Visual estimates of blood loss by medical laypeople: Baseline data
SND-ID: 2020-42-1. Version: 1. DOI: https://doi.org/10.5878/jm2q-xq68
Associated documentation
Citation
Creator/Principal investigator(s)
Erik Prytz
- Linköping University
Research principal
Linköping University
- Department of Computer and Information Science
Description
The data material was collected in a controlled experiment that investigated the ability of laypeople to visually assess blood loss and to examine factors that may impact accuracy and the classification of injury severity. A total of 125 laypeople watched 78 short videos each of individuals experiencing a hemorrhage. Victim gender, volume of blood lost, and camera perspective were systematically manipulated in the videos.
The data set consists of four variables: volume estimate, volume error, response time, and classification.
Each variable has a separate sheet in the excel document.
The data is from 125 individuals, each listed on a separate row with a unique ID for each individual.
Each sheet includes the participant ID (anonymous number), age in years, participant sex (0 = male, 1 = female), perspective of the video clip (0 = top view, 1 = front view), and then one column for each victim gender and loss volume combination (24 total). The column label consists of M or F for male and female victim, followed by underscore and the loss volume (e.g., M_50 for male victim with 50 ml of blood l
The data set consists of four variables: volume estimate, volume error, response time, and classification.
Each variable has a separate sheet in the excel document.
The data is from 125 individuals, each listed on a separate row with a unique ID for each individual.
Each sheet includes the participant ID (anonymous number), age in years, participant sex (0 = male, 1 = female), perspective of the video clip (0 = top view, 1 = front view), and then one column for each victim gender and loss volume combination (24 total). The column label consists of M or F for male and female victim, followed by underscore and the loss volume (e.g., M_50 for male victim with 50 ml of blood loss, or F_1100 for a female victim with 1100 ml of blood loss).
Volume estimates are the participants' estimate of blood loss in ml.
Volume error is the estimate minus the true value, in ml.
Response time is the time it took for participants to classify the bleeding as life-threatening or not, in seconds.
Classification is a value from 0 to 1 for the proportion of times the participant classified that particular gender-volume combination as depicting a life-threatening blood loss . Show less..
Data contains personal data
No
Language
Unit of analysis
Population
Medical laypeople (undergraduate students at an american university)
Study design
Experimental study
Sampling procedure
Participants took part in a controlled experiment in which they viewed a series of 78 five-second film clips featuring a person with a simulated bleeding. They were asked to, as quickly as possible, classify the video as showing a life-threatening or not life-threatening bleeding using a keyboard response. After each video, the participant was asked to estimate how large the bleeding was, classify the severity of the injury, and, if they classified the video as showing a life-threatening bleeding, to estimate how minutes it would take for the victim to die from their bleeding. The participants also completed a basic demographics questionnaire at the end of the experiment. The entire experiment took between 40 to 60 minutes to complete.
The participants were students at a large south-eastern university in the USA. Participants with prior medical training or stop the bleed education were excluded. Thus, all participants were medical laypeople without prior experience.
The variables varied in the videos were victim sex (male or female), blood volume (ml of blood on the floor), and rate of blood
The participants were students at a large south-eastern university in the USA. Participants with prior medical training or stop the bleed education were excluded. Thus, all participants were medical laypeople without prior experience.
The variables varied in the videos were victim sex (male or female), blood volume (ml of blood on the floor), and rate of blood flow (in ml per minute). Further, two video sets were created, one with a top-view (camera placed above the victim) or front view (camera placed facing the victim from the front). In each video, the victim was dressed in blue, hydrophobic scrubs and were seated against a white wall. The simulated wound was not visible. The actors were positioned such that the blood flowed down their thigh and pooled between their legs. The same male and female patient actor were used for all videos. The flow rates used were 80, 200, and 400 ml/minute. The blood volumes used were 0, 50, 100, 150, 200, 300, 400, 500, 700, 900, 1100, and 1900 ml. The combination of three flow rates, 13 blood volumes, and two genders meant that there was 78 videos in total.
For the current dataset, the data has been collapsed across flow rate, and the volume 0 has been excluded, meaning that there are 24 combinations (2 genders x 12 volumes). The dataset includes the response time for the initial classification, the classification response, the volume estimate, and the volume error (calculated as the difference between the true amount and the estimated amount of blood loss). Show less..
Time period(s) investigated
2019-08-01 – 2019-12-31
Variables
100
Number of individuals/objects
125
Data format / data structure
Responsible department/unit
Department of Computer and Information Science
Contributor(s)
Marc Friberg - Linköping University, Center for Disaster Medicine and Traumatology
Rachel Phillips - Old Dominion University, Department of Psychology
Mattias Lantz Cronqvist - Linköping University, Department of Computer and Information Science
Carl-Oscar Jonson - Linköping University, Center for Disaster Medicine and Traumatology, and Department of Biomedical and Clinical Sciences
Research area
Other clinical medicine (Standard för svensk indelning av forskningsämnen 2011)
Applied psychology (Standard för svensk indelning av forskningsämnen 2011)
Keywords