Visual perceptions of wood-integrated material combinations: effects on psychological and physiological responses

In this study, we investigated the psychological and physiological effects of wood-integrated material combinations. Although previous studies have examined responses to individual wood materials, the impact of combination of wood with other materials on such responses remains underexplored. We fabricated 22 material models incorporating wood, fabric, tile, and paint in various combinations and manipulating factors, such as wood coverage, material diversity, and brightness levels. Forty-four participants evaluated these models, and their psychological (measured through semantic differential scales) and physiological responses (skin conductance and temperature) were recorded. Wood was perceived as the warmest material, with warmth perception increasing with wood coverage. Material combinations featuring high diversity were rated as appealing and trending. Bright models were perceived as the most appealing and soft, whereas medium to dark tones were found to be stimulating. Notably, although fabric was the most appealing single material, its appeal diminished when combined with wood. These findings suggest that when integrating wood into interior design, careful consideration of the accompanying materials is essential to optimize positive human responses. This study offers valuable insights for designers and architects aiming to enhance well-being through strategic material combinations in built environments.

Wood, known for its versatility, has been widely incorporated into architectural designs to enhance the well-being of occupants and improve environmental aesthetics [1, 2]. Its unique properties, such as thermal insulation [3], acoustic dampening [4], and the visual appeal of its hues and textures [5, 6], make it an ideal choice for creating comfortable indoor environments. Among these qualities, the visual aesthetics of wood have gained prominence as a key design element, supported by the biophilia theory. The biophilia theory, proposed by Wilson [7], suggests that humans have an innate affinity for nature, which has developed through our evolutionary history of living in natural surroundings. This connection implies that visual exposure to natural elements, such as wood, can offer substantial psychological and physiological benefits. In urban settings, where design elements typically comprise sharp edges, straight lines, and smooth surfaces, the soft edges, irregular patterns, and slightly rough textures of wood offer a contrast that reduces perceptual intensity and stress. Urban residents frequently experience heightened arousal and anxiety [8], and the use of wooden elements can help alleviate these feelings by reducing stress and restoring attention, aligning with the theory that natural elements promote psychological and physiological well-being [9, 10].

Several empirical studies have investigated the reactions of individuals to wood materials compared with those to non-wood materials. For example, Sakuragawa et al. [11] examined the psychological and physiological responses to hinoki and white steel wall panels. Hinoki panels evoked natural impressions, whereas white steel panels triggered depressive feelings in participants. Participants who disliked white steel environments experienced increased blood pressure, whereas those who disliked hinoki panels did not exhibit such physiological effects. These results suggest that individuals who do not prefer wood materials experience fewer adverse physiological reactions than those who dislike white steel. Zhang et al. [12] examined emotional changes and fatigue and conducted subjective evaluations of spaces with dark-brown wooden walls, light-brown wooden walls, and white-painted concrete walls. Wooden environments were associated with lower levels of fatigue, more positive emotions, and greater thermal comfort compared with spaces with white-painted concrete walls. Similarly, Shen et al. [13] found that participants in wooden rooms performed better in cognitive tests, demonstrating higher accuracy and quicker response times than those in concrete rooms. Numerous other studies have also reported positive responses to wood in built environments compared with those to non-wood materials [14, 15].

Although these studies highlight the general benefits of wood, its impact can vary depending on specific characteristics, such as brightness, coverage, and the material with which it is paired. Among visually distinguishable factors, such as wood species, surface patterns, and glossiness, brightness is known to have the greatest influence on cognitive processing. Fujisaki et al. [16] found that the brightness perception of wood produced consistent results, as it involves a lower-level perceptual process than surface clarity or glossiness. Supporting this observation, Wan et al. [17] discovered that the subjective recognition of the brightness and glossiness of wood occurred faster than that of surface patterns, which require high-order cognitive processing. However, opinions differ on whether light or dark wood tones are perceived positively. Wan et al. [17] reported a preference for dark wood materials, whereas Lipovac and Burnard [18] found that medium-toned wood images (e.g., oak and maple) were preferred, and lighter wood images (e.g., spruce, pine, and aspen) were less favored. In contrast, Zhu et al. [19] found that office environments featuring light or medium-toned wood were evaluated more positively than those with dark wood tones. Consistent with this, Burnard and Kutnar [20] also reported more favorable stress responses in office environments with light oak furniture than in those with dark walnut furniture.

The extent of wood coverage also influences psychological and physiological responses. Kim et al. [5] observed a positive correlation between the amount of wood used in virtual residential spaces and reported thermal sensations of participants, linking this effect to the hue-heat hypothesis, which suggests a relationship between color perception and subjective thermal experiences [21]. However, excessive use of wood may lead to decreased preference owing to increased perceived warmth and spatial complexity. Zhu et al. [19] proposed that overusing wood in office spaces could result in negative evaluations, and Nyrud et al. [22] found that intermediate levels of wood were most preferred in patient rooms. Overall, these findings suggest that although wood can enhance the aesthetic and psychological appeal, its use should be carefully moderated to optimize the comfort and preference of occupants.

