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Too stressed to think? A scoping review of the literature for healthcare educators utilising high acuity clinical scenarios

BMC Medical Education volume 24, Article number: 990 (2024) Cite this article

Abstract

Background

The practise of paramedicine can be highly stressful particularly where urgent lifesaving decisions need to be made. Traditionally, educators have adopted the approach of placing students in simulated stressful situations as a way of learning to cope with these challenges. It is unclear from the literature whether traditional stress inoculation enhances or hinders learning. This scoping review aims to identify and examine both the peer-reviewed and grey literature reporting physiological stress responses to high-acuity scenarios in paramedicine and cognate healthcare disciplines.

Methods

Adhering strictly to JBI Evidence Synthesis Manual for conducting a scoping review, medical subject headings and areas, keywords and all other possible index terms were searched across EBSCOhost (Medline, CINAHL and APA PsycInfo), Scopus and, PubMed. English language articles both published (peer-reviewed academic papers, reports and conference proceedings) and unpublished (grey literature, Google Scholar reports) were included, and publications citing retrieved articles were also checked.

Results

Searches performed across five electronic databases identified 52 articles where abstracts indicated potential inclusion. From this, 22 articles which reported physiological or psychophysiological responses to stressful scenario-based education were included.

Conclusion

This review identified that an acceptable level of stress during simulation can be beneficial, however a point can be exceeded where stress becomes a hinderance to learning resulting in underperformance. By identifying strategies to moderate the impact of acute stress, educators of paramedic and other healthcare students can utilise high-acuity clinical scenarios to their andragogical armamentarium which has the potential to improve real-world clinical outcomes.

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Introduction

In many high-income countries, paramedic education has progressively moved from a post-employment vocational training model of the latter part of the 20th century to now sit firmly within the pre-employment tertiary education sector [1]. This evolution of education enables paramedics to provide high-level emergency care as new-to-practice clinicians in high pressure, time-critical environments [2]. To do this, education providers often utilise high-fidelity simulations to apply clinical or other skills in realistic environments. These simulations, are often comprised of high-acuity scenarios which are designed to depict a high severity of illness or injury [3] requiring rapid medical interventions, which can invoke increased physiological and cognitive stress. It may be the case that if these simulations are too stressful, clinical learnings from them may be lost due to the high stress load the participant is exposed to as shown by Takahashi, et al. [4] who identified higher cortisol levels post stress exposure in university students, which correlated with an increased level of memory impairment and poorer performance.

Links between physiological stress and knowledge application have also been reported in the paramedicine sector. LeBlanc, et al. [5] demonstrated that clinicians made more drug calculation errors following exposure to stressful events, whilst senior paramedics exhibited clinical and documentational vulnerabilities during high-acuity scenarios [6]. In the emerging field of undergraduate paramedicine education research, few studies have explored high-acuity scenario-based education and any associated physiological and cognitive stress. This is in contrast to Harvey, et al. [7], LeBlanc, et al. [6] and, more recently Hase, et al. [8] who have recommended that training in high-acuity areas of medicine should include challenge-promoting interventions specifically relevant to stress mitigation.

In the expanding cohort of university-trained paramedicine students, research on empathy [9], prevention of mental health and psychological disorders [10], workplace violence [11], physical characteristics [12] and pre-employment fitness testing [13] have been published. However, linkages between time critical high-acuity scenario-based education with resultant physiological stress and its potential impacts on cognitive decision-making has not been studied. A recent systematic review explored the physiological responses to acute stress in workers of several occupations, mostly within the human service industry [14]. Whilst this paper draws appropriate conclusions about acute physiological changes leading to performance decrement, possible implications for frontline healthcare workers were limited by a small number of healthcare-based studies included within the review. A gap also exists between self-awareness of one’s own physiological stress and how this may impact clinical judgement. Therefore, the purpose of this review was to better understand the physiological and cognitive stress responses observed in the participants undertaking high-acuity clinical scenarios. By appreciating the existence of contributory factors and how they influence stress, educators of paramedics and other healthcare workers can determine which elements of physiologically and mentally stressful scenario-based education can be considered in the design of their own programs.

