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BackgroundOpen design formats for mobile apps help clinicians and stakeholders bring their needs to direct, co-creative solutions. Palliative care for patients with advanced cancers requires intensive monitoring and support and remains an area in high need for innovation.ObjectiveThis study aims to use community-partnered participatory research to co-design and pretest a mobile app that focuses on palliative care priorities of clinicians and patients with advanced cancer.MethodsIn-person and teleconference workshops were held with patient and family stakeholders, researchers, and clinicians in palliative care and oncology. Question prompts, written feedback, semistructured interviews, and facilitated group discussions identified the core palliative care needs. Using Chorus, a no-code app-building platform, a mobile app was co-designed with the stakeholders. A pretest with 11 patients was conducted, with semistructured interviews of clinician and patient users for feedback.ResultsKey themes identified from the focus groups included needs for patient advocacy and encouragement, access to vetted information, patient-clinician communication support, and symptom management. The initial prototype, My Wellness App, contained a weekly wellness journal to track patient-reported symptoms, goals, and medication use; information on self-management of symptoms; community resources; and patient and caregiver testimonial videos. Initial pretesting identified value in app-based communication for clinicians, patients, and caregivers, with suggestions for improving user interface, feedback and presentation of symptom reports, and gamification and staff coordinators to support patient app engagement.ConclusionsThe development of a mobile app using community-partnered participatory research is a low-technology and feasible intervention for palliative care. Iterative redesign and user interface expertise may improve implementation.

Individuals with serious mental illness experience changes in their clinical states over time that are difficult to assess and that result in increased disease burden and care utilization. It is not known if features derived from speech can serve as a transdiagnostic marker of these clinical states. This study evaluates the feasibility of collecting speech samples from people with serious mental illness and explores the potential utility for tracking changes in clinical state over time. Patients (n = 47) were recruited from a community-based mental health clinic with diagnoses of bipolar disorder, major depressive disorder, schizophrenia or schizoaffective disorder. Patients used an interactive voice response system for at least 4 months to provide speech samples. Clinic providers (n = 13) reviewed responses and provided global assessment ratings. We computed features of speech and used machine learning to create models of outcome measures trained using either population data or an individual's own data over time. The system was feasible to use, recording 1101 phone calls and 117 hours of speech. Most (92%) of the patients agreed that it was easy to use. The individually-trained models demonstrated the highest correlation with provider ratings (rho = 0.78, p

The coronavirus pandemic of 2019 (COVID-19) has created unprecedented changes to everyday life for millions of Americans due to job loss, school closures, stay-at-home orders and health and mortality consequences. In turn, physicians, academics, and policymakers have turned their attention to the public mental health toll of COVID-19. This commentary reporting from the field integrates perceptions of academic, community, health system, and policy leaders from state, county, and local levels in commenting on community mental health needs in the COVID-19 pandemic. Stakeholders noted the broad public health scope of mental health challenges while expressing concern about exacerbation of existing disparities in access and adverse social determinants, including for communities with high COVID-19 infection rates, such as African Americans and Latinos. They noted rapid changes toward telehealth and remote care, and the importance of understanding impacts of changes, including who may benefit or have limited access, with implications for future services delivery. Needs for expanded workforce and training in mental health were noted, as well as potential public health value of expanding digital resources tailored to local populations for enhancing resilience to stressors. The COVID-19 pandemic has led to changes in delivery of health care services across populations and systems. Concerns over the mental health impact of COVID-19 has enhanced interest in remote mental care delivery and preventive services, while being mindful of potential for enhanced disparities and needs to address social determinants of health. Ongoing quality improvement across systems can integrate lessons learned to enhance a public mental well-being.

