Résumés
Abstract
Introduction: Eye-tracking offers a distinctive opportunity to assess nurses’ clinical decision-making in simulation. Although its feasibility has been established in various scenarios, most studies have focused on a single participant, typically a physician in a leadership role. The application of eye-tracking in the challenging context of in-hospital cardiac arrest (IHCA) simulations, where nurses juggle diverse roles and undertake physical tasks such as chest compressions, has yet to be explored.
Objectives: This study aimed to assess the feasibility and acceptability of eye-tracking with nurses’ during IHCA simulations. Additionally, the study aimed to describe eye-tracking metrics based on different resuscitation roles and to explore the relationship between eye-tracking metrics to pinpoint the most informative metrics for the design of future studies.
Methods: In this single-group observational study, 56 newly hired nurses wore eye-tracking glasses during IHCA simulations. The primary feasibility criterion was the proportion of usable eye-tracking data. Secondary criteria included recruitment rate, calibration time, and glasses acceptability. The relationship among eye-tracking metrics was investigated through correlation analyses.
Results: Calibration of the devices was rapid, and 85.7% of the data was usable. The glasses were comfortable, non-distracting, and did not impede nurses’ vision or performance. Data were mapped for five areas of interest: the patient’s head and chest, cardiac monitor, teammates, and resuscitation cart. Eye-tracking metrics exhibited variations based on resuscitation roles. Fixation count, fixation duration, and time to first fixation appeared to be the most informative metrics in IHCA simulation.
Discussion and conclusion: These findings demonstrate the feasibility and acceptability of analyzing nurses’ eye-tracking data during IHCA simulations using a role-based approach. Future research should explore correlations with additional attention measures to enhance our understanding of nurse decision-making during cardiac arrest and improve educational strategies and outcomes.
Keywords:
- eye-tracker,
- clinical simulation,
- cardiopulmonary resuscitation,
- visual attention,
- nursing sciences
Résumé
Introduction : L’oculométrie offre une avenue pour évaluer la prise de décision infirmière en simulation. Des études ont montré sa faisabilité dans divers scénarios, mais se sont surtout concentrées sur des médecins dans un rôle de leadership. Son application lors de simulations d’arrêt cardiaque, un contexte où les infirmiers et les infirmières assument plusieurs rôles et tâches physiques comme les compressions thoraciques, reste à explorer.
Objectifs : Évaluer la faisabilité et l’acceptabilité de l’oculométrie auprès d’infirmiers et d’infirmières lors de simulations d’arrêt cardiaque, décrire les métriques d’oculométrie selon différents rôles en réanimation et explorer les relations entre ces métriques pour identifier les métriques les plus informatives pour la conception de futures études.
Méthodes : Dans cette étude observationnelle à groupe unique, 56 infirmiers et infirmières ont porté des lunettes d’oculométrie pendant des simulations d’arrêt cardiaque. Le principal critère d’évaluation de la faisabilité était la proportion de données d’oculométrie utilisables. Les critères d’évaluation secondaires comprenaient le taux de recrutement, le temps de calibration et l’acceptabilité des lunettes. Des analyses de corrélation ont permis d’examiner la relation entre les métriques d’oculométrie.
Résultats : La calibration des lunettes a été rapide et 85,7% des données étaient utilisables. Les lunettes étaient confortables et n’entravaient ni la vision ni la performance. Les données ont été cartographiées pour cinq zones d’intérêt : tête et thorax du patient, moniteur cardiaque, coéquipiers et chariot de réanimation. Les métriques présentaient des variations en fonction des rôles. Le nombre de fixations, la durée des fixations et le temps jusqu’à la première fixation semblaient être les métriques les plus informatives.
Discussion et conclusion : Ces résultats montrent la faisabilité et l’acceptabilité de l’oculométrie pendant des simulations de réanimation cardiorespiratoire. Les recherches futures devraient explorer les corrélations avec d’autres mesures d’attention pour affiner notre compréhension de la prise de décision infirmière lors d’un arrêt cardiaque.
Mots-clés :
- suivi oculaire,
- simulation clinique,
- réanimation cardiorespiratoire,
- attention visuelle,
- sciences infirmières
Veuillez télécharger l’article en PDF pour le lire.
