Managing acoustic noise within MRI: A qualitative interview study among Swedish radiographers.

INTRODUCTION: Acoustic noise from magnetic resonance imaging (MRI) can cause hearing loss and needs to be mitigated to ensure the safety of patients and personnel. Capturing MR personnel's insights is crucial for guiding the development and future applications of noise-reduction technology. This study aimed to explore how MR radiographers manage acoustic noise in clinical MR settings. METHODS: Using a qualitative design, we conducted semi-structured individual interviews with fifteen MR radiographers from fifteen hospitals around Sweden. We focused on the clinical implications of participants' noise management, using an interpretive description approach. We also identified sociotechnical interactions between People, Environment, Tools, and Tasks (PETT) by adopting a Human Factors/Ergonomics framework. Interview data were analyzed inductively with thematic analysis (Braun and Clarke). RESULTS: The analysis generated three main themes regarding MR radiographers' noise management: (I) Navigating Occupational Noise: Risk Management and Adaptation; (II) Protecting the Patient and Serving the Exam, and (III) Establishing a Safe Healthcare Environment with Organizational Support. CONCLUSION: This study offers insights into radiographers' experiences of managing acoustic noise within MRI, and the associated challenges. Radiographers have adopted multiple strategies to protect patients and themselves from adverse noise-related effects. However, they require tools and support to manage this effectively, suggesting a need for organizations to adopt more proactive, holistic approaches to safety initiatives. IMPLICATIONS FOR PRACTICE: The radiographers stressed the importance of a soundproofed work environment to minimize occupational adverse health effects and preserve work performance. They acknowledge noise as a common contributor to patient distress and discomfort. Providing options like earplugs, headphones, mold putty, software-optimized "quiet" sequences, and patient information were important tools. Fostering a safety culture requires proactive safety efforts and support from colleagues and management.

A linear programming model to optimize diets in environmental policy scenarios.

The objective was to develop a linear programming model to formulate diets for dairy cattle when environmental policies are present and to examine effects of these policies on diet formulation and dairy cattle nitrogen and mineral excretions as well as methane emissions. The model was developed as a minimum cost diet model. Two types of environmental policies were examined: a tax and a constraint on methane emissions. A tax was incorporated to simulate a greenhouse gas emissions tax policy, and prices of carbon credits in the current carbon markets were attributed to the methane production variable. Three independent runs were made, using carbon dioxide equivalent prices of $5, $17, and $250/t. A constraint was incorporated into the model to simulate the second type of environmental policy, reducing methane emissions by predetermined amounts. The linear programming formulation of this second alternative enabled the calculation of marginal costs of reducing methane emissions. Methane emission and manure production by dairy cows were calculated according to published equations, and nitrogen and mineral excretions were calculated by mass conservation laws. Results were compared with respect to the values generated by a base least-cost model. Current prices of the carbon credit market did not appear onerous enough to have a substantive incentive effect in reducing methane emissions and altering diet costs of our hypothetical dairy herd. However, when emissions of methane were assumed to be reduced by 5, 10, and 13.5% from the base model, total diet costs increased by 5, 19.1, and 48.5%, respectively. Either these increased costs would be passed onto the consumer or dairy producers would go out of business. Nitrogen and potassium excretions were increased by 16.5 and 16.7% with a 13.5% reduction in methane emissions from the base model. Imposing methane restrictions would further increase the demand for grains and other human-edible crops, which is not a progressive solution for an industry trying to be sustainable. However, these results might depend on the constraints and inputs used in our model (e.g., feed prices), and more extensive analyses are required before they are used in policy development. The model structure was able to incorporate effects of environmental policies in diet formulation and it can assist dairy producers in meeting limits set by these policies. The model can also assist policy makers examining the effects of policies on the dairy production system.