Despite the valuable insights gained from these studies, most have focused on wood in isolation; however, built environments typically involve a combination of wood and other materials. Among the materials commonly paired with wood, fabric materials are strongly associated with tactile-related adjectives such as "soft" [23]. It is reported to provide psychological benefits and healing effects due to its tactile softness and thermal characteristics [24, 25]. Another frequently used material is tiles, which exhibit distinct properties such as high thermal conductivity, surface gloss, weight, and coolness. These qualities contrast with the flexibility of fabric. Studies examining the impact of the visual characteristics of ceramic tiles on perceived comfort [26] and preference [27] have indicated that tiles with high brightness and pattern-free surfaces tend to elicit the most favorable responses. Paint is also a material often used alongside wood. In visual perception experiments, paint has predominantly been employed as a control reference rather than as a comparison subject because of its minimal inherent texture [28]. This contrast in material properties and their distinct perceptual implications underscores the necessity of investigating material combinations, as real environments are composed of multiple materials. In light of this necessity, Ulusoy and Olgunturk [23] addressed this aspect by examining perceptual associations of single and combined materials in an observational experiment. They found that fabric was perceived as "soft" and "deep," timber as "colorful" and "strong," and plasterboard as "strong" and "flat." Notably, these perceptions changed when materials were combined, highlighting the complexity of multi-material impressions.

These findings emphasize the importance of considering visual interactions between material combinations in architectural environments. Although extensive research has been conducted on individual materials, the human response to diverse material combinations remains underexplored. This gap is significant as real-world environments typically comprise various surface materials, limiting the practical relevance of single-material studies. To address this issue, we investigated material combinations that incorporate wood to develop comprehensive and adaptable design approaches. We hypothesize that the synergistic integration of wood with other materials could enhance psychological and physiological responses, leading to effective design strategies in architecture and interior design.

Based on this foundation, we examined how human responses to wood vary when combined with other commonly used interior materials, focusing on the effects of the brightness and coverage of wood. By analyzing these factors alongside material combinations, we aimed to understand how these characteristics collectively influence psychological and physiological outcomes. Through this systematic analysis, we seek to develop insights that can guide more effective and adaptable design strategies.

We employed a within-subject experimental design to investigate the effects of integrating wood with other materials. Participants evaluated adjective pairs while viewing material models, and we simultaneously recorded their electrodermal activity (EDA) and skin temperature (ST).

Stimuli design

In addition to wood, we selected three materials that are commonly used in urban environments: fabric, tile, and paint [29]. Each material plays a key role in the composition of urban design. Fabric and tile were selected for their contrasting properties. Fabric features low thermal conductivity, a large surface area, flexibility, and a soft texture, whereas tile exhibits high thermal conductivity, a narrow surface area, fragility, and a hard texture. These characteristics are also visually distinguishable [30]. Additionally, paint was selected owing to its frequent use in prior studies as a representation of neutral or non-stimulating spaces [12, 28].

Considering the type of wood, we selected North American white oak, a favored hardwood extensively used in high-end furniture, flooring, and structural timber owing to its hardness and consistent surface color [18, 31]. The selected fabric was 100% polyester fur, designed to resemble natural fur, while adhering to ethical standards by being animal-free. Polyester fur, available in various colors and designs, is more durable and cost-effective than natural fur, making it a popular choice for clothing and home decor. Considering the tile, we used porcelain tiles (APN series by NOVAVELL Inc.), which comprise a triaxial composition of clay, quartz, and feldspar, fired at temperatures between 1200 and 1400 °C [32]. These tiles possess the luxurious patterns of natural marble, offering greater resistance to staining and deformation. They can be applied to both walls and floors. Lastly, paint was applied using a roller on a 1 mm thick medium-density fiberboard. Paint is widely regarded as the most common finishing technique in interior design, extending beyond wall treatments to the finishing of furniture, contributing to a cohesive aesthetic. Figure 1 shows the actual image of single materials.

We designed 300 ×ばつ 300-mm material models with various combinations of the four selected materials. Three types of models were created: single-material models, two-material combination models (in a 70:30 ratio), and three-material combination models (in a 70:15:15 ratio) (refer to Fig. 2). The proportions of the material combinations were informed by design practices that emphasize proportional balance, specifically the 70-20-10 rule commonly referenced in interior design [33, 34]. This principle suggests using a dominant element (70%) along with secondary and accent elements (20 and 10%, respectively) to achieve a balanced composition. However, we adjusted the traditional 70:20:10 ratio to 70:15:15 to simplify the study design while maintaining proportional variation, as applying the original ratio across all material combinations would have required creating a significantly larger number of models. In our setup, the 70% material was positioned at the back section of the material model, reflecting spatial hierarchies often found in architectural and interior design where primary materials serve as the background or structural base. To ensure consistent thickness and prevent damage, foam boards were affixed to the back of each model.

Table 1 presents 22 models produced by combining different materials. The models were divided into three categories based on the number of material combinations: single material usage, wood combined with one other material (two-material combinations), and wood combined with two additional materials (three-material combinations). Within the three-material combinations, subcategories were defined based on the proportion of wood, classified as low (15%) or high (70%). By default, all materials were set to a standard medium brightness level. However, in cases of high wood proportions within the three-material combinations, we conducted additional investigation regarding the brightness.

