Ocular morbidity and utilisation of protective eyewear among carpenters in Mushin local government, Lagos, Nigeria
Bibliographic record
Abstract
CONTEXT: Proper use of protective eyewear (PEW) is important in the prevention of occupational eye injury. AIM: The aim of this study was to determine the ocular morbidity and utilisation of PEW among carpenters in Mushin Local Government, Lagos, with a view to promoting ocular health and safety in the workplace. SUBJECT AND METHODS: This was a cross-sectional study of one hundred and fourteen (114) carpenters that were enrolled into the study. Interviewer-administered questionnaires were used to collect information on socio-demographics, work-related ocular history, awareness and utilisation of, as well as barriers to utilisation of PEW. Ophthalmic examination was done. In-depth interviews were also carried out to probe the barriers to utilisation of PEW. Quantitative responses were analysed using the IBM SPSS software, and content data analysis was performed for qualitative responses. RESULTS: The prevalence of reported work-related eye injury and complaints were 30.7% and 32.5%, respectively. The prevalence of ocular morbidity among the respondents was 74.6%. Seventy-seven respondents (67.5%) were aware of PEW; only 21.1% owned PEW, whereas the utilisation level was 26.3%. In-depth interviews revealed ignorance, forgetfulness, and unfamiliarity as the key barriers to PEW use. The odds of using PEW were about three-fold with previous eye injury at work and history of eye complaint. CONCLUSIONS: This study demonstrates a significant prevalence of ocular morbidity and poor utilisation of PEW among carpenters in Mushin, Lagos. There was a significant relationship between previous eye injury or complaint and PEW use. Thus, there is a need to create awareness among carpenters and develop occupational safety policies to improve the use of PEW.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".