Integrating Virtual Simulation with Course Curriculum to Improve Patient Advocacy through Speaking Up

doi:10.21203/rs.3.rs-1829098/v1

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Research Article

Integrating Virtual Simulation with Course Curriculum to Improve Patient Advocacy through Speaking Up

https://doi.org/10.21203/rs.3.rs-1829098/v1

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Purpose Healthcare teams consist of interdisciplinary groups of health professionals that tend to be hierarchically structured. Often it is necessary to challenge authority through speaking up, however, within hierarchies’ individuals tend to demonstrate obedience to authority. Speaking up is an essential skill for preventing patient harm that must be developed. Virtual Simulation integrated with curriculum using Kolb’s Learning Cycle is a promising avenue for improving interprofessional collaboration.

Methods An experimental design was used to determine if a gamified VS along with instruction on patient-advocacy would increase the rate of speaking up in Respiratory Therapy students (n=34) during in-person simulation delivered one month after the classroom instruction. The in-person simulation required students to challenge a senior anesthesiologist to prevent patient harm. Effects of personality and individual differences were also examined.

Results The VS resulted in speaking up at a higher rate than in the control condition (p=0.04) and used CUS more often (p<0.001). No individual differences or personality measures were predictive of speaking up.

Conclusion The findings from the present study support the integration of VS with course curriculum on patient-advocacy, showing improved performance during in-person simulation one month after course delivery. Longitudinal investigation is necessary to determine if the improved performance is indicative of increased likelihood of speaking up in the future.

Simulation

Virtual Simulation

Speaking Up

Positive Deviance

Interprofessional

Challenging Authority

Allied Health

Engaging in Positive Deviance through speaking up (PD/SU) and challenging authority is an essential intraprofessional and interprofessional (IP) aspect of patient-centered care that prevents error and harm and improves patient safety (Holmes et al., 2014; Kaba et al., 2016; Kim et al., 2020). However, challenging authority can be very difficult, particularly for students (Milligan et al., 2017). In part, the challenge of speaking up is due to humans’ tendency towards obedience to authority (Blass, 2009). Obedience to authority is an ecologically rational heuristic that is generally adaptive and is socially and evolutionarily reinforced (Gigerenzer, 2010; Graham et al., 2018). The adaptiveness of obedience (Haidt, 2012) makes it difficult to override the heuristic and speak up (Grzyb et al., 2018); this poses a challenge for improving the rate at which healthcare professionals speak up. To present educational interventions and training on speaking up demonstrate inconsistent effects. There is a need to improve education and training on PD/SU with simple effect interventions that are compatible and non-disruptive to existing educational activities ^{(Daly Guris et al., 2019; Jones et al., 2021; Morrow et al., 2016; O’Donovan & McAuliffe, 2020)}.

Recently the use of virtual simulation (VS), also known as Screen Based Simulation, has grown including gamified simulation, or serious games, to address different aspects of healthcare delivery (Sipiyaruk et al., 2018). When integrated with course curriculum gamified VSs are a compelling method for training interpersonal communication and collaboration that provide a low-stakes experience where mistakes are acceptable. Further, VS allows for conducting asynchronous individual IP-focused activities that can help develop good individual IP collaborators ^{(Bainbridge & Regehr, 2015)}.

Virtual and real simulation are aspects of experiential learning that can be integrated with existing education through the Kolb/Lewinian learning cycle ^{(Fewster-Thuente & Batteson, 2018; Kolb, 1984)}. While theoretical justifications for simulation training often rely on Kolb’s experiential learning theory (ELT), there is a need to integrate better simulation and didactic forms of learning within Kolb’s cycle ^{(Monteiro & Sibbald, 2020)}. Prior research incorporating gamified VSs with didactic information through Kolb’s learning cycle demonstrates promising effects ^{(Fewster-Thuente & Batteson, 2018; Secheresse et al., 2020)}.

Integration can occur through a VS and debriefing on PD/SU to provide concrete experience and reflective observation, functioning as educational sensitization and priming through just-in-time learning for didactic instruction (Poore et al., 2014). Abstract conceptualization occurs through presenting new ideas and modifying existing ideas gained through concrete experience during classroom instruction on patient advocacy and speaking up. Active experimentation occurs during participation in a real simulation where the new and refined knowledge and skills obtained at previous stages of the learning cycle are applied. The experience of a high-impact compliance simulation for PD/SU may improve the likelihood of speaking up when students enter practicum and practice (Violato, 2021) (Figure 1).

