General Practice and Primary Care - Research Publications
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ItemDeprescribing intervention activities mapped to guiding principles for use in general practice: a scoping review(BMJ PUBLISHING GROUP, 2021)OBJECTIVE: To identify and characterise activities for deprescribing used in general practice and to map the identified activities to pioneering principles of deprescribing. SETTING: Primary care. DATA SOURCES: Medline, EMBASE (Ovid), CINAHL, Australian New Zealand Clinical Trials Registry (ANZCTR), Clinicaltrials.gov, ISRCTN registry, OpenGrey, Annals of Family Medicine, BMC Family Practice, Family Practice and British Journal of General Practice (BJGP) from inception to the end of June 2021. STUDY SELECTION: Included studies were original research (randomised controlled trial, quasi-experimental, cohort study, qualitative and case studies), protocol papers and protocol registrations. DATA EXTRACTION: Screening and data extraction was completed by one reviewer; 10% of the studies were independently reviewed by a second reviewer. Coding of full-text articles in NVivo was conducted and mapped to five deprescribing principles. RESULTS: Fifty studies were included. The most frequently used activities were identification of appropriate patients for deprescribing (76%), patient education (50%), general practitioners (GP) education (48%), and development and use of a tapering schedule (38%). Six activities did not align with the five deprescribing principles. As such, two principles (engage practice staff in education and appropriate identification of patients, and provide feedback to staff about deprescribing occurrences within the practice) were added. CONCLUSION: Activities and guiding principles for deprescribing should be paired together to provide an accessible and comprehensive guide to deprescribing by GPs. The addition of two principles suggests that practice staff and practice management teams may play an instrumental role in sustaining deprescribing processes within clinical practice. Future research is required to determine the most of effective activities to use within each principle and by whom.
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ItemMoving from "let's fix them" to "actually listen": the development of a primary care intervention for mental-physical multimorbidity(BMC, 2021-04-01)BACKGROUND: Effective person-centred interventions are needed to support people living with mental-physical multimorbidity to achieve better health and wellbeing outcomes. Depression is identified as the most common mental health condition co-occurring with a physical health condition and is the focus of this intervention development study. The aim of this study is to identify the key components needed for an effective intervention based on a clear theoretical foundation, consideration of how motivational interviewing can inform the intervention, clinical guidelines to date, and the insights of primary care nurses. METHODS: A multimethod approach to intervention development involving review and integration of the theoretical principles of Theory of Planned Behavior and the patient-centred clinical skills of motivational interviewing, review of the expert consensus clinical guidelines for multimorbidity, and incorporation of a thematic analysis of group interviews with Australian nurses about their perspectives of what is needed in intervention to support people living with mental-physical multimorbidity. RESULTS: Three mechanisms emerged from the review of theory, guidelines and practitioner perspective; the intervention needs to actively 'engage' patients through the development of a collaborative and empathic relationship, 'focus' on the patient's priorities, and 'empower' people to make behaviour change. CONCLUSION: The outcome of the present study is a fully described primary care intervention for people living with mental-physical multimorbidity, with a particular focus on people living with depression and a physical health condition. It builds on theory, expert consensus guidelines and clinician perspective, and is to be tested in a clinical trial.
