Low-Fidelity Simulation Versus Live Human Arms for Intravenous Cannulation Training: A Qualitative Assessment

  • Gary L. BoykinSr.Email author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 482)


In the military, as well as in civilian medical settings, the question of whether to use simulation versus live tissue remains in debate. The purpose of this paper is to examine qualitative data provided by students (n = 260) attending the Army’s Licensed Practical Nurse (LPN) program who completed peripheral intravenous cannulation (PIVC) training using either a Simulated Human Arm (SHA) (n = 135) or a Live Human Arm (LHA) (n = 124). Students provided subjective responses in a written format pertaining to their PIVC training method. Data patterns were assessed using Spradley’s semantic relationship approach. Results reveal that both those using a SHA and a LHA reported feeling confident following training, however the reasons for their confidence differed. Those using a SHA felt confident due to the opportunity to repeatedly practice on a simulated arm, while those learning on a LHA felt assured knowing they had performed PIVC successfully on a live human during LPN training.


Simulation Intravenous infusion Nursing Training 



Thanks to the students of the Army’s LPN Program (68WM6) for their outstanding support, and a special thanks to Mr. Robert S. Jones (PI) at the Fort Sam Houston Department of Nursing Science, Dr. Valerie J Rice, Team Lead, ARL-HRED-ATSD, AMEDD Field Element, and Dr. Leah Enders, DCS Corp.


The views expressed in this article are those of the author and do not reflect the official policy or position of the Department of the Army, Department of Defense, U.S. Army Research Laboratory, Department of Nursing Science, or the U.S. Government.


  1. 1.
    Kantor, G.: Net Wellness. Retrieved from IV Complications. (2016)
  2. 2.
    Rotem, H.: The best and the worst: students’ experience of clinical education. Aust. J. Adv. Nurs. 11, 26–33 (1994)Google Scholar
  3. 3.
    Jones, R., Simmons, A., Boykin, G., Stamper, D., Thompson, J.: Measuring intravenous cannulation skills of practical nursing students using rubber mannequin intravenous training arm. Mil. Med. 179(11), 1361–1367 (2014)CrossRefGoogle Scholar
  4. 4.
    Gelenbe, E., Wu, F.: Large scale simulation for human evacuation and rescue. Comput. Math. Appl. 64(12), 3869–3880 (2012)CrossRefGoogle Scholar
  5. 5.
    Seropian, M., Brown, K., Samuelson Gavilanes, J., Drigger, B.: Simulation: not just a manikin. J. Nurs. Educ. 43(4), 164–169 (2004)Google Scholar
  6. 6.
    Armstrong, B., Crouch, R., Read, C., Palfrey, R.: Training nurses in trauma management. Emerg. Nurse 21(4), 14–18 (2013)CrossRefGoogle Scholar
  7. 7.
    Good, M.: Patient simulation for training basic and advanced clinical skills. Med. Educ. 37, 14–21 (2003)Google Scholar
  8. 8.
    Shane, M., Pettitt, B., Morgenthal, C., Smith, C.: Should surgical novices trade their retractors for joysticks? Videogame experience decreases the time needed to acquire surgical skills. Surg. Endosc. 22(5), 1294–1297 (2008)CrossRefGoogle Scholar
  9. 9.
    Lateef, F.: Simulation-based learning: just like the real thing. J. Emerg. Trauma Shock 3(4), 348–352 (2010)CrossRefGoogle Scholar
  10. 10.
    Motola, I., Devine, L., Chung, E., Sullivan, J., Issenberg, S.: Simulation in healthcare education: a best evidence practical guide. AMEE guide No 82. Med. Teach. 35(10), e1511–e1530 (2013)CrossRefGoogle Scholar
  11. 11.
    Okuda, Y., Bryson, E., DeMaria, S., Jacobson, L., Shen, B., Levine, A., Quinones, J.: The utility of simulation in medical education: what is the evidence? Mt Sinai J. Med. 76(4), 330–343 (2009)CrossRefGoogle Scholar
  12. 12.
    Partin, J., Payne, T., Slemmons, M.: Student’s perceptions of the learning experiences using high-fidelity simulation to teach concepts relative to obstetrics. Teach. Technol. 32(3), 186–188 (2011)Google Scholar
  13. 13.
    Engum, S., Jeffries, P., Fisher, L.: Intravenous catheter training system: computer-based education versus traditional learning methods. Am. J. Surg. 186(1), 67–74 (2003)CrossRefGoogle Scholar
  14. 14.
    Munshi, F., Hani, L., Alyousef, S.: Low-versus high fidelity simulation in teaching and assessing clinical skills. J. Taibah Univ. Med. Sci. 10(1), 12–15 (2015)Google Scholar
  15. 15.
    Cannon-Bowers, J., Bowers, C., Stout, R., Ricci, K., Hildabrand, A.: Using cognitive task analysis to develop simulation-based training for medical tasks. Mil. Med. 178, 15–21 (2013)Google Scholar
  16. 16.
    Sittner, B., Aebersold, M., Paige, J., Graham, L., Schram, A., Decker, S., Lioce, L.: INACSL standards of best practice for simulation: past, present and future. Nurs. Edu. Perspect. 36, 295–298 (2015)Google Scholar
  17. 17.
    Loukas, C., Nikiteas, N., Kanakis, M., Georgiou, E.: Evaluating the effectiveness of virtual reality simulation in intravenous cannulation. J. Soc. Simul. Healthc. 6(4), 213–217 (2011)CrossRefGoogle Scholar
  18. 18.
    Savage, E., Tenn, C., Vartanian, O., Blackler, K., Sullivan-Kwantes, W., Garrett, M., Blais, A., Jarmasz, J., Peg, H., Tein, H.: A comparison of live tissue training and high-fidelity patient simulator: a pilot study in battlefield trauma training. J. Trauma Acute Care Surg. 79(4), S157–S163 (2015)CrossRefGoogle Scholar
  19. 19.
    de Giovanni, D., Roberts, T., Norman, G.: Relative effectiveness of high-versus low-fidelity simulation in learning heart sounds. Med. Educ. 43(7), 661–668 (2009)CrossRefGoogle Scholar
  20. 20.
    U.S. Army Program Office for Simulation, Training and Instrumentation.: Product manager for medical simulation. Retrieved 2016, from (2015)
  21. 21.
    U.S. Army Research Laboratory, Human Research and Engineering Directorate, Simulation and Training Technology Center.: Mobil medical lane trainer improving training effectiveness. Retrieved from (2013)
  22. 22.
    Carr, P., Glynn, R., Dineen, B., Flaherty, G., Kropmans, T., Kerin, M.: Interns’ attitudes to IV cannulation: a KAP study. Br. J. Nurs. 20, 15–20 (2011)Google Scholar
  23. 23.
    LeCompte, M.: Qualitative data. Theor. Pract. 39(3), 146–154 (2000)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2017

Authors and Affiliations

  1. 1.U.S. Army Research LaboratorySan AntonioUSA

Personalised recommendations