Open Access
American Research Journal of Humanities and Social Sciences
ISSN (Online): 2378-7031
DOI: 10.46568/arjhss
Emotional Intelligence and Social Support as Predictors of Life Satisfaction among Hospital workers
Abstract
The study investigated emotional intelligence and social support as predicators of life satisfaction
among hospital workers in Lagos, State, Nigeria. The purpose of his study is to investigate the relationship
between emotional intelligence, and social support as predictors of life satisfaction among hospital workers. Life
satisfaction was explained using Veenhoven‟s (1984) Quality of Life (QOL) Model; Emotional Intelligence was
explained with the Emotional Intelligence Model by Salovey. Two direct research hypotheses were formulated. A
cross-sectional survey design was adopted in the study. Participants (hospital workers) across various grades of
each of the selected hospital were accidentally sampled. The dependent variable is life satisfaction. The predictor
variables are emotional intelligence, and social support. This study was conducted using, expost facto factorial
design since it attempted to explain effect based on precursory condition, to determine the influence of a variable
on another variable. Doctors and nurses in Lagos state metropolis, Nigeria constitutes the population of this study.
The result of the study indicated that emotional intelligence significantly predicted life satisfaction (β= 0.473, p <
0.01). The result confirmed hypothesis 1, therefore, the hypothesis was accepted. The prediction of life
satisfaction by social support was significant (β= 0.872, p < 0.01). The finding confirm hypothesis 2 and it was
accepted. The result also indicated that emotional intelligence, and social support jointly contributed a significant
variance of 84.6% to the total variance noted in life satisfaction among health workers [F (2, 183) = 242.342, p <
0.01]. Based on the findings of this study, the researcher recommends as that healthcare practice needs more
evidence that is proved by scientific research results in other to establish a cause and effect relationship among
study variables.