Prolonged sitting in office environments: A scoping review of assessment methods
Bibliographic record
Abstract
BackgroundProlonged sitting in office environments is a major contributor to musculoskeletal disorders (MSDs), representing a growing concern for occupational health and ergonomics.ObjectiveThis scoping review aimed to examine the range of methods used to assess sitting postures among office workers, emphasizing their applications, strengths, and limitations.MethodsA comprehensive search identified 42 studies published between 2000 and December 2023 from an initial pool of 167 articles. Studies were categorized into self-assessment, observational, and instrument-based approaches following PRISMA-ScR guidelines.ResultsSelf-assessment methods were the most common (69.05%), capturing subjective reports of discomfort, followed by observational tools (38.09%) for postural risk evaluation and instrument-based approaches (45.24%) utilizing sensor- and vision-based technologies for objective analysis. Several studies combined two or more methods to improve data validity through cross-validation and to achieve a more comprehensive understanding of posture-related risks.ConclusionsThis review synthesizes current approaches for evaluating sitting postures in office settings and highlights methodological trends, gaps, and opportunities to guide future ergonomic research aimed at reducing MSD risks.
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 | 0.002 | 0.001 |
| 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".