Sara Willems, Dirk Saelens, Ann Heylighen
Languages: English | Pages: 9 pp
Bibliographic info:
41st AIVC/ASHRAE IAQ- 9th TightVent - 7th venticool Conference - Athens, Greece - 4-6 May 2022

Hospitals’ indoor environmental quality (IEQ) impacts on patients’ comfort and well-being. Relationships between IEQ indicators and people’s assessment are often investigated by examining the main IEQ parameters – thermal, visual, and acoustical comfort and indoor air quality – separately. People’s assessment is multi-sensory and balances the positive sensations against the negative. To estimate it, IEQ models aggregate data from sensor measurements and/or surveys, expressing parameters’ relative importance through regression coefficients. Yet, questions arise about the trustworthiness of these models. Comfort and well-being are to some extent socially constructed, and individuals and activities vary. Interactions between IEQ parameters occur, but are not yet fully understood. The wrong parameters might be focused on, and it is unclear how parameters’ satisfaction level is affected by preferences regarding IEQ indicators that are perceived in the same way. Parameters’ relative importance is likely to change continuously, possibly influenced by the level to which they (dis)satisfy. This paper aims to advance the understanding of how methodologies used to estimate patients’ IEQ assessment can be improved based on insights from a pilot case study adopting a mixed-methods approach. At a hospital’s traumatology ward, 84 patients completed a survey. Twelve of them and four others participated in semi-structured interviews about their experience of the indoor environment, while sensors measured IEQ indicators in their room (temperature, relative humidity, illuminance, CO2 and sound level). Based on sensor measurements and/or survey results, participants’ IEQ assessment is estimated in different ways. Semi-structured interviews give insight into how and when IEQ indicators interact and their weight in participants’ multi-sensory assessment. Combining qualitative and quantitative data informs about possible improvements of multi-sensory IEQ models and future methodologies. Multi-sensory IEQ models, which include both quantitative and qualitative variables, will allow to estimate IEQ more accurately.