Research Article

Abstract

Preoperative education may suggest that orthopedic surgery presents unique challenges because complex anatomy and fixation strategies could indicate that words or two-dimensional images alone appear insufficient. This randomized controlled trial could demonstrate important differences among conventional education, 3D printing-assisted education, and virtual reality (VR)-assisted education in patients undergoing surgery for pelvic fractures, spinal fractures, or ankle fractures. A total of 72 patients were randomly assigned to three groups, and anxiety, procedural understanding, and patient-reported educational experience were evaluated. Baseline characteristics appeared comparable among groups. The significant findings could indicate that both the 3D printing group and the VR group demonstrated greater reductions in preoperative anxiety than the control group. Satisfaction, visualization/comprehensibility, and overall educational quality also appeared higher in the two intervention groups. The VR group showed the greatest numerical improvement in several outcomes, but more education time appeared necessary. Postoperative trait anxiety showed no group differences. Overall, both 3D printing-assisted and VR-assisted education could demonstrate improved preoperative education compared with conventional methods, while 3D printing might offer a more practical balance between effectiveness and feasibility.

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Keywords

Orthopedic Surgery, Preoperative Education, Three-dimensional Printing, Virtual Reality, Anxiety.

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Introduction

Preoperative education demonstrates that it functions as a core component of surgical care.1-4 Moreover, significant evidence suggests that its role extends beyond informed consent alone, encompassing patient understanding of disease, surgical purpose, procedural steps, possible risks, and expected recovery.3-5 Furthermore, the findings indicate that this task appears especially critical in orthopedic surgery, where fracture morphology, anatomical alignment, fixation strategy, and implant positioning may prove difficult to explain through words or two-dimensional images.5-8 In light of these important results, the evidence suggests that patients could demonstrate limited understanding of their condition and treatment plan after routine counseling, potentially increasing uncertainty and preoperative anxiety.9,10 Evidence shows anxiety is common: VR reduces it.

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Three-dimensional printing and virtual reality could indicate that these tools demonstrate significant promise for improving preoperative communication.6-8,11-14 However, the findings suggest that 3D printing has expanded from preoperative planning and surgical guidance toward education around complex anatomy.11,12 Additionally, the significant results indicate that VR could provide immersive explanations and improve perioperative preparedness.13-17 Given that evidence from a randomized study in cardiac surgery demonstrates that both 3D-printed models and VR improved patient education, the key findings could suggest that VR showed the greatest benefit for anxiety reduction.14 Study shows 3D printing and VR outperform standard approaches.

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The evidence suggests that direct comparative data in orthopedic patient education appear limited.18 Nevertheless, the findings could indicate that most previous studies have examined surgical planning, technical training, or anxiety reduction in broader surgical populations rather than a head-to-head comparison of educational strategies.19 Therefore, the significant results might demonstrate that the relative advantages of 3D printing and VR in routine orthopedic education remain unclear, particularly in fracture-related conditions involving complex spatial relationships. In light of these key findings, the evidence could suggest that this gap appears especially relevant given the spatial complexity inherent to orthopedic conditions. Research shows that comparative evidence is lacking.

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This randomized controlled trial may demonstrate that it compares conventional education, 3D printing-assisted education, and VR-assisted education in patients undergoing surgery for pelvic fractures, spinal fractures, and ankle fractures. However, the significant findings could indicate that the study examined effects on preoperative anxiety, procedural understanding, and patient-reported educational experience. Furthermore, the key results might suggest that both 3D printing-assisted education and VR-assisted education could demonstrate advantages over conventional education. Given that evidence supports immersive features as potentially beneficial, the findings indicate that VR might show greater numerical benefit in some outcomes. The trial shows VR and 3D printing outperform conventional education.

