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Information Systems Frontiers

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18.09.2017

Intention to Use a Mobile-Based Information Technology Solution for Tuberculosis Treatment Monitoring – Applying a UTAUT Model

verfasst von: Ravi Seethamraju, Krishna Sundar Diatha, Shashank Garg

Erschienen in: Information Systems Frontiers | Ausgabe 1/2018

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Abstract

There are 2.2 million cases of tuberculosis (TB) in India, with an economic burden of $3 billion per year. Efficient monitoring of TB treatment is critical and the Indian Government’s current reliance on a pen and paper system for monitoring patients’ adherence to treatment is neither effective nor scalable. Employing the unified theory of acceptance and use of technology model (UTAUT) as its theoretical foundation, this study investigates the factors influencing the acceptance and use of a mobile-based IT solution for TB treatment monitoring. Data was collected from a survey of healthcare professionals working in TB treatment clinics and analysed using partial least squares structural equation modelling. Four constructs in the UTAUT model, effort expectancy (EE), facilitating conditions (FC), performance expectancy (PE) and social influence (SI) – were found to significantly and positively influence healthcare professionals’ behavioral intention to use the proposed mobile-based IT solution, and explained 56% of the variance. Importantly, our study validates the predictive capabilities of the UTAUT model in public health service delivery context in a developing country.

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Achanta, S., Jaju, J., & Kumar, A. (2013). Tuberculosis management practices by private practitioners in Andhra Pradesh, India. PloS One, 13, e71119.CrossRef

Agarwal, R., Gao, G., Des Rodches, C., & Jha, A. K. (2010). The digital transformation of healthcare: Current status and the road ahead. Information Systems Research, 21(4), 796–809.CrossRef

Ajzen, I. (1991). The theory of planned behaviour. Organizational Behaviour and Human Decision Processes, 50(2), 179–211.CrossRef

Alawadhi, S., & Morris, A. (2009). Factors influencing the adoption of e-government services. Journal of Software, 4(6), 584–590.CrossRef

Alvesson, M., & Karreman, D. (2007). Constructing mystery: empirical matters in theory development. Academy of Management Review, 3(4), 1265–1281.CrossRef

Anna, V., Jose-Maria, B., Maria-Teresa, D., Caterina, G., Consolaxion, D., Dulcis, S., et al. (2004). The role of mobile phones in improving vaccination rates in travellers. Preventive Medicine, 38, 503–509.CrossRef

Armstrong, J. S., & Overton, T. S. (1977). Estimating Nonresponse bias in Mail Surveys. Journal of Marketing Research, 14, 396–402.CrossRef

Bagchi, K., Hart, P., & Peterson, M. (2004). National culture and information technology product adoption. Journal of Global Information Technology, 7(4), 29–46.CrossRef

Barclay, D. W., Higgins, C. A., & Thompson, R. (1995). The partial least squares approach to causal modeling: personal computer adoption and use as illustration. Technology Studies, 2, 285–309.

Bauer, S., Percevic, R., Okon, E., Meermann, R., & Kordy, H. (2003). Use of text messaging in the aftercare of patients with bulimia nervosa. European Eating Disorders Review, 11, 279–290.CrossRef

Brown, S. A., & Venkatesh, V. (2005). Model of adoption of technology in households: a baseline model test and extension incorporating household life cycle. MIS Quarterly, 29(3), 399–426.CrossRef

Brown, S. A., Kelly, H., & Schwar, A. (2006). Reflections on the role of theoretical extensions in the IS discipline: special issue introduction. The Data Base for Advances in Information Systems, 37(2–3), 8–14.CrossRef

Brown, S. A., Dennis, A. R., & Venkatesh, V. (2010). Predicting collaboration technology use: integrating technology adoption and collaboration research. Journal of Management Information Systems, 27(2), 9–53.CrossRef

Burton-Jones, A., & Hubona, G. S. (2006). The mediation of external variables in technology acceptance model. Information Management, 43, 706–717.CrossRef

