Impact of Dry Eye Symptoms and Daily Activities in a Modern Office
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
PURPOSE: Modern offices and the use of electronic devices are increasing factors in work-related eye symptoms. However, symptoms of eye fatigue or dry eye sensation can be mixed and confusing. This study surveys the eye symptoms reported during a working day at modern offices to investigate the possible inhibition on daily work activities. METHODS: Two online digital surveys were sent to three different work locations, by direct e-mail. Survey A consisted of 14 questions that investigated eye symptoms experienced during daily activities at work and the impact on daily activities. Survey B consisted of four general questions, the Dutch Ocular Surface Disease Index, the Work Productivity and Activity Index, and the Illness Perception Questionnaire. RESULTS: A total of 505 participants completed survey A, and 213 completed survey B. The participants reported that a high proportion of their day was spent working on a computer (60%). The majority experienced an air draft (79.1%) and had no adjustable light (81.5%) at their workspace. Dry eye-related symptoms were reported at a significantly higher frequency at work than at home (P < .001). Up to 70% experienced some inhibition of daily activity at work due to eye symptoms, with more than 5% experiencing symptoms most or all of the time. Indoor environment, work environment, and general health were perceived as the main reasons for developing dry eye. Compared with males, females showed a statistically significant higher Ocular Surface Disease Index score (P < .001) and experienced more inhibition and adverse effects on daily life and work productivity. CONCLUSIONS: This investigation shows that dry eye symptoms have a negative impact on daily activities at work. These findings suggest that multidisciplinary understanding of the negative impact of dry eye by a range of specialists will be of help in managing work-related dry eye.
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.
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 | 0.001 |
| 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 it