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BackgroundThe 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. ObjectiveRMHive 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. MethodsThe 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. ResultsThe 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. ConclusionsThe 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 Identifier (IRRID)DERR1-10.2196/26168

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., (© The Authors.)