3
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Classification of road traffic injury collision characteristics using text mining analysis: Implications for road injury prevention

      research-article
      1 , 2 , * , 1 , 1 , 3
      PLoS ONE
      Public Library of Science

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Road traffic injuries are a leading cause of morbidity and mortality globally. Understanding circumstances leading to road traffic injury is crucial to improve road safety, and implement countermeasures to reduce the incidence and severity of road trauma. We aimed to characterise crash characteristics of road traffic collisions in Victoria, Australia, and to examine the relationship between crash characteristics and fault attribution. Data were extracted from the Victorian State Trauma Registry for motor vehicle drivers, motorcyclists, pedal cyclists and pedestrians with a no-fault compensation claim, aged > = 16 years and injured 2010–2016. People with intentional injury, serious head injury, no compensation claim/missing injury event description or who died < = 12-months post-injury were excluded, resulting in a sample of 2,486. Text mining of the injury event using QDA Miner and Wordstat was used to classify crash circumstances for each road user group. Crashes in which no other was at fault included circumstances involving lost control or avoiding a hazard, mechanical failure or medical conditions. Collisions in which another was predominantly at fault occurred at intersections with another vehicle entering from an adjacent direction, and head-on collisions. Crashes with higher prevalence of unknown fault included multi-vehicle collisions, pedal cyclists injured in rear-end collisions, and pedestrians hit while crossing the road or navigating slow traffic areas. We discuss several methods to promote road safety and to reduce the incidence and severity of road traffic injuries. Our recommendations take into consideration the incidence and impact of road trauma for different types of road users, and include engineering and infrastructure controls through to interventions targeting or accommodating human behaviour.

          Related collections

          Most cited references49

          • Record: found
          • Abstract: found
          • Article: not found

          A new method of classifying prognostic comorbidity in longitudinal studies: Development and validation

          The objective of this study was to develop a prospectively applicable method for classifying comorbid conditions which might alter the risk of mortality for use in longitudinal studies. A weighted index that takes into account the number and the seriousness of comorbid disease was developed in a cohort of 559 medical patients. The 1-yr mortality rates for the different scores were: "0", 12% (181); "1-2", 26% (225); "3-4", 52% (71); and "greater than or equal to 5", 85% (82). The index was tested for its ability to predict risk of death from comorbid disease in the second cohort of 685 patients during a 10-yr follow-up. The percent of patients who died of comorbid disease for the different scores were: "0", 8% (588); "1", 25% (54); "2", 48% (25); "greater than or equal to 3", 59% (18). With each increased level of the comorbidity index, there were stepwise increases in the cumulative mortality attributable to comorbid disease (log rank chi 2 = 165; p less than 0.0001). In this longer follow-up, age was also a predictor of mortality (p less than 0.001). The new index performed similarly to a previous system devised by Kaplan and Feinstein. The method of classifying comorbidity provides a simple, readily applicable and valid method of estimating risk of death from comorbid disease for use in longitudinal studies. Further work in larger populations is still required to refine the approach because the number of patients with any given condition in this study was relatively small.
            Bookmark
            • Record: found
            • Abstract: not found
            • Article: not found

            Behavior as seen by the actor and as seen by the observer.

              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              Long-term health status and trajectories of seriously injured patients: A population-based longitudinal study

              Background Improved understanding of the quality of survival of patients is crucial in evaluating trauma care, understanding recovery patterns and timeframes, and informing healthcare, social, and disability service provision. We aimed to describe the longer-term health status of seriously injured patients, identify predictors of outcome, and establish recovery trajectories by population characteristics. Methods and findings A population-based, prospective cohort study using the Victorian State Trauma Registry (VSTR) was undertaken. We followed up 2,757 adult patients, injured between July 2011 and June 2012, through deaths registry linkage and telephone interview at 6-, 12-, 24-, and 36-months postinjury. The 3-level EuroQol 5 dimensions questionnaire (EQ-5D-3L) was collected, and mixed-effects regression modelling was used to identify predictors of outcome, and recovery trajectories, for the EQ-5D-3L items and summary score. Mean (SD) age of participants was 50.8 (21.6) years, and 72% were male. Twelve percent (n = 333) died during their hospital stay, 8.1% (n = 222) of patients died postdischarge, and 155 (7.0%) were known to have survived to 36-months postinjury but were lost to follow-up at all time points. The prevalence of reporting problems at 36-months postinjury was 37% for mobility, 21% for self-care, 47% for usual activities, 50% for pain/discomfort, and 41% for anxiety/depression. Continued improvement to 36-months postinjury was only present for the usual activities item; the adjusted relative risk (ARR) of reporting problems decreased from 6 to 12 (ARR 0.87, 95% CI: 0.83–0.90), 12 to 24 (ARR 0.94, 95% CI: 0.90–0.98), and 24 to 36 months (ARR 0.95, 95% CI: 0.95–0.99). The risk of reporting problems with pain or discomfort increased from 24- to 36-months postinjury (ARR 1.06, 95% CI: 1.01, 1.12). While loss to follow-up was low, there was responder bias with patients injured in intentional events, younger, and less seriously injured patients less likely to participate; therefore, these patient subgroups were underrepresented in the study findings. Conclusions The prevalence of ongoing problems at 3-years postinjury is high, confirming that serious injury is frequently a chronic disorder. These findings have implications for trauma system design. Investment in interventions to reduce the longer-term impact of injuries is needed, and greater investment in primary prevention is needed.
                Bookmark

