jian-wen-low-sepsis-and-trauma-resuscitation-2024

4,960 responses from 40 respondents to 62 items.

About this table

DescriptionComparison of virtual and in-person simulations for sepsis and trauma resuscitation training in Singapore: a randomized controlled trial
ReferenceLow, Matthew Jian Wen, Gene Wai Han Chan, Zisheng Li, Yiwen Koh, Chi Loong Jen, Zi Yao Lee, and Lenard Tai Win Cheng. 2024. “Comparison of Virtual and In-Person Simulations for Sepsis and Trauma Resuscitation Training in Singapore: A Randomized Controlled Trial.” Harvard Dataverse. https://doi.org/10.7910/DVN/KHAYXN.
LicenceCC0 1.0
Source datahttps://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/KHAYXN

Size and shape

Responses4,960
Respondents40
Items62
Response categories3
Responses per respondent124
Responses per item80
Density2
LongitudinalTRUE

Classification

age rangeAdult (18+)
sampleTargeted/specific
construct typeOpinion/attitude
measurement toolSurvey/questionnaire
item formatMixed
primary language(s)eng
construct nameComparison of virtual and in-person simulations for sepsis and trauma resuscitation

Columns

cov_agecov_date_of_intervention_either_mock_code_or_virtual_simulatcov_gendercov_interventioncov_number_of_months_in_em_as_doctor_before_nuh_emdcov_number_of_years_post_graduatecov_ssls_q1cov_ssls_q2cov_ssls_q3cov_ssls_q4cov_ssls_q5iditemraterresp

Get the data

Download CSVno account neededBrowse on Redivisexplore and queryCroissant metadataHugging Face, Kaggle, OpenML

Or load it directly in R or Python:

# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("jian-wen-low-sepsis-and-trauma-resuscitation-2024")
# Python
pip install irw

import irw
df = irw.fetch("jian-wen-low-sepsis-and-trauma-resuscitation-2024")

Version and provenance

IRW versionv393
Redivis datasetitem_response_warehouse_2 v19.0
Redivis dataset DOI10.57761/qtx5-4m80
Manifest pin for this IRW versionv19.0
Metadata sourceirw_meta v23.0