# Knowledge in Oral Infectiology and Antibiotic Stewardship of French Dental Students: A National Cross-Sectional Survey

Marie-louise Constant, Antoine Kimmoun, Alexandre Baudet, Benjamin

Lefèvre, Nathalie Thilly, Maïa Simon, Julie Guillet-Thibault

► To cite this version:

Marie-louise Constant, Antoine Kimmoun, Alexandre Baudet, Benjamin Lefèvre, Nathalie Thilly, et al.. Knowledge in Oral Infectiology and Antibiotic Stewardship of French Dental Students: A National Cross-Sectional Survey. European Journal of Dental Education, 2025, 10.1111/eje.13092 hal-05076930

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22

**Abstract**

23 **Introduction**: Several studies highlighted a lack of knowledge of dentists concerning antibiotic stewardship. The objectives of this study were to evaluate dental student's level of knowledge in infectiology and antibiotic stewardship, and to identify factors associated with a high level of knowledge.
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27 **Materials and methods**: A cross-sectional national multicenter survey was conducted in 2022-2023 through a self-administered and internet-based questionnaire. A knowledge score (out of 34) was calculated for each included student based on their questionnaire results. Hierarchical clustering methods were used to identify clusters of students according to their knowledge score. This approach highlighted distinct score levels. A logistic regression model was then applied to associate specific factors with these levels. The association between the cluster of students with the highest knowledge and the characteristics of the students and their faculties was assessed using logistic regressions.
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36 **Results**: A total of 415 students were included. Two clusters were identified: the cluster "average level of knowledge" included 290 (70%) students (median knowledge score: 26/34, IQR: 24;27), while the cluster "high level of knowledge" grouped 125 (30%) students (median knowledge score: 30/34, IQR: 29;32). Mandatory courses and multiple learning modalities were associated with higher knowledge.
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41 **Conclusion**: French dental students seem to have a high knowledge in infectiology and antibiotic stewardship, as evidenced by the median knowledge score of each cluster, which are objectively high compared to the maximum of 34. We identified several factors associated with a higher knowledge that might help conceiving learning modalities standardized recommendations.
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**Keywords**

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Cluster analysis, dental education, antimicrobial stewardship, students, knowledge

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**In brief:**

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- This is the first French national study to evaluate dental students' knowledge in infectiology and antibiotic stewardship.

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- This study will guide the future standardization of infectiology courses at a national level. These findings could, therefore, be implemented in the policy for curriculum development in dental education.

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- A hierarchical clustering method was used to identify distinct score levels. In this study, a logistic regression model associated mandatory courses with the cluster "high level of knowledge".

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59 **Introduction**

60 Antibiotic resistance is a global public health issue highlighted by the World Health
61 Organization (WHO) since 2014¹. Without preventative measures, it is estimated that
62 by 2050, antibiotic resistance could become the world's primary cause of death with
63 10 million deaths per year.² Antibiotic resistance is accelerated by unnecessary (i.e.
64 prescribing antibiotics in the absence of a bacterial infection or appropriate medical
65 indication) and inappropriate antibiotic use (i.e. prescription of antibiotics that does not
66 respect optimal dosage, duration or does not target the specific bacteria). These two
67 kinds of misuses are frequently encountered in dental practice and contribute to the
68 increase of antibiotic resistance.³ It is well established that the treatment of
69 odontogenic infections primarily relies on surgical intervention. However, in case of
70 systemic involvement, the use of antibiotic therapy is recommended. Yet, the use of
71 these antibiotics in dentistry, in case of odontogenic infections, has been linked to the
72 development of antibiotic resistance. Notably, penicillin is the first-line antibiotic used
73 in dentistry and is a key contributor to antibiotic resistance. These facts highlights the
74 need to adapt prescriptions to the clinical situation, its progression, and the
75 guidelines.⁴⁻⁶ Dentistry is the only medical specialty for which the quantity of antibiotic
76 prescriptions has increased in the last decades in France.⁷ Several studies showed
77 that dentists' prescriptions are often not in line with recommendations in Europe,⁸⁻¹⁰
78 and notably among French dentists where 11.6% prescribed inappropriate
79 antibiotics.¹¹ The lack of clear up-to-date guidelines, insufficient educational programs
80 on antibiotic prescription, and the absence of correlation between dentists' theoretical
81 knowledge and their prescribing practices (which relies more on experience than actual
82 knowledge) underscores the need to further investigate these factors to ensure proper
83 antibiotic use and combat antibiotic resistance.¹²
84 In France, dental education is based on 6 years of training, with the 6th year being the
85 final year of dental school. During this year, students are expected to possess the
86 highest level of knowledge, and as they can practice and prescribe as part of a
87 supervised internship, they already have a significant impact on public health.

88 However, non-standardized infectiology training in French dental faculties results in
89 knowledge gaps. Several comparative studies or cross-sectional surveys showed a
90 lack of knowledge of healthcare students concerning antibiotic stewardship. Most
91 students recognize antimicrobial resistance as a major public health issue, but on the
92 other hand, there are improper practices and a significant gap in knowledge. They
93 prescribe inappropriate antibiotics or use them preventively after extractions to avoid
94 post-treatment infections. It emphasizes the urgent need to improve education on
95 antibiotics, especially among young practitioners.¹³⁻¹⁵

96 The educational adaptation and optimization of the dental training in France is part of
97 the 2022-2025 National Strategy for the Prevention of Infections and Antimicrobial
98 Resistance in Human Health. This strategy is based on two main axes : infection
99 control, prevention and raising awareness about antibiotic stewardship, beginning by
100 stating the global knowledge of the healthcare students.¹⁶

101 A common core of competencies and minimal knowledge in prevention of infections
102 and antibiotic resistance for healthcare workers including dentists was published in
103 December 2022.¹⁷ Assessing dental students' current level of knowledge and
104 associated factors can be used to improve teaching of oral infectiology and antibiotic
105 stewardship, which could lead to better antibiotic use.¹⁸⁻²¹

106 The aims of this study were to evaluate final-year dental student's level of knowledge
107 in oral infectiology and antibiotic stewardship, and to identify students' and faculties'
108 characteristics associated to a high level of knowledge.
109 **Materials and methods**

110

111 **Study setting and population**

112 We targeted all 6th-year dental students across the 15 French dental faculties during
113 the 2022-2023 academic year. In France, the 6th year of study is the last year of
114 dentistry education, offering a comprehensive view of the complete odontology
115 training. In addition to their theoretical learning, they also had a 250-hours internship
116 supervised by a dental practitioner (mentor). These students start practicing and
117 prescribing, therefore they can have a significant impact on antibiotic stewardship and
118 public health. There were 1,285 6th-year students during the considered academic
119 year, averaging 86 students per faculty, ranging from 32 to 210. In France, each dental
120 faculty have an antibiotic resistance mission manager, responsible for communication,
121 learning, and research on antibiotic resistance. They were appointed by the deans of
122 each faculty with the aim of reforming and improving programs in infectious diseases,
123 as well as standardizing knowledge at a national level. In the context of the present
124 study, they helped the connection between the study investigator and the 6th year
125 students from each faculty.