The brightness level is divided into three levels, namely bright, medium, and dark, in the International Commission on Illumination (CIE) 1976 L*a*b* color space [35]. The lightness value, L*, ranges from 0 (black) to 100 (white), whereas the a* axis is relative to the green–red opponent colors, with negative and positive values toward green and red, respectively. The b* axis corresponds to the blue-yellow opponent colors, with negative and positive numbers toward blue and yellow, respectively. Wood color can vary significantly, even within the same species, depending on post-processing methods and environmental factors. Therefore, the criteria for the L* values were established based on previous studies on wood coloration after processing [36, 37]. For fabric, tile, and paint, we selected materials with a* and b* values as close to zero as possible because we aimed to observe the effects solely based on changes in brightness (L* values). Specifically, fabrics and tiles were chosen from commercially available products that exhibited three distinct brightness levels, while paint colors were manually blended to achieve precise adjustments in L* values. To minimize color variation, the ΔE* values, which quantify the Euclidean distance between two color samples, were kept below 6 when compared to the target paint within the same brightness group, excluding wood. For wood, we refrained from controlling the a* and b* values to maintain the inherent impression of its characteristic color, and only L* values were adjusted using water-based white and dark-brown stains. These specific color values are shown in Fig. 3 and presented in Table 2. The surface colors were measured using a spectrophotometer (CM-26d, Konica Minolta, Inc., Osaka, Japan).

Measurement

Psychological responses

In this study, we employed a bidirectional semantic differential scale to assess subjective impressions of each stimulus. A total of 12 pairs of adjectives were selected, and each item was rated on a five-point scale. The evaluation items comprised four questions related to the pleasure-arousal-dominance (PAD) scale, three questions concerning perceived overall impressions, four tactile sensations, and one symbolic descriptor. The survey items are listed in Table 3.

Previous studies have shown that environmental stimuli elicit emotional responses, which in turn influence behavior [38, 39]. Therefore, assessing emotional changes in response to visual stimuli is important. In our study, emotional responses were measured using the PAD scale, a widely used tool for this purpose; however, the dominance factor was excluded. Additionally, three items were selected to evaluate overall perceived impressions [40]. Although the primary focus of this study is material evaluation, these items were included owing to their relevance in indoor space composition. We also included four items to assess perceived tactile sensations, as previous studies have suggested that participants can visually perceive certain material characteristics through learned associations [41]. We also considered thermal sensation as wood is commonly associated with warmth when used alone [42]. Factors, such as thermal conductivity, heat capacity, and color, significantly influence visual thermal perception [25, 43]. Bhatta et al. [44], Tiest and Kappers [45] suggest that materials with low thermal conductivity and heat capacity offer great thermal comfort. Roughness and hardness were also included based on prior studies that explored visual perceptual variations across diverse material types [46]. Perceived weight was included owing to its effect on material perception [47]. Lastly, naturalness was selected based on the unique impression associated with wood, specifically, the natural feel derived from its irregular grain patterns [42]. However, considering the limited evidence on how combining wood with other materials influences this perception, naturalness was included for further investigation.

Physiological responses

We aimed to support the psychological results by confirming variances in emotional arousal and thermal sensation through EDA and ST. The physiological responses of participants were measured using the EmbracePlus wristband (Empatica Inc.). This device, widely employed in research and clinical settings, has demonstrated high accuracy in measuring EDA and ST [48, 49]. Throughout each experimental session, the physiological data of participants were continuously monitored while they observed various material models.

EDA refers to the changes in the skin’s electrical properties caused by sweat secretion. EDA is highly relevant in psychophysiology as it is used to assess both thermal sensation and emotional arousal [50]. It has also been demonstrated to be responsive to visual stimuli [51]. In our study, EDA analysis was conducted using continuous decomposition analysis within the Ledalab tool in MATLAB, which enabled the distinction between phasic and tonic components [52]. In particular, the skin conductance response, representing phasic activity and reflecting attentional responses, was extracted within a timeframe of 1–4 s following the presentation of each stimulus, with a minimum amplitude threshold set at 0.01 μS [53]. The choice of response window and amplitude threshold followed established methodologies for electrodermal response measurement and adhered to recommended usage guidelines for EDA [53].

ST data were used to examine changes in thermal sensation across different models, considering the perceived warmth of wood relative to other materials [25]. Considering ST and EDA analysis, measurements were collected 30 s after the presentation of stimuli. To account for individual physiological differences, all recorded data were transformed into z-scores, calculated using the mean value across all material models of the subject and the mean value for each material model.

Participants

This experimental study included 44 college students (23 females and 21 males), with an average age of 23.9 ± 2.2 years (M ± SD; M: mean, SD: standard deviation). Participants were recruited through campus flyers and a mobile application. To be eligible, participants had to meet specific criteria, including the absence of color detection deficiencies and a normal range of body mass index (BMI). Prior to the experiment, participants were instructed to receive adequate sleep (a minimum of 6 h) and abstain from alcohol and caffeine consumption. These measures were implemented to minimize potential impacts on the experiment and reduce outliers in EDA, ST, and questionnaire responses [54]. This study was approved by the Institutional Review Board of Hanyang University (HYUIRB-202405-009). All participants provided written consent and were compensated for their participation.

