Short-Term Effects of Workstation Exercises on Musculoskeletal Discomfort and Postural Changes in Seated Video Display Unit Workers
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: In recent years, a number of exercise programs have been developed for computer operators in order to promote movement and to reduce musculoskeletal discomfort. Tests of the effectiveness of these exercise programs, especially in field trials, are rare. The authors tested the hypothesis that doing regular, short-term (<10 days) exercises while at a workstation would decrease musculoskeletal discomfort and increase in-chair movement (ICM). SUBJECTS: Eleven directory assistance operators (8 female, 3 male) with no recent history of musculoskeletal problems volunteered. METHODS: In-chair movement was measured by tracking the center of pressure at the buttock-chair interface as subjects sat on a pressure-sensitive mat. Musculoskeletal discomfort was rated through the use of the Body Part Discomfort Scale (BPDS) and a body map. We used a revised Dataspan exercise program. Operators were tested for 2 hours, on 2 occasions: before and after doing exercises for 3- to 5-day shifts. During each test, ICM was measured during three 15-minute periods at the start of the test and at the end of hours 1 and 2. Subjects rated musculoskeletal discomfort per body part using the BPDS at 30, 60, and 120 minutes of each test. The effects of exercises on ICM and BPDS ratings were examined with a two-way repeated-measures analysis of variance with day (2) x time (3) designs. RESULTS: When subjects were doing their exercises, ICM was higher at the start and hour 1, and perceived discomfort was lower during each test period (start, hour 1, and hour 2). When not exercising, subjects' musculoskeletal discomfort increased over time and was higher during all test periods. DISCUSSION AND CONCLUSION: Exercises done by video display unit operators while at a workstation resulted in short-term decreases in both musculoskeletal discomfort and postural immobility. These results suggest that workstation exercises may be beneficial.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".