126 **Survey design and data collection**

127 A cross-sectional national multicentre survey was conducted from December 6, 2022
to February 1, 2023, through a self-administered and internet-based questionnaire
128 hosted on LimeSurvey®.
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130 The development of the 34-item online questionnaire was based on a literature
131 review,¹⁸⁻²² antibiotic recommendations,²³ and the basic knowledge a last-year student
132 should have in antibiotic stewardship according to the modalities knowledge
133 assessment. The questionnaire was developed and validated by a multidisciplinary
group including two hospital and private dentists, a last-year dental student, two methodologists and an infectious disease specialist. Constructed specifically for this study, its scientific validity has been examined. In terms of content, the questionnaire resumes all relevant and essential aspects of oral infectiology and antibiotic stewardship, including recent and fundamental knowledge. It was based on five topics: (i) characteristics of the student and his mentors' (e.g. age and activity) (5 items), (ii) his/her knowledge regarding antimicrobial resistance epidemiology (8 items), (iii) general infectiology (10 items), (iv) antibiotic prescribing recommendations (11 items), and (v) five clinical cases (assessment of knowledge with five clinical vignettes exploring different area of knowledge: infection prevention, preoperative prescriptions, periodontal disease, facial trauma) (table S1). A pre-test was conducted by all members of the multidisciplinary group, and the questionnaire was validated regarding the scientific concepts discussed prior to the pilot test, which was pilot-tested by two dentists to assess its clarity and its relevance.

The students received an e-mail from the antibiotic resistance mission manager of their faculty, inviting them to take part in the study. The mission manager also answered another questionnaire to describe the different learning modalities of his/her faculty considering topics related to antibiotic resistance, and the volume of these courses. E-mail reminders were sent during the third week of December, first and third week of January, and an ultimate reminder on the January 30, 2023.

Every students of each faculty received their e-mail and e-mail reminders as described chronologically above, confirmed through regular communication with the mission manager.
157 **Statistical analyses**

158 Categorical variables were presented as numbers and percentages, while continuous
159 variables were presented as means with standard deviations or medians with
160 interquartile ranges (IQRs). Students were included in the analyses if they completed
161 at least the topics (i) and (ii) of the questionnaire (i.e. if they answered at least the first
162 questions of knowledge). A level of knowledge was estimated for each student using
163 a knowledge score calculated from their questionnaire results. A correct answer was
164 equal to one point, a wrong answer to zero. If a student partially responded, its score,
165 based on the proportion of answered questions, was then scaled to a score out of 34.
166 This adjustment ensured their inclusion in the appropriate clusters, based on a
167 standardized score out of 34.

168 Hierarchical clustering was performed using Ward's method to identify groups of
169 students according to their knowledge score (which reflects their level of knowledge).
170 Bivariate logistic regression analysed the associations between the cluster with "high
171 level of knowledge" and the students' and faculties' characteristics (determined a priori
172 by consensus from authors). Variables, with p-values < 0.10 in bivariate analyses, were
173 considered as candidates for the multivariable logistic regression. Multicollinearity
174 between the candidate variables was assessed before model construction. A backward
175 stepwise approach was applied to identify the most relevant variables based on their
176 contribution to minimizing the Akaike Information Criterion (AIC) and their statistical
177 significance (p<0.05). The selected variables were then included in the final
178 multivariable logistic regression model to identify independent associations. Odds
179 ratios (ORs), adjusted ORs (aORs) and 95% confidence intervals (95%CIs) were
180 reported.
181 Sensitivity analyses using alternative clustering methods (k-means and k-medoids
182 clustering method) were performed to ensure the robustness of the results.
183 Significance was set at p < 0.05. Analyses were performed using R® software version
184 4.3.1.

185 **Ethics**

186 Department of data protection of the University of Lorraine confirmed that no identifying
data were collected, therefore no consent was required. Data from the LimeSurvey
187 questionnaire was only stored on our provider server (University of Lorraine server).
188 Ethical approval was not required for this study according to the current French
189 legislation.
190
191 **Results**

192

193 **Characteristics of students and faculties**

194 Among the 1,285 final-year students of dentistry registered during the 2022-2023
195 academic year, 503 began the questionnaire and 415 students completed at least the
196 topics (i) and (ii) and were included in this study (response rate: 32%). For one faculty,
197 no student answered. The mean age of respondents was 24 ± 2 years old, and 288
198 (69%) were females.

199 Every faculty had a validation test at the end of the semester and had about 39 ± 14
200 hours of classes on microbiology with bacteriology and virology courses, infection
201 prevention and control, antibiotic therapy, clinical cases and/or practical sessions of
202 infectiology. Each faculty had different learning modalities. Among the 14 faculties
203 responding, 3 (21%) had lecture courses only, 6 (43%) had practices, supervised
204 learning and lecture courses, 2 (14%) had practices, supervised learning, lectures and
205 case reports, 1 (7%) had lecture courses and e-learning, and 1 (7%) had all these
206 modalities.

207 All these characteristics were then collected to explore potential associations with
208 knowledge levels. The selected variables were included in the multivariate analysis to
209 assess their impact on the knowledge scores.

210 **Students' level of knowledge**

211 The median knowledge score of students was 27/34 (IQR: 25-29). The detail of the
212 response to each question included in the knowledge score is available in
213 Supplementary data S1 (table S1). This table results indicate a generally good
214 understanding of basic concepts such as antimicrobial resistance epidemiology, 391
215 students (94%) were aware that France was one of the biggest antibiotic prescriber in
Europe and 329 (79%) considered the antibiotic resistance as a worldwide threat. In infectiology, gaps remain on specific topics like asymptomatic osteonecrosis: 187 (45%) did not consider useful to prescribe antibiotics in this case, which was the good practical decision. Regarding antibiotic prescription recommendations, 132 (31%) students confirm awareness considering antibiotic prescription durations. Regarding clinical cases, 155 (37%) had the good medical approach in case of facial trauma. These findings highlight both strength and weaknesses in students' knowledge, particularly in applying theoretical knowledge to clinical scenarios.

