Effects of Periodontal Clinical Database Software on Resident Education During the COVID-19 Pandemic: A Prospective Observational Study | BMC medical training

study design

The present study is a prospective observational study to assess whether periodontal clinical database software and case-based learning method could effectively improve residents’ success in the SRT exam.

Figure 1 shows the training framework for periodontics residents. Dental residents (from Stomatology Hospital, Sun Yat-sen University, Guangzhou, China) volunteered and completed this training program (April 2020 to May 2021). All residents in the present study obtained a bachelor’s degree in stomatology. All residents treated periodontal patients Monday through Friday for 12 weeks under the supervision of clinical teachers (periodontists). In addition, students participated in a case-based learning course once a week. Data of periodontal cases, including intraoral photographs, periodontal examination chart, panoramic radiograph, periodontal prognosis evaluation and treatment plan, were recorded in PCDS (Figs. 2 and 3), which allows all students to learn the cases at home. At the start of the CBL classes, the teacher briefly introduced the case and raised several questions about the diagnosis, prognosis, and treatment plan. The residents discussed in subgroups and reported their answers to the questions group by group. Finally, the teacher analyzed the difficult points of the case and summarized the case.

Fig. 1

Training environment for periodontics residents

Figure 2
Figure 2

The Periodontal Clinical Database Software User Interface (first page)

Figure 3
picture 3

The Periodontal Clinical Database Software User Interface (Second Page) The second page includes Diagnosis, Treatment Plan, Periodontal Risk Assessment, Prognosis Analysis and Case Summary. Photographs are blurred for privacy protection

Residents were asked to take the online tests before and after the SRT. The training program includes 12 weeks of daily outpatient practice and a case-based learning course once a week.

The first page includes patient clinical data (basic information without real name, main complaint, medical history, intraoral examination results), intraoral photographs, panoramic x-ray and periodontal mapping of the upper jaw and lower. Photographs are blurred for privacy protection.

Sample size estimation

In the present study, the α significance level was set at 0.05, and the statistical power of the 1-β test was set at 95%. According to our preliminary study, the standard deviation was 0.17, while the average difference before and after training was 0.1. The sample size of this study estimated by the G*Power software [15] (version is 40 (Fig. 4). Therefore, the sample size for the present study was determined to be over 40.

Figure 4
number 4

Sample size estimation using G*Power software

The paired-samples t-test was used in this study. The significance level α and the statistical power of the 1-β test are set at 0.05 and 0.95 respectively. The effect size is calculated using data from the previous study (mean of difference = 0.1, standard deviation of difference = 0.17). The estimated sample size is 40.

Assessment of periodontal diagnostic and treatment capabilities

All students were asked to complete the online case-based exam within 30 minutes before and after the training program. Each examination includes two periodontal cases, which were used 1-3 years ago in the final examination of the standardized residency training program at Sun Yat-sen University Stomatology Hospital. Each case has several questions regarding the x-ray, diagnosis, prognosis, and treatment plan. The details of the composition of the exam are shown in Table 1.

Table 1 Composition of the examination before and after SRT

The questions are intended to assess students’ abilities in radiographic interpretation, diagnosis of periodontitis using the 2018 classification, diagnosis of other dental diseases, prediction of prognosis and development of a plan appropriate treatment.

statistical analyzes

Examination accuracy before and after SRT was expressed as mean ± standard deviation. The total exam accuracy rate (primary outcome measure) and the sub-item accuracy rate (secondary outcome measure) were analyzed using the paired-samples t-test. The Shapiro-Wilk test was performed to verify the normal distribution of the data. Bonferroni’s correction was used for several test adjustments. All data were analyzed by SPSS Statistics software (Version 22.0, IBM, USA), and p

Maria H. Underwood