Abstract
While simulation has become an increasingly sophisticated and standardized method of clinical teaching and performance assessment in social work, unlike other clinical and health care fields, it is not generally used in other areas of social work research. Yet, it has the potential to address challenges and limitations in several areas of social work research. For instance, in the area of professional decision-making, research has demonstrated high variability in the conclusions of not only different professionals encountering the same case, but also in a single professional encountering a case at different times. However, research that would elucidate differences in professional decision-making is complicated by logistical and ethical constraints of real-life practice, and the fact that professional decision-making occurs outside the realm of conscious deliberation rendering the individual unable to fully articulate the process by which they arrived at their final conclusion. Simulation research methods can address some of these challenges through providing the opportunity to: observe professional decision-making in real time; reflect on the decisional process while reviewing recordings; and compare the approaches of professionals to standardized cases. This paper reviews the use of simulation research methods in clinical and health science fields and the types of simulation research. It then describes the manner in which simulation methods have been applied to a specific program of social work research that examines professional decision-making in high stakes situations, contributing to clinical practice.
Similar content being viewed by others
References
Al-Ghareeb, A. Z., Cooper, S. J., & McKenna, L. G. (2017). Anxiety and clinical performance in simulated setting in undergraduate health professionals education: An integrative review. Clinical Simulation in Nursing, 13(10), 478–491.
Alsaad, A. A., Davuluri, S., Bhide, V. Y., Lannen, A. M., & Maniaci, M. J. (2017). Assessing the performance and satisfaction of medical residents utilizing standardized patient versus mannequin-simulated training. Advances in medical education and practice, 8, 481.
Arad-Davidzon, B., & Benbenishty, R. (2008). The role of workers’ attitudes and parent and child wishes in child protection workers’ assessments and recommendation regarding removal and reunification. Children and Youth Services Review, 30(1), 107–121.
Arzalier-Daret, S., Buléon, C., Bocca, M.-L., Denise, P., Gérard, J.-L., & Hanouz, J.-L. (2018). Effect of sleep deprivation after a night shift duty on simulated crisis management by residents in anaesthesia. A randomised crossover study. Anaesthesia Critical Care & Pain Medicine, 37(2), 161–166.
Beaubien, J. M., & Baker, D. P. (2004). The use of simulation for training teamwork skills in health care: how low can you go? BMJ Quality & Safety, 13(suppl 1), i51–i56.
Bechtel, K., Bhatnagar, A., & Auerbach, M. (2019). Simulation-based research to improve infant health outcomes: Using the infant simulator to prevent infant shaking. Infant Behavior and Development, 56, 101263.
Bender, G. J., & Maryman, J. A. (2018). Clinical macrosystem simulation translates between organizations. Simulation in Healthcare, 13(2), 96–106.
Benishek, L. E., Lazzara, E. H., Gaught, W. L., Arcaro, L. L., Okuda, Y., & Salas, E. (2015). The Template of Events for Applied and Critical Healthcare Simulation (TEACH Sim): a tool for systematic simulation scenario design. Simulation in Healthcare, 10(1), 21–30.
Bhoja, R., Guttman, O. T., Fox, A. A., Melikman, E., Kosemund, M., & Gingrich, K. J. (2020). Psychophysiological stress indicators of heart rate variability and electrodermal activity with application in healthcare simulation research. Simulation in Healthcare, 15(1), 39–45.
Blanchette, I., & Richards, A. (2010). The influence of affect on higher level cognition: A review of research on interpretation, judgement, decision making and reasoning. Cognition & Emotion, 24(4), 561–595.
Bogo, M. (2010). Achieving competence in social work through field education. Toronto: University of Toronto Press.
Bogo, M., Katz, E., Regehr, C., Logie, C., Mylopoulos, M., & Tufford, L. (2013). Toward understanding meta-competence: An analysis of students’ reflection on their simulated interviews. Social Work Education, 32(2), 259–273.
Bogo, M., Regehr, C., Katz, E., Logie, C., Tufford, L., & Litvack, A. (2012). Evaluating an objective structured clinical examination (OSCE) adapted for social work. Research on Social Work Practice, 22(4), 428–436.
