Abstract

BackgroundDepression is a highly prevalent and costly disorder. Effective treatments are available but are not always delivered to the right person at the right time, with both under- and over-treatment a problem. Up to half the patients presenting to general practice report symptoms of depression, but general practitioners have no systematic way of efficiently identifying level of need and allocating treatment accordingly. Therefore, our team developed a new clinical prediction tool (CPT) to assist with this task. The CPT predicts depressive symptom severity in three months’ time and based on these scores classifies individuals into three groups (minimal/mild, moderate, severe), then provides a matched treatment recommendation. This study aims to test whether using the CPT reduces depressive symptoms at three months compared with usual care.MethodsThe Target-D study is an individually randomized controlled trial. Participants will be 1320 general practice patients with depressive symptoms who will be approached in the practice waiting room by a research assistant and invited to complete eligibility screening on an iPad. Eligible patients will provide informed consent and complete the CPT on a purpose-built website. A computer-generated allocation sequence stratified by practice and depressive symptom severity group, will randomly assign participants to intervention (treatment recommendation matched to predicted depressive symptom severity group) or comparison (usual care plus Target-D attention control) arms. Follow-up assessments will be completed online at three and 12 months. The primary outcome is depressive symptom severity at three months. Secondary outcomes include anxiety, mental health self-efficacy, quality of life, and cost-effectiveness. Intention-to-treat analyses will test for differences in outcome means between study arms overall and by depressive symptom severity group.DiscussionTo our knowledge, this is the first depressive symptom stratification tool designed for primary care which takes a prognosis-based approach to provide a tailored treatment recommendation. If shown to be effective, this tool could be used to assist general practitioners to implement stepped mental-healthcare models and contribute to a more efficient and effective mental health system.Trial registrationAustralian New Zealand Clinical Trials Registry (ANZCTR 12616000537459). Retrospectively registered on 27 April 2016. See Additional file 1 for trial registration data.

Highlights

  • Depression is a highly prevalent and costly disorder

  • Gunn et al Trials (2017) 18:342 (Continued from previous page). To our knowledge, this is the first depressive symptom stratification tool designed for primary care which takes a prognosis-based approach to provide a tailored treatment recommendation

  • Despite significant investments in mental health globally, there is no evidence of a reduction in the burden of disease associated with depression [4]

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Summary

Introduction

Depression is a highly prevalent and costly disorder. Effective treatments are available but are not always delivered to the right person at the right time, with both under- and over-treatment a problem. Up to half the patients presenting to general practice report symptoms of depression, but general practitioners have no systematic way of efficiently identifying level of need and allocating treatment . The CPT predicts depressive symptom severity in three months’ time and based on these scores classifies individuals into three groups (minimal/mild, moderate, severe), provides a matched treatment recommendation. One of the biggest challenges facing mental healthcare systems is the need to develop efficient methods of allocating clinically effective treatment in a cost-effective way to the people that need them most [5]. The majority of depression cases are identified, treated, and followed up in primary care [6]. Only 16% of Australians with case level depression or anxiety receive an adequate “dose” of an evidence-based intervention consistent with treatment guidelines [9]. Antidepressant prescriptions far outnumber patients for whom such medication is indicated [11]

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