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Factors Influencing NursesAttitudes Toward Simulation-Based Education

DeCarlo, Deborah BSN, MSNEd; Collingridge, Dave S. PhD; Grant, Carrie BSN, MBA; Ventre, Kathleen M. MD

Simulation in Healthcare: The Journal of the Society for Simulation in Healthcare: July 2008 - Volume 3 - Issue 2 - p 90-96
doi: 10.1097/SIH.0b013e318165819e
Empirical Investigations
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Objective: To identify barriers to nurses’ participation in simulation, and to determine whether prior simulation exposure, professional experience, and practice location influence their tendency to perceive specific issues as barriers. We also sought to identify nurses’ educational priorities, and to determine whether these were influenced by years of experience or practice location.

Methods: We surveyed full-time and part-time nurses in a university-affiliated children’s hospital to gather data on professional demographics, simulation exposure, perceived barriers to participation in simulation, and training priorities.

Results: A total of 523 of 936 (56%) eligible nurses completed the survey. Binary logistic regression analysis revealed that “simulation is ’not the real thing’” was selected as a barrier more often by nurses with prior simulation experience (P = 0.02), fewer years in practice (P = 0.02), and employment in non-acute care areas of the hospital (P = 0.03). “Unfamiliarity with equipment” was reported more often by nurses with less experience (P = 0.01). “Stressful or intimidating environment” was selected more often by those who work in non-acute care areas (P < 0.01). “Providing opportunities to manage rare events” was suggested as a training priority by nurses with less experience (P = 0.08) and by those practicing in acute care areas (P = 0.03).

Conclusions: We identified several barriers to nurses’ participation in simulation training. Nurses’ tendency to name specific issues as barriers is related to prior simulation exposure, years of experience, and area of hospital practice. Rehearsing rare event management is a priority for less-experienced nurses and those in acute care areas.

From the *George and Esther Gross Clinical Simulation Program, Primary Children’s Medical Center, Salt Lake City, Utah; †Statistical Data Center, LDS Hospital, Salt Lake City, Utah; and ‡Division of Critical Care Medicine, University of Utah Department of Pediatrics, Salt Lake City, Utah.

Reprints: Kathleen M. Ventre, MD, George and Esther Gross Clinical Simulation Program, Primary Children’s Medical Center, Salt Lake City, UT (e-mail: kathleen.ventre@hsc.utah.edu).

The authors have indicated that they have no conflicts of interest to disclose.

Reports on the use of simulation in health care education have increased dramatically over the past decade. More recently, interest in using simulation to teach important psychomotor and critical thinking skills to nurses has increased among nursing educators.1–3 Unlike traditional lectures and other formats in which the learner is a passive observer, simulation-based education is responsive to the adult student’s need for an active, learner-centered experience that is embedded in an appropriate clinical context and allows for deliberate practice after a period of reflection.4,5 Computerized mannequin simulators that emulate human physiology have captured a great deal of interest among clinical educators because they can substitute effectively for a patient experiencing a medical emergency. Such “high fidelity,” full-body human simulators allow multidisciplinary teams who interact at the bedside of unstable patients to rehearse treatment approaches that incorporate principles of effective medical emergency management.

As first responders to most clinical emergencies that arise among hospitalized patients, nurses are a particularly important group to integrate into simulation-based courses in effective medical crisis management. Studying hospital-based resuscitation teams composed of intensive care unit nurses, Marsch and colleagues reported that these teams often failed to provide timely defibrillation during simulated cardiac arrests.6 The available evidence indicates that defibrillation delays are relatively common during cardiac arrest management, and human factors have more to do with their occurrence than difficulty recognizing cardiac rhythms.7 These findings suggest a central role for full-scale emergency event simulation in improving the performance of multidisciplinary inpatient resuscitation teams. However, designing effective, learner-centered multidisciplinary simulation sessions is challenging because educators must incorporate the objectives of a diverse group of learners with varying levels of experience in their respective areas of practice.