                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: InvestigationRole: MethodologyRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: InvestigationRole: MethodologyRole: SupervisionRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS One
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                27 January 2021
                2021
                : 16
                : 1
                : e0245636
                Affiliations
                [1 ] Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
                [2 ] Caulfield Pain Management and Research Centre, Caulfield Hospital, Caulfield, Victoria, Australia
                [3 ] Health Data Research UK, Swansea University Medical School, Swansea University, Swansea, Wales, United Kingdom
                Tongii University, CHINA
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                https://orcid.org/0000-0001-7839-6058
                https://orcid.org/0000-0003-3262-5956
                https://orcid.org/0000-0001-7096-7688
                Article
                PONE-D-20-34781
                10.1371/journal.pone.0245636
                7840051
                33503030
                93ce9da7-e79c-48c3-8ab8-f8fb973759b3
                © 2021 Giummarra et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 4 November 2020
                : 4 January 2021
                Page count
                Figures: 7, Tables: 6, Pages: 29
                Funding
                Funded by: Australian Research Council (AU)
                Award ID: DE170100726
                Award Recipient :
                Funded by: Australian Research Council (AU)
                Award ID: DE180100825
                Award Recipient :
                Funded by: Australian Research Council (AU)
                Award ID: FT170100048
                Award Recipient :
                This project was funded by an Australian Research Council (ARC) Discovery Early Career Research Awards to MJG (DE170100726) and BB (DE180100825), and ARC Future Fellowship to BJG (FT170100048). The Victorian State Trauma Registry is funded by the Transport Accident Commission (TAC) and the Department of Health and Human Services (State Government of Victoria).
                Categories
                Research Article
                Engineering and Technology
                Civil Engineering
                Transportation Infrastructure
                Roads
                Engineering and Technology
                Transportation
                Transportation Infrastructure
                Roads
                Medicine and Health Sciences
                Critical Care and Emergency Medicine
                Trauma Medicine
                Traumatic Injury
                Medicine and Health Sciences
                Critical Care and Emergency Medicine
                Trauma Medicine
                Traumatic Injury
                Head Injury
                Earth Sciences
                Geophysics
                Seismology
                Physical Sciences
                Physics
                Geophysics
                Seismology
                Medicine and Health Sciences
                Critical Care and Emergency Medicine
                Trauma Medicine
                Traumatic Injury
                Neurotrauma
                Spinal Cord Injury
                Medicine and Health Sciences
                Neurology
                Spinal Cord Injury
                Medicine and Health Sciences
                Epidemiology
                Medical Risk Factors
                Cancer Risk Factors
                Medicine and Health Sciences
                Oncology
                Cancer Risk Factors
                Social Sciences
                Law and Legal Sciences
                Criminal Justice System
                Law Enforcement
                Police
                People and Places
                Population Groupings
                Professions
                Police
                Medicine and Health Sciences
                Epidemiology
                Medical Risk Factors
                Traumatic Injury Risk Factors
                Road Traffic Collisions
                Medicine and Health Sciences
                Public and Occupational Health
                Traumatic Injury Risk Factors
                Road Traffic Collisions
                Custom metadata
                The authors do not have approval from the data custodians at the VSTR or the TAC to publish the original data. To access a dataset that is similar to that used in the present study would require a data request to the Victorian State Trauma Outcomes Registry and Monitoring Group (VSTORM). Instructions available here: https://www.monash.edu/medicine/sphpm/vstorm/data-requests, and data requests require ethics approval before data can be provided. There may be some other limits to data requests. To obtain the linked data from the Transport Accident Commission (TAC) that was used in this study, which was more extensive than the routine linkage between VSTR and TAC, requires a data request via the client research team at the TAC ( research@ 123456tac.vic.gov.au ). To initiate both of these data requests interested parties should first contact the VSTORM project office; contact details are available here: https://www.monash.edu/medicine/sphpm/vstorm/contact. To gain access to the exact same dataset as that used in the present study interested parties should contact the study corresponding author, and follow the same data custodian request processes outlined above.

                Uncategorized
                Uncategorized

                Comments

                Comment on this article