Bogo, M., Regehr, C., Logie, C., Katz, E., Mylopoulos, M., & Regehr, G. (2011). Adapting objective structured clinical examinations to assess social work students’performance and reflections. Journal of Social Work Education, 47(1), 5–18.
Bogossian, F., Cooper, S., Cant, R., Beauchamp, A., Porter, J., Kain, V., et al. (2014). Undergraduate nursing students’ performance in recognising and responding to sudden patient deterioration in high psychological fidelity simulated environments: an Australian multi-centre study. Nurse education Today, 34(5), 691–696.
Boulet, J., & Murray, D. J. (2019). Designing, choosing, and using assessment tools in healthcare simulation research. In Healthcare simulation research (pp. 183–190). Springer.
Bryant, K., Aebersold, M. L., Jeffries, P. R., & Kardong-Edgren, S. (2019). Innovations in simulation: Nursing leaders’ exchange of best practices. Clinical Simulation in Nursing, 41, 33–40.
Bucknall, T. K., Forbes, H., Phillips, N. M., Hewitt, N. A., Cooper, S., Bogossian, F., & Investigators, F. A. (2016). An analysis of nursing students’ decision-making in teams during simulations of acute patient deterioration. Journal of advanced nursing, 72(10), 2482–2494.
Cabrera-Mino, C., Shinnick, M. A., & Moye, S. (2019). Task-evoked pupillary responses in nursing simulation as an indicator of stress and cognitive load. Clinical Simulation in Nursing, 31, 21–27.
Carter, K., Swanke, J., Stonich, J., Taylor, S., Witzke, M., & Binetsch, M. (2018). Student assessment of self-efficacy and practice readiness following simulated instruction in an undergraduate social work program. Journal of Teaching in Social Work, 38(1), 28–42.
Cheng, A., Auerbach, M., Hunt, E. A., Chang, T. P., Pusic, M., Nadkarni, V., & Kessler, D. (2014). Designing and conducting simulation-based research. Pediatrics, 133(6), 1091–1101.
Cheng, A., Kessler, D., Mackinnon, R., Chang, T. P., Nadkarni, V. M., Hunt, E. A., et al. (2016). Reporting guidelines for health care simulation research: Extensions to the CONSORT and STROBE statements. Advances in Simulation, 1(1), 25.
Cheng, A., Kessler, D., Mackinnon, R., Chang, T. P., Nadkarni, V. M., Hunt, E. A., et al. (2017). Conducting multicenter research in healthcare simulation: Lessons learned from the INSPIRE network. Advances in Simulation, 2(1), 6.
Colvin, A. D., Saleh, M., Ricks, N., & Rosa-Davila, E. (2020). Using simulated instruction to prepare students to engage in culturally competent practice. Journal of Social Work in the Global Community, 5(1), 1.
Craig, S. L., McInroy, L. B., Bogo, M., & Thompson, M. (2017). Enhancing competence in health social work education through simulation-based learning: Strategies from a case study of a family session. Journal of Social Work Education, 53(sup1), S47–S58.
Croft, H., Gilligan, C., Rasiah, R., Levett-Jones, T., & Schneider, J. (2018). Thinking in pharmacy practice: A study of community pharmacists’ clinical reasoning in medication supply using the think-aloud method. Pharmacy, 6(1), 1.
Dieckmann, P., & Ersdal, H. L. (2019). Simulation as a social event: Stepping back, thinking about fundamental assumptions. In Clinical simulation (pp. 171–182). Amsterdam: Elsevier.
Dieckmann, P., Gaba, D., & Rall, M. (2007). Deepening the theoretical foundations of patient simulation as social practice. Simulation in Healthcare, 2(3), 183–193.
Dressendorfer, R. A., Kirschbaum, C., Rohde, W., Stahl, F., & Strasburger, C. J. (1992). Synthesis of a cortisol-biotin conjugate and evaluation as a tracer in an immunoassay for salivary cortisol measurement. Journal of Steroid Biochemistry and Molecular Biology, 43(7), 683–692.
