Requirements for Dental CAD Software: A Survey of Korean Dental Personnel
by
, , , , , and
KeunBaDa Son
1
,
Gyu Ri Kim
1,2, 
Won-Gi Kim
3, 
Wol Kang
3,
Du-Hyeong Lee
4,
So-Yeun Kim
4,
Jae-Mok Lee
5,
Yong-Gun Kim
5,
Jin-Wook Kim
6,
Sung-Tak Lee
6, 
Myoung-Uk Jin
7,
Ho-Jin Kim
8,
Jaesik Lee
9,
Ji-Rak Kim
10 and
Kyu-Bok Lee
1,4,* 1
Advanced Dental Device Development Institute (A3DI), Kyungpook National University, Daegu 41940, Republic of Korea
2
Department of Dental Science, Graduate School, Kyungpook National University, Daegu 41940, Republic of Korea
3
Department of Dental Technology, Daegu Health College, Daegu 41453, Republic of Korea
4
Department of Prosthodontics, School of Dentistry, Kyungpook National University, Daegu 41940, Republic of Korea
5
Department of Periodontology, School of Dentistry, Kyungpook National University, Daegu 41940, Republic of Korea
6
Department of Oral & Maxillofacial Surgery, School of Dentistry, Kyungpook National University, Daegu 41940, Republic of Korea
7
Department of Conservative Dentistry, School of Dentistry, Kyungpook National University, Daegu 41940, Republic of Korea
8
Department of Orthodontics, School of Dentistry, Kyungpook National University, Daegu 41940, Republic of Korea
9
Department of Pediatric Dentistry, School of Dentistry, Kyungpook National University, Daegu 41940, Republic of Korea
10
Department of Oral Medicine, School of Dentistry, Kyungpook National University, Daegu 41940, Republic of Korea
*
Author to whom correspondence should be addressed.
Appl. Sci. 2023, 13(5), 2803; https://doi.org/10.3390/app13052803
Submission received: 17 January 2023
/
Revised: 20 February 2023
/
Accepted: 21 February 2023
/
Published: 22 February 2023
(This article belongs to the Special Issue Digital Dentistry and New Era of Prosthodontics)
Abstract
:This study aimed to evaluate the needs of dentists, dental technicians, dental hygienists, and dental-related workers in terms of dental computer-aided design (CAD) software and artificial intelligence (AI). Based on a factor analysis, 57 survey items were assigned to six categories: (a) considerations when purchasing dental CAD software; (b) prosthesis design process; (c) dental CAD function; (d) use of AI dental CAD crown and denture design; (e) impact of AI; and (f) improvements in AI features. Overall, 93 participants were included in the study, and the reliability of the resultant survey data was estimated using Cronbach’s alpha coefficient. Statistically significant factors in each category were identified using one-way analysis of variance and Tukey’s honestly significant difference test (α = 0.05). The results revealed that design quality, design convenience and reproducibility, margin line setting, and automatic margin setting were considered most important in their respective categories (p < 0.05). There were also significant differences in the importance of certain items, such as branding importance and functional diversity, among different dental personnel groups (p < 0.05). Design speed and convenience were also found to be more important to dentists and dental hygienists compared to other dental personnel (p < 0.05). The importance of specific survey items varied significantly based on age, dental personnel, and work experience groups. Dental personnel, such as dentists and dental technicians, assigned greater importance to certain factors, such as branding, functional diversity, design speed, and compatibility with CAM equipment, compared to other occupational groups.
1. Introduction
Digital dental workflows, which are more commonly used for manufacturing dental prostheses than conventional workflows [1,2,3], typically use a three-dimensional (3D) scanning process to produce virtual casts and dental computer-aided design and manufacturing (CAD/CAM) processes to create dental prostheses [4,5,6]. Among these processes, the design process is typically performed using dental CAD software [7,8,9,10], and the final prostheses are developed based on virtual casts. These CAD processes are performed by dentists and dental hygienists in clinics [11,12,13,14,15] and dental technicians in laboratories to manufacture temporary and permanent dental prostheses, respectively [16,17,18]. Therefore, the efficacy of CAD software can be theoretically improved by configuring it to the environment and purpose, although, to the best of our knowledge, no studies have examined this.
Previous evidence on dental CAD software suggests that learning efficacy can differ according to the type of software used and dental personnel [19,20,21], with the working time varying between the user interface/user experiences and the parameter settings for each type of software [19]. Moreover, factors such as the clinical experience and computer literacy of dentists, technicians, and students play a significant role in their ability to learn the design processes [20,21]. The addition of artificial intelligence (AI)-based functions in CAD software [22,23,24] further highlights the importance of considering the variety of factors that can affect learning.
In the digital workflow for manufacturing dental prostheses, various types of dental CAD software have been reported to affect the quality of dental prostheses [25]. In addition, AI functions are being applied during the CAD work process to improve the design results of dental CAD software [26]. However, according to survey results, dentists still lack understanding of the digital workflow for manufacturing dental prostheses [27], and pre-dental students lack education on overall digital dentistry, including CAD software [28]. In addition, dental personnel, including dentists, need to understand various functions of dental CAD software to plan treatment appropriately for patients [29]. Therefore, through the present study, it is necessary to confirm the perceptions of various dental personnel about the functions required or considered important for dental CAD software.
