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Record W4414620084 · doi:10.1016/j.apergo.2025.104651

Exploring the usability and perceived benefits and barriers of portable lift assist devices among paramedic workers

2025· article· en· W4414620084 on OpenAlexaff
Hailey M Nestor, Amanda M Calford, Daphne C. Ho, Richard Ferron, Taylor W. Cleworth, Andrew C. Laing, Steven L. Fischer

Bibliographic record

VenueApplied Ergonomics · 2025
Typearticle
Languageen
FieldPsychology
TopicErgonomics and Musculoskeletal Disorders
Canadian institutionsYork UniversityMcMaster UniversityUniversity of Waterloo
Fundersnot available
KeywordsLift (data mining)Perceived exertionUsabilityContext (archaeology)Manual handlingHealth careHuman factors and ergonomics

Abstract

fetched live from OpenAlex

Patient lifting can expose health care workers to musculoskeletal disorder (MSD) risk factors. Portable lift assist devices may reduce exposure during lifting, however limited evidence on user feedback and efficacy is available to inform purchase decisions. Therefore, we tested the efficacy of two portable lift assist devices relative to a manual lift when lifting an individual from the floor. Participants lifted an actor from the floor using a manual technique and by using two lift assist devices, either an inflatable bladder or a mechanical device. Ratings of perceived exertion demonstrated that the lift assist devices decreased or maintained perceived exertion relative to the manual lift. Semi-structured interviews provided context where perceived benefits of the devices (i.e., decreased exertion and MSD risk) outweighed barriers (i.e., added time to call). The results of this study can inform stakeholders making decisions about lift assist devices purchases.

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 score0.146
Threshold uncertainty score0.651

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 studies0.0000.001
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 head0.026
GPT teacher head0.258
Teacher spread0.232 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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