Although extending simulation-based training to nurses could help narrow the gap between expected and actual performance of inpatient resuscitation teams, effective integration of nurses into multidisciplinary team training sessions requires development of additional insights into their professional concerns and overall educational objectives. However, our review of the literature yielded no information to clarify whether specific demographic characteristics or previous experience with simulation influence practicing nurses’ perceptions about the value of simulator-based education. Therefore, the primary objective of this study was to identify potential barriers educators may face when introducing nurses to simulation. We specifically sought to determine whether the perceived barriers are influenced by prior simulation exposure, years of professional nursing experience, and area of hospital practice. Our secondary objective was to identify the elements nurses think are important to include in simulator-based training, and to determine whether years of professional nursing experience and area of hospital practice influenced nurses’ educational priorities.

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METHODS

After getting approval from the institutional review board, we distributed a 54-question survey to all full-time and part-time registered nurses who regularly engage in direct patient care at a 252-bed university-affiliated tertiary care teaching hospital and Level I pediatric trauma center, whose referral base covers a 5-state area in the Intermountain West. This facility has a high-fidelity human patient simulation program that became fully operational in January 2007, and focuses on teaching principles of effective crisis resource management.

With permission, an existing survey designed for distribution among anesthesiologists was adopted for this study. The original instrument underwent several iterations of pilot testing to assure comprehensiveness and clarity of the questions.8 The final version of the survey used in this study was designed to collect data on nurses’ professional demographics (eg, level of education, years of experience, area of hospital practice, and professional responsibilities), history of simulation experience, perceived barriers that would prevent or hinder engagement in simulation-based training, and suggested priorities for simulation-based courses. Most survey items asked the participants to rate their agreement with statements using a 5-point Likert-style scale. Other items included checklists, yes/no answers, and selecting a single answer from a multiple-choice format. No personal, identifying marks were placed on the surveys. The survey instrument can be viewed in its entirety in the online Appendix.

Surveys were distributed to eligible study participants by attachment to electronic mail, placement in employee mailboxes, and by distribution at staff meetings, mandatory continuing education courses, and charting areas on hospital wards. Surveys were self-administered in an anonymous fashion and then returned to designated drop-boxes and collection envelopes located throughout the hospital. Return of the survey was interpreted as consent to participate in the study. Data collection occurred from November 15, 2006, to June 15, 2007.

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Statistical Analyses

All analyses were carried out using SPSS version 14.0 software. Descriptive statistics were calculated for demographic variables, including level of education, employment status, age, gender, years of practice, and area employed. We also calculated descriptives for participants’ previous participation in simulator-based training, how many times they have participated in simulation training, as well as the location of this training.

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Primary Outcomes

Primary outcomes were the relationships between barriers that prevented participants from pursuing simulator-based training and 3 dichotomized demographic variables: prior simulation experience (yes versus no), years of clinical experience (0–5 vs. over 5 years), and area of employment (acute care vs. non-acute care). Acute care areas are defined as Emergency Department, intensive care units, operating room, postanesthesia care unit, and interfacility transport. Non-acute care areas include inpatient wards, outpatient clinics, and specialty areas such as radiology. To determine whether these demographic variables are significantly related to the barriers, participants’ responses to a list of potential barriers were dummy coded as 0 (not selected as a barrier) or 1 (selected as a barrier) and then regressed onto prior simulation experience, years of clinical experience, and area of employment using separate logistic regression analyses.

We entered the barriers as the predictor variables and the dichotomized demographic variables as the outcome variables because of the constraints imposed by the nature of the data (ie, the demographic data were binary and there were 10 barriers). Such an arrangement suited our purpose of identifying significant relationships between the demographic variables and participants’ responses to the barriers.

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Secondary Outcomes

Our secondary objective was to define the influence that demographic variables had on participants’ priorities for simulator-based education. Specifically, we analyzed whether years of experience and area of employment significantly influenced participants’ suggested priorities for simulator-based courses. Responses to survey questions 17 to 21, ranging from “not important” (1 point) to “essential” (5 points), were grouped according to years of clinical experience (0–5 years vs. over 5 years) and area of employment (acute care versus non-acute care) and then compared using 2-tailed Mann-Whitney U tests of significance. The Mann-Whitney U test is appropriate for analyzing the ordinal data produced by the Likert questions in our survey.

