In preclinical dental education, dental students are trained and evaluated through various hands-on training sessions. Maintenance of the amount of standard reduction according to prosthesis type is one of the significant evaluation factors. Furness et al.¹ have reported that the lack of occlusal surface clearance is a representative critical error that prevents adequate prosthesis production. Therefore, dental students require training in preclinical practice to become professional dentists. In this practical exercise, students are usually assessed by faculty members. During the evaluation process, students have complained about subjective evaluation, and conduct practice with the sole aim to achieve high test scores;² moreover, various studies have pointed out the limitations of subjective evaluation.³

Recently, the evaluation software of fixed dental practice evaluation using computer-aided design and computer-aided manufacturing (CAD/CAM) has been widely used.^4-10 Compared to traditional learning tools, color mapping for tooth preparation using scanning can provide useful information to students concerning the overall reduction amount. Renne et al.² have reported that evaluation using CAD/CAM software has an important advantage of enabling students to work independently. Use of software as a self-assessment tool by students allows learning independent of time. Several previous studies have reported that evaluation using CAD/CAM software is objective and accurate.^4-12 However, another report has indicated that evaluation of clinically critical errors is not possible using software alone as an evaluation tool.¹ In addition to digital assessment, students should be able to perform self-assessment on their own. Mays and Levine¹² have reported criteria of the Commission on Dental Accreditation (CODA)’s accreditation standards for dental schools of the requirement of graduates to demonstrate self-assessment ability including attaining professional competencies and professional values ??and capacities associated with self-directed lifelong learning, and stressed the importance of lifelong self-assessment even in dentists after graduation; since dental college students have difficulty with self-evaluation on their own, appropriate tools for self-evaluation in dental college practice are needed.¹³

A variety of tools are needed to ensure that students can conduct self-assessments efficiently throughout the preclinical fixed prosthodontics’ course. The purpose of this study was to compare the students’ ability to improve tooth preparation according to various self-assessment methods. The null hypothesis of the study is that there is no difference in tooth-removal improvement based on the three methods.

This study was approved by the Institutional Review Board of Kyungpook National University Dental Hospital (KNUDH-2018-03-004). A total of forty-eight sophomores in Kyungpook National University College of Dentistry who were registered as a part of the preclinical fixed prosthodontics course and agreed to participate in the experiment were included. In all students, tooth preparation of #19 was performed using a plastic resin tooth on a dental typodont (Nissin Dental Products, Kyoto, Japan) and a full gold crown was obtained in one hour. Subsequently, the students were randomly divided into three groups to evaluate their tooth preparation according to three different methods used; in total, forty-eight resin teeth were scanned using an intraoral scanner (CS3600, Carestream Dental, Atlanta, USA). One investigator (JungHan Kim) scanned all the teeth that were initially prepared, in order to reduce operator error. The scan data were saved in standard tessellation language (STL) file format and submitted for 3-dimensional (3D) analysis.

Self-assessment education was performed by all students after the first preparation was obtained. The participants were divided into three groups (visual, digital, and putty index self-assessment group) according to the self-assessment method used. After receiving detailed explanation of the self-assessment method by a skilled operator (JungHan Kim), each group was trained in self-assessment : The visual self-assessment group performed a traditional assessment method comprising visual assessment without teaching tools depending on the crown-reduction criteria for the gold crown which was taught at class (Fig. 1A); the digital self-assessment group conducted digital assessment with color difference mapping after receiving preliminary education on analysis of digital evaluation data (Fig. 1B) since they had not received prior education on this topic in the dental college classroom; the putty index self-assessment group conducted self-assessment using the putty index, which is widely used in the fixed prosthodontics’ course (Fig. 1C). After completion of self-assessment based on the different methods using the same typodont condition of the first preparation, the second tooth preparation of #19 was performed by the students. Subsequently, all the prepared teeth were scanned by one operator with the intraoral scanner in the same manner as that for the first tooth preparation, and the scan data were saved in the STL file format for 3D analysis.

In order to evaluate the specificity of improvement of the different groups, the degree of development was evaluated as follows. The unprepared tooth (# 19) was scanned using the intraoral scanner to obtain the STL file (Fig. 2A). The STL file of the prepared tooth (Fig. 2B) was superimposed with the STL file of the unprepared tooth using 3D analysis software (Geomagic control X, Rock Hill, South Carolina, USA) (Fig. 2C). Only the under subsections of the dental typodont tooth (# 19) were correctly superimposed by optimal alignment process (best-fit alignment) (Fig. 2C). After superimposition, the three cusps of the functional cusp, two cusps of the non-functional cusp, and four axis walls were used as measurement points; the reduction amount at each point was measured (functional cusp: red points, non-functional cusp: purple points, axis wall: green points) (Fig. 2D). The selected points were measured for the distance between the prepared and unprepared teeth (Fig. 2D). All measurements were performed in the same way for both primary and secondary tooth preparations. The amount of reference criteria of the functional cusp slope was set to 1.5 mm, while its non-functional cusp slope and the axial wall were set to 1.2 mm and one mm, respectively. For the purpose of this study, attaining values closer to criteria reduction at nine points reflected increasing student’s ability to prepare the tooth.

All data were analyzed using statistical software (IBM SPSS Statistics v23.0; IBM Corp, Armonk, New York, USA) (α = 0.05). Wilcoxon signed rank test was used to measure whether there was improvement of the student’s tooth preparation for each assessment method. Kruskal-Wallis H Test was used to determine the difference among the three methods.