Methods

Study design

Full systematic literature reviews (SLRs) are generally considered to be the foundation for evidence-based practice, particularly in healthcare [15]. This form of evidence synthesis relies on an extensive base of published literature and is frequently used to validate or refute current practice [16]. However, within the scope of the present study, little extant research reports on physiological changes triggered by high stress learning situations or the consequences this effect has on clinical performance. Given the inter-relationship between acute stress and the degradation of cognitive decision-making ability [7, 17], further research is warranted to characterise this physiological response in undergraduate paramedicine students. In this paper, we employed a scoping review method to explore the extent of published and unpublished literature from cognate heath disciplines to identify key characteristics or factors related to our topic of interest.

Our final protocol was registered on the 21st March 2023, and is publicly available on the Open Science Framework platform (https://osf.io/dxchy/).

Identifying the research question

This scoping review aims to identify and map the scope of current published literature related to physiological stress responses to high-acuity scenarios and, importantly, identify and analyse the knowledge gaps [18]. To achieve the aim, the following search strategy was employed:

  • Participants: higher education students or students in non-university training programs studying towards a recognised healthcare qualification.

  • Concept: any study that incorporates clinical scenarios / simulations where physiological (cardiovascular or endocrine) /or psychophysiological data is recorded.

  • Context: any undergraduate or postgraduate higher education setting or equivalent non-university training facility for the participants mentioned above.

Search strategy and eligibility criteria

The latest version [19] of Joanna Briggs Institute (JBI) comprehensive guide for authors conducting a scoping reviews [20] has been followed step-by-step within this review. A search period restriction from 2000 onwards was applied due to the rapid expansion of wearable technology including augmented and virtual reality. To ensure the review examined the acute physiological stress response, it was necessary to focus on articles that assessed markers of stress in real-time as participants were exposed to a stress-inducing task. An initial search was conducted across three prominent databases (Medline, PubMed and Scopus) to determine key terms as a guide to developing a thorough search strategy. From this and with the assistance of a senior research librarian, the secondary search expanded all identified keywords and incorporated medical subject headings (MeSH), major subject areas, and all other possible index terms as noted in the Appendix 1. The protocol incorporated both published (peer-reviewed academic papers, reports and conference proceedings) and unpublished (incorporating theses and dissertations, research and technical reports) evidence but did exclude non-English language articles. Sources were gathered using EBSCOhost (including Medline, CINAHL and APA PsycInfo) Scopus, and PubMed. Google Scholar was also searched as there is a small body of evidence that suggests this search engine produces highly comprehensive results [21, 22] whilst also searching ‘grey literature’ (published informally, non-commercially or remains unpublished), a format neglected by other databases. Selection of papers for inclusion in the study were then undertaken independently by two members of the research team (DL and EF). Finally, any other articles that cited the retrieved articles were also checked using citation alert with the ISI Web of Knowledge (Appendix 1).

Extracting and charting the data

Data were extracted from the included studies by two reviewers (JB and PH) utilising the JBI template of evidence details, characteristics and results extraction instrument [19]. Initial piloting of the data extraction resulted in some additional data being sought from each publication to allow quality appraisal to occur. This refined data extraction gathered details about study year, study country, study aim, study setting, study design, interventions, and comparators. Additionally, the data included sample size, methods, results, and author recommendations. A third member of the review team (DL) performed an accuracy check.

Quality assessment

Methodological validity and risk-of-bias appraisal, undertaken concurrently with data charting, was performed via the Mixed Methods Appraisal Tool (MMAT) version 2018 critical appraisal instrument designed by Hong, et al. [23]. For the purpose of this scoping review, an overall score was calculated from mean values of each section to determine methodological quality of each reviewed study (Appendix 4). The authors agreed that no cut-off scores would be applicable as the use of the MMAT was not for inclusion or exclusion purpose, but rather to describe the quality of the of publications reported in this review.

Synthesis of results

The first author performed narrative synthesis of identified themes and discussed these with the review team for validation. Descriptive results are subsequently reported which align with the intended scope and objectives of this review.

Ethics statement

Ethical approval was not required for this scoping review.

Results

The search strategy yielded 1427 results, of which 52 remained after title and abstract proofing and duplicate removal (Level 1). Consensus was not reached on seven papers with resolution sought from a third member of the review team (PH) (Appendix 2). Of the 52 studies, 30 were excluded for reasons outlined in Appendix 3. In addition, reference lists of three excluded review articles were checked, although nil additional suitable articles were identified. Unpublished (grey) literature was also assessed with no additional studies deemed suitable for inclusion. Figure 1 illustrates a Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) flow diagram [24] of the process and Table 1 lists the 22 studies deemed eligible for inclusion.

