title: Using decision theory to derive optimal cut-off scores of screening instruments: an illustration explicating costs and benefits of mental health screening.
abstract: This paper shows how decision theory can be used to determine optimal cut-off scores on mental health screeners. The procedure uses (a) the costs and benefits of correct and erroneous decisions, and (b) the rates of correct and erroneous decisions as a function of the cut-off score. Using this information, for each cut-off point expected costs are calculated. The cut-off point with the lowest expected costs is the optimal cut-off score. An illustration is given in which the General Health Questionnaire is employed as a major depression screener. Optimal cut-off points are determined for four different contexts: patients, health service providers, society, and mental health researchers. As in these four situations different costs are encountered, different optimal cut-off points were found.
authors.affiliation: Department of Clinical Psychology, Vrije Universiteit, Amsterdam, The Netherlands. n.smits@psy.vu.nl
authors.forename: Niels
authors.initials: N
authors.lastname: Smits
authors.forename: Filip
authors.initials: F
authors.lastname: Smit
authors.forename: Pim
authors.initials: P
authors.lastname: Cuijpers
authors.forename: Ron
authors.initials: R
authors.lastname: De Graaf
mesh_terms: D000203:Activities of Daily Living; D015982:Bias; D003362:Cost-Benefit Analysis; D003662:Decision Theory; D003865:Major Depressive Disorder / Q000191:economics / Q000453:epidemiology / Q000523:psychology; D004185:Disability Evaluation; D006801:Humans; D008403:Mass Screening / Q000191:economics*; D001523:Mental Disorders / Q000175:diagnosis / Q000191:economics* / Q000453:epidemiology* / Q000523:psychology; D015588:Observer Variation; D010555:Personality Inventory / Q000706:statistics & numerical data*; D011594:Psychometrics / Q000706:statistics & numerical data; D011788:Quality of Life; D012372:ROC Curve; D011795:Surveys and Questionnaires