The three self-assessment methods showed statistically significant differences (P < 0.001). Tables 1 to 4 show the reduction errors (the difference between the actual reduction and the criteria value of reduction) before and after the self-assessment. And the tables confirmed that there was a significant reduction in reduction error through self-assessment. The results of each method were compared with four criteria of the functional cusp slope (Table 1), non-functional cusp slope (Table 2), axial walls (Table 3), and total reduction (Table 4).

First, in the functional cusp slope, with criteria value of 1.5 mm, the reduction error value of visual self-assessment was 0.4521 mm in the first preparation and 0.3574 mm in the second preparation. The mean value was decreased, and there was no statistically significant difference (P = 0.31). In the second group of digital self-assessment methods, the reduction error value was 0.4464 mm in the first preparation and 0.3943 mm in the second preparation after the evaluation. The mean value was decreased, and there was no statistically significant difference (P = 0.063). In the third group of Putty index self-assessment method, the mean reduction error value was 0.4552 mm in the first preparation and 0.2966 mm in the second preparation, with statistical significance (P = 0.017).

With regard to the non-functional cusp slope, with a value of 1.2 mm, the reduction error value of visual self-assessment was 0.3262 mm in the first preparation and 0.4410 mm in the second preparation, with statistical significance (P = 0.03). In the second group of digital self-assessment methods, the reduction error value was 0.3997 mm in the first preparation and 0.3526 mm in the second preparation after the evaluation. The mean value was decreased, without significant difference (P = 0.94). In the Putty index self-assessment method, the reduction error value was 0.3158 mm in the first preparation and 0.3004 mm in the second preparation after the evaluation, and there was no statistically significant difference (P = 0.94).

With regard to the axial walls, with a criteria value of 1.0 mm, the reduction error value of visual self-assessment was 0.4307 mm in the first preparation and 0.3993 mm in the second preparation. The mean value was decreased, with no statistically significant difference (P = 0.084). In the second group of digital self-assessment methods, the reduction error value was 0.4783 mm in the first preparation and 0.3444 mm in the second preparation after the evaluation. The mean value was decreased with statistical significance (P = 0.046). In the Putty index self-assessment method, the reduction error value was 0.4365 mm in the first preparation and 0.3383 mm in the second preparation after the evaluation, with statistical significance (P = 0.018).

Finally, with regard to the visual self-assessment method, the reduction error value of total reduction at a criteria value of 1.0 mm was 0.4146 mm in the first preparation and 0.3946 mm in the second preparation; there was no statistically significant difference (P = 0.319). In the second group of digital self-assessment methods, the reduction error value was 0.4502 mm in the first preparation and 0.3628 mm in the second preparation. The mean value was decreased, with statistical significance (P = 0.018). In the third group of putty index self-assessment method, the reduction error value was 0.4159 mm in the first preparation and 0.3160 mm in the second preparation, with statistical significance (P = 0.002).

Based on the statistical results of this study, the null hypothesis was rejected. There was a difference in the degree of improvement after students’ tooth preparation, according to the three self-assessment methods. In the first group of visual evaluation, the tooth preparation improvement was statistically significant only in the comparison using the axial wall as a reference point. Non-functional cusp slope indicated a tendency of increase in the amount of preparation. Overall, visual assessment without any self-assessment tools is not expected to improve the ability to prepare the tooth. Even a skilled clinician is unable to analyze the amount of reduction using only his or her naked eyes. Therefore, visual assessment without any tools may not be suitable for continuous self-assessment in sophomore dental students.

The second group of digital self-assessment using color difference mapping showed statistically improved results of the axial walls and total reduction criteria. Digital assessment through color difference mapping that expresses over-reduction and under-reduction based on color standard, is expected to show improved performance for all criteria, because it provides the total amount of reduced teeth rather than normal 2D-images. However, in this study, we observed improved results for only two of the four criteria. These results suggested that students were not familiar with digital methods.

The third group of putty index showed statistically improved results for criteria of the functional cusp, axial wall, and total reduction. The results indicated the most improved tooth preparation ability among the three approaches. Unlike the digital method, putty index only reflects the amount of reduction in a specific section. Despite these drawbacks, this group attained highest improvement, which could be explained by the fact that students were already familiarized with using putty index in the fixed prosthodontics course before participating in the experiment.

Digital-based color difference mapping is not a regular self-assessment tool used in fixed prosthodontics’ courses, and all students received training of one hour’s duration before performing self-assessment. Zitzmann et al.¹⁴ reported that students who were initially introduced to both digital and traditional methods simultaneously, learned the techniques easily and preferred the digital procedure; moreover, achieving a certain level of skill took a shorter time under the digital method, which indicates that digital education should be introduced early in the curriculum of dental schools.¹⁴ Further study including students exposed to putty index and digital color difference mapping at the same rate is necessary to compare the improvement of tooth preparation abilities according to the two methods.

And the limitation in presented study suggest that because the participants are students, the variation in the tooth preparation ability and the number of exercises can be much larger than the variation in the three self-evaluation methods. Therefore, further study is needed according to the variation of tooth preparation ability and the number of exercises of each student.

Within the limitations of our study, students showed significant differences in improvement of tooth preparation ability according to the three self-evaluation methods used. In addition, self-assessment using the putty index showed the highest level of improvement among the three methods. Digital self-assessment also revealed the students’ improved tooth preparation abilities.