| 2023 Journal of the Academy of Health Sciences: A Pre-Print Repository | Categories Paper

Simulation Stress: Positive Challenge or Negative Threat?

by Angela Coker, MD ↓; Deirdre Caplin, PhD. MS ↓; Brian F. Flaherty, MD ↓; Stefanie Pease-Romero, MSN, RN, CHSE ↓; Wendy Dahmen, MSN-Ed, RN ↓; Angela P. Presson, PhD, MS ↓; Zhining Ou, MS ↓ & Jared W. Henricksen, MD, MS-HPEd ↓

Introduction

Simulation-based education (SBE) is used to teach healthcare providers clinical knowledge, communication skills, crisis resource management, and team dynamics [1–4]. However, SBE may be stressful to participants as it exposes educational gaps and often requires performance in front of peers [5,6]. Stress can enhance learning when perceived as positive and challenging or impair learning when perceived as negative and threatening [7–10]. While stress may be inherent in SBE, it remains largely unknown how participants experience stress, which participants are at higher risk of negative stress, and what the best practice is for SBE facilitators to manage participants’ stress. A better understanding of SBE-related stress is needed to identify participants at risk for negative stress and to guide SBE facilitators to prioritize emotional recovery or learning during simulation sessions.

One approach to understanding the impact of stress is examining participants’ self-appraisal of stress known as cognitive appraisal. Individuals appraise a situation in two ways: 1) as a challenge if conscious and subconscious resources outweigh the demands of a task at hand, or 2) as a threat if the demands are greater than available resources [11–15]. Challenge appraisal is associated with benefits likely to impact SBE participants’ learning in a positive way such as increased positive affect and effective adaptive physiologic responses [16,17]. Threat appraisal is likely to negatively impact SBE participants’ learning experience and is incongruent with the principles of psychological safety in simulation environments [18–22].

In this prospective cohort study, we will assess challenge and threat cognitive appraisal among SBE participants before and after a simulation scenario. We will evaluate SBE participant factors associated with their cognitive appraisal including demographics, prior SBE experience, global perceived stress, and baseline risk for anxiety disorders. We hypothesize that most SBE participants will appraise their stress as a challenge rather than a threat, where participants earlier in their career or training and those with less simulation experience being more likely to appraise their stress as a threat. We will also examine whether SBE facilitators are able to identify participants who experience SBE as a threat by using a psychological distress identification tool [5]. We hypothesize that participants assigned higher psychological distress scores will be more likely to appraise their stress as a threat.

Methods

This study was approved by the University of Utah institutional review board. Simulation participants at the Primary Children’s Hospital Simulation Center going through their regularly-scheduled simulation training sessions between March to September 2020 were recruited to take surveys before and after one of their simulation events as part of this study. Most sessions were multidisciplinary and included practicing nurses, patient care technicians, respiratory therapists, and providers such as an attending physician, fellow, resident, nurse practitioner (NP), or physician’s assistant (PA). Some sessions had only nurses, and there were no student participants in this study. The sessions were formative and confidential. All two-hour simulation sessions consisted of a prebrief, a short brief before two simulation scenarios with high-fidelity mannikins each followed by a debrief, and a summary at the end. The sessions were facilitated by Intermountain Health-certified simulation facilitators with a simulation specialist present to operate the mannikin. An unrestricted variety of simulation scenarios were used with variable learning objectives, all chosen from a scenario library by the facilitator to suit the needs of the participant group which ranged from novice to expert. All participants were shown a consent cover letter indicating participation in the study was voluntary prior to accessing the study surveys. Survey responses were collected via REDCap, an internet-based database and survey tool [23]. Surveys were accessed by a QR code linking to REDCap where participants entered a simulation session event number to identify simulation type, and an individual study number assigned to them when they entered the simulation center to keep participant responses anonymous.

Participants were surveyed at two time points: 1) after the session prebrief and before the first scenario brief, and 2) after the first scenario was complete and before the first debrief. The pre-scenario survey included questions about demographics, healthcare role, prior simulation experience, and the following three surveys: the National Institute of Health (NIH) Perceived Stress Scale (PSS), the Generalized Anxiety Disorder screening tool (GAD-7), and the Acute Stress Appraisal survey (ASA). See appendix A to view these study surveys.

