This prospective, randomized, single-blinded experimental study was conducted at the Simulation and Surgical Skills Training Centre of Zhejiang Provincial People’s Hospital over four weeks. The study followed methodological principles used in previous laparoscopic skills research, including the structured simulation approaches described by Seymour et al. [15] and Van Sickle et al. [16], with modifications tailored to camera-specific training. The protocol was designed to evaluate the effect of simulation-based exposure to three standardized laparoscopic camera angles on the acquisition of visuospatial and camera manipulation skills among novice trainees.

All participants provided written informed consent and agreed to comply with the study schedule. The study followed a pre-test/post-test framework, allowing both within-group and between-group comparisons, and adhered to CONSORT recommendations for reporting randomized trials [17]. The study design and participant flow are summarized in Figure 1. Eligible novice medical students were randomly allocated to either the training or control group. Both groups completed baseline and repeated assessment sessions, while the intervention group additionally underwent fifteen structured simulation-training sessions during the study period.

A convenience sample of twenty undergraduate clinical-year medical students (3rd-5th year) was recruited. Eligibility screening confirmed that participants had no prior exposure to laparoscopic simulation, minimally invasive surgical training, or MIS workshops. Twenty-four students initially expressed interest, of whom four were excluded due to scheduling conflicts, leaving twenty eligible participants who were randomized into study and control groups.

During the trial, four participants (three in the study group and one in the control group) were withdrawn due to repeated absenteeism (missing > 2 scheduled sessions). The final analysis was therefore conducted on a per-protocol basis, including only participants who completed all study procedures. A total of 16 participants were included in the final analysis (study group, n = 7; control group, n = 9).

Although these post-randomization withdrawals may have influenced group balance given the small sample size, baseline characteristics, including age, gender, year of study, hand dominance, laparoscopic interest, and prior simulator experience, remained comparable between groups, as shown in Table 1.

Figure 1.Study flowchart showing participant recruitment, screening, randomization, withdrawals, and final analysis.

Before randomization, all participants attended a structured 45-minute introductory lecture that provided foundational knowledge necessary for the study. This session covered the principles of minimally invasive surgery, the mechanics of instrument handling and ergonomic posture, and core visuospatial concepts such as depth perception and the fulcrum effect. Participants were also introduced to the basics of laparoscopic camera operation, including horizon control and maintenance of a stable visual field. To reinforce these concepts, a brief demonstration video illustrating fundamental laparoscopic visualization tasks was shown to all participants. After the lecture, students completed a seven-item knowledge quiz designed to ensure a uniform theoretical baseline before pre-testing; only those who achieved a perfect score proceeded to the next phase of the study.

Table 1. The baseline characteristic for participants.

Randomization was performed using a computer-generated sequence in a 1:1 ratio. Each participant received a unique identification number, and group assignments were secured using sealed opaque envelopes opened at the first session. Due to the nature of the intervention, participant blinding was not feasible. However, video-based scoring was performed by a single blinded expert reviewer, who was unaware of group assignments, ensuring assessor blinding and reducing bias.

The training was conducted using two primary laparoscopic simulation systems. The first was the Laparoscopic Simulation Trainer 200-E, manufactured by Shanghai Rushing Laboratory Equipment Co., Ltd., which served as the foundational platform for developing basic laparoscopic handling skills. Following the initial phase, participants progressed to a portable Laparoscopic Sim Box equipped with advanced 3D-printed task models, allowing practice under varied camera angulations and facilitating suturing exercises with enhanced spatial realism (Figure 2) [18].

Figure 2.Laparoscopic simulation tasks and training setup illustrating the structured progression of simulation tasks used to develop core laparoscopic skills, including object transfer, cutting, camera angulation exercises, and intracorporeal suturing on 3D-printed models. (A) Bean transfer task between stations to improve hand dexterity using Maryland dissector and grasping forceps. (B) Precision cutting task using laparoscopic scissors and Maryland instrument under timed assessment. (C) Tissue manipulation and demonstration of intracorporeal suturing using Maryland grasper and needle holder. (D) Triangulation principle during camera holding and suturing practice. (E) Knot tying under different camera angles. (F-G) Portable 3D simulator box models used for repetitive laparoscopic skills training.

