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Record W7053449538

Use of a probabilistic model to explore the hip fracture and health economic outcomes of safety flooring implemented in an Ontario retirement home environment

2023· dissertation· en· W7053449538 on OpenAlexaffabout

Bibliographic record

VenueUWSpace (University of Waterloo) · 2023
Typedissertation
Languageen
FieldEngineering
TopicLaser Design and Applications
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsHip fractureObservational studyPopulationRisk factorPoison controlInjury preventionRisk assessmentAustralian populationPopulation ageing
DOInot available

Abstract

fetched live from OpenAlex

Hip fractures suffered by older adults are a serious public health concern. The direct yearly expenditure for hip fractures exceeds one billion dollars in Canada and with the older adult population expected to increase within the upcoming years, this issue will become more significant. Hip fractures therefore require consistent, structured investigations into their mechanism, and any insight which could mitigate the challenges associated with their occurrence, should be actively pursued. Hip fracture investigations frequently employ the factor of risk principle which posits that a hip fracture occurs when the loads applied to the hip exceed the strength of the bone. Appropriately designed safety flooring reduces fall-related impact forces and should theoretically reduce hip fracture risk, however, when implemented into an older adult setting the expected reduction in hip fracture risk is not observed. Yet still economic evaluations of safety flooring suggest that it is a better alternative than standard flooring, supporting its inclusion into older adult settings. \nMathematical modelling provides a cost-effective, non-invasive, investigative tool which can be used in tandem with experimental and observational approaches to consider hip fracture risk. A previous model unified experimental and observational data to simulate a population of Canadian older adults, subsequently quantifying their hip fracture risk using the factor or risk principle. However, the simulated population may not be representative of distinct subsets of the Canadian older adult population. Additionally, the model can only assess hip fracture risk in two unique conditions: when the entire population falls on safety flooring, or the entire population falls on standard flooring. These limitations reduce confidence in the model’s ability to quantify hip fracture risk for arbitrary populations and reduce the model’s ability to replicate situations which are objectively more feasible to recreate in the real-world. \nThe objectives of this thesis were to expand the capabilities of the pre-existing probabilistic model, increase its real-world utility by integrating components to simulate specific subpopulations of older adults, incorporate the probabilities of falls in different locations, and consider the economics of implementing safety flooring in specific locations within residential care facilities. The modified probabilistic model supports the notion of population-specific/population-dependent investigations. It also reaffirms the accuracy of understood model assumptions by exhibiting similar behaviours across different populations. Additionally, the model successfully integrated fall location probabilities from observational data to highlight an effect of sex and location on hip fracture risk. Finally, the model suggests that both savings and decisions to implement safety flooring may depend not only on the location of falls but sex characteristics as well. \nUltimately, this thesis demonstrates the feasibility of coupling mechanics, epidemiology, and health economics perspectives within a simulation tool to explore the effects of a safety flooring intervention on hip fracture risk in a retirement home setting on older adult hip fracture risk. The outcomes of this thesis may assist decision-makers within multiple industries (residential care facilities, flooring manufacturers, government policy makers) in developing funding policies, priorities, and design decisions.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.328
Threshold uncertainty score0.660

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.063
GPT teacher head0.244
Teacher spread0.181 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations0
Published2023
Admission routes2
Has abstractyes

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