## Cluster analysis

Two clusters were identified as the optimal number of clusters for our sample, using the elbow method. This method was applied by calculating the within-cluster sum of squares (WCSS) for a range of cluster numbers (from 1 to 10). A graph was plotted to visualize the results. The point of inflection on this graph, observed at k=2, indicated that two clusters were optimal to provide a simple model and to explain the variance. Additional analysis confirmed this choice by assessing the inertia relative to other cluster numbers (like k=3). This analysis showed that using two clusters provided the most meaningful grouping of the data.

The cluster 1 "average level of knowledge" included 290 students (70%) with a median knowledge score of 26/34 (IQR: 24-27) with scores ranging from 8 to 27. The cluster 2 "high level of knowledge" included 125 students (30%) with a median knowledge score of 30/34 (IQR: 29-32) with scores ranging from 27 to 34.

**Figure 1** (histogram of knowledge scores by cluster with ward clustering method) illustrates the knowledge score distribution across the clusters, revealing a minor overlap around the score 27. This overlap represents a natural transition zone between individuals with similar knowledge levels assigned to different clusters. This overlap
might not invalidate the robustness of the clustering solution, as the choice of two clusters is then confirmed through sensitivity analyses using other clustering methods. All of which identified two clusters as the most appropriate representation of the data.

**Figure 2** (Histograms of the cluster-specific distributions of score) presents the distribution of scores for each cluster separately. The cluster "average level of knowledge" presents scores around the median range, with the majority of students scoring between 24 and 27. In contrast, the cluster "high level of knowledge" is characterized by a higher overall knowledge level.

**Table 1** presents the characteristics of students and faculties according to the two clusters. Most students were females (211, 73%) in the cluster "average level of knowledge". Only 11 (4%) students in this cluster had mandatory courses. In the cluster "high level of knowledge", 77 were female students (62%) and 14 students (11%) had mandatory courses.

Table 2 and 3 present the factors analysed in the bivariate and multivariate models respectively, derived from the individual questionnaire responses. These factors were then associated with student's knowledge scores.

**Table 2** shows that mandatory courses (OR 3.20, 95%IC 1.41-7.26, p=0.005) and multiple learning modalities (OR 1.14, 95%IC 1.01-1.28, p=0.029) were significantly associated with higher level of knowledge, along with gender (OR 1.66, 95%IC 1.06-2.56 p=0.024) and the mentor's rural activity (OR 1.56, 95%IC 1.00-2.38, p=0.047). These significant variables were then included in the multivariate model, which achieved an AIC of 496.57. The final model identified three variables significantly associated with a high level of knowledge: mandatory courses (aOR 3.20, 95%IC 1.40-7.49, p=0.006), multiple learning modalities (aOR 1.15, 95%IC 1.02-1.29, p=0.025), and gender (aOR 1.72, 95%IC 1.08-2.70, p=0.021), as shown in **table 3**.
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Together, these results underline the importance of curricular design and pedagogical strategies in influencing knowledge acquisition.

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## Sensitivity analyses

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We used two additional clustering methods, k-means and k-medoids, to validate results. Both methods produced close and coherent results, represented in the **tables S2 to S5**. The clustering process obtained the same distribution of students between clusters as observed with the main Ward method, supporting the consistency of the results. The gender variable had significant associations level in both univariate and multivariate analyses for all methods. Similarly, mandatory courses demonstrated high relevance in both sensitivity analyses. However, the "learning modalities" variable was excluded from the stepwise multivariable analysis in the k-means and k-medoids methods. This exclusion is linked to potential collinearity with "mandatory courses" in these clustering models. Despite this, the consistency of results across methods reinforces the robustness of the main findings regarding the importance of "mandatory courses" in high level of knowledge.

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## Score gradient for learning modalities

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A score gradient has been identified descriptively, without formal statistical testing. The purpose was to associate the main knowledge score of each faculty with the proportion of mandatory courses offered, explaining an initial exploration of this potential relationship. There were 5 faculties that didn't have any mandatory courses, their median knowledge score was 26/34 (IQR: 24-27). Eight faculties had at least one mandatory course and reached a median knowledge score around 27/34 (IQR: 25-28). Finally, only one faculty offered a majority of mandatory courses, and obtained a median score of 29/34 (IQR: 28-30). This finding supports the integration of mandatory

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290 courses as potential strategy to improve students' academic and professional

291 performances.

292
293 **Discussion**

294 This cross-sectional survey conducted among final-year French dental students
295 highlighted that the global student's level of knowledge in infectiology and antibiotic
296 stewardship was satisfying (median: 27/34). Some factors appeared associated with a
297 high level of knowledge.

298 Having mandatory courses during the infectiology and microbiology training multiplies
299 by 3.2 the chance to have a high level of knowledge. Other studies among the medical
300 students showed that setting up mandatory courses, with interactive learning and
301 practices improves knowledge and comfort levels towards encountering complicated
302 and polypathological patients.²⁴,²⁵ Students following mandatory courses were better
303 prepared for clinical situations. This can illustrate the need to shift to standardized and
304 mandatory courses in infectiology learnings.

305 Male students have a 1.72 higher chance of being in "the high level of knowledge" than
306 female ones. This finding reveals a notable gender disparity. Similarly, a study
307 conducted among French dentists showed male had better antibiotic prescription
308 practices.²⁶

309 The bivariate analysis highlighted a significant association between the multiple
310 learning modalities and the level of knowledge. Among faculties which proposed
311 different types of learning modalities like practices and supervised learning in addition
312 to lectures, 27% of students had a high level of knowledge when 19% had an average
313 level of knowledge. Wasson et al. had also showed that having additional learning
314 modalities and not only lectures can increase the student's level, interest, and
315 appropriateness in his use of antibiotics.²⁴ We can find this same result in an American
316 study, which analysed the student's preference concerning different modalities of
learning infectiology. They needed standardized stewardship with practical and
interactive learning experiences. That way, they could apply their skills and get
feedbacks on their way to prescribe and communicate with the patient. They want to
understand the rational reasons behind the recommendations, specifically to be able
to argue and convince other health care professionals in the setting of conflict.²⁵
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However, this need of standardized and improved learning experiences must be
understood in the specific context of French education. The fight against antibiotic
resistance is a public health priority, as described in the 2022-2025 National Strategy
for the Prevention of Infections and Antimicrobial Resistance in Human Health. The
government emphasizes the importance of educating young practitioners. This study
provides an opportunity to assess their knowledge, and the teaching methods used in
France. In higher education, courses are rarely mandatory or interactive, which may
limit the educational institution's ability to meet students' knowledge needs. Improving
educational strategies is a key of the national infection prevention strategy. In France,
there is a strong commitment to this strategy, reflected in the collective effort by
faculties to enhance the training of young practitioners.
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The French students had some difficulties regarding clinical cases and specifically
handling a facial trauma (only 37% had the good approach). This could be explained
by a lack of direct exposure to such cases during their training and insufficient
confidence. For example, most students administer antibiotics after a trauma, possibly
due to fear of complications or an unclear understanding of the severity of the situation,
leading them to overprescribe antibiotics as a protective measure and for
reassurance.¹² The same observation applies to the management of non-infected
osteonecrosis: only 45% adhered to the recommendations and did not systematically
prescribe antibiotic therapy. Osteonecrosis can be concerning for a dental student and
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young dentist who is unfamiliar with these kinds of cases. Furthermore, an insufficient
knowledge of the guidelines can cause these types of overprescription.