Fig. 1
figure 1

PRISMA flow diagram findings

Full size image
Table 1 Articles eligible for inclusion
Full size table

From the twenty-two studies identified that met the inclusion criteria, the majority originated from Europe and North America. Only one study [25] involved paramedics or paramedicine students. Twelve studies involved medical or surgical trainees [7, 26,27,28,29,30,31,32,33,34,35,36], five studied nursing or nurse anaesthetist students [37,38,39,40,41], three studies involved physiotherapy students [42,43,44], and one study examined psychology students [45].

No studies were identified that warranted exclusion based on major methodological flaws on any significant risk of bias. However, study design flaws and lower levels of evidence were common. Of most concern were poorly described methodologies and under-powered sample sizes incapable of producing statistically significant results (see Appendix 4 for tabulated quality assessment results). Examining the methodology used, sixteen studies adopted a mixed methods approach and six utilised a quantitative method. Randomised controlled trials were reported in seven papers and a battery of different metrics were recorded across the studies. Heart rate variability and salivary cortisol levels were the most frequently reported objective data, whilst the state trait anxiety inventory was the most common subjective measure (see Table 2).

Table 2 Study metrics of stress
Full size table

In general terms, the twenty-two included studies had similar aims centring around determining how successful high stress simulation could be at replicating clinical experience. Most studies involved both male and female participants with samples sizes ranging from n = 8 to n = 166, with a mean of n = 53 and a median of n = 33. Multiple studies assessed and compared stress levels of participants in different situations, and then used these results to determine if stress had affected clinical performance. Other studies used similar data to improve education or training with the aim of ultimately increasing student confidence and performance. The key outcomes from the included studies are summarised in Table 3.

Table 3 Key study findings
Full size table

Discussion

This review identified studies exploring physiological responses of participants undertaking high stress scenario-based education or training. While acknowledging much of the evidence was of low methodological quality [46] and therefore limits generalisability, the results still provide some useful insights that may be used to inform educators of future paramedics and other healthcare workers.

One of the key findings from this review was the identification of pre-performance or anticipatory anxiety exhibited across multiple studies [37, 38, 45]. This is an area where simulation may not replicate clinical work. Students aware of an upcoming scenario well in advance have ample time to prepare and mount a physiological stress response. This could be controlled if students were given little notice, however this was not commonly reported in the studies. Healthcare educators utilising scenario-based education may choose to restrict prior notification as a means of assessing any changes in the stress response amongst their students. In high-acuity clinical work, paramedics usually have little time to prepare, which may reduce the anticipatory stress response. Potentially this may be seen as positive, as stress has been demonstrated to lead to poorer performance is some paramedic research [5, 6]. However, the evident stress of attending high-acuity cases must also be considered and its impact on performance. In the context of anticipatory anxiety predicting future performance, little research has examined its immediate effect on motor task performance.

The reviewed publications also provide contradictory support for simulation as a tool to replicate the psychophysiological stress of high-acuity clinical work. Baker, et al. [37], in a study with trainees in the highly specialised field of anaesthetics, found simulation was able to replicate the physical and procedural forms of clinical work, however it was unable to replicate the intrinsic level of stress the trainees exhibited when working with a real patient in an operating theatre. These results are potentially influenced by small participant numbers (n = 8) and may also be applicable to highly specialised and highly technical fields such as anaesthesia. For paramedicine, contemporary literature [47] highlights simulation allowing for the training of skills that are rarely needed or rarely practiced in the field and supports recommendation made by O’Meara, et al. [2]. For educators of paramedics and other healthcare workers, simulating high-acuity situations is a crucial way to expose students to potential clinical scenarios they may face early in their career. In designing programs of study, careful use of stress-inducing high-acuity simulation can be a beneficial but can also lead to continued underperformance if the stress is chronically too high.

