Symptoms of depression and challenging behaviours in people with intellectual disability: a Bayesian analysis

Clinicians need to know the likelihood of a condition given a positive or negative diagnostic test. In this study a Bayesian analysis of the Clinical Behavior Checklist for Persons with Intellectual Disabilities (CBCPID) to predict depression ill people with intellectual disability was conducted. The CBCPID was administered to 92 adults with intellectual disability referred,for psychiatric assessment. The presence or absence of each item of the CBCPID was compared to the presence or absence of a diagnosis of depression by a psychiatrist. Generally, CBCPID items had very lore sensitivity and specificity. However, acceptably: high values of Bayes' formula were observed for items such as loss of appetite, weight loss, self-reproach, suicidality, loss of confidence acid constipation. Behavioural items had lore values of Bayes' formula. Clinicians and researchers can use certain characteristic symptoms of depression, but not challenging behaviours, as predictors of depression in people with intellectual disability.