Abstract

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.

Highlights

  • There are substantial health impacts from environmental disasters, including exacerbation of pre-existing illnesses, risk from exposure to toxins, injury, increased risk for chronic illnesses from aggravation of structural determinants of health [1,2,3,4,5,6,7] and threats to mental health [8,9,10,11,12,13]

  • Healthcare and community-based programs that are assigned to Community Engagement and Planning (CEP) and Technical Assistance (TA) will both receive training and support for implementation of an expanded model of evidence-based depression collaborative care that addresses social determinants and disaster readiness

  • CEP supports a series of biweekly to monthly meetings to develop network and individual program capacity, prepare stakeholders as co-leads, and create a written training plan following Community Partnered Participatory Research (CPPR) principles [49,64]

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Summary

Introduction

There are substantial health impacts from environmental disasters, including exacerbation of pre-existing illnesses, risk from exposure to toxins, injury, increased risk for chronic illnesses from aggravation of structural determinants of health [1,2,3,4,5,6,7] and threats to mental health [8,9,10,11,12,13]. The literature cited above on resilience in the context of social determinants suggests employing a socio-ecological framework to promote resilience to multiple types of adversity, as disasters and their impacts occur in the context of pre-existing individual, social, and environmental factors [46] Within such a framework, maintaining mental health-related quality of life by addressing depressive symptoms that compromise diverse areas of functioning may facilitate individual and community capacities to activate protective factors—consistent with the Sendai Framework for Disaster Risk. The design was developed in full partnership with community stakeholders

Aims
Design
Community
Methods
Interventions
CEP for Coalitions
TA for Individual Programs
Individual-Level Mobile Apps
Measures
Randomization
Communities
Programs
Human Subjects Protection
Power Calculations
Proposed Analysis
Qualitative Analysis
Linguistic Predictors
Mixed-Methods Analyses
Partnered Synthesis
Discussion
Conclusions
Full Text
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