Investigating factors influencing the adoption of e-Health in developing countries: A patient’s perspective

References

• World Health Organization. Eastern Mediterranean Region Health Observatory, 2003. http://www.emro.who.int/ehealth/ (accessed 10 January 2014).
   Google Scholar
• Ball, MJ, Lillis J. E-health: Transforming the physician/patient relationship. International Journal of Medical Informatics 2001;61(1):1–10.
   PubMed Web of Science ®Google Scholar
• Ludwick DA, Doucette J. Adopting electronic medical records in primary care: Lessons learned from health information systems implementation experience in seven countries. International Journal of Medical Informatics 2009;78(1):22–31.
   PubMed Web of Science ®Google Scholar
• World Health Organization eHealth Tools and Services. Global Observatory for eHealth Report’ 2006. WHO/EHL/06.1.
   Google Scholar
• Yaylacicegi U, Mitchell S. Differential impacts of four types of EHR implementation on small, medium, and large hospitals. AMCIS 2012 Proceedings; 2012; Seattle, Washington.
   Google Scholar
• Cruickshank J, Packman C, Paxman J. Personal Health Records – Putting Patients in Control. Online available at http://www.2020health.org/2020health/Publications/publications-2012/Public-Health-Records.html ( access June 18, 2014).
   Google Scholar
• Lohman T. Australian e-health spending to top $2 billion in 2010’, 15/04/2010. Online available at: http://www.computerworld.com.au/article/343220/australian_ehealth_spending_top_2_billion_2010/ ( accessed 18 June, 2014).
   Google Scholar
• Mair FS, Carl M, Catherine O, Tracy F, Frank S, Elizabeth M. Factors that promote or inhibit the implementation of e-health systems: An explanatory systematic review. Bulletin of the World Health Organization 2012;90(5): 357–64.
   PubMed Web of Science ®Google Scholar
• Detmer DE. Building the national health information infrastructure for personal health, health care services, public health, and research. BMC Medical Informatics and Decision Making 2003;3(1):1.
   PubMedGoogle Scholar
• Yasnoff WA, Humphreys BL, Overhage JM, Detmer DE, Brennan PF, Morris RW, Fanning, JP. A consensus action agenda for achieving the national health information infrastructure. Journal of the American Medical Informatics Association 2004;11(4):332–38.
   PubMed Web of Science ®Google Scholar
• Wickramasinghe NS, Fadlalla AM, Geisler E, Schaffer JL. A framework for assessing e-health preparedness. International Journal of Electronic Healthcare 2005;1(3):316–34.
   PubMedGoogle Scholar
• Lafky DB, Thomas AH. Personal health records Consumer attitudes toward privacy and security of their personal health information. Health Informatics Journal 2011;17(1): 63–71.
   PubMed Web of Science ®Google Scholar
• Wilkowska W, Martina Z. Privacy and data security in E-health: Requirements from the user’s perspective. Health Informatics Journal 2012;18(3):191–201.
   PubMed Web of Science ®Google Scholar
• Demiris G, Hilaire T, Jaime B, Thai L, Shomir C, Jane C. Older adults’ acceptance of a community-based telehealth wellness system. Informatics for Health and Social Care 2012;38(1):27–36.
   PubMed Web of Science ®Google Scholar
• Chhanabhai P, Holt A. Consumers are ready to accept the transition to online and electronic records if they can be assured of the security measures. Medscape General Medicine 2007;9(1):8.
   PubMedGoogle Scholar
• Australian Governetment ComlLaw Personally Controlled Electronic Health Records Act 2012. http://www.comlaw.gov.au/Details/C2012A00063 (accessed 18 June, 2014).
   Google Scholar
• U.S Department of Health & Human Services, 2013 HHS HIPAA: Health Insurance Portability and Accountability Act. http://www.ama-assn.org/ama/pub/physician-resources/solutions-managing-your-practice/coding-billing-insurance/hipaahealth-insurance-portabilityaccountability-act.page? (accessed 18 June, 2014).
   Google Scholar
• McConnell, RR, Shields, T, Drury, P, Kumekawa, J, Louw, J, Fereday, G, Nyamai-Kisia, C. Improving health, connecting people: The role of ICTs in the health sector of developing countries. A framework paper, 2006.