  1. NIH PSS: This survey quantifies the degree of perceived stress over the past month by assessing how much control respondents feel they have over their lives. For this 10-item survey, an uncorrected T-score of ≤40 indicates low levels of stress while a score ≥60 suggests high levels of perceived stress [24,25].
  2. GAD-7: This survey quantifies baseline anxiety through a 7-item survey assessing anxiety symptoms over 2 weeks to measure severity of symptoms and risk of having an anxiety disorder. A total score of 0-4 indicates no anxiety disorder, 5-9 indicates a mild anxiety disorder, 10-14 a moderate anxiety disorder, and more than 14 indicates a severe anxiety disorder [26,27].
  3. ASA: The Acute Stress Appraisal survey (ASA) determined the cognitive appraisal ratio of threat or challenge and was used with permission from the developer, Wendy Mendes, PhD of University of California San Francisco [28]. This survey is commonly used in psychology research and asks respondents about their capability to handle a stressful task. The survey has two parts with 12 questions answered before a task is completed (ASA pre) and 10 questions answered after the task is done (ASA post) to assess the demands on the participant and resources available to the participant before and after task completion. A threat ratio is then calculated by dividing the demand score by the resource score. A threat ratio >1 indicates the stress associated with a task is threatening (demands exceed resources) while a ratio ≤1 indicates the stress associated with a task is challenging (resources exceed demands). Each participant filled out the ASA pre that was part of the first survey before the brief of the first simulation scenario, and filled out the ASA post in the second survey after the scenario was complete and before the debrief was done.

Session facilitators were all clinical personnel who regularly facilitate simulation sessions, but none were psychologists or psychiatrists. At the end of the simulation session, the session facilitator assigned each participant a psychological distress level (PDL). This level was determined by using the Simulation Psychological Distress Algorithm, a measure designed by Henricksen, et al. to assist facilitators in recognizing and beginning to assist any simulation participant who may be in a psychologically distressed state [5]. The algorithm has four levels of distress: 0 (none), 1 (mild), 2 (moderate), and 3 (severe). Levels are based on facilitator-observed behavior that may indicate psychological distress such as participant withdrawal from the group, tearfulness, anger or raised voice. The PDL was matched to participant surveys in REDCap by the assigned individual study number. Every facilitator scored simulation participants on the PDL scale at the time of the simulation session and were blinded to all participant survey results such as baseline anxiety levels and stress appraisal. Each facilitator had immediate access to select study authors (Coker and Dahmen) to collaborate regarding PDL scoring of each participant to minimize inter-rater scoring differences. Each session only had one facilitator.

Statistical Analysis. Participants were excluded from analysis if they did not complete both the pre and post scenario surveys. Demographics and clinical outcomes of interest were summarized using mean and standard deviation (SD) or median and interquartile range (IQR) for continuous variables. For categorical variables, counts and percentages were reported. Participants were categorized into one of four outcome groups based on the stress state from the ASA pre and post surveys: Challenge/Challenge, Challenge/Threat, Threat/Challenge, and Threat/Threat. Demographic, PSS, and GAD-7 data were compared between these four groups using the Wilcoxon rank sum test for skewed continuous variables and chi-squared or Fisher’s exact test for categorical variables. Univariable logistic regression models evaluated the association between the dichotomized outcome Challenge/Challenge versus the other three combinations (Challenge/Threat, Threat/Challenge, and Threat/Threat) for each variable of interest. Variables with p-value<0.10 were included in a multivariable logistic model. Odds ratios (ORs) and 95% confidence intervals (CIs) were reported. Statistical significance was assessed at the 0.05 level. PDL and ASA scores were compared in a cross-tabulation table using Fisher’s exact tests. Statistical analyses were implemented using R v. 4.0.3 (R Core Team, 2020).

