PREDICTORS (MICHIGAN)

                         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.


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