Télécharger
Parties annexes
Bibliography
- Al-Moteri, M., Cooper, S., Symmons, M., & Plummer, V. (2020). Nurses' cognitive and perceptual bias in the identification of clinical deterioration cues. Australian Critical Care, 33(4), 333-342. https://doi.org/10.1016/j.aucc.2019.08.006
- Al-Moteri, M. O., Symmons, M., Cooper, S., & Plummer, V. (2018). Inattentional blindness and pattern-matching failure: The case of failure to recognize clinical cues. Applied Ergonomics, 73, 174-182. https://doi.org/10.1016/j.apergo.2018.07.001
- Blondon, K., Wipfli, R., & Lovis, C. (2015). Use of eye-tracking technology in clinical reasoning: A systematic review. Studies in health technology and informatics, 210, 90-94.
- Browning, M., Cooper, S., Cant, R., Sparkes, L., Bogossian, F., Williams, B., O'Meara, P., Ross, L., Munro, G., & Black, B. (2016). The use and limits of eye-tracking in high-fidelity clinical scenarios: A pilot study. International Emergency Nursing, 25, 43-47. https://doi.org/10.1016/j.ienj.2015.08.002
- Capogna, E., Capogna, G., Raccis, D., Salvi, F., Velardo, M., & Del Vecchio, A. (2021). Eye tracking metrics and leader's behavioral performance during a post-partum hemorrhage high-fidelity simulated scenario. Advances in Simulation, 6(1), 4. https://doi.org/10.1186/s41077-021-00156-2
- Cohen, J. (2013). Statistical power analysis for the behavioral sciences (Revised ed.). Academic press.
- Damji, O., Lee-Nobbee, P., Borkenhagen, D., & Cheng, A. (2019). Analysis of eye-tracking behaviours in a pediatric trauma simulation. Canadian Journal of Emergency Medicine, 21(1), 138-140. https://doi.org/10.1017/cem.2018.450
- Desvergez, A., Winer, A., Gouyon, J. B., & Descoins, M. (2019). An observational study using eye tracking to assess resident and senior anesthetists' situation awareness and visual perception in postpartum hemorrhage high fidelity simulation. PLoS One, 14(8), e0221515. https://doi.org/10.1371/journal.pone.0221515
- Douglas, C., Booker, C., Fox, R., Windsor, C., Osborne, S., & Gardner, G. (2016). Nursing physical assessment for patient safety in general wards: reaching consensus on core skills. Journal of Clinical Nursing, 25(13-14), 1890-1900. https://doi.org/10.1111/jocn.13201
- Duchowski, A. T., & Duchowski, A. T. (2017). Eye Tracking Methodology: Theory and Practice. Springer.
- Eldridge, S. M., Chan, C. L., Campbell, M. J., Bond, C. M., Hopewell, S., Thabane, L., & Lancaster, G. A. (2016). CONSORT 2010 statement: extension to randomised pilot and feasibility trials. BMJ (Clinical research ed.), 355, i5239. https://doi.org/10.1136/bmj.i5239
- Gundrosen, S., Solligård, E., & Aadahl, P. (2014). Team competence among nurses in an intensive care unit: The feasibility of in situ simulation and assessing non-technical skills. Intensive and Critical Care Nursing, 30(6), 312-317. https://doi.org/10.1016/j.iccn.2014.06.007
- IBM Corporation. (2022). IBM SPSS Statistics (version 28.0) [Computer software]. https://www.ibm.com/support/pages/downloading-ibm-spss-statistics-28
- Katz, T. A., Weinberg, D. D., Fishman, C. E., Nadkarni, V., Tremoulet, P., Te Pas, A. B., Sarcevic, A., & Foglia, E. E. (2019). Visual attention on a respiratory function monitor during simulated neonatal resuscitation: an eye-tracking study. Archives of Disease in Childhood Fetal & Neonatal Edition, 104(3), F259-F264. https://doi.org/10.1136/archdischild-2017-314449
- Krage, R., Zwaan, L., Tjon Soei Len, L., Kolenbrander, M. W., van Groeningen, D., Loer, S. A., Wagner, C., & Schober, P. (2017). Relationship between non-technical skills and technical performance during cardiopulmonary resuscitation: does stress have an influence? Emergency Medicine Journal, 34(11), 728-733. https://doi.org/10.1136/emermed-2016-205754
- Laerdal. (2024). SimMan ALS. https://laerdal.com/ca/products/simulation-training/emergency-care-trauma/simman-als/
