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Record W2024454748 · doi:10.1371/journal.pone.0071891

An Ounce of Discretion Is Worth a Pound of Wit — Ergonomics Is a Healthy Choice

2013· article· en· W2024454748 on OpenAlexaboutno aff
Rehana Rehman, Rakhshaan Khan, Ambreen Surti, Hira Khan

Bibliographic record

VenuePLoS ONE · 2013
Typearticle
Languageen
FieldPsychology
TopicErgonomics and Musculoskeletal Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsChristian ministryMedicineOccupational safety and healthPound (networking)Fluid ounce (US)Back painHuman factors and ergonomicsDiscretionLow back painPhysical therapyDemographyGerontologyPoison controlEnvironmental healthAlternative medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: The objective of the study was to identify the occurrence and outcome of low back ache amongst computer users and their relation to age, gender, occupation and duration of computer use. MATERIALS AND METHODS: A self reported questionnaire tailored from Occupational Health and Safety Act of the Ministry of Labor, Ontario, Canada was used. RESULTS: 416 participants 55.5% males and 45% females using computers for a minimum of five years with age range 22 to 59 years belonged to different occupational groups. Consecutive hours of computer work was found to be associated with work related backache or discomfort in 27.4% (n = 114) participants (16.1% male, 11.3% female). Frequent short breaks improved backache (p value <0.001) in 93 (22.4%) participants (13.2% male, 9.2% female). No significant relation was observed with the duration of computer usage or usage per day; between the two genders or occupational groups. Backache had no significance within age groups. CONCLUSION: Our study identifies the occurrence of low back pain among those who are using computer for consecutive hours without breaks and the results suggest the need to create health awareness especially use of short breaks to minimize the risk and occurrence of low back pain. The result of this study can also be used to improve ergonomic design and standards.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.434
Threshold uncertainty score0.999

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)0.0020.000

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 head0.039
GPT teacher head0.289
Teacher spread0.250 · 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

Citations14
Published2013
Admission routes1
Has abstractyes

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Same venuePLoS ONESame topicErgonomics and Musculoskeletal DisordersFrench-language works237,207