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Methods

Study design and setting

This study may suggest that a single-center, randomized controlled trial framework could provide the significant evidence needed to compare educational modalities at Shanghai Sixth People's Hospital. Moreover, the findings indicate that patients were enrolled between December 25, 2025, and April 21, 2026. Furthermore, the key aim is to demonstrate that comparing conventional preoperative education, 3D printing-assisted education, and virtual reality-assisted education might reveal important differences in anxiety relief, procedural understanding, and education-related experience in patients undergoing orthopedic surgery. Given that the evidence supports a balanced allocation, eligible patients were randomly assigned in a 1:1:1 ratio to the control group, the 3D printing group, or the VR group. The study shows each group included 24 participants. However, the results may suggest that all patients received preoperative education before surgery, and the significant core content was delivered across groups, with the educational modality being the key difference. Additionally, the important baseline demographic and clinical characteristics could indicate that group comparability was assessed before the intervention (Figure 1).

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Figure 1. Overview of study design and randomization. Seventy-two patients were randomized in a 1:1:1 ratio to conventional education, 3D printing-assisted education, or VR-assisted education. The balanced allocation ensured comparable baseline characteristics across groups, allowing valid comparison of anxiety reduction and procedural understanding outcomes.

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Participants

Notwithstanding the broad screening criteria, adult patients scheduled for orthopedic surgery at our institution during the study period were considered for inclusion. Therefore, the findings may suggest that the study population mainly comprised patients with pelvic fractures, spinal fractures, and ankle fractures. Moreover, the significant evidence could indicate that patients who were able to understand the educational content and complete the questionnaires were eligible for participation. In light of these results, individuals with severe cognitive impairment, communication barriers, or other conditions that prevented completion of the education process or outcome assessments were excluded from the study. Results show baseline variables affected eligibility. However, the key demographic and background information could demonstrate that age, sex, educational level, medical background, and whether the patient had previously received information regarding the planned surgery were all recorded before the intervention. Furthermore, the important results may suggest that these variables were incorporated into subsequent analyses to explore their possible association with changes in anxiety and procedural understanding.

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Educational interventions

Given that standardized delivery could indicate consistent comparability, all participants underwent routine preoperative counseling delivered by the clinical team. Moreover, the significant evidence may suggest that the educational session focused on the relevant anatomy, injury characteristics, surgical rationale, major operative steps, and perioperative precautions. Thus, the key findings could demonstrate that the educational content was standardized as far as possible among the three groups, while the method of presentation differed according to group assignment. Additionally, the important results might indicate that in the control group, patients received conventional preoperative education consisting of verbal explanation with standard visual materials routinely used in clinical practice. The study shows that group assignment determined the modality. In the 3D printing group, the findings may suggest that the educational session was supplemented by physical 3D-printed orthopedic models. Furthermore, the significant evidence could indicate that most of the models used in this study were general teaching models designed for common fracture patterns and surgical demonstration. However, the key results might suggest that for a small number of patients with relatively complex conditions, patient-specific printed models were additionally used to facilitate individualized explanation. In light of this evidence, these models could demonstrate that the surgeon used them during the consultation to improve the patient's understanding of fracture morphology, anatomical relationships, and the planned surgical procedure (Figure 2).20

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Figure 2. 3D-printed models for ankle surgery, spinal surgery, and pelvic surgery. (A) A 3D-printed model for ankle surgery, used to demonstrate the anatomy of the ankle joint and the distal tibia and fibula, as well as the surgical approaches. (B) A 3D-printed model for spinal surgery, illustrating the anatomical features of the spine and the anterior anatomical structures adjacent to the vertebral column. (C) A 3D-printed pelvic model, with commercially available internal fixation implants sutured to the model, was used to demonstrate the surgical outcomes of pelvic fracture repair. These models facilitated improved spatial understanding and contributed to greater improvements in procedural understanding and anxiety reduction compared with conventional education.

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Notwithstanding the differences in hardware, the results may suggest that in the VR group, patients received preoperative education using a VR-based approach. Moreover, the significant findings could indicate that the hardware platform was Meta Quest 2, and the software used for visualization was Osso VR. Therefore, the important evidence might demonstrate that during the session, the physician accompanied the patient and provided a real-time explanation while demonstrating relevant anatomy and surgical concepts within the immersive environment. Given that the results support a communication-focused application, the key findings could suggest that the VR intervention in this study was primarily used to facilitate anatomical visualization and enhance communication rather than to provide independent patient-operated simulation training.

