In Fig. 1, this study explores systematically the effects of sensory processing differences on color and texture preferences in individuals with ASD. First, it describes what the research objectives are and how to recruit participants with a variety of sensory profiles. The paintings are created with carefully designed controlled variations in color intensity and texture complexity. Preference ratings are collected through quantitative surveys and sensory and emotional insights are collected through qualitative interviews. Key patterns are identified through statistical analysis (e.g., ANOVA) and thematic coding, allowing for a complete understanding of sensory-driven aesthetic preferences (Braun and Clarke 2023).
Methodological framework for analysing sensory processing and aesthetic preferences in ASD.
Participants
This study was to examine the effects of differences in sensory processing on the preference for aesthetics of visual art, 46 participants with ASD were recruited. To compare the different sensory sensitivities of the participants with ASD to their reactions to color and texture, participants were selected based on their sensory profile and preferences. It was evident that the participants were at different developmental stages as they were aged between 6 and 40 years. Due to such a wide range of ages, the study may include how preferences of certain shades, touches, or artistic preferences may shift over time. By including both the elderly and youths in society, the goal of the study is to clarify how and in what ways aesthetic preferences are different at different ages by analyzing whether the specific aspects of sensory processing increase, decrease or remain stable with age. As expected, due to gender diversity in the ASD population, the participants included both males, females, and those who identified as non-binary. Since previous literature suggests that gender may affect sensory experiences and preferences, this portrayal is necessary. If one wants to create art therapy and art education programs that can be safe for every participant and can meet each of them on his or her level, one has to understand gender differences and how people of different genders can perceive art and interact with it, especially when it comes to sensory integration. The feature of participant characteristics such as age, gender, and sensory is a positive guarantee for the investigation of the different ways in which the variation in sensory processing in ASD affects aesthetics. This range of demographics is crucial for understanding how the different individuals with ASD interact with visual art, information that may inform treatment interventions and art instruction. Demographic and sensory processing profiles of participants along with their age, gender, sensory sensitivity level, and preferred color and texture as well as their emotional resonance score about the paintings are represented in Table 2.
An interesting pattern of sensory sensitivity, color preference, and texture preference is observed in the participants. High sensory sensitive people have a different range of emotional response scores and slightly predominate “Soft” colors, which can be associated with the notion of comfort. Besides, participants preferring “Smooth” texture more often provided higher scores for the degree of emotional impact, which could indicate the link between the smoothness of the texture and the positive emotions. The bar plot enhances these distinctions, showing the way, average emotional resonance scores vary with Sensory Sensitive and Non-Sensory Sensitive, as well as, Red Blue and Green groups. This visualization and summary underpin the correlation between certain sensory attributes and feelings thus offering useful information to art-based therapeutic interventions and improving the sensory engagement of clients with ASD. Such findings are especially valuable when designing sensory-specific therapeutic and educational strategies for children with ASD.
Data collection
Quantitative surveys
In the quantitative part of the study, structured questionnaires were used to measure respondents’ preference for color and texture in visual art. A total of 120 respondents participated in the survey. The survey included a preference rating scale where respondents provided a preference rating of several paintings that differed in terms of color intensity and texture coarseness. Respondents were asked to rate using a Likert scale of 1–5, with 1 corresponding to a strong dislike and 5 to a strong preference. This scale made it possible to quantify the preferences so that the results could be analyzed statistically later. Besides, the survey collected data on the age, gender, and level of sensory sensitivity, which was very important in analyzing the results. The data gathered were analyzed using the Analysis of Variance (ANOVA) to determine the preference differences due to sensory sensitivity. These analyses aimed to discover relationships between sensory integration impairments and certain preferences in the choice of colors and textures.
Qualitative interviews
The qualitative part of the study was centered on the administration of semi-structured interviews with the participants to examine their emotional feelings and sensory experiences toward their color and texture preferences. A purposive sample of 15 participants was selected from the survey pool for in-depth interviews. The interviews were semi-structured to allow the participants to express themselves while at the same time ensuring that they were asked questions related to their feelings and experience with the paintings. This approach promoted free discussion and provided the opportunity to reveal many details. The participants were asked to name the feelings they associate with the analyzed pieces of art, focusing on feelings of comfort and attraction, as well as such concepts as ‘overstimulation’. This qualitative data gave the quantitative ratings a useful background that demonstrated how aesthetics is a subjective matter. The responses were then subjected to thematic coding, where the participants’ accounts were examined for emerging patterns and themes. This analysis aspired to uncover how their sensory processing affects their affection toward art.