Additional barriers to participation in simulation as well as additional priorities for simulation training were identified in free-text comments provided by the respondents. These were counted and classified into thematic groups by 2 independent investigators (D.D. and K.V.), and disagreements were resolved by consensus. The majority of the barriers identified from supplementary written comments were considered to be synonymous with existing items in checklists provided on the survey. In these cases, the barriers that were written in free-text areas were added to the tally of comparable checklist items, unless the corresponding barrier had already been selected by the same respondent. If the corresponding barrier had already been selected, the barriers reiterated in free-text comments were not added to the tally. Novel barriers were tallied separately. Similarly, free-text comments reiterating priorities for simulation-based education that were already rated in the relevant survey questions were considered redundant and were not added to the tally. Novel priorities were categorized under major common themes, and were tallied and reported separately.

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RESULTS

A total of 523 nurses returned the survey out of 936 who met criteria for inclusion in the study population at the time data collection ended, for a total response rate of 56%. The demographic characteristics of the survey respondents are summarized in Table 1.

Table 1

Table 1

Figures 1A to C show the percentage of respondents who selected specific barriers, stratified by prior simulation experience, years of professional experience, and area of hospital practice, respectively. Each figure shows that issues most commonly selected as major barriers included “being videotaped,” “unfamiliar with equipment,” and “stressful environment.” The issues least commonly selected as major barriers included “training with non-nurses,” “not the real thing,” and “inaccurate reflection of skills.” The rate at which individual issues were selected as barriers was fairly consistent across all subgroups evaluated.

Figure 1.

Figure 1.

Analysis of free-text comments yielded 4 novel barriers: lack of financial compensation for participation in simulation (3 respondents), simulation is not required (1 respondent), simulation is a waste of time (4 respondents), and “not sure what the barriers would be” (1 respondent). Analysis of free-text comments also yielded a few novel priorities: “provide opportunities for practicing routine nursing skills such as patient assessment or IV placement” (5 respondents), “simulation should be mandatory” (1 respondent), and “educators should create a safe educational environment during simulation sessions” (1 respondent). Novel barriers and priorities were not included in the statistical analyses.

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Primary Outcomes

Relationship Between Prior Simulation Exposure and Perceived Barriers to Engagement in Simulation-Based Education

Nurses with prior simulation exposure generally selected fewer barriers than nurses without simulation exposure (Fig. 1A). To determine which barriers are significantly related to prior simulation training, participants’ responses (selected and nonselected barriers) were regressed onto prior simulation training data using binary logistic regression. Although relatively few nurses selected “[simulation is] not the real thing” as a barrier, logistic regression analysis revealed that previous simulation exposure was significantly related to selecting this issue as a barrier to engaging in simulation-based education (Fig. 1A; Wald χ2 = 5.284, P= 0.02). Specifically, nurses who viewed “not the real thing” as a significant barrier were more likely to have had prior simulation training compared with those who did not select this as a barrier. History of prior simulation exposure did not relate significantly to respondents’ tendency to select any other barriers to engagement in simulation-based education.

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Relationship Between Professional Experience and Perceived Barriers to Engagement in Simulation-Based Education

Using binary logistic regression, participants’ responses (selected and nonselected barriers) were regressed onto years of professional practice to determine whether selected barriers are significantly related to years of experience. Results show that years of professional experience was significantly related to selecting “[simulation is] not the real thing” (Wald χ2 = 5.85, P= 0.02) and “unfamiliar with equipment” (Wald χ2 = 6.84, P= 0.01) as barriers (Fig. 1B). Nurses selecting “not the real thing” and “unfamiliar with equipment” as major barriers were more likely to have had 5 or fewer years of experience compared with those not selecting these barriers. Respondents’ professional experience was not significantly related to any other barriers.

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Relationship Between Practice Location and Perceived Barriers to Engagement in Simulation-Based Education

Participants’ responses (selected and nonselected barriers) were regressed onto practice location using binary logistic regression to determine whether practice location is significantly related to selected barriers. Results indicate that area of employment was significantly related to identifying “not the real thing” (Wald χ2 = 4.50, P= 0.03), and “stressful/intimidating environment” (Wald χ2 = 12.60, P < 0.01) as important barriers (Fig. 1C). Nurses selecting “not the real thing” and “stressful/intimidating environment” as barriers were more likely to have worked in non-acute care settings than those not selecting these barriers. Respondents’ area of professional practice did not relate significantly to any other barriers.

