Research of Surface Materials for Children’s Household Medical Products Based on Visual and Tactile Experience

Abstract

With people’s concern for health and the development of medical technology, medical products for children are gradually appearing in pharmacies and online stores. However, the appearance of most children’s household medical products tends to meet the needs of adults, which leads to low acceptance of medical products. This study aimed to explore 10- to 16-year-old children’s visual and tactile perception of different materials by researching the relationship between the psychological quantities of visual and tactile perception and the physical quantities of the material surface. Based on the theory of kansei engineering, we measured the physical quantities of nine materials used in insulin syringe products and administered a perceptual questionnaire test for children. By correlating subjective perceptions with the physical attributes of the materials’ surfaces, we determined a strong correlation between the visual and tactile psychological properties and the properties of the materials’ surfaces. Children clearly perceive materials, and materials with lower roughness can elicit calmness, while materials with higher gloss elicit negative emotions. This paper establishes an evaluation model and provides a scientific selection method for surface materials in different children’s household medical products.

1. Introduction

According to statistics, 10–20% of children and adolescents worldwide are suffering from chronic diseases and the prevalence of chronic diseases in children is rising [1]. Among those chronic diseases, diabetes is common among children. Diabetes is a chronic metabolic disease characterized by an absolute lack of insulin, and is categorized into type 1 diabetes mellitus (T1DM) and type 2 diabetes mellitus (T2DM). Most pediatric patients are in the age group of 10 to 14 years, and some of them require long-term exogenous insulin injection therapy, even lifelong disease management [2,3,4]. A long-term chronic metabolic disease seriously affects their daily life and learning, and also produces different degrees of fear, anxiety, depression, or other negative emotions [5,6].

Nowadays, as independent social individuals, children are highly valued as consumers of products for their physical and psychological needs [7,8]. However, the appearance and function of insulin syringes tend to be more adult, resulting in low acceptance of such medical products by the pediatric patient population. Therefore, it is essential to research the surface properties of children’s household medical products and their visual–tactile perceptions.

Currently, kansei engineering is used not only in color design, service design, and human–machine interface design but also has achieved much in terms of the study of product design [9,10,11,12,13]. Based on the theory of kansei engineering, Chen et al., (2020) [14] analyzed the style characteristics of women’s undershirts worn in the workplace. An evaluation model of undershirt styles and consumers’ perceived preferences was established that could serve as a guide for the development and design of new products for apparel companies. Based on the theory of kansei engineering, Liang et al., (2020) [15] determined the main factors affecting users’ perceptions of automobile interiors by establishing a sensory experience and perceived-value evaluation model. The purpose was to guide automobile designers in better meeting the emotional needs of automobile drivers. Based on the semantic differential method, Bhatta et al., (2017) [16] analyzed several different natural and coated wood surfaces by touch. The study aimed to explore whether there is a positive correlation between different kinds of wooden surfaces and users’ affective evaluations, and provided possibilities for improving the positive tactile experience of wooden products. Based on haptic experience, Xiong et al., (2020) [17] analyzed the effects of different types of sandpaper and sanding time on the physical properties of straw particleboard surfaces. Their study combined kansei engineering theory, obtained users’ psychological perceptions of straw particleboards with different degrees of surface roughness, and provided analytical methods and ideas for furniture design.

In summary, kansei engineering is one of the essential theoretical research tools for rationalizing and systematizing design. It is one of the methods of quantifying users’ sensory experiences and accompanying emotions scientifically and is widely used in product design. However, there is still a research gap for children’s household medical product design [18]. This study was based on kansei engineering theory. Typical household medical products were the focus, and the emotional needs of children aged 10 to 16 years were taken as the starting point to study emotional changes brought about by different material surfaces from the perspective of their visual and tactile experience. We analyzed correlations between subjective perception and the physical attributes of material surfaces. Through perceptual evaluations and mathematical and statistical methods, an evaluation model of visual and tactile perception–material surface physical quantity attributes–is established for the evaluation of children’s household medical products. This will provide possibilities for household medical products gaining greater acceptance among children and promoting the emotional connection between medical products and patients.

