Occupants’ Perceptions of Comfort, Control, and Adaptation in Colonial Revival Style Residences
School of Architecture, University of Utah, Salt Lake City, UT 84112, USA
Sustainability 2023, 15(3), 1932; https://doi.org/10.3390/su15031932
Submission received: 6 November 2022
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Revised: 5 January 2023
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Accepted: 16 January 2023
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Published: 19 January 2023
(This article belongs to the Special Issue Environmental Assessment of Occupied Buildings Facing Future Challenges)
Abstract
:This study examines occupants’ perceptions of comfort, control, and adaptation in Colonial Revival style residences in the “Building America Climate” cold region of the United States. The research considered these buildings due to their attractiveness and availability in the study area. The research intends to address the following question—Do occupants’ perceptions of comfort significantly impact their perceptions of control and adaptation within the buildings? This study utilized indoor monitoring of variables in the summer, thermal comfort surveys (110 respondents), walk-throughs, observations, and informal interviews to collect data for analysis. The residents that perceived higher air movement and humidity also use control more often and are more often satisfied with the level of control. The differences between the mean neutral temperatures were within the range of 2.2 °C. On a seven-point scale, the mean thermal sensation votes (TSV) and thermal comfort (TC) were 3.25 and 5.05, respectively. The study revealed higher perceptions of the thermal environment among residents who spent longer hours in the buildings than those that spent fewer hours within the residences. The research implies that while there are limited options for control, the residents who spent longer hours in the buildings perceived themselves to be more comfortable and to be able to adapt better using available adaptive measures than those who spent fewer hours in the residences. The study notes that, as people migrate from one thermal environment to another, their adaptation level may change depending on certain factors, including the adaptive measures available to them. The research recommends the integration of transitional smart devices (such as remotely controlled thermostats, etc.), including control for the residents who spent fewer hours in those buildings.
1. Introduction
The paper investigates and discusses occupants’ perceptions of thermal comfort, control, and adaptation in selected Colonial Revival style residences in the cold region of the United States. The current study considers this category of residential buildings due to their attractiveness and availability within the study area [1,2]. The main goal of the research is to investigate whether the residents’ perceptions of thermal comfort significantly influence their perceptions of control and adaptation within the buildings in warm season. To the best of the author’s knowledge, this is the first study that examines people’s perceptions of thermal comfort, control, and adaptation concurrently in multi-family Colonial Revival residences.
Existing research has reviewed occupants’ perceptions and preferences in different thermal environments [3,4,5,6,7,8,9]. Li et al. [10] examined people’s perceptions and preferences in naturally ventilated buildings in China. The study [10] established a relationship between humidity sensation and preference. Li et al. [10] noted that the humidity effect on thermal comfort should be considered at low temperatures and elevated temperatures. Similarly, Yao et al. [11] conducted a long-term field investigation in free-running buildings and explained that thermal conditions within the thermal environment in different seasons are severe. The authors [11] suggest that both behavioral and psychological adaptations play a critical role in adjusting to the thermal environment.
In a study performed in selected residential buildings of a highly altitudinal Himalayan region in the eastern part of India, it was reported that female residents preferred lesser clothing insulation than male residents [12]. The study [12] also mentioned that female residents have lower perceptions of thermal discomfort and sensation with higher comfort temperatures than male subjects. Likewise, Luo et al. [13] assessed perceptions of indoor climate, migration, and comfort expectations in buildings. Their research notes that it is much faster for people to accept a neutral indoor climate than to reduce their expectation and adjust to the thermal environment.
Both Adekunle and Nikolopoulou [9] and Luo et al. [13] explained that occupants’ understanding of thermal comfort could change depending on their experience of the thermal environment. Additionally, existing research noted among other factors [9,14,15,16,17,18,19,20,21], age and gender of occupants [12,15], ownership status [9], hours of occupation per day [9,16], aesthetics [17,18], building type, size, design [17], elements [18], control features [9,18], building location [17,18,19], income level [20,21], effectiveness of control [9,22], length of occupancy [9], proximity to public amenities [23], subsidized tenancy [24], seasonal change [5,11,25,26,27,28], daylighting [29], climatic region [11,21,28], materials used for the construction of buildings [9,12,21,30], and social status [21,31] could also influence people’s perception of comfort and adaptation, as well as their experiences within the thermal environment.
Moreover, past investigations have evaluated occupants’ perceptions of thermal comfort using various rating scales [1,11,12,13], while indoor monitoring of environmental variables was conducted concurrently in those buildings [1,2,11,12,13]. Observations [32], formal [33] and informal interviews [33,34], and walk-throughs [32] have also been used in conjunction with thermal comfort surveys to understand people’s perception of comfort, environmental control, and adaptation within the thermal environment [32,33,34]. Additionally, existing research [9,32,33,34] has utilized these techniques to capture more data for analysis. In connection with field investigations of thermal adaptation in the built environment [14], Brager and de Dear [3,6] and Fountain et al. [35] have highlighted the notion of expectation in their research of thermal comfort as a psychological adapting strategy. Certain investigations [3,6,35] have outlined why occupants are more tolerant of the broader ranges of thermal conditions in free-running building environments than non-naturally ventilated environments.
In a related study on how people perceive thermal conditions within the environment, Fanger and Toftum [36] proposed “expectation” as the seventh variable in their predicted mean vote (PMV) model to expand the PMV function in naturally ventilated buildings in warm regions. The proposition regarding the “expectation” as the seventh variable in the PMV model discussed by Fanger and Toftum [36], also aligns with the concept of “thermal comfort expectation”, which was first proposed by McInytre [37]. Even though past investigations have focused on the assessment of the concept of expectation [36,37], existing research has also referred to the possible effects of this concept [38,39,40,41,42,43].
To mention a few studies that have referred to the possible effects of the concept of “thermal comfort expectation”, an investigation conducted by Nicol and Humphreys [38] discussed comfort temperatures within the indoor thermal environments of office buildings between the 1970s and 1990s. The authors [38] noted that comfortable temperatures were more closely grouped in the 1990s than they were in the 1970s. Amin et al. [39] assessed the impact of users’ thermal histories on the use of controls and the preferences of indoor temperature in selected educational facilities. Their research outcomes revealed that the mean indoor temperature of the thermal environment in warm regions exceeds the value obtained for cold regions by 2.3 °C [39]. Equally, the occupants in the severe cold region are likely to adjust to the indoor temperatures steadily even if the thermal environment gets overheated [42].
On thermal adaptation in the built environment [3], existing research mentions a design concept that involves two major approaches [44]. Firstly, thermal zoning permits the short-term use of spaces based on comfort needs. The first technique requires the careful utilization of energy needed for heating and cooling the thermal environment [45]. The second technique requires people to adjust their behavior and habits [44]. As previously discussed, occupants will adjust their patterns of occupation [9] and expectations of comfort [38,39,40,41,42,43] based on seasonal changes [5,11,25,26,27,28]. They will also be involved in social and cultural traditions that enhance the thermal quality of the environment [44]. Behavioral patterns and actions, including dining, adjusting clothing insulation, attending meetings, opening and closing their windows, and other activities, tend to be adjusted and limited based on the ease of use of energy sources for cooling and heating.