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Secondary Outcomes

Effect of Professional Experience and Area of Professional Practice on Suggested Priorities for Simulation-Based Course Content

Respondents collectively ranked “providing opportunities to manage rare events” as the highest priority (mean = 4.17), followed by “practicing and teaching therapy guidelines and algorithms” (mean = 4.11), “teaching technical skills” (mean = 4.05), “fostering teamwork and involving other professionals” (mean = 3.90) and “teaching nontechnical communication skills” (mean = 3.74). Mann-Whitney U tests of significance were used to ascertain whether nurses’ years of professional experience (0–5 years vs. >5 years) influenced their priorities for developing future simulation-based courses. Responses to survey questions 17 to 21 were entered into the analysis. These questions are listed in Table 2 along with the possible responses and response frequencies, stratified by subgroup. The difference between beginner and veteran nurses’ responses to question 17 (“providing opportunities to manage rare events”) approached but did not reach statistical significance (Mann-Whitney U test, z = −1.76, P= 0.08). Nurses with 0 to 5 years experience ranked the opportunity to manage rare events somewhat higher than nurses with >5 years experience. Responses to questions 18 to 21 did not significantly differ based on years of experience.

Table 2

Table 2

We also investigated whether nurses’ area of professional practice (acute care versus non-acute care) influenced priorities for developing future simulation-based courses (ie, responses to questions 17–21), using Mann-Whitney U tests of significance. Responses to question 17 (“providing opportunities to manage rare events”) were significantly different (Mann-Whitney U test, z = −2.23, P= 0.03), with acute care nurses ranking the opportunity to manage rare events as a higher priority than non-acute care nurses (Table 2). Responses to questions 18 to 21 did not significantly differ based on area of professional practice.

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DISCUSSION

Our study finds that there are numerous barriers that can affect the inclination of hospital-based nurses to participate in simulation training. The 3 issues most commonly selected by survey respondents as major barriers included “being videotaped,” “[being] unfamiliar with equipment,” and “stressful environment.” The tendency of nurses to identify specific barriers is influenced by prior simulation exposure, years of professional practice, and area of employment within the hospital. Although “not the real thing” was not commonly identified as a barrier by the entire population of survey respondents, nurses who did select it were significantly more likely to have a prior history of simulation experience, fewer years in professional practice, and employment in non-acute care areas of the hospital. Selecting “unfamiliar with equipment” and “[simulation training would create] a stressful or intimidating environment” was significantly associated with having 5 or fewer years of experience and working in non-acute care areas, respectively. Moreover, nurses’ educational priorities are influenced by years in practice and area of hospital employment. “Providing opportunities to manage rare events” was commonly suggested as a priority for simulation-based education, particularly among nurses with 5 or fewer years of professional experience and among those who practice in acute care areas of the hospital.

These results add to the existing evidence base regarding learners’ perspectives on simulation-based education. Savoldelli and colleagues surveyed 89 anesthesiologists using a similar instrument and found that 81% of respondents reported at least one barrier to participating in simulation-based education.8 Lack of time for such training was selected as a barrier by 55% of staff anesthesiologists and 33% of anesthesia trainees (P < 0.05), and “stressful or intimidating environment” was selected by 25% of staff and 22% of resident anesthesiologists. “Lack of training opportunities” was identified as a major barrier by 23% of the staff anesthesiologists and 39% of residents, a proportion comparable to what we observed in our own survey. As in our population of practicing nurses, anesthesiologists’ top educational priority was “[providing] opportunities to manage rare events.”8

Our survey identified a high prevalence of prior simulation exposure among nurses at our institution, despite the fact that our on-site simulation facility opened during the data collection period. Between 39% and 45% of our respondents reported some prior simulation experience, either by answering “yes” to the survey question asking if they had ever participated in simulation, or by indicating elsewhere in the survey that they had participated in at least one prior simulation session (Table 1). Previous encounters with simulation often occurred during nursing school, and were largely concentrated among nurses with 5 or fewer years of professional experience (Table 1). Interestingly, we found a bimodal distribution of cumulative exposure among respondents with prior simulation experience, with a large portion of respondents indicating that their experience is limited to a single session (Table 1). These findings concur with recent published reports suggesting that use of human patient simulation is becoming common in undergraduate nursing education, but its use accounts for a relatively small fraction of available class hours.9 However limited in number, our respondents’ previous experiences with simulation apparently influenced their attitudes about this form of instruction.