When investigating the impact of personality and individual differences on speaking up there has been a focus on self-efficacy (Morrow et al., 2016; Okuyama et al., 2014; Oner et al., 2018; Roussin et al., 2018). While some personality characteristics have been investigated the effects are unclear, and further research is required (Peadon et al., 2020).

Integrating virtual and real simulation with existing classroom instruction is expected to have two effects: 1) Improved engagement with didactically delivered information resulting in enhanced performance in a real simulation. 2) A positive feedback loop where experience and improved performance during a high-intensity compliance simulation leads to greater confidence in speaking up and an increased possibility of speaking up in the future. Two research questions were developed to investigate these effects and attempt to enhance education for PD/SU for a student sample preparing to enter practicum:

1. Will integrating a virtual simulation with course curriculum on patient advocacy improve performance during an in-person simulation delivered one month after classroom instruction?

2. Will measures of individual differences predict the likelihood of making a successful challenge?

Procedures

The study consisted of a one-way experimental design completed in two stages (see Figure 2). Ethics approval was granted by the Northern Alberta Institute of Technology Research Ethics Board (#2021-03).

Stage One

In March 2021, second-year Respiratory Therapy (RT) students were scheduled to cover course content on patient advocacy, including instruction on speaking up and challenging authority. During the course, an emphasis was placed on the use of CUS, a structured method for escalating concern in a situation by stating you are Concerned, Uncomfortable and what is occurring is a Safety Issue (Gerstle, 2018). The sample cohort was targeted as their profession plays a vital role in ensuring patient safety during airway management (Rutherford et al., 2012) and was preparing to begin practicum placements in Fall 2021. Study materials, including consent form, individual difference measures, and VS, were hosted on Qualtrics ^{(Qualtrics XM, 2021)}. No deception was used. Participants were informed the purpose of the study was to enhance the retention of course material and improve speaking up skills. Participants in the experimental condition completed a gamified virtual asynchronous simulation using a Choose-Your-Own-Adventure format. In the VS the participants make choices for an emergency department respiratory therapist who is providing treatment to a status asthmatic. The simulation contained six decision points, two of which were therapeutic decisions and four of which related to IP competencies. At each decision point there was a correct choice, a partially correct choice, and one or two incorrect choices to choose from. Feedback was provided after each decision point in the simulation and participants had the ability to go backwards and try again if they chose incorrectly. To reach the conclusion of the simulation participants had to successfully use CUS to convince a doctor to provide appropriate attention and care to a patient. Participants were provided with a written debriefing about the simulation, the purpose of the simulation, and the need for speaking up (see supplemental material).

Individual Difference Measures

Data were collected on demographic characteristics, procedure-related confidence and experience, and four personality scales. The personality scales included 1) the Big Five, the Conscientiousness, and Agreeableness subscales have been linked with obedience and conformity (Bègue et al., 2015); 2) Moral Foundations Questionnaire (MFQ); The MFQ can be used to determine how moral dispositions influence obedience, in particular, In Group Loyalty and Respect for Authority (Doğruyol et al., 2019); 3) the Brief State Humility Scale, correlates with the honesty-humility subscale of the HEXACO (Kruse et al., 2017), low humility is associated with hierarchy orientation (Lee et al., 2009); 4) the very short version of the Authoritarianism-Conservatism-Traditionalism (ACT); authoritarian dispositions have been associated with group loyalty, conformity, and obedience ^{(Bizumic & Duckitt, 2018; Duckitt et al., 2010)}.

Stage Two

One month after course instruction, in April 2021, participants completed an in-person high-impact compliance simulation. A one-month delay was used to determine the short-term stability of learning. After the simulation, participants were debriefed and asked not to share information about the simulation with classmates, thanked for their participation, and dismissed.

The Scenario

The simulation was an interprofessional airway management scenario. A senior anesthesiologist was on the third attempt in a can’t-intubate scenario and the participant must challenge the anesthesiologist to prevent patient harm. Before the simulation the actors and facilitators received training and rehearsed the scenario. The actors were all Caucasian females between 40-50 years old and were instructed to act authoritatively. The actors were all registered RTs who had experience and confidence performing intubation. Facilitators were knowledgeable about patient advocacy and challenging authority and were experienced with conducting simulation and debriefing.