Egonsdotter, G., Bengtsson, S., Israelsson, M., & Borell, K. (2018). Child protection and cultural awareness: Simulation-based learning. Journal of Ethnic & Cultural Diversity in Social Work, 29(5), 362–376.
Fent, G., Blythe, J., Farooq, O., & Purva, M. (2015). In situ simulation as a tool for patient safety: A systematic review identifying how it is used and its effectiveness. BMJ Simulation and Technology Enhanced Learning, 1(3), 103–110.
Fey, M. K., Gloe, D., & Mariani, B. (2015). Assessing the quality of simulation-based research articles: A rating rubric. Clinical Simulation in Nursing, 11(12), 496–504.
Forneris, S. G., Neal, D. O., Tiffany, J., Kuehn, M. B., Meyer, H. M., Blazovich, L. M., et al. (2015). Enhancing clinical reasoning through simulation debriefing: A multisite study. Nursing education perspectives, 36(5), 304–310.
Forsberg, E., Ziegert, K., Hult, H., & Fors, U. (2014). Clinical reasoning in nursing, a think-aloud study using virtual patients—A base for an innovative assessment. Nurse Education Today, 34(4), 538–542.
Fraser, K., & McLaughlin, K. (2019). Temporal pattern of emotions and cognitive load during simulation training and debriefing. Medical Teacher, 41(2), 184–189.
Fung, L., Boet, S., Bould, M. D., Qosa, H., Perrier, L., Tricco, A., et al. (2015). Impact of crisis resource management simulation-based training for interprofessional and interdisciplinary teams: A systematic review. Journal of Interprofessional Care, 29(5), 433–444.
Gellis, Z. D., & Kim, E. G. (2017). Training social work students to recognize later-life depression: Is standardized patient simulation effective? Gerontology & geriatrics education, 38(4), 425–437.
Ghazali, D. A., Darmian-Rafei, I., Nadolny, J., Sosner, P., Ragot, S., & Oriot, D. (2018). Evaluation of stress response using psychological, biological, and electrophysiological markers during immersive simulation of life threatening events in multidisciplinary teams. Australian Critical Care, 31(4), 226–233.
Goel, V., & Vartanian, O. (2011). Negative emotions can attenuate the influence of beliefs on logical reasoning. Cognition and Emotion, 25(1), 121–131.
Hamstra, S. J., Brydges, R., Hatala, R., Zendejas, B., & Cook, D. A. (2014). Reconsidering fidelity in simulation-based training. Academic Medicine, 89(3), 387–392.
Harden, R. M., & Gleeson, F. (1979). Assessment of clinical competence using an objective structured clinical examination (OSCE). Medical Education, 13(1), 39–54.
Hargreaves, R., & Hadlow, J. (1997). Role-play in social work education: Process and framework for a constructive and focused approach. Social Work Education, 16(3), 61–73.
Harris, B., Watkins, S., Cook, N., Walker, R. F., Read, G. F., & Riad-Fahmy, D. (1990). Comparisons of plasma and salivary cortisol determinations for the diagnostic efficacy of the dexamethasone suppression test. Biological Psychiatry, 27(8), 897–904.
Havig, K., Pharris, A., McLeod, D. A., Natale, A. P., & Miller-Cribbs, J. (2020). Assessing new child welfare worker competency through social simulation with standardized clients: Rubric development and pilot testing. Journal of Public Child Welfare. https://doi.org/10.1080/15548732.2020.1724237
Hitchcock, L. I., Peterson, D. T., Debiasi, L., Shipman, S., Varley, A., & White, M. L. (2018). Learning about poverty through simulation: A pilot evaluation. Journal of Social Work Education, 54(3), 517–531.
Hong, H. S., Issenberg, S. B., & Roh, Y. S. (2020). Effects of standardized patient-based training on surgical nurses’ competencies for managing hand injuries. The Journal of Continuing Education in Nursing, 51(4), 189–196.
Huang, J., Tang, Y., Tang, J., Shi, J., Wang, H., Xiong, T., et al. (2019). Educational efficacy of high-fidelity simulation in neonatal resuscitation training: A systematic review and meta-analysis. BMC Medical Education, 19(1), 323.