Although simulation-exposed nurses were significantly more likely to select “not the real thing” as a barrier to ongoing participation, it is important to emphasize that this issue was considered less of a barrier than other issues, such as being videotaped. This is reinforced by the finding that only 25% of simulation-exposed nurses we surveyed reported difficulty suspending their disbelief, while 85% indicated that the overall educational value of the sessions was still high (Table 3). These data align with existing reports indicating that nursing students and medical students seem to think that high-fidelity human patient simulation is realistic.10,11 Taken together, our data suggest that prior simulation training is relatively common among newly employed nurses who practice in the hospital setting, and although this training may vary in its ability to represent reality, nurses seem to come away from these experiences with an optimistic opinion about simulation’s pedagogical benefits. Fulfilling the promise of simulation training for practicing nurses will depend on designing simulated clinical scenarios that convey the complexity of decision making that nurses routinely encounter in hospital-based practice.

Table 3

Table 3

Besides being significantly more likely to have had prior simulation training, nurses who selected “not the real thing” as a barrier were also significantly more likely to have 5 or fewer years of professional experience. This less-experienced cohort was also significantly more likely to report “lack of familiarity with equipment” as a barrier to participating in simulation training. Our survey instrument did not attempt to distinguish whether respondents interpreted the word “equipment” to mean the human patient simulator itself, or the emergency medical equipment that they might use to stabilize the simulated patient during a training session. However, our finding that less-experienced nurses were more likely to have undergone prior simulation training suggests that lack of confidence in their ability to use emergency medical equipment may be the barrier. Existing evidence suggests that this finding may not be unique to our study population. Several investigators have reported that even highly qualified nurses tend to wait for the arrival of a physician before defibrillating both simulated and actual patients in cardiac arrest.6,12,13

Effectively desensitizing less-experienced nursing staff to using emergency medical equipment without risking patient harm seems possible through periodic simulation training. De Vita and colleagues have demonstrated that multidisciplinary resuscitation teams enrolled in a simulation-based crisis team training course were able to complete more key tasks with each successive simulation session, which lead to improved survival of the simulated patient.14 As simulation training becomes more common for hospital-based nurses, educators will need to acknowledge the role of simulation in facilitating competent use of emergency equipment, while recognizing that less-experienced nurses come to the laboratory with significant concerns about their ability to demonstrate adequate knowledge of equipment in this setting. Reminding educators and coparticipants not to share information about what they witness during training sessions may be the most practical way for simulation facilities to address these types of concerns. Ultimately, as outcome measures for human performance in simulations are developed and validated, educators may need to adopt policies that allow protected time for individual participants to develop specific competencies before releasing information that would satisfy hospitals’ inevitable interest in tracking competency maintenance by collecting outcomes data from simulation facilities.

With regard to simulation training priorities, we found that less-experienced nurses tended to rate “providing opportunities to manage rare events” as a higher priority for simulation-based courses than their more experienced counterparts. This finding suggests that nurses in the first 5 years of professional employment may be motivated to attend simulation sessions that are dedicated to providing them with additional experience in this area. Naming “providing opportunities to manage rare events” as an educational priority was also significantly related to area of employment in the hospital; acute care nurses rated this as a higher priority than non-acute care nurses. This finding may be related to non-acute care nurses’ tendency to name “stressful or intimidating environment” as a barrier to participation in simulation significantly more often than their acute care nursing colleagues. It is also possible that some other unmeasured variable is responsible for this relationship. Our results suggest that educators may face significant challenges when trying to motivate more experienced nurses and nurses from non-acute care areas of the hospital to attend simulation sessions that require them to rehearse management of rare crisis events.

