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Record W3108482735 · doi:10.1080/00140139.2020.1859138

Ergonomics training coupled with new Sit-Stand workstation implementation influences usage

2020· article· en· W3108482735 on OpenAlexafffund
Maureen F. Riddell, Jack P. Callaghan

Bibliographic record

VenueErgonomics · 2020
Typearticle
Languageen
FieldPsychology
TopicErgonomics and Musculoskeletal Disorders
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsWorkstationTraining (meteorology)SittingHuman factors and ergonomicsLongitudinal studyMedical educationOperations managementEngineeringPhysical therapyMedicinePoison controlMedical emergency

Abstract

fetched live from OpenAlex

Currently, there is no guidance on the training programme approach that should be provided to new sit-stand workstation users to optimally integrate workstation usage patterns into their working day. The objective of this research study was to determine if a training programme could influence long-term usage of sit-stand workstations. Thirty-five employees from the University of Waterloo volunteered to participate in this longitudinal study. Two different types of training programmes were delivered: (1) an example from industry and (2) based on current literature. There was an influence of training programme on the frequency of sit to stand transitions made each day. Those who received the additional training programme also reported sitting less, standing more and used their sit-stand workstations more consistently day-to-day than those who did not. Practitioner Summary: A longitudinal study was conducted to assess the impact of training programmes on sit-stand workstation usage. A training programme based on current literature resulted in more consistent sit-stand usage than an industry example.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.663
Threshold uncertainty score1.000

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)0.0010.000

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 head0.043
GPT teacher head0.316
Teacher spread0.273 · 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.

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

Citations13
Published2020
Admission routes2
Has abstractyes

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