Response of Flight Nurses in a Simulated Helicopter Environment

Air Medical Journal xxx (2017) 1e4

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Response of Flight Nurses in a Simulated Helicopter Environment David M. Kaniecki, DNP, MSN, ACNP-C, RN, CCRN *, Ronald L. Hickman Jr., PhD, RN, ACNP-BC, FAAN, Celeste M. Alfes, DNP, MSN, RN, Andrew P. Reimer, PhD, RN Student of Doctor of Nursing Practice, Frances Payne Bolton School of Nursing, Case Western Reserve University, Cleveland, OH

a b s t r a c t Objective: The purpose of this study was to determine if a helicopter flight simulator could provide a useful educational platform by creating experiences similar to those encountered by actual flight nurses. Methods: Flight nurse (FN) and non-FN participants completed a simulated emergency scenario in a flight simulator. Physiologic and psychological stress during the simulation was measured using heart rate and perceived stress scores. A questionnaire was then administered to assess the realism of the flight simulator. Results: Subjects reported that the overall experience in the flight simulator was comparable with a real helicopter. Sounds, communications, vibrations, and movements in the simulator most approximated those of a real-life helicopter environment. Perceived stress levels of all participants increased significantly from 27 (on a 0-100 scale) before simulation to 51 at the peak of the simulation and declined thereafter to 28 (P < .001). Perceived stress levels of FNs increased significantly from 25 before simulation to 54 at the peak of the simulation and declined thereafter to 30 (P < .001). Perceived stress levels of non-FNs increased significantly from 31 before simulation to 49 at the peak of the simulation and declined thereafter to 25 (P < .001). There were no significant differences in perceived stress levels between FNs and non-FNs before (P ¼ .58), during (P ¼ .63), or after (P ¼ .55) simulation. FNs' heart rates increased significantly from 77 before simulation to 100 at the peak of the simulation and declined thereafter to 72 (P < .001). Conclusion: The results of this study suggest that simulation of a critical care scenario in a high-fidelity helicopter flight simulator can provide a realistic helicopter transport experience and create physiologic and psychological stress for participants. Copyright © 2017 by Air Medical Journal Associates

Flight nurses (FNs) require extensive and ongoing training to perform their jobs adequately. Current methods to prepare FNs are expensive and time-consuming, partially because of the low flight volume and relatively few critical experiences encountered during FN orientation. The helicopter emergency medical service (HEMS) industry relies heavily on actual patient transports to develop FN competency within the helicopter environment (ie, learning on the job). The use of simulation has become widespread to train health care professionals in critical and emergency care settings1 and is increasingly prevalent in the HEMS industry. Although the impact

* Address for correspondence: David M. Kaniecki, DNP, MSN, ACNP-C, RN, CCRN, Student of Doctor of Nursing Practice, Frances Payne Bolton School of Nursing, Case Western Reserve University, Cleveland, OH. E-mail address: [email protected] (D.M. Kaniecki). 1067-991X/$36.00 Copyright © 2017 by Air Medical Journal Associates http://dx.doi.org/10.1016/j.amj.2017.02.005

of simulation on patient-oriented outcomes is unknown,2e4 most participants report increased confidence and feeling better prepared for actual clinical practice after simulation training.5e8 Winkelmann et al9 recently showed beneficial effects of simulator-based medical training in experienced emergency air medical staff. Although increasingly used, the degree to which high-fidelity flight simulation can replicate actual FN experiences remains unknown. Therefore, the purpose of this study was to examine whether simulation of a critical care scenario in a high-fidelity helicopter flight simulator could provide a realistic helicopter transport experience and create physiologic and psychological stress for participants. Methods Design A mixed methods exploratory descriptive study was conducted, and internal investigational review board approval was obtained