Standards for dental CAD software released by various manufacturers are still ambiguous regarding the criteria dental personnel should consider when purchasing such software. Moreover, the information required by various dental personnel remains insufficient for the development and advancement of dental CAD software. Therefore, this study aimed to evaluate the needs of dental personnel in terms of dental CAD software. The null hypothesis was that the individual survey items in each category would not differ in importance.
2. Materials and Methods
2.1. Selection of Survey Items
A questionnaire for dental CAD software requirements was developed based on existing evidence, and the individual questions were reviewed in detail by clinical experts. Overall, 85 questions were included in the survey, and modifications and deletions were conducted after classification and reliability verification (further details provided below).
2.2. Factor and Reliability Analysis of Survey Items
A pilot study was conducted to test the reliability of the questionnaire, and the coefficient of Cronbach’s alpha was estimated using statistical software (SPSS Version 25.0, IBM, Chicago, IL, USA). Previous evidence suggested that Cronbach’s alpha values of >0.9 indicated excellent reliability and consistency among items. The Bartlett’s sphericity test and Kaiser–Meyer–Olkin (KMO) measures were used to assess the appropriateness of the variables selected for factor analysis (≥0.9: very good; 0.8–0.89: excellent; 0.7–0.79: adequate; 0.6–0.69: mediocre; 0.5–0.59: not desirable; <0.5: not usable for surveys). Factor analysis was performed to reduce the number of variables, remove unnecessary ones, understand their characteristics, and evaluate the validity of each measurement item. Communality values were used to assess how well each variable was explained by the extracted factors (a communality value was considered appropriate if it was ≥0.5).
The questionnaire items were modified after reliability verification and factor analysis, and the results are shown in Table 1. The final survey factors (Cronbach’s alpha ≥ 0.9) exhibited very good reliability and consistency between items, whereas the KMO measure (KMO = 0.829) and Bartlett’s sphericity test (Bartlett’s X2 = 340.001, p < 0.001) indicated good suitability of the variables selected for factor analysis. The communality value (>0.5) of the 57 factors in the 6 categories selected for the survey indicated an explanatory power of 94.273% of the total variance (Table 1).
2.3. Survey
This study was approved by the Clinical Trial Ethics Committee of Kyungpook National University Dental Hospital (IRB no. KNUDH-2021-04-04-01). The individuals who participated in this study were selected based on their extensive expertise and experience in digital dentistry. The team consisted of dental clinicians and dental university professors who had a deep understanding of the latest digital dental medical devices and had used them extensively in dental clinics. They were also active researchers who had published many research papers related to digital dentistry. Individuals who understood the purpose of the study, actively participated, and had clinical experience were included in the study, and the final sample comprised 93 dental personnel (including 25 dentists, 50 dental technicians, 7 dental hygienists, and 11 dental-related workers). The participants assigned scores based on the perceived importance of the factors within each of the six categories, and statistical analysis of the final scores was conducted.
2.4. Statistical Analysis
Reliability analysis of the survey data was conducted using the coefficient of Cronbach’s alpha. The normal distribution of the data was confirmed using the Shapiro–Wilk test, and the groups were compared using one-way analysis of variance (α = 0.05) and Tukey’s honestly significant difference post hoc test. All analyses were conducted using statistical software (SPSS Version 25.0, IBM, Chicago, IL, USA), and the level of significance was set at α = 0.05.
3. Results
The Cronbach’s alpha value for 93 surveys was 0.934, indicating the high reliability of the findings. Among the 93 participants, there were dental technicians (54%), dentists (27%), dental-related workers (12%), and dental hygienists (7%); their work experience varied between ≥10 years (34%) and 5–10 years (28%) (Figure 1). The dental CAD software packages included in the study were 3Shape (40%), Exocad (36%), Zirkonzahn (13%), Cerec (9%), and Dental Wings (2%), and most of them were used to manufacture fixed dental prostheses, such as crowns (55%) and implant prostheses (35%; Figure 1).
3.1. Comparison of the Importance of Survey Items within Each Category
Table 2 shows the importance of survey items within each of the six categories. In Category 1 (considerations when purchasing dental CAD software), design quality was considered the most important, followed by price, diversity of features, ease of learning, compatibility with various scanners, and CAM equipment (Table 2, p < 0.05).
In Category 2 (dental prosthesis design process), design convenience and reproducibility were considered the most important, whereas the diversity of the design tools and compatibility with various items of CAM equipment were considered the least important (Table 2, p < 0.05). In Category 3 (dental CAD software features), margin line setting and virtual articulator function in the crown design section showed the highest and lowest scores, respectively, whereas the border line setting and artificial tooth arrangement functions in the denture design section exhibited the highest scores (Table 2, p < 0.05).
In Category 4, Section 1 (AI function in crown design), automatic margin setting was considered the most important, whereas automatic shade detection and contact point formation were considered the least important (Table 2, p < 0.05). An automatic artificial tooth arrangement, automatic border line formation, and automatic occlusion adjustment exhibited the highest scores in Category 4, Section 2 (AI function in denture design), whereas automatic gingival formation, automatic relief, and block out exhibited the lowest scores (Table 2, p < 0.05).