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Outcome Assessment

Findings show outcomes assessed at predefined time points. However, the significant evidence may suggest that anxiety and procedural understanding were evaluated before the educational intervention (T0) and immediately after the educational intervention (T1). Furthermore, the important results could indicate that trait anxiety was assessed at T2, which was defined as postoperative day 3 to 7 or before discharge. In light of these findings, anxiety was demonstrated to be measured using the Visual Analog Scale for Anxiety (VAS-A) and the short version of the State-Trait Anxiety Inventory (STAI).21-23 Moreover, the key evidence may suggest that VAS-A scores ranged from 0 to 10, with higher scores indicating greater anxiety. Additionally, the significant findings could demonstrate that the STAI assessment included the state anxiety subscale (STAI-S) and the trait anxiety subscale (STAI-T).24 Thus, the important results might indicate that STAI-S was recorded at T0 and T1 to reflect immediate changes in situational anxiety associated with the educational intervention, while STAI-T was measured at T2 to evaluate background anxiety tendency after surgery. The study shows procedural understanding assessed via a self-developed questionnaire.

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Nevertheless, the key findings may suggest that scores were transformed to a 0–100 scale, with higher scores indicating better understanding of the disease condition, surgical procedure, and related perioperative information. Furthermore, the significant evidence could demonstrate that this questionnaire was administered at T0 and T1, and the difference between the two assessments was used to reflect the improvement in procedural understanding after education. Moreover, the important results might indicate that following the educational session, patients rated their satisfaction with the educational process, the visualization/comprehensibility of the explanation, and the overall quality of the education on a 0–100 scale. Given that session duration could provide relevant context, the key evidence may suggest that the duration of each educational session was recorded in minutes.

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Statistical analysis

Results show continuous variables presented as mean ± standard deviation. However, the significant findings may suggest that categorical variables are presented as numbers with percentages. Furthermore, the important evidence could indicate that baseline continuous variables among the three groups were compared using one-way analysis of variance, while categorical variables were compared using the chi-square test or Fisher's exact test, as appropriate. In light of these analytical considerations, the key results might demonstrate that for the main study outcomes, overall between-group comparisons were performed using one-way analysis of variance. The study shows post hoc correction applied when needed. Moreover, the significant findings may suggest that when a significant overall difference was identified, post hoc pairwise comparisons were conducted with Bonferroni correction. Additionally, the important results could indicate that changes in anxiety and procedural understanding were calculated as the difference between post-education and baseline values (T1 − T0). Therefore, the key evidence might demonstrate that multivariable linear regression analyses were performed to further identify independent factors associated with changes in anxiety and procedural understanding. Given that covariate selection could indicate important baseline considerations, the significant findings may suggest that the regression models included study group and baseline covariates, including age, sex, educational level, prior information about surgery, and the relevant baseline score. Furthermore, the important results could demonstrate that regression results are reported as β coefficients with 95% confidence intervals, and a two-sided P<0.05 was considered statistically significant.

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Results and Discussion

Results

The study may suggest that a total of 72 patients were included in the final analysis, with 24 participants assigned to each of the three groups. Moreover, the significant findings could indicate that baseline demographic and clinical characteristics were generally comparable across groups. Furthermore, the important evidence might demonstrate that the mean age was 64.1 ± 8.7 years in the control group, 65.3 ± 9.4 years in the 3D printing group, and 63.8 ± 10.1 years in the VR group, with no significant between-group difference (P = 0.84). Given that sex distribution could indicate further balance, the key results may suggest that the proportion of male patients was 41.7% in the control group, 37.5% in the 3D printing group, and 45.8% in the VR group (P = 0.81). Groups show no baseline differences (all P > 0.05). However, the significant findings may suggest that there were no significant differences among groups with respect to college education or above, medical background, or previous information about surgery, indicating good baseline balance after randomization (Table 1). Moreover, the important evidence could demonstrate that at baseline, anxiety levels measured by VAS-A were similar among the three groups, with mean scores of 5.8 ± 1.7 in the control group, 5.9 ± 1.8 in the 3D printing group, and 5.7 ± 1.6 in the VR group (P = 0.91). Furthermore, the key results might indicate that after the educational intervention, significant between-group differences emerged, as the mean VAS-A scores decreased to 5.2 ± 1.6, 4.5 ± 1.5, and 3.9 ± 1.4, respectively (P < 0.001). In light of these results, the significant findings could demonstrate that the magnitude of change in VAS-A also differed significantly across groups (P<0.001). Results show VR produced the greatest VAS-A reduction. Additionally, the important evidence may suggest that compared with the modest reduction observed in the control group (−0.6 ± 0.8), greater decreases were found in the 3D printing group (−1.4 ± 0.9) and the VR group (−1.8 ± 1.0). Therefore, the key findings could indicate that post hoc analysis showed that both 3D printing and VR resulted in significantly greater reductions in VAS-A than conventional education alone, with P = 0.006 for 3D printing versus control and P < 0.001 for VR versus control, whereas the difference between the 3D printing and VR groups was not statistically significant (P = 0.11).