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(2016-1520). The 2 primary objectives were 1) to identify which components of the high-fidelity flight simulator most replicated that of a real-life helicopter environment and 2) to determine if patient care simulation in this simulated helicopter environment could create a stressful event with measurable changes in heart rate (HR) and perceived stress survey scores. Setting and Sample Simulation of an emergency critical care scenario occurred in a patient care high-fidelity helicopter simulator fabricated using a retired Sikorsky S-76 aircraft frame with a medically configured interior. All participants were age 18 years or older, able to read and understand English, and either a current registered nurse working in HEMS or a non-FN. Participants were directed to avoid caffeine before the study, and those taking medications for asthma, heart problems, blood pressure, thyroid, depression, anxiety, and/or a cold were excluded from HR analysis. All participants were later subdivided into 2 groups for analysis: group 1 included all FNs, and group 2 included non-FN participants (ie, paramedics and emergency/critical care nurses). Study Protocol Subjects were exposed to a clinical scenario an FN is likely to encounter in practice. Participants were asked to transport a patient having an active inferior wall ST-segment elevation myocardial infarction and were expected to manage the following conditions: hypotension after receiving sublingual nitroglycerin, stable ventricular tachycardia, and ventricular fibrillation (V-fib) cardiac arrest. All participants were exposed to the same simulation lasting 15 minutes and the same preprogrammed patient scenario using the ALSi (iSimulate Pty Ltd, Albany, NY) platform. ALSi runs on 2 iPads (Apple, Cupertino, CA) and uses 1 iPad as a controller (the facilitator) and the second iPad as the student display.10 Physiologic stress was measured with HR using a Polar RS400 (Polar Electro Oy, Kempele, Finland) monitor, and psychological stress was measured via self-report using a perceived stress sliding bar scale with values ranging from 0 (no stress) to 100 (most stress). To limit possible confounding of the crew partner effect on stress level, the same research assistant acted as each subject's partner during simulation. Researchers anticipated that the layout of the provided medical equipment (ie, medical bags) would differ from what participants were accustomed to in their normal setting. The inability for participants to find equipment rapidly may have created stress and confounded results. Therefore, for our simulation, researchers informed participants that the research assistant was familiar with the medical equipment and how to operate the monitor. Participants were instructed to direct our research assistant as needed for patient care. Interventions within our scenario were designed and timed so they could be completed by a single individual. Each FN participant was informed that he or she was considered to be the team leader and to assign, as much as possible, specific tasks to the research assistant who would then provide patient intervention. Once the simulation was finished and stress measurements obtained, subjects completed an online Qualtrics Survey (Qualtrics, Provo, UT) using a computer located next to the flight simulator. Demographic data, work history, and prior simulation experience were reported by all participants. FNs were questioned about which components of the flight simulator were similar to a real-life helicopter environment. The non-FNs (group 2) were not offered this line of questioning. Data indicative of participant performance during the simulation were collected to determine whether or not the patient was managed appropriately. Appropriate patient management was defined as 1) fluid bolus given to correct hypotension after the patient was given nitroglycerin in the setting of an inferior

wall ST-segment elevation myocardial infarction, 2) application of defibrillation pads either before or during a 10-second run of ventricular tachycardia, and 3) rapid identification (0 < 30 seconds) with subsequent immediate defibrillation of witnessed V-fib arrest. Patient management information was collected for internal assessment of participant performance and to guide the debriefing component of the simulation. Measurements and Key Outcome Measures Realism of the simulator was assessed via a survey using a 7-point Likert scale (strongly agree, agree, somewhat agree, neutral, somewhat disagree, disagree, and strongly disagree). We developed the realism survey by incorporating traditional physical senses of sight, hearing, smell, and touch into our assessment. After simulation, participants with experience in HEMS rated the sounds, vibrations, smells, views, movements, and overall experience of the simulator compared with their own real-life experiences. Evaluation of the stress response was performed using HR and perceived stress with repeated measures analysis of variance (ANOVA) at 3 time points: mean HR before the simulation, peak HR during simulation, and mean HR after the simulation. Polar RS400 HR monitors were applied immediately after written consent was obtained, and HR was recorded in a single continuous measurement at 5-second intervals. The RS400 has proven reliability measuring HR with correlation coefficients ranging from 0.97 to 1.00.11 HR before simulation was obtained while subjects sat in a chair for 10 minutes. We used the mean HR of the final 2-minute period (minutes 8-10) as our HR time 1 measurement. Participants then proceeded to simulation, and the peak HR during simulation was our time 2 measurement. Once the simulation was completed, subjects returned to the same chair, and the postsimulation HR was collected for an additional 15 minutes. The mean HR recorded during the 2-minute period between 40 and 42 minutes was used as the time 3 measurement. Perceived stress levels were recorded using a 0 (none) to 100 (most) sliding bar scale immediately before simulation (ANOVA time 1). Peak and postsimulation stress levels (ANOVA times 2 and 3) were measured immediately after simulation. Data Analysis Survey data were collected directly from participants with the Qualtrics Survey platform via a personal computer and then imported into IBM SPSS Statistics 24.0 (IBM, Armonk, NY) for analysis. HRs were extracted from the Polar RS400 using Polar ProTrainer 5 software and then exported into Excel (Microsoft, Redmond, WA). Mean before, peak during, and mean postsimulation HRs were calculated for each participant in Microsoft Excel and then imported into SPSS Statistics 24.0 for analysis. Descriptive statistics were used to identify outliers, data entry errors, and variable distributions in preparation for analysis. Tabulations were also used to examine participants' perceptions of the simulator compared with a real-life helicopter. Researchers examined the change in participants' perceived stress levels and HRs for times 1 through 3 using repeated measures ANOVA. Model assumptions, including sphericity and linearity, were verified using the Mauchly test and the ShapiroWilk test, respectively. All variables approximated a Gaussian distribution; however, the Greenhouse-Geisser correction for sphericity was used to reduce the likelihood of type I error in the absence of equal variances. Bonferroni post hoc comparisons and linear contrasts were used to determine whether stress responses significantly varied over the 3 time points. Alpha was set a priori at .05.

