Characteristics of nosologically informative data sets that address key diagnostic issues facing the Diagnostic and Statistical Manual of Mental Disorders, fifth edition (DSM-V) and International Classification of Diseases, eleventh edition (ICD-11) substance use disorders workgroups.
OBJECTIVE
Over the past two decades, many nosological issues have been addressed by the Diagnostic and Statistical Manual of Mental Disorders (DSM) and International Classification of Diseases (ICD) substance use disorders workgroups. Even with those efforts, there are key issues that have not been resolved and must be revisited, or addressed de novo, by the workgroups. These lingering points are broad, due to the array of substances classified under the diagnostic umbrella of substance use disorders. They include substantive issues ranging from dimensional approaches, similar criteria for each substance, cut-points and thresholds, distinct abuse and dependence classifications, new criteria and drugs, to less substantive ones, such as the adjectives used to describe the severity of the behaviors.


RESULTS
This paper describes the characteristics of the data sets that will be needed to resolve the key nosological issues. Ten points are described: (1) data must be true to nomenclature under study; (2) flexible regarding rearrangements of scoring algorithms; (3-4) able to assess substances individually and retain former versions of the criteria; (5) not rely on shortened versions; (6) utilize samples that are generalizable; (7) make diagnoses with transparent algorithms; (8) combine mixed methods for corroborating data; (9) utilize assessments that collect reliable and valid diagnoses and criteria; and (10) stretch the limits by allowing for new discoveries.


CONCLUSIONS
This paper describes each of these and gives examples of the limitations and strengths of data for the purpose of defining a useful, unified concept of addictive behaviors.
Cottler
Linda B
LB
Washington University School of Medicine, Department of Psychiatry, St Louis, USA. cottler@epi.wustl.edu
Grant
Bridget F
BF
D000465:Algorithms; D039721:Diagnostic and Statistical Manual of Mental Disorders; D006801:Humans; D038801:International Classification of Diseases; D011619:Psychotropic Drugs / Q000009:adverse effects; D015203:Reproducibility of Results; D019966:Substance-Related Disorders / Q000145:classification* / Q000175:diagnosis; D009626:Terminology as Topic
D011619:Psychotropic Drugs