2.5.1. Training Tasks

The curriculum was structured into four progressive tasks (Figure 2). Task 1 focused on basic hand-eye coordination and instrument handling through repeated bean-transfer exercises performed ten times, analogous to peg transfer drills [19]-[21]. Task 2 advanced to precision cutting tasks using laparoscopic scissors and graspers. Task 3 introduced camera angulation and visualization strategies under different viewing perspectives. Task 4 emphasized intracorporeal suturing and knot tying using 3D-printed tissue models. Standardized camera positions used during angle-specific training are illustrated in Figure 3.

2.5.2. Camera Angulation Conditions

Three clinically relevant camera angles were used to assess variation in laparoscopic visualization: the Umbilical (midline) entry, which offers a direct and intuitive visual axis with minimal distortion [22]; Palmer’s Point in the left upper quadrant, which produces a lateral off-axis view associated with increased visuospatial and cognitive demands [23]; and the Lee-Huang Point in the mid-upper abdomen, which provides a superior vantage point with moderate non-linear distortion [24]. All trocar locations were pre-positioned on the trainer for standardized replication, and the order of angles during post-testing was randomized to reduce sequence-related bias. The 3D simulator box was equipped with multiple ports to allow camera insertion at these standardized positions, including the umbilical, Lee-Huang, and Palmer’s Point locations, as illustrated in Figure 3.

Figure 3.Standardized simulation setup for angle-specific laparoscopic camera training demonstrating the standardized simulator setup, trocar placement, and camera orientation corresponding to the three tested viewing angles: umbilical, Palmer’s Point, and Lee-Huang Point. (A) Simulator box with multiple camera insertion ports. (B) Left upper quadrant camera position (Palmer’s Point) on the 3D model. (C-D) Umbilical camera port insertion with ipsilateral instrument alignment. (E) Lee-Huang Point (mid-upper abdomen) demonstrating triangulation principles. (F) Camera adjustment to optimize exposure and visualization.

2.6.1. Study Group

The study group underwent a structured simulation-based curriculum consisting of fifteen supervised sessions, with five sessions dedicated to each camera angle. Each session lasted approximately 15 minutes and followed a standardized instructional sequence that included a brief orientation to the assigned angle, a short warm-up period to stabilize the camera and familiarize participants with the visual field, a focused bean-transfer visualization task performed under the designated angle, and a brief debriefing emphasizing horizon leveling, target acquisition, and image stability. To maintain methodological rigor, assistance from the instructor was minimal during task execution, thereby reducing coaching bias and ensuring that improvements reflected genuine skill acquisition.

2.6.2. Control Group

The control group received a single 45-minute theoretical lecture covering the principles of laparoscopic visualization, including depth perception, camera stability, and fulcrum mechanics, without structured hands-on training. This approach reflects the traditional imbalance in early surgical education, where trainees often receive theoretical instruction without equivalent practical exposure, and aligns with “lecture-only” comparator models used in previous minimally invasive surgery training studies [25].

To allow comparison of performance trends over time, participants in the control group performed the same standardized assessment tasks at matched time intervals but did not receive structured training or feedback between sessions.

2.6.3. Study Timeline

The study followed a structured timeline. All participants first completed a baseline assessment of camera-handling performance across the three camera angles (umbilical, Palmer’s Point, and Lee-Huang), using the standardized simulator setup shown in Figure 3. Following randomization, the intervention group completed fifteen simulation sessions (five per camera angle) over the study period, while the control group did not undergo structured training. Performance assessments were conducted at five predefined time points to evaluate progression over time. Both groups then completed a final post-intervention assessment using identical tasks and outcome measures.