Experimental setting

The experiments were conducted in a laboratory with a width, depth, and height of 8700, 3450, and 2400 mm, respectively (Fig. 4a). To ensure consistent lighting, a blackout curtain was used to minimize the effects of daylight. Prior to the experiment, the space was ventilated by opening the door and window to remove indoor air pollutants. During the experiment, ambient temperature was automatically recorded using the Testo 174 T device (Testo SE & CO. KGaA, Germany). The average air temperature was 24.4 ± 0.3 °C. The air temperature met the requirements of the American Society of Heating, Refrigerating, and Air-Conditioning Engineers (ASHRAE) for indoor space [55].

A viewing booth (Thouslite LEDcubes), with dimensions of 1000 mm (width) ×ばつ 600 mm (depth) ×ばつ 600 mm (height), was placed on a table at a height of 72 cm and positioned 30 cm away from seated participants (Fig. 4b). Within the booth, models featuring different material combinations were illuminated using a D50 simulator with 750 lx. These conditions were selected because D50 is considered the standard neutral white color temperature and reference illuminant used in graphic technology and photography-viewing conditions. Additionally, an illuminance level of 750 lx is recommended for precision tasks in the woodworking industry [56, 57]. The lighting conditions were measured using an illuminance spectrophotometer (Konica Minolta CL-500A). The interior of the viewing booth was painted with Munsell N7 spectrally neutral paint. The booth’s large, uniformly lit surfaces ensured more consistent adaptation to the lighting condition [58].

Based on the Korean Statistical Information Service (KOSIS) database for adults aged 20-24 years, the average seated height is 938 mm for males and 876 mm for females in South Korea. Given our viewing setup, this resulted in viewing angles of approximately 38.8° for male participants and 35.7° for female participants (difference of ± 3.1°). Participants used a tablet placed in front of them to answer the survey questions.

Procedure

Prior to the experiment, participants were provided a detailed overview of the study’s objectives and asked to sign a consent form. They were then provided demographic information and were fitted with a wristband, with instructions to minimize hand movements on the side affixed with the device. To ensure accurate physiological measurements, participants were required to spend at least 20 min adjusting to the wearable device [5]. During this adaptation session, they were asked to read interior design magazines that were carefully selected to be neutral and unrelated to the study materials, minimizing any potential influence on the survey results. Subsequently, we conducted a practice session using two randomly selected material models to familiarize participants with the procedure. In the experimental phase, 22 distinct material models were presented. At the start of each inspection, participants closed their eyes until the models were placed in the viewing booth. They then pressed the timestamp button on their wearable device and opened their eyes to view the material. They observed the material for 20 s without moving, rated it on a five-point scale using polar adjective pairs for approximately 80 s, timestamped it again, and closed their eyes. This process was repeated 22 times over the course of approximately 50 min. This duration aligns with prior studies that measured psychological and physiological responses in similar settings and reported no significant stress responses during the experiments [59, 60]. The total duration of the experiment was 80 min. Presented model sequences were randomized to minimize order effects. An overview of the procedure is shown in Fig. 5.

Statistical analysis

In this study, analyses were conducted using IBM SPSS Statistics version 27 (IBM Corp., Armonk, New York, USA). We used repeated measures to investigate how changes in material combinations influenced the psychological and physiological responses of observers. The first step involved factor analysis of all items using varimax rotation to reduce the number of factors. Subsequently, we verified that all the data met the assumptions of normality and sphericity to conduct parametric tests. In experimental data, the skew and kurtosis indexes ranged from − 0.67 to 1.96 (for all factors) and − 1.12 to 5.43, respectively. These values are in accordance with the guidelines for univariate normality [61]. Subsequently, we conducted Mauchly’s test of sphericity. If any groups did not meet the sphericity criteria, we applied the Greenhouse–Geisser correction. We then conducted one-way repeated measures analysis of variance (RM ANOVA) and paired sample t-test to investigate significant differences in the psychological and physiological responses of observers. To address the issue of multiple comparisons arising from these tests, the Bonferroni correction was applied to adjust significance levels. A p-value less than 0.05 indicates statistical significance. Additionally, gender disparities and the interaction effects between gender and materials were investigated using a two-way between-subjects ANOVA.

Factor analysis

Exploratory factor analysis was conducted to reduce dimensions and interpret the results. The Kaiser–Meyer–Olkin (KMO) measure of sampling adequacy was 0.77, indicating suitability for factor analysis. Bartlett’s test of sphericity yielded \({X}^{2}\) = 4527.28 (p < 0.001), confirming that correlations in data were sufficiently strong to use dimension reduction. All items were subjected to factor analysis using varimax rotation, resulting in four factors. The first, second, third, and fourth factors are labeled "Appealing," "Stimulating," "Soft," and "Warm," respectively. These factor names were derived from the associated adjective pairs. The four factors explain 70.086% of the total variance. Within the "Stimulating" factor, as the "Tidy" item has a negative value, an untidy appearance is more stimulating (Table 4).