Barbadoro, et al. [26] and Judd, et al. [43] found simulation provided a higher level of stress in their participants when compared to equitable clinical work, whilst Demaria, et al. [28] found that high stress situations can be beneficial for learning. This benefit of high stress learning was also supported by the work of Keitel, et al. [32], who found increased levels of the key stress hormone cortisol correlated with improved memory retention and medical performance amongst medical trainees. An increased stress response was also reported when supervisors or assessors were present within the simulation [30, 31] and, unsurprisingly, vital signs as a measure of physiological stress, increased when the simulation itself was exertive [25, 27, 36]. The stress placed on students involved in high-acuity simulation must be further studied to allow educators to determine what level of anxiety may enhance learning without impeding performance.

Performance ability or academic standing was also found to correlate with stress. McKay, et al. [38] found low performers increased stress and performed poorly, whereas high performers also increased stress but performed superbly in a cohort of student nurses. Paramedicine courses may show similar trends, with students likely to self-assess their academic abilities and stress tolerance. Educators could potentially use real-time learning analytics to offer tailored support and guidance based on live biometric data, proactively aiding students. This would be resource intensive for academics with large student numbers; but in smaller cohorts, the individual feedback around acceptable stress to achieve simulated clinical success may enhance the education program.

Lacking from the literature is a detailed discussion of a variety of variables related to student stress responses from the level of acuity of a scenario. These confounding variables, such as pre-established coping styles and perceived stress intensity within participants, need to be quantified to accurately gauge the success of any interventions aimed at alleviating the stress response, and in examining what levels of anxiety may enhance learning without impeding performance.

Limitations

Whilst the systematic approach to this scoping review explored multiple electronic bibliographic repositories, there is potential some contemporary conference proceedings, dissertations and theses, along with grey literature not readily available in electronic databases or Google Scholar, may have been missed. Non-English literature may have added value to this review and we attempted to seek translated papers where possible, but we accept that some results may have been missed through this process.

Directions and recommendations for future research

This scoping review identified inconsistencies and varying methodologies for the assessment of participant stress response in scenario-based education. Recommendations should be developed to identify gold standard quantification of psychophysiological stress responses during high stress scenarios. This would then allow meta-analysis or other systematic synthesis of data to be undertaken to accurately determine any inter-relationship between acute stress and the degradation of cognitive decision-making for healthcare education programs. In addition, variables related to student stress responses from the level of acuity of a scenario should be investigated. For example, individual differences in participants such as pre-established coping styles and strategies, perceived stress intensity, perceived control of stress or coping skill, as well as context specific stressors such as the outcomes associated with scenario performance (e.g., high stakes versus low stakes outcomes) may all be important variables for future research.

Conclusion

The studies identified in this scoping review have shown high-acuity simulation can induce stress comparable with paramedicine clinical practice. For educators, understanding the factors or elements which contribute to an acceptable level of stress can allow participants the opportunity to fail and learn from their errors during simulation. This further provides opportunities to improve student outcomes in paramedicine and other healthcare education by facilitating high-acuity clinical scenarios that challenge students without inducing stress levels that hinder performance. As educational and wearable technology further evolves, utilisation of real-time biofeedback through passive measurement devices also hold promise as an intervention to reduce the negative effects of acute physiological stress during training scenarios.

Data availability

Data supporting Fig. 1; Tables 1, 2 and 3 and available within the Supplementary Information (Appendices).

References

  1. Hou XY, Rego J, Service M. Review article: paramedic education opportunities and challenges in Australia. Emerg Med Australasia. 2013;25(2):114–9.

    Article  Google Scholar 

  2. O’Meara P, Furness S, Gleeson R. Educating paramedics for the future: a holistic approach. J Health Human Serv Adm. 2017;40(2):219–53.

    Google Scholar 

  3. Chrimes N. The Vortex: a universal ‘high-acuity implementation tool’ for emergency airway management. Br J Anaesth. 2016;117(Suppl 1):i20–7.

    Article  Google Scholar 

  4. Takahashi T, Ikeda K, Ishikawa M, Tsukasaki T, Nakama D, Tanida S, et al. Social stress-induced cortisol elevation acutely impairs social memory in humans. Neurosci Lett. 2004;363(2):125–30.

    Article  Google Scholar 

  5. LeBlanc VR, MacDonald RD, McArthur B, King K, Lepine T. Paramedic performance in calculating drug dosages following stressful scenarios in a human patient simulator. Prehospital Emerg Care. 2005;9(4):439–44.

