UTAUT for HSS: initial framework to study health IT adoption in the developing countries

Psychometric analysis of a measure of acceptance of new technologies (UTAUT), applied to the use of haptic virtual simulators in dental students

BACKGROUND

The aims of this study are (a) to assess the psychometric quality of an instrument of acceptance of new technologies adapted from the UTAUT model, (b) to validate the UTAUT model as a valid measure to be applied in dental education, and (c) to determine which factors of the UTAUT model predict the behavioural intention of using a haptic virtual simulator (HVS).

METHODS

A cross-sectional design study with a sample of 265 dentistry students was carried out.

RESULTS

Using structural equation modelling, confirmatory factor analysis verified the adequacy of four-factor model, although the only factor that directly predicts behavioural intention is performance expectancy. Internal consistency coefficients of each factor ranged from 0.800 to 0.969.

DISCUSSION

These findings, as well as the predictive power of performance expectancy on behaviour intention, are in line with previous evidence found in the literature.

CONCLUSION

These findings suggest that the UTAUT scale has adequate reliability and construct factorial validity; therefore, UTAUT model could be a valuable approach to assess haptic virtual simulator acceptance in dental education.

Evaluation of effective factors in the acceptance of mobile health technology using the unified theory of acceptance and use of technology (UTAUT), case study: Blood transfusion complications in thalassemia patients

Background: Mobile health or MHealth refers to the use of mobile phone in healthcare services to enhance the health level of people. Before using MHealth, it is necessary to study the effective factors in physicians' adoption and acceptance of technology in the field of thalassemia. Methods: This cross sectional study was conducted using the survey and correlation methods. The statistical population of the study consisted of hematologists who were selected using the convenience sampling method. In this study, 58 questionnaires along with structural equations modeling based on partial least squares were used. SPSS and SMART PLS2 were used for data analysis. P values less than 0.05 were considered as statistically significant. Results: Based on the outcomes of the model from all theories, the coefficient of variation seems to be positive and the possibility of test is lower than 5%. The results indicated that all factors introduced in the proposed model are significantly effective in MHealth technology adoption. Conclusion: In this study, using the inputs from hematologists in hospitals and clinics in Tehran, it was aimed to find the factors affecting the hematologists' decision to use mobile health technology in reducing the complications of blood transfusion in patients with thalassemia who needed blood transfusion. Thus, plans were made determine to priorities and the existing conditions to implement this new system. Also, the strengths and weaknesses of each factor were measured to improve the weaker factors. UTAUT was used to determine the acceptance factors. After reviewing the results, the use of this model is recommended to physicians.