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Record W2790166957 · doi:10.1097/jtn.0000000000000354

Examining Injury Among Indigenous Young People: A Narrative Scoping Review

2018· article· en· W2790166957 on OpenAlexaff
Crystal McLeod, Amanda Helt, Bayan Alilyyani

Bibliographic record

VenueJournal of Trauma Nursing · 2018
Typearticle
Languageen
FieldMedicine
TopicTrauma and Emergency Care Studies
Canadian institutionsWestern University
Fundersnot available
KeywordsIndigenousInclusion (mineral)PopulationPoison controlMedicineInjury preventionExploratory researchIntervention (counseling)PsychologyNursingMedical emergencyEnvironmental healthSociologySocial psychologySocial science

Abstract

fetched live from OpenAlex

Indigenous young people of circumpolar developed countries experience a disproportionate incidence of injury compared with non-Indigenous young people. Much has been published about the experience of injury within the general Indigenous population, but literature is limited with regard to Indigenous young people. Trauma nurses, who are important members of the multidisciplinary team that provides injury intervention to Indigenous populations, need to be aware of this literature, as well as subsequent research gaps, to provide effective care to Indigenous young people experiencing injury. The purpose of this study was to provide an updated comprehensive review of the research-based evidence related to all-cause injury for Indigenous young people. An exploratory scoping review was conducted with a narrative synthesis. To locate literature, 7 electronic databases were searched from 2003 to 2017. Criteria were applied to all located articles to determine inclusion and then data were extracted from each study's findings. A total of 15 studies were included in this review that met the inclusion criteria. Themes derived from the knowledge synthesis process are as follows: incidence rates, mechanisms of injury, risk factors, and gaps in research. A strong epidemiological focus has emerged from the research found in this review of injury among Indigenous young people. The results of this review serve as a starting point for trauma nurses to successfully assess, build trusting relationships with, and further research injury among Indigenous young people.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.563
Threshold uncertainty score0.673

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.047
GPT teacher head0.371
Teacher spread0.324 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations5
Published2018
Admission routes1
Has abstractyes

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