   Google Scholar
• Hoque, MR, Mazmum, MF, Bao, Y. e-Health in Bangladesh: Current Status, Challenges, and Future Direction. The International Technology Management Review 2014;4(2):87–96.
   Google Scholar
• Tierney, WM, Kanter, AS, Fraser, HS, Bailey, C. A toolkit for e-health partnerships in low-income nations. Health Affairs 2010;29(2):268–73.
   Web of Science ®Google Scholar
• Khalifehsoltani SN, Gerami M. E-health challenges, opportunities and experiences of developing countries. Presented at the International Conference on e-Education, e-Business. Sanya, China: IC4E ‘10; 2010.
   Google Scholar
• Chetley AJ, Davies B, Trude H, Ramirez R. Improving health connecting people: The role of ICTs in the health sector of developing countries, infoDev 2006;7(1):1–65.
   Google Scholar
• Ahmed, SM, Evans, TG, Standing, H, Mahmud, S. Harnessing pluralism for better health in Bangladesh. The Lancet 2013;382(9906):1746–55.
   PubMed Web of Science ®Google Scholar
• Health Bulletin. Ministry of health and family welfare. Government of the People’s Republic of Bangladesh; 2013; Dhaka, Bangladesh.
   Google Scholar
• World Health Organization. World health statistics 2012. World Health Organization; Geneva, Switzerland.
   Web of Science ®Google Scholar
• Karim, MA. Digital Bangladesh for good governance. Bangladesh Development Forum; 2011.
   Google Scholar
• Commonwealth T. Library and archive. From the Commonwealth http://www.thecommonwealth.org/files/178347/FileName/Bangladesh%2Survey.pdf ( accessed July 2, 2013)
   Google Scholar
• Sheraz U, Inayatullah S, Shah A. E-health futures in Bangladesh. Foresight 2013;15(3):177–89.
   Google Scholar
• Ashraf M, Malik B, Grunfeld H. Evaluating health behaviour outcomes of an ICT project; results from research in three villages in Bangladesh. Journal of eHealth Technology and Application 2009;7(2):179. Abstract published from the proceedings of the IEEE Healthcom 2009 Workshop. ISSN: 1881–4581.
   Google Scholar
• Sharifi M, Ayat M, Jahanbakhsh M, Tavakoli N, Mokhtari H, Wan Ismail, WK. E-health implementation challenges in Iranian medical centers: A qualitative study in Iran. Telemedicine and e-Health 2013;19(2):122–128.
   PubMed Web of Science ®Google Scholar
• Vanagas G, Klimavičiūtė-Gudauskiene R. Factors affecting electronic health information needs in primary care patients. Telemedicine and e-Health 2012;18(10):724–28.
   PubMed Web of Science ®Google Scholar
• Chen RF, Hsiao JL. An empirical study of physicians’ acceptance of hospital information systems in Taiwan. Telemedicine and e-Health 2012;18(2):120–25.
   PubMed Web of Science ®Google Scholar
• Khan SZ, Shahid Z, Hedstrom K, Andersson A. Hopes and fears in implementation of electronic health records in Bangladesh. The Electronic Journal of Information Systems in Developing Countries 2012;54(8):1–18.
   Google Scholar
• Ilie V, Van VC, Green G, Lou H. Gender differences in perceptions and use of communication technologies: A diffusion of innovation approach. Information Resources Management Journal (IRMJ) 2005;18(3):13–31.
   Google Scholar
• Jaruwachirathanakul B, Fink D. Internet banking adoption strategies for a developing country: The case of Thailand. Internet Research 2005;15(3):295–11.
   Web of Science ®Google Scholar
• Davison R, Vogel D, Harris R, Jones N. Technology leapfrogging in developing countries-an inevitable luxury? The Electronic Journal of Information Systems in Developing Countries 2000;1(5):1–10.
   Google Scholar
• Bass FM. A new product growth model for consumer durables. Management Science 1969; 15(January):215–27.
   Google Scholar
• Rogers E. Elements of diffusion in diffusion of innovations. 4th ed. New York, NY: The Free Press; 1995. 1–37 pp.
   Google Scholar
• Arthur DL. The strategic management of technology. Cambridge, MA: MIT Press; 1981.