Performance was assessed at both baseline and post-training using the same standardized laparoscopic task [26] for all participants. The primary assessment consisted of a modified peg-transfer drill designed to evaluate essential components of camera handling and visuospatial control. During the task, participants were required to manipulate the laparoscopic camera with one hand while maintaining a level horizon, preserving continuous visualization of the target field, demonstrating accurate depth perception, and completing object transfers without losing sight of the operative area. A single, uniform task template was used throughout the study to ensure consistency across all assessments and to minimize variability between participants and testing sessions.

2.8.1. Quantitative Outcome Measures

Outcome measures included both objective and subjective assessments of performance. Task completion time was recorded from the start of visualization to the end of the bean-transfer sequence, while error rates captured occurrences such as dropped objects, loss of target view, horizon tilt, excessive shaking, or camera repositioning. Camera stability was rated on a 0 - 5 scale by a blinded reviewer. Subjective performance was evaluated using a Likert-scale questionnaire assessing visualization clarity, depth perception, spatial orientation, perceived difficulty, and confidence with camera manipulation. This questionnaire reflected established self-assessment tools used in laparoscopic skills training.

2.8.2. Qualitative Outcome Measures

A qualitative component was incorporated to complement the quantitative findings and provide deeper insight into the cognitive processes underlying camera angulation skill acquisition. Semi-structured interviews lasting approximately 15 minutes were conducted with participants in the study group following completion of the training protocol. These interviews explored trainees’ perceptions of differences between the three camera angles, the cognitive challenges associated with off-axis visualization, the adaptive strategies developed during repeated practice, and perceived progression in visuospatial understanding over time.

All interviews were audio-recorded and transcribed verbatim. The transcripts were analyzed using an inductive thematic approach [27]. Two researchers independently coded the data using an iterative process. An initial coding framework was developed based on recurring patterns and refined through discussion. Discrepancies were resolved by consensus, and final themes were generated to ensure consistency and representativeness of participant experiences. Triangulation with quantitative findings was used to enhance interpretive depth.

Quantitative data were analyzed using IBM SPSS Statistics (version 27.0; IBM Corp., Armonk, NY, USA). Continuous variables are presented as mean ± standard deviation (SD). Between-group comparisons were performed using independent samples t-tests or non-parametric equivalents where appropriate, depending on data distribution [28].

A mixed-design analysis of variance (ANOVA) was conducted to evaluate the effects of group (simulation-trained vs control) as the between-subject factor and repeated measures (session or camera angle, as applicable) as the within-subject factor. Interaction effects between group and repeated measures were also assessed [28]. Assumptions of normality and sphericity were evaluated using the Shapiro-Wilk and Mauchly’s tests, respectively. Where violations of sphericity were detected, Greenhouse-Geisser corrections were applied. Post hoc comparisons were performed using Bonferroni adjustment. Missing data were minimal and handled using listwise deletion. Statistical significance was set at p < 0.05 [28].

Qualitative data were analyzed using Braun and Clarke’s six-phase thematic analysis, allowing for inductive generation of themes. Triangulation with quantitative findings was used to enhance interpretive depth and ensure consistency across data sources [27].

Ethical approval was obtained from the institutional review board of Zhejiang Provincial People’s Hospital. Participation was voluntary, and all students provided written informed consent. Confidentiality was maintained by anonymizing videos and interview transcripts. Participants were free to withdraw at any time without academic penalty.

Operation Time on 3D-Printed Model

Across five repeated assessment sessions, the study group demonstrated significantly faster operation times compared with the control group (all p < 0.001). Although the control group did not receive structured training, they completed the same assessment tasks at matched time intervals to enable comparison of performance trends over time.

As shown in Figure 4, the study group outperformed the control group from the first session onward. At the first session, the study group completed the task in 354.71 ± 46.80 s, compared with 742.50 ± 95.54 s in the control group (F = 94.735, p < 0.001). This difference remained significant across all sessions, with final session times of 281.71 ± 62.51 s in the study group and 587.50 ± 94.80 s in the control group (F = 52.560, p < 0.001).

Repeated-measures ANOVA demonstrated a significant main effect of group (F = 81.632, p < 0.001), a significant effect of session (F = 55.851, p < 0.001), and a significant group × session interaction (F = 8.528, p < 0.001).

