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Background: The dichotic digits test is one of the most widely used assessment tools for central auditory processing disorder. However, questions remain concerning the impact of cognitive factors on test results.
Purpose: To develop the Dichotic Digits difference Test (DDdT), an assessment tool that could differentiate children with cognitive deficits from children with genuine dichotic deficits based on differential test results. The DDdT consists of four subtests: dichotic free recall (FR), dichotic directed left ear (DLE), dichotic directed right ear (DRE), and diotic. Scores for six conditions are calculated (FR left ear [LE], FR right ear [RE], and FR total, as well as DLE, DRE, and diotic). Scores for four difference measures are also calculated: dichotic advantage, right-ear advantage (REA) FR, REA directed, and attention advantage.
Research Design: Experiment 1 involved development of the DDdT, including error rate analysis. Experiment 2 involved collection of normative and test-retest reliability data.
Study Sample: Twenty adults (aged 25 yr 10 mo to 50 yr 7 mo, mean 36 yr 4 mo) took part in the development study; 62 normal-hearing, typically developing, primary-school children (aged 7 yr 1 mo to 11 yr 11 mo, mean 9 yr 4 mo) and 10 adults (aged 25 yr 0 mo to 51 yr 6 mo, mean 34 yr 10 mo) took part in the normative and test-retest reliability study.
Data Collection And Analysis: In Experiment 1, error rate analysis was conducted on the 36 digit-pair combinations of the DDdT. Normative data collected in Experiment 2 were arcsine transformed to achieve a distribution that was closer to a normal distribution and z-scores calculated. Pearson product-moment correlations were used to determine the strength of relationships between DDdT conditions.
Results: The development study revealed no significant differences in the adult population between test and retest on any DDdT condition. Error rates on 36 digit pairs ranged from 1.5% to 16.7%. The most and the least error-prone digits were removed before commencement of the normative data study, leaving 25 unique digit pairs. Average z-scores calculated from the arcsine-transformed data collected from the 62 children who took part in the normative data study revealed that FR dichotic processing (LE, RE, and total) was highly correlated with diotic processing (r ranging from 0.5 to 0.6; p < 0.0001). Significant improvements in performance on retest occurred for the FR LE, RE, total, and diotic conditions (p ranging from 0.05 to 0.0004), the conditions that would be expected to improve with practice if the participant's response strategies are better the second time around.
Conclusions: The addition of a diotic control task-that shares many response demands with the usual dichotic tasks-opens up the possibility of differentiating children who perform below expectations because of poor dichotic processing skills from those who perform poorly because of impaired attention, memory, or other cognitive abilities. The high correlation between dichotic and diotic performance suggests that factors other than dichotic performance play a substantial role in a child's ability to perform a dichotic listening task. This hypothesis is investigated further in the cognitive correlation study that follows in the companion paper (DDdT Study Part 2; Cameron et al, 2016).