Although the literature review in this study pinpoints the concept of thermal comfort expectations, existing research has not fully captured the impacts of the concept, which is a complex combined effect of different parameters, including difference in culture, climatic region, building type, income level, etc. These observations further confirm that additional investigations should examine and generate direct empirical sets of data to identify fundamental concepts and dynamics of comfort expectations in different thermal environments. As such, the current study focuses on users’ perceptions of comfort, control, and adaptation in the selected buildings in the study location.
The Novelty of the Study and Research Objectives
Based on the papers reviewed in the current study and existing research in field studies of thermal comfort (FSTC) across the globe, the current study is the first reported work to evaluate occupants’ perceptions of comfort, control, and adaptation at the same time in multi-family Colonial Revival residences in the study area. In terms of the motivation for the research, the current study intends to contribute to on-going investigations on thermal comfort and adaptation in residential buildings, which still require further research. The study aims to address the following research question—Do residents’ perceptions of thermal comfort significantly influence their perceptions of control and adaptation within the buildings in summertime?
The current research revisited two previous related studies on multi-family Colonial Revival style buildings [1,2]. The first study focused on energy assessments [1] and the second examined summertime overheating and heat indices [2] in a case study of buildings. The current study does not replicate the findings of the two previous studies. This study fully captures the findings of the thermal comfort surveys, observations, walkthroughs, and informal interviews which were not covered in the previous papers. The objectives of the current research include:
- (a)
- An examination of occupants’ perceptions of comfort in the selected residences using various research techniques to collect data for analysis.
- (b)
- An investigation as to whether people’s perceptions of thermal comfort significantly impact their perceptions of control and adaptation within the buildings in summer.
2. Materials and Methods
The section is divided into four subsections. The first subsection discusses the study area. The second subsection describes the buildings of the case study. The third subsection discusses the field investigations and outlines the research techniques utilized to collect data for the research. The subsection also explains the data protocol adopted in this research. The last subsection presents data analysis and highlights the strategies employed for the analysis.
2.1. Case Study Location
The subtype climate of the area (43.2994° N, 74.2179° W) is defined by the Koppen climate classification (Dfa) and is characterized by significant seasonal temperature variations [46,47]. The study area is designated as “humid”, though this does not imply that the humidity levels are certain to be high at all times. In the warm season, daily average temperatures vary from 20.0 °C to 23.0 °C during the day, while in the cold period, daily average temperatures range from −1.0 °C to 1.0 °C during the day [48]. Table 1 summarizes the monthly mean of the historical climatic data of the study location [47,48].
2.2. Description of Case Study Buildings
More than 90% of US residential buildings are constructed with timber materials [1,2,49], and over 40% of the existing buildings in the study area were built more than 70 years ago [1,2,50]. Baechler et al. [51] and the US Department Energy Building America Program [52,53] defined the main “Building America” climate regions (i.e., marine, hot-dry, mixed-dry, hot-humid, mixed-humid, cold, and very cold) using a similar illustration as shown in Figure 1. Additionally, the technical report by Reyna et al. [54], and the dataset from [55] provide further explanation regarding the various building climate zones. Figure 2 shows various categories of residential building stock in “Building America” climate regions in the United States. Additionally, Figure 3 showcases the existing building stock and average floor area of multi-family 2–4-unit buildings in these regions. The buildings examined in this case study fall into the category of multi-family 2–4-unit buildings.
The current research examined four selected buildings in the region (Figure 1). The case study buildings exhibit the features of typical Colonial Revival architecture as shown in Figure 4. The features of Colonial Revival architecture have been discussed in existing research [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,56,57], and will not be repeated in this paper.
Additionally, the configuration, average plot size of each case study, average floor area, and other crucial features of the units have been captured in two previous papers [1,2] and will not be discussed further in the current study. Table 2 highlights the main features of the case study buildings, including the thermo-physical properties of their components.
2.3. Field Investigations
Before the field investigations were conducted, the residents were contacted to collect informed consent and seek their permission to investigate the buildings. This study explored different techniques, including indoor monitoring, thermal comfort surveys of the residents, observations, walkthroughs, and informal interviews to follow up with some additional information provided on the questionnaire.
2.3.1. Indoor Monitoring of Environmental Variables
This research conducted physical measurements of variables in the residences during the summer months. Some variables were also computed using the measured data from the surveys. The HOBO sensors monitored and recorded data at 60-min intervals throughout the surveys. According to the ANSI/ASHRAE Standard 55 [58], there are three major heights (0.6 m, 1.1 m, and 1.7 m) above the floor level at which measurements of environmental variables can be recorded. The current study considered the measurements taken at 1.1 m, which aligned with the recommendation of the ANSI/ASHRAE Standard 55 for accessing occupants in sedentary positions [58], it also collected external weather data from a weather station located near to the study location.
2.3.2. Thermal Comfort Surveys
This study considered thermal comfort surveys of the residents of the case study buildings concurrently with the indoor monitoring of environmental parameters. The criteria used to select the participants and questionnaire administered in the study were similar those that have been used in existing research [1]. The current study also followed similar testing procedures to those discussed in existing research [1,2].
The questionnaire is divided into three major sections. The first section includes general questions relating to address or building name, date, time, gender, and the space the respondent currently occupies. The second part of the questionnaire covers questions relating to thermal sensation, thermal comfort, air quality sensation, humidity sensation, thermal preference, control satisfaction, etc. Table 3 presents some of the questions featured in the second part of the questionnaire, along with their rating scales. The third section of the questionnaire captures questions on overall well-being, additional questions, etc.
In total, the study retrieved 112 questionnaires. After the questionnaires were thoroughly checked, the current study identified and selected 110 completed questionnaires for analysis. The data from the thermal comfort surveys were checked again after the selection of the questionnaires and entered into the Statistical Package for the Social Sciences (SPSS version 27.0) and Excel. The statistical software explored in the current study helps to generate relevant charts that are appropriate for the research and to identify the level of associations between the variables evaluated during the surveys.
2.3.3. Observations, Walkthroughs, and Informal Interviews
This research also utilized observations, walkthroughs, and informal interviews to collect additional information from the residents. Observations could be undertaken in several ways, including observing the behavioral patterns of occupants [59], observing thermal comfort charts [60] and indices [61], etc. [28,62,63], to understand the thermal environment. Physical observations were utilized to visually evaluate and record any significant changes or modifications within the thermal environment that could influence the residents’ perceptions of comfort, control, and adaptation. Additionally, observations helped the study to ask questions and engage in follow-up conversations with the residents. Observations were made at the initial visits to the case study buildings, during the indoor monitoring of environmental variables, and during administration of thermal comfort surveys. The study also made some observations at the end of the monitoring and when the questionnaires were retrieved.
The study conducted walkthroughs during the surveys by seeking permission from the residents to walk-through each of the dwelling units. In some cases, the residents gave permission to walk through all the spaces. In a few cases, the occupants only gave permission to access the spaces that were monitored. This technique (i.e., walkthrough) provided an opportunity to take additional notes, ask and answer questions, and provide further clarification to the residents regarding the field investigation.
