Abstract:
Introduction: The precise epidemiological burden of autism is unknown because
of the limited capacity to identify and diagnose the disorder in resource-
constrained settings, related in part to a lack of appropriate standardised
assessment tools and health care experts. We assessed the reliability, validity,
and diagnostic accuracy of the Developmental Diagnostic Dimensional Interview
(3Di) in a rural setting on the Kenyan coast.
Methods: Using a large community survey of neurodevelopmental disorders
(NDDs), we administered the 3Di to 2,110 children aged between 6 years and 9
years who screened positive or negative for any NDD and selected 242 who had
specific symptoms suggestive of autism based on parental report and the screening
tools for review by a child and adolescent psychiatrist. On the basis of recorded
video, a multi-disciplinary team applied the Autism Diagnostic Observation
Schedule to establish an autism diagnosis. Internal consistency was used to
examine the reliability of the Swahili version of the 3Di, tetrachoric correlations to
determine criterion validity, structural equation modelling to evaluate factorial
structure and receiver operating characteristic analysis to calculate diagnostic
accuracy against Diagnostic Statistical Manual of Mental Disorders (DSM) diagnosis.
Results: The reliability coefficients for 3Di were excellent for the entire scale
{McDonald’s omega (w) = 0.83 [95% confidence interval (CI) 0.79–0.91]}. A
higher-order three-factor DSM-IV-TR model showed an adequate fit with the
model, improving greatly after retaining high-loading items and correlated items.
A higher-order two-factor DSM-5 model also showed an adequate fit. There
were weak to satisfactory criterion validity scores [tetrachoric rho = 0.38 (p =
0.049) and 0.59 (p = 0.014)] and good diagnostic accuracy metrics [area under
the curve = 0.75 (95% CI: 0.54–0.96) and 0.61 (95% CI: 0.49–0.73] for 3Di against the DSM criteria. The 3Di had a moderate sensitivity [66.7% (95% CI: 0.22–0.96)]
and a good specificity [82.5% (95% CI: 0.74–0.89)], when compared with the
DSM-5. However, we observed poor sensitivity [38.9% (95% CI: 0.17–0.64)] and
good specificity [83.5% (95% CI: 0.74–0.91)] against DSM-IV-TR.
Conclusion: The Swahili version of the 3Di provides information on autism traits,
which may be helpful for descriptive research of endophenotypes, for instance.
However, for accuracy in newly diagnosed autism, it should be complemented by
other tools, e.g., observational clinical judgment using the DSM criteria or
assessments such as the Autism Diagnostic Observation Schedule. The
construct validity of the Swahili 3Di for some domains, e.g., communication,
should be explored in future studies.