2. Materials and Methods

2.1. Test Subjects

Some studies have shown that children aged 10–16, under the influence of learning and education from parents, school, and society already possess essential cognitive judgment and behavioral tendencies and attach importance to their inner experience [19]. Our study did not require further ethics committee approval as it did not involve human clinical trials and was not unethical. The anonymity and confidentiality of the test subjects were completely voluntary, and all the tests were based on the consent of the child’s guardian.

There were 53 test subjects in this experiment, 25 boys and 28 girls, and all of them were native speakers of Chinese.

2.2. Test Materials

Due to the characteristics of children’s household medical products regarding their functions, usage scenarios, and population, the materials’ safety, comfort, and efficiency need to be considered in the product design processes [20].

Materials’ safety, comfort, and efficiency are key factors during the product design process. According to the comparative analysis of the materials used in existing insulin syringes, plastic, metal, and silicone are commonly used. They were taken as the objects of study and further summarized and classified according to the different processing technologies of materials. Finally, 9 kinds of typical materials of medical products were used for the expert evaluation method and the KJ method [21].

The materials for this study were the same size, as shown in

Table 1. Samples of materials for household medical products.

P1	P2	P3	P4	P5
Plastic PP	Plastic PP	Plastic PVC	Plastic PVC	Plastic ABS
M1	M2	M3	S1
Metal Aluminum	Metal Stainless Steel	Metal Stainless steel	Silicone

. The sizes of the squares are identical: 10 cm long, 10 cm wide, and 0.1 cm thick.

2.3. Visual and Tactile Subjective Evaluation Test

Hundreds of perceptual vocabularies describing children’s household medical products were collected by reading related literature, product descriptions, advertisements, and product comments. Through preliminary screening of synonyms and combining the expert evaluation method with the KJ method, 8 sets of typical perceptual image semantic words were selected: “cold–warm”, “unlively–lively”, “complicated–handy”, “rough–smooth”, “painful–cozy”, “anxious–calm”, “dangerous–safe” and “hard–soft”.

This experiment mainly used the semantic difference analysis (SD method) in kansei engineering research. As shown in

Table 2. Visual/tactile perceptual evaluations.

Material	Perceptual Vocabulary	−3	−2	−1	0	1	2	3	Perceptual Vocabulary
	Cold	○	○	○	○	○	○	○	Warm
	Unlively	○	○	○	○	○	○	○	Lively
	Complicated	○	○	○	○	○	○	○	Handy
	Rough	○	○	○	○	○	○	○	Smooth
	Painful	○	○	○	○	○	○	○	Cozy
	Anxious	○	○	○	○	○	○	○	Calm
	Dangerous	○	○	○	○	○	○	○	Safe
	Hard	○	○	○	○	○	○	○	Soft

, the questionnaire was designed using a 7-point Likert scale with 8 sets of perceptual image semantic words for the subjective rating of 9 material samples [22].

2.4. Kansei Measurement Procedures

The essential experimental materials for the experiment were a chair, a long table, and 9 different materials. Due to the young age group of the test subjects, the experimenter spent 10–15 min explaining all the experimental procedures before the experiment using A4 paper as a hypothetical test material. Before the experiment started, the test subjects were seated comfortably and put on soundproof headphones.

During the experiment, 9 different materials were randomly presented. After the experimenter placed the subject material in the appropriate location and reminded the test subjects through body language, the test subjects would begin touching and observing the material. The experiment needed to ensure that the test subjects’ touching time for each material was maintained for at least 15 s.

After examining each subject material, the test subjects scored it in a range from −3 to +3 for each set of perceptual image semantic words. Before touching the next material, test subjects would take a short break before moving on to the next one.

2.5. Material Surface Roughness Test

The surface roughness of 9 materials was tested using a JB-4C precision roughness instrument produced by Shanghai Tarmin Optical Instruments Co., Ltd. (Shanghai, China).

In this experiment, a diamond probe with a radius of curvature about 2 μm was used. The probe was moved along the right side of the roughness meter by 2.5 mm at a speed of 0.5 mm/s to measure the surface roughness of the test material. The roughness data of 2 random measurement points in the longitudinal direction and 2 in the transverse direction of each test material were recorded, and the average value was the final measurement value.

2.6. Material Surface Gloss Test

According to the test method stipulated in GB/T 20503-2006 [23], an HG268 glossiness measuring instrument produced by Shenzhen Sanenshi Intelligent Technology Co. (Shenzhen, China), the experimental instrument needs to be on a standard mirror before measurement at a 60° incident reflection measurement angle to measure the glossiness of the tested material after calibration.

