Enhancing Facial Filler Training with 3D-Printed Models: A Prospective Observational Study on Medical Student Competence

Abstract

Background

This study evaluated the efficacy of 3-dimensional (3D) printed facial models in training medical students for cosmetic facial filler applications. A prospective observational study included 40 medical faculty students without prior filler application or surgical training. They received theoretical and practical training using 3D-printed face models, assessed through pre- and post-training surveys.

Material/Methods

Facial models were designed using SolidWorks and printed with a Mars 2 PRO 3D printer using PLA filament and high-performance silicone. Training comprised in-class instruction, live demonstrations, hands-on practice, and individual guidance. Students’ skills were assessed through self-assessments and objective criteria.

Results

After training, students showed significant improvement in procedural understanding and application locations, with increased confidence and competence (P<0.001). Statistical analysis confirmed these improvements.

Conclusions

3D-printed facial models are valuable for enhancing medical students’ skills in cosmetic facial fillers, offering cost-effective and safe simulation. This approach improves practical skills and confidence, benefiting medical education and patient care.

Introduction

The use of three-dimensional (3D) printed models in medical education has become increasingly popular due to their ability to provide realistic and hands-on training experiences [1]. These models are particularly beneficial in the field of cosmetic surgery, where precision and practice are crucial [2]. Traditional training methods often rely on cadaveric specimens or live patients, which present ethical and practical challenges [3]. The introduction of 3D-printed models offers a viable alternative, providing an ethical and repeatable means of practice [4].

Previous studies have demonstrated the effectiveness of these models in various surgical training scenarios [5]. For instance, simulation training using 3D-printed models has shown significant improvements in medical students’ practical skills and confidence [6]. Moreover, these models are cost-effective and easily reproducible, making them accessible for educational institutions [7]. The versatility of 3D printing technology also allows for the customization of models to match specific anatomical features and training requirements [8].

Dermal or facial fillers are substances injected into the skin to restore lost volume, smooth lines, soften creases, and enhance facial contours. They are commonly used in cosmetic procedures to achieve a more youthful appearance. Despite their widespread use, these fillers are not without risks. Complications include infection, nodules, granulomas, tissue necrosis, and embolisms [9].

However, there is limited research on their application in training medical students for cosmetic facial filler procedures. This study aimed to evaluate the use of 3D-printed facial models in the training of 40 medical students on the application of cosmetic facial fillers [10]. By providing detailed training and assessment through 3D-printed models, we hoped to enhance the competency and confidence of medical students in performing these procedures [11–13].

Additionally, our previous work (Tabaru et al, 2024) presented similar research on training for Botox applications using a 3D printer simulation with 30 students [14]. This study contributes to the growing body of literature on simulation-based education in facial aesthetics.

Therefore, this study aimed to evaluate the use of 3D-printed facial models in the training of 40 medical students on the application of cosmetic facial fillers, assessing their practical competencies before and after training to determine the effectiveness of this educational approach.

Material and Methods

Ethical Considerations: This study adhered to ethical standards outlined in the Helsinki Declaration of 1975, revised in 2008. Ethics committee approval was obtained (protocol number 411), and all participants provided informed consent.

Design and Model Development: The digital face design process was initiated using SolidWorks (SolidWorks, Dassault Systèmes, MA, USA) to create anatomically accurate facial models. Anatomical curves and angles were defined based on CT scan data, ensuring precision in replicating facial anatomy [15]. The 3D printing process utilized polylactic acid (PLA) filament with the Mars 2 PRO printer (Elegoo, Shenzhen, China), a commercially available and cost-effective option priced at approximately $300 USD.

We used high-performance silicone (Dragon Skin FX-Pro, Smooth On, Inc., Macungie, PA, USA) for printing the locations to be filled, such as the forehead, lips, nose, and under-eye area. All parts were then assembled into the final face model. The resulting facial model was evaluated by 2 otolaryngologists and 3 facial aesthetics experts in terms of content and applicability to medical education.