Carstensen, L. L., Fung, H. H., & Charles, S. T. (2003). Socioemotional selectivity theory and the regulation of emotion in the second half of life. Motivation Emotion, 27(June 2), 103–123.CrossRef

Chang, I. C., Hwang, H. G., Hung, M. C., Lin, M. H., & Yen, D. C. (2007). Factors affecting the adoption of electronic signature: executives’ perspective of hospital information department. Decision Support Systems, 44(91), 350–359.CrossRef

Chau, P. Y. K., & Hu, P. J. (2002). Investigating healthcare professionals’ decisions to accept telemedicine technology: an empirical test of competing theories. Information Management, 39(4), 297–311.CrossRef

Chaudhry, B., Wang, J., Wu, S., Maglione, M., Mojica, W., Roth, E., Morton, S. C., & Shekelle, P. G. (2006). Systematic review: impact of health information technology on quality, efficiency, and costs of medical care. Annals of Internal Medicine, 144, 742–752.CrossRef

Chin, W. W. (2010). How to write up and report PLS analysis. In V. E. Vinzi, W. W. Chin, J. Henseler, & H. Wang (Eds.), Handbook of partial least squares: Concepts, methods and applications in marketing and related fields (pp. 655–690). Berlin: Springer.CrossRef

Cimperman, M., Brencic, M. M., & Trkman, P. (2016). Analysing older users’ home telehealth services acceptance behaviour-applying an Extended UTAUT model. International Journal of Medical Informatics, 90, 22–31.CrossRef

Cohen, J. (1992). A power primer. Psychological Bulletin, 112(1), 155–159.CrossRef

Compeau, D. R., & Higgins, C. A. (1995). Application of social cognitive theory to training for computer skills. Information Systems Research, 6(2), 118–143.CrossRef

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340.CrossRef

Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: a comparison of two theoretical models. Management Science, 35(8), 982–1002.CrossRef

De Vaus, D. A. (2014). Surveys in social research (6th ed.). Sydney: Allen and Unwin.

Downer, S. R., Meara, J. G., & Da Costa, A. C. (2005). Use of SMS text messaging to improve outpatient attendance. The Medical Journal of Australia, 183(7), 366–368.

Dwivedi, Y. K., Rana, N. P., Jeyaraj, A., Clement, M., & Williams, M. D. (2017). Re-examining the Unified Theory of Acceptance and Use of Technology (UTAUT): Towards a Revised Theoretical Model. Information Systems Frontiers. https://doi.org/10.1007/s10796-017-9774-y published online on 8 June 2017.

Fitchett, J. R., MacPherson, P., & Corbett, E. L. (2016). Implementing the end TB strategy and the intersection with the sustainability development goals, 2016-2030. Transactions Royal Society for Tropical Medicine & Hygiene, 110(3), 145–147.CrossRef

Foon, Y. S., & Fah, B. C. Y. (2011). Internet banking in Kuala Lumpur: An application of UTAUT model. International Journal of Business and Management, 6(4), 161–167.

Gagnon, M.-P., Ngangue, P., Gagnon, J.-P., & Desmartis, M. (2016). m-Health adoption by healthcare professionals: a systematic review. Journal of American Medical Information Association, 23, 212–220.CrossRef

Garg, S., & Mony, P. K. (2013). Electronic data capture for health surveys in developing countries: use of a mobile phone based application in Southern India. Indian Journal of Medical Informatics, 7(2), 84–93.

Gefen, D., Rigdon, E. E., & Straub, D. (2011). Editor’s comments: an update and extension to SEM guidelines for administrative and social science research. MIS Quarterly, 35(2), A1–A7.CrossRef

Goodhue, D.L., Lewis, W., Thompson, R. (2006). PLS, Small Sample Size, and Statistical Power in MIS Research. Proceedings of the 39th Hawaii International Conference on System Sciences.