Results

Five-hundred and fifty-one pediatric healthcare personnel participated in the study. Four hundred eighty-five (485) participants completed both surveys and sixty-six (66) participants completed only one of the surveys and were therefore excluded due to incomplete data. A summary of demographic information, job variables, simulation experience and type, and PSS, GAD-7, and ASA pre/postsurvey scores are shown in Table 1. The majority of participants were nurses (n=347, 71.5%). Forty-three (43) medical trainees participated in the study, and 40% were in their first year of training. The majority (92.2%) of participants had completed at least one simulation session in the past two years. Almost half (48.7%) of simulation scenarios were for non-critical care groups working in the medical/surgical unit, same day surgery center, or post-anesthesia care unit. The vast majority (99.4%) of participants scored 40 or less on the PSS, indicating low perceived stress over the last month (median 32, IQR 30-34). On the GAD-7, 80.3% of participants scored in the “no” or “mild” anxiety disorder range.

The four ASA state groups are compared in Table 2. The majority of participants (n=325, 67.6%) appraised their stress as a challenge before and after the simulation scenario (Challenge/Challenge). Eighty-one participants (16.7%) appraised their stress as a threat before the scenario and a challenge after the scenario (Threat/Challenge). 9.9% and 5.8% were in the Challenge/Threat and Threat/Threat groups, respectively. There was a statistically significant difference between the four ASA state groups when looking at job type, simulation type, years in practice and training, and anxiety disorder scores. There was no statistically significant difference in prior SBE participation, gender, and chronic stress scores between the four groups. Results of logistic regression analysis comparing the Challenge/Challenge group to the other three ASA state groups are shown in Table 3. Univariable logistic regression showed that nurses and assistive personnel (patient care technicians and respiratory therapists) were more likely to appraise their stress as a challenge rather than a threat compared to advanced providers (attending physicians, NPs, and PA’s). Trainees (residents and fellows) were analyzed separately from attending physicians. When compared to advanced providers, assistive personnel were 10 times more likely to be in the Challenge/Challenge group (p<0.001, OR 10.31172[3.15-38.05]), and nurses were 4 times more likely to be in the Challenge/Challenge group (p=0.012, OR 4.09[1.42-13.38]). Simulation type and chronic stress scores were not significant in univariable regression analysis. Prior simulation experience was variably significant, with those who attended three or more simulation sessions in the past two years ultimately being more likely to appraise stress as a challenge in multivariate analysis. In multivariable logistic regression analysis, nurses, assistive personnel, and participants with lower anxiety disorder scores continued to be significantly more likely to appraise stress as a challenge.

Table 4 displays results comparing participant ASA scores with facilitator-assigned PDL scores. Of 23 participants in the Threat/Threat group, one was given a distress score 1 or higher. Thirteen participants were given a distress score 1 or higher out of 282 participants in the Challenge/Challenge group. Overall, there was no association between the PDL and ASA scoring (p>0.99).

Discussion

Our survey study of cognitive appraisal in SBE participants primarily aimed to categorize simulation-induced stress as challenging or threatening and to identify participant and simulation factors predictive of cognitive appraisal. This is the largest and only multidisciplinary study of cognitive appraisal in SBE.

Other studies have used the challenge and threat stress state to characterize simulation participants. Carenzo, et al. showed that residents in a simulation-based competition performed better when they were in a challenge state with a high level of resources until demands increased, shifting towards a threat state [29]. In their study, a greater level of training and higher self-confidence were associated with challenging stress, and state anxiety levels were not. Harvey, et al. showed that threat appraisal is associated with more difficult simulation scenarios and higher salivary cortisol levels [30]. In contrast to these studies, our study did not show that simulation type was significantly associated with the challenge or threat state, perhaps indicating there were participants who appraised their stress as a challenge and threat in every type of simulation despite any level of simulation difficulty. Also, our study used the GAD-7 which measures risk for an anxiety disorder rather than state anxiety levels and we made no attempt to correlate participant physiology to psychology.