    Article  Google Scholar 

  6. LeBlanc VR, Regehr C, Tavares W, Scott AK, Macdonald R, King K. The impact of stress on paramedic performance during simulated critical events. Prehosp Disaster Med. 2012;27(4):369–74.

    Article  Google Scholar 

  7. Harvey A, Nathens AB, Bandiera G, Leblanc VR. Threat and challenge: cognitive appraisal and stress responses in simulated trauma resuscitations. Med Educ. 2010;44(6):587–94.

    Article  Google Scholar 

  8. Hase A, O’Brien J, Moore LJ, Freeman P. The relationship between challenge and threat states and performance: a systematic review. Sport Exerc Perform Psychol. 2019;8(2):123–44.

    Google Scholar 

  9. Williams B, Boyle M, Earl T. Measurement of empathy levels in undergraduate paramedic students. Prehosp Disaster Med. 2013;28(2):145–9.

    Article  Google Scholar 

  10. Wild J, El-Salahi S, Tyson G, Lorenz H, Pariante CM, Danese A, et al. Preventing PTSD, depression and associated health problems in student paramedics: protocol for PREVENT-PTSD, a randomised controlled trial of supported online cognitive training for resilience versus alternative online training and standard practice. BMJ Open. 2018;8(12):e022292.

    Article  Google Scholar 

  11. Boyle M, McKenna L. Paramedic student exposure to workplace violence during clinical placements - a cross-sectional study. Nurse Educ Pract. 2017;22:93–7.

    Article  Google Scholar 

  12. Davies S, Naidoo N, Parr B. Physical performance characteristics of South African male and female Emergency Care students (ECS). Ergon SA: J Ergon Soc South Afr. 2008;20(2):3–14.

    Google Scholar 

  13. Thornton KE, Sayers MG. Unfit for duty? Evaluation of 4 years of paramedic preemployment fitness screening test results. Prehospital Emerg Care. 2014;18(2):201–6.

    Article  Google Scholar 

  14. Frazier SE, Parker SH. Measurement of physiological responses to acute stress in multiple occupations: a systematic review and implications for front line healthcare providers. Transl Behav Med. 2019;9(1):158–66.

    Article  Google Scholar 

  15. Munn Z, Porritt K, Lockwood C, Aromataris E, Pearson A. Establishing confidence in the output of qualitative research synthesis: the ConQual approach. BMC Med Res Methodol. 2014;14(1):108.

    Article  Google Scholar 

  16. Pearson A, Jordan Z, Munn Z. Translational science and evidence-based healthcare: a clarification and reconceptualisation of how knowledge is generated and used in healthcare. Nurs Res Pract. 2012;2012:792519.

    Google Scholar 

  17. Domes G, Heinrichs M, Rimmele U, Reichwald U, Hautzinger M. Acute stress impairs recognition for positive words–association with stress-induced cortisol secretion. Stress. 2004;7(3):173–81.

    Article  Google Scholar 

  18. Munn Z, Peters MDJ, Stern C, Tufanaru C, McArthur A, Aromataris E. Systematic review or scoping review? Guidance for authors when choosing between a systematic or scoping review approach. BMC Med Res Methodol. 2018;18(1):143.

    Article  Google Scholar 

  19. Peters MDJ, Marnie C, Tricco AC, Pollock D, Munn Z, Alexander L, et al. Updated methodological guidance for the conduct of scoping reviews. JBI Evid Synthesis. 2020;18(10):2119–26.

    Article  Google Scholar 

  20. Peters MD, Godfrey CM, Khalil H, McInerney P, Parker D, Soares CB. Guidance for conducting systematic scoping reviews. Int J Evid Based Healthc. 2015;13(3):141–6.

    Article  Google Scholar 

  21. Bajpai A, Davuluri S, Haridas H, Kasliwal G, Ks HD. S, In search of the right literature search engine(s). Nat Precedings. 2011.

  22. Gehanno JF, Rollin L, Darmoni S. Is the coverage of Google Scholar enough to be used alone for systematic reviews. BMC Med Inf Decis Mak. 2013;13(1):7.

    Article  Google Scholar 

  23. Hong QN, Fàbregues S, Bartlett G, Boardman F, Cargo M, Dagenais P, et al. The mixed methods Appraisal Tool (MMAT) version 2018 for information professionals and researchers. Educ Inform. 2018;34(4):285–91.