Huizinga, C. R., Tummers, F. H., Marang-van de Mheen, P. J., Cohen, A. F., & van der Bogt, K. E. (2019). A review of current approaches for evaluating impaired performance in around-the-clock medical professionals. Sleep Medicine Reviews, 46, 97–107.
Ignacio, J., Dolmans, D., Scherpbier, A., Rethans, J.-J., Chan, S., & Liaw, S. Y. (2015). Comparison of standardized patients with high-fidelity simulators for managing stress and improving performance in clinical deterioration: A mixed methods study. Nurse Education Today, 35(12), 1161–1168.
Judd, B. K., Currie, J., Dodds, K. L., Fethney, J., & Gordon, C. J. (2019). Registered nurses psychophysiological stress and confidence during high-fidelity emergency simulation: Effects on performance. Nurse Education Today, 78, 44–49.
Katz, E. (2019). Teaching note—Using simulation to teach advanced competencies in mindfulness to social work students. Journal of Social Work Education, 55(3), 602–615.
Kemeny, M. (2003). The psychobiology of stress. Current Directions in Psychological Science. https://doi.org/10.1111/1467-8721.01246
Khan, R., Plahouras, J., Johnston, B. C., Scaffidi, M. A., Grover, S. C., & Walsh, C. M. (2018). Virtual reality simulation training for health professions trainees in gastrointestinal endoscopy. Cochrane Database of Systematic Reviews(8).
Konakondla, S., Fong, R., & Schirmer, C. M. (2017). Simulation training in neurosurgery: Advances in education and practice. Advances in Medical Education and Practice, 8, 465.
Kourgiantakis, T., Bogo, M., & Sewell, K. M. (2019). Practice Fridays: Using simulation to develop holistic competence. Journal of Social Work Education, 55(3), 551–564.
Kourgiantakis, T., Sewell, K. M., Hu, R., Logan, J., & Bogo, M. (2019). Simulation in social work education: A scoping review. Research on Social Work Practice, 1049731519885015.
Kourgiantakis, T., Sewell, K. M., Lee, E., Adamson, K., McCormick, M., Kuehl, D., & Bogo, M. (2019). Enhancing social work education in mental health, addictions, and suicide risk assessment: A teaching note. Journal of Social Work Education, 9(6), e024659.
Kozlowski, S. W., & DeShon, R. P. (2004). A psychological fidelity approach to simulation-based training: Theory, research and principles. Scaled worlds: Development, validation, and applications, pp. 75–99.
Lamé, G., & Dixon-Woods, M. (2020). Using clinical simulation to study how to improve quality and safety in healthcare. BMJ Simulation and Technology Enhanced Learning. https://doi.org/10.1136/bmjstel-2018-000370
Larsen, C. R., Oestergaard, J., Ottesen, B. S., & Soerensen, J. L. (2012). The efficacy of virtual reality simulation training in laparoscopy: A systematic review of randomized trials. Acta Obstetricia et Gynecologica Scandinavica, 91(9), 1015–1028.
Lavoie, P., Deschênes, M.-F., Nolin, R., Bélisle, M., Garneau, A. B., Boyer, L., et al. (2020). Beyond technology: A scoping review of features that promote fidelity and authenticity in simulation-based health professional education. Clinical Simulation in Nursing, 42, 22–41.
LeBlanc, V., Regehr, C., Birze, A., King, K., Scott, A., McDonald, R., & Taveres, W. (2011). The association between pre-existing trauma symptoms and acute stress responses in paramedics. Traumatology, 17(4), 10–16.
LeBlanc, V., Regehr, C., Shlonsky, A., & Bogo, M. (2012). Stress responses and decision making in child protection workers faced with high conflict situations. Child abuse & neglect, 36(5), 404–412.
Lee, E., Kourgiantakis, T., & Bogo, M. (2020). Translating knowledge into practice: Using simulation to enhance mental health competence through social work education. Social Work Education, 39(3), 329–349.
Leu, S., Staerkle, R. F., Gaukel, S., Fink, L., Soll, C., Aasen, D. M., et al. (2019). Impact of sleep deprivation on surgical laparoscopic performance in novices: A computer-based crossover study. Surgical Laparoscopy, Endoscopy & Percutaneous Techniques, 29(3), 162–168.