Result analysis

One-way RM ANOVA and paired sample t-test were conducted to assess significant differences for material models. Owing to data loss, physiological data from 34 participants (18 females and 16 males) with an average age of 22.8 ± 2.1 years were included for analysis. Considering the psychological responses, significance was initially confirmed using mean factor scores (FSs), and subsequently, individual item scores (ISs) were further analyzed to interpret the results with high accuracy. The results derived from FS, as well as physiological data, are presented in Table 5.

Single material

Figure 6 shows the alterations in psychological responses when observing single-material models: wood, fabric, tile, and paint. FS analysis of the "Appealing" factor indicated that fabric (M: 3.55, SD: 0.87) was rated as the most appealing material, with a significant difference compared with paint (M: 2.58, SD: 0.99) (p < 0.05). No significant differences were observed between wood (M: 3.15, SD: 0.99) and other materials. Further analysis of individual ISs supported these findings. For the "Stimulating" factor, no significant results were observed; however, a significance difference emerged in the "Tidy" item, wherein fabric (M: 3.52, SD: 1.32) appeared as the least tidy material, and paint (M: 4.23, SD: 1.22) was perceived as the tidiest (p < 0.05). For the "Soft" factor, fabric (M: 3.79, SD: 0.69) scored the highest, whereas tile (M: 2.29, SD: 0.74) scored the lowest (p < 0.05). Similar results were observed in the individual item analysis, except for the "Trendy" item, wherein fabric (M: 3.91, SD: 1.42) and wood (M: 1.43, SD: 1.42) scored the highest and lowest, respectively. For the "Warm" factor, wood (M: 3.93, SD: 0.94) scored the highest, followed by fabric (M: 3.39, SD: 0.97), tile (M: 2.20, SD: 1.01), and paint (M: 1.82, SD: 0.86) (p < 0.05). The results of individual item analysis for the "Natural" item were consistent with the factor score results. However, for the "Warm" item, fabric scored the highest (M: 3.82, SD: 1.28), followed by wood (M: 2.41, SD: 1.15), paint (M: 1.73, SD: 1.02), and tile (M: 1.68, SD: 1.14) (p < 0.05). In summary, fabric was rated the most appealing and softest material, whereas wood was considered the warmest. In contrast, paint was perceived as the least appealing and least warm material.

Physiological data analysis indicated that EDA was highest for fabric (M: − 0.06, SD: 0.78) and lowest for paint (M: − 0.21, SD: 0.97), although this difference was not statistically significant. STs were the highest and lowest when observing wood (M: 0.23, SD: 1.03) and tile (M: − 0.21, SD: 0.85), respectively; however, this result was also not statistically significant.

Brightness

Figure 7 shows the psychological responses of participants based on variations in brightness. A total of nine material models were employed to analyze the data, comprising three-material combination models: three each in dark, medium, and bright colors, respectively.

In the analysis of the "Appealing" factor, the bright tone (M: 3.78, SD: 2.95) was more appealing than the medium (M: 2.95, SD: 0.77) and dark (M: 2.65, SD: 0.86) tones (p < 0.05). This result was consistent in the analysis of individual items (p < 0.05). Considering the "Stimulating" factor, the dark (M: 2.79, SD: 0.93) and medium (M: 2.80, SD: 0.65) tones received significantly higher scores than the bright tone (M: 2.23, SD: 0.80) (p < 0.05). Individual items within the factor did not show significance for the "Excited" and "Stimulated" items, whereas only the "Tidy" item exhibited consistent results (p < 0.05). In the case of the "Soft" factor, a significant difference was observed in the order of the bright (M: 3.57, SD: 0.60), medium (M: 3.06, SD: 0.60), and dark (M: 2.40, SD: 0.50) tones, and this result was consistent in the analysis among individual items (p < 0.05). Finally, the "Warm" factor did not show significance across all items. Overall, bright materials were perceived as appealing and soft, whereas mid-tone and dark materials were found to be more stimulating than bright tones. In the physiological data, EDA and ST were highest for dark tones; however, the differences were not statistically significant.

Wood coverage

Figure 8 shows the variations in psychological responses corresponding to different levels of wood coverage in the material models. For analysis, we used a total of 13 material models, including one single-material model with 100% wood coverage, three models with a combination of two materials with 70% wood coverage, three models with a combination of three materials with 70% wood coverage (medium tone), and six models with a combination of three materials with 15% wood coverage.

