Article

Treatment-seeking behaviours for depression in the general population: results from the National Epidemiologic Survey on Alcohol and Related Conditions.

National Drug and Alcohol Research Centre, University of New South Wales, Sydney, NSW, Australia.
Journal of Affective Disorders (Impact Factor: 3.71). 06/2009; 121(1-2):59-67. DOI: 10.1016/j.jad.2009.05.009
Source: PubMed

ABSTRACT In light of the public health and clinical significance of major depression, treatment utilisation is an important issue. Epidemiological data is particularly useful for yielding accurate estimates of national trends; assessing unmet need in the population; and, informing mental health policy and focused planning of public health prevention and intervention programs.
Based on data from the 2001-2002 National Epidemiologic Survey on Alcohol and Related Conditions (NESARC), latent class analysis (LCA) was used to empirically identify and validate a typology of treatment-seeking behaviours for depression. Analyses were based on a subsample of individuals with a lifetime diagnosis of major depressive disorder (MDD).
A three-class solution emerged as the best-fitting model. The classes were labelled highly active treatment-seeking, partially active treatment-seeking, and inactive treatment-seeking. The classes were validated by reference to predisposing, enabling, and need factors associated with treatment utilisation.
Since information was retrieved by retrospective self-report it was not possible to corroborate information on treatment utilisation or medical conditions with independent clinical or administrative records. Reporting bias and recall error therefore cannot be ruled out. Also, given that the NESARC utilised lay interviewer-administered structured interviews to determine mental health diagnoses, one should be mindful that diagnoses are epidemiological research diagnoses rather than clinician diagnoses.
This study demonstrated the utility of LCA for identifying clinically meaningful subgroups of treatment-seeking behaviour.

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