Because the study considered observations and walkthroughs, there was an opportunity for the research to ask additional questions in the form of informal interviews when meeting with the residents. Some questions asked during the interview related to the overall experience of the residents, to control efficiency, and to the various adaptive measures taken. Overall, the techniques provided additional information for the research and enriched the quality of the data collected during the field investigation.
2.4. Analysis of Data
The study analyzed the data collected during the thermal comfort surveys by calculating the descriptive values (mean, median, mode, range, variance, skewness, percentiles) and the variations between means of humidity sensation, air movement sensation, thermal sensation, air quality sensation, thermal comfort, control satisfaction votes, etc. Additionally, the research considered statistical tests (such as two-sample t-tests, etc.) with the same variances to establish various levels of significance and differences between the groups. For the statistical tests, the outcomes were considered to be statistically significant when p was less than or equal 0.01 (i.e., p ≤ 0.01).
From the research, one can determine that p ≤ 0.001 indicates a high level of significance (i.e., highly significant) and that, when significance is noted, the results suggest that 0.001 < p ≤ 0.01 (i.e., statistically significant). If a weak level of significance is reported, the outcome shows that 0.01 < p ≤ 0.05 (i.e., weakly significant). Inversely, when p > 0.05, one can determine that the outcome is not significant (i.e., statistically not significant). The approaches adopted in this study to establish if the results are statistically significant or statistically insignificant are also similar to the method of interpreting research outcomes that are outlined and discussed in existing studies [13,64,65,66].
The current study also computed the effect size (i.e., Cohen’s d) [67,68,69]. Cohen’s d is also known as standardized mean difference and is used to measure the influence of the sample sizes on the statistically significant variations (i.e., the effect size of the variation between two means) [67]. The results were interpreted based on the limits discussed in existing research [68]. According to Sawilowsky [68] and Aarts et al. [69], d = 0.01 implies a very small difference, d = 0.2 indicates a small difference, d = 0.5 implies a medium difference, d = 0.8 indicates a large difference, d = 1.2 implies a very large difference, and d = 2.0 indicates a huge difference. The data from the indoor monitoring of environmental variables were also entered into Excel (2022 version) and statistical analyses were conducted. Likewise, the study also processed, evaluated, and integrated the information gathered during observations, walkthroughs, and informal interviews.
3. Results
This section outlines the results of the research using different subsections to discuss the main findings of the research.
3.1. Environmental Monitoring of the Thermal Environment
The study noted 22.0 °C as the mean external temperature for the duration of the field investigation. The mean outdoor temperature reported in this study was within the range of daily average temperatures (historical) of 20.0 °C to 23.0 °C. The difference between the maximum temperature and the minimum outdoor temperature was 26.0 °C. While the difference between the mean maximum temperature and the mean minimum temperature in the study area was 22.0 °C. The difference between the highest and lowest average indoor temperatures in the dwelling units was 1.9 °C. For the average relative humidity (RH), the difference between the highest and lowest indoor RHs was 6.2%. The mean dew point temperatures were within the range of 0.5 °C. Figure 5 shows the average indoor and outdoor temperatures (weekly) over a selected timeline during the field investigation.
3.2. Indoor Thermal Environment and Adaptation
Table 4 highlights the summary of the descriptive statistics for gender; time when completing the questionnaire; room occupied when completing the questionnaire; spaces where the participants spent most of their time; activity undertaken within the last hour; and when the residents enter the building. Some major findings from Table 4 reveal a higher response among female residents than among male occupants. Furthermore, that more questionnaires were completed in the evening than in the morning or afternoon and that residents spent more time in their living areas than in other spaces when completing the questionnaires. Additionally, the study indicated that the effect size (Cohen’s d) between the means varied from a very large difference to a huge difference in some of the subjects’ votes presented in the table; meanwhile, a large effect, medium effect, and small effect were each observed in the remaining subjects’ votes
Table 5 captures the assessment of the subjects’ votes of the thermal environmental conditions of the dwelling units. Additionally, Figure 6 highlights the percentage distribution of the votes on the indoor thermal environment of the dwelling units. Some initial and significant findings can be deduced from the study. Thermal comfort (TC) vote was dominated by “comfortable” while the mean vote was around “slightly comfortable”. The thermal sensation vote (TSV) and the mean vote were dominated by “neutral”. The majority of the votes on TSV tended to aggregate around “cool”, “slightly cool”, and “neutral”. The air quality sensation vote was dominated by “good”, while the majority of air movement sensation votes were around “slightly little”, “neutral”, and “slightly much”. Control satisfaction vote was dominated by “satisfied”. The finding on control satisfaction aligned with the feedback from the residents that spent longer hours within the residences. They mentioned that they are satisfied with the level of control. However, the residents that spent longer hours outside the buildings per day preferred additional measures to enhance the level of control and attain control satisfaction within the units. The effect size (Cohen’s d) between the means for each variable varied from a very large difference to a huge difference in some of the subject’s votes, including TSV, TC, daylighting sensation, air quality sensation, and air movement sensation.
This study assessed the mean, median, and mode values of the votes on the indoor thermal conditions of the units as shown in Figure 7. Correlations between those parameters were also assessed. Some of the initial findings that can be deduced from the figure are as follows. Firstly, correlations exist between the mean, median, and mode values of all the variables. The mean values for air quality sensation and thermal sensation exceed the median values for those parameters. There are no significant changes in the mean, median, and mode values of air movement sensation and humidity sensation. Significant changes are noted between the mean, median, and mode values of control satisfaction, thermal comfort, and daylighting sensation. Additionally, on the rating scales, thermal comfort and daylighting sensation votes received the highest ratings for each of the subjects (Figure 8).
3.3. Relationship between the Perceptions of the Thermal Environment, Control, and Adaptation
Additional statistical tests were conducted to determine the level of relationships between the variables assessed during the comfort surveys. Firstly, correlations between the variables were determined. The following correlation coefficients and degrees of linear correlations were applied to this study. R values show the degrees of correlation: when they equal 1 they imply a complete correlation; when they range from 0.8 to ≈1 they imply very strong correlations; from 0.3 to ≈0.8 they indicate strong correlations; from 0 to ≈0.3 they imply weak correlations; and when they are less than 0 they indicate no correlation (i.e., correlations do not exist). R2 (i.e., squared value of R) values varied from 0.000 to 0.198.
From Table 6, one can see that the initial findings revealed strong correlations that occurred between the following variables: humidity sensation and overall well-being; air movement sensation and frequency of use of control; air movement sensation and control satisfaction; air quality sensation and frequency of use of control; air quality sensation and control satisfaction. Correlations were either weak or entirely absent between the remaining parameters outlined in the table. Table 6 also presents the correlation confidence interval (CI) of the statistical analysis. The correlation confidence interval highlights the lower and upper values in relation to the correlation scale for each of the statistical tests.
Additionally, paired sample correlations and significance were also assessed on the perceptions of comfort, control, and adaptations in the dwelling units (Table 7). On the one hand, there is a significance reported between some of the variables, such as thermal sensation and air movement sensation. On the other hand, significance is not observed between some variables, such as thermal sensation and overall well-being. Additionally, a huge difference is noted between the means of paired samples effect sizes as shown in Table 7.
