BACKGROUND The COVID-19 pandemic has highlighted the importance of health care workers’ mental health and well-being for the successful function of the health care system. Few targeted digital tools exist to support the mental health of hospital-based health care workers, and none of them appear to have been led and co-designed by health care workers. OBJECTIVE RMHive is being led and developed by health care workers using experience-based co-design (EBCD) processes as a mobile app to support the mental health challenges posed by the COVID-19 pandemic to health care workers. We present a protocol for the impact evaluation for the rapid design and delivery of the RMHive mobile app. METHODS The impact evaluation will adopt a mixed methods design. Qualitative data from photo interviews undertaken with up to 30 health care workers and semistructured interviews conducted with up to 30 governance stakeholders will be integrated with qualitative and quantitative user analytics data and user-generated demographic and mental health data entered into the app. Analyses will address three evaluation questions related to engagement with the mobile app, implementation and integration of the app, and the impact of the app on individual mental health outcomes. The design and development will be described using the Mobile Health Evidence Reporting and Assessment guidelines. Implementation of the app will be evaluated using normalization process theory to analyze qualitative data from interviews combined with text and video analysis from the semistructured interviews. Mental health impacts will be assessed using the total score of the 4-item Patient Health Questionnaire (PHQ4) and subscale scores for the 2-item Patient Health Questionnaire for depression and the 2-item Generalized Anxiety Scale for anxiety. The PHQ4 will be completed at baseline and at 14 and 28 days. RESULTS The anticipated average use period of the app is 30 days. The rapid design will occur over four months using EBCD to collect qualitative data and develop app content. The impact evaluation will monitor outcome data for up to 12 weeks following hospital-wide release of the minimal viable product release. The study received funding and ethics approvals in June 2020. Outcome data is expected to be available in March 2021, and the impact evaluation is expected to be published mid-2021. CONCLUSIONS The impact evaluation will examine the rapid design, development, and implementation of the RMHive app and its impact on mental health outcomes for health care workers. Findings from the impact evaluation will provide guidance for the integration of EBCD in rapid design and implementation processes. The evaluation will also inform future development and rollout of the app to support the mental health needs of hospital-based health care workers more widely. INTERNATIONAL REGISTERED REPORT DERR1-10.2196/26168
Abstract Background Mental health policies outline the need for codesign of services and quality improvement in partnership with service users and staff (and sometimes carers), and yet, evidence of systematic implementation and the impacts on healthcare outcomes is limited. Objective The aim of this study was to test whether an adapted mental health experience codesign intervention to improve recovery‐orientation of services led to greater psychosocial recovery outcomes for service users. Design A stepped wedge cluster randomized‐controlled trial was conducted. Setting and Participants Four Mental Health Community Support Services providers, 287 people living with severe mental illnesses, 61 carers and 120 staff were recruited across Victoria, Australia. Main Outcome Measures The 24‐item Revised Recovery Assessment Scale (RAS‐R) measured individual psychosocial recovery. Results A total of 841 observations were completed with 287 service users. The intention‐to‐treat analysis found RAS‐R scores to be similar between the intervention (mean = 84.7, SD= 15.6) and control (mean = 86.5, SD= 15.3) phases; the adjusted estimated difference in the mean RAS‐R score was −1.70 (95% confidence interval: −3.81 to 0.40; p = .11). Discussion This first trial of an adapted mental health experience codesign intervention for psychosocial recovery outcomes found no difference between the intervention and control arms. Conclusions More attention to the conditions that are required for eight essential mechanisms of change to support codesign processes and implementation is needed. Patient and Public Involvement The State consumer (Victorian Mental Illness Awareness Council) and carer peak bodies (Tandem representing mental health carers) codeveloped the intervention. The adapted intervention was facilitated by coinvestigators with lived‐experiences who were coauthors for the trial and process evaluation protocols, the engagement model and explanatory model of change for the trial.
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.
