The effects of COVID-19 related shutdowns on perceived lifestyle and prevalence of musculoskeletal discomfort
Bibliographic record
Abstract
BACKGROUND: COVID-19 caused a transition to work-from-home conditions, closures of recreation facilities and cancelation of social events. OBJECTIVE: This study sought to characterize and quantify the impact COVID-19 related shutdowns had on perceptions of health and wellbeing, musculoskeletal discomfort, and physical characteristics of workstation set-up in full time workers who transitioned to working from home. METHODS: 297 participants from 8 countries completed a retrospective pre/post survey design that assessed outcomes prior to COVID-19 shutdowns and when each participant was experiencing peak pandemic-related restrictions. There were 3 categories including, health and wellbeing, musculoskeletal discomfort, and workplace ergonomics. RESULTS: General discomfort on a scale from 1 to 100 increased from 31.4 pre to 39.9 during COVID-19. Notable areas increasing in severity of discomfort from pre to during included the neck (41.8 to 47.7), upper back (36.3 to 41.3) and right wrist (38.7 to 43.5). The percentage of the population experiencing discomfort increased from pre to during in the low back (41.5% to 55.2%), upper back (28.7% to 40.9%), neck (45.5% to 60.9%) and right wrist (16.1% to 23.7%). CONCLUSION: There were three distinct groups for physical activity one group including, one maintaining and one that decreased, which did not have an impact on perceived general discomfort. There was a significant decrease in usage of a desk and adjustable chair and an increase in laptop use. Working from home in some capacity will likely be a more common occurrence which will require further ergonomic assessments and considerations to keep a healthy workforce.
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 | 0.000 | 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".