In Category 5, Section 1 (positive impact of AI-based dental CAD software), increase in convenience was considered the most important, whereas marketing strategy, future prospects for the dental field, and labor cost reduction were considered the least important (Table 2, p < 0.05). In Category 5, Section 2 (negative effects of AI-based dental CAD software), wage reduction, increase in the unemployment rate, and reduced use of conventional workflow showed the highest scores (Table 2, p < 0.05). Finally, in Category 6 (requirements for purchasing AI-based dental CAD software), price, compatibility with existing software, implementation of meaningful functions in clinical practice, and design speed and convenience exhibited the highest scores (Table 2, p < 0.05).
Table 2.
A comparison of the importance of survey items within each category.
| Item | Mean | SD | 95% Confidence Interval | p | Comparison | |||
|---|---|---|---|---|---|---|---|---|
| Lower Limit | Upper Limit | |||||||
| Category 1: Considerations when purchasing dental CAD Software | Price | 7.48 | 3.00 | 6.87 | 8.10 | <0.001 * | A | |
| Branding | 5.15 | 2.64 | 4.61 | 5.69 | B | |||
| Diversity of functions | 7.90 | 2.35 | 7.42 | 8.39 | A | |||
| UI/UX | 6.33 | 2.61 | 5.80 | 6.87 | C | |||
| Easy learning | 7.58 | 2.41 | 7.08 | 8.08 | A | |||
| Design quality | 9.54 | 1.89 | 9.15 | 9.93 | D | |||
| Installed capacity | 4.62 | 2.40 | 4.13 | 5.12 | BE | |||
| Recommendation from acquaintance | 3.01 | 2.30 | 2.54 | 3.48 | F | |||
| Wide range of scanners and CAM compatibility | 7.52 | 2.09 | 7.09 | 7.95 | A | |||
| Need for high-performance computers | 3.30 | 2.08 | 2.87 | 3.73 | F | |||
| Periodic update | 3.53 | 2.22 | 3.07 | 3.99 | EF | |||
| Category 2: Dental prosthesis design process | Design speed | 3.11 | 1.27 | 2.85 | 3.37 | <0.001 * | A | |
| Design convenience | 4.01 | 0.99 | 3.81 | 4.22 | B | |||
| Reproducibility of design form | 3.77 | 1.24 | 3.52 | 4.03 | B | |||
| Variety of design tools | 1.98 | 0.96 | 1.78 | 2.18 | C | |||
| Compatibility with various items of CAM equipment | 2.13 | 1.25 | 1.87 | 2.39 | C | |||
| Category 3: Dental CAD software features | Section 1: Crown design | Parameter function | 4.66 | 1.95 | 4.25 | 5.06 | <0.001 * | A |
| Margin line setting function | 5.53 | 1.74 | 5.17 | 5.89 | B | |||
| Wax-up function | 3.91 | 1.70 | 3.56 | 4.26 | A | |||
| Contact surface forming function | 4.19 | 1.38 | 3.91 | 4.48 | A | |||
| Occlusal function | 4.48 | 1.67 | 4.14 | 4.83 | A | |||
| Dental tooth library utilization | 3.05 | 1.96 | 2.65 | 3.46 | C | |||
| Virtual articulator function | 2.17 | 1.65 | 1.83 | 2.51 | D | |||
| Section 2: Denture design | Border line formation function | 4.60 | 1.69 | 4.25 | 4.95 | <0.001 * | A | |
| Choose from a variety of artificial tooth types | 3.06 | 1.62 | 2.73 | 3.40 | B | |||
| Artificial tooth arrangement function | 4.26 | 1.32 | 3.99 | 4.53 | A | |||
| Gingival formation function | 3.20 | 1.48 | 2.90 | 3.51 | B | |||
| Virtual articulator function | 2.97 | 1.59 | 2.64 | 3.30 | B | |||
| Relief and block out function | 2.90 | 1.73 | 2.55 | 3.26 | B | |||
| Category 4: AI Functions in dental CAD software | Section 1: Crown design | Automatic crown shape design | 3.59 | 1.27 | 3.33 | 3.85 | <0.001 * | A |
| Automatic margin line setting | 4.31 | 0.83 | 4.14 | 4.48 | B | |||
| Automatic occlusion adjustment | 3.46 | 0.87 | 3.28 | 3.64 | A | |||
| Automatic shade detection function | 1.63 | 0.92 | 1.45 | 1.82 | C | |||
| Automatic contact point formation | 2.00 | 1.00 | 1.79 | 2.21 | C | |||
| Section 2: Denture design | Automatic gingival formation | 2.53 | 1.53 | 2.21 | 2.84 | <0.001 * | AB | |
| Automatic artificial teeth placement | 3.57 | 1.31 | 3.30 | 3.84 | C | |||
| Automatic border line formation | 3.46 | 1.33 | 3.19 | 3.74 | C | |||
| Automatic occlusion adjustment | 3.05 | 1.16 | 2.81 | 3.29 | BC | |||
| Automatic relief and block out | 2.39 | 1.34 | 2.11 | 2.66 | A | |||
| Category 5: Impact of AI-based dental CAD software | Section 1: Positive impact | Increase in sales | 3.91 | 1.83 | 3.54 | 4.29 | <0.001 * | A |
| Increased work convenience | 6.15 | 1.20 | 5.90 | 6.40 | B | |||
| Increased productivity | 5.31 | 1.26 | 5.05 | 5.57 | C | |||
| Quality improvement | 4.29 | 1.81 | 3.92 | 4.66 | A | |||
| Marketing | 2.83 | 1.57 | 2.50 | 3.15 | D | |||
| Prospects for the dental field | 2.73 | 1.51 | 2.42 | 3.04 | D | |||
| Labor cost savings | 2.77 | 1.69 | 2.43 | 3.12 | D | |||
