Effect of monitor positioning on visual attention and situation awareness during neonatal resuscitation: a randomised simulation study
Brenda Hiu Yan Law,
Po-Yin Cheung,
Sylvia van Os
et al.
Abstract:ObjectivesTo compare situation awareness (SA), visual attention (VA) and protocol adherence in simulated neonatal resuscitations using two different monitor positions.DesignRandomised controlled simulation study.SettingsSimulation lab at the Royal Alexandra Hospital, Edmonton, Canada.ParticipantsHealthcare providers (HCPs) with Neonatal Resuscitation Program (NRP) certification within the last 2 years and trained in neonatal endotracheal intubations.InterventionHCPs were randomised to either central (eye-level… Show more
“…The present SEEV model findings support previous research investigating the association of eye tracking metrics and situation awareness measures ( Law et al, 2020 ; Moore & Gugerty, 2010 ). Similar to Moore and Gugerty (2010) , SA level 1 was associated with model fit but, also similar to Moore and Gugerty (2010) , the explained variance was small.…”
Section: Discussionsupporting
confidence: 90%
“…To complement our analysis, we also investigated the association of observed PDTs in phase 5 with the perception scores, as in previous research ( Law et al, 2020 ; Moore & Gugerty, 2010 ). As summarized in Table 4 , the PDT on the AOI group patient showed significant negative correlations with global situation perception ( r s = −.341) and environmental perception ( r s = −.322).…”
Section: Resultsmentioning
confidence: 99%
“…In the context of healthcare, Law et al (2020) manipulated the position of the patient monitor during a simulated neonatal resuscitation. As a secondary analysis, Law et al. (2020) reported a nonsignificant correlation of r s = .39 ( p = .07) between a composite SAGAT score (SA levels 1–3) with the percentage of visual attention on the patient monitor.…”
Section: Introductionmentioning
confidence: 99%
“…By investigating the correlation of the SEEV model fit and SAGAT score, we contribute to and extend the above research in several ways. First, previous research with actual domain experts (e.g., Law et al, 2020 ; Moore & Gugerty, 2010 ) was limited in relation to sample size ( N = 11–29). The present sample includes 61 qualified anesthesiologists.…”
Objective In the context of anesthesiology, we investigated whether the salience effort expectancy value (SEEV) model fit is associated with situation awareness and perception scores. Background The distribution of visual attention is important for situation awareness—that is, understanding what is going on—in safety-critical domains. Although the SEEV model has been suggested as a process situation awareness measure, the validity of the model as a predictor of situation awareness has not been tested. Method In a medical simulation, 31 senior and 30 junior anesthesiologists wore a mobile eye tracker and induced general anesthesia into a simulated patient. When inserting a breathing tube into the mannequin’s trachea (endotracheal intubation), the scenario included several clinically relevant events for situation awareness and general events in the environment. Both were assessed using direct awareness measures. Results The overall SEEV model fit was good with no difference between junior and senior anesthesiologists. Overall, the situation awareness scores were low. As expected, the SEEV model fits showed significant positive correlations with situation awareness level 1 scores. Conclusion The SEEV model seems to be suitable as a process situation awareness measure to predict and investigate the perception of changes in the environment (situation awareness level 1). The situation awareness scores indicated that anesthesiologists seem not to perceive the environment well during endotracheal intubation. Application The SEEV model fit can be used to capture and assess situation awareness level 1. During endotracheal intubation, anesthesiologists should be supported by technology or staff to notice changes in the environment.