Simple-effects analysis showed that both groups exhibited reductions in operation time across sessions (p < 0.05 for all comparisons). However, the study group demonstrated a more consistent pattern of improvement, with significant reductions primarily observed between early and later sessions (1st vs 3rd, 2nd vs 3rd, 1st vs 5th, and 2nd vs 5th).

Overall, task completion time was significantly shorter in the simulation-trained group compared to the control group across all assessment sessions, as presented in Table 2.

Table 2. Operation time on 3D model across training sessions between groups.

Note: a means compared with 1st session, p < 0.05; b means compared with 2nd session, p < 0.05; c means compared with 3rd session, p < 0.05; d means compared with 4th session, p < 0.05; BSE: Between-Subjects Effects; WSE: Within-Subjects Effects; IE: Interactions Effects.

Figure 4.Learning curves for task completion time across training sessions showing mean task completion times across five repeated sessions for the simulation-trained and control groups, demonstrating progressive improvement and superior performance in the trained group.

Comparison between Umbilical and Non-Umbilical Angulations

Subjective evaluations from the seven study-group participants demonstrated that the umbilical angle was consistently perceived as more favorable than non-umbilical angles across several performance domains. Participants reported significantly better instrument control at the umbilical entry (median 4.0 vs. 3.0, p = 0.017), along with improved spatial orientation (3.0 vs. 2.0, p = 0.038) and more effective camera-instrument coordination (4.0 vs. 3.0, p = 0.011). They also found tasks easier to complete smoothly and without discomfort under the umbilical angle (5.0 vs. 3.0, p = 0.001), and described the learning curve as gentler and quicker to master compared with non-umbilical angles (3.0 vs. 2.0, p = 0.007). In contrast, no significant differences were observed between the two angle categories regarding visual clarity and depth perception (p = 0.073) or levels of stress and concentration (p = 0.535). These findings suggest that while perceptual clarity was similar across visualization angles, the umbilical view provided distinct advantages in motor control and spatial processing. Participants’ self-evaluation revealed a strong preference for the umbilical camera angle over other angulations. The umbilical angle was rated significantly higher for instrument control accuracy, reduction of spatial disorientation, minimization of visual obstruction, task completion smoothness, and a gentler learning curve (Table 3).

Table 3. Self-Evaluation of operative performance under different camera angles.

Participants rated instructor guidance and the training structure extremely highly, with median scores of 5.0 for skill development, spatial awareness, camera coordination, and hand-eye coordination. Willingness to undergo additional non-standard angle training also scored 5.0 (IQR 3.0 - 5.0). Participants strongly agreed that laparoscopic training curricula should incorporate tasks using varying camera angles (4.0 (3.0 - 5.0)) and that the training design has meaningful potential to enhance teaching systems (4.0 (4.0 - 5.0)). Overall, the subjective assessment indicated that participants found the training highly valuable. The guidance from instructors and the improvement in spatial and hand-eye coordination were rated highest, and most participants agreed that laparoscopic curricula should include training from different camera perspectives (Table 4).

Table 4. Subjective assessment of training effectiveness and educational value.

Semi-structured interviews revealed three major themes:

3.4.1. Cognitive Difficulty and Adaptation

Participants initially described off-axis views, especially Palmer’s Point, as disorienting and mentally challenging. This experience aligns with findings by Aust and other researchers [29][30], who noted that repeated exposure helps novices learn to anticipate rotational discrepancies and make better sense of spatial cues.

P5: “The off-axis perspective forced me to think harder than usual. But the more I practiced, the quicker I adapted. Eventually, interpreting those angles felt much easier.”

3.4.2. Importance of Repetition and Structured Practice

Repetition was consistently identified by participants as essential for developing proficiency. Although many described the early sessions as mentally taxing, they also noted a clear reduction in cognitive effort as practice progressed.

P2: “At the beginning, it felt mentally exhausting, but after repeating the task several times, it became much easier to manage.”

