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Record W2090857072 · doi:10.1136/ip.2010.029215.227

A public health approach to fall and injury prevention among seniors in Canada

2010· article· en· W2090857072 on OpenAlexaffabout
Vera Scott, Mark L. Herman, E. John Gallagher, Alison Sum

Bibliographic record

VenueInjury Prevention · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsMinistry of Health
Fundersnot available
KeywordsPublic healthSuicide preventionInjury preventionGovernment (linguistics)Occupational safety and healthPoison controlFall preventionGerontologyHuman factors and ergonomicsMedicineEpidemiologyEnvironmental healthMedical emergencyNursing

Abstract

fetched live from OpenAlex

Introduction The need to prevent falls and related injuries among seniors is a significant public health issue in Canada, and all nations where an aging demographic puts higher numbers at risk. To address this costly and complex problem, a sustained collaboration has occurred over the past 20 years among falls prevention leaders within government, the health system, academia and local communities. Methods This review summarizes key elements of a coordinated, public health approach to the prevention of falls and related injuries among those aged 65 years, with an epidemiological analysis of fall-related hospital and mortality data for persons aged 65 years and older. Review methods included a synthesis of historical records, a scan of existing programs and findings from in-depth interviews with key informants. Results Outcomes of this sustained approach include a significant reduction in fall-related hospitalization and death rates in some Canadian provinces, which is paralleled by a growth in evidence-based falls prevention programs and services for those at risk. Conclusion This presentation concludes with a summary of the key developments in the evolution of fall and related injury prevention activities over the past two decades. In particular, how the sustained, collaborative efforts have resulted in Canada emerging as an example of success in the formation of comprehensive networks for the integration of evidence-based falls prevention into health service delivery for seniors.

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)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.211
Threshold uncertainty score0.496

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.037
GPT teacher head0.337
Teacher spread0.299 · 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

Citations1
Published2010
Admission routes2
Has abstractyes

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