Nevertheless, they had good knowledge in epidemiology, infectiology generalities and
antibiotic recommendations for the general population. But when it comes to patients
with infectious risks, such as managing those at risk of infective endocarditis, students
are more likely to prescribe antibiotics even when recommendations advise against it.

Similarly, deficiencies in terms of dosage and choice of antimicrobial agents have been
identified.

This analysis of infectiology education across dental schools highlights the variability
in the number of teaching units, hours, and the scope of topics covered. The mission
manager of each faculty described their educational programs towards one of the
questionnaires. While some programs dedicate significant time to microbiology and
hygiene, others adopted more diverse subjects such as antibiotic resistance, oral
infections and therapeutic strategies. A few curricula stand out for integrating
interdisciplinary seminars or innovative teaching methods. However, this heterogeneity
suggests a need for more standardized and unified content and pedagogical
approaches in infectiology education. Based on these observations, several key for
improvement can be proposed for the harmonization of the core content. A majority of
the faculties include essential topics such as general microbiology or hygiene, but there
is a real need to include in all programs, some subjects that are not included in every
faculty curriculum, like general and oral infectiology, prevention of infections and
guidelines. Enhancing the focus on oral-specific infections and their management,
which remain underdeveloped in certain curricula, is crucial.

This study presents a few limitations. Only 32% of the French final year students in
dentistry were included in this study. Some similar publications had a participation rate
around 30% on a non-national level.²⁴,²⁵ This low participation rate, combined with the exclusion of one faculty due to no responses, may have introduced selection bias, restricted the representativeness of the findings and reduced the statistical power to identify subtle differences. The participation was voluntary, this may be a source of self-selection bias. The students who answered the questionnaire might be more interested in antibiotic resistance and antibiotic stewardship than average. It may impact the generalizability of these findings to all French dental students. The sample might overrepresent individuals with a higher knowledge or motivation regarding these topics. Future studies could organize mandatory participation to ensure a more representative sample to the target population. Each student from 13 faculties answered directly by internet, one faculty conducted the questionnaire directly with the entire class, that represents 21% (87 students) of our population: 71% were grouped in the cluster "average level of knowledge", in line with the global result (70% of this study were grouped in the cluster "average level of knowledge"). The students answering at home have access to different resources. That might have artificially improved their knowledge score. However, knowing where to look and find the right information is also a guarantee of good practice.

Nevertheless, this study was to our knowledge the first study conducted on a national level, with 14 French faculties out of the 15 existing ones, with a participation rate comparable to other non-national studies evaluating the same subject.²⁴,²⁵ Using a questionnaire developed by an expert group specifically for this study.

The present study shows that French students have good knowledge of antibiotics, yet the practitioners' prescriptions' quality is low.²⁶ This may be due to unconsciousness about antibiotic resistance despite proper training, or to a lack of up-to-date training of dentists in practice for many years. Even with infectiology education, students might
lack awareness about their role in antibiotic resistance. More than half of the students believe that dentists account for less than 10% of antibiotic prescriptions worldwide. This indicates a lack of awareness regarding the impact that dentists might have on antibiotic prescriptions and the development of antibiotic resistance.

This study highlights the necessity of implementing mandatory courses for better knowledge and improved patient care regarding infectiology and antibiotic stewardship. These mandatory courses should be developed with content specifically designed to address the current gaps in knowledge regarding these topics. The findings of this study also revealed disparities in the content of infectiology education across faculties, emphasizing the need of harmonisation. All these findings will be discussed and used by faculty representatives to identify leverage points for improvement. In terms of odontogenic infections, studies have underlined the importance of aligning educational programs with evidence-based guidelines to improve prescription habits and reduce the development of resistance⁴,⁶. This initiative could reduce disparities between students, improve their confidence, and enhance awareness, aligning with the French national strategy.

However, awareness about antibiotic resistance and the role of French and international dentists in the development of theses resistances is crucial for enhancing prescription practices and education regarding antibiotic stewardship. Students and future practitioners must therefore strengthen their knowledge with a good sense of responsibility.

## Conclusion

Dental students who had mandatory courses in their faculty had a high level of knowledge about antibiotic stewardship. The organization and various teaching
modalities are specific to each faculty. However, this study clearly demonstrates that
certain teaching modalities are more effective than others, potentially serving as the
foundation for adjustments in teaching methods. Future efforts should focus on
harmonizing curricula while ensuring the quality of course content.

To work on these disparities, the establishment of a standardized, evidence-based
national program is essential. This program should also integrate, in addition to
mandatory courses, oral-specific infections and their management contents.

These measures have a large public health implication. Dental practitioners play an
important role in combating antibiotic resistance through intelligent use of antibiotics
and the prevention of healthcare-associated infections. By educating students with
robust knowledge and skill, it may contribute to this global health challenge. Academic
institutions must prioritize these reforms to align educational goals with the need to
stop antibiotic resistance at both national and international levels.

## Data Availability Statement

Due to the nature of the research and ethical reasons, supporting data is not available.
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17. Ministère de la santé. Stratégie nationale 2022-2025 de prévention des infections et de l'antibiorésistance. Santé humaine 2022. https://sante.gouv.fr/IMG/pdf/strategie_nationale_2022-2025_prevention_des_infections_et_de_lZOAntibioresistance.pdf. Accessed August 25, 2023.

482

483

484

485

486

487

488

489

490

18. SF2H, CMIT. Socle commun de compétences et connaissances minimales en prévention des infections et de l'antibiorésistance pour les professionnels de santé des filières maïeutique, médecine, odontologie, pharmacie, soins infirmiers 2022. https://www.sf2h.net/k-stock/data/uploads/2023/03/SocleCompetences-2022.pdf. Accessed August 25, 2023.