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Table 1. Baseline demographic and clinical characteristics of the study participants. No significant differences were observed among the three groups (all P > 0.05), confirming successful randomization and baseline comparability. Data are presented as mean ± standard deviation or number (percentage). P values were calculated using one-way analysis of variance for continuous variables and the chi-square test or Fisher’s exact test for categorical variables, as appropriate.

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The findings may suggest that a similar pattern could emerge for state anxiety as measured by STAI-S. Moreover, the significant results indicate that baseline STAI-S scores did not differ among groups, measuring 24.8 ± 4.6 in the control group, 25.1 ± 4.9 in the 3D printing group, and 24.6 ± 4.7 in the VR group (P = 0.93). Furthermore, the key evidence could demonstrate that immediately after education, the corresponding values declined to 23.9 ± 4.5, 21.8 ± 4.2, and 20.7 ± 4.0, respectively, and the overall between-group difference was significant (P = 0.018). Given that the results appear to support this pattern, the mean change in STAI-S was −0.9 ± 2.4 in the control group, compared with −3.3 ± 2.8 in the 3D printing group and −3.9 ± 3.0 in the VR group (P = 0.004). Pairwise post hoc testing shows that both groups reduced anxiety more than the control group. However, the important findings may indicate that no significant difference was identified between the 3D printing and VR groups (P = 0.47). Additionally, the evidence could suggest that postoperative trait anxiety measured at T2 showed no significant difference among groups, with STAI-T scores of 21.7 ± 4.2, 21.0 ± 4.0, and 20.8 ± 4.5 in the control, 3D printing, and VR groups, respectively (P = 0.71).

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In light of the significant data, procedural understanding appears to have been comparable at baseline, with scores of 56.3 ± 11.4 in the control group, 57.8 ± 10.9 in the 3D printing group, and 56.9 ± 12.1 in the VR group (P = 0.88). Nevertheless, the results could indicate that after education, all groups showed clear improvement, but the increase was more pronounced in the intervention groups. Results show post-education scores rose markedly across groups. Therefore, the significant findings may suggest that post-education procedural understanding scores rose to 74.2 ± 10.6 in the control group, 84.7 ± 9.2 in the 3D printing group, and 88.9 ± 8.5 in the VR group, yielding a significant overall difference (P < 0.001). Notwithstanding these results, the key evidence could demonstrate that the corresponding mean changes were 17.9 ± 8.7, 26.9 ± 9.1, and 32.0 ± 10.0, respectively (P < 0.001). Moreover, the important data may indicate that in the pairwise analysis, both the 3D printing group and the VR group demonstrated significantly greater gains in procedural understanding than the control group (P = 0.002 and P < 0.001, respectively), whereas the difference between VR and 3D printing did not reach statistical significance (P = 0.09). Pairwise data show the VR-3D printing gap is nonsignificant. However, the significant findings could suggest that education-related ratings further supported the superiority of the technology-assisted educational strategies. Furthermore, the evidence may indicate that satisfaction scores differed significantly among groups, with mean values of 81.5 ± 9.8 in the control group, 90.8 ± 7.9 in the 3D printing group, and 92.6 ± 7.5 in the VR group (P < 0.001). Given that these results appear to support the key findings, perceived visualization and comprehensibility were also significantly better in the two intervention groups, with scores of 79.3 ± 10.7 in the control group, 91.1 ± 7.2 in the 3D printing group, and 94.4 ± 6.8 in the VR group (P < 0.001). In light of the important evidence, the overall quality of education could demonstrate that ratings favored intervention groups, with mean scores of 83.2 ± 10.1, 92.4 ± 7.5, and 93.8 ± 6.9 for the control, 3D printing, and VR groups, respectively (P < 0.001). Education quality scores favor intervention groups. Additionally, the results may suggest that the time required to complete the educational session also differed significantly across groups, with a mean education time of 16.8 ± 2.7 minutes in the control group, 18.4 ± 3.1 minutes in the 3D printing group, and 20.2 ± 3.4 minutes in the VR group (P = 0.002). Nevertheless, the significant data could indicate that post hoc analysis showed that VR-assisted education required significantly more time than conventional education (P = 0.001), while the differences between the 3D printing group and the control group (P = 0.08) and between the VR and 3D printing groups (P = 0.09) were not statistically significant (Table 2).