| Section 2: Negative impact | Wages decreased | 3.26 | 1.44 | 2.96 | 3.55 | <0.001 * | A | |
| Unemployment rising | 3.38 | 1.25 | 3.12 | 3.63 | A | |||
| Deterioration of dental technology | 2.61 | 1.24 | 2.36 | 2.87 | B | |||
| Decreased use of conventional workflow | 3.20 | 1.40 | 2.92 | 3.49 | A | |||
| Shrinking of the digitally vulnerable | 2.55 | 1.54 | 2.23 | 2.87 | B | |||
| Category 6: Requirements for purchasing AI-based dental CAD software | Price | 3.31 | 1.97 | 2.91 | 3.72 | <0.001 * | AB | |
| UI/UX | 3.10 | 1.56 | 2.78 | 3.42 | A | |||
| Training in the use of software | 3.09 | 1.67 | 2.74 | 3.43 | A | |||
| Compatibility with existing software | 3.74 | 1.45 | 3.44 | 4.04 | AB | |||
| Implementation of meaningful functions in clinical practice | 3.91 | 1.67 | 3.57 | 4.26 | B | |||
| Design speed and convenience | 3.86 | 1.71 | 3.51 | 4.21 | B | |||
* Indicates significant differences within each category or section based on the results of one-way ANOVA testing (p < 0.05). Identical capital letters within each category or section indicate no statistically significant differences (p > 0.05).
3.2. Comparison of the Importance of Each Survey Item by Age, Dental Personnel, and Work Experience Groups
Table 3 shows the importance of each survey item in terms of age, dental personnel, and work experience groups. In Category 1 (considerations when purchasing software), branding importance differed significantly by dental personnel (p = 0.017), with dentists and dental technicians allocating significantly higher importance compared with the other dental personnel (p < 0.05). Moreover, the importance of functional diversity significantly differed by dental personnel (p = 0.001), with dental technicians and dental-related workers assigning significantly greater importance compared with the other dental personnel (p < 0.05). A significant difference was also observed in the importance of acquaintance recommendation (p = 0.015), with dentists and dental-related workers placing greater importance on it than the other dental personnel groups (p < 0.05).
In Category 2 (dental prosthesis design process), significant differences in the importance of design speed were observed between dental personnel (p = 0.026), with dentists and dental-related workers placing greater importance on this factor than the other occupational groups (p < 0.05). The importance of design convenience differed significantly (p = 0.003), with dentists and dental hygienists allocating greater importance than the other occupational groups (p < 0.05). The importance of compatibility with various items of CAM equipment varied significantly (p = 0.02), with dentists, dental technicians, and dental hygienists placing greater importance on this than the dental-related worker group (p < 0.05).
In Category 3, the importance of dental tooth library utilization significantly varied by dental personnel (p = 0.003), with dentists and dental hygienists placing greater importance on this factor than other occupational groups (p < 0.05). The importance of the virtual articulator function significantly varied in terms of age group (p = 0.009), with greater importance being assigned by those in their twenties and forties compared to those in their fifties (p < 0.05).
In Category 4, the importance of automatic occlusion adjustment during crown design varied significantly by work experience (p = 0.035), with greater importance being allocated by those with <3 years of experience compared to those with >3 years of experience (p < 0.05). Significant differences in the importance assigned to automatic occlusion adjustment during denture design by dental personnel were also observed (p = 0.042), with dentists and dental hygienists placing greater importance on it than other dental personnel (p < 0.05).
In Category 5, Section 1, significant differences in the importance placed on dental prospects between dental personnel were observed (p < 0.001), with dental technicians placing significantly greater importance on this factor than other dental personnel (p < 0.05). In Category 6, the importance of design speed and convenience also significantly varied by dental personnel (p = 0.044), with dentists and dental hygienists placing significantly greater importance on these aspects than other dental personnel (p < 0.05).
Table 3.
A comparison of the importance assigned to each survey item by age, dental personnel, and work experience groups.
Table 3.
