Calidad de vida y productividad en trabajadores présbitas no corregidos: revisión sistemática
Bibliographic record
Abstract
Presbyopia is a normal degenerative process associated with age that affects the visual system making it difficult to sharply focus images in near vision, aspect that can generate a decrease in the productivity of workers who need to perform tasks closely and consequently affect their quality of life. This research aims to synthesize scientific evidence on how uncorrected presbyopia decreases productivity and quality of life of workers over 40. The methodology used was based on a bibliographic search and the report was made meeting the criteria of the prism 2020 declaration; subsequently, the documents were evaluated with the tools of Newcastle Ottawa and RoB 2. Results: 94 % of presbyopia cases have not been corrected globally and presbyopia is expected to increase to about 2.1 billion by 2030. The highest prevalence of presbyopia reported was greater than 70 %, which varied between regions and age groups in participants older than 35 years. Conclusions: Presbyopia generates physiological changes, difficulty in the ability to relate activities such as reading and writing, and affects the quality of life, since it represents a psychosocial risk for people. The estimated productivity loss due to uncorrected presbyopia is estimated at $25 billion per year. The population affected by this problem is mainly women from rural areas.
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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 | 0.027 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.017 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".