The primary intended use of the Conners 4–ADHD Index is to effectively distinguish between individuals with and without a diagnosis of ADHD (i.e., the General Population and ADHD groups). To validate that the Conners 4–ADHD Index is effective at this classification activity, scores on the Conners 4–ADHD Index were compared between individuals from the general population and individuals with all presentations of ADHD (i.e., ADHD Inattentive, ADHD Hyperactive/Impulsive, and ADHD Combined). A description of the Total Sample, which contains the General Population group used here can be found in Table 6.5 and Table 6.6 in the Standardization Phase section of chapter 6, Development, and details about the ADHD Reference Samples can be found in Tables 7.30 to 7.35 of chapter 7, Standardization.

Conners 4–ADHD Index probability scores were computed based on raw scores and classified into one of six score categories, ranging from Very Low to Very High (see Table 4.6 in chapter 4, Interpretation). The percentage of each sample with Conners 4–ADHD Index probability scores in each score category was compared, with results presented in Table 12.24. Individuals from the General Population group (i.e., without any clinical diagnosis) overwhelmingly received Conners 4–ADHD Index probability scores between 1% and 39%, falling in the Very Low and Low ranges (85.7% for Parent, 72.0% for Teacher, 70.7% for Self-Report). Conversely, and as expected, individuals diagnosed with ADHD were much more likely to have Conners 4–ADHD Index probability scores in the Moderate, High, and Very High ranges (i.e., probability scores greater than 60%; 82.8% for Parent, 68.3% for Teacher, 65.9% for Self-Report). Although there is a gradient of possible scores for both groups, it is clear from the skewed distribution of scores shown in Table 12.24 that the probability score captures the increased likelihood of high scores reflecting ratings from individuals diagnosed with ADHD. These results provide support for the use of the Conners 4–ADHD Index for effective classification of individuals with and without ADHD.

Another way to examine the ability of the Conners 4–ADHD Index to predict group membership is to dichotomize scores into two groups: scores less than 60% (i.e., where individuals from the general population would be expected to score) and scores of 60% or greater (i.e., where individuals diagnosed with ADHD would be expected to score). Once the data were dichotomized, a second set of analyses investigated the dichotomized classification category of an obtained probability score in contrast with an individual’s actual group membership via confusion matrices. Using the approach outlined by Kessel and Zimmerman (1993), the confusion matrices were then used to derive classification accuracy statistics (see Inconsistency Index in chapter 6, Development). Predicting diagnostic status depends on the prevalence of ADHD in the population. The prevalence (or base rate of ADHD in the clinician’s referral population) can vary widely depending on the purpose of the evaluation and the setting. For example, in a screening setting, one might expect the prevalence of ADHD to be around 10% or less, whereas in a clinically referred sample, a prevalence of approximately 50% may be more likely, while in an ADHD-specific clinical practice, a prevalence of 60%–80% would be expected. Accordingly, the classification accuracy statistics, assuming a 50% base rate, are summarized in Table 12.25, and the Positive Predictive and Negative Predictive Values based on varying base rates are provided in Table 12.26. The overall correct classification rate was 85.7% for Parent, 73.6% for Teacher, and 72.8% for Self-Report.