Table 3 presents the questionnaire used for the qualitative study.
Stimuli details
In this study, the paintings presented to participants varied systematically in two main sensory dimensions: hue saturation and surface gloss. For color intensity, the paintings were either low saturation colors such as pastel blue, pink, and green which were meant to have low visual stimulation, or high saturation colors such as red, yellow, and deep blue to have high stimulation (Ashburner et al. 2021). The feelings of smoothness can also be observed in some paintings that had uniform concepts of textural variation and areas of normals with little to no layers of paint that are applied thick and glossy to gain a feel of the texture that a surface of that species brings to the hands of the beholder, on the other hand, there were feelings of roughness or complicated in different paintings that had bulky complex and over layers and paint hardened textures Each painting combined one type of color intensity and one type of texture complexity, resulting in four distinct categories: soft color, matte finish, soft color, glossy finish, bright color, matte finish, and bright color, glossy finish. This structured approach enabled a systematic comparison of participants’ preferences based on the within and between variations in color and texture.
Categories of data collected
Data were collected across three primary categories: Preference Ratings, Emotional Response, and Perceived Sensory Experience. The categories provided a complete understanding of the participants’ aesthetic preferences and the sensory and emotional experience with the stimuli (Baker et al. 2019).
Preference ratings
Each painting was also given a preference score by the participants on the Likert scale ranging from 1 – least preferred to 5 – most preferred. For instance, one participant with very high sensory processing sensitivity provided high (4–5) ratings to paintings with soft color and smooth texture and demonstrated a clear preference for less intense sensory stimuli. On the other hand, the same participant placed the level of tolerance or preference for bold color, rough texture painting lower at 1–2, meaning that he or she has less tolerance or liking of paintings that are highly saturated in color and have a rough texture. These ratings provide important information about the effect of sensory aspects on the perceived aesthetics and choice of people with ASD (Crane et al. 2020).
Emotional responses
Qualitative data was gathered by asking participants to give verbal reports of their feelings about each painting. For example, one of the studies outlined getting “comfortable” when looking at a painting that has a matt finish, soft colors, and “no roughness” to the touch. In contrast, the same participant said: “I felt overwhelmed and anxious when I was given a piece of art with a bold color and a rough texture,” they showed how different sensory characteristics of art may cause diverse emotions. These descriptors provide information as to how certain visual stimuli may affect the feelings of people with ASD (Fletcher-Watson et al. 2023).
Perceived sensory experiences
Each painting was discussed in terms of how it affected the participants’ experience of the painting in terms of the color and texture they felt comfortable with. For example, one of the participants identified with hypersensitivity mentioned that bold colors and rough texture cause discomfort as they regard these stimuli as shocking and distasteful. However, the same participant preferred smooth paint texture and soft colors as these combinations felt ‘gentle’ or ‘good’. These descriptions emphasized inter-subjective variability of the perceived sensations and stressed on variability of combinations of colors and textures in terms of comfort and liking (Jones and White 2023).
The participant’s responses to paintings based on color intensity and texture and their associated preference ratings, emotional responses, and sensory experiences are represented in Table 4. It shows how differences in sensory processing affect aesthetic preferences in people with ASD by organizing the data gathered during the study.
The results showed that participants with an increased sensibility of the receptors preferred paintings with gentle colors and smooth surfaces, higher and associated with positive emotions. On the other hand, participants with lower sensory sensitivity preferred paintings with bright colors and coarse surfaces, the description of these paintings as ‘interesting’, and ‘stimulating’ implies that the higher level of sensory stimulation corresponds to the participants’ needs. The relationship between sensory appreciation and emotional effects was supported by quantitative feedback since many participants view art that is described as ‘smooth’, ‘relaxing’, or ‘comforting’. The more complex dataset gives a richer picture of how people with ASD make decisions about aesthetic stimuli based on sensory input, specifically the color and texture of art. The implications of these findings for changing the environment of therapy and art for the sensations of comfort and psychological states of those with ASD are important.