In this experimental test, the surface of each subject material needs to be wiped clean with alcohol pads. After drying, the subject material and the apparatus were put on a horizontal table. Then, the glossiness of the test material was measured and recorded at 5 random points. Each point was measured twice parallel and perpendicular to the texture and the average value of the glossiness of the test material was calculated.

3. Results

3.1. Visual and Tactile Subjective Evaluation

Finally, 53 valid questionnaires were collected to obtain the average subjective evaluation scores of the 9 subject materials, which are shown in

Table 3. Average scores of materials in visual and tactile perception evaluations.

Material Number	Cold– Warm	Unlively–Lively	Complicated–Handy	Rough–Smooth	Painful–Comfortable	Anxious–Calm	Dangerous–Safe	Hard–Soft
P1	0.23	0.32	1.06	1.87	1.4	0.94	1.17	1.58
P2	0.66	0.79	0.91	0.17	1	0.6	1.21	0.96
P3	0.19	0.53	0.58	1.38	1.26	1.02	1.09	1.26
P4	0.21	0.38	0.72	1.45	1.06	1.09	1.04	1.21
P5	0.09	0.62	0.74	1.51	1.11	0.83	1.06	1.21
M1	−2.17	−1.87	−1.58	1.08	−0.74	0.94	−0.68	−1.28
M2	−0.96	−0.6	−1.04	0.49	0.4	0.87	0.55	−0.15
M3	−1.85	−1.4	−1.21	0.38	−0.17	0.6	−0.25	−0.62
S1	1.94	2.11	2.17	1.7	2.11	0.74	2.23	2.51

.

As shown in Figure 1, the average scores of the subjective material tactile perception evaluations from high to low were S1 (silicone), P1 (plastic PP), P3 (plastic PVC), P4 (plastic PVC), P5 (plastic ABS), P2 (plastic PP), M2 (metal stainless steel), M3 (metal stainless steel), and M1 (metal aluminum).

The data of this questionnaire were analyzed using Cronbach’s coefficient with IBM SPSS Statistics 27.0 software (IBM Corp., Armonk, NY, USA). As shown in

Table 4. Questionnaire reliability test.

Cronbach’s Alpha Coefficient (Cronbach’s Alpha)	Item Count
0.931	9

, Cronbach’s alpha coefficient for the questionnaire of this study was 0.931, which means that the questionnaire data have relatively high reliability and usefulness [4].

Secondly, for validity testing of the questionnaire evaluation data,

Table 5. Questionnaire validity test.

KMO Test	0.691
Bartlett’s test of sphericity	Chi-squared value	117.189
	Degrees of freedom	28
	Significance	0.000

shows the KMO test value of the questionnaire in this study was 0.691, a value close to 0.7. The significance of Bartlett’s spherical test was 0.000, which is less than 0.05 and significant. This indicates that the variables in this questionnaire are significantly related and the evaluation data are suitable for factor or principal component analysis.

Table 6. Commonality of variables of principal component analysis.

Perceptual Vocabulary Pairs	Initial	Extraction
Cold–Warm	1	0.984
Unlively–Lively	1	0.985
Complicated–Handy	1	0.974
Rough–Smooth	1	0.860
Painful–Comfortable	1	0.981
Anxious–Calm	1	0.902
Dangerous–Safe	1	0.981
Hard–Soft	1	0.992

shows all perceptual vocabulary pairs. The table shows that the value of the common degree of all variables was greater than 0.850, indicating a strong correlation between the variables and the items under study.

Principal Component Factor Analysis

Factors with initial eigenvalues bigger than 1 are principal component factors [24,25]. A comprehensive analysis of

Table 7. Total variance explained.

	Initial Eigenvalue			Extract Sum of Squared Loads			Sum of Squares of Rotational Loads
Component	Total	Variance (%)	Cumulative (%)	Total	Variance (%)	Cumulative (%)	Total	Variance (%)	Cumulative (%)
1	6.195	77.435	77.435	6.195	77.435	77.435	5.993	74.917	74.917
2	1.464	18.306	95.741	1.464	18.306	95.741	1.666	20.824	95.741
3	0.262	3.272	99.013
4	0.045	0.557	99.570
5	0.027	0.341	99.911
6	0.006	0.074	99.985
7	0.001	0.010	99.996
8	0.000	0.004	100.00

reveals that there were two factors with factor eigenvalues bigger than 1 and the cumulative variance contribution rate of these two public factors was 95.741%, which means the effect of this factor analysis is prominent.