Goodhue, D. L., Lewis, W., & Thompson, R. (2012). Does PLS have advantages for small sample size or non-normal data? MIS Quarterly, 36(3), 981–1001.

Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: indeed a silver bullet. Journal of Marketing Theory and Practice, 19(2), 139–151.CrossRef

Hair, J. F., Sarstedt, M., Ringle, C. M., & Mena, J. A. (2012). An assessment of the use of partial least squares structural equation modelling in marketing research. Journal of the Academy of Marketing Science, 40, 414–433.CrossRef

Hair Jr., J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2014). A primer on partial least squares structural equation modelling. Thousand Oaks: Sage Publications.

Holden, R., & Karsh, B. Z. (2010). The Technology Acceptance Model: its past and its future in health care. Journal of Biomedical Informatics, 43(1), 159–172.CrossRef

Hu, P. J., Chau, P. Y. K., Sheng, O. R. L., & Tam, K. Y. (1999). Examining the Technology Acceptance Model using physician acceptance of telemedicine technology. Journal of Management Information Systems, 16(2), 91–112.CrossRef

Jarosawlski, S., & Pai, M. (2012). Why are inaccurate tuberculosis serological tests widely used in the Indian private healthcare sector? A root-cause analysis. Journal of Epidemial Global Health, 2, 39–50.CrossRef

Johns, G. (2006). The essential impact of context on organizational behavior. Academy of Management Review, 31(2), 386–408.CrossRef

Khechine, H., Lakhal, S., & Ndjambou, P. (2016). A meta-analysis of the UTAUT model: eleven years later. Canadian Journal of Administrative Sciences, 33, 138–152.CrossRef

Kijsanayotin, B., Pannarunothai, S., & Speedie, S. M. (2009). Factors influencing health information technology adoption in Thailand’s community health centres: applying the UTAUT Model. International Journal of Medical Informatics, 78(6), 404–410.CrossRef

Kim, S., Lee, K.-H., Hwang, H., & Yoo, S. (2016). Analysis of the factors influencing healthcare professionals’ adoption of mobile electronic medical record (EMR) using the unified theory of acceptance and use of technology (UTAUT) in a tertiary hospital. BMC Medical Informatcis and Decision Making, 16, 12. https://doi.org/10.1186/s12911-016-0249-8.CrossRef

Kock, N., & Hadaya, P. (2016). Minimum sample size estimation in PLS-SEM: the inverse square root and gamma-exponential methods. Information Systems Journal. https://doi.org/10.1111/isj.12131.

Lapointe, L., & Rivard, S. (2006). Getting physicians to accept new information technology: insights from case studies. Canadian Medical Association Journal, 174(11), 1573–1578.CrossRef

Lee, A. S., & Baskerville, R. L. (2003). Generalizing generalizability in information systems research. Information Systems Research, 14(3), 221–243.CrossRef

Lewis, W., Agarwal, R., & Sambamurthy, V. (2003). Sources of influence on beliefs about information technology use: an empirical study of knowledge workers. MIS Quarterly, 27, 657–678.CrossRef

Melas, C. D., Zampetakis, L. A., Dimopoulou, A., & Moustakis, V. (2011). Modeling the acceptance of clinical information systems among hospital medical staff: an extended TAM model. Journal of Biomed Informatics, 44(4), 553–564.CrossRef

Morris, M. G., Venkatesh, V., & Ackerman, P. L. (2005). Gender and age in technology adoption and usage decisions: toward the emergence of a unisex work force. IEEE Transactions on Engineering Management, 52(1), 69–84.CrossRef

Nunnaly, J. C., & Bernstein, I. H. (1994). Psychometric theory (3rd ed.). New York: McGraw Hill.

Nysveen, H., & Pedersen, P. E. (2016). Consumer adoption of RFID-enabled services. Applying an extended UTAUT model. Information Systems Frontiers, 18(2), 293–314.CrossRef

Oliveira, T., & Martins, M. F. (2011). Literature review of information technology adoption models at firm level. The Electronic Journal of Information Systems Evaluation, 14(1), 110–121.