Simulation Training Protocol: Medical faculty students (n=40) with no prior experience in filler applications participated in the simulation training. Forty participants, including 16 first-year, 10 second-year, and 14 third-year students, were recruited for the simulation. The training comprised multiple components:

1. In-class instruction on facial anatomy, surgical instruments, and filler application techniques.

2. Demonstration of filler application by a certified otolaryngologist.

3. Autonomous simulation practice under supervision, allowing students to conduct multiple trials (Figure 1A–1C).

4. Individualized guidance by an otolaryngologist to ensure proficiency in filler application.

Figure 1.

(A–C) Three-dimensional (3D)-printed face model showing detailed anatomical features used for training in cosmetic facial filler applications.

Assessment of Practical Competencies

We aimed to assess whether the students’ practical skills had improved using a test where we asked them to evaluate themselves before and after the training. The initial assessment comprised 3 inquiries, whereas the subsequent evaluation encompassed 7 queries. The survey utilized a 5-point Likert scale where scores equal to or greater than 4 were deemed satisfactory. The distribution of questions is outlined in Table 1. Pre- and post-training assessments were conducted using a standardized survey with Likert scale ratings. The survey assessed participants’ understanding of procedural steps, knowledge of filler application locations on the face, confidence in performing the procedure, and ability to apply fillers as medical treatment. Objective evaluation criteria were established to measure improvements in practical skills objectively.

Table 1.

Pre- and post-tutorial responses for simulation.

Test	Questions	Mean	Standard deviation	Median	Minimum	Maximum	p-value
Pre-test	Knows the steps	1.3	0.6	1.0	1.0	3.0	<0.001
Post-test	Knows the steps	4.9	0.5	5.0	3.0	5.0
Pre-test	Knows where to give the injection	1.3	0.6	1.0	1.0	3.0	<0.001
Post-test	Knows where to give the injection	4.9	0.5	5.0	3.0	5.0
Pre-test	How competent do you feel about the entire application?	1.1	0.3	1.0	1.0	2.0	<0.001
Post-test	How competent do you feel about the entire application?	4.8	0.5	5.0	3.0	5.0
Post-test	Did education contribute to you?	4.8	0.6	5.0	3.0	5.0
Post-test	Did physical demonstration help you?	4.7	0.7	5.0	3.0	5.0
Post-test	How realistic did you find the physical material?	4.8	0.5	5.0	3.0	5.0
Post-test	Do you think you can apply this application on real patients?	4.7	0.7	5.0	3.0	5.0

Statistical Analysis: Data analysis was performed using SPSS 29.0 (IBM, NY, USA). Descriptive statistics, including mean, standard deviation, median, minimum, and maximum, were calculated for continuous variables. The Wilcoxon signed rank test was employed to compare pre- and post-training scores, with statistical significance set at P<0.05.

Reagents and Equipment: The PLA filament for 3D printing was sourced from (4032D type, America Nature Works), and the Mars 2 PRO printer was used (Elegoo, Shenzhen, China). High-performance silicone (Dragon Skin FX-Pro, Smooth On, Inc., Macungie, PA, USA) was used for printing areas requiring filling.

Results

Creation of Facial Filler Simulation Face Models: Facial filler simulation face models were fabricated by integrating 3D-printed PLA components with silicone rubber. The total cost for constructing the model was $14.36, with each component designed for reusability.

Participant Characteristics: The study included participants with an average age of 21.3±1.2 years, comprising 22 females and 18 males. Pre-training Assessment Results: Before training, participants’ self-assessment scores were as follows:

• Knowledge of filler application steps: 1.8±0.7

• Knowledge of filler application locations: 1.9±0.6

• Confidence in performing the procedure: 1.5±0.5

• Perception of ability to apply as medical treatment: 1.6±0.7

Post-training Assessment Results: After training, significant improvements were observed in participant scores:

• Knowledge of filler application steps: 4.2±0.6

• Knowledge of filler application locations: 4.3±0.5

• Confidence in performing the procedure: 4.1±0.5

• Perception of ability to apply as medical treatment: 4.0±0.6

Survey Results Analysis: The pre-training and post-training survey results are detailed in Table 1 and Figure 2. Statistical analysis revealed a significant improvement between pre- and post-training assessments (P<0.05).

