Perceived and measured indoor environmental quality in hospitals: closing the gap.

The design of healthcare environments can have an impact on patients' emotions. These emotions can influence their comfort and health, and interlink with adaptation, i.e. the response to restore comfort when discomfort occurs. Adaptation affects energy use. In that context, researchers seek to develop models that predict comfort (MCP) or adaptations of indoor conditions (MAP); or try to understand the roles of the built environment (RBE) in experiences.

In MCP research, discrepancies are observed between predicted and experienced (dis)comfort; in MAP research, between predicted and actual adaptations of indoor conditions. In RBE research the roles of the built environment in experiences are not yet fully understood. More attention is needed for interactions (1) between people and indoor conditions through perceived control and adaptation, and (2) between the different indoor environmental quality (IEQ) factors in experience, as well as for differences (3) between people and (4) between settings.

This research addresses these four points of attention. It focuses on the question: How do hospitalized patients’ experiences of their patient room’s indoor environment relate to measureable values of IEQ parameters (e.g. temperature)? This with the objective to explore whether integrating RBE, MCP, and MAP research enables improving the understanding of the four points of attention described above.

MCP, RBE and MAP research were integrated. This integration occurred through two mixed methods case studies in surgical wards of two Belgian hospitals. The data collection included: interviews with 16 (case 1) and 19 (case 2) patients; self-documentation by eight patients (case 1); sensor measurements of IEQ parameters (mainly noise, light, and indoor air temperature levels) (case 1 and 2); questionnaires with 84 (case 1) and 238 (case 2) patients as well as simulations of the free-running temperature, the total short-wave solar radiation through the windows and the heat demand. During data analysis and interpretation, quantitative and qualitative data were integrated via joint displays, and figures were combined with an explanation based on the interviews. Implications were discussed with engineers, architects and nurses.

Five adaptation strategies were identified in the interactions between patients and indoor conditions. When participants perceive control, they adapt (1) indoor conditions, (2) sensations (e.g. hot or cold) or the environmental information (e.g. heating or incident sunlight), (3) or their position; or (4) they adapt to indoor conditions by choice. In the absence of perceived control (5), the adaptation feels imposed. The first three strategies seem to support both hedonic (i.e. pleasure) and eudaimonic well-being (i.e. a sense of functioning well), the fourth and sometimes the last only eudaimonic well-being. There is a tendency towards more neutral or more preferable sensations and higher satisfactions when participants adapt indoor conditions or have no wish to do so than when they adapt by choice or when adaptation feels imposed. Since differences in experience do not correspond to those noticed in values of IEQ parameters, the strategies seem to influence experience in a psychological way.

More insight was gained into how IEQ factors interact in experience. The overall assessment of the comfort in the room correlates with the assessment of the individual IEQ factors and that of different IEQ factors correlate with each other. Interactions are observed between satisfaction with one IEQ factor and variations in IEQ parameters associated with another IEQ factor or in satisfaction with these IEQ factors. Interactions seem to occur because sensations are experienced simultaneously as well as objects and events.

A better understanding was obtained of how thermal and visual comfort and adaptation differ between patients and settings. Three scenarios were identified: (1) situations in which experienced comfort and adaptation are similar, (2) in which adaptation differs and experienced comfort is similar, or (3) in which experienced comfort differs and indoor conditions are similar. In addition, eleven models of thermostat adaptations in patient rooms were set up and their strengths and weaknesses with respect to three design purposes compared: for energy-sensitive design, for obtaining robust designs, or for attending to the simultaneity of energy use. Which model performs best seems to depend on the application purpose. In general, models that take differences in thermostat adaptations between days, interactions between characteristics related to patients and their setting that can impact on the adaptations, and the stochasticity of these adaptations into account, seem best suited for the three design purposes.

The positive influence on patients’ experience when they adapt indoor conditions suggests to design adaptable building characteristics that align with various competences of patients, and patient room designs that support autonomy. This design strategy is expected to increase comfort while reducing the percentage of time that the heating or lighting are working. The insights can increase designers' understanding of patients’ adaptation strategies and provide researchers with a basis for improving models of comfort and adaptation. The insights from this research can support the design of more comfortable patient rooms, with a reduced gap between experienced and predicted indoor environmental comfort.