Frequency of postural changes during sitting whilst using a desktop computer – exploring an analytical methodology
Bibliographic record
Abstract
BACKGROUND: Dynamic movement whilst sitting is advocated as a way to reduce musculoskeletal symptoms from seated activities. Conventionally, in ergonomics research, only a 'snapshot' of static sitting posture is captured, which does not provide information on the number or type of movements over a period of time. A novel approach to analyse the number of postural changes whist sitting was employed in order to describe the sitting behaviour of adolescents whilst undertaking computing activities. METHODS: A repeated-measures observational study was conducted. A total of 12 high school students were randomly selected from a conveniently selected school. Fifteen minutes of 3D posture measurements were recorded to determine the number of postural changes whilst using computers. RESULTS: Data of 11 students were able to be analysed. Large intra-subject variation of the median and IQR was observed, indicating frequent postural changes whilst sitting. CONCLUSION: Better understanding of usual dynamic postural movements whilst sitting will provide new insights into causes of musculoskeletal symptoms experienced by computer users.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".