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Record W4387598118 · doi:10.1080/00140139.2023.2270728

Quantifying how functional and structural personal factors influence biomechanical exposures in paramedic lifting tasks

2023· article· en· W4387598118 on OpenAlexaff
Daniel P. Armstrong, Tyson A.C. Beach, Steven L. Fischer

Bibliographic record

VenueErgonomics · 2023
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsRange of motionKinematicsFlexibility (engineering)Physical medicine and rehabilitationHip flexionWork (physics)Functional movementBiomechanicsBack injuryPhysical therapyPoison controlMotion analysisPsychologyMedicineMathematicsComputer scienceEngineeringStatisticsPhysicsAnatomyArtificial intelligence

Abstract

fetched live from OpenAlex

It is unknown how structural (sex, stature, body mass) and functional (strength, flexibility) personal factors influence lifting strategy in paramedic work. We explored whether variance in peak low back forces and kinematic coordination patterns could be explained by structural and functional personal factors in paramedic lifting tasks. Seventy-two participants performed backboard and stretcher lifts. Peak low back forces normalised to body mass, as well as kinematic coordination patterns, were calculated as dependent variables. Being female, stronger, shorter, having higher body mass, and/or having greater lower body range of motion (ROM) were all independently associated with lower normalised low back forces across backboard and stretcher lifting. Females and stronger individuals seemed to define a movement objective to consistently minimise compressive forces, while individuals with greater hip ROM consistently minimised anteroposterior shear forces. The efficacy of improving strength and hip ROM to reduce low back forces in paramedic lifting should be investigated.Practitioner summary: Females, stronger individuals, and individuals with greater hip range of motion consistently exhibited lower normalised low back forces in paramedic lifting. Improving strength and hip range of motion via training is a potential proactive ergonomics approach to reduce peak low back forces in paramedic lifting tasks.

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)0.000
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 score0.037
Threshold uncertainty score0.371

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.041
GPT teacher head0.297
Teacher spread0.256 · 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

Citations8
Published2023
Admission routes1
Has abstractyes

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