4. Discussion
4.1. The General Conditions of the Thermal Environment and Neutral Temperatures
An overall average indoor temperature of 25.3 °C is observed in the residences. Because the measurements of the variables in this study were taken at 1.1 m above the floor level, as opposed to the measurements taken at 1.7 m above the floor level in a prior study [1], the overall mean indoor temperature in the current study is lower by 0.1 °C than the average temperature reported in that previous investigation [1]. Similarly, the mean values of other environmental parameters, such as dew point, etc., were lower in the current study than the values reported in the existing research [1]. This study also assessed the neutral temperature by plotting the average temperatures against thermal sensation votes (TSV). The neutral temperatures within the residences ranged from approximately 24.3 °C to 26.5 °C (Figure 9). The differences between the mean neutral temperatures in the residences were within the range of 2.2 °C. The neutral temperatures reported in this study exceed the temperatures predicted in previous studies [1,66]. However, the neutral temperatures computed in this study are much lower than the neutral temperatures calculated in other existing research, especially those examining hot and dry climate locations [21].
4.2. The Diversity of the Occupants’ Perceptions of Comfort, Control, and Adaptation
The paired samples tests to establish links between the variables were helpful in evaluating occupants’ perceptions of comfort within the thermal environment. The relationship between thermal sensation and humidity sensation is statistically significant (p < 0.001, SD = 1.712, t = −3.286). The residents that feel warm also feel less humid in the dwelling units. Significance is reported between thermal sensation and daylighting sensation (p < 0.001, SD = 2.555, t = −10.413). The occupants that feel less warm have higher ratings for daylighting sensation. The association between thermal sensation and air quality sensation is statistically significant ((p < 0.001, SD = 2.187, t = −7.280). The residents that feel warm also perceived the indoor air quality to be poor.
Similarly, the link between thermal sensation and thermal comfort is statistically significant (p < 0.001, SD = 2.013, t = −9.378). The participants that feel less warm are thermally comfortable within their dwellings. The occupants that reported feeling less warm reported undertaking activities such as watching TV or reading in their last 15 min within the thermal environment. Occupants that did activities such as walking reported feeling much warmer than those that did less rigorous activities within the same period (p < 0.001, SD = 2.666, t = −7.831).
Regarding the occupants’ perceptions of control and adaptation within the thermal environment, significance is also reported between thermal sensation and frequency of use of control. The residents that reported feeling warm use control more frequently than the occupants that reported feeling less warm (p < 0.001, SD = 3.371, t = −3.196). The study noted that the residents that reported feeling less warm spent more hours indoors per day than the residents that reported feeling much warmer in their dwellings The percentage of thermal sensation votes around neutrality was higher in the current study than existing research [13,66]. The research outcome aligns with the concept discussed in previous investigations that people are likely to be thermally adjusted to cooler sensations [70,71], especially when they have spent longer hours per day within the thermal environment [66].
Feedback from a group of the residents revealed that they would prefer to have a higher level of control, including the use of smart devices, to enable them to adjust the thermal environment even when they are not physically present in the buildings. This observation aligned with the concept of the “endowment effect”, that explains that people who are not owners may value their building less [72] and are likely to require additional adaptive measures to regulate the thermal environment. The relationship between thermal sensation and control satisfaction is not statistically significant.
The residents that perceived air quality as “good” reported feeling satisfied with the level of control provided in the buildings. Additional information from the surveys showed that the occupants that perceived good air quality also noted a satisfaction with the control measures that are used to adjust the thermal environment. On the contrary, the residents that perceived air quality as being “stuffy” or “very stuffy” reported being unsatisfied with the control measures available in their buildings. This outcome revealed that occupants’ perceptions of control satisfaction are not only about availability of control, but should also enhance indoor the air quality of the thermal environment.
Significance is noted between thermal sensation and the overall well-being of the residents (p < 0.001, SD = 2.104, t = −5.011). The residents that perceived higher air movement to be “slightly much” or “much” are thermally comfortable (p < 0.001, SD = 1.651, t = −9.125). The relationship between air movement sensation and daylighting sensation is statistically significant (p < 0.001, SD = 2.102, t = −10.840). Significance is observed between air movement sensation and air quality sensation. The residents that perceived higher air movement indicated that their air quality was good (p < 0.001, SD = 1.322, t = 9.163). The occupants that did less rigorous activities in the last 15 min perceived higher air movement than those that did rigorous activities within the thermal environment (p < 0.001, SD = 2.580, t = 6.614).
The association between occupants’ perceptions of overall well-being and air movement sensation is statistically significant (p < 0.001, SD = 2.470, t = 4.268). Significance is noted between daylighting sensation and humidity sensation (p < 0.001, SD = 1.935, t = 10.842). Significance is also reported between the perceptions of overall well-being and humidity sensation (p < 0.001, SD = 2.227, t = 4.080). The residents that perceived the daylighting level to be acceptable to them are thermally comfortable (p < 0.001. SD = 2.179, t = 3.545). The occupants that use control frequently also perceived that the daylighting level was appropriate for the thermal environment (p < 0.001, SD = 3.202, t = 4.943).
4.3. Migration of the Residents within the Thermal Environment
The study also observed that some of the residents migrated within the thermal environment during the field surveys. Further conversations with the residents showed that they explored internal migration from one space to another during the day within the buildings as one of the adaptive measures to adjust to the environment. Statistical tests to understand if significance is noted between the variables were conducted. Significance is reported between preference for air temperature and the space the residents occupied in the last hour. On the one hand, weak correlations exist between the space the residents occupied in the last hour and how often they use control (R = 0.181), as well as the space occupied in the last hour and control satisfaction (R = 0.104). On the other hand, a strong correlation exists between the space occupied in the last hour and how the residents rated their overall well-being (R = −0.312). Further investigations will be needed to provide more information about this finding.
4.4. Limitations of the Study, Practical Implications, and Future Work
This study only captured field investigations in summertime. Different outcomes may be obtained if residents’ perceptions of the thermal environment in winter are considered. A winter survey was conducted in one of the Colonial Revival residences in the study location prior to this investigation. The outcomes cannot be used for comparison in this study since questionnaires were not administered during the survey. Moreover, the timelines of monitoring during the winter survey and the current study were not the same. In future work, seasonal changes of occupants’ perceptions within the thermal environment can be further assessed. However, this study assessed occupants’ perceptions of the thermal environment in summertime. The investigation explored various techniques to improve the diversity of data evaluated in this study. The research also captured the issue of migration within the thermal environment during the surveys.
One of the practical implications of the study reveals that the concept of thermal comfort is subjective, and depends on a range of factors such as the thermal environment or people’s expectations, which in turn can be influenced by social, economic, cultural, and health backgrounds. Occupancy type can also influence people’s expectations within the thermal environment. Moreover, this study highlights how, while there are limited options for control in the residences, the residents who spent longer hours in the buildings perceived themselves to be more thermally comfortable and able to adapt better using available adaptive measures than those who spent fewer hours in their residences. This study implies that the residents that spent fewer hours within their residences would require more control measures to adjust the thermal environment.
Future work would capture seasonal variations regarding the perceptions of comfort, control, and adaptation in the buildings. The investigation would require field investigations to be conducted in different seasons. This approach will provide additional information about the performance of the buildings in various periods of the year. As noted in existing research, we should advocate for better flexibility in comfort approaches [13,73]. Another area for further investigation is to examine how this concept of better flexibility in comfort strategies can be explored in several types of residences with different ownership and occupancy statuses.
