts familial quality of life and also decreases satisfaction with the healthcare process. When told to “wait and see,” families report frustration and decreased satisfaction with the current process. The risk of mental health problems for caregivers increases, and the family’s quality of life can decrease due to challenges associated with problem behaviors and limited social outlets (e.g., McMorris et al., 2013).”
  • “Factoring in the entire clinical ASD evaluation process, from initial consultation to testing to report writing, clinicians work on a particular case over an average of 152 days (Ahlers et al., 2019).”
  • “The development of new screeners continues, although many recent additions fail to address children over the age of 3 years.”
  • “The introduction of new screeners, however, fails to address the need for enhancements in clinical diagnostic methodology. Traditional methods lack standardization, require 5 to 8 various screeners, tests, and measures, and can take months to collect all the data that is needed (e.g., Ahlers et al., 2019).”
  • “As the current process is failing to accommodate the increase in prevalence rate, the development of a new dynamic diagnostic process that better matches the need has been required. One such dynamic process, the CLEAR Autism Diagnostic Evaluation (CADE) model, was designed to improve, shorten, and standardize the clinical ASD evaluation process. The CADE model is a dynamic methodology to reduce the duration of the evaluation process while maintaining accuracy and providing support for clinical judgement.”
  • “The purpose of the present investigation was to determine the validity of the CADE scale in diagnostic accuracy and in comparison with other measures currently utilized in the ASD diagnostic process.”
  • “Research Questions

    Question #1: Can a questionnaire instrument be developed that identifies ASD consistently with traditional testing methods? (over 80% consistent with scores on the ADOS (Gotham et al., 2007))

    Question #2: Can a scale be developed that predicts ASD accurately? (over 90% consistent with expert clinical diagnostic decisions)”

  • “The CADE scale was evaluated for reliability and validity using a dataset of 191 cases. The method of data collection is described below. Reliability was assessed using Cronbach’s alpha. Convergent and discriminant validity were assessed using correlations with current testing methods and diagnostic findings. Logistic regression was used to determine the predictability of autism diagnosis with the inclusion of various subsets of items. “
  • Question 1: “Yes, this hypothesis was supported in the study. Using correlations between CADE scores and ADOS scores (the current gold standard instrument), the researchers found that this scale is consistent with current methods. The scale was found to be 98% consistent with ADOS scores, which is well over the hypothesized 80% figure. For convergent validity, correlations over .7 with an established measure are considered acceptable (Terwee et al., 2007). “
  • Question 2: “Yes, the research supports the hypothesis that a scale can accurately predict autism as compared to the diagnostic decisions of independent subject matter experts. The diagnosis predicted by CADE was over 96% consistent with expert diagnosis, which is well over the hypothesized 90% number. “
  • “This research is particularly promising because this measure is faster than traditional approaches, which may potentially reduce waitlists, allow for earlier detection and increase the accuracy of diagnosis for patients. This novel instrument could be a meaningful contribution to the families who are facing a diagnosis of ASD and in need of appropriate therapies to enable better outcomes for their children.”