Although Haiti has been experiencing natural disasters since the 15th century, nonetheless, the human causalities and infrastructure decimation during the last two decades, notably the 2010 earthquake, have been devastated. This 7.0 magnitude earthquake killed an estimated 200,000 people and left 1.5 million of Haiti’s 10 million people homeless. In rural parts of Haiti, an estimated 100,000 households (or 500,000 individuals) were affected (OxfamAmerica, 2010) Consequently, many rural communal sectors experienced extensive losses of lives, homes, schools, hospitals, businesses, and agricultural infrastructure, with damage estimates at about $2.3 billion (OxfamAmerica, 2010). Despite these adversities, many Haitians continuous to acquire and use education as the tool to improve their economic status.
The World Health Organization suggests that the top nursing credential for entry into practice for nurses should be the bachelor’s degree. Consequently, a United States not-for-profit organization, Promoting Health in Haiti, partnered with the University of Haiti to offer an RN completion program for nurses in Haiti. There are approximately 25 physicians and 11 nurses per 100,000 population. Therefore, nurse with a bachelor's degree will be equipped with more critical-thinking skills and to be able to function more independently to meet the need of an expanding population with less resources. Moreover, nurses with a bachelor's degree will be able to participate in the Nurse Practitioners' program and following completion will be able to relieve the physicians of some of their responsibilities. Most notably, these Nurse Practitioners will be able to provide primary care, a specialty with a dearth of provider.
Although there is a plethora of research examining the impact of natural disaster on resiliency globally, Haitians resiliency process, especially Haitian Nurses, is missing from the scholarly journal and ultimately the academic discourse. Therefore, the purpose of this inquiry is to understand the resiliency process of Haitian Nurses who participate in an RN completion program. The findings from this study have global benefits to educators, especially those who educate under-served population
Purpose
The purpose of this study will be to measure the resiliency of registered nurses in a bachelor’s degree completion program in Haiti., using the Connor-Davidson Resiliency scale-10 items. Furthermore, the study will explore the impact of self-esteem (Rosenberg self-esteem scale), religion (Spiritual Experience survey, and support system (social support survey) on resilience. It is crucial for nursing education to gain an understanding of the factors influencing nurses’ resiliency, to create strategies to increase the retention rate of nurses.
Design
SPSS would be used for statistical analysis. The data analysis plan will be conducted in three phases. First, all study variables will be presented using descriptive statistics, such as, means, standard deviation, and minimum/maximum values for continuous variables (Interval/Ratio level) and frequencies and percentages for categorical variables (Nominal/Ratio level).
Next, a series of bivariate tests (Pearson correlations, One-Way ANOVA, independent samples t-test) will be used to identify which explanatory variables are related to the dependent variable resilience at a statistically significant level (p<.05). The explanatory variables examined will be the possible covariate variables (demographic variables) and independent variables (self-esteem, support, religion). All explanatory variables related to the dependent variable at a statistically significant level will be included in the third phase of analysis, multivariate analysis.
The third phase of data analysis will be multivariate analysis. Specifically, a multiple linear regression model will be used to model resilience as a function of all explanatory variables related to the dependent variable at a significant level in bivariate analysis. The goal of multivariate analysis will be to determine if the independent variables are related to the dependent variable at a statistically significant level, while controlling for the effects of all demographic variables related to the dependent variable at a statistically significant level.
Within the inferential analysis, the parametric test assumptions of normality, linearity, homoscedasticity, and no undue influence of outlier scores will be examined. If there are missing values within the data, an analysis will be completed to determine the amount of data missing and if there are any patters to the missingness (MCAR (missing completely at random), MAR (missing at random), MNAR (missing not at random). According to the result of this examination a proper method to account for the missing data will be chosen. Regarding the psychometric properties of the study instruments, all standardized scales will be examined to be sure sufficient levels of internal consistency are present (Cronbach’s alpha = >.70). In terms of statistical power, the G*power software indicated that for a Pearson’s correlation a large size effect size with power set at .80 and alpha set at .05, would require a sample size of 25 study participants. Thus, the projected sample size of 45 study participants would provide approximately sufficient statistical power for the analysis
Theoretical Framework
Bandura’s Self-Efficacy Theory guides this inquiry. This scholar’s framework defines self-efficacy as one’s belief in his/her capabilities to execute actions to produce positive outcomes. According to Bandura, people's opinions about their efficacy can be developed by four primary sources of influence: mastery of tasks, observation of role models, persuasion of influential people in your life, emotional state, and having the ability to visualize yourself behaving effectively or successfully in a given situation. The underpinning for creating a strong sense of efficacy is through mastery experiences. Successes build a robust belief in one's efficacy. Failures undermine it, especially if failures occur before a sense of efficacy is firmly established. Therefore, this researcher will use Bandura’s Self-Efficacy paradigm to inform educators on factors influencing resiliency in nurses pursuing a BSN completion program.
Data Collection
Data collection will be done January-February 2019, and data analysis February-March 2019.
Findings
Work in progress
See more of: Evidence-Based Practice Sessions: Oral Paper & Posters