Quantitative analysis
Analysis of variance (ANOVA)
Figure 2 shows that ANOVA (Analysis of Variance) (James et al. 2023) is a collection of statistical models used to compare the means of two independent groups by dividing the variability into systematic and random factors. It helps to determine the effect of the independent variable on the dependent variable. We conducted the primary quantitative analysis using ANOVA to determine if sensory sensitivity levels significantly influenced preference ratings of color intensity and texture complexity. ANOVA compared the mean preference ratings across three sensory sensitivity groups: sensitivity of high, medium, and low (Kinnealey et al. 2022). The statistical model for ANOVA can be represented as:
$${Y}_{{ij}}=\mu +{\alpha }_{i}+{\in }_{{ij}}$$
(1)
Where: Yij is the preference rating of the j-th participant in the i-th sensory sensitivity group, μ is the mean preference rating overall, αi is the effect of the i-th sensory sensitivity group (high, medium, or low) and ∈ij is unexplained variability, random error term.
Analysis of variance (ANOVA).
The null hypothesis (H0) was tested by the ANOVA analysis that there were no significant differences in mean preference ratings were found across sensory sensitivity groups. A p-value of less than 0.05 (p < 0.05 indicated statistically significant differences.
Regression analysis
Linear regression (Lee et al. 2024) is an algorithm that provides a linear relationship between an independent variable and a dependent variable to predict the outcome of future events. A graphical representation of linear regression is shown in Fig. 3. Linear regression was conducted to explore the relationship between sensory profiles and aesthetic choices. This analysis examined the effect of changes in sensory sensitivity levels on preference ratings of color and texture attributes (Lee et al. 2024). The regression model is defined as:
$$Y={\beta }_{0}+{\beta }_{1}X+e$$
(2)
Where: Y is color or texture preferred prediction, β0 is baseline preference rating (baseline preference rating), β1 is a coefficient describing the influence of sensory sensitivity on preference ratings, X sensory sensitivity score, and ϵ is the error term.
Interaction terms were included in some cases to examine whether age or gender moderated the association between sensory sensitivity and preference. The extended model was:
$$Y={\beta }_{0}+{\beta }_{1}X+{\beta }_{2}Z+{\beta }_{3}\left(X\cdot Z\right)+e$$
(3)
Where Z denoted as the moderating variable (e.g. age or gender);
Qualitative analysis
Thematic coding
To analyze the qualitative data collected through interviews, thematic coding (Murray et al. 2021) was used to identify patterns and recurring themes from identification in participants’ descriptions of their sensory and emotional experiences of movement and environment. Responses were categorized into themes that included sensory comfort, overstimulation, and emotional resonance. Participants described sensory comfort as ‘gentle’, ‘soothing’, and ‘calm’, while overstimulation was indicated by ‘overwhelming’, and ‘intense’. The lines gave emotional resonance—feeling evoked using the words relaxed, and energized, to express the emotional response to the paintings. The workflow of thematic analysis is shown in Fig. 4.
Workflow of thematic analysis.
Coding process
Thematic coding of the qualitative interview data was conducted using e.g., NVivo 12, which facilitated systematic and organized analysis (Patel and Garcia 2023). The process began with data familiarization, where all interview transcripts were carefully read multiple times to identify recurring sensory and emotional descriptors. During the initial coding phase, preliminary labels were manually assigned to meaningful data segments, such as “comfort,” “overstimulation,” or “attraction.” These initial codes were then reviewed and grouped into broader themes during the theme development phase, for example, combining codes related to gentle and soothing sensations under the theme “sensory comfort.” To ensure reliability and consistency, a validation step was undertaken where the coding framework was reviewed and applied uniformly across all transcripts (Smith et al. 2022).
Quantitative and qualitative data integration
The results of the thematic coding were integrated with the quantitative data to deepen the understanding of the findings. Strong alignments between numerical preferences and descriptive feedback were found in this cross-referencing. For example, in the quantitative surveys, participants who ranked paintings with soft colors and smooth textures high frequently described these paintings as ‘soothing’ or ‘comfortable’ in the interviews. This integration of the sensory sensitivity levels and emotional responses reinforced the sensory processing differences in aesthetic preferences perspective (Stoppelbein and Greening 2021).
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