A comparison of the importance assigned to each survey item by age, dental personnel, and work experience groups.
| Item | Age | Dental Personnel | Work Experience | |||||
|---|---|---|---|---|---|---|---|---|
| F | p | F | p | F | p | |||
| Category 1: Considerations when purchasing dental CAD Software | Price | 0.379 | 0.768 | 0.859 | 0.466 | 0.379 | 0.823 | |
| Branding | 0.533 | 0.661 | 3.593 | 0.017 * | 1.657 | 0.167 | ||
| Diversity of functions | 1.618 | 0.191 | 6.355 | 0.001 * | 0.889 | 0.474 | ||
| UI/UX | 0.987 | 0.403 | 0.113 | 0.952 | 0.822 | 0.514 | ||
| Easy learning | 0.186 | 0.906 | 0.788 | 0.503 | 0.957 | 0.435 | ||
| Design quality | 0.133 | 0.94 | 0.686 | 0.563 | 0.2 | 0.938 | ||
| Installed capacity | 0.46 | 0.711 | 1.078 | 0.363 | 1.205 | 0.315 | ||
| Recommendation from acquaintance | 1 | 0.397 | 3.696 | 0.015 * | 0.939 | 0.445 | ||
| Wide range of scanners and CAM compatibility | 0.608 | 0.611 | 0.9 | 0.445 | 1.25 | 0.296 | ||
| Need for high-performance computers | 0.076 | 0.973 | 0.122 | 0.947 | 0.713 | 0.585 | ||
| Periodic update | 0.411 | 0.745 | 0.34 | 0.796 | 0.626 | 0.645 | ||
| Category 2: Dental prosthesis design process | Design speed | 0.801 | 0.497 | 3.235 | 0.026 * | 0.795 | 0.532 | |
| Design convenience | 0.875 | 0.457 | 5.076 | 0.003 * | 1.905 | 0.117 | ||
| Reproducibility of design form | 2.245 | 0.089 | 1.757 | 0.161 | 2.045 | 0.095 | ||
| Variety of design tools | 1.175 | 0.324 | 0.182 | 0.909 | 0.795 | 0.532 | ||
| Compatibility with various items of CAM equipment | 0.711 | 0.548 | 3.438 | 0.02 * | 0.939 | 0.446 | ||
| Category 3: Dental CAD software features | Section 1: Crown design | Parameter function | 0.337 | 0.798 | 1.133 | 0.34 | 0.653 | 0.626 |
| Margin line setting function | 1.659 | 0.182 | 1.331 | 0.269 | 0.849 | 0.498 | ||
| Wax-up function | 1.214 | 0.309 | 1.133 | 0.34 | 0.613 | 0.655 | ||
| Contact surface forming function | 1.433 | 0.239 | 1.262 | 0.292 | 0.416 | 0.797 | ||
| Occlusal function | 2.241 | 0.089 | 1.754 | 0.162 | 1.01 | 0.407 | ||
| Dental tooth library utilization | 0.413 | 0.744 | 5.111 | 0.003 * | 0.618 | 0.651 | ||
| Virtual articulator function | 4.082 | 0.009 * | 0.429 | 0.733 | 1.231 | 0.304 | ||
| Section 2: Denture design | Border line formation function | 0.266 | 0.85 | 0.301 | 0.825 | 1.359 | 0.255 | |
| Choose from a variety of artificial tooth types | 0.98 | 0.406 | 0.596 | 0.619 | 2.391 | 0.057 | ||
| Artificial tooth arrangement function | 0.372 | 0.773 | 0.502 | 0.682 | 0.791 | 0.534 | ||
| Gingival formation function | 2.417 | 0.072 | 0.698 | 0.556 | 1.62 | 0.176 | ||
| Virtual articulator function | 1.091 | 0.357 | 0.613 | 0.608 | 1.069 | 0.377 | ||
| Relief and block out function | 0.463 | 0.709 | 1.903 | 0.135 | 1.424 | 0.233 | ||
| Category 4: AI functions in dental CAD software | Section 1: Crown design | Automatic crown shape design | 1.18 | 0.322 | 0.319 | 0.812 | 2.184 | 0.077 |
| Automatic margin line setting | 2.374 | 0.075 | 0.27 | 0.847 | 2.533 | 0.11 | ||
| Automatic occlusion adjustment | 1.017 | 0.389 | 0.632 | 0.596 | 2.72 | 0.035 | ||
| Automatic shade detection function | 1.331 | 0.27 | 1.598 | 0.195 | 1.303 | 0.275 | ||
| Automatic contact point formation | 1.556 | 0.206 | 0.531 | 0.662 | 2.524 | 0.222 | ||
| Section 2: Denture design | Automatic gingival formation | 2.014 | 0.118 | 0.558 | 0.644 | 2.048 | 0.094 | |
| Automatic artificial teeth placement | 0.272 | 0.846 | 0.792 | 0.502 | 0.558 | 0.693 | ||
| Automatic border line formation | 1.124 | 0.344 | 0.945 | 0.423 | 0.394 | 0.812 | ||
| Automatic occlusion adjustment | 0.735 | 0.534 | 2.672 | 0.042 | 0.367 | 0.832 | ||
| Automatic relief and block out | 1.84 | 0.146 | 2.424 | 0.071 | 3.179 | 0.161 | ||
| Category 5: AI-based dental CAD software | Section 1: Positive impact | Increase in sales | 1.619 | 0.191 | 2.111 | 0.104 | 0.169 | 0.954 |
| Increased work convenience | 3.403 | 0.021 * | 0.456 | 0.714 | 4.29 | 0.003 * | ||
| Increased productivity | 1.406 | 0.246 | 2.965 | 0.036 | 0.895 | 0.471 | ||
| Quality improvement | 0.248 | 0.863 | 0.888 | 0.45 | 0.798 | 0.53 | ||
| Marketing | 1.056 | 0.372 | 0.993 | 0.4 | 1.062 | 0.38 | ||
| Prospects for the dental field | 2.452 | 0.069 | 12.541 | <0.001 * | 0.775 | 0.544 | ||
| Labor cost savings | 0.471 | 0.703 | 1.727 | 0.167 | 0.413 | 0.799 | ||
| Section 2: Negative impact | Wages decreased | 3.48 | 0.092 | 2.21 | 0.092 | 1.642 | 0.171 | |
| Unemployment rising | 3.112 | 0.135 | 2.047 | 0.113 | 1.642 | 0.171 | ||
| Deterioration of dental technology | 0.933 | 0.428 | 1.679 | 0.177 | 0.274 | 0.894 | ||