FS analysis on the "Appealing" factor did not show significance; however, significance was observed in the "Satisfied" item. The participants rated the material with 100% wood coverage (M: 3.48, SD: 1.11) as the most satisfying, whereas that with 70% wood coverage (M: 2.83, SD: 0.66) was rated the least satisfying (p < 0.05). Considering the "Stimulating" factor, materials with 70% (M: 2.74, SD: 0.55) and 15% (M: 2.60, SD: 0.55) wood coverage were identified as stimulating, whereas that with 100% wood coverage (M: 1.89, SD: 0.86) was considered less stimulating (p < 0.05). All individual items consistently showed significant results (p < 0.05). Within the "Soft" factor, materials with 15% wood coverage (M: 3.24, SD: 0.40) appeared the softest, followed by materials with 70% (M: 2.89, SD: 0.44) and 100% (M: 2.45, SD: 0.66) wood coverage. However, further analysis revealed that the perception of softness at 15% wood coverage was significantly higher only when the major material was fabric. When the major materials were tile or paint, no significant difference in softness perception was observed between 15 and 70% wood coverage. This finding suggests that the dominant material type, particularly fabric, plays a crucial role in the perceived softness of low-wood-coverage models. Except for those of the "Light" item, the results of all individual items were consistent with the FS (p < 0.05). Considering the "Warm" factor, FS decreased with low wood coverage; specifically, materials with 100% wood coverage were the warmest (M: 3.93, SD: 0.94), followed by those with 70% (M: 2.80, SD: 0.47) and 15% (M: 2.45, SD: 0.55) wood coverage (p < 0.05), which are similarly reflected in individual results. In summary, participants assessed that increasing the wood coverage evoked warmth, whereas decreasing it resulted in a stimulating effect.

In physiological data, high levels of wood coverage were associated with a decrease in EDA (\({M}_{100\%}\): − 0.13, \({SD}_{100\%}\): 0.78, \({M}_{15\%}\): − 0.02, \({SD}_{15\%}\): 0.34) and an increase in ST (\({M}_{100\%}\): 0.23, \({SD}_{100\%}\): 1.03, \({M}_{15\%}\): 0.00, \({SD}_{15\%}\): 0.23); however, these differences were not statistically significant.

Material diversity

A paired sample t-test was conducted to examine changes in psychological and physiological responses with increasing material diversity, as shown in Fig. 9. A total of six material models were used for the evaluation, comprising three models with a combination of two materials and three models with a combination of three materials.

Considering the FS, significant values were only observed in the "Soft" factor, wherein the three-material combination (M: 3.06, SD: 2.72) was rated softer than the two-material combination (M: 2.72, SD: 0.49). The analysis of Individual items showed significance for "Soft" and "Trendy" items, with consistent results (p < 0.05). Although the results of the "Appealing" factor were not significant, a significant difference was observed in the results of the "Appealing" item. In particular, the results of the three-material combination (M: 2.92, SD: 0.91) were significantly higher than those of the two-material combination (M: 2.54, SD: 0.82) (p < 0.05). The data suggest that an increase in the number of material combinations leads to high levels of appeal, trendiness, and softness. However, no significant differences were observed in the physiological data.

Combinations of different materials

We conducted an additional analysis to examine the responses of participants when different materials were combined with wood. Figure 10 shows the individual differences across seven material models, including single material (wood), three two-material combinations, and three three-material combinations with 70% wood coverage.

Our results showed that the effects observed with single materials may not necessarily hold when combined. For example, when wood was paired with fabric, both appeal and warmth decreased compared with when using wood alone (p < 0.05), although the fabric demonstrated high appeal and warmth in the results of the single-material test. Moreover, the wood–fabric combination elicited significantly more stimulating responses than either material alone. Considering the physiological data, although ST was relatively high for the single material (wood), it decreased when wood was combined with fabric; however, these physiological differences were not statistically significant.

Gender effect

A two-way ANOVA was conducted to examine the effects of gender. In the comparison of different single materials, a significant interaction effect was observed for the "Appealing" item (F(3, 168) = 3.04). Women rated fabric (\(\it {\text{M}}_{\text{woman}}\): 3.96, \(\it {\text{M}}_{\text{man}}\): 3.67) and tile (\(\it {\text{M}}_{\text{woman}}\): 3.74, \(\it {\text{M}}_{\text{man}}\): 3.19) as more appealing than men; however, they reported that wood (\(\it {\text{M}}_{\text{woman}}\): 2.52, \(\it {\text{M}}_{\text{man}}\): 3.33) and paint (\(\it {\text{M}}_{\text{woman}}\): 2.48, \(\it {\text{M}}_{\text{man}}\): 2.81) were less appealing. Considering brightness, significant interaction effects were observed for the "Appealing" (F(2, 390) = 5.22) and "Satisfied" items (F(2, 390) = 4.92). Women scored lower than men for mid- (Appealing; \(\it {\text{M}}_{\text{woman}}\): 2.83, \(\it {\text{M}}_{\text{man}}\): 3.03, Satisfied; \(\it {\text{M}}_{\text{woman}}\): 2.87, \(\it {\text{M}}_{\text{man}}\): 3.00) and dark tones (Appealing; \(\it {\text{M}}_{\text{woman}}\): 2.46, \(\it {\text{M}}_{\text{man}}\): 3.19, Satisfied; \(\it {\text{M}}_{\text{woman}}\): 2.57, \(\it {\text{M}}_{\text{man}}\): 3.29) but higher for bright tone (Appealing; \(\it {\text{M}}_{\text{woman}}\): 4.07, \(\it {\text{M}}_{\text{man}}\): 3.79, Satisfied; \(\it {\text{M}}_{\text{woman}}\): 4.07, \(\it {\text{M}}_{\text{man}}\): 3.87). Considering wood coverage, an interaction effect was observed in the "Smooth" item (F(2, 566) = 3.57), wherein women rated models with 100% (\(\it {\text{M}}_{\text{woman}}\): 2.57, \(\it {\text{M}}_{\text{man}}\): 3.43) and 70% (\(\it {\text{M}}_{\text{woman}}\): 2.98, \(\it {\text{M}}_{\text{man}}\): 3.33) wood as rougher compared with men. The ratings for the model with 15% wood coverage were similar between women and men (\(\it {\text{M}}_{\text{woman}}\): 3.48, \(\it {\text{M}}_{\text{man}}\): 3.45). Lastly, in terms of material diversity, no interaction effects were observed. Similarly, the analysis of FSs also revealed no interaction effects. Significant interaction effects and post-hoc analysis results (independent sample t-test, one-way ANOVA with Bonferroni post-hoc test) are shown in Fig. 11.