5. Conclusions
This research evaluated occupants’ perceptions of comfort, control, and adaptation in the selected Colonial Revival style residences. The study assessed the links between the variables and considered different techniques to accomplish the research goals. The investigation addressed this research question—Do occupants’ perceptions of comfort significantly impact their perceptions of control and adaptation within the buildings? The following outcomes and recommendations are noted.
- Though the residences have similar features in terms of architectural style, layout, materials used for the construction, size, etc., the temperatures at which the residents feel “neutral” or “no change” (i.e., neutral temperatures) varied due to the subjective state of mind of the residents within the thermal environment and other expectations, including need for additional control measures to adjust the environment.
- The investigation observed that, as people change or move from one thermal environment to another, their level of adaptation could change, depending on how long they have spent within the thermal environment and the adaptive measures available to them.
- This research indicates that, while there are limited options for control in the residences, the residents who spent longer hours in those buildings perceived themselves to be more comfortable and to be able to adapt much better using available adaptive measures than those who spent fewer hours in the residences.
- Lastly, this study recommends integration of transitional smart devices (such as remotely controlled thermostats, smart plugs or electrical outlets that remotely permit disconnection, etc.), including control measures to enhance the overall thermal comfort, satisfaction, and adaptation of residents who may spend fewer hours in those buildings. The initial cost of installation, operational or maintenance cost (if any), and payback period for such investments would require further assessment.
Funding
This research received no external funding.
Institutional Review Board Statement
The study was conducted in accordance with the Declaration of Helsinki, and approved by the Institutional Review Board (or Ethics Committee) (Proposal ID#: PRO20211111).
Informed Consent Statement
Informed consent was obtained from the residents that participated in the surveys.
Data Availability Statement
Data will be provided on request.
Acknowledgments
Many thanks to the residents of the dwelling units for their willingness to participate in this survey, including informed consent provided before the study was conducted. The author appreciates the University of Utah for participating in the Institutional Open Access Program (IOAP).
Conflicts of Interest
The author declares no conflict of interest.
References
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Figure 1.
The map of the United States highlighting the major “Building America” climate regions.
Figure 2.
US residential building stock, including average building floor area in different regio.
Figure 3.
Multi-family 2–4-unit segments in different Building America climate regions.
Figure 4.
(a) Some of the case study buildings examined in the study. (b) Another example of a multi-family residential building that highlights the features of Colonial Revival architecture.
Figure 4.
(a) Some of the case study buildings examined in the study. (b) Another example of a multi-family residential building that highlights the features of Colonial Revival architecture.
Figure 5.
Average indoor and outdoor temperatures (weekly) versus a selected timeline (during the field survey). MFRBA—multi-family residential building A; MFRBB—multi-family residential building B; MFRBC—multi-family residential building C; MFRBD—multi-family residential building D.
Figure 5.
Average indoor and outdoor temperatures (weekly) versus a selected timeline (during the field survey). MFRBA—multi-family residential building A; MFRBB—multi-family residential building B; MFRBC—multi-family residential building C; MFRBD—multi-family residential building D.
Figure 6.
Percentage distribution of the votes on the general indoor thermal environment of the case study buildings (thermal sensation: 1—cold to 7—hot; thermal comfort: 1—very uncomfortable to 7—very comfortable; air quality sensation: 1—very stuffy to 7—very good; air movement sensation: 1—very little to 7—very much; humidity sensation: 1—very dry to 7—very humid; control satisfaction: 1—very dissatisfied to 7—very satisfied; daylighting sensation: 1—very dim to 7—very bright).
Figure 6.
Percentage distribution of the votes on the general indoor thermal environment of the case study buildings (thermal sensation: 1—cold to 7—hot; thermal comfort: 1—very uncomfortable to 7—very comfortable; air quality sensation: 1—very stuffy to 7—very good; air movement sensation: 1—very little to 7—very much; humidity sensation: 1—very dry to 7—very humid; control satisfaction: 1—very dissatisfied to 7—very satisfied; daylighting sensation: 1—very dim to 7—very bright).
Figure 7.
Mean, median, and mode distribution of the votes on the general indoor thermal environment of the case study buildings (thermal sensation: 1—cold to 7—hot; thermal comfort: 1—very uncomfortable to 7—very comfortable; air quality sensation: 1—very stuffy to 7—very good; air movement sensation: 1—very little to 7—very much; humidity sensation: 1—very dry to 7—very humid; control satisfaction: 1—very dissatisfied to 7—very satisfied; daylighting sensation: 1—very dim to 7—very bright).
Figure 7.
Mean, median, and mode distribution of the votes on the general indoor thermal environment of the case study buildings (thermal sensation: 1—cold to 7—hot; thermal comfort: 1—very uncomfortable to 7—very comfortable; air quality sensation: 1—very stuffy to 7—very good; air movement sensation: 1—very little to 7—very much; humidity sensation: 1—very dry to 7—very humid; control satisfaction: 1—very dissatisfied to 7—very satisfied; daylighting sensation: 1—very dim to 7—very bright).
Figure 8.
(a) Rating and (b) range of the subject votes on the general indoor thermal environment of the case study buildings (thermal sensation: 1—cold to 7—hot; thermal comfort: 1—very uncomfortable to 7—very comfortable; air quality sensation: 1—very stuffy to 7—very good; air movement sensation: 1—very little to 7—very much; humidity sensation: 1—very dry to 7—very humid; control satisfaction: 1—very dissatisfied to 7—very satisfied; daylighting sensation: 1—very dim to 7—very bright).
Figure 8.
(a) Rating and (b) range of the subject votes on the general indoor thermal environment of the case study buildings (thermal sensation: 1—cold to 7—hot; thermal comfort: 1—very uncomfortable to 7—very comfortable; air quality sensation: 1—very stuffy to 7—very good; air movement sensation: 1—very little to 7—very much; humidity sensation: 1—very dry to 7—very humid; control satisfaction: 1—very dissatisfied to 7—very satisfied; daylighting sensation: 1—very dim to 7—very bright).
Figure 9.
Chart showing the average indoor temperatures versus thermal sensation votes to predict the neutral temperatures within the dwelling units. MFRBA—multi-family residential building A; MFRBB—multi-family residential building B; MFRBC—multi-family residential building C; MFRBD—multi-family residential building D.
Figure 9.
Chart showing the average indoor temperatures versus thermal sensation votes to predict the neutral temperatures within the dwelling units. MFRBA—multi-family residential building A; MFRBB—multi-family residential building B; MFRBC—multi-family residential building C; MFRBD—multi-family residential building D.
Table 1.
