In Intensive Care Units (ICUs), excessive non-human and human sounds cause behavioural and psychological problems in patients and reduce professionals' job satisfaction and performance. Rather than relying solely on quantitative (psycho/acoustic) metrics, their combination with qualitative data (soundscape descriptors) provides the most reliable method to assess this context, as it considers the perceived environment. Moreover, sound event detection (SED) and classification techniques enhance the reliability of the assessment model. However, they also raise ethical concerns regarding vulnerable patients' rights. Therefore, the development of audio data ethics is essential for designing research strategies that strike a balance between patients' rights and research effectiveness. This study aims to define audio data ethics based on expert interviews and outline the basics of a tool to identify and assess risks for mitigation strategies. Results indicate that quantitative and qualitative data present minimal ethical risks, but audio recording for event identification poses significant ones. Managing these risks helps prevent patient re-identification, discrimination, and mistrust in research. The results will be validated in an ICU.

Intensive care units (ICUs) are the ultimate socio-technological environments known for their loud sound levels. Alarms, noise produced by patient support devices, loud conversations, physical interactions with tools and the environment in general contribute collectively to a sound quality generally perceived as low. This paper reports the results from a study conducted inside the old and new ICUs at Erasmus Medical Center, Rotterdam, the Netherlands. Sound level measurements have been collected continuously for three weeks in several matching rooms inside the old and new ICUs at full operational level at a one-year distance from one another. The results support the idea that changes in architectural layout, procedures, and culture have contributed to a significant decrease of the measured sound levels across all daily shifts, both inside patient rooms and in the nurse stations. We further discuss the results in light of a series of contextual considerations that emerged from interviews with healthcare providers (i.e., nurses and intensivists) who actively worked in both the old and the new ICU.

The hospital soundscape is known for high noise levels and a perception of chaos, leading to concerns about its impact on patients, families, professionals, and other hospital staff. This study investigates the relationship between sound, Annoyance, and sleep quality in a multi-patient neurology ward. A mixed-methods approach was employed. Interviews were conducted with medical staff (n = 7) to understand their experiences with sound. Questionnaires and sleep tracking devices (n = 20) assessed patient sleep quality and Annoyance caused by sound events. In addition, listeners (n = 28) annotated 429 nighttime audio recordings to identify sound sources and rate Annoyance level, which we considered the key emotional descriptor for patients. Over 9,200 sound events were analysed. While snoring, a patient-generated sound dominated the nighttime soundscape and was highly rated for Annoyance, and staff-generated sounds such as speech and footsteps were found to contribute more to accumulated Annoyance due to their extended duration. This study suggests that patient sleep quality can be improved by focusing on design interventions that reduce the impact of specific sounds. These might include raising awareness among staff about activities that might produce annoying sounds and implementing strategies to mitigate their disruptive effects.