The scenario pre-briefing was presented in an OSCE style. Participants were told they were returning from lunch and a charge nurse informed them that Dr. Anderson from anaesthesia was attempting to intubate a patient and needed help. The participant needed to make three strong challenges to complete the scenario successfully. After the second challenge attempt, the doctor would state, “It’s ultimately my responsibility for what happens here. I need to get this tube in,” if the participant challenged again, the scenario would end. An open environment with no specific points for challenge or reply was used to create a naturalistic scenario. The participant was able to challenge the doctor at any moment. The scenario would end after a successful challenge or three minutes. Facilitators had the discretion to end the simulation early if the participant was not taking any action. The scenario was identical to the one used by Violato et al. (Violato, Witschen, et al., 2021) (see Figure 3 and supplemental material). A CAE Healthcare iStan Mannequin (CAE Healthcare, 2017) was used. Three simulations ran concurrently, all simulations were audio and video recorded for analysis.

Outcome Measures

The primary outcome measure was a successful challenge coded dichotomously, yes or no. As no uniformly accepted method for engaging in PD/SU exists, no specific phrases constituted a successful challenge. A successful challenge was defined as the participant making an explicit, direct, and persistent challenge to the doctor that removes ambiguity. Challenges must be explicit and direct to elicit change effectively (Bandura, 1999; Violato, Witschen, et al., 2021). A strong challenge could comprise, though was not limited to, statements such as what is occurring is unsafe or is a safety issue, making a statement about stopping, or indicating they would call for help (Violato, Witschen, et al., 2021). As a backup in the case of lost audio or video, the facilitators scored successful challenges during the simulation.

As CUS was emphasized during classroom instruction, instances of using the components of CUS were recorded. CUS was scored as a binary categorical variable, use or no use. Using one, two, or all three elements of CUS were recorded as a single instance.

Prior research (Delaloye et al., 2017; Pattni et al., 2017; Pian-Smith et al., 2009; Sydor et al., 2013) has scored speaking up using a modified Advocacy Inquiry Scale (mAIS). The mAIS is a scale based on the principles of advocacy (stating one's observation) and inquiry (requesting further information) (Delaloye et al., 2017). The mAIS was used to score behaviour in a continuous manner, with scores ranging from 1 (no action) to 6 (physical action) (see supplemental material).

Video Review

Each video-recorded simulation was reviewed by two independent raters (EV, JW) blind to the randomization of the conditions. Videos were scored for a successful challenge, CUS, mAIS, frequency of questions/suggestions, the number of times participants read the blood oxygen saturation (Sp0₂), a successful challenge after the physician’s responsibility phrase, and time to challenge.

The raters used a modified version of the confederate hierarchical demeanor rating (HDR) scale (Delaloye et al., 2017; Sydor et al., 2013) to determine the consistency of confederate behaviour between the three simulations. Confederate HDR was calculated by assigning a score of “1” to each hierarchical demeanor statement answered “yes” and a score of “0” to each statement answered “no” (Delaloye et al., 2017) (see supplemental material)

Analysis

Statistical analysis was performed using jamovi (Version 1.8.1), a point and click interface for R (jamovi, 2021) and R (R Core Team, 2019) using the caret package (Kuhn, 2019) and glmnet package (Friedman et al., 2010). Interrater reliability (IRR) for categorical data was calculated using Cohen’s Kappa, IRR for continuous data was calculated using intraclass correlation coefficients (ICC). Mean scores for the mAIS, HDR, frequency of reading questions, suggestions, and SpO₂ were used for all analyses.

Chi-square analysis was used to analyze the binary categorical variables of challenge x condition, challenge x CUS and condition x CUS. A t-test was used to compare mAIS scores.