| Decreased use of conventional workflow | 2.719 | 0.088 | 0.818 | 0.487 | 0.736 | 0.57 | ||
| Shrinking of the digitally vulnerable | 1.204 | 0.313 | 1.095 | 0.355 | 1.055 | 0.384 | ||
| Category 6: Requirements for purchasing AI-based dental CAD software | Price | 0.825 | 0.484 | 2.767 | 0.046 * | 1.625 | 0.175 | |
| UI/UX | 0.542 | 0.655 | 1.52 | 0.215 | 0.679 | 0.608 | ||
| Training in the use of software | 1.116 | 0.347 | 0.928 | 0.431 | 1.081 | 0.371 | ||
| Compatibility with existing software | 0.15 | 0.929 | 0.786 | 0.505 | 0.502 | 0.734 | ||
| Implementation of meaningful functions in clinical practice | 1.873 | 0.14 | 1.536 | 0.211 | 1.417 | 0.235 | ||
| Design speed and convenience | 1.527 | 0.213 | 2.809 | 0.044 * | 0.194 | 0.941 | ||
* Indicates significant differences within each category or section when using one-way ANOVA testing (p < 0.05).
4. Discussion
This questionnaire survey study aimed to evaluate the needs of dentists, dental technicians, dental hygienists, and dental-related workers in terms of dental computer-aided design (CAD) software and AI. The 57 survey items included in the six categories were found to significantly differ in terms of their perceived importance (Table 2, p < 0.05); therefore, the null hypothesis was rejected.
Previous studies have reported that the aesthetic outcomes and marginal fit of dental prostheses can vary depending on the dental CAD software used in the design process [1,2]. Therefore, dental personnel have no choice but to take design outcomes into consideration when selecting dental CAD software. The findings of the present study were in agreement with this, with the quality of the design outcome being identified as the most important factor to consider when purchasing dental CAD software (Table 2, p < 0.05).
Design convenience indicates the ability of dental personnel to reproduce the process of designing a dental prosthesis using specific dental CAD software systems [4,5]. In the present study, design convenience and reproducibility were found to be important factors in the prosthesis design process (Table 2, p < 0.05). A dental prosthesis is typically used to replace the function of a prepared tooth or to fill an edentulous area; therefore, the accurate fit of the prosthetic device in the affected area is important. The findings of the current study were in agreement with this, with the margin and border lines in the crown and denture design being considered crucial (Table 2, p < 0.05). A previous study reported that the margin line in crown design could differ according to the dental CAD software used [3]; therefore, manufacturers should take this into consideration when developing such software.
Although the application of AI technology can have a positive impact by reducing human errors and increasing convenience, there are concerns about the consequent decrease in manpower required [22,23,24]. The current study found that the increase in design convenience was considered a positive aspect of AI technology in dental CAD software, although dental personnel were also concerned about the consequent decrease in wages, increase in unemployment, and reduction in the need for the conventional workflow. However, it was suggested that AI-based dental CAD software can be purchased if it is economical, compatible with existing software, implements useful functions in clinical practice, and improves the speed and convenience of the design process (Table 2, p < 0.05).
The usability of dental CAD software varies considerably with the dental personnel under study [19], and previous studies have reported observing significant differences in the learning efficacies of different types of software [20]. The findings of the current study were in accordance with this, with the importance of certain elements in the survey differing between dental personnel (Table 3, p < 0.05). This could be attributed to the fact that dentists and dental hygienists pursue convenience when using dental CAD software to manufacture temporary dental prostheses. Therefore, dental CAD software intended for use by dentists and dental hygienists must have a faster design process and increased convenience through the use of tooth libraries. In contrast, dental technicians use dental CAD software in laboratories for manufacturing permanent dental prostheses, and this was reflected in the current study, in which they regarded functional diversity as an important factor (Table 3, p < 0.05). These results suggest that manufacturers should tailor the convenience and usability of dental CAD software to the target dental personnel.