Improving access to primary healthcare (PHC) for vulnerable populations is important for achieving health equity, yet this remains challenging. Evidence of effective interventions is rather limited and fragmented. We need to identify innovative ways to improve access to PHC for vulnerable populations, and to clarify which elements of health systems, organisations or services (supply-side dimensions of access) and abilities of patients or populations (demand-side dimensions of access) need to be strengthened to achieve transformative change. The work reported here was conducted as part of IMPACT (Innovative Models Promoting Access-to-Care Transformation), a 5-year Canadian-Australian research program aiming to identify, implement and trial best practice interventions to improve access to PHC for vulnerable populations. We undertook an environmental scan as a broad screening approach to identify the breadth of current innovations from the field. We distributed a brief online survey to an international audience of PHC researchers, practitioners, policy makers and stakeholders using a combined email and social media approach. Respondents were invited to describe a program, service, approach or model of care that they considered innovative in helping vulnerable populations to get access to PHC. We used descriptive statistics to characterise the innovations and conducted a qualitative framework analysis to further examine the text describing each innovation. Seven hundred forty-four responses were recorded over a 6-week period. 240 unique examples of innovations originating from 14 countries were described, the majority from Canada and Australia. Most interventions targeted a diversity of population groups, were government funded and delivered in a community health, General Practice or outreach clinic setting. Interventions were mainly focused on the health sector and directed at organisational and/or system level determinants of access (supply-side). Few innovations were developed to enhance patients' or populations' abilities to access services (demand-side), and rarely did initiatives target both supply- and demand-side determinants of access. A wide range of innovations improving access to PHC were identified. The access framework was useful in uncovering the disparity between supply- and demand-side dimensions and pinpointing areas which could benefit from further attention to close the equity gap for vulnerable populations in accessing PHC services that correspond to their needs.
There is increased recognition that people with lived-experience of mental ill-health ought to be centred in research design, implementation and translation, and quality improvement and program evaluation of services. There is also an increased focus on ways to ensure that co-design processes can be led by people with lived-experience of mental ill-health. Despite this, there remains limited explanation of the physical, social, human, and economic infrastructure needed to create and sustain such models in research and service settings. This is particularly pertinent for all health service sectors (across mental and physical health and social services) but more so across tertiary education settings where research generation occurs for implementation and translation activities with policy and services. The Co-Design Living Labs program was established in 2017 as an example of a community-based embedded approach to bring people living with trauma and mental ill-health and carers/family and kinship group members together with university-based researchers to drive end-to-end research design to translation in mental healthcare and research sectors. The program’s current membership is near to 2000 people. This study traces the evolution of the program in the context of the living labs tradition of open innovation. It overviews the philosophy of practice for working with people with lived-experience and carer/family and kinship group members—togetherness by design. Togetherness by design centres on an ethical relation of being-for that moves beyond unethical and transactional approaches of being-aside and being-with , as articulated by sociologist Zygmunt Bauman. The retrospective outlines how an initial researcher-driven model can evolve and transform to become one where people with lived-experience of mental ill-health and carer/family kinship group members hold clear decision-making roles, share in power to enact change, and move into co-researcher roles within research teams. Eight mechanisms are presented in the context of an explanatory theoretical model of change for co-design and coproduction, which are used to frame research co-design activities and provide space for continuous learning and evolution of the Co-Design Living Labs program.
The use of chiropractic services is widespread, however, little is known about the characteristics of people who seek chiropractic care in Australia. This study compared the characteristics of users and non-users of chiropractic services from a cohort of patients sourced from general medical practice in Victoria, Australia. This is a secondary analysis of baseline screening data from a prospective adult cohort study beginning in 2005. Thirty randomly selected Australian general medical practices mailed out surveys to 17,780 of their patients. Differences were examined between chiropractic users and others, and between chiropractic users who reported a back problem to those who did not. Of 7,519 respondents, 15% indicated they had visited a chiropractor in the last 12 months. Chiropractic users were more likely to have their GP located in a rural location and to be born in Australia; they were less likely to be in the older age group (55–76), to be unemployed or to have a pension/benefit as their main source of income. Chiropractic users were more likely to: have a back problem; use complementary or alternative medication; visit another type of complementary health practitioner or a physiotherapist. They were less likely to take medication for certain health problems (e.g. for high blood pressure, high cholesterol or asthma). No important differences were seen between chiropractic users and non-users for other health problems. People who visited a chiropractor and reported a back problem were more likely to: be a current smoker; have a number of other chronic conditions, including arthritis, hypertension, chronic sinusitis, asthma, dermatitis, depression and anxiety; report taking medications, including antidepressants, analgesics (painkillers and arthritis medication) and complementary or alternative medications. This large cross-sectional study of general medical practice attendees suggests that chiropractors are the most commonly consulted complementary health profession. Chiropractors should ensure they are aware of their patients' health conditions other than musculoskeletal problems and should ensure they are appropriately managed.
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