Pai, M., Yadav, P., & Anupindi, R. (2014). Tuberculosis control needs a complete and patient-centric solution. The Lancet Infectious Diseases, 2, e189–e190. https://doi.org/10.1016/s2214-109X(14)70198-6 Accessed 10 July 2014.

Pai, M., Daftary, A., & Satyanarayana, S. (2016). TB control: challenges and opportunities for India. Transactions Royal Society for Tropical Medicine & Hygiene, 110(3), 158–160.CrossRef

Peng, D. X., & Lai, F. (2012). Using partial least squares in operations management research: a practical guideline and summary of past research. Journal of Operations Management, 30(6), 467–480.CrossRef

Reinartz, W., Haenlein, M., & Henseler, J. (2009). An Empirical Comparison of the Efficacy of Covariance-Based and Variance-Based SEM. International Journal of Research in Marketing, 26(4), 332–344.CrossRef

Ringle, C. M., Sarstedt, M., & Straub, D. W. (2012). Editor’s comments: a critical look at the use of PLS-SEM in MIS Quarterly. MIS Quarterly, 36(1), iii–xiv.

Ringle, C. M., Wende, S., & Becker, J.-M. (2015). SmartPLS3. Boenningstedt: SmartPLS GmgH http://www.smartpls.com.

Rogers, E. M. (1995). Diffusion of innovations. New York: The Free Press.

Sarstedt, M., Henseler, J., & Ringle, C. M. (2011). Multigroup analysis in partial least squares (PLS) path modelling: alternative methods and empirical results. In M. Sarstedt, M. Schwaiger, & C. R. Taylor (Eds.), Measurement and research methods in international marketing (advances in international marketing, volume 22) (pp. 195–218). Bradford: Emerald.CrossRef

Seeman, E., & Gibson, S. (2009). Predicting acceptance of electronic medical records: is the Technology Acceptance Model enough? SAM Advanced Management Journal, 74(4), 21–26.

Seethamraju, R. (2015). Adoption of Software as a Service (SaaS) Enterprise Resource Planning (ERP) systems in Small and Medium Sized Enterprises (SMEs). Information Systems Frontiers, 17(3), 475–492.CrossRef

Soper, D.S. (2017). A-priori sample size calculator for Structural Equation Models [Software]. Available from http://www.danielsoper.com/statcalc. Acessed 6 Feb 2017.

Sun, J., & Qu, Z. (2015). Understanding health information technology adoption: A synthesis of literature from an activity perspective. Information Systems Frontiers, 17(5), 1177–1190.CrossRef

Tanimura, T., Jaramillo, E., Weil, D., Raviglione, M., & Lonnroth, K. (2014). Financial burden for tuberculosis patients in low and middle income countries: a systematic review. European Respiratory Journal. https://doi.org/10.1183/09031936.00193413.

Thompson, R. L., Higgins, C. A., & Howell, J. M. (1991). Personal computing: toward a conceptual model of utilization. MIS Quarterly, 15(1), 124–143.CrossRef

Tornatzky, L. G., & Fleischer, M. (1990). The processes of technological innovation. Lexington: Lexington Books.

Udwadia, Z. F. (2012). MDR, XDR, TDR tuberculosis: ominous progression. Thorax, 67, 286–288.CrossRef

Udwadia, Z. F., Pinto, L. M., & Uplekar, M. W. (2010). Tuberculosis management by private practitioners in Mumbai, India: has anything changed in two decades? PloS One, 5, e12023.CrossRef

van Gemert-Pijnen, J. E., Nijland, N., van Limburg, M., Ossebaard, H. C., Kelders, S. M., Eysenbach, G., et al. (2011). A holistic framework to improve the uptake and impact of eHealth technologies. Journal of Medical Internet Research, 13(4), e111.CrossRef

Vandan, N., Ali, M., Prasad, R., & Kuroiwa, C. (2009). Assessment of doctors’ knowledge regarding tuberculosis management in Lucknow, India: a public–private sector comparison. Public Health, 123, 484–489.CrossRef

Venkatesh, V. (2010). Technology acceptance, summary of technology acceptance models. http://www.vvenkatesh.com/IT/organizations/Theoretical_Models.asp. Accessed 10 Nov 2015.