Summary of the monthly averages of the climatic data for the study area from 2017–2022 1.
| Variables | January | February | March | April | May | June | July | August | September | October | November | December |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Maximum temp. (°C) | 20.0 | 21.0 | 22.0 | 29.0 | 34.0 | 36.0 | 37.0 | 34.0 | 34.0 | 29.0 | 24.0 | 17.0 |
| Mean max. temp. (°C) | 14.0 | 17.0 | 19.0 | 22.0 | 31.0 | 33.0 | 36.0 | 33.0 | 30.0 | 26.0 | 21.0 | 15.0 |
| Average high temp. (°C) | 3.0 | 5.0 | 8.0 | 14.0 | 20.0 | 25.0 | 28.0 | 28.0 | 24.0 | 18.0 | 10.0 | 5.0 |
| Daily mean temp. (°C) | −1.0 | 1.0 | 3.0 | 9.0 | 15.0 | 20.0 | 23.0 | 23.0 | 19.0 | 13.0 | 6.0 | 1.0 |
| Average low temp. (°C) | −5.0 | −4.0 | −1.0 | 4.0 | 10.0 | 15.0 | 19.0 | 18.0 | 14.0 | 9.0 | 1.0 | −3.0 |
| Mean minimum temp. (°C) | −18.0 | −16.0 | −11.0 | −3.0 | 3.0 | 10.0 | 14.0 | 11.0 | 6.0 | −0.0 | −8.0 | −12.0 |
| Minimum temp. (°C) | −21.0 | −20.0 | −15.0 | −7.0 | 1.0 | 5.0 | 13.0 | 9.0 | 4.0 | −4.0 | −12.0 | −17.0 |
| Average precipitation (mm) | 70.0 | 88.0 | 94.0 | 129.0 | 111.0 | 102.0 | 166.0 | 123.0 | 97.0 | 135.0 | 100.0 | 129.0 |
| Ave. precipitation days (≥1 mm) | 8.0 | 10.0 | 9.0 | 13.0 | 12.0 | 11.0 | 14.0 | 12.0 | 9.0 | 11.0 | 10.0 | 10.0 |
| Mean monthly sunshine hours | 151.0 | 188.0 | 260.0 | 250.0 | 289.0 | 323.0 | 345.0 | 328.0 | 280.0 | 224.0 | 207.0 | 179.0 |
| Mean daily daylight hours | 9 h 31 min | 10 h 36 min | 11 h 58 min | 13 h 22 min | 14 h 33 min | 15 h 8 min | 14 h 49 min | 13 h 45 min | 12 h 25 min | 11 h 1 min | 9 h 48 min | 9 h 11 min |
| UV index (month maximum) | 3.0 | 5.0 | 7.0 | 7.0 | 9.0 | 9.0 | 10.0 | 10.0 | 8.0 | 6.0 | 4.0 | 2.0 |
| Wind speed (m/s) | 2.9 | 3.0 | 2.9 | 2.5 | 2.0 | 1.8 | 1.7 | 1.7 | 1.9 | 2.2 | 2.4 | 2.6 |
| Solar energy (kWh) | 2.0 | 2.8 | 4.0 | 5.3 | 6.2 | 6.7 | 6.6 | 5.9 | 4.9 | 3.5 | 2.3 | 1.7 |
| Water temperature (°C) | 5.0 | 3.0 | 4.0 | 7.0 | 11.0 | 16.0 | 20.0 | 22.0 | 20.0 | 17.0 | 12.0 | 8.0 |
| Snowfall (mm) | 256.9 | 238.6 | 123.7 | 16.4 | 0.1 | 0.0 | 0.0 | 0.0 | 0.0 | 4.1 | 40.7 | 176.1 |
| Cloud cover (fraction)—clearer (%) | 48.0 | 47.0 | 48.0 | 48.0 | 49.0 | 53.0 | 59.0 | 62.0 | 64.0 | 61.0 | 53.0 | 48.0 |
| Cloud cover (fraction)—cloudier (%) | 52.0 | 53.0 | 52.0 | 52.0 | 51.0 | 47.0 | 41.0 | 38.0 | 36.0 | 39.0 | 47.0 | 52.0 |
1 The values presented in the table are rounded up to the nearest one decimal place, with the exception of the values provided for mean daily daylight hours.
Table 2.
Summary of the key features of the case study buildings 2.
| Building Components | Notes | U-Values (W/m2K) |
|---|---|---|
| External walls | Mostly timber-frame construction clads with vinyl products | ≈0.30–0.50 |
| Windows | Double-glazed window, low-e, argon filled. Some spaces are single glazed. | ≈0.25–0.35 |
| Doors | Fiberglass products. Internal doors are wooden materials. | ≈0.35 |
| Roofs | The materials for roof covering architectural shingles. | ≈0.25–0.30 |
| Floor | Timber-frame construction covered with hardwood flooring, carpets, etc. | ≈1.45–2.5 |
2 The U-values are estimated based on the information gathered during the field investigation and reference materials.
Table 3.
Question scales for the thermal comfort surveys 3.
| Scale/Variable | Thermal Sensation | Thermal Comfort | Air Quality Sensation | Air Movement Sensation | Humidity Sensation | Frequency of Use of Control | Control Satisfaction | Daylighting Sensation | Overall Well-Being |
|---|---|---|---|---|---|---|---|---|---|
| 1 | Cold | Very uncomfortable | Very stuffy | Very little | Very dry | Very little | Very dissatisfied | Very dim | NA * |
| 2 | Cool | Uncomfortable | Stuffy | Little | Dry | Little | Dissatisfied | Dim | Unhealthy |
| 3 | Slightly cool | Slightly uncomfortable | Slightly stuffy | Slightly little | Slightly dry | Slightly little | Slightly dissatisfied | Slightly dim | Slightly unhealthy |
| 4 | Neutral | Neutral | Neutral | Neutral | Neutral | Neutral | Neutral | Neutral | Neutral |
| 5 | Slightly warm | Slightly comfortable | Slightly good | Slightly much | Slightly humid | Slightly much | Slightly satisfied | Slightly bright | Slightly healthy |
| 6 | Warm | Comfortable | Good | Much | Humid | Much | Satisfied | Bright | Healthy |
| 7 | Hot | Very comfortable | Very good | Very much | Very humid | Very much | Very satisfied | Very bright | NA * |
3 Scales of questions featured in the thermal comfort surveys. The table does not include scales for questions with less than five (5) rating levels. In the “Overall well-being” column, NA * means “Not Applicable”.
Table 4.
Summary of the votes on the general information and activities of the respondents 4.