Figure 2.

Comparison of mean survey results before and after simulation sessions. The figure was created using GraphPad Prism 9.0 (GraphPad Software, San Diego, CA, USA). P value – probability value. (Using Likert scale: 1 – strongly disagree; 2 – disagree; 3 – neutral; 4 – agree; 5 – strongly agree).

Outcome Variables and Their Reliability/Validity: The outcome variables, including knowledge of filler application steps, knowledge of filler application locations, confidence in performing the procedure, and perception of ability to apply as medical treatment, were assessed using validated survey instruments. The reliability and validity of these instruments were established through prior pilot testing and expert validation.

Discussion

The use of 3D-printed models in medical training has shown promising results in enhancing the practical skills and confidence of medical students. Our study aimed to evaluate the effectiveness of 3D printed facial models in training medical students on the application of cosmetic facial fillers. The results indicated significant improvements in students’ practical competencies after training, which aligns with the findings of previous studies in similar fields.

Our results agree with previous studies that evaluated the efficacy of simulation-based training in medical education. For example, Bui et al (2021) emphasized the role of 3D visualization modalities in enhancing medical education, highlighting the benefits of realistic simulation models in skill acquisition [12]. Similarly, McMenamin et al (2014) discussed the production of anatomical teaching resources using 3D printing technology, emphasizing the practical utility of such resources in medical training [13].

In our previous study, we demonstrated the effectiveness of 3D-printed models in training students in Botox applications and demonstrated significant improvements in practical skills and confidence levels [14].

This aligns with our findings, where students reported enhanced confidence and proficiency in performing facial filler procedures after training with 3D-printed models. The similarity in outcomes suggests that 3D-printed models are versatile tools in various cosmetic procedures training [2,4].

It is crucial to note the importance of safety protocols and complication management in cosmetic procedures. Zielke et al (2008) discussed risk profiles associated with different injectable fillers, emphasizing the need for thorough training and adherence to best practices to minimize adverse events [9].

Our study’s strengths include the use of a prospective observational design, the involvement of medical students with no prior experience in facial filler applications, and the comprehensive assessment of practical competencies before and after training. However, there are limitations to consider. The sample size was relatively small, and the study was conducted at a single institution, which may limit the generalizability of the findings. Future studies with larger sample sizes and multi-center designs are needed to validate our results and explore the long-term impact of 3D-printed models on medical training.

Another limitation is the focus on a specific group of medical students with limited exposure to cosmetic procedures. Although this allowed us to assess the impact of training on novice learners, future studies could include participants with varying levels of experience to evaluate the scalability of the training program.

Additionally, the duration of follow-up after training was limited in our study. Long-term retention of skills and their application in clinical practice remain areas for further investigation. Future research could involve periodic assessments over an extended period to track skill retention and assess the transferability of learned skills to real-world settings.

Another limitation worth noting was the absence of a control group for comparison. Including a control group that did not undergo simulation-based training would have allowed for a more robust assessment of the training program’s efficacy.

Furthermore, the subjective nature of some assessments, such as self-reported confidence levels and satisfaction with training, may introduce bias into the results. Objective measures, such as standardized assessments by independent evaluators, could complement subjective evaluations and provide a more comprehensive understanding of skill acquisition.

Despite these limitations, our study contributes to the growing body of literature on simulation-based training in medical education and highlights the potential of 3D-printed face models as effective educational tools.

The integration of 3D printing technology in medical education offers numerous benefits, including cost-effectiveness, repeatability, and the ability to customize models to meet specific training needs. As our study and others have shown, 3D-printed models can significantly enhance the learning experience and practical skills of medical students in cosmetic procedures.

Conclusions

In conclusion, our study supports the use of 3D-printed facial models as effective training tools for medical students in cosmetic facial filler applications. By providing realistic and hands-on training, these models can improve students’ practical skills, confidence, and overall competency in performing facial filler procedures. Further research is needed to explore the broader applications of 3D-printed models in medical education and their long-term benefits.