Perceived Factors Influencing Adoption Of Electronic Data Capture Technologies In Health Research Institutions In Kisumu County, Kenya
With the advent of Information and Communication Technologies (ICTs) and the legislative ICT policy guidelines and targets, researchers in the Health Sector are inclined to adopt electronic data capture technologies. This study entitled “Perceived factors influencing adoption of electronic data capture technologies in selected health research institutions in Kisumu County” sought to enumerate those factors that lead to reluctance by such institutions to adopt such promising technologies. The study was guided by five objectives namely: to establish the influence of initial start-up cost, user friendliness, privacy, security, and institutional leadership in adoption of electronic data capture technologies in health research institutions in Kisumu County. The study adopted a cross-sectional survey design and mixed methods concurrent approaches to gather responses from 216 respondents purposively selected from health research institutions in the study population. A semi-structured questionnaire with a 5-point Likert scale was used. Data was then entered using a statistical package Statistical Package for Social Scientists (SPSS v20) software with appropriate codes and variable specifications and counter-checked for possible erroneous entries. Data analyzed based on the themes of research objectives. The specific effects of independent variables vis-à-vis dependent variable were tested through multivariate analysis. The test of hypotheses to determine the level of significance of an independent variable against the dependent variable were tested through multiple regression analysis and correlation. The significance level was set at probability p< 0.05 for every statistical set. For the parametric data, Pearson’s product Moment Correlation Coefficient (r) and regression R2 analysis was used. The influence of moderating variable on the relationship between the independent and dependent variables were derived by using Regression R2. Pilot testing to ascertain the validity and reliability of research instrument was done prior to the study. The respondent rate stood at 88% with more females 118(54.6%) than males participating in this survey. No significant relationship exists for the EDC start-up cost and adoption of EDC technologies. A linear relationship F (5, 20) =12.20, p<0.05 exists between adoption of EDC technologies and factors influencing its adoption in the study setting. Three of the predictors, access to EDC technologies (β=0.072), institutional leadership (β=0.193), privacy and security of EDC technologies (β=0.139) and user-friendliness of EDC technologies (β=0.339) have positive influence on the adoption of EDC technologies in selected health research institutions in Kisumu County, western Kenya. However, initial start-up cost of EDC technologies (β=-0.011) had negative coefficients. The conclusion of the study is that institutional leadership, user friendliness of EDC technologies and data security have strong influence on adoption of EDC technologies in health research institutions in Kisumu County. …. There is need for further research on financial modelling on either electronic and paper based methods of data collection or a combination of both.
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