The scree plot in Figure 2 shows that the first two factors have steeper slope lines and the fold plot moves more gently after the second factor, so the first two factors are the main factors.

As shown in

Table 8. Component matrix and rotated component matrix.

Perceptual Vocabulary Pairs	Component Matrix		Rotated Component Matrix
	Component Factor 1	Component Factor 2	Component Factor 1	Component Factor 2
Hard–Soft	0.996		0.973
Painful–Comfortable	0.990		0.975
Complicated–Handy	0.985		0.977
Dangerous–Safe	0.982		0.988
Cold–Warm	0.981		0.990
Unlively–Lively	0.980		0.992
Anxious–Calm		0.945		0.944
Rough–Smooth		0.709		0.817

, the rotated component matrices had more apparent assignments than the unrotated component matrices. Thus, the rotated component matrices were more likely to substantiate the significance of the factors. The top two perceptual vocabulary pairs for principal component factor 1 were “unlively–lively” and “cold–warm”, with values of 0.992 and 0.990, respectively. In principal component factor 2, the top 2 perceptual intention word pairs were “anxious–calm” and “rough–smooth”, with values of 0.944 and 0.817, respectively.

According to the results, “unlively–lively”, “cold–warm”, “anxious–calm”, and “rough–smooth” can be used as representative perceptual image semantic words.

3.2. Evaluation of Physical Properties for Different Materials

3.2.1. The Surface Roughness of Materials

As seen in Figure 3, P2 (plastic PP) had the highest Ra value of 0.459 μm and P4 (plastic PVC) had the lowest Ra value of 0.291.

The surface roughness of the nine tested materials, from high to low, was P2 (plastic PP), M3 (metal stainless steel), M2 (metal stainless steel), P5 (plastic ABS), P1 (plastic PP), M1 (metal aluminum), S1 (silicone), P3 (plastic PVC), and P4 (plastic PVC).

3.2.2. The Surface Gloss of Materials

As shown in the test results in Figure 4, S1 (metal aluminum) had the highest gloss of 398.94 GU at a projection angle of 60°. The material with the lowest surface gloss was P2 (plastic PP), with a gloss of 16.24 GU at a projection angle of 60°.

The surface gloss of the nine tested materials, from high to low, was M1 (metal aluminum), M3 (metal stainless steel), P5 (plastic ABS), S1 (silicone), P4 (plastic PVC), M2 (metal stainless steel), P3 (plastic PVC), and P2 (plastic PP).

4. Discussion

4.1. Data Analysis of “Rough–Smooth” Perception Words and Material Surface Roughness

In SPSS 27.0 software, the mean values of the perceptual scores for the perception words “rough–smooth” were correlated with the corresponding surface roughness of the material, as shown in

Table 9. Correlation analysis between “rough–smooth” and material surface roughness.

		Rough–Smooth	Roughness
Rough–Smooth	Pearson correlation	1	−0.777 *
	Significance (2-tailed)		0.014
	Number of cases	9	9
Roughness	Pearson correlation	−0.777 *	1
	Significance (2-tailed)	0.014
	Number of cases	9	9

* Correlation is significant at the 0.05 level (2-tailed).

, resulting in a Pearson’s correlation of r = −0.777. The two perception words are highly correlated, with a Pearson’s correlation value |r| of 0.70–0.89 [26]. The results showed a significant correlation between the “rough–smooth” perceptual scores and the subject material.

Figure 5 shows a polynomial curve fitting of the “rough–smooth” perception words, with an R² of 0.6166 to the material’s surface roughness.

According to the fitting data, when the roughness of the material’s surface was 0.459 μm, the children’s feeling of “roughness” was more prominent.

The data show that the surface roughness of P1 (plastic PP) was 0.331 μm and the surface roughness of P2 (plastic PP) was 0.459 μm. Objectively, these two materials are made of the same polymer with different surface processes, and children’s perception of P1 (plastic PP) tended to be more for smooth than P2 (Plastic PP).