Venkatesh, V., & Bala, H. (2008). Technology acceptance model 3 and a research agenda on interventions. Decision Sciences, 39(3), 273–315.CrossRef

Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: four longitudinal field studies. Management Science, 46(2), 186–204.CrossRef

Venkatesh, V., & Morris, M. G. (2000). Why don’t men ever stop to ask for directions? Gender, social influence, and their role in technology acceptance and usage behaviour. MIS Quarterly, 24(1), 115–139.CrossRef

Venkatesh, V., & Zhang, X. (2010). Culture and technology adoption: theory and empirical test of the Unified Theory of Acceptance and Use of Technology (UTAUT) in the US vs China. Journal of Global Information Technology Management, 13(1), 5–27.CrossRef

Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: toward a unified view. MIS Quarterly, 27(3), 425–478.CrossRef

Venkatesh, V., Zhang, X., & Sykes, T. A. (2011a). Doctors do too little technology: a longitudinal field study of an electronic healthcare. Journal Information Systems Research, 22(3), 523–546.CrossRef

Venkatesh, V., Sykes, T. A., & Zhang, X. (2011b). Just what the doctor ordered: a revised UTAUT for EMR system adoption and use by doctors. Proceedings of the 44 ^th Hawaii International Conference on System Sciences (pp. 1–10).

Venkatesh, V., Thong, J. Y. L., & Xu, X. (2012). Consumer acceptance and use of information technology: extending the Unified Theory of Acceptance and Use of Technology. MIS Quarterly, 36(1), 157–178.

Wang, Y.-S., & Shih, Y.-W. (2009). Why do people use information Kiosks? A validation of the Unified Theory of Acceptance and Use of Technology. Government Information Quarterly, 26, 158–165.CrossRef

Warshaw, P. R. (1980). A new model for predicting behavioural intentions: an alternative to Fishbein. Journal of Marketing Research, 17(2), 153–172.CrossRef

WHO. (2007). Tuberculosis surveillance and monitoring – Report of an intercountry consultation. World Health Organization (WHO): New Delhi.

WHO (2011). The global plan to stop TB. www.stoptb.org/global/plan/. Accessed 6 Sept 2016.

WHO. (2014). Global Tuberculosis Report 2013. Geneva: World Health Organization (WHO).

WHO (2015). Global tuberculosis report 2015, 20th edition. http://www.who.int/tb/publications/global_report/en. Accessed 8 Sept 2016.

Wong, K. K. (2013). Partial least squares structural equation modeling (PLS-SEM) techniques using SmartPLS. Marketing Bulletin, 24, Technical Note 1, (pp. 1–32). Downloaded from http://marketing-bulletin.massey.ac.nz. Accessed 14 Feb 2017.

Zhang, N., Guo, X., & Chen, G. (2011). Why adoption and use behaviour of IT/IS cannot last? – two studies in China. Information Systems Frontiers, 13(2), 381–395.CrossRef

Titel: Intention to Use a Mobile-Based Information Technology Solution for Tuberculosis Treatment Monitoring – Applying a UTAUT Model
verfasst von: Ravi Seethamraju
Krishna Sundar Diatha
Shashank Garg
Publikationsdatum: 18.09.2017
Verlag: Springer US
Erschienen in: Information Systems Frontiers / Ausgabe 1/2018
Print ISSN: 1387-3326
Elektronische ISSN: 1572-9419
DOI: https://doi.org/10.1007/s10796-017-9801-z

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