| Vote | Groups of Subjects | Mean | Median | Standard Deviation | Standard Error Mean | Variance | Skewness | Kurtosis | Cohen’s d | |
|---|---|---|---|---|---|---|---|---|---|---|
| Group | % (N) | |||||||||
| Gender | 1 = Male | 32.7% (36) | 1.67 | 1.67 | 0.47 | 0.05 | 0.22 | −0.75 | −1.47 | 0.47 |
| 2 = Female | 67.3% (74) | |||||||||
| Time when completing the questionnaire | 1 = Morning | 31.8% (35) | 2.05 | 2.08 | 0.83 | 0.08 | 0.69 | −0.10 | −1.55 | 0.83 |
| 2 = Afternoon | 30.9% (34) | |||||||||
| 3 = Evening | 37.3% (41) | |||||||||
| Room currently occupied | 1 = Living room | 66.4% (73) | 1.34 | 1.34 | 0.48 | 0.05 | 0.23 | 0.73 | −1.54 | 0.48 |
| 2 = Bedroom | 33.6% (37) | |||||||||
| Space where you occupant most of their time in the last hour | 1 = Living room | 57.3% (63) | 1.52 | 1.47 | 0.66 | 0.06 | 0.44 | 0.91 | −0.30 | 0.66 |
| 2 = Bedroom | 33.6% (37) | |||||||||
| 3 = Kitchen | 9.1% (10) | |||||||||
| Time elapsed since the occupant entered the building | 1 = 15 min | 19.1% (21) | 3.67 | 4.28 | 1.66 | 0.16 | 2.76 | −0.65 | −1.34 | 1.66 |
| 2 = 30 min | 11.8% (13) | |||||||||
| 3 = 45 min | 8.2% (9) | |||||||||
| 4 = 1 h | 4.5% (5) | |||||||||
| 5 = More than 1 h | 56.5% (62) | |||||||||
| Activities within the last hour | 1 = Watching TV | 20.0% (22) | 5.09 | 6.29 | 2.52 | 0.24 | 6.36 | −0.81 | −1.20 | 2.52 |
| 2 = Cooking | 9.1% (10) | |||||||||
| 3 = Walking | 2.7% (3) | |||||||||
| 4 = Washing | 2.7% (3) | |||||||||
| 5 = Reading | 11.8% (13) | |||||||||
| 6 = Other | 53.6% (59) | |||||||||
| Occupant’s actions during the 15 min | 1 = Watching TV | 14.5% (16) | 5.25 | 6.28 | 2.35 | 0.22 | 5.51 | −0.94 | −0.86 | 2.35 |
| 2 = Cooking | 9.1% (10) | |||||||||
| 3 = Standing | 3.6% (4) | |||||||||
| 4 = Walking | 1.8% (2) | |||||||||
| 5 = Washing | 2.7% (3) | |||||||||
| 6 = Reading | 17.3% (19) | |||||||||
| 7 = Other | 50.9% (56) | |||||||||
4 Scales and percentage of the subject votes per scale are also featured in the table. Number of sample (N) = 110.
Table 5.
Summary of the assessment of the subjects’ votes within the thermal environment 5.
| Vote | Groups of Subjects | Mean | Median | Standard Deviation | Standard Error Mean | Variance | Skewness | Kurtosis | Cohen’s d | |
|---|---|---|---|---|---|---|---|---|---|---|
| Group | % (N) | |||||||||
| Thermal sensation | 1 = Cold | 3.6% (4) | 3.25 | 3.21 | 1.20 | 0.11 | 1.44 | 0.69 | 1.11 | 1.20 |
| 2 = Cool | 25.5% (28) | |||||||||
| 3 = Slightly cool | 29.1% (32) | |||||||||
| 4 = Neutral | 31.8% (35) | |||||||||
| 5 = Slightly warm | 6.4% (7) | |||||||||
| 6 = Warm | 0.9% (1) | |||||||||
| 7 = Hot | 2.7% (3) | |||||||||
| Thermal comfort | 1 = Very uncomfortable | 1.8% (2) | 5.05 | 5.24 | 1.24 | 0.12 | 1.54 | −0.87 | 0.70 | 1.24 |
| 2 = Uncomfortable | 0.9% (1) | |||||||||
| 3 = Slightly uncomfortable | 7.3% (8) | |||||||||
| 4 = Neutral | 22.7% (25) | |||||||||
| 5 = Slightly comfortable | 20.0% (22) | |||||||||
| 6 = Comfortable | 41.8% (48) | |||||||||
| 7 = Very comfortable | 5.5% (6) | |||||||||
| Air quality sensation | 1 = Very stuffy | 2.7% (3) | 4.77 | 4.85 | 1.38 | 0.13 | 1.90 | −0.69 | 0.51 | 1.38 |
| 2 = Stuffy | 1.8% (2) | |||||||||
| 3 = Slightly stuffy | 7.3% (8) | |||||||||
| 4 = Neutral | 40.0% (44) | |||||||||
| 5 = Slightly good | 2.7% (3) | |||||||||
| 6 = Good | 41.8% (46) | |||||||||
| 7 = Very good | 3.6% (4) | |||||||||
| Air movement sensation | 1 = Very little | 10.9% (12) | 3.62 | 3.72 | 1.43 | 0.14 | 2.04 | −0.21 | −0.38 | 1.42 |
| 2 = Little | 11.8% (13) | |||||||||
| 3 = Slightly little | 14.5% (16) | |||||||||
| 4 = Neutral | 40.9% (45) | |||||||||
| 5 = Slightly much | 11.8% (13) | |||||||||
| 6 = Much | 9.1% (10) | |||||||||
| 7 = Very much | 0.9% (1) | |||||||||
| Humidity sensation | 1 = Very dry | 2.7% (3) | 3.79 | 3.87 | 0.80 | 0.08 | 0.64 | −1.45 | 3.68 | 0.80 |
| 2 = Dry | 5.5% (6) | |||||||||
| 3 = Slightly dry | 10.9% (12) | |||||||||
| 4 = Neutral | 72.7% (80) | |||||||||
| 5 = Slightly humid | 7.3% (8) | |||||||||
| 6 = Humid | 0.9% (1) | |||||||||
| 7 = Very humid | Nil * (0) | |||||||||
| Control satisfaction | 1 = Very dissatisfied | 29.1% (32) | 3.86 | 5.10 | 2.65 | 0.25 | 7.04 | −0.53 | −1.44 | 0.45 |
| 2 = Dissatisfied | 0.9% (1) | |||||||||
| 3 = Slightly dissatisfied | 9.1% (10) | |||||||||
| 4 = Neutral | 8.2% (9) | |||||||||
| 5 = Slightly satisfied | 0.9% (1) | |||||||||
| 6 = Satisfied | 45.5% (50) | |||||||||
| 7 = Very satisfied | 6.4% (7) | |||||||||
| Daylighting sensation | 1 = Very dim | 10.9% (12) | 5.79 | 6.42 | 1.95 | 0.18 | 3.82 | −1.67 | 1.54 | 1.95 |
| 2 = Dim | 1.8% (2) | |||||||||
| 3 = Slightly dim | 0.9% (1) | |||||||||
| 4 = Neutral | 1.8% (2) | |||||||||
| 5 = Slightly bright | 9.1% (10) | |||||||||
| 6 = Bright | 19.1% (21) | |||||||||
| 7 = Very bright | 56.4% (62) | |||||||||
5 Scales and percentage of the subject votes per scale are also featured in the table. Number of sample (N) = 110. * Nil indicates no subject votes recorded for the category.
Table 6.
Summary of the correlations between the perceptions of the indoor thermal environment, control, and adaptation 6.
Table 6.
