A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä
Rural trauma team development training amongst medical trainees and traffic law enforcement professionals in a low-income country: a protocol for a prospective multicenter interrupted time series
Tekijät: Lule Herman, Mugerwa Michael, SSebuufu Robinson, Kyamanywa Patrick, Posti Jussi P, Wilson Michael L
Julkaisuvuosi: 2024
Journal: International journal of surgery protocols
Tietokannassa oleva lehden nimi: International journal of surgery protocols
Lehden akronyymi: Int J Surg Protoc
Vuosikerta: 28
Numero: 1
Aloitussivu: 12
Lopetussivu: 19
ISSN: 2468-3574
eISSN: 2468-3574
DOI: https://doi.org/10.1097/SP9.0000000000000013
Verkko-osoite: https://journals.lww.com/ijsprotocols/fulltext/2024/03000/rural_trauma_team_development_training_amongst.3.aspx
Rinnakkaistallenteen osoite: https://research.utu.fi/converis/portal/detail/Publication/387209435
Background: Road traffic injuries and their resulting mortality disproportionately affect rural communities in low-middle-income countries (LMICs) due to limited human and infrastructural resources for postcrash care. Evidence from high-income countries show that trauma team development training could improve the efficiency, care, and outcome of injuries. A paucity of studies have evaluated the feasibility and applicability of this concept in resource constrained settings. The aim of this study protocol is to establish the feasibility of rural trauma team development and training in a cohort of medical trainees and traffic law enforcement professionals in Uganda.
Methods: Muticenter interrupted time series of prospective interventional trainings, using the rural trauma team development course (RTTDC) model of the American College of Surgeons. A team of surgeon consultants will execute the training. A prospective cohort of participants will complete a before and after training validated trauma related multiple choice questionnaire during September 2019-November 2023. The difference in mean prepost training percentage multiple choice questionnaire scores will be compared using ANOVA-test at 95% CI. Time series regression models will be used to test for autocorrelations in performance. Acceptability and relevance of the training will be assessed using 3 and 5-point-Likert scales. All analyses will be performed using Stata 15.0. Ethical approval was obtained from Research and Ethics Committee of Mbarara University of Science and Technology (Ref: MUREC 1/7, 05/05-19) and Uganda National Council for Science and Technology (Ref: SS 5082). Retrospective registration was accomplished with Research Registry (UIN: researchregistry9490).
Ladattava julkaisu This is an electronic reprint of the original article. |