# Integrative Factors of E-Health Laboratory Adoption: A Case of Indonesia
## 6 Discussion
\begin{table}
\begin{tabular}{c c c c c} \hline \hline  & **Hypothesis** & **(\beta)** & **tStatistics** & **Conclusion** \\ \hline H1 & Task Characteristics \(>\) Task Technology Fit & 0.238 ** & 2.492 & Hypothesis accepted \\ H2 & Technology Characteristics \(>\) Task Technology Fit & 0.642 ** & 6.912 & Hypothesis accepted \\ H3 & Task Technology Fit \(>\) Perceived Usefulness & 0.183 ** & 2.872 & Hypothesis accepted \\ \hline H4 & Task Technology Fit \(>\) Perceived Base of Use & -0088 & 0.671 & Hypothesis rejected \\ H5 & Information Quality \(>\) Perceived Usefulness & 0.257 ** & 2.79 & Hypothesis accepted \\ H6 & Information Quality \(>\) Perceived Base of Use & 0.240 ** & 3.785 & Hypothesis accepted \\ H7 & Accessibility \(>\) Perceived Usefulness & 0.261 ** & 3.348 & Hypothesis accepted \\ H8 & Accessibility \(>\) Perceived Base of Use & 0.220 ** & 3.065 & Hypothesis accepted \\ \hline H9 & Design \(>\) Perceived Usefulness & -0001 & 0.001 & Hypothesis rejected \\ H10 & Design \(>\) Perceived Base of Use & 0.472 ** & 5.801 & Hypothesis accepted \\ H11 & Personal Innovativeness \(>\) Perceived Usefulness & 0.279 ** & 3.215 & Hypothesis accepted \\ \hline H12 & Personal Innovativeness \(>\) Perceived Base of Use & 0.085 & 1.493 & Hypothesis rejected \\ H13 & Perceived Usefulness \(>\) Adoption & 0.550 ** & 7.856 & Hypothesis accepted \\ H14 & Perceived Base of Use \(>\) Adoption & 0.153 ** & 2.14 & Hypothesis accepted \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Hypothesis testing result. laboratory adoption. The difference in this hypothesis came from the quality of information, accessibility, and design to explain the perceived ease of use in e-health laboratories. The results obtained were positive and significant on the quality of information, and these results were similar to the results of previous studies [70; 88]. Positive and significant results of accessibility to perceived ease of use in this study were similar to the results of previous studies [94; 96]. The design showed positive and significant results on perceived ease of use; these results were in line with the research in [100]. Whereas TTF and personal innovativeness did not support this model, the insignificant results on personal innovativeness were contrary to the results of the study [70; 71; 106] which showed significant results on the perceived ease of use. A focus on the insignificant results between TTF and the perceived ease of use in e-health laboratory adoption showed that these results were different from the results of the study [37; 77; 79; 118]. The four previous studies found that TTF influenced the perception of ease of use. This different result was probably due to the current reason that users did not have many e-health laboratory options to use since this laboratory service was still a new service in Indonesia. This could reveal the relationship between TTF and perceived ease of use which was not significant. The research model explained 41.7% of variations in e-health laboratory adoption. Based on the results, we believe that perceived usefulness and perceived ease of use supported efforts in e-health laboratory adoption. If e-health laboratory users felt that the service matches their perceived benefits and ease of use is felt by them, then they would voluntarily adopt e-health laboratory services. These results also indicated that adoption in e-health laboratories allowed for further exploration to find out other variations of variables that supported users in adopting e-health laboratories. The implications of research on theory and practice are summarized below.