Summary of the correlations between the perceptions of the indoor thermal environment, control, and adaptation 6.
| Variable 1 | Variable 2 | Correlation (R Value) | R2 Value | Lower Correlation Confidence Interval (C.I.) | Upper Correlation Confidence Interval (C.I.) |
|---|---|---|---|---|---|
| Thermal comfort | Frequency of use of control | 0.155 | 0.024 | −0.034 | 0.332 |
| Control satisfaction | 0.281 | 0.079 | 0.099 | 0.445 | |
| Overall well-being | 0.252 | 0.064 | −0.074 | 0.529 | |
| Humidity sensation | Frequency of use of control | 0.268 | 0.072 | 0.085 | 0.433 |
| Control satisfaction | 0.275 | 0.076 | 0.093 | 0.440 | |
| Overall well-being | −0.302 | 0.091 | −0.567 | 0.019 | |
| Air movement sensation | Frequency of use of control | 0.423 | 0.179 | 0.256 | 0.566 |
| Control satisfaction | 0.405 | 0.164 | 0.236 | 0.551 | |
| Overall well-being | −0.278 | 0.077 | −0.549 | 0.046 | |
| Air quality sensation | Frequency of use of control | 0.377 | 0.142 | 0.205 | 0.527 |
| Control satisfaction | 0.445 | 0.198 | 0.282 | 0.584 | |
| Overall well-being | −0.229 | 0.052 | −0.511 | 0.098 | |
| Thermal sensation | Frequency of use of control | −0.275 | 0.076 | −0.439 | −0.092 |
| Control satisfaction | −0.231 | 0.053 | −0.401 | −0.046 | |
| Overall well-being | -−0.013 | 0.000 | −0.332 | 0.308 | |
| Daylighting sensation | Frequency of use of control | 0.146 | 0.021 | −0.042 | 0.325 |
| Control satisfaction | 0.079 | 0.006 | −0.109 | 0.263 | |
| Overall well-being | −0.005 | 0.000 | −0.324 | 0.315 |
6 The table provides correlation results for some selected variables.
Table 7.
Summary of the paired sample correlations and paired sample effect sizes between the perceptions of the indoor thermal environment, control, and adaptation 6.
Table 7.
Summary of the paired sample correlations and paired sample effect sizes between the perceptions of the indoor thermal environment, control, and adaptation 6.
| Paired Variables | Paired Sample Correlations | Paired Sample Effect Sizes | |||
|---|---|---|---|---|---|
| Correlation (R Value) | Significance (One-Sided p) | Significance (Two-Sided p) | Cohen’s d | Hedges’ Correction | |
| Thermal sensation and air movement sensation | −0.318 | <0.001 | <0.001 | 2.136 | 2.151 |
| Thermal sensation and humidity sensation | −0.440 | <0.001 | <0.001 | 1.712 | 1.724 |
| Thermal sensation and daylighting sensation | −0.271 | 0.002 | 0.004 | 2.555 | 2.572 |
| Thermal sensation and air quality sensation | −0.436 | <0.001 | <0.001 | 2.187 | 2.202 |
| Thermal sensation and thermal comfort | −0.361 | <0.001 | <0.001 | 2.013 | 2.027 |
| Thermal sensation and frequency of use of control | −0.275 | 0.002 | 0.004 | 3.371 | 3.395 |
| Thermal sensation and control satisfaction | −0.231 | 0.008 | 0.015 | 3.154 | 3.176 |
| Thermal sensation and overall well-being | −0.013 | 0.468 | 0.937 | 2.104 | 2.148 |
| Air movement sensation and thermal comfort | 0.240 | 0.006 | 0.012 | 1.651 | 1.662 |
| Air movement sensation and humidity sensation | 0.474 | <0.001 | <0.001 | 1.262 | 1.271 |
| Air movement sensation and daylighting sensation | 0.257 | 0.003 | 0.007 | 2.102 | 2.117 |
| Air quality sensation and air movement sensation | 0.557 | <0.001 | <0.001 | 1.332 | 1.331 |
6 The table provides paired samples correlation and paired samples effect sizes’ results for some selected variables.
Table 8.
Summary of the additional statistical tests on the effect sizes between the perceptions of the indoor thermal environment, control, and adaptation 7.
Table 8.
Summary of the additional statistical tests on the effect sizes between the perceptions of the indoor thermal environment, control, and adaptation 7.
| Variables | Effect Sizes | |||
|---|---|---|---|---|
| Types of the Effect Sizes | Point Estimate | 95% Confidence Interval Lower | 95% Confidence Interval Upper | |
| Thermal sensation | Eta-squared | 0.074 | 0.000 | 0.182 |
| Epsilon-squared | −0.039 | −0.121 | 0.083 | |
| Omega-squared Fixed-effect | −0.037 | −0.118 | 0.081 | |
| Omega-squared Random-effect | −0.009 | −0.027 | 0.022 | |
| Humidity sensation | Eta-squared | 0.192 | 0.000 | 0.341 |
| Epsilon-squared | 0.094 | −0.121 | 0.261 | |
| Omega-squared Fixed-effect | 0.091 | −0.118 | 0.256 | |
| Omega-squared Random-effect | 0.025 | −0.027 | 0.079 | |
| Daylighting sensation | Eta-squared | 0.271 | 0.000 | 0.423 |
| Epsilon-squared | 0.183 | −0.121 | 0.353 | |
| Omega-squared Fixed-effect | 0.179 | −0.118 | 0.347 | |
| Omega-squared Random-effect | 0.052 | −0.027 | 0.117 | |
| Air quality sensation | Eta-squared | 0.138 | 0.000 | 0.278 |
| Epsilon-squared | 0.034 | −0.121 | 0.190 | |
| Omega-squared Fixed-effect | 0.033 | −0.118 | 0.186 | |
| Omega-squared Random-effect | 0.008 | −0.027 | 0.054 | |
| Thermal comfort | Eta-squared | 0.092 | 0.000 | 0.212 |
| Epsilon-squared | −0.018 | −0.121 | 0.117 | |
| Omega-squared Fixed-effect | −0.018 | −0.118 | 0.114 | |
| Omega-squared Random-effect | −0.004 | −0.027 | 0.031 | |
| Frequency of use of control | Eta-squared | 0.077 | 0.000 | 0.187 |
| Epsilon-squared | −0.035 | −0.121 | 0.089 | |
| Omega-squared Fixed-effect | −0.034 | −0.118 | 0.087 | |
| Omega-squared Random-effect | −0.008 | −0.027 | 0.023 | |
| Control satisfaction | Eta-squared | 0.066 | 0.000 | 0.167 |
| Epsilon-squared | −0.048 | −0.121 | 0.066 | |
| Omega-squared Fixed-effect | −0.046 | −0.118 | 0.064 | |
| Omega-squared Random-effect | −0.011 | −0.027 | 0.017 | |
| Air movement sensation | Eta-squared | 0.082 | 0.000 | 0.196 |
| Epsilon-squared | −0.029 | −0.121 | 0.099 | |
| Omega-squared Fixed-effect | −0.029 | −0.118 | 0.097 | |
| Omega-squared Random-effect | −0.007 | −0.027 | 0.026 | |
7 The table provides the outcomes of the effects sizes for some selected variables.
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Adekunle, T.O. Occupants’ Perceptions of Comfort, Control, and Adaptation in Colonial Revival Style Residences. Sustainability 2023, 15, 1932. https://doi.org/10.3390/su15031932
AMA Style
Adekunle TO. Occupants’ Perceptions of Comfort, Control, and Adaptation in Colonial Revival Style Residences. Sustainability. 2023; 15(3):1932. https://doi.org/10.3390/su15031932
Chicago/Turabian StyleAdekunle, Timothy O. 2023. "Occupants’ Perceptions of Comfort, Control, and Adaptation in Colonial Revival Style Residences" Sustainability 15, no. 3: 1932. https://doi.org/10.3390/su15031932
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