Effective measures to decrease air contaminants through risk and control visualization: a study of the effective use of QR codes to facilitate safety training
2016 (English)In: Safety Science, ISSN 0925-7535, E-ISSN 1879-1042, Vol. 82, 120-128 p.Article in journal (Refereed) Published
Woodworking industries still consists of wood dust problems. Young workers are especially vulnerable to safety risks. To reduce risks, it is important to change attitudes and increase knowledge about safety. Safety training have shown to establish positive attitudes towards safety among employees. The aim of current study is to analyze the effect of QR codes that link to Picture Mix EXposure (PIMEX) videos by analyzing attitudes to this safety training method and safety in student responses. Safety training videos were used in upper secondary school handicraft programs to demonstrate wood dust risks and methods to decrease exposure to wood dust. A preliminary study was conducted to investigate improvement of safety training in two schools in preparation for the main study that investigated a safety training method in three schools. In the preliminary study the PIMEX method was first used in which students were filmed while wood dust exposure was measured and subsequently displayed on a computer screen in real time. Before and after the filming, teachers, students, and researchers together analyzed wood dust risks and effective measures to reduce exposure to them. For the main study, QR codes linked to PIMEX videos were attached at wood processing machines. Subsequent interviews showed that this safety training method enables students in an early stage of their life to learn about risks and safety measures to control wood dust exposure. The new combination of methods can create awareness, change attitudes and motivation among students to work more frequently to reduce wood dust.
Place, publisher, year, edition, pages
2016. Vol. 82, 120-128 p.
PIMEX, QR code, safety attitude, safety training, wood dust, woodworking industry
Research subject Complex Systems – Microdata Analysis
IdentifiersURN: urn:nbn:se:du-20325DOI: 10.1016/j.ssci.2015.09.011ISI: 000366766800012ScopusID: 2-s2.0-84942279591OAI: oai:DiVA.org:du-20325DiVA: diva2:875442