Elastic-net regression was used to examine individual difference scale scores and demographic variables as predictors of speaking up. Elastic-net regression is designed for cases where p > n and is more effective than traditional regression methods when sample sizes are small ^{(James et al., 2013; Zou & Hastie, 2005)}. However, due to the small absolute sample size, including all potential individual differences in a single predictive model would produce suboptimal prediction. The Big Five and MFQ represent different constructs, comprising multiple subscales; as such each scale was examined separately along with the BSHS and ACT, which are comprised of a single global score. Two models were trained with different resampling methods, one using 5-fold Cross-Validation (CV) with 5 repeats and one using Bootstrapping. A tuning grid was set for alpha from 0-1 and lambda from .0001-1 with a search length of 100. With the smaller number of predictors for demographic characteristics, and airway management and intubation experience, binary logistic regression was used.

Data Preprocessing

Survey data were checked for careless responding. There were no inordinately fast completion times or response patterns indicating careless responding. Each of the four scales and subscales was examined for normality and outliers. Several data points outside 1.5x the interquartile range were identified. The outliers did not have a substantial influence on descriptive statistics or cause deviations from normality as examined through QQ plots and the Shapiro-Wilk test. As the cases were not influential and no careless responding was identified, the data points were included. No significant deviation from normality was identified for the mAIS, Shapiro-Wilk p = .9.

Two videos of the in-person simulation were lost due to technical issues; the facilitator's backup rating was used. Though post-hoc power calculations indicated β = .5 and the sample was small, the sample was adequate for the planned analysis (Campbell, 2007). For successful challenge the initial agreement between the coders was 24/32 (79%), Kappa = .54, Rater bias ratio = 1 χ2 = 9, p = .003. An iterative process of discussion and re-coding was engaged, after which there was 100% agreement. For the mAIS, ICC = .93, Rater bias ratio = .09, χ2 = 15.7, p < .001. For the HDR, the ICC = .96; for confederate HDR between simulations a Kruskal-Wallis test indicated no significant difference, χ²(7) = 4.32, p = .7.

Speaking Up

Thirty-four participants completed all stages of the study. Twenty-three students (67.6%) successfully challenged the anesthetist, eleven (32.3%) did not. A marginally significant difference existed for speaking up between the experimental and control condition, χ²(1, 34) = 4.30, p = .04, Odds-Ratio (95%CI) = 5.0(1.03-24.3), ϕ = .36, (Table 1).

Participants in the experimental condition used at least one aspect of CUS at a significantly higher rate than those in the control condition, χ²(1, 32) = 15.2, p < .001, ϕ = .69. Participants using at least one element of CUS challenged at a significantly higher rate than those that did not χ²(1, 32) = 7.94, p < .005, ϕ = .50 (Table 1). One participant that attempted to use CUS was unsuccessful. The participant used Concerned and Uncomfortable though stopped after the doctor used the responsibility phrase; the participant was from the experimental condition.

Participants had a mean (SD [range, median]) mAIS score of 4.22 (1.13 [2-6, 4.5]). There was no significant difference in mAIS score between the experimental (4.47) and control conditions (3.97), t(30) = 1.27, p = .22, Cohen’s d (95%CI) = .45(-.27–1.15). A significant difference existed in mAIS score for those that successfully challenged (4.89) and those that did not (2.75), t(30) = 10.8, p < .001, Cohen’s d (95%CI) = 4.11(2.7-5.5). Four participants engaged in physical action to stop the doctor, mAIS score = 6.

Secondary Aspects of Speaking Up

Successfully challenging was not related to how many Questions/Suggestions were made or the number of SpO₂readings (Table 2). For time, Mean (SD), Median (Interquartile Range[Range]), those in the experimental condition, 111(32.1), 108(84.5-130[64-180]) s, completed the simulation significantly faster than those in the control condition, 139(36.5), 143(83.5-140[143-170]) s, t(30) = 2.35, p = .03, Cohen’s d(95%CI) = .83(.07–1.6), mean difference = 28s.

Twenty of the successful participants challenged after hearing the responsibility phrase and two challenged before. All unsuccessful participants heard the responsibility phrase.

Individual Difference Measures

The sample was comprised of twenty-nine females and five males, with a mean(Standard Deviation [Range]) age of 24.3(5.32 [20-44]). Six participants had prior experience as healthcare professionals, including two Medical Laboratory Technologists, Sleep Clinician, Porter, Lab Assistant, and an international residency in Respiratory Medicine; two of the six with previous experience spoke up. Of the demographic and airway management and intubation items, only age neared significance as a predictor of a successful challenge, p = .07, Odds-Ratio(95%CI) = 1.4(.98 – 1.89). No variables from the personality scales were predictive of speaking up (see supplemental material for scale results)

The possibility that the training washed out any influences of individual differences was investigated using a post-hoc exploratory model building approach with logistic regression, adding condition as a covariate. No scales or variables were selected as a predictor at any point. Only VS emerged as a significant predictor, aligning with the primary analysis.

