The Applicability of the Modified Technology Acceptance Model (TAM) on the Sustainable Adoption of eHealth Systems in Resource-Limited Settings
BACKGROUND: The implementation of eHealth systems with a trial-and-error approach is very expensive and unsuccessful. So, this study aims to examine the constructs and relationships of the modified technology acceptance model (TAM) to determine whether it can be applied to assess health professional...
Autores principales: | , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Dove
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7721313/ https://www.ncbi.nlm.nih.gov/pubmed/33299320 http://dx.doi.org/10.2147/JMDH.S284973 |
Sumario: | BACKGROUND: The implementation of eHealth systems with a trial-and-error approach is very expensive and unsuccessful. So, this study aims to examine the constructs and relationships of the modified technology acceptance model (TAM) to determine whether it can be applied to assess health professional’s behavioral intention to adopt eHealth systems in resource-limited settings or not. METHODS: The institutional-based cross-sectional study design was conducted among a total of 384 healthcare professionals in referral hospitals of Amhara regional state, Ethiopia. Self-administered questionnaire was used to collect the data, and the data were entered using Epi-info version 7 and the descriptive data were analyzed using SPSS version 25. Structural equation modeling, using AMOS 22, was also applied to describe and validate the degree of relationships between variables. RESULTS: The findings of the structural equation modeling (SEM) indicate that perceived usefulness has a significant influence on attitude (β =0.298, P<0.01) and intention to use eHealth (β =0.387, P<0.01). Perceived ease of use has significant influence on perceived usefulness (β=0.385, P<0.05) and attitude (β=0.347, P<0.05) and intention to use eHealth (β=0.339, P<0.01). Technical infrastructure has significant influence on attitude (β =0.412, P<0.01) and intention to use eHealth (β =0.355, P<0.01). The staffs IT experience has a significant influence on perceived usefulness (β =0.595, P<0.01) and attitude (β =0.267, P<0.05), but the effect of IT experience on the intention to use eHealth was not significant. Among all the constructs, healthcare professionals attitude towards eHealth showed the strongest effect on the intention to use eHealth systems (β = 0.52, P<0.01). CONCLUSION: Overall, this model describes 56.2% of the variance in behavioral intention to use eHealth systems. Therefore, the implementers should give priority in enhancing the organizations technical infrastructure, staff’s IT skill, and their attitude towards eHealth by giving continuous support. |
---|