   Google Scholar
• Fishbein M, Ajzen I. Belief, attitude, intention and behavior: An introduction to theory and research. Reading, MA: Addison-Wesley; 1975.
   Google Scholar
• Davis FD. Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly 1989;13:983–1003.
   Web of Science ®Google Scholar
• Scherer MJ. Assistive technology: Matching device and consumer for successful rehabilitation. Washington, DC: APA Books; 2002. ISBN 1-55798-840–4.
   Google Scholar
• Bandura A. Social cognitive theory of self-regulation. Organizational Behavior and Human Decision Processes 1991; 50 (2):248–87.
   Web of Science ®Google Scholar
• Jackie F, Mark R. Mastering the hype cycle: How to choose the right innovation at the right time. Watertown, MA: HBS Press; 2008.
   Google Scholar
• Ajzen I. The theory of planned behavior. Organizational Behavior and Human Decision Processes 1991;50(2):179–211.
   Web of Science ®Google Scholar
• Orruño E, Gagnon MP, Asua J, Abdeljelil AB. Evaluation of teledermatology adoption by health-care professionals using a modified technology acceptance model. Journal of Telemedicine and Telecare 2011;17(6):303–07.
   PubMed Web of Science ®Google Scholar
• Dünnebeil S, Sunyaev A, Blohm I, Leimeister JM, Krcmar H. Determinants of physicians’ technology acceptance for e-health in ambulatory care. International Journal of Medical Informatics 2012;81(11):746–60.
   PubMed Web of Science ®Google Scholar
• Aggelidis VP, Chatzoglou PD. Using a modified technology acceptance model in hospitals. International Journal of Medical Informatics 2009;78(2):115–26.
   PubMed Web of Science ®Google Scholar
• Holden RJ, Karsh BT. The technology acceptance model: Its past and its future in health care. Journal of Biomedical Informatics 2010;43(1):159–72.
   PubMed Web of Science ®Google Scholar
• Davis FD, Venkatesh V. Toward preprototype user acceptance testing of new information systems: Implications for software project management. IEEE Transactions on Engineering Management 2004;51(1):31–46.
   Web of Science ®Google Scholar
• King WR, He J. A meta-analysis of the technology acceptance model. Information & Management 2006;43(6);740–55.
   Google Scholar
• Jung ML, Loria K. Acceptance of Swedish e-health services. Journal of Multidisciplinary Healthcare 2010;3:55.
   PubMedGoogle Scholar
• Wilson EV, Lankton NK. Modeling patients’ acceptance of provider-delivered e-health. Journal of the American Medical Informatics Association 2004;11(4):241–48.
   PubMed Web of Science ®Google Scholar
• Kim NE, Han SS, Yoo KH, Yun EK. The impact of user’s perceived ability on online health information acceptance. Telemedicine and e-Health 2012;18(9):703–08.
   PubMed Web of Science ®Google Scholar
• Or CK, Karsh BT, Severtson DJ, Burke LJ, Brown RL, Brennan PF. Factors affecting home care patients’ acceptance of a web-based interactive self-management technology. Journal of the American Medical Informatics Association 2011;18(1):51–59.
   PubMed Web of Science ®Google Scholar
• Hu PJ, Chau PY, Sheng ORL, Tam KY. Examining the technology acceptance model using physician acceptance of telemedicine technology. Journal of Management Information Systems 1999;16(2):91–112.
   Web of Science ®Google Scholar
• Wu JH, Shen WS, Lin LM, Greenes RA, Bates DW. Testing the technology acceptance model for evaluating healthcare professionals’ intention to use an adverse event reporting system. International Journal for Quality in Health Care 2008;20(2):123–29.
   PubMed Web of Science ®Google Scholar
• Venkatesh V, Davis FD. A theoretical extension of the technology acceptance model: four longitudinal field studies. Management Science 2000;46(2): 186–204.
   Web of Science ®Google Scholar
• Plouffe CR, Hulland JS, Vandenbosch M. Research report: Richness versus parsimony in modeling technology adoption decisions—understanding merchant adoption of a smart card-based payment system. Information Systems Research 2001;12(2):208–22.
   Web of Science ®Google Scholar
• Kibelloh M, Bao YK. Can online MBA programmes allow professional working mothers to balance work, family, and career progression? A case study in China. The Asia-Pacific Education Researcher 2014;23(2):249–59.