491

492

493

19. Akba A, Alquwez N, Alsolais A, Thazha S, Ahmad M, Cruz J. Knowledge about antibiotics and antibiotic resistance among health-related students in a Saudi University. Infect Dev Ctries. 2021;15(7): 925-933.

494

20. Holz M, Naavaal S, Stilianoudakis S, Carnico S, Byrne B, Myers G. Antibiotics and antimicrobial resistance: Evaluation of the knowledge, attitude, and perception among students and faculty within US dental schools. J Dent Educ. 2021 Mae;85(3): 383-391.

495

496

497

498

499

500

21. Huang Y, Gu J, Zhang M, et al. Knowledge, attitude and practice of antibiotics: a questionnaire study among 2500 Chinese students. BMC Med Educ. 2013;13:163.
22. Struzycka I, Mazinska B, Bachane T, et al. Knowledge of antibiotics and antimicrobial resistance amongst final year dental students of polish medical schools: a cross-sectional study. Eur J Dent Educ. 2019;23(3): 295-303.

23. ANSM. Prescription des antibiotiques en pratique buccodentaire. [Recommandations] 2011. https://ansm.sante.fr/uploads/2021/02/04/reco-prescription-des-antibiotiques-en-pratique-buccodentaire-septembre2011.pdf.

Accessed August 25, 2023.

24. Wasson M, Luther V, Armstrong W, et al. Skills, not just knowledge: infectious diseases (ID) fellows' recommendations regarding antimicrobial stewardship training. Clin Infect Dis. 2023; ciad358.

25. Back D, Haberstroh N, Sostmann K, et al. High efficacy and students' satisfaction after voluntary vs mandatory use of an e-learning program in traumatology and orthopedics- a follow-up study. J Surg Educ. 2014;71(3): 353-9.

26. Simon M, Pereira O, Constant ML, Guillet J, Pulcini C, Thilly N. Characteristics of dentists and patients associated with appropriate antibiotic prescriptions by French dentists: a cross-sectional study using Health Insurance databases. BMC Oral Health. 2023; 23(29).
<figure><img src="image_2.png" /><figcaption>**Figure 2.** Histograms of the cluster-specific distributions of score</figcaption></figure>

<figure><img src="image_3.png" /><figcaption>**Table 1.** Population characteristics according to clusters from Ward method (N=415)</figcaption></figure>
<table><thead><tr><th>Characteristics</th><th>Total Population<br>N = 415</th><th>Cluster 1<br>"Average level of<br>knowledge"<br>n = 290 (69.9%)</th><th>Cluster 2<br>"High level of<br>knowledge"<br>n = 125 (30.1%)</th></tr></thead><tbody><tr><td>Knowledge score<br>(/34)</td><td>27 (25-29)</td><td>26 (24-27)</td><td>30 (29-32)</td></tr><tr><td>Student's age (years old)</td><td>24 ± 2</td><td>24 ± 2</td><td>24 ± 2</td></tr><tr><td>Student's gender</td><td></td><td></td><td></td></tr><tr><td>Male</td><td>127 (31%)</td><td>79 (27%)</td><td>48 (38%)</td></tr><tr><td>Female</td><td>288 (69%)</td><td>211 (73%)</td><td>77 (62%)</td></tr><tr><td>Faculty</td><td></td><td></td><td></td></tr><tr><td>F 1</td><td>29 (7%)</td><td>21 (7%)</td><td>8 (6%)</td></tr><tr><td>F 2</td><td>72 (17%)</td><td>56 (19%)</td><td>16 (13%)</td></tr><tr><td>F 3</td><td>27 (7%)</td><td>14 (5%)</td><td>13 (10%)</td></tr><tr><td>F 4</td><td>11 (3%)</td><td>6 (2%)</td><td>5 (4%)</td></tr><tr><td>F 5</td><td>13 (3%)</td><td>6 (2%)</td><td>7 (6%)</td></tr><tr><td>F 6</td><td>19 (5%)</td><td>15 (5%)</td><td>4 (3%)</td></tr><tr><td>F 7</td><td>11 (3%)</td><td>7 (2%)</td><td>4 (3%)</td></tr><tr><td>F 8</td><td>35 (8%)</td><td>29 (10%)</td><td>6 (5%)</td></tr><tr><td>F 9</td><td>4 (1%)</td><td>4 (1%)</td><td>0 (0%)</td></tr><tr><td>F 10</td><td>20 (5%)</td><td>13 (4%)</td><td>7 (6%)</td></tr><tr><td>F 11</td><td>9 (2%)</td><td>6 (3%)</td><td>3 (3%)</td></tr><tr><td>F 12</td><td>NR</td><td>NR</td><td>NR</td></tr><tr><td>F 13</td><td>87 (21%)</td><td>62 (21%)</td><td>25 (20%)</td></tr><tr><td>F 14</td><td>25 (6%)</td><td>11 (4%)</td><td>14 (11%)</td></tr><tr><td>F 15</td><td>53 (13%)</td><td>40 (14%)</td><td>13 (10%)</td></tr><tr><td>Mandatory courses</td><td>25 (6%)</td><td>11 (4%)</td><td>14 (11%)</td></tr><tr><td>Additional non-mandatory<br>courses</td><td>400 (96%)</td><td>280 (97%)</td><td>120 (96%)</td></tr><tr><td>Learning hours (hours)</td><td>39 ± 13</td><td>39 ± 13</td><td>39 ± 8</td></tr><tr><td>Multiple learning modalities</td><td>149 (35%)</td><td>88 (30%)</td><td>61 (48%)</td></tr><tr><td>Mentor's age</td><td></td><td></td><td></td></tr><tr><td>Under 50<br>years old</td><td>137 (33%)</td><td>87 (30%)</td><td>50 (40%)</td></tr><tr><td>Over 50 years<br>old</td><td>278 (67%)</td><td>203 (70%)</td><td>75 (60%)</td></tr><tr><td>Mentor's activity</td><td></td><td></td><td></td></tr><tr><td>Rural</td><td>268 (65%)</td><td>192 (66%)</td><td>76 (61%)</td></tr><tr><td>Urban</td><td>147 (35%)</td><td>98 (34%)</td><td>49 (39%)</td></tr></tbody></table>
531 **Table 2.** Comparison of student's and learning characteristics between the two clusters

532 (identified by the Ward clustering method) – Bivariate analyses (N = 415 students).

