Socio-ecological factors supporting resilience in trauma recovery

Abstract

Background Injury mortality rates have declined in many countries largely because of the development of sophisticated Trauma and injury prevention systems and improved patient care. However the morbidity following severe traumatic physical injury is increasingly recognized as an important public health matter. Little is known about injury recovery patterns and associated causes once patients are discharged home to their communities. Here, prevention activities are targeted at the secondary and tertiary levels in community settings, aiming to reduce or eliminate impairment and disability, minimize suffering and pain, and maximize quality of life for irremediable conditions. Studies show that factors in patients’ socio-ecological environments contribute to poor outcomes. Socioeconomic disadvantage, blue collar jobs, and low levels of family, social and community support frequently appear as significant covariates in inception cohort studies of trauma patients. The socio-ecological model is a well-recognized framework for activating prevention strategies. For trauma patients their ‘eco-system’ incorporates resilient and healthy caregivers and families, supportive social networks and community and rehabilitation services. It also encompasses a neighborhood, defined by economic, social and physical properties that provide access to resources, enabling trauma recovery. Variations in individuals’ resilience and in their resilient resources might explain why some people experience better outcomes compared to others, after suffering the same type of adversity. Resilience is rapidly becoming a factor of interest in trauma rehabilitation. It is a positive, protective quality, amenable to interventions, and bolstered by social and environmental factors. Resilience promotion, in rehabilitation could potentially, support people and families exposed to severe trauma. The over-arching aim of this thesis is to develop a program of research that investigated ‘resilience’ as part of the trauma patients’ socio-ecological system. Firstly, resilience at the community level was examined by synthesizing the research evidence of the effectiveness of socio-ecological resilience rehabilitation programs on the outcomes of people sustaining traumatic physical injuries. Secondly, a form of ‘neighborhood’ resilience characterized by the physical, social and economic aspects of patient’s neighborhoods were analysed in relation to rurality and short-term patient outcomes. And finally, resilience was examined in a cohort of primary informal caregivers of patients sustaining severe traumatic musculoskeletal injuries Methods A systematic review was conducted to identify the effectiveness of multifaceted community socio-ecological rehabilitation programs aimed at fostering resilience. Twenty-one studies were retrieved and reviewed (11,904 participants). The results of 19 randomised intervention studies of moderate to high methodological quality were then pooled using a random-effects meta-analysis. Mean differences for continuous outcomes and risk ratios for outcomes including return to work (RTW), self efficacy and stress reduction were calculated. To examine the influence of factors characterizing neighborhood resilience on trauma patients’ outcomes, data were accessed from the Gold Coast University Hospital Trauma Registry. A cross-sectional study design was employed, and geocoding methods enabled the creation of two area-level explanatory variables describing relative Socioeconomic Disadvantage, and remoteness from services. These variables were linked to individual patients represented on the Trauma Registry, along with data items including age, injury severity, anatomical region, discharge disposition, number of comorbidities, injury mechanism, postcode of injury occurrence, and the first provider of care. From this study sample, the association of these two neighborhood indices with inpatient outcomes was analysed using a retrospective cohort design. Outcome variables were acute length of stay days (ALSD) and inpatient mortality. Step-wise multivariable negative binomial regression and proportional hazards regression analyses were conducted, adjusting for age, injury severity, mechanism and comorbidity and sites of injury. Finally, a prospective cohort study was designed to examine resilience in primary, informal caregivers of severe musculoskeletal trauma patients. Patient and caregiver dyads were recruited, shortly after the injury event and followed up three months later. Resilience was measured, using the Connor Davidson resilience scale (CD-RISC 10). Primary outcomes were caregiver burden and quality of life measured respectively, using the Caregiver Strain Index and the Short Form Version 12 (SF-12) Health Survey. Results Resilience based community rehabilitation: Resilience rehabilitation programs significantly increased the likelihood of RTW (OR 2.09 95% CI 0.99-4.44 p=0.05), decreased the time taken to RTW (Mean difference -7.80, 95% CI -13.16 - -2.45 p=<0.001), and increased levels of self-efficacy (Mean difference 5.19, 95% CI 3.12 - 7.26 p<0.001). Favourable RTW outcomes resulted from programs involving workplace support (p<0.001) compared to programs without this support. Positive RTW outcomes were more common in people with musculoskeletal or orthopedic injuries compared with brain injuries (p=0.02). Neighborhood resilience: 1025 patients were available for analysis, of which 77% were male. The mean age was 45 (SD 19.46) and median ISS was 17 (IQR=12). Increasing relative socioeconomic disadvantage was statistically significantly, and positively associated with remoteness of residence (X2=41.61, p<0.001) remoteness of injury location (X2=19.73, p<0.001), and number of comorbidities (KW H Statistic=11.26, p=0.01). Of those who received initial care from a regional hospital, there is a significant and positive trend according to increased likelihood of being disadvantaged category compared with those treated at the major trauma center. (X2=14.14, p=0.003). After adjusting for age, sex, injury severity and remoteness of injury location, a positive gradient of increasing disadvantage according to geographical remoteness of residence was evident, with a six fold increase in the odds of being in the most disadvantaged category, compared to the least disadvantaged (OR 6.21, 95% CI 3.07-12.57, p<0.001). Based on the above cohort of trauma patients, increased hazard of inpatient mortality was found for age group (75+), (HR 3.53, 95% CI 1.77-7.11 p=0.003), higher ISS (HR 5.27, 95% CI 2.78-10.02, p<0.001), and injury mechanisms related to intentional self-harm or assault (HR 2.72, 95% CI 1.48-5.03, p=0.001). Increased risk for longer ALSD was evident for: older age, namely 65-74 (RR 1.37, 95% CI 1.10-1.83), head injury (HR 1.36 95% CI 1.15-1.62, p<0.001), extremity injuries (RR 1.62 95% CI 1.36-1.94 p<0.001), higher ISS (RR 2.05, 95% CI 1.76-2.39, p<0.001), and discharge to rehabilitation facility (RR 1.75 95% CI 1.43-2.14, p<0.001). Caregiver resilience: Fifty-three (77%) eligible patient/carer dyads participated, with an attrition rate of 28%. At baseline, caregiver resilience was statistically significantly (p<0.05) associated with their physical health, community support and family resilience. Significant reductions from baseline were found at follow up, for levels of resilience, mental health, physical exercise and community support. In multiple regression models, caregiver resilience independently predicted lower caregiver burden (β= -0.74, p=0.008) and higher levels of patient physical health and function (β= -0.69, p=0.003). Conclusion Trauma patients recover in a highly contextual environment where family, community and neighborhood factors are integral to successful patient outcomes. These studies showed that strategies aimed at addressing the public health burden of trauma disability should target the multiple and interacting layers of patients’ socio-ecological environment ensuring that all have capacity to support resilient recovery after severe traumatic injuries.