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.

Industry 4.0 in the contemporary operating context carries important sources of complexity. This context generates both traditional risks and emerging risks that must be managed. The management of these risks includes both industrial risks and occupational risks, since they are heavily interlinked. The human factor can be considered the main link between both types of risks. Thus, understanding risks originating from human errors and organizational weaknesses as causes of accidents and other disruptions in complex systems requires elaborating sophisticated modeling approaches. Therefore, the objective of this paper is to propose an organizational and human performance approach to improve the emerging risk management linked to the complex systems, like as Human‐Machine Interactions (HMI) and Human‐Robot Interaction (HRI). To fulfill this objective, we first introduce the concept of emerging risk linked to human factor. Then, we introduce the concept of emerging risk management in the Industry 4.0 context. Under this complex context, we expose the concept considering the current models of risk management. Finally, we discuss how enhancing human and organizational performance can be achieved through risk management in complex systems linked to Industry 4.0. Therefore, we conclude that while Industry 4.0 brings numerous advantages, it must contend with emerging risks and challenges associated with organizational and human factors. These emerging risks include industrial risks as well as occupational risks. Moreover, the human factor aspect of Industry 4.0 is directly linked to industrial emerging and occupational emerging via context of operations. To cope with these new challenges, it is necessary to develop new approaches. One of such approaches is Complex System Governance. This approach is discussed along with the need for adequate organizational and human performance models dealing with, for example, experience from other domains such as nuclear, space, aviation, and petrochemical.

Besides traditional occupational risks, advanced manufacturing processes (AMP) can generate other risks described by the European Agency for Safety and Health at Work (EU-OSHA) as “new and emerging risks” (NER) to occupational safety and health. Several studies have been carried out by the EU-OSHA in order to identify all these risks. However, the direct use of this set of NER in identification procedures of occupational risks, generally applied in labour processes and particularly in AMP, may result in the identification of traditional occupational risks rather than NER, mainly because they have been defined without following a risk reference model. To solve this problem a risk model has been developed that improves and complements the NER definition of EU-OSHA, from which a second model has been developed to analyze the structure of the considered set of NER. It is observed that with the results obtained, the current descriptions of these NER do not explain their quality of “new and “emerging”

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 ± SD = 54.7 ± 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 ⁻¹ . 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.