General Practice and Primary Care - Research Publications
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ItemMatching depression management to severity prognosis in primary care: results of the Target-D randomised controlled trial(ROYAL COLL GENERAL PRACTITIONERS, 2021-02)BACKGROUND: Mental health treatment rates are increasing, but the burden of disease has not reduced. Tools to support efficient resource distribution are required. AIM: To investigate whether a person-centred e-health (Target-D) platform matching depression care to symptom severity prognosis can improve depressive symptoms relative to usual care. DESIGN AND SETTING: Stratified individually randomised controlled trial in 14 general practices in Melbourne, Australia, from April 2016 to February 2019. In total, 1868 participants aged 18-65 years who had current depressive symptoms; internet access; no recent change to antidepressant; no current antipsychotic medication; and no current psychological therapy were randomised (1:1) via computer-generated allocation to intervention or usual care. METHOD: The intervention was an e-health platform accessed in the GP waiting room, comprising symptom feedback, priority-setting, and prognosis-matched management options (online self-help, online guided psychological therapy, or nurse-led collaborative care). Management options were flexible, neither participants nor staff were blinded, and there were no substantive protocol deviations. The primary outcome was depressive symptom severity (9-item Patient Health Questionnaire [PHQ-9]) at 3 months. RESULTS: In intention to treat analysis, estimated between- arm difference in mean PHQ-9 scores at 3 months was -0.88 (95% confidence interval [CI] = -1.45 to -0.31) favouring the intervention, and -0.59 at 12 months (95% CI = -1.18 to 0.01); standardised effect sizes of -0.16 (95% CI = -0.26 to -0.05) and -0.10 (95% CI = -0.21 to 0.002), respectively. No serious adverse events were reported. CONCLUSION: Matching management to prognosis using a person-centred e-health platform improves depressive symptoms at 3 months compared to usual care and could feasibly be implemented at scale. Scope exists to enhance the uptake of management options.
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ItemNo Preview AvailableDevelopment of a Mobile Clinical Prediction Tool to Estimate Future Depression Severity and Guide Treatment in Primary Care: User-Centered Design(JMIR PUBLICATIONS, INC, 2018-04)BACKGROUND: Around the world, depression is both under- and overtreated. The diamond clinical prediction tool was developed to assist with appropriate treatment allocation by estimating the 3-month prognosis among people with current depressive symptoms. Delivering clinical prediction tools in a way that will enhance their uptake in routine clinical practice remains challenging; however, mobile apps show promise in this respect. To increase the likelihood that an app-delivered clinical prediction tool can be successfully incorporated into clinical practice, it is important to involve end users in the app design process. OBJECTIVE: The aim of the study was to maximize patient engagement in an app designed to improve treatment allocation for depression. METHODS: An iterative, user-centered design process was employed. Qualitative data were collected via 2 focus groups with a community sample (n=17) and 7 semistructured interviews with people with depressive symptoms. The results of the focus groups and interviews were used by the computer engineering team to modify subsequent protoypes of the app. RESULTS: Iterative development resulted in 3 prototypes and a final app. The areas requiring the most substantial changes following end-user input were related to the iconography used and the way that feedback was provided. In particular, communicating risk of future depressive symptoms proved difficult; these messages were consistently misinterpreted and negatively viewed and were ultimately removed. All participants felt positively about seeing their results summarized after completion of the clinical prediction tool, but there was a need for a personalized treatment recommendation made in conjunction with a consultation with a health professional. CONCLUSIONS: User-centered design led to valuable improvements in the content and design of an app designed to improve allocation of and engagement in depression treatment. Iterative design allowed us to develop a tool that allows users to feel hope, engage in self-reflection, and motivate them to treatment. The tool is currently being evaluated in a randomized controlled trial.
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ItemTarget-D: a stratified individually randomized controlled trial of the diamond clinical prediction tool to triage and target treatment for depressive symptoms in general practice: study protocol for a randomized controlled trial(BMC, 2017-07-20)BACKGROUND: 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 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. METHODS: The 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. DISCUSSION: 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. 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 REGISTRATION: Australian New Zealand Clinical Trials Registry (ANZCTR 12616000537459 ). Retrospectively registered on 27 April 2016. See Additional file 1 for trial registration data.
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ItemMental health interventions and future major depression among primary care patients with subthreshold depression(ELSEVIER, 2015-05-15)BACKGROUND: Subthreshold depression is prevalent in primary care and is associated with poorer quality of life, higher health care use and increased risk of major depressive disorder (MDD). Currently, it is unclear how subthreshold depression should be managed in primary care and no studies have investigated the relationship between current models of care and the development of MDD. This study aimed to describe usual care over a six month follow-up for primary care patients with subthreshold depression and to investigate the relationship between usual care and the development of MDD. METHODS: Data were derived from 250 participants with subthreshold depression from the diamond study, a longitudinal cohort study of primary care patients. Participants completed questionnaires at three and six months on their health care use, the interventions they received and their depression status. Interventions were categorised according to the NICE guidelines for the management of depression in adults. Generalised estimating equation (GEE) models and logistic regression were used to estimate the association between receiving an intervention and MDD over six months. RESULTS: Four fifths (80.8%) of participants received a mental health intervention. Therapeutic listening, reassurance, pharmacotherapy and advice to exercise were most common. Subsequent MDD was predicted by history of depression, baseline depressive symptom severity and receiving a mental health intervention. LIMITATIONS: Usual care was assessed via patient self-report. CONCLUSIONS: Primary care physicians deliver mental health interventions to most subthreshold patients. However, it appears that current interventions are not averting MDD. Further research to identify effective interventions which are feasible in primary care is needed.