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(P < .001). Figure 1 includes a line graph depicting the mean HR variations for all recorded HRs over the course of the simulation.

Table 1 Sample Distribution by Participant Status

Sex Male Female Age, median (range) Race/ethnicity White Hispanic Work history (years) Intensive care unit, median (range) Emergency department, median (range) Air medical transport, median (range)

3

Overall (N ¼ 19)

FN (n ¼ 11), Group 1

Non-FN (n ¼ 8), Group 2

n (%)

n (%)

n (%)

11 (57.9) 8 (42.1) 34 (23-55)

5 (45.5) 6 (54.5) 36 (30-55)

6 (75.0) 2 (25.0) 31 (23-43)

18 (94.7) 1 (5.3)

11 (100) 0 (0)

7 (87.5) 1 (12.5)

3 (0-21)

3 (0-21)

1.5 (0-7)

1 (0-25)

4 (0-25)

.5 (0-5)

2.5 (0-13)

5 (1-13)

0 (0-1)

All percentages are column percents.

Results Descriptive information about the sample is provided in Table 1. Of the 19 participants in our study, there were 11 FNs and 8 non-FNs. Slightly more than half of the sample was male, and nearly all participants were white. The median age of all participants was 34 years, with a median duration of experience working in an intensive care unit of 3 years, an emergency department of 1 year, and air medical transport of 2.5 years. A Simulator Compared With a Real Helicopter The first objective of this study was to compare FN participants' experiences with the simulator compared with a real helicopter. Results are provided in Table 2. All participants agreed that the sounds and communications in the simulator approximated those of a real-life helicopter environment. More than half of the participants agreed (or strongly agreed) that simulator vibrations, views, and movements mimicked a real-life helicopter; 1 participant did not believe that the smells and views of the simulator were similar to a real helicopter environment. Stress Response: Perceived Stress The second objective of this study was to determine if patient care simulation in a simulated helicopter environment could create a stressful event with measurable changes in HR and perceived stress survey scores. The mean perceived stress scores of all participants (N ¼ 19) increased from 27 (standard deviation [SD] ¼ 21) before the simulation to 51 (SD ¼ 21) at the peak of the simulation. After the simulation, stress declined to 28 (SD ¼ 19). The mean perceived stress scores of FNs (n ¼ 11) increased from 25 (SD ¼ 23) before the simulation to 54 (SD ¼ 23) at the peak of the simulation. After the simulation, stress declined to 30 (SD ¼ 18). The mean perceived stress scores of non-FNs (n ¼ 8) increased from 31 (SD ¼ 18) before the simulation to 49 (SD ¼ 21) at the peak of the simulation. After the simulation, stress declined to 25 (SD ¼ 20). These time effects were all statistically significant (P < .001). There were no significant differences in perceived stress levels between the group of FNs and non-FNs before (P ¼ .58), during (P ¼ .63), or after (P ¼ .55) simulation. Stress Response: HR Complete HR recordings were obtained from 8 of 11 FNs. No HRs were obtained from non-FNs. The mean HR increased from 77 (SD ¼ 12) before the simulation to 100 (SD ¼ 15) at the peak of the simulation and declined to 72 (SD ¼ 10) after the simulation

