Book chapters will be unavailable on Saturday 24th August between 8am-12pm BST. This is for essential maintenance which will provide improved performance going forwards. Please accept our apologies for any inconvenience caused.
To send content items to your account,
please confirm that you agree to abide by our usage policies.
If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account.
Find out more about sending content to .
To send content items to your Kindle, first ensure firstname.lastname@example.org
is added to your Approved Personal Document E-mail List under your Personal Document Settings
on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part
of your Kindle email address below.
Find out more about sending to your Kindle.
Note you can select to send to either the @free.kindle.com or @kindle.com variations.
‘@free.kindle.com’ emails are free but can only be sent to your device when it is connected to wi-fi.
‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.
The nosological status of generalized anxiety disorder (GAD) versus dysthymic disorder (DD) has been questioned. The aim of this study was to examine qualitative differences within (co-morbid) GAD and DD symptomatology.
Latent class analysis was applied to anxious and depressive symptomatology of respondents from three population-based studies (2007 Australian National Survey of Mental Health and Wellbeing; National Comorbidity Survey Replication; and Netherlands Mental Health Survey and Incidence Study-2; together known as the Triple study) and respondents from a multi-site naturalistic cohort [Netherlands Study of Depression and Anxiety (NESDA)]. Sociodemographics and clinical characteristics of each class were examined.
A three-class (Triple study) and two-class (NESDA) model best fitted the data, reflecting mainly different levels of severity of symptoms. In the Triple study, no division into a predominantly GAD or DD co-morbidity subtype emerged. Likewise, in spite of the presence of pure GAD and DD cases in the NESDA sample, latent class analysis did not identify specific anxiety or depressive profiles in the NESDA study. Next, sociodemographics and clinical characteristics of each class were examined. Classes only differed in levels of severity.
The absence of qualitative differences in anxious or depressive symptomatology in empirically derived classes questions the differentiation between GAD and DD.
Identifying depressive subtypes is an important tool in reducing the heterogeneity of major depressive disorder. However, few studies have examined the stability of putative subtypes of depression over time.
The sample included 488 persons from the Netherlands Study of Depression and Anxiety (NESDA) who had major depressive disorder at baseline and at the 2-year follow-up assessment. A latent transition analysis (LTA) was applied to examine the stability of depressive subtypes across time-points. Differences in demographic, clinical, psychosocial and health correlates between subtypes were evaluated in a subsample of persons with stable subtypes.
Three subtypes were identified at each time-point: a moderate subtype (prevalence T0 39%, T1 42%), a severe typical subtype (T0 30%, T1 25%), and a severe atypical subtype (T0 31%, T1 34%). The LTA showed 76% stability across the 2-year follow-up, with the greatest stability in the severe atypical class (79%). Analyses of correlates in the stable subtypes showed a predominance of women and more overweight and obesity in the severe atypical subtype, and a greater number of negative life events and higher neuroticism and functioning scores in the severe typical subtype.
Subtypes of major depressive disorder were found to be stable across a 2-year follow-up and to have distinct determinants, supporting the notion that the identified subtypes are clinically meaningful.
Current classification of unipolar depression reflects the idea that prognosis is essential. However, do DSM categories of major depressive disorder (MDD), dysthymic disorder (Dysth) and double depression (DD=MDD+Dysth) indeed adequately represent clinically relevant course trajectories of unipolar depression? Our aim was to test DSM categories (MDD, Dysth and DD) in comparison with empirically derived prognostic categories, using a prospectively followed cohort of depressed patients.
A large sample (n=804) of out-patients with unipolar depression were derived from a prospective cohort study, the Netherlands Study of Depression and Anxiety (NESDA). Using latent class growth analysis (LCGA), empirically derived 2-year course trajectories were constructed. These were compared with DSM diagnoses and a wider set of putative predictors for class membership.
Five course trajectories were identified, ranging from mild severity and rapid remission to high severity and chronic course trajectory. Contrary to expectations, more than 50% of Dysth and DD were allocated to classes with favorable course trajectories, suggesting that current DSM categories do not adequately represent course trajectories. The class with the most favorable course trajectory differed on several characteristics from other classes (younger age, more females, less childhood adversity, less somatic illnesses, lower neuroticism, higher extraversion). Older age, earlier age of onset and lower extraversion predicted poorest course trajectory.
MDD, Dysth and DD did not adequately match empirically derived course trajectories for unipolar depression. For the future classification of unipolar depression, it may be wise to retain the larger, heterogeneous category of unipolar depression, adopting cross-cutting dimensions of severity and duration to further characterize patients.
Email your librarian or administrator to recommend adding this to your organisation's collection.