   Web of Science ®Google Scholar
• An JY, Hayman LL, Panniers T, Carty B. Theory development in nursing and healthcare informatics: A model explaining and predicting information and communication technology acceptance by healthcare consumers. Advances in Nursing Science 2007;30(3):E37–E49.
   Google Scholar
• Kibelloh M, Bao YK. Perceptions of international female students towards E-learning in resolving high education and family role strain. Journal of Educational Computing Research 2014;50(4):471–91.
   Web of Science ®Google Scholar
• Wu JH, Wang SC, Lin LM. Mobile computing acceptance factors in the healthcare industry: A structural equation model. International Journal of Medical Informatics 2007;76(1): 66–77.
   PubMed Web of Science ®Google Scholar
• Bagozzi RP. The legacy of the technology acceptance model and a proposal for a paradigm shift. Journal of the Association for Information Systems 2007;8(4):3.
   Web of Science ®Google Scholar
• Tung FC, Chang SC, Chou CM. An extension of trust and TAM model with IDT in the adoption of the electronic logistics information system in HIS in the medical industry. International Journal of Medical Informatics 2008;77(5):324–35.
   PubMed Web of Science ®Google Scholar
• Ortega EJM, Román GMV. Explaining physicians’ acceptance of EHCR systems: An extension of TAM with trust and risk factors. Computers in Human Behavior 2011;27(1):319–32.
   Web of Science ®Google Scholar
• Appari A, Johnson ME. Information security and privacy in healthcare: Current state of research. International Journal of Internet and Enterprise Management 2010;6(4):279–14.
   Google Scholar
• Applebaum PS. Privacy in psychiatric treatment: Threats and response. American Journal of Psychiatry 2002; 159:1809–18.
   PubMed Web of Science ®Google Scholar
• Angst CM, Agarwal R. Adoption of electronic health records in the presence of privacy concerns: The elaboration likelihood model and individual persuasion. MIS Quarterly 2009;33(2):339–70.
   Web of Science ®Google Scholar
• Sankaranarayanan J, Sallach RE. Rural patients’ access to mobile phones and willingness to receive mobile phone-based pharmacy and other health technology services: A pilot study. Telemedicine and e-Health 2014;20(2):182–185.
   Google Scholar
• Westin AF. Improving access and protecting privacy. Connecting Americans to their Health Care. http://www. phrconference. org/conf_resources/presentations/dec7/improving_access. pdf ( last accessed March 2, 2007).
   Google Scholar
• Moorman C, Deshpande R, Gerald Z. Factors affecting trust in market relationships. Journal of Marketing 1993; 57(January):81–101.
   Google Scholar
• Ozawa S, Sripad P. How do you measure trust in the health system? A systematic review of the literature. Social Science & Medicine 2013;91:10–14.
   PubMed Web of Science ®Google Scholar
• Zwaan L, Thijs A, Wagner C, Timmermans DR. Does inappropriate selectivity in information use relate to diagnostic errors and patient harm? The diagnosis of patients with dyspnea. Social Science & Medicine 2013;91:32–38.
   PubMed Web of Science ®Google Scholar
• Sillence E, Briggs P, Harris P, Fishwick L. A framework for understanding trust factors in web-based health advice. International Journal of Human-Computer Studies 2006;64(8):697–13.
   Web of Science ®Google Scholar
• Briggs P, Burford B, De AA, Lynch P. Trust in online advice. Social Science Computer Review 2002;20(3):321–32.
   Web of Science ®Google Scholar
• Smith AD, Manna DR. Exploring the trust factor in e-medicine. Online Information Review 2004;28:346–55.
   Web of Science ®Google Scholar
• Williams P, Huntington P, Nicholas D. Health information on the Internet: A qualitative study of NHS direct online users. Aslib Proceedings 2003;55(5/6):304–12.
   Google Scholar
• Luo W, Najdawi M. Trust-building measures: A review of consumer health portals. Communications of the ACM 2004;47(1):108–13.
   Web of Science ®Google Scholar
• Stefan EK, Kristina EB, Raimo N. Use of and trust in health information on the Internet: A nationwide eight-year follow-up survey. Informatics for Health and Social Care 2013;38(3): 236–45.