Discussion This study was the first to establish the realism of a highfidelity full-motion helicopter simulator while creating a psychological and physiologic stress response during simulation. This study identified which components of the simulator were more akin to a real helicopter (communications, sounds, and vibrations) and can aid in the modification of this and future flight simulators in less similar areas (smells and views) to improve the overall realistic experience. High-fidelity simulated experiences in other high-stress practice settings such as emergency medicine, prehospital care, and anesthesia have also shown an increased stress response to simulation.2,12e15 Based on our findings, the high-fidelity flight simulator appears to create physiologic and psychologic stress while closely replicating a real helicopter environment. The significant increase in HR and perceived stress at the peak of the simulation and subsequent decrease in HR and perceived stress after the simulation suggested that participation in the simulation increased participants' stress levels. Additionally, we were unable to detect significant differences in the perceived stress levels of FN and non-FN participants, which may be because of the limited sample size, but may also suggest that this simulation modality is a useful tool for training and assessing new and practicing FNs. The literature is clear that stress levels may impair learning, decision making, and performance in high-stress situations such as an aviation emergency or simulated patient resuscitation.16e18 A more complete understanding of the individual stress response during flight simulation may allow us to improve the overall effectiveness of simulation in this environment. For example, scenarios may be individually tailored and based on experience in order to avoid scenarios that push learner stress levels beyond a point of effective learning. A better understanding of this stress response may also allow instructors to slowly increase the stress level of each new scenario or optimize teaching time points, such as debriefing, to times in which stress levels are less likely to impair learning. Conceivably, future simulation competency may require students to remain calm during simulation (ie, avoid high levels of stress or have a rapid return to baseline), which can be quantified using physiologic measurements. The intent of this exploratory descriptive study was to provide a basis for future qualitative and quantitative research. The limitations of this study are consistent with this type of design. These limitations include an inability to show a causal relationship or predictor of stress response (ie, it is unclear what caused stress, only that it was present). Our use of a subjective measure of selfreported stress does not identify the actual source(s) of the stress. The number of recorded HRs (n ¼ 8) in our study was relatively low and may only be a reflection of the FNs who participated in this study. Because all FNs who participated were from 1 of only 3 flight programs, our findings may reflect the training environment and/or instructional methods of these programs and may not be generalizable beyond our local setting. HR elevations may have been caused by movements during the simulation. In particular, several FNs began chest compressions while preparing for defibrillation immediately upon identification of the V-fib arrest, which likely contributed to an elevated HR. Conclusion The results of this study suggest that simulation of a critical care scenario in a high-fidelity helicopter flight simulator can provide a realistic helicopter transport experience and create

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Table 2 The Flight Simulator Is Similar to a Real-life Helicopter

Sounds Communications Vibrations Smells Views Movements Overall

Strongly Agree, % (n)

Agree, % (n)

Somewhat Agree, % (n)

Neither Agree Nor Disagree, % (n)

Somewhat Disagree

Disagree, % (n)

Strongly Disagree

45.5 72.7 36.4 9.1 36.4 45.5 45.5

54.5 27.3 27.3 27.3 27.3 36.4 45.5

d d 36.4 27.3 18.2 9.1 9.1

d d d 27.3 (3) 9.1 (1) 9.1 (1) d

d d d d d d d

d d d 9.1 (1) 9.1 (1) d d

d d d d d d d

(5) (8) (4) (1) (4) (5) (5)

(6) (3) (3) (3) (3) (4) (5)

(4) (3) (2) (1) (1)

Figure 1. The mean of all recorded HRs during entire simulation. The time points tested with ANOVA include (1) mean HR before simulation, (2) peak HR during simulation, and (3) mean postsimulation HR. Simulation summary: (A) HR collected before simulation gradually elevates while waiting for simulation. (B) The walk to the simulator elevated HR. (C) Simulation progressively elevated HR with hypotensive episode and run of ventricular tachycardia. (D) V-fib arrest (or performing cardiopulmonary resuscitation) during scenario elevated HR. (E) HR after V-fib arrest trended back toward the presimulation level. (F) Walk away from simulator elevated HR. (G) HR after simulation appears to be lower than presimulation.

physiologic and psychological stress for participants. Future studies are needed to confirm our findings and discern what components of the simulation contribute to developing stress during the simulation (ie, helicopter environment, scenario, and physical activity).

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