Lewis, J. B., Jr., Falk, D., & Cipolla, C. (2020). The use of simulations to teach social work practice with diverse clients. Journal of Teaching in Social Work, 40(1), 2–17.
Littlewood, K. E. (2011). High fidelity simulation as a research tool. Best practice & Research Clinical Anaesthesiology, 25(4), 473–487.
Macauley, K., Brudvig, T. J., Kadakia, M., & Bonneville, M. (2017). Systematic review of assessments that evaluate clinical decision making, clinical reasoning, and critical thinking changes after simulation participation. Journal of Physical Therapy Education, 31(4), 64–75.
Massoth, C., Röder, H., Ohlenburg, H., Hessler, M., Zarbock, A., Pöpping, D. M., & Wenk, M. (2019). High-fidelity is not superior to low-fidelity simulation but leads to overconfidence in medical students. BMC Medical Education, 19(1), 29.
Maynard, S. P. (2019). Standardized simulations in social work supervision courses: MSW students’ perceptions. Journal of Social Work Education, 1–12.
Mills, B. W., Carter, O.B.-J., Rudd, C. J., Claxton, L. A., Ross, N. P., & Strobel, N. A. (2016). Effects of low-versus high-fidelity simulations on the cognitive burden and performance of entry-level paramedicine students: A mixed-methods comparison trial using eye-tracking, continuous heart rate, difficulty rating scales, video observation and interviews. Simulation in Healthcare, 11(1), 10–18.
Mirza, N., Cinel, J., Noyes, H., McKenzie, W., Burgess, K., Blackstock, S., & Sanderson, D. (2019). Simulated patient scenario development: A methodological review of validity and reliability reporting. Nurse Education Today, 85, 104222.
Mohr, P. N., Biele, G., & Heekeren, H. R. (2010). Neural processing of risk. Journal of Neuroscience, 30(19), 6613–6619.
Mooradian, J. K. (2008). Using simulated sessions to enhance clinical social work education. Journal of Social Work Education, 44(3), 21–36.
Muñoz, J. E., Quintero, L., Stephens, C. L., & Pope, A. T. (2020). A Psychophysiological model of firearms training in police officers: A virtual reality experiment for biocybernetic adaptation. Frontiers in Psychology, 11, 683.
Munroe, B., Buckley, T., Curtis, K., & Morris, R. (2016). Designing and implementing full immersion simulation as a research tool. Australasian Emergency Nursing Journal, 19(2), 90–105.
Murphy, M., Curtis, K., & McCloughen, A. (2016). What is the impact of multidisciplinary team simulation training on team performance and efficiency of patient care? An integrative review. Australasian Emergency Nursing Journal, 19(1), 44–53.
Mutter, M. K., Martindale, J. R., Shah, N., Gusic, M. E., & Wolf, S. J. (2020). Case-based teaching: Does the addition of high-fidelity simulation make a difference in medical students’ clinical reasoning skills? Medical Science Educator, 1–7.
Nabi, R. L. (2003). Exploring the framing effects of emotion: Do discrete emotions differentially influence information accessibility, information seeking, and policy preference? Communication Research, 30(2), 224–247.
Neander, L. L., Hanson, B. L., Edwards, A. E., Shercliffe, R., Cattrell, E., Barnett, J. D., et al. (2018). Teaching SBIRT through simulation: Educational case studies from nursing, psychology, social work, and medical residency programs. Journal of Interprofessional Education & Practice, 13, 39–47.
Neuschwander, A., Job, A., Younes, A., Mignon, A., Delgoulet, C., Cabon, P., et al. (2017). Impact of sleep deprivation on anaesthesia residents’ non-technical skills: a pilot simulation-based prospective randomized trial. BJA: British Journal of Anaesthesia, 119(1), 125–131.
Nimmagadda, J., & Murphy, J. I. (2014). Using simulations to enhance interprofessional competencies for social work and nursing students. Social Work Education, 33(4), 539–548.