According to previous studies on digital dentistry surveys [26,27], it was found that dentists have a positive attitude towards dental CAD/CAM technology [26]. Additionally, CAD software for dentistry is increasingly popular among dentists [27]. However, various CAD software packages for dentistry can produce different quality designs for dental prostheses [25]. In the present study, the design quality of CAD software for dentistry was identified as the most important factor (Table 2, p < 0.05). Previous studies have emphasized the importance of learning and the ease of use of CAD software for dentistry regarding appropriateness of use in dental clinics [19,20,21]. Similarly, in the present study, work speed (learning) and ease of use were identified as very important factors in dental clinical practice (Table 2, p < 0.05). Previous studies described the digital implant dentistry Ph.D. program, which includes habilitation with CAD software and provides education on the basics and applications of CAD software in dentistry [29]. However, many dentists still have limited knowledge of 3D design in dentistry, indicating a need for educational improvement in this area [27]. Therefore, the results of this present study can be used as evidence for the education of digital dentistry.
Understanding digital dentistry is increasingly important in clinical practice as digital technology continues to revolutionize the field [26,27]. The present study emphasizes the importance of understanding digital dentistry for the successful implementation of digital workflows in dental clinics. As digital dental technology continues to advance, it is essential for clinicians and researchers to stay up to date with the latest innovations and understand how to properly utilize these tools to improve patient care. The individuals who participated in this study were dentists and dental college professors who had a high understanding of the latest digital dental medical devices and had extensive experience in digital dentistry, which is widely used in dental clinics. The inclusion of experts from diverse backgrounds allowed the survey to support a comprehensive and multidimensional analysis of digital technologies.
The present study found that the importance of certain survey items varied significantly by age, dental personnel, and work experience groups. These findings suggest that when choosing dental CAD software, it is important to consider individual needs and preferences based on specific demographics, as well as factors such as branding, functional diversity, and design speed and convenience. The main limitation of the current study was that the sample included Korean dental personnel only, thereby limiting the generalizability of the findings. Further studies in more diverse populations are necessary to elucidate factors to be taken into consideration when using dental CAD software. The limitations of the present study, which only considered clinical experience without considering the training level or digital technology skills of the participants, are significant. The degree of expertise of healthcare professionals can impact their clinical decision making, as more highly trained professionals may have a greater knowledge base and better proficiency with complex cases. Additionally, the use of digital technology in healthcare is becoming increasingly prevalent, and the proficiency of healthcare professionals with such technology may impact the effectiveness of their clinical practice. Ignoring the experience and skills of healthcare professionals with digital technology could limit the potential benefits of these technologies in improving patient outcomes. Future research could investigate the impact of the degree of expertise and digital technology skills on clinical decision making and patient outcomes.
5. Conclusions
The present study assessed the importance of various factors in dental CAD software and found that design quality, design convenience, and reproducibility are important factors. Additionally, the present study found that certain features, such as automatic margin setting and artificial tooth arrangement, were considered more important than others. The present study also found that the importance of certain factors varied based on age, work experience, and dental personnel, with dentists and dental hygienists generally placing greater importance on design speed and convenience. Furthermore, the present study found that dental technicians assigned greater importance to functional diversity and dental prospects.
Author Contributions
K.S. contributed to study conception and design, analysis, and writing of the original draft; G.R.K., W.-G.K., W.K., S.-Y.K., J.-M.L., Y.-G.K., J.-W.K., S.-T.L., M.-U.J., H.-J.K., J.L. and J.-R.K. contributed to data acquisition and interpretation; D.-H.L. and K.-B.L. contributed to supervision and project administration. All authors have read and agreed to the published version of the manuscript.
Funding
This work was supported by a National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIT, no. 2022R1C1C2007040) and the Bio Industry Technology Development Program of the Korea Evaluation Institute of Industrial Technology (KEIT) funded by the Ministry of Trade, Industry and Energy (20018114).
Institutional Review Board Statement
The study protocol was approved by the Kyungpook National University Dental Hospital Institutional Review Board (approval no. KNUDH-2021-04-04-01). The study was carried out in accordance with relevant guidelines and regulations, and informed consent was collected from all participants.
Informed Consent Statement
Patient consent was waived for the present study because a survey evaluation method was performed.
Data Availability Statement
The datasets used and/or analyzed in the current study are available from the corresponding author on reasonable request.
Acknowledgments
The authors thank the researchers at the Advanced Dental Device Development Institute, Kyungpook National University, for their time and contribution to the study.
Conflicts of Interest
The authors declare no conflict of interest.
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Figure 1.
Demographic characteristics of survey participants.
Table 1.