   PubMed Web of Science ®Google Scholar
• McGraw D, Dempsey JX, Harris L, Goldman J. Privacy as an enabler, not an impediment: Building trust into health information exchange. Health Affairs 2009;28(2):416–27.
   Web of Science ®Google Scholar
• Saad G, Gill T. Applications of evolutionary psychology in marketing. Psychology Market 2000;17:1005–34.
   Web of Science ®Google Scholar
• Powell M, Ansic D. Gender differences in risk behaviour in financial decision-making: An experimental analysis. Journal of Economic Psychology 1997;18(6):605–28.
   Web of Science ®Google Scholar
• Venkatesh V, Morris MG, Davis GB, Davis FD. User acceptance of information technology: Toward a unified view. MIS Quarterly 2003;27(3):425–478.
   Google Scholar
• Zhang X, Guo X, Lai KH, Guo F, and Li C. Understanding gender differences in m-health adoption: A modified theory of reasoned action model. Telemedicine and e-Health 2014;20(1):39–46.
   PubMed Web of Science ®Google Scholar
• Bao Y, Xiong T, Hu Z, Kibelloh M. Exploring gender differences on general and specific computer self-efficacy in mobile learning adoption. Journal of Educational Computing Research 2013;49(1):111–32.
   Web of Science ®Google Scholar
• Venkatesh V, Morris MG. Why don’t men ever stop to ask for directions? Gender, social influence, and their role in technology acceptance and usage behavior. MIS Quarterly 2000;24(1):115–39.
   Web of Science ®Google Scholar
• Busch T. Gender differences in self-efficacy and attitudes toward computers. Journal of Educational Computing Research 1995;12(2):147–58.
   Web of Science ®Google Scholar
• Hiroshi O, Madeline Z. Gender and the Internet. Social Science Quarterly 2003;84(1):111–121.
   Web of Science ®Google Scholar
• Slyke VC, Comunale CL, Belanger F. Gender differences in perceptions of web-based shopping. Communications of the ACM 2002; 45(8):82–6.
   Web of Science ®Google Scholar
• Sun H, Zhang P. The role of moderating factors in user technology acceptance. International Journal of Human-Computer Studies 2006;64(2):53–78.
   Web of Science ®Google Scholar
• Baker EW, Al-Gahtani SS, Hubona GS. The effects of gender and age on new technology implementation in a developing country: Testing the theory of planned behavior (TPB). Information Technology & People 2007;20(4):352–75.
   Google Scholar
• Zikmund WG, Babin BJ, Carr JC, Griffin M. Business research methods. 8th ed. South-Western Cangage learning; 2010; New Delhi, India.
   Google Scholar
• Lee AS. Integrating positivist and interpretive approaches to organizational research. Organization Science 1991;2(4):342–65.
   Web of Science ®Google Scholar
• Azam MS, Quaddus M. Examining the influence of national culture on adoption and use of information and communication technology: A study from Bangladesh’s SME perspective. The International Technology Management Review 2013;3(2):116–126.
   Google Scholar
• Eze UC, Manyeki JK, Yaw LH, Har LC. Factors affecting Internet banking adoption among young adults: Evidence from Malaysia. 2011 International Conference on Social Science and Humanity; IPEDR, vol. 5, IACSIT Press, Singapore; 2011.
   Google Scholar
• Chau PY, Hu PJH. Investigating healthcare professionals’ decisions to accept telemedicine technology: An empirical test of competing theories. Information & Management 2002;39(4):297–11.
   Web of Science ®Google Scholar
• Taylor S, Todd P. Assessing IT usage: The role of prior experience. MIS Quarterly 1995;19(4):561–70.
   Web of Science ®Google Scholar
• Featherman MS, Pavlou PA. Predicting e-services adoption: A perceived risk facets perspective. International Journal of Human-Computer Studies 2003;59(4):451–74.
   Web of Science ®Google Scholar
• Chellappa RK. Consumers’ trust in electronic commerce transactions: The role of perceived privacy and perceived security; Emory University 2002:1–45.
   Google Scholar
• Chellappa RK, Pavlou PA. Perceived information security, financial liability and consumer trust in electronic commerce transactions. Logistics Information Management 2002;15(5/6):358–68.
   Google Scholar
• Korgaonkar PK, Wolin LD. A multivariate analysis of web usage. Journal of Advertising Research 1999:39:53–68.