Nippita, S., Haviland, M. J., Voit, S. F., Perez-Peralta, J., Hacker, M. R., & Paul, M. E. (2018). Randomized trial of high-and low-fidelity simulation to teach intrauterine contraception placement. American Journal of Obstetrics and Gynecology, 218(2), 258. e251–258. e211.
Nusair, M. B., Cor, M. K., Roberts, M. R., & Guirguis, L. M. (2019). Community pharmacists’ clinical reasoning: A protocol analysis. International journal of clinical pharmacy, 41(6), 1471–1482.
O’Brien, J. E., Hagler, D., & Thompson, M. S. (2015). Designing simulation scenarios to support performance assessment validity. The Journal of Continuing Education in Nursing, 46(11), 492–498.
Padgett, J., Cristancho, S., Lingard, L., Cherry, R., & Haji, F. (2018). Engagement: What is it good for? The role of learner engagement in healthcare simulation contexts. Advances in Health Sciences Education, 1–15.
Paterson, B., Dowding, D., Harries, C., Cassells, C., Morrison, R., & Niven, C. (2008). Managing the risk of suicide in acute psychiatric inpatients: A clinical judgement analysis of staff predictions of imminent suicide risk. Journal of Mental Health, 17(4), 410–423.
Putney, J. M., Levine, A. A., Collin, C.-R., O’Brien, K. H., Mountain-Ray, S., & Cadet, T. (2019). Teaching note—Implementation of online client simulation to train and assess screening and brief intervention skills. Journal of Social Work Education, 55(1), 194–201.
Rall, M., & Dieckmann, P. (2005). Simulation and patient safety: The use of simulation to enhance patient safety on a systems level. Current Anaesthesia & Critical Care, 16(5), 273–281.
Rawlings, M. A., & Blackmer, E. R. (2019). Assessing engagement skills in public child welfare using OSCE: A pilot study. Journal of Public Child Welfare, 13(4), 441–461.
Regehr, C. (2018). Stress, Trauma and Decision-Making for Social Workers. New York: Columbia University Press.
Regehr, C., & Bober, T. (2005). In the line of fire: Trauma in the emergency services. Oxford: Oxford University Press.
Regehr, C., Bogo, M., LeBlanc, V. R., Baird, S., Paterson, J., & Birze, A. (2015). Suicide risk assessment: Clinicians’ confidence in their professional judgment. Journal of Loss and Trauma, 1–17.
Regehr, C., LeBlanc, V., Bogo, M., Paterson, J., & Birze, A. (2015). Suicide risk assessments: Examining influences on clinicians’ professional judgment. American Journal of Orthopsychiatry, 85(4), 295–301.
Regehr, C., LeBlanc, V., Jelley, R. B., & Barath, I. (2008). Acute stress and performance in police recruits. Stress and Health, 24(4), 295–303.
Regehr, C., LeBlanc, V., Shlonsky, A., & Bogo, M. (2010). The influence of clinicians’ previous trauma exposure on their assessment of child abuse risk. Journal of Nervous and Mental Disease, 198(9), 614–618.
Regehr, C., & LeBlanc, V. R. (2017). PTSD, acute stress, performance and decision-making in emergency service workers. The Journal of the American Academy of Psychiatry and the Law, 45(2), 184.
Roberson, C. J. (2019a). Simulation in Social Work Education: A Qualitative Study of MSW Student Development. Journal of Social Work Education, 1–13.
Roberson, C. J. (2019). Understanding simulation in social work education: A conceptual framework. Journal of Social Work Education, 56(3), 576–586.
Roberts, F., & Cooper, K. (2019). Effectiveness of high fidelity simulation versus low fidelity simulation on practical/clinical skill development in pre-registration physiotherapy students: A systematic review. JBI Database of Systematic Reviews and Implementation Reports, 17(6), 1229–1255.
Rudolph, J. W., Simon, R., & Raemer, D. B. (2007). Which reality matters? Questions on the path to high engagement in healthcare simulation. LWW.
Sacco, P., Ting, L., Crouch, T. B., Emery, L., Moreland, M., Bright, C., et al. (2017). SBIRT training in social work education: Evaluating change using standardized patient simulation. Journal of Social Work Practice in the Addictions, 17(1–2), 150–168.
