DSM-5 Field Trials in the United States and Canada, Part II: Test-Retest Reliability of Selected Categorical Diagnoses
ABSTRACT OBJECTIVE The DSM-5 Field Trials were designed to obtain precise (standard error <0.1) estimates of the intraclass kappa as a measure of the degree to which two clinicians could independently agree on the presence or absence of selected DSM-5 diagnoses when the same patient was interviewed on separate occasions, in clinical settings, and evaluated with usual clinical interview methods. METHOD Eleven academic centers in the United States and Canada were selected, and each was assigned several target diagnoses frequently treated in that setting. Consecutive patients visiting a site during the study were screened and stratified on the basis of DSM-IV diagnoses or symptomatic presentations. Patients were randomly assigned to two clinicians for a diagnostic interview; clinicians were blind to any previous diagnosis. All data were entered directly via an Internet-based software system to a secure central server. Detailed research design and statistical methods are presented in an accompanying article. RESULTS There were a total of 15 adult and eight child/adolescent diagnoses for which adequate sample sizes were obtained to report adequately precise estimates of the intraclass kappa. Overall, five diagnoses were in the very good range (kappa= 0.60-0.79), nine in the good range (kappa= 0.40-0.59), six in the questionable range (kappa= 0.20-0.39), and three in the unacceptable range (kappa values <0.20). Eight diagnoses had insufficient sample sizes to generate precise kappa estimates at any site. CONCLUSIONS Most diagnoses adequately tested had good to very good reliability with these representative clinical populations assessed with usual clinical interview methods. Some diagnoses that were revised to encompass a broader spectrum of symptom expression or had a more dimensional approach tested in the good to very good range.
- SourceAvailable from: Hendrikus Hendriksen
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- "The criteria for a major depressive disorder for instance involve a wide range of symptoms, leading to large heterogeneity in the population of patients diagnosed with a major depressive disorder. Moreover, the DSM based diagnosis for depression has a poor reliability (Clarke et al., 2013; Friedman et al., 2013; Narrow et al., 2013; Regier et al., 2013). Furthermore, it does not take into account the severity of the depression or comorbidity with anxiety, which are both important predictors for the outcome of pharmacotherapy (Fournier et al., 2010). "
ABSTRACT: Psychopharmacology has had some bad publicity lately. Frankly, there have been some major problems along the way in developing new effective drugs for psychiatric disorders. After a prolonged period of high investments but low success rates, big pharmaceutical companies seem to retract their activities in the psychopharmacology field. Yet, the burden of mental disorders is likely to keep on growing in the next decades. In this position paper, we focus on drug development for depression and anxiety disorders, to narrow the scope of the assay. We describe the current situation of the psychopharmacology field, and analyse some of the methods and paradigms that have brought us here, but which should perhaps change to bring us even further. In addition, some of the factors contributing to the current stagnation in psychopharmacology are discussed. Finally, we suggest a number of changes that could lead to a more rational strategy for central nervous system drug development and which may circumvent some of the pitfalls leading to "me too" approaches. Central to the suggested changes, is the notion that mental disorders do not lead to several symptoms, but a network of causally related symptoms convolutes into a mental disorder. We call upon academia to put these changes in the early phases of drug development into effect. Copyright © 2015. Published by Elsevier B.V.European journal of pharmacology 03/2015; 759. DOI:10.1016/j.ejphar.2015.03.020 · 2.68 Impact Factor
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- "The DSM - 5 field trials estimated the reliabilities of selected DSM - 5 diagnoses in large representative clinical populations ( Regier et al . , 2013 ) ; reliability was assessed by measuring the degree to which two clinicians independently agreed on the presence or absence of psychiatric conditions . The trials yielded a " ques - tionable " reliability of depression diagnosis of 0 . 28 , indicating a very low agreement . The degree of diagnostic certainty was much lower for depressi"
ABSTRACT: Major depression (MD) is a highly heterogeneous diagnostic category. Diverse symptoms such as sad mood, anhedonia, and fatigue are routinely added to an unweighted sum-score, and cutoffs are used to distinguish between depressed participants and healthy controls. Researchers then investigate outcome variables like MD risk factors, biomarkers, and treatment response in such samples. These practices presuppose that (1) depression is a discrete condition, and that (2) symptoms are interchangeable indicators of this latent disorder. Here I review these two assumptions, elucidate their historical roots, show how deeply engrained they are in psychological and psychiatric research, and document that they contrast with evidence. Depression is not a consistent syndrome with clearly demarcated boundaries, and depression symptoms are not interchangeable indicators of an underlying disorder. Current research practices lump individuals with very different problems into one category, which has contributed to the remarkably slow progress in key research domains such as the development of efficacious antidepressants or the identification of biomarkers for depression. The recently proposed network framework offers an alternative to the problematic assumptions. MD is not understood as a distinct condition, but as heterogeneous symptom cluster that substantially overlaps with other syndromes such as anxiety disorders. MD is not framed as an underlying disease with a number of equivalent indicators, but as a network of symptoms that have direct causal influence on each other: insomnia can cause fatigue which then triggers concentration and psychomotor problems. This approach offers new opportunities for constructing an empirically based classification system and has broad implications for future research.Frontiers in Psychology 03/2015; 6(306):1-11. DOI:10.3389/fpsyg.2015.00309 · 2.80 Impact Factor
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- "The Diagnostic and Statistical Manual of Mental Disorders (DSM) criteria for major depression (MD) assign the same diagnosis to patients with very heterogeneous clinical syndromes (Ostergaard et al., 2011). This limits advancement of research on the pathophysiology and treatment of depression (Fink et al., 2007; Parker and Brotchie, 2009) and was not resolved in the DSM-V (Regier et al., 2013). Hence, identifying more homogeneous subgroups of patients could enable researchers to achieve more consistent and replicable findings and advance the understanding of each of these subtypes. "
ABSTRACT: Clinical observation and research data suggest that major depression (MD) is a heterogeneous disorder, possibly representing a group of different clinical entities. The identification of more homogeneous subtypes of depression could enhance research and enable development of more specific treatments. A melancholic subtype of MD, defined by the presence of observable psychomotor disturbance (PMD), is proposed to be more homogeneous and associated with biological determinants. The aim of this study was to investigate the homogeneity of this melancholic subtype in terms of symptoms by searching for an association between melancholia and a unidimensional subscale of the Hamilton Depression Rating Scale (HAM-D) proposed to have biological validity (HAM-D6).MethodsA cross-sectional assessment of 385 outpatients presenting with a unipolar major depressive episode was carried out to evaluate depressive symptoms using the HAM-D and melancholic or nonmelancholic subtype, according to the CORE measure of PMD.ResultsMelancholic patients exhibited more severe depressive symptoms, mainly associated with the HAM-D6. The items of this melancholia subscale represent 42.3% of the total HAM-D and were responsible for 59.4% of between-group differences. Correlation analysis showed similar results.LimitationsMost patients received previous treatment, and some were not at the nadir of the episode when assessed. This could have lowered the CORE measure sensibility.Conclusion Melancholic depression, as assigned by the CORE measure, represents a more severe and homogeneous subtype of MD. This observation may allow identification of proper biomarkers and development of more specific treatments.Journal of Affective Disorders 10/2014; 172. DOI:10.1016/j.jad.2014.09.050 · 3.71 Impact Factor