533

<table><thead><tr><th rowspan="2">Characteristics</th><th rowspan="2"></th><th>Cluster "High level of knowledge"<br>versus Cluster "Average level of<br>knowledge"</th><th rowspan="2">p-value</th></tr><tr><th>Ref is average level of knowledge</th></tr><tr><th></th><th></th><th>Odds Ratio<br>(95% confidence interval)</th><th></th></tr></thead><tbody><tr><td>Student's age</td><td></td><td>0.96 (0.87-1.07)</td><td>0.435</td></tr><tr><td rowspan="2">Student's gender</td><td>Female</td><td>1 (reference)</td><td>-</td></tr><tr><td>Male</td><td>1.66 (1.06-2.56)</td><td><strong>0.024</strong></td></tr><tr><td rowspan="2">Mentor's age</td><td>Under 50 years old</td><td>1 (reference)</td><td>-</td></tr><tr><td>Over 50 years old</td><td>1.26 (0.82-1.95)</td><td>0.291</td></tr><tr><td rowspan="2">Mentor's activity</td><td>Urban</td><td>1 (reference)</td><td>-</td></tr><tr><td>Rural</td><td>1.56 (1.00-2.38)</td><td><strong>0.047</strong></td></tr><tr><td rowspan="2">Mandatory courses</td><td>None</td><td>1 (reference)</td><td>-</td></tr><tr><td>At least one</td><td>3.20 (1.41-7.26)</td><td><strong>0.005</strong></td></tr><tr><td rowspan="2">Additional non-<br>mandatory courses</td><td>None</td><td>1 (reference)</td><td>-</td></tr><tr><td>At least one</td><td>0.86 (0.29-2.56)</td><td>0.782</td></tr><tr><td>Learning hours</td><td></td><td>1 (0.99-1.01)</td><td>0.586</td></tr><tr><td>Multiple learning modalities</td><td></td><td>1.14 (1.01-1.28)</td><td><strong>0.029</strong></td></tr></tbody></table>

534 Bold indicates a p-value < 0.10.
535 **Table 3.** Comparison of student's and learning characteristics between the two clusters (identified by the Ward clustering method) – Multivariable analyses (N = 415 students).

<table><thead><tr><th rowspan="2">Characteristics</th><th rowspan="2"></th><th>Cluster "High level of knowledge"<br>versus Cluster "Average level of<br>knowledge"</th><th rowspan="2">p-value</th></tr><tr><th>Odds Ratio<br>(95% confidence interval)</th></tr></thead><tbody><tr><td rowspan="2">Student's gender</td><td>Female</td><td>1 (reference)</td><td>-</td></tr><tr><td>Male</td><td>1.72 (1.08-2.70)</td><td><strong>0.021</strong></td></tr><tr><td rowspan="2">Mentor's activity</td><td>Urban</td><td>1 (reference)</td><td>-</td></tr><tr><td>Rural</td><td>1.53 (0.97-2.38)</td><td>0.064</td></tr><tr><td rowspan="2">Mandatory courses</td><td>None</td><td>1 (reference)</td><td>-</td></tr><tr><td>At least one</td><td>3.20 (1.40-7.49)</td><td><strong>0.006</strong></td></tr><tr><td>Multiple learning modalities</td><td></td><td>1.15 (1.02-1.29)</td><td><strong>0.025</strong></td></tr></tbody></table>

538 Bold indicates a p-value < 0.05.
<table><caption>**Table S1: 34-item questionnaire and results for each item (N=415)**</caption><thead><tr><th>Items</th><th>Right answer</th><th>Number of students who responded well to this item (N=415)</th></tr></thead><tbody><tr><td>France is the country with the least use of antibiotics in Europe</td><td>False</td><td>391 (94%)</td></tr><tr><td>It is estimated that more than 5,500 deaths per year in France are attributable to antibiotic resistance.</td><td>True</td><td>352 (84%)</td></tr><tr><td>Less than 10% of antibiotics prescribed by French dentists are useless or inappropriate</td><td>False</td><td>332 (80%)</td></tr><tr><td>Less than 2500 patients develop each year in France an infection linked to a resistant bacterium according to a recent study</td><td>False</td><td>280 (67%)</td></tr><tr><td>Dentists are responsible for less than 10% of antibiotic prescriptions worldwide</td><td>False</td><td>228 (54%)</td></tr><tr><td>Antibiotic resistance is a source of a significant additional cost for health systems</td><td>True</td><td>376 (90%)</td></tr><tr><td>Someone can transmit an antibiotic-resistant bacterium to another individual, regardless of their state of health and even if the other one has never taken antibiotics in his life.</td><td>True</td><td>292 (70%)</td></tr><tr><td>Antibiotic resistance could, by 2050, become one of the main causes of death in the world</td><td>True</td><td>329 (79%)</td></tr><tr><td>Gram-positive bacteria are more present in the oral commensal flora of a healthy subject than Gram-negative bacteria.</td><td>True</td><td>279 (67%)</td></tr><tr><td>An antibiotic may be prescribed to treat a viral infection</td><td>False</td><td>362 (87%)</td></tr><tr><td>A focal oral infection is an infection localized to a distant organ, caused by an oral infectious focus</td><td>True</td><td>251 (78%)</td></tr><tr><td>A brain abscess can be caused by an oral infectious focus</td><td>True</td><td>325 (78%)</td></tr><tr><td>Spiramycine is an antibiotic</td><td>True</td><td>364 (60%)</td></tr></tbody></table>
<table>
  <tr>
    <td>Osteonecrosis of the jaws requires antibiotic therapy, even in an asymptomatic situation</td>
    <td>False</td>
    <td>187 (45%)</td>
  </tr>
  <tr>
    <td>Diclofenac is an antibiotic</td>
    <td>False</td>
    <td>355 (85%)</td>
  </tr>
  <tr>
    <td>An anti-inflammatory must always be combined with antibiotic treatment</td>
    <td>False</td>
    <td>354 (85%)</td>
  </tr>
  <tr>
    <td>Amoxicillin-clavulanic acid combines a penicillin with a beta-lactamase inhibitor</td>
    <td>True</td>
    <td>311 (75%)</td>
  </tr>
  <tr>
    <td>The amoxicillin-clavulanic acid combination should never be prescribed as first-line therapy in dentistry</td>
    <td>False</td>
    <td>194 (46%)</td>
  </tr>
  <tr>
    <td>Patients with moderate risk of infective endocarditis should be treated like the general population</td>
    <td>True</td>
    <td>158 (38%)</td>
  </tr>
  <tr>
    <td>Patients with a heart murmur are at high risk for infective endocarditis</td>
    <td>False</td>
    <td>354 (85%)</td>
  </tr>
  <tr>
    <td>An invasive act is an act that can lead to bacteremia and therefore likely to cause a local, distant, or even general infection.</td>
    <td>True</td>
    <td>355 (85%)</td>
  </tr>
  <tr>
    <td>A patient with an orthopedic joint prosthesis requires antibiotic prophylaxis before any invasive oral procedure, to limit intraoperative bacteremia</td>
    <td>False</td>
    <td>324 (78%)</td>
  </tr>
  <tr>
    <td>In the general population, antibiotic prophylaxis is indicated if you perform an avulsion requiring an alvelectomy</td>
    <td>False</td>
    <td>296 (71%)</td>
  </tr>
  <tr>
    <td>In the general population, antibiotic prophylaxis is indicated in the event of avulsion of the mandibular third not impacted</td>
    <td>False</td>
    <td>320 (77%)</td>
  </tr>
  <tr>
    <td>In the general population antibiotic prophylaxis is indicated for pre-implant surgery such as a sinus lift</td>
    <td>True</td>
    <td>289 (70%)</td>
  </tr>
  <tr>
    <td>In the general population, all antibiotics used in dentistry are prescribed for a minimum of 7 days to treat a proven infection</td>
    <td>False</td>
    <td>135 (32%)</td>
  </tr>
  <tr>
    <td>Concerning patients at high risk of infective endocarditis, antibiotic prophylaxis is not recommended for procedures involving manipulation of the gums such as scaling</td>
    <td>False</td>
    <td>254 (61%)</td>
  </tr>
  <tr>
    <td>Concerning patients at high risk of infective endocarditis, antibiotic prophylaxis is indicated in the event of excision of a carious lesion remote from the dental pulp.</td>
    <td>False</td>
    <td>257 (61%)</td>
  </tr>
  <tr>
    <td>Concerning patients at high risk of infective endocarditis, only an antibiotic</td>
    <td>True</td>
    <td>246 (59%)</td>
  </tr>
</table>
prophylaxis is recommended to perform a
simple dental extraction

