# Using Eye Tracking to Reveal Responses to the Built Environment and Its Constituents
## 3 Results
### Results Summary  
In total, the results for the different categories are illustrated in Figure 23, while the remainder of the images used and their heatmaps, not shown here, can be found in the supplementary data.  
Figure 21: **(A)** Paired image of parking garage wall in Somerville, MA, and a processed version with patterns. **(B)** Heatmap of this pair. **(C)** AOIs. The TTFF was shorter for the blank wall over the patterned one; the dwell time however was longer for the latter (photos ©[PERSON], [PERSON]).  
Figure 22: **(A)** Paired image of a spoon with rudimentary face-like cut-outs, and a processed version without them. **(B)** Heatmap of the pair. **(C)** AOIs.The TTFF was shorter for the spoon with a face over the blank one without, and the dwell time was longer for it (photos ©[PERSON]).  
The results from the seven studies fall into five categories of image pairs: traditional vs. modern buildings (_Style_), rich vs. poor texture, presence or absence of fenestration, presence of eyes and face-like features, and natural vs. artificial environment images. Data sets were analyzed per category; they were first tested for normality using the Shapiro-Wilk test, which is appropriate for small sample sizes (<50 samples), and then compared in pairs using a \(t\)-test.)  
TTFF was generally shorter for images with organized complexity (traditional, increased texture, presence of fenestration, and presence of eyes and face-like features) and similar between artificial and natural structures images. However, in \(t\)-tests, in none of these cases did the \(p\) values of the two-tailed test reach 0.05 or lower. More specifically, it  
Figure 23: (**A**) TTFF from all studies, organized by thematic category. (**B**) Dwell time from all studies, organized by thematic category. Single asterisk indicates \(p\) < 0.05, and two asterisks indicate \(p\) < 0.01 in Student’s \(t\)-test.  
was 0.145 for Style, 0.158 for Texture, 0.336 for Fenestration, 0.382 for Eyes- and face-like features, and 0.906 for Natural vs. Artificial.  
Dwell times were longer for these same more complex images in all categories. In all cases (except natural vs. artificial) the \(p\) value in \(t\)-tests was lower than 0.05, as indicated by the asterisks. More specifically, it was 0.004 for Style, 0.031 for Texture, 0.003 for Fenestration, and 0.007 for Eyes- and face-like features. For Natural vs. Artificial it was 0.150.  
The same results are presented in Supplementary Figure S7 (TTFF) and Supplementary Figure S8 (dwell time), but this time with data segregated according to the placement of the photographs in the pair (left-right). There is a positional bias in some cases, with the first position conferring an advantage, with shorter TTFF and longer dwell time, but always with the same pattern as seen in the cumulative results. Finally, based on the premise on which this study was conceptualized, that is, that there are some geometries that are \"nature-like\" and some that are not, we added together the data from all the pairs of results from the 5 categories into one large data pair, containing data from images with \"Nature-Like Geometry\" (NLG) and those with \"Non-Nature-Like Geometry\" (NNLG). The first group contained all data from images of traditional buildings, rich textures, presence of fenestration, presence of eyes-and face-like features, and nature, while the NNLG category contained all data from modern buildings, poor textures, absence of fenestration, absence of eyes-and face-like features, and artificial structures. The results were the same as when individual categories were examined separately. TTFF was shorter for NLG, but again with \(p\) > 0.05 (\(p\) = 0.17), while dwell time was longer in NLG, with a very high significance (\(p\) = 7.8 \(\times\) 10\({}^{-8}\), Figure 24).