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Record W4392951781 · doi:10.3390/ijerph21030363

Paramedic Willingness to Report Violence Following the Introduction of a Novel, Point-of-Event Reporting Process in a Single Canadian Paramedic Service

2024· article· en· W4392951781 on OpenAlexafffundabout
Justin Mausz, Michael-Jon Braaksma, Mandy Johnston, Alan M Batt, Elizabeth Donnelly

Bibliographic record

VenueInternational Journal of Environmental Research and Public Health · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicWorkplace Violence and Bullying
Canadian institutionsUniversity of WindsorQueen's University
FundersUniversity of Windsor
KeywordsContext (archaeology)AccountabilityPsychologyOccupational safety and healthService (business)Public relationsMedicineMedical emergencyApplied psychologyNursingBusinessPolitical scienceMarketingGeography

Abstract

fetched live from OpenAlex

Violence against paramedics is increasingly recognized as an important occupational health problem, but pervasive and institutionalized underreporting hinders efforts at risk mitigation. Earlier research has shown that the organizational culture within paramedicine may contribute to underreporting, and researchers have recommended involving paramedics in the development of violence prevention policies, including reporting systems. Eighteen months after the launch of a new violence reporting system in Peel Region, Ontario, Canada, we surveyed paramedics about their experiences reporting violent encounters. Our objectives were to assess their willingness to report violence and explore factors that influence their decisions to file a report. Between September and December 2022, a total of 204 (33% of eligible) paramedics chose to participate, of whom 67% (N = 137) had experienced violence since the launch of the new reporting process, with 83% (N = 114) reporting the incidents at least some of the time. After thematically analyzing free-text survey responses, we found that the participants cited the accessibility of the new reporting process and the desire to promote accountability among perpetrators while contributing to a safer workplace as motivating factors. Their decisions to file a report, however, could be influenced by the perceived 'volitionality' and severity of the violent encounters, particularly in the context of (un)supportive co-workers and supervisors. Ultimately, the participants' belief that the report would lead to meaningful change within the service was a key driver of reporting behavior.

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)0.013
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.519
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.086
GPT teacher head0.435
Teacher spread0.349 · 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 designQualitative
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

Citations9
Published2024
Admission routes3
Has abstractyes

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