title: Diagnostic Differences and Demographic Predictors of Respondents Adjudicated Civilly Incompetent Versus Competent.
abstract: The purpose of this study was to determine if diagnostic and demographic variables predict civil competency adjudications, a topic that has received scant research attention. Respondents (i.e., individuals alleged to be incompetent) were evaluated by a licensed psychologist to assist the court in civil competency and possible guardianship determination. Prior research using some of the same participants demonstrated select differences on activities of daily living between these groups (Quickel & Demakis, ), but the current set of analyses was not conducted. The current study included 107 competency evaluations in Mecklenburg County North Carolina and, at conclusion of the case, the public record of the adjudication was obtained. Based on prior legal theorizing in related criminal areas--focused on discrimination of individuals with mental illness--we predicted that cases involving respondents with psychiatric diagnoses would be likely to be overrepresented in those referred for evaluation as well as those subsequently adjudicated incompetent. A series of analyses indicated no statistical differences between competency groups (psychiatric/substance abuse, neurological, both psychiatric and neurological, and intellectually disabled). In a series of exploratory logistic regression analyses, we found that respondents who were single versus in a relationship and those not living at home versus living at home were significantly more likely to be adjudicated incompetent, even after controlling for difference in activities of daily living. There were no differences in incompetency adjudication by age, education, gender, race, or relationship status. Results are discussed in terms of implications for individuals with mental illness in incompetency hearings, as well as specific issues for psychologists evaluating a broad range of respondents.
authors.forename: George J
authors.initials: GJ
authors.lastname: Demakis
authors.forename: Charlie L
authors.initials: CL
authors.lastname: Reeve
mesh_terms: D000328:Adult; D000368:Aged; D001499:Bayes Theorem; D016208:Databases, Factual; D003710:Demography; D005260:Female; D006801:Humans; D008297:Male; D016743:Mental Competency / Q000331:legislation & jurisprudence*; D001523:Mental Disorders / Q000175:diagnosis*; D008875:Middle Aged; D009657:North Carolina