Evaluation of the efficacy of a virtual reality-based safety training and human factors training method: study protocol for a randomised-controlled trial.

BACKGROUND: The construction industry has a high risk of occupational accidents and injuries. More randomised controlled trials are needed to identify effective techniques for improving the occupational safety of construction sector workers. New technologies such as virtual reality (VR) offer the potential to develop engaging learning tools for safety training. Although the number of VR applications in occupational safety training is increasing, only a few studies have evaluated the learning outcomes of VR safety training. Furthermore, previous studies indicate that learning to recognise human factors at work has positive outcomes for safety skills. However, there is lack of knowledge regarding the efficacy of human factors-related training in the construction industry. OBJECTIVE: To evaluate the efficacy and the implementation process of a VR-based safety training and a human factors-related safety training. METHODS: In Finland, 8 study organisations and approximately 130 construction sector workers will participate in a randomised controlled trial. The study participants will be randomly assigned to one of four intervention arms: (1) immersive VR safety training alone, (2) lecture-based safety training alone, (3) combined immersive VR safety training and HF Tool training or (4) combined lecture-based safety training and HF Tool training. We will test the efficacy of the safety training processes in these four arms. Randomisation of study participants is stratified by work experience. Baseline assessment will take place before randomisation. The short-term follow-up measurements of all study participants will be conducted immediately after the VR safety training and lecture-based safety training. The study participants will complete second measurements immediately after the HF Tool training approximately 1 month after previous safety training. The second measurement of the intervention arms 1 and 2 study participants will be conducted during the same week as that of the intervention arms 3 and 4 participants, who will not take part in the HF Tool training. Finally, semistructured individual interviews will be conducted to evaluate the learning process. OUTCOME MEASURES: Outcome measures include safety knowledge, safety locus of control, safety self-efficacy, perceived control over safety issues, safety-related outcome expectancies, safety motivation and safety performance. DISCUSSION: Study results will provide knowledge on the efficacy of VR safety training and human factors-related safety training. Furthermore, study provides knowledge on pedagogical techniques that can be used to guide future intervention plans and development. TRIAL REGISTRATION NUMBER: ISRCTN55183871.

Managing Quartz Exposure in Apartment Building and Infrastructure Construction Work Tasks.

The present report describes exposure to respirable silica and dust in the construction industry, as well as means to manage them. The average exposure in studied work tasks (n = 148) amounted to 64% of the Finnish OEL value of 0.05 mg/m3. While 10% of exposure estimates exceeded the OEL, the 60% percentile was well below 10% of the OEL, as was the median exposure. In other words, exposure was low in more than half of the tasks. Work tasks where exposure was low included construction cleaning, work management, installation of concrete elements, rebar laying, driving work machines equipped with cabin air intake filtration, and landscaping, in addition to some road construction tasks. Excessive exposure (>OEL) was related to not using respiratory protection at all or not using it for long enough after the dusty activity ceased. Excessive exposures were found in sandblasting, dismantling facade elements, diamond drilling, drilling hollow-core slabs, drilling with a drilling rig, priming of explosives, tiling, use of cabinless earthmoving machines, and jackhammering, regardless of whether the hammering took place in an underpressurized compartment or not. Even in these tasks, it was possible to perform the work safely, following good dust prevention measures and, when necessary, using respiratory protection suitable for the job. Furthermore, in all tasks with generally low exposure, one could be significantly exposed through the general air or by making poor choices in terms of dust control.

Finding statistically significant high accident counts in exploration of occupational accident data.

INTRODUCTION: Finnish companies are legally required to insure their employees against occupational accidents. Insurance companies are then required to submit information about occupational accidents to the Finnish Workers' Compensation Center (TVK), which then publishes occupational accident statistics in Finland together with Statistics Finland. Our objective is to detect silent signals, by which we mean patterns in the data such as increased occupational accident frequencies for which there is initially only weak evidence, making their detection challenging. Detecting such patterns as early as possible is important, since there is often a cost associated with both reacting and not reacting: not reacting when an increased accident frequency is noted may lead to further accidents that could have been prevented. METHOD: In this work we use methods that allow us to detect silent signals in data sets and apply these methods in the analysis of real-world data sets related to important societal questions such as occupational accidents (using the national occupational accidents database). RESULTS: The traditional approach to determining whether an effect is random is statistical significance testing. Here we formulate the described exploration workflow of contingency tables into a principled statistical testing framework that allows the user to query the significance of high accident frequencies. CONCLUSIONS: Our results show that we can use our iterative workflow to explore contingency tables and provide statistical guarantees for the observed frequencies. PRACTICAL APPLICATIONS: Our method is useful in finding useful information from contingency tables constructed from accident databases, with statistical guarantees, even when we do not have a clear a priori hypothesis to test.

Implementing and evaluating novel safety training methods for construction sector workers: Results of a randomized controlled trial.

INTRODUCTION: The construction industry is regarded as one of the most unsafe occupational fields worldwide. Despite general agreement that safety training is an important factor in preventing accidents in the construction sector, more studies are needed to identify effective training methods. To address the current research gap, this study evaluated the impact of novel, participatory safety training methods on construction workers' safety competencies. Specifically, we assessed the efficacy of an immersive virtual reality (VR)-based safety training program and a participatory human factors safety training program (HFST) in construction industry workplaces. METHOD: In 2019, 119 construction sector workers from eight workplaces participated in a randomized controlled trial conducted in Finland. All the study participants were assessed using questionnaires at baseline, immediately after the intervention and at one-month follow-up. We applied generalized linear mixed modeling for statistical analysis. RESULTS: Compared to lecture-based safety training, VR-based safety training showed a stronger impact on safety motivation, self-efficacy and safety-related outcome expectancies. In addition, the construction sector workers who participated in the VR-based safety training showed a greater increase in self-reported safety performance at one-month follow-up. Contrary to our study hypotheses, we found no significant differences between the study outcomes in terms of study participants in the HFST training condition and the comparison condition without HFST training. CONCLUSION: Our study indicates that VR technology as a safety training tool has potential to increase safety competencies and foster motivational change in terms of the safety performance of construction sector workers. In the future, the efficacy of participatory human factors safety training should be studied further using a version that targets both managerial and employee levels and is implemented in a longer format. PRACTICAL IMPLICATIONS: Safety training in virtual reality provides a promising alternative to passive learning methods. Its motivating effect complements other safety training activities.