Musculoskeletal disorders (MSDs) have been identified as a predisposing factor for lesser productivity and are considered to be a major occupational health problem contributing significantly to absenteeism, disability and loss of productivity. Computer users may develop musculoskeletal disorders due to the forces applied, muscle use, posture and wrist velocity and acceleration exposures during computer use. Work-related musculoskeletal disorders (WMSDs) in computer users cause substantial worker discomfort, disability and loss of productivity. The aim of this study is to review systematically the relevant literature on applicable posture analysis methods to computer workers. A bibliographic survey based on PRISMA statement methodology was performed. A review on different approaches for computer workers posture was accomplished and noted that the simultaneous utilization of the different methods allows achieving better posture analysis, compared to situations when each one of them was used individually.
Introduction: Many occupations are characterized by sedentary behavior (SB) and lack of physical activity (PA). There is growing evidence that prolonged sitting is associated with multiple health risks, including musculoskeletal disorders, biomarkers of increased cardiovascular diseases, some forms of cancer. There is an increasing interest in changing the work environment by implementing various interventions to reduce barriers and promote physical activity. The aim of this short review is to identify factors that affected workers' SB and/or PA to design appropriate interventions. Methodology The search was performed based on PRISMA statement methodology and was conducted in Scopus for articles and reviews published in scientific journals from 2010 until 2019 in English, using a set of root keywords as "sedentary work," "physical activity" and "effectiveness intervention". Results and discussion the review included 12 studies describing effective factors on PA in three categories: organizational factor, individual factor, and social factor. The main organizational factors found were: supportive workplace policies and resources, time for involvement in intervention, paying for activity, management support, work environment factors, and job type (passive jobs, and high-strain jobs). Interpersonal factors, knowledge include (educational level and information about physical activity guidelines) and some sociodemographic factors as individual factors associated with the physical work activity. Furthermore, social factors like social support and social norm have a significant effect on willing to do physical activity in workers. Some studies used "behavior change techniques" to find effective factors on physical activity for identifying the most appropriate interventions. Conclusion: Current evidence demonstrates that some individual, organizational and social factors influence work physical activity; therefore, they need to be considered in each population specifically, before choosing the intervention type. It can contribute to the increasing effectiveness of interventions intended to improve physical activity. Future research in this area should consider the association of various factors identified to enhance the effectiveness of interventions.
The level of contractor's Health, Safety, and Environment (HSE) is a major concern in outsourcing of the works for large organizations. Contractors with acceptable HSE system and their appropriate performance in this area not only have a considerable impact on employer HSE status but also reduce the cost of outsourcing projects. Moreover, since a large number of contractors HSE activities and their acceptable HSE performance during the contract have directly related to their initial HSE status in pre-contract phase, there seems to be a substantial gap in the study of HSE criteria before inviting contractors to a tender. Therefore, it is essential to determine the level of contract in the pre-contract phase and consequently consider different HSE requirements for each level. The main objective of the present study is to develop an index to evaluate the level of contract based on HSE criteria to reduce the project costs in the pre-contract phase. In this study, by investigating the classification procedure of the contracts available in reliable international manuals and models, 6 main criteria were selected including "contract operational risk level", "length of contract", "number of the contractor workforce", "interference in activities of the contractor and employer", "presence of subcontractors", and "contract cost". Also, an index, called "contract separation" was proposed by weighting the criteria based on four sub-criteria characteristics. Then, by preparing a questionnaire and applying the experts' opinion, the final weight of the criteria was specified for all the contracts of Tehran Oil Refinery Company were divided into four levels, namely (1) advanced, (2) moderate, (3) basic, and (4) exempted from the initial HSE assessment. Results of the study showed that the operational risk level had the highest impact percentage on determining the level of the contract compared with other criteria. Also, the cost of the contract had the lowest weight. Although it is one of the most effective criteria in the contract classification, it cannot by itself represent the magnitude of the contract from the HSE perspective and its impact must be considered along with other criteria associated with HSE to determine the contract level.Proposing an index to determine the contract level at the pre-contract stage from the viewpoint of Health, Safety, and Environment (HSE) Mapatar et al.
Industry 4.0 has shaped the way people look at the world and interact with it, especially concerning the work environment with respect to occupational safety and health (OSH). Machine learning (ML), as a branch of Artificial Intelligence (AI), can be effectively used to create expert systems to exhibit intelligent behavior to provide solutions to complicated problems and finally process massive data. Therefore, a study is proposed to provide the best methodological practice in the light of ML. Alongside the review of previous investigations, the following research aims to determine the ML approaches appropriate to OSH issues. In other words, highlighting specific ML methodologies, which have been employed successfully in others areas. Bearing this objective in mind, one can identify an appropriate ML technique to solve a problem in the OSH domain. Accordingly, several questions were designed to conduct the research. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) extension for Protocols and Systematic Reviews were used to draw the research outline. The chosen databases were SCOPUS, PubMed, Science Direct, Inspect, and Web of Science. A set of keywords related to the topic were defined, and both exclusion and inclusion criteria were determined. All of the eligible papers will be analyzed, and the extracted information will be included in an Excel form sheet. The results will be presented in a narrative-based form. Additionally, all tables summarizing the most important findings will be offered.
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