This progression aligns with the findings of Sankaranarayanan et al. [31], who reported that repeated training, particularly under cognitive load, enhances learners’ ability to manage mental demands and improves performance in real surgical tasks. Together, these insights highlight the value of structured, repetitive practice in building both skill and cognitive resilience.

3.4.3. Angle-Specific Learning Curves and Preferences

Participants reported clear differences in how easily they adapted to each viewing angle. The umbilical angle was consistently preferred for its intuitive and ergonomically favorable orientation. In contrast, the Lee-Huang angle, though initially unfamiliar, became manageable with repeated exposure. Palmer’s Point remained the most challenging due to its off-axis perspective, yet participants noted meaningful progress with structured guidance. One trainee reflected,

P1: “With Palmer’s Point, I kept losing my sense of direction at first, but once I understood the angle’s logic, my confidence improved a lot.”

These observations align with Supe et al. [5], who emphasized the importance of ergonomically optimized views in reducing cognitive strain and improving efficiency in laparoscopic performance. The participants’ experiences highlight how ergonomic principles shape angle-specific learning curves and influence preferences during skill development.

Tables 5-7 present angle-specific performance outcomes for task completion time, error rates, and camera stability across the three camera positions (umbilical, Lee-Huang, and Palmer’s Point).

Table 5.Task completion time across camera angles.

Note: Values are presented as mean ± standard deviation. p-values from independent-samples t-tests comparing groups at each camera angle.

Table 6.Error rates across camera angles.

Note: Error rates represent the mean number of errors per task. Values are presented as mean ± standard deviation. p-values derived from independent samples t-tests.

Table 7. Camera stability scores across camera angles.

Note: Camera stability was assessed on a 0 - 5 scale by a blinded evaluator. Higher scores indicate better stability. Values are presented as mean ± standard deviation. p-values derived from independent samples t-tests.

The simulation-trained group demonstrated significantly superior performance compared to the control group across all camera angles (all p < 0.001). This included markedly faster task completion times, fewer procedural errors, and improved camera stability at each viewing position. Among the angles, the umbilical position consistently demonstrated the most efficient performance, whereas Palmer’s Point represented the most challenging orientation.

For task completion time, a mixed-design ANOVA revealed a significant main effect of group (p < 0.001, η p 2 = 0.999), indicating that the simulation-trained group performed substantially faster than controls. A significant main effect of camera angle was also observed (p < 0.001, η p 2 = 1.000), confirming that performance differed across the three viewing positions. Additionally, a significant interaction between group and camera angle (p < 0.001, η p 2 = 0.994) indicated that the magnitude of training-related improvement varied depending on camera angulation.

Analysis of error rates similarly demonstrated a significant main effect of group (p < 0.001, η p 2 = 0.959), with fewer errors observed in the simulation-trained group. A significant main effect of camera angle (p < 0.001, η p 2 = 0.979) and a significant interaction effect (p < 0.001, η p 2 = 0.790) were also identified, indicating that error reduction differed across the three camera positions.

Camera stability scores followed the same pattern. There was a significant main effect of group (p < 0.001, η p 2 = 0.992), with higher stability achieved by the trained participants. A significant effect of camera angle (p < 0.001, η p 2 = 0.942), along with a significant interaction effect (p < 0.001, η p 2 = 0.584), demonstrated that improvements in stability were dependent on camera angulation. The very large effect sizes observed should be interpreted in the context of the small sample size and controlled simulation environment. Overall, these findings confirm that simulation-based training not only enhances performance across all viewing conditions but also differentially improves adaptation to specific camera angles, with the greatest benefits observed in more complex, off-axis perspectives.

Across objective metrics, subjective ratings, and qualitative feedback, structured simulation-based camera-angulation training produced clear improvements in operative performance. Trainees who received systematic practice demonstrated faster completion times, fewer errors, greater stability, and stronger visuospatial confidence than controls. Collectively, these results support the incorporation of angle-specific camera-handling modules into early laparoscopic skills curricula.