Clinical case 1: Mr. A, 46 years old, comes to you, for pain regarding the tooth 42. The patient tells you that he was the victim of a public road accident 2 years ago, causing a displaced right parasympphyseal mandibular fracture, osteosynthesis, as you can see on the panoramic X-ray. He has no other history and is not taking any treatment. On clinical examination, you find the gums inflamed and note mobility of the tooth. Retro-alveolar X-ray reveals advanced root resorption of 42, indicating its avulsion.

For this case,
you do not
prescribe
antibiotics

311 (75%)

Clinical case 2: Antoine, 7 years old, comes to the office because he fell from a bicycle 2 hours ago. The patient has no history but is allergic to penicillins. After cleaning with an antiseptic solution, you reduce the dislocation of 11, perform a bonded retainer, and:

You only
prescribe local
treatments such
as antiseptic
mouthwashes to
be carried out 3
times a day for
7 days.

155 (37%)

Clinical case 3: Mr B, 21 years old, is referred to your practice for the removal of third molars. He weighs 80 kg, is in good general condition, has no medical history and has no allergies. He complains of severe radiating pain over 38. You clinically diagnose acute suppurative pericoronitis. You therefore plan to remove it as well as those of teeth 18 and 48 at the next appointment. What do you prescribe?

You prescribe
local care and 3
g of amoxicillin
per day for 7
days, to start
immediately to
treat the
pericoronitis,
then 2 g to be
taken 1 hour
before the
planned remote
intervention.

217 (52%)

Clinical case 4: You see Mrs. M in your office, she has an irreversible pulpitis of tooth 32. The patient has a mechanical mitral valve. The tooth can be preserved, and the canal light is clearly visible radiologically, so you decide to carry out the endodontic treatment, in a single session and under rubber dam. What do you prescribe?

You prescribe
2 g of amoxicillin
in one dose,
one hour before
performing the
procedure.

248 (60%)

Clinical case 5: A young 23-year-old patient presents for consultation. She has been complaining of major gingival pain (EN 8/10) for a week. She tells you that she is very stressed and smokes a lot.

You prescribe
metronidazole
1500 mg per
day in 3 doses
for 7 days.

233 (56%)

<table><tr><td>Clinical case 1: Mr. A, 46 years old, comes to you, for pain regarding the tooth 42. The patient tells you that he was the victim of a public road accident 2 years ago, causing a displaced right parasympphyseal mandibular fracture, osteosynthesis, as you can see on the panoramic X-ray. He has no other history and is not taking any treatment. On clinical examination, you find the gums inflamed and note mobility of the tooth. Retro-alveolar X-ray reveals advanced root resorption of 42, indicating its avulsion.</td><td>For this case, you do not prescribe antibiotics</td><td>311 (75%)</td></tr><tr><td>Clinical case 2: Antoine, 7 years old, comes to the office because he fell from a bicycle 2 hours ago. The patient has no history but is allergic to penicillins. After cleaning with an antiseptic solution, you reduce the dislocation of 11, perform a bonded retainer, and:</td><td>You only prescribe local treatments such as antiseptic mouthwashes to be carried out 3 times a day for 7 days.</td><td>155 (37%)</td></tr><tr><td>Clinical case 3: Mr B, 21 years old, is referred to your practice for the removal of third molars. He weighs 80 kg, is in good general condition, has no medical history and has no allergies. He complains of severe radiating pain over 38. You clinically diagnose acute suppurative pericoronitis. You therefore plan to remove it as well as those of teeth 18 and 48 at the next appointment. What do you prescribe?</td><td>You prescribe local care and 3 g of amoxicillin per day for 7 days, to start immediately to treat the pericoronitis, then 2 g to be taken 1 hour before the planned remote intervention.</td><td>217 (52%)</td></tr><tr><td>Clinical case 4: You see Mrs. M in your office, she has an irreversible pulpitis of tooth 32. The patient has a mechanical mitral valve. The tooth can be preserved, and the canal light is clearly visible radiologically, so you decide to carry out the endodontic treatment, in a single session and under rubber dam. What do you prescribe?</td><td>You prescribe 2 g of amoxicillin in one dose, one hour before performing the procedure.</td><td>248 (60%)</td></tr><tr><td>Clinical case 5: A young 23-year-old patient presents for consultation. She has been complaining of major gingival pain (EN 8/10) for a week. She tells you that she is very stressed and smokes a lot.</td><td>You prescribe metronidazole 1500 mg per day in 3 doses for 7 days.</td><td>233 (56%)</td></tr></table>
You clinically diagnose necrotic ulcerative gingivitis. In addition to local care, what do you prescribe?
542 **Table S2:** Comparison of student's and learning characteristics between the two clusters

543 (identified by the k-means clustering method) – Bivariate analyses (N = 415 students)