“…The present SEEV model findings support previous research investigating the association of eye tracking metrics and situation awareness measures ( Law et al, 2020 ; Moore & Gugerty, 2010 ). Similar to Moore and Gugerty (2010) , SA level 1 was associated with model fit but, also similar to Moore and Gugerty (2010) , the explained variance was small.…”
Section: Discussionsupporting
confidence: 90%
“…To complement our analysis, we also investigated the association of observed PDTs in phase 5 with the perception scores, as in previous research ( Law et al, 2020 ; Moore & Gugerty, 2010 ). As summarized in Table 4 , the PDT on the AOI group patient showed significant negative correlations with global situation perception ( r s = −.341) and environmental perception ( r s = −.322).…”
Section: Resultsmentioning
confidence: 99%
“…In the context of healthcare, Law et al (2020) manipulated the position of the patient monitor during a simulated neonatal resuscitation. As a secondary analysis, Law et al. (2020) reported a nonsignificant correlation of r s = .39 ( p = .07) between a composite SAGAT score (SA levels 1–3) with the percentage of visual attention on the patient monitor.…”
Section: Introductionmentioning
confidence: 99%
“…By investigating the correlation of the SEEV model fit and SAGAT score, we contribute to and extend the above research in several ways. First, previous research with actual domain experts (e.g., Law et al, 2020 ; Moore & Gugerty, 2010 ) was limited in relation to sample size ( N = 11–29). The present sample includes 61 qualified anesthesiologists.…”
Objective In the context of anesthesiology, we investigated whether the salience effort expectancy value (SEEV) model fit is associated with situation awareness and perception scores. Background The distribution of visual attention is important for situation awareness—that is, understanding what is going on—in safety-critical domains. Although the SEEV model has been suggested as a process situation awareness measure, the validity of the model as a predictor of situation awareness has not been tested. Method In a medical simulation, 31 senior and 30 junior anesthesiologists wore a mobile eye tracker and induced general anesthesia into a simulated patient. When inserting a breathing tube into the mannequin’s trachea (endotracheal intubation), the scenario included several clinically relevant events for situation awareness and general events in the environment. Both were assessed using direct awareness measures. Results The overall SEEV model fit was good with no difference between junior and senior anesthesiologists. Overall, the situation awareness scores were low. As expected, the SEEV model fits showed significant positive correlations with situation awareness level 1 scores. Conclusion The SEEV model seems to be suitable as a process situation awareness measure to predict and investigate the perception of changes in the environment (situation awareness level 1). The situation awareness scores indicated that anesthesiologists seem not to perceive the environment well during endotracheal intubation. Application The SEEV model fit can be used to capture and assess situation awareness level 1. During endotracheal intubation, anesthesiologists should be supported by technology or staff to notice changes in the environment.
“…These studies should assess long-term neurodevelopmental outcomes. Studies are also required to determine whether an RFM adds to the attentional and cognitive demands on healthcare providers or diverts attention away from the infant 40–44. It is unclear whether specialised training is required to maximise the benefit of an RFM 43…”
ImportanceAnimal and observational human studies report that delivery of excessive tidal volume (VT) at birth is associated with lung and brain injury. Using a respiratory function monitor (RFM) to guide VT delivery might reduce injury and improve outcomes.ObjectiveTo determine whether use of an RFM in addition to clinical assessment versus clinical assessment alone during mask ventilation in the delivery room reduces in-hospital mortality and morbidity of infants <37 weeks’ gestation.Study selectionRandomised controlled trials (RCTs) comparing RFM in addition to clinical assessment versus clinical assessment alone during mask ventilation in the delivery room of infants born <37 weeks’ gestation.Data analysisRisk of bias was assessed using Covidence Collaboration tool and pooled into a meta-analysis using a random-effects model. The primary outcome was death prior to discharge.Main outcomeDeath before hospital discharge.ResultsThree RCTs enrolling 443 infants were combined in a meta-analysis. The pooled analysis showed no difference in rates of death before discharge with an RFM versus no RFM, relative risk (RR) 95% (CI) 0.98 (0.64 to 1.48). The pooled analysis suggested a significant reduction for brain injury (a combination of intraventricular haemorrhage and periventricular leucomalacia) (RR 0.65 (0.48 to 0.89), p=0.006) and for intraventricular haemorrhage (RR 0.69 (0.50 to 0.96), p=0.03) in infants receiving positive pressure ventilation with an RFM versus no RFM.ConclusionIn infants <37 weeks, an RFM in addition to clinical assessment compared with clinical assessment during mask ventilation resulted in similar in-hospital mortality, significant reduction for any brain injury and intraventricular haemorrhage. Further trials are required to determine whether RFMs should be routinely available for neonatal resuscitation.
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