BELL, EUNICE ANN HERRIMAN; PHD
MICHIGAN STATE UNIVERSITY, 1987
HEALTH SCIENCES, NURSING (0569); EDUCATION, ADMINISTRATION (0514)
This investigation was an attempt to add to the body of research in innovation
diffusion in the sector of
nursing management. The study was designed to answer questions about the effect
of selected factors
on innovation adoption by the chief nursing executive. A major element of innovation
research is the
innovation process and this provided the theoretical framework for the study.
Two levels of variables,
organizational and individual, were operationalized and integrated into the
framework of the Zaltman
model of the innovation process. The first stage of the process, initiation;
with its substages
knowledge-awareness, attitude formation, and decision making, provided the basis
for this study. The
research was planned to survey the population of chief nursing executives of
hospitals in Michigan. The
survey instrument was designed with the assistance of researchers in innovation
diffusion and hospital
administration. A panel of nurses, composed of experts from the field of computer
technology in health
care, developed the list of computerized management applications which comprised
the innovation
index. The data were analyzed using univariate frequencies, Chi-square tests,
correlation coefficients,
and multiple regression statistics. The analysis focused on two questions. First,
what is the significance
of each of the eight bivariate relationships? Secondly, which variables contribute
the most to an
explanation of the variance in the dependent variable? Data from bivariate relationships
revealed a
positive correlation between six of the eight independent variables and the
dependent variable,
innovation adoption. The organizational level variables, size and climate were
significantly related and
fiscal control was not. The individual level variables, role/position, computer
knowledge, professionalism,
and education were significantly related and experience was not. Three multiple
regression equations
were estimated to assess the effects of predictor variables both overall and
by levels. The individual
variables computer knowledge and education were determined to be the strongest
predictors with size a
weaker predictor. The individual level variables were stronger predictors of
innovation adoption by chief
nursing executives than the organizational level variables. Additional findings,
conclusions, and
recommendations are included in the study.
Social
Systems Simulation Group
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