Medicine, Dentistry & Health Sciences Collected Works - Research Publications

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    Self-reported reasons for reducing or stopping antidepressant medications in primary care: thematic analysis of the diamond longitudinal study
    Coe, A ; Gunn, J ; Fletcher, S ; Murray, E ; Kaylor-Hughes, C (CAMBRIDGE UNIV PRESS, 2023-02-27)
    BACKGROUND: Current treatment guidelines advise that the deprescribing of antidepressants should occur around 6 months post-remission of symptoms. However, this is not routinely occurring in clinical practice, with between 30% and 50% of antidepressant users potentially continuing treatment with no clinical benefit. To support patients to deprescribe antidepressant treatment when clinically appropriate, it is important to understand what is important to patients when making the decision to reduce or cease antidepressants in a naturalistic setting. AIM: The current study aimed to describe the self-reported reasons primary care patients have for reducing or stopping their antidepressant medication. METHODS: Three hundred and seven participants in the diamond longitudinal study reported taking an SSRI/SNRI over the life of the study. Of the 307, 179 reported stopping or tapering their antidepressant during computer-assisted telephone interviews and provided a reason for doing so. A collective case study approach was used to collate the reasons for stopping or tapering. FINDINGS: Reflexive thematic analysis of patient-reported factors revealed five overarching themes; 1. Depression; 2. Medication; 3. Healthcare system; 4. Psychosocial, and; 5. Financial. These findings are used to inform suggestions for the development and implementation of antidepressant deprescribing discussions in clinical practice.
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    Link-me: Protocol for a randomised controlled trial of a systematic approach to stepped mental health care in primary care
    Fletcher, S ; Chondros, P ; Palmer, VJ ; Chatterton, ML ; Spittal, MJ ; Mihalopoulos, C ; Wood, A ; Harris, M ; Burgess, P ; Bassilios, B ; Pirkis, J ; Gunn, J (ELSEVIER SCIENCE INC, 2019-03)
    Primary care in Australia is undergoing significant reform, with a particular focus on cost-effective tailoring of mental health care to individual needs. Link-me is testing whether a patient-completed Decision Support Tool (DST), which predicts future severity of depression and anxiety symptoms and triages individuals into care accordingly, is clinically effective and cost-effective relative to usual care. The trial is set in general practices, with English-speaking patients invited to complete eligibility screening in their general practitioner's waiting room. Eligible and consenting patients will then complete the DST assessment and are randomised and stratified according to predicted symptom severity. Participants allocated to the intervention arm will receive feedback on DST responses, select treatment priorities, assess motivation to change, and receive a severity-matched treatment recommendation (information about and links to low intensity services for those with mild symptoms, or assistance from a specially trained health professional (care navigator) for those with severe symptoms). All patients allocated to the comparison arm will receive usual GP care plus attention control. Primary (psychological distress) and secondary (depression, anxiety, quality of life, days out of role) outcomes will be assessed at 6 and 12 months. Differences in outcome means between trial arms both across and within symptom severity group will be examined using intention-to-treat analyses. Within trial and modelled economic evaluations will be conducted to determine the value for money of credentials of Link-me. Findings will be reported to the Federal Government to inform how mental health services across Australia are funded and delivered in the future.
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    The influence of personality on trajectories of distress, health and functioning in mild-to-moderately depressed adults with type 2 diabetes
    Sanatkar, S ; Baldwin, P ; Clarke, J ; Fletcher, S ; Gunn, J ; Wilhelm, K ; Campbell, L ; Zwar, N ; Harris, M ; Lapsley, H ; Hadzi-Pavlovic, D ; Christensen, H ; Proudfoot, J (ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD, 2020-03-15)
    Identification of mental health risk is important for optimising diabetes care in type 2 diabetes mellitus (T2DM). Personality is linked to diabetes health and may assist detection of individuals with T2DM most at risk of chronic mental health difficulties. This study examined the moderator effect of personality factors on changes in psychological distress and functioning in adults with T2DM and mild-to-moderate depressive symptoms across a 12-month period. Data were obtained from participants in a randomised controlled trial of adults with T2DM.  Participants completed measures of depression (Patient Health Questionnaire-9), anxiety (General Anxiety Disorder-7), general functioning (Work and Social Adjustment Scale), diabetes distress (Diabetes Distress Scale), and diabetes self-management (Self-Management Profile for Type 2 Diabetes) at baseline, 3-, 6- and 12-months. Glycaemic control (HbA1c) was measured at baseline, 6- and 12-months. Two hundred trial completers agreed to complete a personality inventory (Big Five Inventory). Low neuroticism was linked with reduced depression, anxiety, functional impairment and diabetes distress over the year. High extraversion was associated with decreased anxiety and functional impairment. High conscientiousness was linked to increased healthy eating. No personality trait moderated HbA1c levels. Personality screening may help identify mental health risk and guide medical carer approach in T2DM patients.
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    Development of a Mobile Clinical Prediction Tool to Estimate Future Depression Severity and Guide Treatment in Primary Care: User-Centered Design
    Wachtler, C ; Coe, A ; Davidson, S ; Fletcher, S ; Mendoza, A ; Sterling, L ; Gunn, J (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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    Target-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
    Gunn, J ; Wachtler, C ; Fletcher, S ; Davidson, S ; Mihalopoulos, C ; Palmer, V ; Hegarty, K ; Coe, A ; Murray, E ; Dowrick, C ; Andrews, G ; Chondros, P (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.