The first research question was supported. Participants in the VS condition successfully challenged at a higher rate than participants in the control condition during an in-person simulation delivered one month after course instruction. Participants in the VS condition used CUS at a significantly higher rate and successfully challenged more frequently and faster than participants in the control condition. No difference in mAIS score was observed between participants in the experimental and control condition, participants that successfully challenged obtained higher mAIS scores. The second research question was not supported, no individual difference characteristics were identified as predictive of a successful challenge.

It appears the VS helped people speak up at a higher rate. Based on significance the p-value and OR are not unequivocal however, the interpretation is supported. It is likely with a slightly larger sample size the values would have demonstrated a more robust level of significance. Further support for the effect of the VS is garnered from the phi (ϕ) value, which represents a medium effect size and the absolute frequencies by condition (Table 1). The VS also appears to have better equipped participants to act more quickly, by 28s, than participants in the control condition. Considering the average time for intubation is less than 30s, acting 28s faster could substantially improve patient outcomes (Griesdale et al., 2012). Additionally, despite the study being underpowered (β = .5) and susceptible to Type II error, an effect was still observed. Further support is indicated by the significantly higher rate of participants from the experimental condition using CUS to challenge. The VS, coupled with the course material, helped people use at least one element of CUS and ultimately enact a strategy to challenge successfully.

The VS influenced the use of CUS though there was no effect on the mAIS score. However, those who successfully challenged achieved higher mAIS scores. There are three explanations for the discrepancy. 1) The VS required students to successfully use CUS rather than explicitly focusing on escalation as measured through the mAIS. 2) Some participants in the experimental condition did not speak up, achieving low mAIS scores, while some participants in the control condition spoke up. 3) Persistence was necessary, reaching a high level on the mAIS would not qualify as a successful challenge if the student did not persist with a challenge after being rebuked.

The use of the responsibility phrase by the physician was highly impactful for some participants. All participants who did not successfully challenge heard the responsibility phrase. Some of these students primarily asked questions and made suggestions and would either stop or continue with questions and suggestions, though in a weaker manner. In contrast, four others, such as the one that used CUS, attempted to challenge though decreased after the responsibility phrase.

Aligning with prior research on obedience in healthcare (Barzallo Salazar et al., 2014; Peadon et al., 2020) and psychology (Blass, 1999; Doliński et al., 2017) the present study did not identify any effect for personality or demographic characteristics. Additionally, the sample was small and highly uniform across scales, a larger sample would be required to detect any small but real differences. Age did near significance and has been previously identified as a predictive variable for the personal expectation of speaking up (Violato et al., 2020; Violato, King, et al., 2021). The present study's findings provide support for further investigation of professional and life experience for speaking up.

Implications for Education and Research

Education

A VS incorporated with course curriculum, based on Kolb’s learning cycle, appears to increase the rate of successful challenges and implementation of skills learned during didactic instruction when participating in a high-intensity compliance simulation delivered after a month delay. An effective gamified VS can be easily designed and developed to align with course materials. Exposure to speaking up using a structured method (CUS) in a VS can prime students for subsequent training on patient advocacy and skills for speaking up. Regardless of course content, other programs or interventions for speaking up could easily incorporate a gamified VS aligned with instructional objectives as preparatory material to improve learning outcomes.

Such interventions would likely be most effective with students that have not had previous experience or exposure to PD/SU. Simulation should not be viewed as a limitation to research designs or only as a method for investigating interventions but should be a part of the intervention itself. Incorporating different simulation modalities can provide valuable experiential learning for PD/SU that may increase the likelihood of speaking up in the future (Violato, 2021).

These implications align with the recommendation by Daly Guris et al (2019) to develop simple, brief, and cost-effective interventions that can positively and durably impact speaking up while compatibility and non-disruptively fitting within the context of existing educational activities.