The data also show that the 10- to 16-year-old children were more sensitive to the perception of roughness of material surfaces. They still had high sensitivity to the perception of material variability of surfaces resulting from different surface treatment processes for the same material. This is consistent with the conclusion of Klocker et al. (2012), who explored the surface of a material by touch [27].

4.2. Data Analysis of “Anxious–Calm” Perception Words and Material Surface Roughness

In SPSS 27.0 software, the mean perceptual scores of the perception words “anxious–calm” were correlated with the corresponding surface roughness of the material. As shown in

Table 10. Correlation analysis between “anxious–calm” and material surface roughness.

		Anxious–Calm	Roughness
Anxious–Calm	Pearson correlation	1	−0.746 *
	Significance (2-tailed)		0.021
	Number of cases	9	9
Roughness	Pearson correlation	−0.746 *	1
	Significance (2-tailed)	0.021
	Number of cases	9	9

* Correlation is significant at the 0.05 level (2-tailed).

, Pearson’s correlation of r = −0.746 was negatively and strongly correlated, which showed that the two variables were highly correlated.

A polynomial fitting of the “anxious–calm” perception words with an R² of 0.5992 to the surface roughness of the material is shown in Figure 6 by fitting to the data.

At a surface roughness of 0.291 μm, the feeling of “anxiety” was more obvious. When the material surface roughness was lower, 10- to 16-year-old children are more receptive to this kind of material and their feelings tended to be calmer, so when the surface roughness is higher, it may cause anxiety and worry.

Therefore, when designing household medical products suitable for children of this age group, materials with high surface roughness should be avoided when in contact with a large area of the human body. Materials with a lower surface roughness should be selected for children, such as plastic and silicone.

4.3. Data Analysis of “Unlively–Lively” Perception Words and Material Surface Gloss

In SPSS 27.0 software, the mean values of the perceptual scores for the perception words “unlively–lively” were correlated with the corresponding surface gloss of the material and Pearson’s correlation of r = −0.688 showed a strong negative correlation, a high degree of correlation between the two variables. The data are shown in

Table 11. Correlation analysis between “unlively–lively” and material surface gloss.

		Unlively–Lively	Gloss
Unlively–Lively	Pearson correlation	1	−0.688 *
	Significance (2-tailed)		0.041
	Number of cases	9	9
Gloss	Pearson correlation	−0.688 *	1
	Significance (2-tailed)	0.041
	Number of cases	9	9

* Correlation is significant at the 0.05 level (2-tailed).

.

Figure 7 shows a polynomial fit of the “unlively–lively” perception words with an R² of 0.4768 to the gloss of the material surface.

Children in the age group of 10 to 16 years old perceived materials with GU values in the range of 0–90 as more sensitive in terms of tactile and visual sensations and tended to perceive such materials positively. On the contrary, material with a higher GU value may slow children’s perception and make them feel rigid, bored, or other negative emotions.

When designing household medical products for children, the gloss of the materials used in the products should be fully considered. Materials with higher gloss, such as stainless steel, should be avoided for large areas. This conclusion contradicts the findings of Jin et al. (2023), who studied the preferences of older adults regarding perceived surface gloss [28].

4.4. Data Analysis of “Cold–Warm” Perception Words and Material Surface Gloss

In SPSS 27.0 software, the correlation between the mean values of the perceptual scores of the perception words “cold–warm” and the corresponding surface gloss of the material was analyzed. As shown in

Table 12. Correlation analysis between “cold–warm” and material surface gloss.

		Cold–Warm	Gloss
Cold–Warm	Pearson correlation	1	−0.672 *
	Significance (2-tailed)		0.047
	Number of cases	9	9
Gloss	Pearson correlation	−0.672 *	1
	Significance (2-tailed)	0.047
	Number of cases	9	9

* Correlation is significant at the 0.05 level (2-tailed).

, Pearson’s correlation of r = −0.672 showed a strong negative correlation, indicating a high degree of correlation between the two variables.

A polynomial fitting of the “cold–warm” perception words with an R² of 0.4607 to the surface gloss of the material is shown in Figure 8.