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Table 2. Anxiety, procedural understanding, and education-related outcomes among the three groups. Both 3D printing and VR significantly reduced preoperative anxiety and improved procedural understanding compared with conventional education, with VR showing the greatest numerical improvement in several outcomes. Data are presented as mean ± standard deviation. T0 indicates baseline before education; T1, immediately after education; T2, postoperative day 3–7 or before discharge. P values represent overall between-group comparisons using one-way analysis of variance.

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Moreover, the key findings may demonstrate that multivariable linear regression analysis showed that both 3D printing and VR were independently associated with greater reductions in VAS-A compared with the control group. VR and 3D printing show independent associations with reduced VAS-A. Therefore, the important evidence could suggest that relative to conventional education, the 3D printing group had a β coefficient of −0.74 (95% CI, −1.28 to −0.20; P = 0.008), while the VR group had a β coefficient of −1.10 (95% CI, −1.66 to −0.54; P < 0.001). In light of the significant results, baseline VAS-A score appears to have been independently associated with a larger reduction in anxiety (β = −0.29, 95% CI, −0.42 to −0.16; P < 0.001), whereas age, sex, educational level, and previous information about surgery were not significant predictors. Notwithstanding these findings, the key data may indicate that when a change in STAI-S was used as the dependent variable, both intervention modalities again remained significant predictors. Furthermore, the evidence could demonstrate that compared with the control group, the β coefficient was −1.98 (95% CI, −3.75 to −0.21; P = 0.029) for the 3D printing group and −2.54 (95% CI, −4.36 to −0.72; P = 0.007) for the VR group. Baseline STAI-S scores were independently associated with greater improvement. However, the significant findings may suggest that baseline STAI-S score was likewise independently associated with greater improvement (β = −0.31, 95% CI, −0.45 to −0.17; P < 0.001), while the remaining covariates were not significantly related to the degree of change.

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Multivariable analysis may suggest that both 3D printing and VR independently contributed to greater improvement in procedural understanding score relative to conventional education. Moreover, the significant findings could indicate that the β coefficient was 8.32 (95% CI, 3.01 to 13.63; P = 0.003) for the 3D printing group and 12.41 (95% CI, 6.89 to 17.93; P < 0.001) for the VR group. Furthermore, the evidence might indicate that having a college education or above appears positively associated with improvement in procedural understanding (β = 3.86, 95% CI, 0.11 to 7.61; P = 0.044). In light of these key results, the data could demonstrate that baseline procedural understanding score appears negatively associated with subsequent change (β = −0.36, 95% CI, −0.50 to −0.22; P < 0.001). Results show that lower initial understanding links to greater educational benefit (Table 3).