The objective of this study was to examine variations in psychological and physiological responses when wood is integrated with other materials. A set of 22 models, incorporating wood, fabric, tile, and paint, was crafted for the experiment. These models were designed to investigate differences in participant responses based on the brightness levels, wood coverage, and material diversity. Psychological assessments focused on four factors: aesthetic appeal, stimulation, perceived softness, and warmth perception. Simultaneously, physiological responses were quantitatively measured through EDA and ST.

The analysis of responses to single-material models revealed distinct patterns, particularly regarding the effects of wood, fabric, tile, and paint on the perceptions of aesthetic appeal and warmth of participants. Paint was rated the least appealing, likely owing to its lack of surface texture and visual complexity, which plays a role in stimulation and emotional arousal [62]. Conversely, wood, tile, and fabric, with their unique textures, were perceived as more appealing. In particular, in the case of fabric, the soft and fluffy texture may have contributed to its high appeal, with the added possibility of a healing effect [24]. These findings confirm that utilizing materials with appropriate amounts of surface patterns can significantly enhance psychological appeal. When assessing the warmth perception of individual materials, wood was perceived as the warmest, whereas paint was considered the least warm. The perceived warmth of wood can be linked to its inherent color and texture characteristics. Wastiels et al. [43] reported that materials displaying red and yellow hues, lacking surface gloss, and possessing low thermal efficiency enhance the perception of warmth. Wood, appearing closer to red and yellow in the visible spectrum, with a relatively rough texture and low thermal efficiency, likely contributed to its higher warmth perception compared with other materials.

Considering material brightness, bright materials were perceived as the most appealing, smoothest, and least stimulating. However, preferences for wood brightness are inconsistent in the literature. Some studies suggest that dark or mid-toned woods are preferred over light woods [17, 18]; however, other studies indicate that bright woods are favored for use in spaces or furniture [19, 20]. These conflicting findings may be attributed to whether wood was studied in isolation or as part of a combination. In previous experiments focusing solely on wood, participants favored dark tones [17, 18]; however, in studies that examined wood within spatial contexts, participants showed a preference for light tones [19, 20]. Conversely, these variations could be influenced by the demographic factors, such as age or gender, of participants. In our study, gender analysis revealed that men preferred dark material combinations more than women, consistent with prior research [63].

The analysis of wood coverage revealed that the perception of warmth increased with greater wood application, consistent with the results of previous studies [5]. Additionally, the highest level of wood application elicited the lowest stimulation perception. The observed decrease in stimulation could be attributed to the attention restoration effects associated with wood as a natural material, a phenomenon described by Kaplan [9]. This result further validates the attention restoration effect associated with nature-derived elements. Additionally, material diversity enhanced the appeal, trendiness, and perceived softness, suggesting that combining multiple materials can amplify positive responses. This is likely ascribed to increased visual complexity, which is associated with greater preference [62, 64]. However, our analysis was constrained to comparing models with two and three materials, limiting the extent to which we could generalize these findings. Moreover, Tong et al. [62] stated that visual complexity and consumer emotions follow an inverted U-shaped curve, suggesting that excessive visual complexity may elicit negative emotional responses. This implies that a potential threshold may exist for the effective use of multiple materials, necessitating cautious application. Therefore, to draw more definitive conclusions regarding the positive impact of material diversity, further research involving a wide variety of material combinations is required.

Moreover, the types of materials combined must be carefully considered. Additional analysis was conducted to observe the responses of participants when different materials were combined with wood. Notably, although combining wood with tiles or paint was acceptable, pairing it with fabric diminished its appeal. Simultaneously, the level of stimulation increased. Although fabric was rated highly on its own, its combination with wood resulted in an appeal score similar to that of paint, namely, the least appealing material. This result may be attributed to the excessive visual stimulation resulting from combining the rough surface of wood with plush fur or an aesthetically disharmonious visual impression. However, this effect disappeared when a third material was added, indicating that the pairing of wood and fabric was not universally unfavorable. Further research is required to understand the underlying causes of these results.

