Is autism overdiagnosed?
Eric Fombonne
Abstract
After attention was drawn in the late 1960s to the poor reproducibility of psychiatric diagnosis between clinicians, methods and procedures used to diagnose psychiatric disorders were greatly improved. Sources of variance contributing to the poor reliability of psychiatric diagnosis were identified that included: information variance (how clinicians go about enquiring about symptoms), interpretation variance (how clinicians weigh the observed symptomatology towards diagnostic formulations), and criterion variance (how clinicians arrange symptom constellations to generate specific diagnoses). To improve the reliability of diagnosis, progresses were made in two major directions. First, diagnostic instruments were developed to standardize the way symptoms are elicited, evaluated, and scored. These diagnostic interviews were either highly structured for use in large-scale studies (e.g. the DIS), by lay interviewers without a clinical background, and with a style of questioning that emphasized adherence to the exact wording of probes, reliance on closed questions with simple response formats (Yes/No) and recording respondents’ answers without interviewer’s judgment contribution. By contrast, semi-structured interviews (e.g. the SADS) were designed to be used by clinically trained interviewers and adopted a more flexible, conversational style, using open-ended questions, utilizing all behavioral descriptions generated in the interview, and developing scoring conventions that called upon the clinical judgment of the interviewer. Second, diagnostic criteria and algorithms were introduced in nosographies in 1980 for the DSM and soon after in ICD. Algorithm-derived diagnoses could subsequently be tested for their validity using follow-up, family history, treatment response studies, or other external criteria.
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Dr. Eric Fombonne is a Joint Editor for JCPP, a full profile can be found here.