    Article  Google Scholar 

  24. Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. PLoS Med. 2021;18(3):e1003583.

    Article  Google Scholar 

  25. MacQuarrie AS, Hunter JR, Sheridan S, Hlushak A, Sutton C, Wickham J. Paramedic Student Clinical Performance during High-Fidelity Simulation after a physically demanding Occupational Task: a pilot randomized crossover trial. Simul Healthcare: J Soc Simul Healthc. 2022;17(4):234–41.

    Article  Google Scholar 

  26. Barbadoro P, Brunzini A, Dolcini J, Formenti L, Luciani A, Messi D, et al. Stress responses in high-fidelity simulation and standard simulation training among medical students. BMC Med Educ. 2023;23(1):116.

    Article  Google Scholar 

  27. Bialka S, Copik M, Ubych A, Marciniak R, Smereka J, Szarpak L, et al. Effect of high-fidelity simulation on alpha-amylase activity and concentrations of secretory immunoglobulin class A, cortisol, and testosterone among medical students. Endocrine. 2021;73(2):431–8.

    Article  Google Scholar 

  28. Demaria S Jr., Bryson EO, Mooney TJ, Silverstein JH, Reich DL, Bodian C, et al. Adding emotional stressors to training in simulated cardiopulmonary arrest enhances participant performance. Med Educ. 2010;44(10):1006–15.

    Article  Google Scholar 

  29. DeMaria S, Silverman ER, Lapidus KA, Williams CH, Spivack J, Levine A, et al. The impact of simulated patient death on medical students’ stress response and learning of ACLS. Med Teach. 2016;38(7):730–7.

    Article  Google Scholar 

  30. Feeley AA, Feeley IH, McManus R, Lunn JV, Sheehan E, Merghani K. Evaluating the impact of Supervision on Surgical trainees stress response during simulated Surgical procedures; a crossover randomized Trial. J Surg Educ. 2022;79(6):1379–86.

    Article  Google Scholar 

  31. Flinn JT, Miller A, Pyatka N, Brewer J, Schneider T, Cao CG. The effect of stress on learning in surgical skill acquisition. Med Teach. 2016;38(9):897–903.

    Article  Google Scholar 

  32. Keitel A, Ringleb M, Schwartges I, Weik U, Picker O, Stockhorst U, et al. Endocrine and psychological stress responses in a simulated emergency situation. Psychoneuroendocrinology. 2011;36(1):98–108.

    Article  Google Scholar 

  33. Los K, Chmielewski J, Cebula G, Bielecki T, Torres K, Luczynski W. Relationship between mindfulness, stress, and performance in medical students in pediatric emergency simulations. GMS J Med Educ. 2021;38(4):Doc78.

    Google Scholar 

  34. Martin-Rodriguez F, Castro Villamor MA, Lopez-Izquierdo R, Portillo Rubiales RM, Ortega GJ, Sanz-Garcia A. Can anxiety in undergraduate students in a high-fidelity clinical simulation be predicted? A randomized, sham-controlled, blinded trial. Nurse Educ Today. 2021;98:104774.

    Article  Google Scholar 

  35. Rieber N, Betz L, Enck P, Muth E, Nikendei C, Schrauth M, et al. Effects of medical training scenarios on heart rate variability and motivation in students and simulated patients. Med Educ. 2009;43(6):553–6.

    Article  Google Scholar 

  36. Tramèr L, Becker C, Hochstrasser S, Marsch S, Hunziker S. Association of electrocardiogram alterations of rescuers and performance during a simulated cardiac arrest: a prospective simulation study. PLoS ONE. 2018;13(6):e0198661.

    Article  Google Scholar 

  37. Baker BG, Bhalla A, Doleman B, Yarnold E, Simons S, Lund JN, et al. Simulation fails to replicate stress in trainees performing a technical procedure in the clinical environment. Med Teach. 2017;39(1):53–7.

    Article  Google Scholar 

  38. McKay KA, Buen JE, Bohan KJ, Maye JP. Determining the relationship of acute stress, anxiety, and salivary alpha-amylase level with performance of student nurse anesthetists during human-based anesthesia simulator training. AANA J. 2010;78(4):301–9.