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Table 3. Multivariable linear regression analyses for changes in anxiety and procedural understanding. Regression models demonstrate that both 3D printing and VR were independently associated with greater reductions in anxiety and greater improvements in procedural understanding compared with conventional education, after adjustment for baseline characteristics. Dependent variable: change in procedural understanding score from T0 to T1. Abbreviations: CI, confidence interval; STAI-S, State-Trait Anxiety Inventory-State; VAS-A, Visual Analog Scale for Anxiety; VR, virtual reality.

 

Table 3A. Factors associated with a change in VAS-A score. Both intervention groups remained significant predictors of greater VAS-A reduction after multivariable adjustment.

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​Dependent variable: change in VAS-A score from T0 to T1.

Table 3B. Factors associated with a change in STAI-S score. Both 3D printing and VR independently predicted greater improvement in STAI-S scores.

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Dependent variable: change in STAI-S score from T0 to T1.

Table 3C. Factors associated with a change in procedural understanding score. VR showed the largest independent effect size for improving procedural understanding

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Discussion

This randomized controlled trial suggests that both 3D printing-assisted education and VR-assisted education could demonstrate greater effectiveness than conventional education in orthopedic patients.20 Moreover, the significant findings may indicate that both interventions produced greater reductions in preoperative anxiety, better procedural understanding, and higher ratings for satisfaction and overall educational quality. However, the key results could suggest that the VR group showed the largest numerical improvements in several outcomes, especially anxiety and understanding. In light of these findings, the evidence may support that most differences between VR and 3D printing appear statistically non-significant. Findings show both strategies improve preoperative education.

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Furthermore, the study may suggest that preoperative education appears especially important in orthopedics because many conditions and procedures remain difficult to explain with words or two-dimensional images alone.26,31 Additionally, the results could indicate that this issue appeared highly relevant in the cohort, which mainly included pelvic fractures, spinal fractures, and ankle fractures. Given that these injuries often involve complex anatomy and fixation strategies, the evidence may suggest that both physical 3D models and VR-based visualization made these concepts easier for patients to understand. Notwithstanding the heterogeneity observed, the significant results could demonstrate that this mechanism likely contributed to greater improvement in procedural understanding and a better patient-reported educational experience in the two intervention groups. Results show anxiety findings support the same interpretation. Thus, the key findings may suggest that both intervention groups showed greater reductions in VAS-A and STAI-S than the control group. Moreover, the evidence could indicate that enhanced visualization appears to reduce immediate preoperative anxiety by reducing uncertainty.30 However, the significant results may demonstrate that the VR group showed the greatest numerical reduction, possibly because VR provided a more immersive and guided explanation.32 In light of the evidence, the findings could suggest that the absence of a significant difference between VR and 3D printing appears to support that physical models can achieve similar benefits in many patients. Data show postoperative STAI-T scores unchanged across groups. Furthermore, the key evidence may suggest that this result appears expected because trait anxiety is relatively stable and less responsive to a single educational intervention.

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Additionally, the results could indicate that the findings appear consistent with previous studies showing that 3D-printed models can improve patient communication and understanding in different surgical fields.25,28,29 Given that prior studies support VR-based approaches, the evidence may demonstrate that VR-based education could reduce anxiety and improve perioperative preparedness.33 Nevertheless, the significant findings could suggest that this study extends the evidence to fracture-related orthopedic surgery and directly compares conventional education, 3D printing-assisted education, and VR-assisted education within one randomized framework. In light of the patient experience data, the results may indicate that patients in the 3D printing and VR groups reported higher satisfaction and better visualization and comprehensibility than those in the control group. The study shows routine education improves without patient-specific models. Moreover, the key findings could suggest that most patients in the 3D printing group used general teaching models rather than patient-specific models, yet the group still showed clear benefit.