This study defined four groups of simulation participants depending on their stress appraisal before and after simulation: Challenge/Challenge, Challenge/Threat, Threat/Challenge, and Threat/Threat. We found that 68% of participants appraised their stress surrounding a simulation scenario as a challenge rather than a threat before and after simulation (Challenge/Challenge group). Nurses and assistive personnel had higher odds of appraising simulation stress as a challenge compared to advanced providers. Lower anxiety disorder screening scores and more simulation experience were also associated with the Challenge/Challenge appraisals.

Advanced providers were less likely to be in the Challenge/Challenge group than nurses and assistive staff. This may be because advanced providers are often expected to take the team leader roles and may have more expectations placed on them during a scenario either by themselves or by other participants. They may worry about a loss of respect from the rest of the multidisciplinary team when knowledge gaps are revealed. Trainees were not significantly different from advanced providers on univariable analysis.

Our findings support our hypothesis that most SBE participants appraise simulation-induced stress as a challenge. Challenge appraisal indicates participants feel they have the experience, knowledge, and skills (i.e., resources) to confront the simulation scenario even if the content is unfamiliar to them. Challenging stress is associated with improved performance and personal growth [13,29].

It seems intuitive that some (17% in our study) who appraise their stress as a threat before simulation were relieved when the simulation was done and appraised their stress as a challenge after simulation (Threat/Challenge group). We recognize that less than 6% of participants appraised their stress as a threat before and after simulation (Threat/Threat group), and some (~10%) appraised their stress a challenge before simulation and switched to threat after simulation (Challenge/Threat group). These last two groups are intriguing and warrant more study.

We further aimed to evaluate facilitators’ abilities to accurately identify participants whose ASA scores would indicate they are in a threatened stress state by having the facilitators assign PDL scores. Contrary to our hypothesis, there was no relationship between PDL and ASA scores. This indicates facilitators are not able to accurately associate observed simulation participant behaviors with a participant’s appraisal of stress. Henricksen, et al previously showed that PDL scores > 0 are rare in simulation, occurring in <1% of participants [5]. In our study, 4% of participants had a PDL of 1 or higher. Yet, despite a higher incidence of PDL scores, there was no correlation to ASA scoring. Unless a participant is having an exceptional emotional response, it may be near impossible to know who is in a threatened state.

Healthcare providers are trained to work in stressful conditions and can internally regulate their emotions while remaining functional in their jobs [31]. What is perceived as distress by a facilitator may be excitement or distraction for a participant. All personnel have impression management skills that can defy facilitators’ skills in detecting most threatening stress [32,33]. Thus arises a debriefing conundrum where most SBE participants are in a challenge state and ready to learn, but a small percentage of participants exist in a hidden threatened state.

We propose that pragmatic debriefing with emotional surveillance be used to help the majority of simulation participants obtain maximal simulation benefit. Most particpants are likely to be in a challenge state and all participants have impression management skills that may defy facilitator identification of psychological distress. Thus, those in a threatened state are hidden amongst simulation participants. By focusing on learning objectives as well as discovering what happened and what consequences of actions occurred during simulation, debriefing can concentrate on improving performance. Being watchful for signs of psychological distress will help every facilitator maintain awareness that simulation is threatening to some participants, and there may be a participant that needs special attention. Monitoring participants for psychological distress and offering assistance when appropriate is what we can do to help those in a threatened state, given the difficulty of identifying them. Incidentally, helping each team member improve may help them psychologically rather than exposing their threatened state to every participant.