Factor and reliability analysis.
| Items | Factor Analysis | Cronbach’s Alpha | ||||
|---|---|---|---|---|---|---|
| Factor Load | Communalities | Contribution Rate (%) | ||||
| Category 1: Considerations when purchasing dental CAD Software | Price | 0.887 | 0.982 | 29.741 | 0.913 | |
| Branding | 0.85 | 0.835 | ||||
| Diversity of functions | 0.831 | 0.994 | ||||
| UI/UX | 0.83 | 0.836 | ||||
| Easy learning | 0.819 | 0.973 | ||||
| Design quality | 0.796 | 0.969 | ||||
| Installed capacity | 0.791 | 0.972 | ||||
| Recommendation from acquaintance | 0.774 | 0.937 | ||||
| Wide range of scanners and CAM compatibility | 0.756 | 0.995 | ||||
| Need for high-performance computers | 0.745 | 0.879 | ||||
| Periodic update | 0.713 | 0.985 | ||||
| Category 2: Dental prosthesis design process | Design speed | 0.855 | 0.953 | 10.341 | 0.954 | |
| Design convenience | 0.852 | 0.984 | ||||
| Reproducibility of design form | 0.755 | 0.995 | ||||
| Variety of design tools | 0.751 | 0.966 | ||||
| Compatibility with various items of CAM equipment | 0.748 | 0.97 | ||||
| Category 3: Dental CAD software features | Section 1: Crown design | Parameter function | 0.853 | 0.983 | 23.095 | 0.975 |
| Margin line setting function | 0.678 | 0.971 | ||||
| Wax-up function | 0.659 | 0.971 | ||||
| Contact surface forming function | 0.593 | 0.953 | ||||
| Occlusal function | 0.593 | 0.991 | ||||
| Dental tooth library utilization | 0.589 | 0.975 | ||||
| Virtual articulator function | 0.586 | 0.998 | ||||
| Section 2: Denture design | Border line formation function | 0.582 | 0.994 | |||
| Choose from a variety of artificial tooth types | 0.581 | 0.901 | ||||
| Artificial tooth arrangement function | 0.571 | 0.986 | ||||
| Gingival formation function | 0.556 | 0.993 | ||||
| Virtual articulator function | 0.541 | 0.98 | ||||
| Relief and block-out function | 0.502 | 0.989 | ||||
| Category 4: AI functions in dental CAD software | Section 1: Crown design | Automatic crown shape design | 0.852 | 0.931 | 17.833 | 0.968 |
| Automatic margin line setting | 0.839 | 0.992 | ||||
| Automatic occlusion adjustment | 0.766 | 0.987 | ||||
| Automatic shade detection function | 0.636 | 0.992 | ||||
| Automatic contact point formation | 0.62 | 0.985 | ||||
| Section 2: Denture design | Automatic gingival formation | 0.783 | 0.971 | |||
| Automatic artificial teeth placement | 0.641 | 0.989 | ||||
| Automatic border line formation | 0.558 | 0.982 | ||||
| Automatic occlusion adjustment | 0.558 | 0.994 | ||||
| Automatic relief and block out | 0.537 | 0.955 | ||||
| Category 5: Impact of AI-based dental CAD software | Section 1: Positive impact | Increase in sales | 0.958 | 0.989 | 8.255 | 0.906 |
| Increased work convenience | 0.925 | 0.996 | ||||
| Increased productivity | 0.86 | 0.989 | ||||
| Quality improvement | 0.722 | 0.982 | ||||
| Marketing | 0.702 | 0.95 | ||||
| Prospects for the dental field | 0.561 | 0.957 | ||||
| Labor cost savings | 0.535 | 0.993 | ||||
| Section 2: Negative impact | Wages decreased | 0.53 | 0.959 | |||
| Unemployment rising | 0.53 | 0.982 | ||||
| Deterioration of dental technology | 0.525 | 0.977 | ||||
| Decreased use of conventional workflow | 0.521 | 0.851 | ||||
| Shrinking of the digitally vulnerable | 0.521 | 0.986 | ||||
| Category 6: Requirements for purchasing AI-based dental CAD software | Price | 0.591 | 0.973 | 5.008 | 0.945 | |
| UI/UX | 0.59 | 0.998 | ||||
| Training in the use of software | 0.589 | 0.947 | ||||
| Compatibility with existing software | 0.584 | 0.996 | ||||
| Implementation of meaningful functions in clinical practice | 0.511 | 0.983 | ||||
| Design speed and convenience | 0.507 | 0.997 | ||||
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Son, K.; Kim, G.R.; Kim, W.-G.; Kang, W.; Lee, D.-H.; Kim, S.-Y.; Lee, J.-M.; Kim, Y.-G.; Kim, J.-W.; Lee, S.-T.; et al. Requirements for Dental CAD Software: A Survey of Korean Dental Personnel. Appl. Sci. 2023, 13, 2803. https://doi.org/10.3390/app13052803
AMA Style
Son K, Kim GR, Kim W-G, Kang W, Lee D-H, Kim S-Y, Lee J-M, Kim Y-G, Kim J-W, Lee S-T, et al. Requirements for Dental CAD Software: A Survey of Korean Dental Personnel. Applied Sciences. 2023; 13(5):2803. https://doi.org/10.3390/app13052803
Chicago/Turabian StyleSon, KeunBaDa, Gyu Ri Kim, Won-Gi Kim, Wol Kang, Du-Hyeong Lee, So-Yeun Kim, Jae-Mok Lee, Yong-Gun Kim, Jin-Wook Kim, Sung-Tak Lee, and et al. 2023. "Requirements for Dental CAD Software: A Survey of Korean Dental Personnel" Applied Sciences 13, no. 5: 2803. https://doi.org/10.3390/app13052803
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