Effectiveness of Slip Resistant Footwear in Dairy Industry

Overview

In the dairy industry, same-level falls are a major problem and a well-known challenge. At Arla's dairy in Taulov, where this RCT study is being carried out, reports of risk observations, near incidents, and workplace accidents have increased over the past five years. Accident statistics further show that same-level falls are the most common incidents, with slippery floors and surfaces being by far the main cause of both near incidents and risk observations. Because of this, it is necessary to test different types of safety footwear that, based on laboratory studies, are considered particularly suitable for the working environment in a dairy. it is hypothesized that employees, through subjective questionnaires, will rate one shoe as less slippery than the other. At the same time, it is hypothesized that employees will also subjectively find one shoe more comfortable than the other.

Slipping, tripping, and falling (STF) are the second most common risk factor for serious occupational accidents in Denmark, accounting for 18.9% of the cases. In fact, general fall accidents in 2016 were estimated to cause annual additional costs of 3.9 billion DKK due to lost productivity, and a further 4.8 billion DKK in healthcare and long-term care expenses. Similar numbers are observed in the United States, where STF is likewise reported as the second most common cause of workplace accidents. The primary cause of STF incidents is often insufficient friction between footwear and walking surfaces. In response to this issue, ASTM International in 2021 raised the minimum threshold for certified slip-resistant footwear, making it even more challenging for manufacturers to meet test requirements. Although recent years have brought advances in the understanding of mechanisms leading to STF events-particularly slipping-there is still insufficient research translating this knowledge into practical preventive measures. Data from the Danish Working Environment Authority confirm this gap, showing that reported STF accidents increased between 2016 and 2021. Moreover, the actual number of near incidents is likely even higher, as many are never formally registered. Implementing existing prevention knowledge into effective, practical interventions remains a key challenge. Analysis of gait patterns has been suggested as a way to better understand changes in walking stability, thereby enabling quantification of near-incidents occurrences. This RCT study will, for the first time, combine multiple measurement parameters, including reported falls, near incidents, risk situations, perceived slip resistance, and gait characteristics (e.g., step length, cadence). These outcomes will be measured through both quantitative and qualitative methods. Quantitative gait data will be collected using accelerometers, with two sensors allocated to each participants foot/shoe. This system has previously been used to quantify gait patterns. Qualitative data will be collected through self-reported records. By linking spatiotemporal gait parameters with self-reported accident and near-miss data, this study will provide new insights into the relationship between objective and subjective safety outcomes. In addition, it is crucial to identify potential barriers and challenges experienced both by employees using slip-resistant footwear and by procurement decision-makers responsible for footwear acquisition. To address this, focus group interviews and surveys will be conducted among study participants as well as procurement staff at Arla in Taulov. A power calculation estimated the required sample size at 28 participants, based on an expected α of 0.05, β of 0.20, and an effect size of 0.25. Allowing for an anticipated dropout rate of 20%, the recruitment target is set at 34 participants (17 in each study arm). Considering the number of employees working in slippery zones, it was decided that only a cross-over design will enable to recruit a sufficient number of participants. Employees at Arla's Taulov dairy will be recruited and randomized (1:1) to either start working with one pair of safety shoes while the other half will start with the other pair of safety shoes using a computer-generated minimization sequence, ensuring balance between groups in terms of sex, age, and prior fall history. Quantitative and qualitative data will be presented descriptively. Following a thematic analysis approach, outcomes such as comfort, gait patterns, perceived safety, fall/near-fall experiences, and economic considerations (e.g., purchase costs) will be displayed in a structured format that provides an overview of participants' experiences of the intervention as well as perceived barriers and benefits. To evaluate changes over time, quantitative outcomes will be analyzed using two-way repeated measures ANOVA. Multiple imputation will be used to handle potential missing data, and differences between groups will be further assessed using post-hoc tests.