This study does have limitations. Generalizability of these results may be limited since this is a single center study. Employees providing direct patient care at Primary Children’s Hospital are required to attend simulation sessions with their units at least once a year and are frequently exposed to the concept of psychological safety. Our institutional culture may make SBE participants more comfortable in the simulation center than in an institution where simulation is less routine, and may have affected study results. Institutional simulation culture may need to be understood better to understand stress in simulation. Our study population may also affect generalizability. Nurses were well represented, but other types of healthcare providers such as resident and fellow trainees were a smaller proportion of the study population making it difficult to draw absolute conclusions about this group. Although study authors were available to assist facilitators in assigning PDL scores to each study participant, inter-rater reliability was not measured because of study authors’ availability to every facilitator. Thus, assigned PDL scores were given from the perspective of two consistent study personnel and a session facilitator who all observed the study participants and the scores may be subject to any observer bias they may have had. Further research with a more balanced study population would make it easier to assess differences between advanced practitioners, nurses, trainees, and assistive personnel. Also, we did not study the effect of debriefing on cognitive stress appraisal. We assessed stress states immediately after a simulation scenario but before debriefing. It is possible that debriefing can provide support to SBE participants and change their cognitive appraisal to favor a challenge state. Future studies could repeat the ASA post survey after debriefing to investigate if debriefing changes a participant’s cognitive appraisal. Different debriefing strategies could be studied using this ASA survey as well. Finally, data collection was interrupted by quarantine procedures during the start of the COVID-19 pandemic, which limited study participation and had an unknown effect on the baseline stress and anxiety of the participants.

This was a prospective cohort study assessing cognitive stress appraisal in participants engaged in multidisciplinary simulation scenarios. The results show that SBE stress is mostly appraised as a challenge, particularly for nurses, respiratory therapists, and patient care technicians compared to attending physicians, NPs, and PAs. More prior simulation experience and lower anxiety disorder risk scores were also associated with greater likelihood of challenge appraisal whereas time in healthcare role, chronic stress, and simulation type were not significant on multivariable analysis. Self-reported participant threatened stress appraisal was not correlated to facilitator-assigned distress scores, indicating facilitators are not likely to detect threatened participants by their behavior. The debate on whether to concentrate on the learning and improvement of the challenged majority or the emotional evaluation of the hidden and threatened minority may begin.

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Tables

Table 1. Summary of demographics and survey scores

Current Job Position/Credentials Chronic stress/PSS scores 
Advanced providers: Attending + NP + PA15 (3.1%)≤40 low stress482 (99.4%)
Assistive personnel: Tech + Resp Therapist + other80 (16.5%)40-60 moderate stress3 (0.6%)
Nurse347 (71.5%)Mean (SD)31.9 (3.3)
Trainees: Resident + Student + Fellow43 (8.9%)Median (IQR)32.0 (30, 34)
Current Year in Training (PGY) 1  17 (39.5%)Range(10, 43)
210 (23.3%)Chronic anxiety/GAD-7 scores 
  0-4 minimal anxiety203 (41.9%)
36 (14%)5-9 mild anxiety186 (38.4%)
45 (11.6%)10-14 moderate anxiety74 (15.3%)
5+5 (11.6%)15+ severe anxiety22 (4.5%)
Years in Practice Mean (SD)5.9 (4.4)
<2123 (27.8%)  
2-595 (21.5%)Median (IQR)5.0 (2, 8)
5-1093 (21%)Range(0, 21)
10+131 (29.6%)ASA pre scores <1 stress is a challenge  376 (77.5%)
Mean (SD)7.6 (8.3)>1 stress is threat109 (22.5%)
Median (IQR)5.0 (1.5, 10)Mean (SD)0.8 (0.4)
Range(0, 40)Median (IQR)0.8 (0.6, 1)
SBE participation (# sessions in past 2 years) Range(0.1, 2.6)
038 (7.8%)  
165 (13.4%)ASA post scores <1 stress is a challenge  409 (84.3%)
2192 (39.6%)>1 stress is threat76 (15.7%)
381 (16.7%)Mean (SD)0.7 (0.3)
440 (8.2%)Median (IQR)0.7 (0.5, 0.9)
5+69 (14.2%)Range(0.1, 2.6)
Gender   
Female427 (88%)  
Male58 (12%)  
Simulation type   
Dental Clinic13 (2.7%)  
ED/Obs unit68 (14%)  
PICU Fellows Boot Camp15 (3.1%)  
Med/Surg + Outpatient Procedures/PACU236 (48.7%)  
ECMO16 (3.3%)  
NICU14 (2.9%)  
Nurse Residency56 (11.5%)  
PICU67 (13.8%)  
Summary of demographics and job characteristics of participants, Generalized Anxiety Disorder-7 (GAD) results for likelihood of anxiety disorder, Perceived Stress Scale (PSS) results of amount of stress, Acute Stress Appraisal (ASA) score results before and after simulation for cognitive appraisal, and simulation type. All results are expressed as mean and percentage unless otherwise indicated.