Although this study provides valuable insights, it has several limitations that provide opportunities for future research. First, the selection and characteristics of materials used in this study have some limitations. The relatively narrow selection of materials, while designed to represent contrasting characteristics—fabric and tile for their distinct textures, and paint for its minimal visual stimulation—may limit the generalizability of our findings. Therefore, a broader array of materials should be investigated in future studies. Additionally, different wood species, cutting methods, and post-processing techniques can produce varying perceptual outcomes [36], suggesting the need for further investigation into how these factors influence psychological and physiological responses. Moreover, the hue and saturation values of non-wood materials were controlled to remain close to zero, apart from brightness, to minimize the influence of color. However, variations in material colors could potentially alter the findings, emphasizing the need for further exploration in this area.

Second, the design of the material models may have influenced the findings. This study positioned the dominant material (70%) in the back section of the material model, reflecting spatial hierarchies commonly observed in architectural and interior design, where primary materials often serve as structural elements or the background. However, reversing this placement—placing the dominant material in the foreground—can significantly alter user impressions. Moreover, while our adaptation of the 70:20:10 design rule to a 70:15:15 ratio met the practical needs of this study, future research should investigate how varying proportional relationships between materials affect perceptions. Furthermore, the use of 300 ×ばつ 300-mm models may not fully capture real-world perceptions. To overcome this limitation, future studies should utilize virtual reality to simulate diverse environments, thereby offering a more comprehensive understanding of material combinations.

Third, several limitations arise from the experimental design and setup. One issue is the inclusion of materials from the practice session in the main experiment, which introduces a potential bias, as it may have influenced subjective survey evaluations. Additionally, materials were observed against a Munsell N7 neutral paint background under D50 illumination at 750 lx; however, changes in these variables could alter subjective perception [65]. Similarly, the context in which materials are used can also influence evaluation; for example, the same combination may be perceived differently in commercial versus residential settings. Finally, the absence of significant physiological responses may be attributed to the small sample size and the short exposure time. In real-world settings, where material combinations are applied in large spaces or over prolonged periods, these combinations may have a more substantial impact on both subjective reports and physiological responses. Future studies should consider these adjustments to better capture the full range of material impacts.

Finally, participant-related variations may have influenced our findings. Visual perception may have varied due to differences in participants’ seated heights, which introduced differences in viewing angles between male and female participants. Although this variation was relatively small, future studies should standardize viewing angles across participants to minimize discrepancies. Additionally, as this study was conducted with Korean university students, caution should be exercised when generalizing the findings to a broader population. Future research exploring how demographic factors, such as cultural background and age, influence preferences could provide further insights, as suggested by the gender-related differences observed in this study.

In this study, we investigated the psychological and physiological effects of combining wood with other materials, addressing a gap in previous research that primarily focused on individual wood materials. Our findings revealed that wood was perceived as the warmest material, whereas paint was rated the least appealing. Bright materials were generally considered most appealing, and increased wood coverage correlated with higher warmth perception and lower stimulation. Although material diversity generally enhanced positive responses, combining wood with fabric unexpectedly diminished its appeal. In terms of gender differences, women rated fabric and tile as more appealing than men, whereas they rated wood and paint as less appealing. Women also gave lower appeal and satisfaction scores for mid and dark tones, but higher scores for bright tones, compared to men. Additionally, women perceived models with high wood coverage (70–100%) as rougher than men.

This study offers important insights into the effective integration of wood with other materials. Our results provide valuable guidance not only for interior and product designers aiming to use wood in projects but also for architects, furniture makers, and material researchers. Professionals can leverage these findings to develop designs that optimally harness the sensory characteristics of wood in combination with other materials, enhancing the overall human experience and well-being of their products. Furthermore, understanding the interplay between wood and other materials can contribute to more effective and innovative uses of wood in various applications. Future studies should delve deeper into identifying the materials and combinations that yield the most positive effects when used with wood. Additionally, exploring the contextual and cultural factors influencing material preferences could further enrich the practical applications of our findings.

The datasets used and/or analyzed during this study are available from the corresponding author on reasonable request.

EDA:

Electrodermal activity

ST:

Skin temperature

PAD:

Pleasure-arousal-dominance

BMI:

Body Mass Index

ASHRAE:

American Society of Heating, Refrigerating, and Air-conditioning Engineers

KOSIS:

Korean Statistical Information Service

RM ANOVA:

Repeated measures analysis of variance

KMO:

Kaiser–Meyer–Olkin

PCA:

Principal component analysis

FS:

Factor score

IS:

Individual score

We would like to express our sincere gratitude to Nayeon Choi from the Biostatistical Consulting and Research Laboratory at Hanyang University for statistical assistance with this study.

This study was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. RS-2023–00252597) and research fund of Hanyang University (HY-202400000001647).

Authors and Affiliations

1. Department of Interior Architecture Design, Hanyang University, 222 Wangsimni-Ro, Seongdong-Gu, Seoul, 04763, Republic of Korea

   Subin Kwak & Kyungah Choi

Contributions

SK designed and conducted the experiments, analyzed the data, and wrote the initial draft of the manuscript. KC supervised the overall research, provided critical feedback, and reviewed and edited the manuscript. Both authors read and approved the final manuscript.

Corresponding author

Correspondence to Kyungah Choi.

Competing interests

The authors declare that they have no competing interests.

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