   Web of Science ®Google Scholar
• Gefen D, Karahanna E, Straub D. Trust and TAM in online shopping: An integrated model. MIS Quarterly 2003;27:51–90.
   Web of Science ®Google Scholar
• Yoon SJ. The antecedents and consequences of trust in online purchase decisions. Journal of Interactive Marketing 2002;16(2):47–63.
   Google Scholar
• Hair JF, Hult GTM, Ringle C, Sarstedt M. A primer on partial least squares structural equation modeling (PLS-SEM). New Delhi, India: SAGE Publications, Incorporated; 2013.
   Google Scholar
• Hair JF, Anderson RE, Tatham RL, and William C. Multivariate data analysis with readings. New Jersey: Prentice Hall; 1995.
   Google Scholar
• Hair J, Anderson R, Tatham L, Black W. Multivariate data analysis with regarding. Multivariate Data Analysis with Regarding 1992;6(1):1–15.
   Google Scholar
• Henseler J, Ringle CM, Sinkovics RR. The use of partial least squares path modeling in international marketing. Advances in International Marketing 2009;20(1):277–19.
   Google Scholar
• Efron B, Tibshirani R. An introduction to the bootstrap. Boca Raton, FL: Chapman & Hall/CRC. ISBN 0-412-04231-2. 1993, software.
   Google Scholar
• Lim S, Xue L, Yen CC, Chang L, Chan HC, Tai BC, Choolani M. A study on Singaporean women’s acceptance of using mobile phones to seek health information. International Journal of Medical Informatics 2011;80(12):e189–202.
   PubMed Web of Science ®Google Scholar
• Wu IL, Li JY, Fu CY. The adoption of mobile healthcare by hospital’s professionals: An integrative perspective. Decision Support Systems 2011;51(3):587–96.
   Web of Science ®Google Scholar
• Beldad A, De Jong M, Steehouder M. How shall I trust the faceless and the intangible? A literature review on the antecedents of online trust. Computers in Human Behavior 2010;26(5):857–69.
   Web of Science ®Google Scholar
• Paul DL, McDaniel RR. A field study of the effect of interpersonal trust on virtual collaborative relationship performance. MIS Quarterly 2004:183–27.
   Web of Science ®Google Scholar
• Wilkowska W, Ziefle M. Perception of privacy and security for acceptance of E-health technologies: Exploratory analysis for diverse user groups. In IEEE 5th International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth); 2011. 593–600 pp..
   Google Scholar
• Bhuiya I, Bhattacharya A. A situation analysis of care and support for rape survivors at first point of contact in India and Bangladesh. Frontiers in Reproductive Health 2008;2(1):1–120.
   Google Scholar
• Siegrist M. The influence of trust and perceptions of risks and benefits on the acceptance of gene technology. Risk Analysis 2000;20(2):195–204.
   PubMed Web of Science ®Google Scholar
• Awad NF, Ragowsky A. Establishing trust in electronic commerce through online word of mouth: An examination across genders. Journal of Management Information Systems 2008;24(4):101–121.
   Web of Science ®Google Scholar
• Gefen D, Straub DW. Gender differences in the perception and use of E-mail: An extension to the technology acceptance model. MIS Quarterly 1997;21(4):389–400.
   Google Scholar
• Venkatesh V, Thong JY, & Xu X. Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Quarterly 2012;36(1):157–78.
   Web of Science ®Google Scholar
• Gagliardi A, Jadad AR. Examination of instruments used to rate quality of health information on the Internet: chronicle of a voyage with an unclear destination. British Medical Journal 2002;324(7337):569–73.
   PubMed Web of Science ®Google Scholar
• Cotten SR, Gupta SS. Characteristics of online and offline health information seekers and factors that discriminate between them. Social Science & Medicine 2004;59(9):1795–806.
   PubMed Web of Science ®Google Scholar
• Kunst H, Groot D, Latthe PM, Latthe M, Khan KS. Accuracy of information on apparently credible websites: Survey of five common health topics. BMJ: British Medical Journal 2002;324(7337):581.
   Web of Science ®Google Scholar
• Ouma S, Herselman ME. E-health in rural areas: Case of developing countries. International Journal of Biological and Life Sciences 2008;4(4):194–200.
   Google Scholar