This manuscript presents the protocol and participatory planning process for implementing the Community Resilience Learning Collaborative and Research Network (C-LEARN) study. C-LEARN is designed to determine how to build a service program and individual client capacity to improve mental health-related quality of life among individuals at risk for depression, with exposure to social risk factors or concerns about environmental hazards in areas of Southern Louisiana at risk for events such as hurricanes and storms. The study uses a Community Partnered Participatory Research (CPPR) framework to incorporate community priorities into study design and implementation. The first phase of C-LEARN is assessment of community priorities, assets, and opportunities for building resilience through key informant interviews and community agency outreach. Findings from this phase will inform the implementation of a two-level (program-level and individual client level) randomized study in up to four South Louisiana communities. Within communities, health and social-community service programs will be randomized to Community Engagement and Planning (CEP) for multi-sector coalition support or Technical Assistance (TA) for individual program support to implement evidence-based and community-prioritized intervention toolkits, including an expanded version of depression collaborative care and resources (referrals, manuals) to address social risk factors such as financial or housing instability and for a community resilience approach to disaster preparedness and response. Within each arm, the study will randomize individual adult clients to one of two mobile applications that provide informational resources on services for depression, social risk factors, and disaster response or also provide psychoeducation on Cognitive Behavioral Therapy to enhance coping with stress and mood. Planned data collection includes baseline, six-month and brief monthly surveys for clients, and baseline and 12-month surveys for administrators and staff.

Predictive analytics in health is a complex, transdisciplinary field requiring collaboration across diverse scientific and stakeholder groups. Pilot implementation of participatory research to foster team science in predictive analytics through a partnered-symposium and funding competition. In total, 85 stakeholders were engaged across diverse translational domains, with a significant increase in perceived importance of early inclusion of patients and communities in research. Participatory research approaches may be an effective model for engaging broad stakeholders in predictive analytics.

ObjectiveWe describe the rationale, development, and progress on the Community and Patient Partnered Research Network (CPPRN). The CPPRN builds on more than a decade of partnered work and is designed to promote health equity by developing partnered research on behavioral health and social risk factors in Los Angeles and New Orleans.SettingA community-academic partnership across Los Angeles County and New Orleans.MethodsReview of rationale, history, structure, activities and progress in applying community partnered participatory research (CPPR) to CPPRN.FindingsPatient and community stakeholders participated in all phases of development, including local and national activities. Key developments include partnered planning efforts, progress on aggregating a large, de-identified dataset across county agencies, and development of an information technology-supported screening approach for behavioral and social determinants in health care, social, and community-based settings.ConclusionThe CPPRN represents a promising approach for research data networks, balancing the potential benefit of information technology and data analytic approaches while addressing potential risks and priorities of relevant stakeholders.

ObjectiveTo assess the feasibility of a novel, partnered technology development process to co-create mobile health applications (apps) addressing community health priorities, using psychoeducation of cognitive behavioral therapy (CBT) principles for enhancing resilience as an example.DesignStakeholder engagement, workgroups, pilot feasibility study using mixed methods during October 2013 through January 2016 over three phases: 1) defining the vision of the project and increasing technical capacity, 2) co-development and pilot testing of the app, and 3) planning for sustainability.SettingAn academic-community partnership in South Los Angeles, California.ParticipantsEight stakeholders; 30 pilot participants from the community.Main outcome measuresQualitative analysis of audio-recordings of the app development process and stakeholder interviews, surveys of stakeholders' perception of the development process, app use data, and feedback from pilot participants.ResultsThe participatory technology development process resulted in creation and pilot-testing of a resiliency-focused text messaging app. Of the 1,107 messages sent, 23 out of 30 (77%) app users responded to explore interactive content. Stakeholders reported increased perceived competency in creating mobile apps and that the process fostered a culture of co-leadership. There was also sustained engagement in mobile app development by stakeholders beyond the initial project period.ConclusionsThis is the first study, to our knowledge, to demonstrate the feasibility of participatory technology development, an approach involving direct participation in the development, tailoring and maintenance of a mobile app by a broad set of stakeholders with high representation from racial/ethnic minorities from an under-resourced community. Participatory technology development is a promising approach for creating sustainable, relevant and engaging health technologies across different technological, clinical and community settings.