544

<table><thead><tr><th rowspan="2">Characteristics</th><th rowspan="2"></th><th>Cluster "High level of knowledge"<br>versus Cluster "Average level of<br>knowledge"</th><th rowspan="2">p-value</th></tr><tr><th>Ref is average level of knowledge</th></tr><tr><th></th><th></th><th>Odds Ratio<br>(95% confidence interval)</th><th></th></tr></thead><tbody><tr><td>Student's age</td><td></td><td>0.90 (0.89-1.1)</td><td>0.864</td></tr><tr><td rowspan="2">Student's gender</td><td>Male</td><td>1 (reference)</td><td>-</td></tr><tr><td>Female</td><td>0.48 (0.27-0.84)</td><td><strong>0.010</strong></td></tr><tr><td rowspan="2">Mentor's age</td><td>Under 50 years old</td><td>1 (reference)</td><td>-</td></tr><tr><td>Over 50 years old</td><td>0.81 (0.51-1.31)</td><td>0.400</td></tr><tr><td rowspan="2">Mentor's activity</td><td>Rural</td><td>1 (reference)</td><td>-</td></tr><tr><td>Urban</td><td>1.04 (0.64-1.70)</td><td><strong>0.087</strong></td></tr><tr><td rowspan="2">Mandatory courses</td><td>None</td><td>1 (reference)</td><td>-</td></tr><tr><td>At least one</td><td>2.17 (0.63-7.41)</td><td><strong>0.217</strong></td></tr><tr><td rowspan="2">Additional non-<br>mandatory courses</td><td>None</td><td>1 (reference)</td><td>-</td></tr><tr><td>At least one</td><td>0 (0-2-Inf)</td><td>0.980</td></tr><tr><td>Learning hours</td><td></td><td>1 (0.99-1.01)</td><td>0.360</td></tr><tr><td>Multiple learning modalities</td><td></td><td>1.21 (1.03-1.41)</td><td><strong>0.020</strong></td></tr></tbody></table>

545 Bold indicates a p-value < 0.10.
546 Table S3: Comparison of student's and learning characteristics between the two clusters

547 (identified by the k-medoids clustering method) – Bivariate analyses (N = 415 students)

548

<table><thead><tr><th rowspan="2">Characteristics</th><th rowspan="2"></th><th>Cluster "High level of knowledge"<br>versus Cluster "Average level of<br>knowledge"</th><th rowspan="2">p-value</th></tr><tr><th>Ref is average level of knowledge</th></tr><tr><th></th><th></th><th>Odds Ratio<br>(95% confidence interval)</th><th></th></tr></thead><tbody><tr><td>Student's age</td><td></td><td>0.94 (0.85-1.04)</td><td>0.219</td></tr><tr><td rowspan="2">Student's gender</td><td>Male</td><td>1 (reference)</td><td>-</td></tr><tr><td>Female</td><td>0.62 (0.40-0.94)</td><td><strong>0.024</strong></td></tr><tr><td rowspan="2">Mentor's age</td><td>Under 50 years old</td><td>1 (reference)</td><td>-</td></tr><tr><td>Over 50 years old</td><td>1.18 (0.79-1.78)</td><td>0.413</td></tr><tr><td rowspan="2">Mentor's activity</td><td>Rural</td><td>1 (reference)</td><td>-</td></tr><tr><td>Urban</td><td>0.69 (0.46-1.05)</td><td><strong>0.082</strong></td></tr><tr><td rowspan="2">Mandatory courses</td><td>None</td><td>1 (reference)</td><td>-</td></tr><tr><td>At least one</td><td>3.02 (1.27-7.17)</td><td><strong>0.012</strong></td></tr><tr><td rowspan="2">Additional non-<br>mandatory courses</td><td>None</td><td>1 (reference)</td><td>-</td></tr><tr><td>At least one</td><td>0.65 (0.23-1.82)</td><td>0.408</td></tr><tr><td>Learning hours</td><td></td><td>0.99 (0.99-1.00)</td><td>0.176</td></tr><tr><td>Multiple learning modalities</td><td></td><td>1.08 (0.97-1.21)</td><td>0.178</td></tr></tbody></table>

549 Bold indicates a p-value < 0.10.
550 **Table S4.** Comparison of student's and learning characteristics between the two clusters (identified by the k-means clustering method) – Multivariable analyses (N = 415 students).

<table><thead><tr><th rowspan="2">Characteristics</th><th rowspan="2"></th><th>Cluster "High level of knowledge"<br>versus Cluster "Average level of<br>knowledge"</th><th rowspan="2">p-value</th></tr><tr><th>Odds Ratio<br>(95% confidence interval)</th></tr></thead><tbody><tr><td rowspan="2">Student's gender</td><td>Male</td><td>1 (reference)</td><td>-</td></tr><tr><td>Female</td><td>0.43 (0.24-0.76)</td><td><strong>0.004</strong></td></tr><tr><td rowspan="2">Mentor's activity</td><td>Rural</td><td>1 (reference)</td><td>-</td></tr><tr><td>Urban</td><td>0.85 (0.48-1.51)</td><td>0.064</td></tr><tr><td rowspan="2">Mandatory courses</td><td>None</td><td>1 (reference)</td><td>-</td></tr><tr><td>At least one</td><td>2.11 (1.10-4.25)</td><td><strong>0.029</strong></td></tr></tbody></table>

553 Bold indicates a p-value < 0.05.
554 **TableS5.** Comparison of student's and learning characteristics between the two clusters (identified by the K-medoids clustering method) – Multivariable analyses (N = 415 students).

<table><thead><tr><th rowspan="2">Characteristics</th><th rowspan="2"></th><th>Cluster "High level of knowledge"<br>versus Cluster "Average level of<br>knowledge"</th><th rowspan="2">p-value</th></tr><tr><th>Odds Ratio<br>(95% confidence interval)</th></tr></thead><tbody><tr><td rowspan="2">Student's gender</td><td>Male</td><td>1 (reference)</td><td>-</td></tr><tr><td>Female</td><td>0.62 (0.4-0.95)</td><td><strong>0.027</strong></td></tr><tr><td rowspan="2">Mentor's activity</td><td>Rural</td><td>1 (reference)</td><td>-</td></tr><tr><td>Urban</td><td>0.67 (0.44-1.02)</td><td>0.064</td></tr><tr><td rowspan="2">Mandatory courses</td><td>None</td><td>1 (reference)</td><td>-</td></tr><tr><td>At least one</td><td>2.83 (1.22-7.11)</td><td><strong>0.019</strong></td></tr></tbody></table>

557 Bold indicates a p-value < 0.05.