Wipa Sae-Sia

Determinants of resilience among people who sustained spinal cord injury from the 2015 earthquake in Nepal

Study design:Cross-sectional study.Objectives:To assess the level of resilience, compare resilience by demographic and injury-related characteristics, and identify significant determinants of resilience in Nepalese people who sustained spinal cord injury (SCI) from the 2015 earthquake.Setting:Spinal Injury Rehabilitation Center, Kavre and 14 communities in Nepal.Methods:Eighty-two participants were included using a convenience sampling technique. A demographic and injury-related questionnaire was used to identify the characteristics of the participants. The Connor-Davidson Resilience Scale was used to measure resilience. Linear regression analysis was performed to determine the demographic and injury-related factors that contribute to resilience.Results:Almost 54% of the participants had low level of resilience. Independent samples t-tests and ANOVA showed that participants with higher resilience outcome were more likely to be male, employed, paraplegic level of injury and pain free. The regression analysis revealed that only gender was a unique determinant of resilience (β=0.38, t=3.40, P=0.001) in Nepalese with earthquake-related SCI.Conclusion:More than half of Nepalese who sustained SCI from the 2015 earthquake in Nepal had not achieved a high level of resilience 2 years later. Gender was a significant determinant of resilience. The results highlighted the importance of providing appropriate intervention and allocating continuing support to the Nepalese people with SCI. A further longitudinal study is recommended to determine predictive factors of the dynamic nature of resilience.

Predicting quality of life among family caregivers of people with spinal cord injury having chronic low back pain in Nepal: a cross-sectional pilot study

Study designDescriptive cross-sectional study.ObjectiveThis study aims to determine the factors predicting quality of life among Nepalese family caregivers of people with spinal cord injury (SCI) having low back pain.SettingEight districts of the Bagmati Zone of Nepal.MethodsSixty-five family caregivers of people with SCI having chronic low back pain were recruited from January to March 2017. The factors examined as independent variables included monthly household income, daily caregiving hours, functional independence of people with SCI, low back pain intensity, and functional disability of family caregivers. The measures were the Family Caregivers’ and Spinal Cord Injury Patients’ Demographic Form, the Modified Barthel Index, the Pain Intensity Scale, the Oswestry Disability Index, and the World Health Organization Quality of Life-BREF Nepali version. A hierarchical multiple regression analysis was used to predict quality of life.ResultsFunctional independence of people with SCI, monthly household income, and functional disability of family caregivers with chronic low back pain could significantly predict quality of life at 41% (adjusted R2 = 0.41, Fchange (3,59) = 11.02, p < 0.01). The functional dependence of persons with SCI was the most powerful factor contributing to QoL of caregivers (β = 0.36, p < 0.01) followed by monthly household income (β = 0.30, p < 0.01) and caregivers’ functional disability (β = –0.28, p < 0.01).ConclusionThe findings suggested that in order to improve the quality of life of family caregivers who have chronic low back pain while providing care for people with SCI during a long period, health professionals should strengthen the functional independence of the patients after discharge to reduce the functional disability of the caregivers. Financial support is needed for caregivers who have a low income.

Response to Correspondence by Fakhr-Movahedi et al.

1. Numerical Rating Scale: There are reasons underpinning our decision not to do the reliability testing of the Numerical Rating Scale (NRS). First, the NRS has been evidenced and recommended as one of the most reliable and universal tools to assess pain in persons who can communicate [1, 2]. Second, the NRS has been widely used in Nepal and a recent study conducted among Nepalese with musculoskeletal pain yielded good validity, reliability, and responsiveness using the NRS [3]. Third, pain intensity was collected in terms of injury-related information of the participants but not as an outcome measure in our study; reliability testing in our study focused on the main research instrument (Connor–Davidson Resilience Scale (CD-RISC) 25). However, this inquiry raises our awareness of examining the reliability of the instruments when using a new sample. We are very concerned about this point and we actually accept this as one of the limitations of our study. 2. Multivariate versus multiple regression: In our study, we have a single dependent variable (resilience). As the first step, we used simple linear regression (univariate analysis). Then we used multiple regression (multivariate analysis) entering only the factors that were significant in the simple regression [4]. It is notable that multiple regression is one kind of multivariate statistics. The term ‘multivariate regression’ was then used interchangeably with multiple regression [5]; therefore, we used this term in our study. We also believe it would be unequivocal to the readers to use multiple regression in lieu of multivariate regression. 3. Cut-off points of resilience: Since there are no published standard cut-off scores for the CD-RISC, we took the mean resilience score from a previous study as a reference and applied the cut-off scores to the similar context in Nepal since India and Nepal are neighboring countries. Moreover, both of these two countries are eastern and developing countries that are quite similar in a cultural context. In addition, the study by Rajan et al. was conducted among the parents (age range 21–60 years) of children with disabilities rather than the children. In the manual of CD-RISC, both of the samples belong to a group of people who are under stress [6]. Furthermore, participants from both studies were adults and mostly from rural areas. In addition, it may not be helpful to use the score distribution in our own sample to describe proportions of the participants as low or high. Hence, we used the reference from the previous similar study.

Development of a Trauma-based Continuing Care Model for Enhancing Care Outcomes in Social Unrest Area: A Case Study

Background: Improving care outcomes in trauma patients is regarded as important and linked to an appropriate model of care particularly in social unrest area where there are limited resources and accessibility after discharge. To facilitate prompt management to improve patient recovery or quality of life and decrease some complications, a specific model of continuing care for those trauma survivors is required. Objective: This participatory action research (PAR) aimed to develop the trauma-based continuing care model (TCCM) for enhancing care outcomes in trauma patients affected from Social Unrest area. Method: A three-phase of PAR design was implemented with stakeholders in both hospital and community services related to care for trauma survivors and their families. In the first phase, 11 trauma survivors were interviewed and 3 focus group discussions with nurses and related health care staff were conducted to identify existing systems and problems encountered. The second phase consisted of two workshops, involving 20 key informants and allied health staff for the purpose of developing the model. The final phase evaluated the initial effects of the model after implementing with 20 patients by measuring the care process and outcomes such as nurses’satisfaction, patients’quality of life, patients’self care ability, caregivers’ ability to care. Data were analyzed using descriptive statistics for care outcomes and content analysis for the care process. Result: The model consisted of a) trauma-care process through a trauma nurse-initiated discharge planning program b) patient-family follow up. With the PAR process, the following steps included 1) preparing the multidisciplinary health care team including patient and family caregivers, 2) organizing the system, identifying individual role and function for continuing care, and 3) collaborating with community support network for patient and family management. The main strategies to drive all process were teamwork involvement, care coordination, and staff education. The model could enhance both health care staff and family caregivers in providing better care. In this study, most patients were able to manage themselves. Twenty patients and 10 family caregivers were satisfied with the care process and obtained better outcomes regarding health status and quality of life. In addition, the developed trauma nurse-initiated discharge planning program was also discussed for further implication. Conclusion: The key success was derived from trauma nurse-initiated discharge planning process and collaborating with community support network. To enhance the sustainability of the model, care managed by enhancing networking of community nurse, patient and family after discharge needs to be further explored.