- Lancaster, G. A., & Thabane, L. (2019). Guidelines for reporting non-randomised pilot and feasibility studies. Pilot and Feasibility Studies, 5, 114. https://doi.org/10.1186/s40814-019-0499-1
- Lapierre, A., Lavoie, P., Castonguay, V., Lonergan, A.-M., & Arbour, C. (2023). The influence of the simulation environment on teamwork and cognitive load in novice trauma professionals at the emergency department: Piloting a randomized controlled trial. International Emergency Nursing, 67, 101261. https://doi.org/10.1016/j.ienj.2022.101261
- Lavoie, P., Lapierre, A., Maheu-Cadotte, M.-A., Fontaine, G., Khetir, I., & Bélisle, M. (2022). Transfer of Clinical Decision-Making–Related Learning Outcomes Following Simulation-Based Education in Nursing and Medicine: A Scoping Review. Academic Medicine, 97(5), 738-746. https://doi.org/10.1097/acm.0000000000004522
- Law, B. H. Y., Cheung, P. Y., Wagner, M., van Os, S., Zheng, B., & Schmolzer, G. (2018). Analysis of neonatal resuscitation using eye tracking: a pilot study. Archives of Disease in Childhood Fetal & Neonatal Edition, 103(1), F82-F84. https://doi.org/10.1136/archdischild-2017-313114
- Marjanovic, N. S., Teiten, C., Pallamin, N., & L’Her, E. (2018). Evaluation of emotional excitation during standardized endotracheal intubation in simulated conditions. Annals of intensive care, 8(1), 117. https://doi.org/10.1186/s13613-018-0460-0
- McNaughten, B., Hart, C., Gallagher, S., Junk, C., Coulter, P., Thompson, A., & Bourke, T. (2018). Clinicians' gaze behaviour in simulated paediatric emergencies. Archives of Disease in Childhood, 103(12), 1146-1149. https://doi.org/10.1136/archdischild-2017-314119
- Michaelis, P., & Leone, R. J. (2019). Cardiac Arrest After Cardiac Surgery: An Evidence-Based Resuscitation Protocol. Critical Care Nurse, 39(1), 15-25. https://doi.org/10.4037/ccn2019309
- Microsoft Corporation. (2018). Surface Pro tablet (version 6). https://support.microsoft.com/en-us/surface/surface-pro-6-specs-and-features-ade5cfc2-e99a-6fd1-abbe-c0e8a8a3942d
- Mitchell, O. J. L., Motschwiller, C. W., Horowitz, J. M., Friedman, O. A., Nichol, G., Evans, L. E., & Mukherjee, V. (2019). Rapid Response and Cardiac Arrest Teams: A Descriptive Analysis of 103 American Hospitals. Critical Care Explorations, 1(8), e0031. https://doi.org/10.1097/cce.0000000000000031
- Mumma, J. M., Durso, F. T., Dyes, M., Dela Cruz, R., Fox, V. P., & Hoey, M. (2018). Bag Valve Mask Ventilation as a Perceptual-Cognitive Skill. Human Factors, 60(2), 212-221. https://doi.org/10.1177/0018720817744729
- Panchal, A. R., Bartos, J. A., Cabanas, J. G., Donnino, M. W., Drennan, I. R., Hirsch, K. G., Kudenchuk, P. J., Kurz, M. C., Lavonas, E. J., Morley, P. T., O'Neil, B. J., Peberdy, M. A., Rittenberger, J. C., Rodriguez, A. J., Sawyer, K. N., Berg, K. M., Adult, B., & Advanced Life Support Writing, G. (2020). Part 3: Adult Basic and Advanced Life Support: 2020 American Heart Association Guidelines for Cardiopulmonary Resuscitation and Emergency Cardiovascular Care. Circulation, 142(16_suppl_2), S366-S468. https://doi.org/10.1161/CIR.0000000000000916
- Pauszek, J. R. (2023). An introduction to eye tracking in human factors healthcare research and medical device testing. Human Factors in Healthcare, 3, 100031. https://doi.org/10.1016/j.hfh.2022.100031
- Schulz, C. M., Schneider, E., Fritz, L., Vockeroth, J., Hapfelmeier, A., Brandt, T., Kochs, E. F., & Schneider, G. (2011). Visual attention of anaesthetists during simulated critical incidents. British journal of anaesthesia, 106(6), 807-813. https://doi.org/10.1093/bja/aer087
- Schulz, C. M., Schneider, E., Fritz, L., Vockeroth, J., Hapfelmeier, A., Wasmaier, M., Kochs, E. F., & Schneider, G. (2011). Eye tracking for assessment of workload: a pilot study in an anaesthesia simulator environment. British journal of anaesthesia, 106(1), 44-50. https://doi.org/10.1093/bja/aeq307