Table 2. Summary of baseline variables stratified by ASA scores before and after a simulation scenario

 All: N=485Challenge/Challen ge (C/C): N=328Challenge/Thre at (C/T): N=48Threat/Challen ge (T/C): N=81Threat/Thre at (T/T):p-value
  Current Job Position/    N=28  <0.001s
Credentials      
Attending Physician + NP + PA15 (3%)5 (1.5%)6 (12.5%)3 (3.7%)1 (3.6%) 
Tech + Resp Therapist +80 (16%)67 (20.4%)3 (6.2%)6 (7.4%)4 (14.3%) 
Other Nurse  347  233 (71%)  33 (68.8%)  66 (81.5%)  15 (53.6%) 
 (72%)     
Resident + Student + Fellow43 (9%)23 (7%)6 (12.5%)6 (7.4%)8 (28.6%) 
Current Year in Training (PGY)     0.048f
117 (40%)6 (26.1%)1 (16.7%)3 (50%)7 (87.5%) 
210 (23%)8 (34.8%)0 (0%)2 (33.3%)0 (0%) 
36 (14%)4 (17.4%)1 (16.7%)1 (16.7%)0 (0%) 
45 (12%)2 (8.7%)2 (33.3%)0 (0%)1 (12.5%) 
5+5 (12%)3 (13%)2 (33.3%)0 (0%)0 (0%) 
Years in Practice     0.029s
<212376 (24.9%)19 (45.2%)19 (25.3%)9 (45%) 
 (28%)     
2-595 (21%)67 (22%)2 (4.8%)21 (28%)5 (25%) 
5-1093 (21%)70 (23%)9 (21.4%)13 (17.3%)1 (5%) 
10+13192 (30.2%)12 (28.6%)22 (29.3%)5 (25%) 
  SBE participation (#(30%)      0.26s
sessions in past 2 years)      
038 (8%)21 (6.4%)9 (18.8%)5 (6.2%)3 (10.7%) 
165 (13%)40 (12.2%)6 (12.5%)12 (14.8%)7 (25%) 
2192135 (41.2%)16 (33.3%)34 (42%)7 (25%) 
 (40%)     
381 (17%)58 (17.7%)4 (8.3%)13 (16%)6 (21.4%) 
440 (8%)28 (8.5%)4 (8.3%)6 (7.4%)2 (7.1%) 
5+69 (14%)46 (14%)9 (18.8%)11 (13.6%)3 (10.7%) 
Gender: Female427284 (86.6%)41 (85.4%)77 (95.1%)25 (89.3%)0.16f
  Chronic stress/PSS scores(88%)      0.30k
Median (IQR)32 (30,32 (30, 33.2)32 (29, 34)33 (30, 35)32 (30, 34) 
  Chronic anxiety/GAD-734)      0.004k
scores Median (IQR) Simulation type5 (2, 8)5 (2, 8)5 (2, 8.2)6 (4, 8)9 (5, 12)  <0.001s
Dental Clinic13 (3%)8 (2.4%)1 (2.1%)4 (4.9%)0 (0%) 
ED/Obs Unit68 (14%)52 (15.9%)4 (8.3%)10 (12.3%)2 (7.1%) 
PICU Fellows15 (3%)7 (2.1%)4 (8.3%)1 (1.2%)3 (10.7%) 
Med/Surg + Outpatient236167 (50.9%)12 (25%)40 (49.4%)17 (60.7%) 
Procedures/PACU(49%)     
ECMO16 (3%)6 (1.8%)3 (6.2%)5 (6.2%)2 (7.1%) 
NICU14 (3%)10 (3%)0 (0%)4 (4.9%)0 (0%) 
Nurse Residency56 (12%)28(8.5%)16(33.3%)8(9.9%)4(14.3%) 
PICU67 (14%)50(15.2%)8(16.7%)9(11.1%)0(0%) 
s Chi-squared test by Montecarlo simulation, f Fisher’s exact test, k Kruskal-Wallis test.
 
