This cross-sectional study estimated computer vision syndrome (CVS) prevalence and analysed its relationship with video display terminal (VDT) exposure, as well as sociodemographic, refractive, environmental, and ergonomic characteristics in 109 presbyopic VDT workers wearing progressive addition lenses (PALs). Usual spectacles were measured with a lens analyser, and subjective refraction was performed by an optometrist. CVS was measured with the CVS-Q©. VDT exposure was collected. Ergonomic evaluations were conducted in a normal working posture looking at the screen. Air temperature and relative humidity were measured (thermohygrometer), and illumination was measured (luxmeter). Descriptive analysis and differences in CVS prevalence, as a function of the explanatory variables, were performed (chi-square test). Multivariate logistic regression was used to identify factors associated with CVS (OR and 95% CI). The mean age was 54.0 ± 4.8 years, and 43.1% were women. The mean hours of VDT use at work was 6.5 ± 1.3 hours/day. The prevalence of CVS was 74.3%. CVS was significantly associated with women (OR 3.40; 95% CI, 1.12–10.33), non-neutral neck posture (OR 3.27; 95% CI, 1.03–10.41) and altered workplace lighting (OR 3.64; 95% CI, 1.22–10.81). Providing training and information to workers regarding the importance of adequate lighting and ergonomic postures during VDT use is advised to decrease CVS and increase workplace quality of life.

Purpose: To estimate the prevalence of computer vision syndrome (CVS) in presbyopic digital device workers using two ophthalmic progressive lens designs during the working day, and to analyse the association of CVS with sociodemographic, occupational, digital device exposure and refractive factors. Methods: This time series, quasi-experimental design study included 69 presbyopic digital device workers (age range: 46-69 years; mean AE SD = 54.7 AE 5.0). All used desktop computers at their workplace. Progressive addition lenses (PALs) and occupational lenses were used for three months each. CVS was measured with the CVS-Q © questionnaire before intervention (baseline) and at 1 week, 1 month and 3 months after wearing the lenses. A multivariate logistic regression model was used to identify the factors that were associated with an improved CVS-Q © score. Results: 37.7% of the subjects were female and 78.3% were ametropes; 65.2% had advanced presbyopia. 56.2% used digital devices at work >6 h day À1 . The prevalence of CVS at baseline, after wearing PALs for three months and after three months of occupational lens wear was 68.1%, 33.3% and 18.8%, respectively. The mean CVS-Q © score was lower with occupational lenses than with PALs (p = 0.001). 40.6% of the digital device workers improved their CVS-Q © score ≥2 points with the occupational lenses. Ametropes were less likely than emmetropes to improve with occupational lenses (OR = 0.27, p = 0.05). 89.8% of the sample workers were satisfied or very satisfied with the occupational lenses and 71% were similarly satisfied with the PALs. 73.9% chose the occupational lenses as their first choice of lens for digital device use, compared with 17.4% for PALs. Conclusions: Computer vision syndrome is reduced in presbyopic desktop computer workers wearing occupational lenses compared with PALs, especially in emmetropes.

It is important to evaluate the risks in industrial parks and their processes due to the consequences of major accidents and especially the domino effect. Scientific works present a wide possibility of models to deal with these situations. In this work, based on the information extracted from the scientific literature, six groups of risk methodologies are defined, analyzed, and characterized with methods that cover the standards, preventive, probabilistic, traditional, modern, and dynamic evaluation that are applied or could be used in industrial parks. It also tries to achieve the objective of determining which are more appropriate if the possible situations and causes that can produce an accident are taken into account, identifying and evaluating them with characteristics of simultaneity and immediacy, determining the probability of an accident occurring with sufficient advance in time to avoid it under the use of a working operational procedure. There is no definitive methodology, and it is necessary that they complement each other, but considering the proposed objective, the integrated application of traditional methodologies together with the management of safety barriers, the dynamic evaluation of risks, and the inclusion of machine learning systems could fulfill the proposed objective.