- Shinnick, M. A. (2016). Validating Eye Tracking as an Objective Assessment Tool in Simulation. Clinical Simulation in Nursing, 12(10), 438-446. https://doi.org/10.1016/j.ecns.2016.06.001
- Szulewski, A., Braund, H., Egan, R., Gegenfurtner, A., Hall, A. K., Howes, D., Dagnone, D., & van Merrienboer, J. J. G. (2019). Starting to Think Like an Expert: An Analysis of Resident Cognitive Processes During Simulation-Based Resuscitation Examinations. Annals of Emergency Medicine, 74(5), 647-659. https://doi.org/10.1016/j.annemergmed.2019.04.002
- Szulewski, A., Egan, R., Gegenfurtner, A., Howes, D., Dashi, G., McGraw, N. C. J., Hall, A. K., Dagnone, D., & van Merrienboer, J. J. G. (2019). A new way to look at simulation-based assessment: the relationship between gaze-tracking and exam performance. Canadian Journal of Emergency Medicine, 21(1), 129-137. https://doi.org/10.1017/cem.2018.391
- Szulewski, A., & Howes, D. (2014). Combining First-Person Video and Gaze-Tracking in Medical Simulation: A Technical Feasibility Study. The Scientific World Journal, 2014, 1-4. https://doi.org/10.1155/2014/975752
- Tobii. (2020a). Tobi Pro Glasses 3. https://www.tobii.com/products/eye-trackers/wearables/tobii-pro-glasses-3
- Tobii. (2020b). Glasses 3 controller app (version 1.16.4). https://www.tobii.com/products/eye-trackers/wearables/tobii-pro-glasses-3/controller-app
- Tobii. (2022). Tobii Pro Lab analysis software (version 1.207) [Computer software]. https://connect.tobii.com/s/lab-downloads?language=en_US
- Toubasi, S., Alosta, M. R., Darawad, M. W., & Demeh, W. (2015). Impact of simulation training on Jordanian nurses' performance of basic life support skills: A pilot study. Nurse Education Today, 35(9), 999-1003. https://doi.org/10.1016/j.nedt.2015.03.017
- Tsao, C. W., Aday, A. W., Almarzooq, Z. I., Alonso, A., Beaton, A. Z., Bittencourt, M. S., Boehme, A. K., Buxton, A. E., Carson, A. P., Commodore-Mensah, Y., Elkind, M. S. V., Evenson, K. R., Eze-Nliam, C., Ferguson, J. F., Generoso, G., Ho, J. E., Kalani, R., Khan, S. S., Kissela, B. M., . . . Martin, S. S. (2022). Heart Disease and Stroke Statistics—2022 Update: A Report From the American Heart Association. Circulation, 145(8), e153-e639. https://doi.org/10.1161/CIR.0000000000001052
- Vincent, A., Semmer, N. K., Becker, C., Beck, K., Tschan, F., Bobst, C., Schuetz, P., Marsch, S., & Hunziker, S. (2021). Does stress influence the performance of cardiopulmonary resuscitation? A narrative review of the literature. Journal of Critical Care, 63, 223-230. https://doi.org/10.1016/j.jcrc.2020.09.020
- Wagner, M., Gropel, P., Bibl, K., Olischar, M., Auerbach, M. A., & Gross, I. T. (2020). Eye-tracking during simulation-based neonatal airway management. Pediatric research, 87(3), 518-522. https://doi.org/10.1038/s41390-019-0571-9
- White, M. R., Braund, H., Howes, D., Egan, R., Gegenfurtner, A., van Merrienboer, J. J. G., & Szulewski, A. (2018). Getting Inside the Expert's Head: An Analysis of Physician Cognitive Processes During Trauma Resuscitations. Annals of Emergency Medicine, 72(3), 289-298. https://doi.org/10.1016/j.annemergmed.2018.03.005
- Zhang, T., Yang, J., Liang, N., Pitts, B. J., Prakah-Asante, K. O., Curry, R., Duerstock, B. S., Wachs, J. P., & Yu, D. (2020). Physiological Measurements of Situation Awareness: A Systematic Review. Human Factors, 0018720820969071. https://doi.org/10.1177/0018720820969071
- Zordan, R., Lethborg, C., Forster, J., Mason, T., Walker, V., McBrearty, K., & Torcasio, C. (2022). Development, implementation, and evaluation of a trauma-informed simulation-based training program for graduate nurses: A single arm feasibility and pilot study. Nurse Education Today, 117, 105460. https://doi.org/10.1016/j.nedt.2022.105460