Research

Future research should attempt to separate the effects of VS alone, VS combined with didactic material, and impact on knowledge related to patient advocacy. Implementing a knowledge test after delivery of didactic material along with a delayed high-impact simulation in a VS/No Instruction x VS/Instruction design would help further determine the primary driver of change.

Most existing research on speaking up has used algorithmic simulations with clear decision points and opportunities to challenge (Calhoun et al., 2014; Calhoun et al., 2013; Pattni et al., 2017; Pian-Smith et al., 2009; Sydor et al., 2013). Future simulations for education to enhance speaking up should use more open environments with high-intensity situations where a patient is at serious risk, and the participant is met with strong resistance. These scenarios can “stretch” students and may enhance the effect of the simulation (Emmerich et al., 2018; Teodorczuk et al., 2021).

Pattni et al (2017) identified that female anesthetists were more likely to be challenged by an RT regardless of RT sex. In the present study, all the anesthetists were female and the sample was predominantly female, yet produced comparable rates of successful challenges to Violato et al (2021) who used male anesthetists in the same scenario where 64.4% of participants successfully challenged and 35.6% did not challenge an anesthetist. Though sex is typically not a predictor of obedience (Blass, 1999), the contrast with the Pattni study indicates the power of the situation is important, and contextual, professional, and individual effects, including sex, merit further investigation. The proportion of female participants was representative of the profession (Canadian Institute for Health Information, 2020).

Limitations

There were two primary limitations. 1) Small sample size. The sample size did not allow all personality and demographic variables to be included in a single model to predict a successful challenge and may have been too small to detect effects for these measures. 2) A single profession sample was used. Future research should include multiple professions at the same or different stages of education and knowledge to allow for better inferences about the generalizability of the intervention to other professions.

Obedience to authority is an evolutionarily and socially reinforced heuristic that poses a challenge for education to improve speaking up. A gamified asynchronous individual interprofessional VS using a Choose-Your-Own-Adventure format aligned with course content helped students challenge at a higher rate during an in-person simulation. Though the results are not unequivocal, multiple strands of evidence indicate there is likely a true effect. Virtual simulation is a high yield intervention; VS is cost-effective, evergreen, simple and efficient to implement and can improve a critical behaviour. Future research should be continued with interventions informed by Kolb’s learning cycle that use virtual and high-impact simulations.

Ethics: Approval was obtained from the ethics committee of the Northern Alberta Institute of Technology. The procedures used in this study adhere to the tenets of the Declaration of Helsinki.

Data Availability: The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.

Previous Presentations: None

Disclaimers and Competing Interests: The authors have no competing interests to declare that are relevant to the content of this article

Funding: This study was funded by a Mitacs Accelerate Grant #IT18354

Acknowledgments: The authors would like to thank the Respiratory Therapy program at NAIT

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Table 1. Contingency Table for Challenges and CUS by Condition

	Challenged			Used CUS
Condition	Yes	No	Total	Yes	No	Total
Virtual Sim	15	3	17	13	3	16
Control	8	8	16	2	14	16
Total	23	11	34*	15	17	32

*Video was missing for two participants; facilitator determination of successful challenge was used.

Table 2. Number of Questions/Suggestions, Reading of Blood Oxygen Saturation, and Time

	Successful Challenge^a
	Yes	No	Overall**
Questions/Suggestions*	5.82(2.08 [6.0])	4.60(1.37 [4.75])	5.44(1.95 [5.0])
Sp0₂*	2.93(1.99 [2.5])	2.80(1.32 [2.75])	2.89(1.79 [2.5])
Time***	111(33.4), 110(83.5-140[58.5-175]) s	154(25.7), 156(129-180[119-180]) s	125(36.8), 125(93.5-147[58.5-180]) s

* Mean(SD [Median])

**ICC Questions/Suggestions = .82; ICC SP0² = .86.

*** Mean (SD), Median (Interquartile Range[Range]), a significant difference for time existed between a successful and unsuccessful challenge, p < .001.

^aNo significant differences were observed for the number of Questions and Suggestions or SPO²readings for successful and unsuccessful challenges, p > .05 or the number of Questions and Suggestions or SPO²readings between the Experimental vs. Control condition, p > .05

No competing interests reported.

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Integrating Virtual Simulation with Course Curriculum to Improve Patient Advocacy through Speaking Up

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