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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 AvailableClinical efficacy of a Decision Support Tool (Link-me) to guide intensity of mental health care in primary practice: a pragmatic stratified randomised controlled trial(ELSEVIER SCI LTD, 2021-03)BACKGROUND: The volume and heterogeneity of mental health problems that primary care patients present with is a substantial challenge for health systems, and both undertreatment and overtreatment are common. We developed Link-me, a patient-completed Decision Support Tool, to predict severity of depression or anxiety, identify priorities, and recommend interventions. In this study, we aimed to examine if Link-me reduces psychological distress among individuals predicted to have minimal/mild or severe symptoms of anxiety or depression. METHODS: In this pragmatic stratified randomised controlled trial, adults aged 18-75 years reporting depressive or anxiety symptoms or use of mental health medication were recruited from 23 general practices in Australia. Participants completed the Decision Support Tool and were classified into three prognostic groups (minimal/mild, moderate, severe), and those in the minimal/mild and severe groups were eligible for inclusion. Participants were individually and randomly assigned (1:1) by a computer-generated allocation sequence to receive either prognosis-matched care (intervention group) or usual care plus attention control (control group). Participants were not blinded but intervention providers were only notified of those allocated to the intervention group. Outcome assessment was blinded. The primary outcome was the difference in the change in scores between the intervention and control group, and within prognostic groups, on the 10-item Kessler Psychological Distress Scale at 6 months post randomisation. The trial was registered on the Australian and New Zealand Clinical Trials Registry, ACTRN12617001333303. OUTCOMES: Between Nov 21, 2017, and Oct 31, 2018, 24 616 patients were invited to complete the eligibility screening survey. 1671 of these patients were included and randomly assigned to either the intervention group (n=834) or the control group (n=837). Prognosis-matched care was associated with greater reductions in psychological distress than usual care plus attention control at 6 months (p=0·03), with a standardised mean difference (SMD) of -0·09 (95% CI -0·17 to -0·01). This reduction was also seen in the severe prognostic group (p=0·003), with a SMD of -0·26 (-0·43 to -0·09), but not in the minimal/mild group (p=0·73), with a SMD of 0·04 (-0·17 to 0·24). In the complier average causal effect analysis in the severe prognostic group, differences were larger among those who received some or all aspects of the intervention (SMD range -0·58 to -1·15). No serious adverse effects were recorded. INTERPRETATION: Prognosis-based matching of interventions reduces psychological distress in patients with anxiety or depressive symptoms, particularly in those with severe symptoms, and is associated with better outcomes when patients access the recommended treatment. Optimisation of the Link-me approach and implementation into routine practice could help reduce the burden of disease associated with common mental health conditions such as anxiety and depression. FUNDING: Australian Government Department of Health.
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ItemNo Preview AvailableLink-me: Protocol for a randomised controlled trial of a systematic approach to stepped mental health care in primary care(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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ItemA Mobile Phone App to Improve the Mental Health of Taxi Drivers: Single-Arm Feasibility Trial(JMIR Publications, 2020-01-15)Background: Psychological distress among taxi drivers is 5 times higher than that in the general population, and more than half of all drivers have experienced 3 or more potentially traumatic events in their lifetime. Nevertheless, help-seeking for mental health problems in this male-dominated, predominately immigrant workforce is low. Mobile technologies have the potential to increase mental health awareness, teach self-help skills, and encourage help-seeking in this hard-to-reach population. Objective: This study aimed to assess the feasibility, acceptability, and potential efficacy of Driving to Health, a mobile phone–friendly mental health website app designed for people working as taxi drivers. Methods: Drivers (n=46) were recruited from the Melbourne Airport Taxi Holding Yard to participate in a single-arm trial. Self-reported, paper-based assessments were completed at baseline and at 1 month. Feasibility was measured by completion rates, representativeness of study participants, and levels of use. Acceptability was assessed by measuring users’ perception of the quality of the app and anticipated levels of future use. The efficacy of Driving to Health to increase awareness, self-help behaviors, and intentions to seek help was assessed using the user version of the Mobile App Rating Scale (uMARS) and the General Help-Seeking Questionnaire (GHSQ). Psychological symptoms were measured using the short form of the Depression, Anxiety, and Stress Scale (DASS-21). Data were analyzed using complete case analysis. Results: In total, 42 participants comprising drivers from 10 different countries of origin, and 14 different languages, completed pre- and poststudy measures (42/46, 91% completion rate). Just under half (45%) of all users used the app more than once with an average visit of 4 min 8 seconds. Responding to the uMARS, 62% (26/42) of the participants said that they would recommend the app to many people. Nearly all (40/42, 95%) participants said that Driving to Health increased awareness of their own mental health; 86% (36/42) said that it increased their mental health knowledge; and 76% (32/42) said that it increased their self-help behaviors. Increases in help-seeking intentions on the GHSQ were not significant, and increases on all 3 scales of DASS-21 were not reliable or meaningful. Conclusions: This study suggests that Driving to Health is an acceptable and feasible electronic health intervention for a hard-to-reach population. Our findings also suggest that Driving to Health results in increases in mental health awareness, behaviors, and willingness to seek help.
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ItemThe influence of personality on trajectories of distress, health and functioning in mild-to-moderately depressed adults with type 2 diabetes(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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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.