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Record W1759260537 · doi:10.3233/wor-2010-1079

Effectiveness of an ergonomic keyboard for typists with work related upper extremity disorders: A follow-up study

2010· article· en· W1759260537 on OpenAlexaff
Jacquie Ripat, Ed Giesbrecht, Arthur O. Quanbury, Sarah Kelso

Bibliographic record

VenueWork · 2010
Typearticle
Languageen
FieldPsychology
TopicErgonomics and Musculoskeletal Disorders
Canadian institutionsWinnipeg Regional Health AuthorityUniversity of Manitoba
Fundersnot available
KeywordsHuman factors and ergonomicsPhysical medicine and rehabilitationPhysical therapyMedicineRepeated measures designTypingPoison controlMedical emergencyComputer scienceSpeech recognition

Abstract

fetched live from OpenAlex

OBJECTIVE: To investigate whether long-term use of an ergonomic keyboard was effective in reducing symptom severity and improving functional status for individuals who experience symptoms of work related upper extremity disorders (WRUED). PARTICIPANTS: Twenty-nine symptomatic workers employed by a single company. METHODS: Participants were assessed after using an ergonomic keyboard for an average of 34 months. Symptom severity, clinical signs, functional status, and typing speed were measured and compared with baseline and six-month study data. RESULTS: Repeated-measure analysis identified that participants maintained the improvement realized at the six-month study mark for symptom severity and functional status, and maintained their typing speed and accuracy. CONCLUSIONS: The results of the study suggest that continuous ergonomic keyboard use was effective in maintaining improvements obtained after six months of use. The potential for ergonomic keyboard use in preventing injury in keyboard operators warrants further investigation.

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)0.001
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 score0.053
Threshold uncertainty score0.908

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.008
GPT teacher head0.274
Teacher spread0.267 · 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

Citations7
Published2010
Admission routes1
Has abstractyes

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