Summary of participant characteristics and survey scores grouped by combination of cognitive appraisal of challenge or threat before and after a simulation scenario. Results are expressed as mean and percentage unless otherwise indicated.

Table 3. Univariable and multivariable logistic regression comparing Challenge/Challenge to all others

UnivariableMultivariable
 OR (95% CI)p-valueOR (95% CI)p-value
Current Job Position/Credentials    
Attending Physician + NP + PAReference   
Tech + RT + other10.31<0.00116.4 (4.58,66.09)<0.001
 (3.15,38.05)   
Nurse4.09 (1.42,13.38)0.0124.9 (1.58,17.08)0.008
Resident + Student + Fellow2.3 (0.69,8.45)0.18––
Current Year in Training (PGY)    
1Reference   
27.33 (1.33,60.29)0.034––
33.67 (0.55,32.7)0.20––
41.22 (0.13,9.56)0.85––
5+2.75 (0.36,25.76)0.33––
Years in Practice    
< 2Reference   
2-51.48 (0.84,2.64)0.181.14 (0.6,2.17)0.69
5-101.88 (1.05,3.45)0.0371.5 (0.76,2.97)0.24
10+1.46 (0.87,2.47)0.161.52 (0.83,2.8)0.18
SBE participation (# sessions in past 2 years) 0    Reference   
11.3 (0.57,2.92)0.531.65 (0.66,4.23)0.29
21.92 (0.93,3.9)0.072.2 (0.92,5.33)0.08
32.04 (0.91,4.57)0.082.68 (1.04,7.02)0.042
41.89 (0.75,4.88)0.182.96 (1.02,8.9)0.049
5+1.62 (0.72,3.66)0.242.73 (1.05,7.24)0.04
Gender – Male1.58 (0.86,3.08)0.16––
Chronic stress/PSS scores0.97 (0.91,1.03)0.28––
Chronic anxiety/GAD-7 scores0.95 (0.91,0.99)0.0110.93 (0.89,0.98)0.005
Simulation type    
Dental ClinicReference   
ED/Obs Unit2.03 (0.55,7.01)0.27––
PICU Fellows0.55 (0.11,2.44)0.43––
Med/Surg + Outpatient Surg/PACU1.51 (0.44,4.7)0.48––
ECMO0.38 (0.08,1.65)0.20––
NICU1.56 (0.31,8.28)0.59––
Nurse Residency0.63 (0.17,2.11)0.46––
PICU1.84 (0.5,6.31)0.34––
Univariable and multivariable analysis of Challenge/Challenge group to all others combined. Variables that were statistically significant in the univariable analysis were included in the multivariable analysis.

Table 4: Cross-tabulation of Psychological Distress Level (PDL) versus Acute Stress Appraisal (ASA) scores

 PDL      ASA     
    C/C + C/T + T/CT/TC/T + T/C + T/TC/C
 No distress (=0)39123
1		132282
 Distress (=1/2/3)18613
Cross-tabulation of Participant Distress Level (PDL) assigned by simulation facilitator with Acute Stress Appraisal scores indicated by participants.

Appendix

GAD-7
Author: Wendy Berry Mendes, PhD. March 2017. Wendy.Mendes@ucsf.edu
Author: Wendy Berry Mendes, PhD. March 2017. Wendy.Mendes@ucsf.edu


Return to Table of Contents: 2023 Journal of the Academy of Health Sciences: A Pre-Print Repository

Simulation Stress: Positive Challenge or Negative Threat? by Angela Coker, MD, Deirdre Caplin, PhD. MS, Brian F. Flaherty, MD, Stefanie Pease-Romero, MSN, RN, CHSE, Wendy Dahmen, MSN-Ed, RN, Angela P. Presson, PhD, MS, Zhining Ou, MS & Jared W. Henricksen, MD, MS-HPEd