    Google Scholar 

  39. Nakayama N, Arakawa N, Ejiri H, Matsuda R, Makino T. Heart rate variability can clarify students’ level of stress during nursing simulation. PLoS ONE. 2018;13(4).

  40. Park HJ, Choi D, Park HA, Lee CA. Nurse evaluation of stress levels during CPR training with heart rate variability using smartwatches according to their personality: a prospective, observational study. PLoS ONE. 2022;17(6).

  41. Stecz P, Makara-Studzińska M, Białka S, Misiołek H. Stress responses in high-fidelity simulation among anesthesiology students. Sci Rep. 2021;11(1):17073.

    Article  Google Scholar 

  42. Beltrán-Velasco AI, Ruisoto-Palomera P, Bellido-Esteban A, García-Mateos M, Clemente-Suárez VJ. Analysis of Psychophysiological Stress Response in higher education students undergoing clinical practice evaluation. J Med Syst. 2019;43(3):68.

    Article  Google Scholar 

  43. Judd BK, Alison JA, Waters D, Gordon CJ. Comparison of psychophysiological stress in Physiotherapy Students Undertaking Simulation and Hospital-based Clinical Education. Simul Healthcare: J Soc Simul Healthc. 2016;11(4):271–7.

    Article  Google Scholar 

  44. Palekar TJ, Mokashi MG, Anwer S, Kakrani AL, Khandare SD, Alghadir AH. Effect of galvanic skin resistance-aided Biofeedback Training in reducing the pulse rate, respiratory rate, and blood pressure due to perceived stress in Physiotherapy students. / Fizyoterapi Öğrencilerinde Algılanan Strese Bağlı Nabız Hızı, Solunum Hızı ve Kan Basıncının Azaltılmasında Galvanik Deri Direnci Destekli Bio-geri Bildirim Eğitiminin Etkisi. Turkish J Phys Med Rehabilitation / Turkiye Fiziksel Tip ve Rehabilitasyon Dergisi. 2015;61(2):116–9.

    Google Scholar 

  45. Beltrán-Velasco AI, Bellido-Esteban A, Ruisoto-Palomera P, Clemente-Suárez VJ. Use of Portable Digital devices to analyze autonomic stress response in psychology objective structured clinical examination. J Med Syst. 2018;42(2):35.

    Article  Google Scholar 

  46. Burns PB, Rohrich RJ, Chung KC. The levels of evidence and their role in evidence-based Medicine. Plast Reconstr Surg. 2011;128(1):305–10.

    Article  Google Scholar 

  47. Diamond A, Bilton N. The current state on the Use of Simulation in Paramedic Education. Australasian J Paramedicine. 2021;18:1–5.

    Article  Google Scholar 

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Acknowledgements

The authors wish to acknowledge and thank senior research librarian Meena Gupta for assistance with developing and refining key search terms within the research protocol.

Funding

No funding sources or any specific materials need to be disclosed.

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Authors and Affiliations

  1. Faculty of Health, Australian Catholic University, Building 403, Daniel Mannix Building, 8 – 14 Brunswick St, Fitzroy, VIC, 3065, Australia

    Jason Betson

  2. School of Health and Medical Sciences, Centre for Health Research, University of Southern Queensland, Ipswich, Australia

    Jason Betson & David Long

  3. School of Clinical Sciences, Queensland University of Technology, Brisbane, Australia

    Peter Horrocks

  4. School of Psychology and Wellbeing, Centre for Health Research, University of Southern Queensland, Toowoomba, Australia

    Erich C. Fein

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Contributions

JB, DL, EF and PH conceived the study. JB and DL equally designed the study approach. DL, EF and PH undertook the review. JB and PH undertook data extraction and quality control. JB interpreted the data. JB, DL and EF drafted the manuscript and circulated to authors for contribution. All authors edited drafts and approved the current manuscript for publication. JB as the corresponding author is responsible for the overall content.

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Correspondence to Jason Betson.

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Betson, J., Fein, E.C., Long, D. et al. Too stressed to think? A scoping review of the literature for healthcare educators utilising high acuity clinical scenarios. BMC Med Educ 24, 990 (2024). https://doi.org/10.1186/s12909-024-05949-3

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  • DOI: https://doi.org/10.1186/s12909-024-05949-3

Keywords

BMC Medical Education

ISSN: 1472-6920

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