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Furthermore, the evidence may indicate that the difference in education time appears to have practical importance. However, the significant results could demonstrate that the VR group required more time than the control group, which may suggest that VR provides stronger immersion but also appears to increase workflow burden. Given that the 3D printing group achieved significant benefit without a significant increase in education time, the findings may suggest that this approach could appear easier to implement in routine practice. Evidence shows the study has several limitations. Additionally, the key results could indicate that this was a single-center trial with a relatively small sample size, which may limit the generalizability of the findings. In light of these constraints, the evidence may suggest that the study included different fracture types, which could introduce clinical heterogeneity into the results. Notwithstanding these concerns, the findings could demonstrate that procedural understanding was measured with a self-developed questionnaire, which may limit comparability with other studies. Moreover, the significant evidence may suggest that the interventions appear not completely uniform, as most 3D models were general teaching models, while some complex cases used patient-specific models. Limitations show cost-effectiveness unassessed. Thus, the key findings may indicate that larger multicenter studies appear to be needed to confirm the results, clarify which orthopedic subgroups benefit most, and define the best balance between educational benefit, workflow burden, and resource use.

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Furthermore, the evidence could suggest that both 3D printing-assisted education and VR-assisted education appear to improve preoperative education compared with conventional methods in patients undergoing surgery for pelvic, spinal, and ankle fractures. However, the significant results may demonstrate that both approaches reduced short-term anxiety and improved procedural understanding and patient experience. Given that VR showed the greatest numerical benefit in several outcomes, the findings could indicate that it required more time, which may represent a practical consideration for implementation. Notwithstanding this constraint, the key evidence may suggest that 3D printing provided substantial benefit with better practical feasibility in routine orthopedic care. Results show that visualization-enhanced education warrants further study.

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Conclusion

The study may suggest that both 3D printing-assisted education and virtual reality-assisted education improved preoperative education for orthopedic surgery patients when compared with conventional counseling alone. However, the significant findings could indicate that both technology-enhanced approaches were associated with greater reductions in short-term preoperative anxiety, better procedural understanding, and higher ratings of satisfaction among patients undergoing surgery for pelvic fractures, spinal fractures, and ankle fractures. Furthermore, the results may demonstrate that visualization-based communication tools support patients in understanding complex orthopedic anatomy, fracture patterns, and surgical strategies. In light of these findings, the evidence could suggest that both educational modalities provide key improvements in overall educational quality and comprehensibility. Results show VR outperforms 3D printing numerically across outcomes.

Notwithstanding the numerical advantages observed in the VR group, the evidence may suggest that most differences between VR and 3D printing were not statistically significant. Moreover, the significant results could indicate that VR-assisted education requires more time to complete, suggesting a potential trade-off between educational immersion and clinical feasibility. Thus, the important findings might demonstrate that 3D printing-assisted education achieved substantial benefits without a significant increase in educational time. Given that the data could support that this balance may make 3D printing a more practical option, the results appear to favor routine implementation in busy orthopedic settings. 3D printing shows better feasibility than VR.

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Multivariable analyses may suggest that both 3D printing and VR were independently associated with improved educational outcomes after adjustment for baseline characteristics. Additionally, the significant evidence could demonstrate that the observed benefits were attributable to the educational modality itself rather than to differences in patient background. However, the key results might indicate that this study was limited by its single-center design, modest sample size, and heterogeneity of fracture types. In light of the findings, the evidence may suggest that the use of a self-developed procedural understanding questionnaire could represent an additional important limitation. The study shows that a single-center design limits generalizability.

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Visualization-enhanced preoperative education may suggest that this approach represents a promising strategy for improving patient communication in orthopedic surgery. Furthermore, the significant findings could demonstrate that both 3D printing and VR offer meaningful advantages over conventional methods. Therefore, the important evidence might indicate that 3D printing may provide the best balance between effectiveness, feasibility, and workflow integration. Given that the results could support that larger multicenter studies appear warranted, the data may suggest that confirming the findings and determining the optimal application across different orthopedic populations remains a critical next step. Larger studies are needed to confirm findings.

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Acknowledgements

I thank Dr. Siyue Tao for guiding and supporting me throughout this project.

 

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Author

Zhiyang Kang is an upcoming Grade 12 student at The Frederick Gunn School. He is interested in psychology, youth well-being, and human-centered approaches to supporting young people through stress and anxiety. Outside of research, Kevin enjoys playing ultimate frisbee and reading fantasy novels.

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​Bojun Cao is from Department of Orthopaedic Surgery, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, 200233, China.

 

* Corresponding author email: 1048347821@qq.com