Salas, E., Rosen, M. A., & DiazGranados, D. (2009). Expertise-based intuition and decision making in organizations. Journal of Management, 36(4), 941–973.
Sanchez-Martin, J. R., Cardas, J., Ahedo, L., Fano, E., Echebarria, A., & Azpiroz, A. (2001). Social behavior, cortisol, and sIgA levels in preschool children. Journal of Psychosomatic Research, 50(4), 221–227.
Schoenherr, J. R., & Hamstra, S. J. (2017). Beyond fidelity: deconstructing the seductive simplicity of fidelity in simulator-based education in the health care professions. Simulation in Healthcare, 12(2), 117–123.
Schreiber, J. C., & Minarik, J. D. (2018). Simulated clients in a group practice course: Engaging facilitation and embodying diversity. Journal of Social Work Education, 54(2), 310–323.
Schuerman, J., Rossi, P. H., & Budde, S. (1999). Decisions on placement and family preservation: Agreement and targeting. Evaluation review, 23(6), 599–618.
Scourfield, J., Maxwell, N., Zhang, M. L., De Villiers, T., Pithouse, A., Kinnersley, P., et al. (2019). Evaluation of a fast-track postgraduate social work program in England using simulated practice. Research on Social Work Practice, 29(4), 363–374.
Sharma, S., Boet, S., Kitto, S., & Reeves, S. (2011). Interprofessional simulated learning: the need for ‘sociological fidelity.’ New York: Taylor & Francis.
Sherwood, R. J., & Francis, G. (2018). The effect of mannequin fidelity on the achievement of learning outcomes for nursing, midwifery and allied healthcare practitioners: Systematic review and meta-analysis. Nurse Education Today, 69, 81–94.
Sollid, S. J., Dieckman, P., Aase, K., Søreide, E., Ringsted, C., & Østergaard, D. (2019). Five topics health care simulation can address to improve patient safety: Results from a consensus process. Journal of Patient Safety, 15(2), 111.
Spielberger, C. (1983). Manual for the State-Trait Anxiety Inventory. Palo Alto, CA: Consulting Psychologists Press.
Stevens, R., Galloway, T., & Willemsen-Dunlap, A. (2019). Advancing our understandings of healthcare team dynamics from the simulation room to the operating room: A neurodynamic perspective. Frontiers in Psychology, 10, 1660.
Thackray, D., & Roberts, L. (2017). Exploring the clinical decision-making used by experienced cardiorespiratory physiotherapists: A mixed method qualitative design of simulation, video recording and think aloud techniques. Nurse Education Today, 49, 96–105.
Tremblay, M.-L., Lafleur, A., Leppink, J., & Dolmans, D. H. (2017). The simulated clinical environment: Cognitive and emotional impact among undergraduates. Medical teacher, 39(2), 181–187.
Tun, J. K., Alinier, G., Tang, J., & Kneebone, R. L. (2015). Redefining simulation fidelity for healthcare education. Simulation & Gaming, 46(2), 159–174.
Vartanian, O., & Mandel, D. R. (2011). Neural bases of judgment and decision making. Judgment and decision making as a skill: Learning, development, and evolution, 29.
Walsh, C. M., Sherlock, M. E., Ling, S. C., & Carnahan, H. (2012). Virtual reality simulation training for health professions trainees in gastrointestinal endoscopy. Cochrane Database of Systematic Reviews(6).
Washburn, M., & Zhou, S. (2018). Teaching note—Technology-enhanced clinical simulations: Tools for practicing clinical skills in online social work programs. Journal of Social Work Education, 54(3), 554–560.
Weiss, D., & Marmar, C. (1997). The impact of Event Scale-Revised. In J. W. T. Keane (Ed.), Assessing psychological trauma and PTSD. New York: Guilford Press.
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Regehr, C., Birze, A. Use of Simulation Methods in Social Work Research on Clinical Decision-Making. Clin Soc Work J 49, 244–255 (2021). https://doi.org/10.1007/s10615-020-00778-5
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10615-020-00778-5