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




TekijätLule Herman, Mugerwa Michael, SSebuufu Robinson, Kyamanywa Patrick, Posti Jussi P, Wilson Michael L

Julkaisuvuosi2024

JournalInternational journal of surgery protocols

Tietokannassa oleva lehden nimiInternational journal of surgery protocols

Lehden akronyymiInt J Surg Protoc

Vuosikerta28

Numero1

Aloitussivu12

Lopetussivu19

ISSN2468-3574

eISSN2468-3574

DOIhttps://doi.org/10.1097/SP9.0000000000000013

Verkko-osoitehttps://journals.lww.com/ijsprotocols/fulltext/2024/03000/rural_trauma_team_development_training_amongst.3.aspx

Rinnakkaistallenteen osoitehttps://research.utu.fi/converis/portal/detail/Publication/387209435


Tiivistelmä

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).


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Last updated on 2024-26-11 at 13:41