The same types of materials have different surfaces gloss due to different treatment processes. Combined with fitting plots, M2 (metal stainless steel) had a GU value of 71.76 and M3 (metal stainless steel) had a GU value of 142.9. M3 (metal stainless steel) was rated lower on the perceptual scale by 10- to 16-year-old children and tended to be “colder” than M2 (metal stainless steel).

The lower a material’s GU value, the warmer 10- to 16-year-old children tended to perceive it. On the contrary, when the material’s GU value exceeded 100 GU, the children’s perception of coldness gradually decreased. Therefore, when choosing materials for children’s household medical products, we should compare the effects of different surface treatment processes of similar materials.

5. Limitations, and the Future Studies

We must acknowledge that there are several limitations in this study. Firstly, only nine kinds of typical materials of medical products were considered when selecting the experimental samples, and other materials, such as more sustainable or eco-friendly materials, were not selected. It is important for us to compare these novel materials with typical materials in future studies. Secondly, no material sample was color-processed. In future studies, the visual and tactile perceptual experiences of different-colored materials on children will be considered to help designers choose the best design. Thirdly, only Chinese children aged 10 to 16 were chosen as test subjects. In future studies, we will choose more test subjects from different cultures and linguistic backgrounds and enlarge the sample size to improve the reliability and applicability of the study. Next, this study only examined children’s transient perceptual experiences for different material surfaces, and we will have deeper insights into whether perceptions change with repeated use or as children grow older in future research. This study was based on kansei engineering theory, which is subjective in the perceptual evaluation of each material. In future studies, it will be combined with multi-domain methods, such as EEG and eye tracker experimentation, to ultimately obtain user perceptions. Finally, we only focused on insulin syringes and investigated the relationship between children’s perception and surface materials. In future studies, we will experiment with other kinds of children’s household medical products for broader applicability that may benefit manufacturers in the product design process.

6. Conclusions

The comparative analysis of the roughness of the material surface of children’s household medical products and the “rough–smooth” visual and tactile psychometric measure of the material surface showed that the higher the roughness of the material surface, the more obvious the children’s perception of the roughness of the material was. Moreover, children’s sensitivity to the roughness of materials was higher when the roughness of similar materials varied due to different surface treatment processes. Therefore, when selecting and designing materials for household medical products for children aged 10–16, similar materials with different surface treatment processes can be chosen to match the design.

For the children’s household medical products, material surface roughness and “anxious–calm” visual and tactile psychological quantities were comparatively analyzed. When the value of a material’s surface roughness was lower, the children’s perception of the material tended to be more “calm,” indicating that the acceptance of the material would be higher. Therefore, when choosing and designing materials for household medical products for children aged 10 to 16, material surface roughness should be considered to avoid children’s aversion and anxiety.

For children’s household medical product material surface gloss and material surface “unlively–lively” visual and tactile psychological quantities, comparative analysis showed that when the surface GU value of the material was 0–90, 10- to 16-year-old children’s perception of this material tended to be positive. Therefore, materials with low surface gloss should be chosen when selecting and designing household medical products for children aged 10 to 16 years old.

A comparative analysis of the glossiness of the surface of children’s household medical products and the “cold–warm” visual and tactile perceptions was conducted. For the children’s household medical products, material surface roughness and “anxious–calm” visual and tactile psychological quantity comparative analysis of the surface of the material showed that when the glossiness of the surface of the material was 90 GU, the speed of the children’s perception of “cold” gradually diminished. A material with a lower glossy surface can give children a “warm” sensation. Therefore, when choosing and designing materials for household medical products for children aged 10 to 16 years old, we should compare different surface treatment processes to avoid selecting materials with higher gloss.

This study used kansei engineering theory to analyze the visual and tactile subjective perception of children’s household medical product material surfaces. It also involved experiments to investigate the relationship between children’s visual and tactile perception and the roughness and glossiness of children’s household medical product material surfaces. Nowadays, the medical industry is developing rapidly, and medical technology and equipment are constantly being strengthened. Still, more attention should be paid to the psychological condition of child patients when they use related medical products. The material of children’s household medical products is an essential medium for children. Through the selection of appropriate materials, the sensory needs of children can be truly transferred to deep-seated sensory needs. In this way, medical products can provide positive therapeutic effects by meeting the feelings and needs of pediatric patients.