Monitoring Performance and Mental Workload in an Automated System

Background Anesthesia information management systems (AIMSs) automatically import real-time vital signs from physiological monitors to anesthetic records, replacing part of anesthetists’ traditional manual record keeping. However, only a handful of studies have examined the effects of AIMSs on anesthetists’ monitoring performance. Objective This study aimed to compare the effects of AIMS use and manual record keeping on anesthetists’ monitoring performance, using a full-scale high-fidelity simulation. Methods This simulation study was a randomized controlled trial with a parallel group design that compared the effects of two record-keeping methods (AIMS vs manual) on anesthetists’ monitoring performance. Twenty anesthetists at a tertiary hospital in Hong Kong were randomly assigned to either the AIMS or manual condition, and they participated in a 45-minute scenario in a high-fidelity simulation environment. Participants took over a case involving general anesthesia for below-knee amputation surgery and performed record keeping. The three primary outcomes were participants’ (1) vigilance detection accuracy (%), (2) situation awareness accuracy (%), and (3) subjective mental workload (0-100). Results With regard to the primary outcomes, there was no significant difference in participants’ vigilance detection accuracy (AIMS, 56.7% vs manual, 56.7%; P=.50), and subjective mental workload was significantly lower in the AIMS condition than in the manual condition (AIMS, 34.2 vs manual, 46.7; P=.02). However, the result for situation awareness accuracy was inconclusive as the study did not have enough power to detect a difference between the two conditions. Conclusions Our findings suggest that it is promising for AIMS use to become a mainstay of anesthesia record keeping. AIMSs are effective in reducing anesthetists’ workload and improving the quality of their anesthetic record keeping, without compromising vigilance.

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New Interface To Cope With Unreliable Airspeed Indications: A Behavioral And Eye-Tracking Study.

10.31224/osf.io/nx4d2 ◽

2021 ◽

Author(s):

Eve Fabre ◽

Patrick Braca ◽

Vsevolod Peysakhovich ◽

Frédéric Dehais

Keyword(s):

Eye Tracking ◽

Efficient Solution ◽

Mental Workload ◽

Flight Deck ◽

Monitoring Performance

When unreliable airspeed events occur, the pilot flying (PF) is required to fly the aircraft using the thrust and the pitch parameters that are displayed in two distanced locations of the flight deck. The Sycopaero interface was designed to limit the PF’s workload by automatically displaying thrust and pitch values specific to aircraft configuration on the Primary Flight Display. Participants performed a simulated flight scenario in which they lost airspeed information during take-off with and without the Sycopaero interface. Both behavioral and ocular results demonstrate that the Sycopaero interface significantly lowers PFs’ mental workload and improves their monitoring performance. Taken together, these results suggest that the Sycopaero interface may be an efficient solution in case of unreliable airspeed events.

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Automation and Crew Performance: The Importance of Who and What

Proceedings of the Human Factors and Ergonomics Society Annual Meeting ◽

10.1177/154193129604000209 ◽

1996 ◽

Vol 40 (2) ◽

pp. 49-53 ◽

Cited By ~ 5

Author(s):

Florian Jentsch ◽

Clint Bowers

Keyword(s):

Task Performance ◽

Mental Workload ◽

Automated System ◽

Perceived Effort ◽

The Past ◽

Navigation Computer ◽

Different Types ◽

Levels Of Automation ◽

Different Levels ◽

Detailed Picture

In the past, “automation” in the cockpit has been associated with both an increase and a reduction in workload, performance, and crew communications. A reason for these apparently contradictory results could be that different types of automation were studied, for example, automation that required little vs. considerable interaction with a machine. The current study investigated whether automation of different task domains for different crewmembers has differential effects. Sixteen pilots formed two-pilot crews. The crews each completed four experimental flights in a PC-based simulator, encountering different levels of automation. Systematically, an automated system for the pilot (a simple autopilot) and one for the copilot (a navigation computer) were made available or were unavailable, alone or in combination. The results showed that the automation manipulations improved task performance only when they were combined. Additionally, the use of the navigation computer reduced communications within the cockpit, while the autopilot was associated with larger contributions by the pilot. Further, mental workload and frustration were lower when the navigation computer was available. Also, perceived effort was lower with the autopilot on. The results of the current study suggest a more detailed picture of automation effects than previously known. Additionally, the results suggest that different types of automation can interact to create unexpected effects that may not be uncovered if one studies automated systems individually.

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Comparison of the Effects of Automated and Manual Record Keeping on Anesthetists’ Monitoring Performance: Randomized Controlled Simulation Study (Preprint)

10.2196/preprints.16036 ◽

2019 ◽

Author(s):

Man-Kei Tse ◽

Simon Y W Li ◽

Tsz Hin Chiu ◽

Chung Wai Lau ◽

Ka Man Lam ◽

...

Keyword(s):

Situation Awareness ◽

Simulation Study ◽

Mental Workload ◽

Detection Accuracy ◽

High Fidelity ◽

High Fidelity Simulation ◽

Record Keeping ◽

Randomized Controlled ◽

Monitoring Performance ◽

Manual Record

BACKGROUND Anesthesia information management systems (AIMSs) automatically import real-time vital signs from physiological monitors to anesthetic records, replacing part of anesthetists’ traditional manual record keeping. However, only a handful of studies have examined the effects of AIMSs on anesthetists’ monitoring performance. OBJECTIVE This study aimed to compare the effects of AIMS use and manual record keeping on anesthetists’ monitoring performance, using a full-scale high-fidelity simulation. METHODS This simulation study was a randomized controlled trial with a parallel group design that compared the effects of two record-keeping methods (AIMS vs manual) on anesthetists’ monitoring performance. Twenty anesthetists at a tertiary hospital in Hong Kong were randomly assigned to either the AIMS or manual condition, and they participated in a 45-minute scenario in a high-fidelity simulation environment. Participants took over a case involving general anesthesia for below-knee amputation surgery and performed record keeping. The three primary outcomes were participants’ (1) vigilance detection accuracy (%), (2) situation awareness accuracy (%), and (3) subjective mental workload (0-100). RESULTS With regard to the primary outcomes, there was no significant difference in participants’ vigilance detection accuracy (AIMS, 56.7% vs manual, 56.7%; <i>P</i>=.50), and subjective mental workload was significantly lower in the AIMS condition than in the manual condition (AIMS, 34.2 vs manual, 46.7; <i>P</i>=.02). However, the result for situation awareness accuracy was inconclusive as the study did not have enough power to detect a difference between the two conditions. CONCLUSIONS Our findings suggest that it is promising for AIMS use to become a mainstay of anesthesia record keeping. AIMSs are effective in reducing anesthetists’ workload and improving the quality of their anesthetic record keeping, without compromising vigilance.

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