Our study has some noteworthy limitations. First, our survey instrument defined simulation as “… use of a high fidelity mannequin capable of physiologic and pharmacologic responses.” However, the focus of the simulation-based instruction that the respondents received could have ranged from basic skills training on the mannequin (ie, IV placement or patient assessment) to higher fidelity, full-scale event simulation. Such heterogeneity might account for the simulation-exposed nurses’ tendency to select “not the real thing” as a major barrier to ongoing participation. In general, conclusions regarding the impact of prior simulation experience on nurses’ perspectives should be drawn with caution, because most respondents with prior simulation experience reported having only one session (Table 1). Second, although we were able to capture responses from a large cohort of hospital-based nurses, our study was conducted in a single pediatric facility, which could limit the generalizability of our findings. Our study is also vulnerable to nonresponse bias due to our limited ability to capture responses from part-time and per diem employees, and because the population of nurses who engage in direct patient care in a single hospital is continually changing. In this context, it is difficult to know the degree to which the findings accurately reflect the attitudes of our entire study population at any given time, or hospital-based pediatric nurses in general.

Our data support the conclusion that barriers to nurses’ participation in simulation training as well as nursespriorities for simulation courses are influenced by prior simulation experience, professional experience, and the hospital area in which they work. These findings may assist educators in developing simulation-based training sessions that are sensitive to nurses’ concerns and tailored to their specific educational objectives. We believe this information could facilitate the integration of nurses into multidisciplinary team training for emergencies that arise among hospitalized patients.

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ACKNOWLEDGMENTS

The authors acknowledge the kind assistance of Georges Savoldelli, MD, who provided us with the survey instrument we adopted for use in this study. They also acknowledge the assistance of Mr. David Fowers, who provided IT support for the study. Finally, the authors thank the nursing staff at Primary Children’s Medical Center for their participation.

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REFERENCES

1. Monti EJ, Wren K, Haas R, et al. The use of an anesthesia simulator in graduate and undergraduate education. CRNA 1998;9:59–66.
2. Rauen CA. Using simulation to teach critical thinking skills. You can’t just throw the book at them. Crit Care Nurs Clin North Am 2001;13:93–103.
3. Nehring WM, Lashley FR. Use of the human patient simulator in nursing education. Annu Rev Nurs Educ 2004;2:163–181.
4. Schon D. Educating the Reflective Practitioner: Toward a New Design for Teaching and Learning in the Professions. San Francisco: Jossey-Bass; 1987.
5. Mezirow J. Transformative Dimensions of Adult Learning. San Francisco: Jossey-Bass; 1991.
6. Marsch SC, Tschan F, Semmer N, et al. Performance of first responders in simulated cardiac arrests. Crit Care Med 2005;33:963–967.
7. Abella BS, Kim S, Edelson DP, et al. Difficulty of cardiac arrest rhythm identification does not correlate with length of chest compression pause before defibrillation. Crit Care Med 2006;34(12 Suppl):S427–S31.
8. Savoldelli GL, Naik VN, Hamstra SJ, et al. Barriers to use of simulation-based education. Can J Anaesth 2005;52:944–950.
9. Nehring WM, Lashley FR. Current use and opinions regarding human patient simulators in nursing education: an international survey. Nurs Educ Perspect 2004;25:244–248.
10. Kuznar K. Associate degree nursing students’ perceptions of learning using a high-fidelity human patient simulator. Teach Learn Nurs 2007;2:46–52.
11. Gordon JA, Wilkerson WM, Shaffer DW, et al. “Practicing” medicine without risk: students’ and educators’ responses to high-fidelity patient simulation. Acad Med 2001;76:469–472.
12. Coady EM. A strategy for nurse defibrillation in general wards. Resuscitation 1999;42:183–186.
13. Murphy M, Fitzsimons D. Does attendance at an immediate life support course influence nurses’ skill deployment during cardiac arrest? Resuscitation 2004;62:49–54.
14. DeVita MA, Schaefer J, Lutz J, Dongilli T, Wang H. Improving medical crisis team performance. Crit Care Med 2004;32(2 Suppl):S61–S65.
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APPENDIX: SIMULATION EDUCATION QUESTIONNAIRE

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Keywords:

Simulation; Crisis resource management; Nurses; Nursing education; Training; Education; Attitudes; Barriers; Priorities; Survey

© 2008 Society for Simulation in Healthcare