The goal of this trial is to compare the effect of using 3D-enhanced versus standard 3D (three-dimensional) training models when novice medical students practise certain laparoscopic tasks. The main question our trial aims to answer is:

-Are the 3D-enhanced training models used superior compared to the existing standard 3D LapPass training models for laparoscopic skills learning in novice medical students?

Participants will be assigned in one of the 2 groups and practise laparoscopic tasks in 2 separate sessions.

There is ample evidence supporting the use of low-fidelity surgical simulators, often referred to as benchtop models, for fundamental laparoscopic skills acquisition using both basic and advanced tasks. The purpose of using low-fidelity training models is mainly skills acquisition rather than recreation of in situ anatomy. Benchtop models have the potential to be low-cost compared to other high-fidelity simulators, whilst enhancing transferability of those vital skills to the operative room. It has been demonstrated in the literature that the use of the 3D visual systems in laparoscopy is associated with an improved depth perception providing an enhanced visuo-spatial context and performance in the surgical or simulation setting, facilitating the execution of complex laparoscopic tasks. The use of this technology is often associated with certain limitations of adaptability to personnel, practicalities and financial considerations of its introduction to the everyday teaching curriculum of novice individuals. Hence, there is potential of following a differential approach by utilising low-fidelity, 3D-enhanced training models with increased dimensionality and spatial complexity to expedite training and skill acquisition in the 2D visual modality, which is most commonly used both in the simulation and operative settings.

Monocular cues are important to compensate for lack of depth perception in 2D vision. These include motion parallax through movement of the laparoscope, shading of light and dark, texture grading, relative position and instrument and anatomic structure size. Depth perception can be improved through experience as processing of monocular cues is enhanced and adaptation, which is a learning process, ultimately results to improved performance. Experienced surgeons have mastered the skill of identifying indirect monocular cues and gain depth perception by utilising them, resulting to accurate and efficient movements.

The 3D training models used in LapPass for training and assessment purposes lack variable contours and spatial complexity. In the current model for the polo manipulation and grasping task, all the posts are on the same height and mounted on a flat surface, This is the first exercise performed and heavily practised by novices to develop the fundamental laparoscopic skills of depth perception, hand-eye coordination and bimanual dexterity, which are vital for smooth progression to the other tasks. The laparoscopic suturing and intracorporeal knot tying task, similarly, introduces a 3D training model for suturing and approximation of slightly indented circles on a flat suturing pad. Perhaps, the adoption of these standard 3D training models could act as a limiting factor in technical skills acquisition and ultimately prolong the training time to achieve a higher level of expertise, compared to other improved alternatives. Achieving proficiency in basic laparoscopic skills can result in faster acquisition of more complex laparoscopic skills such as suturing and ultimately results to a more cost-effective training. By increasing the dimensionality of the tasks, a more realistic surgical environment could be achieved, addressing this potential technical skills gap and leading to faster, more cost-effective training.

In this study, the polo task will be converted using a 3D-enhanced Jenga polo model developed in our institution. The model was initially developed for the FLS program's simpler peg transfer task and the equipment will be adjusted to simulate the LapPass polo grasping and manipulation task, a more technically demanding task. In addition, the suturing task will be converted using a 3D-enhanced suturing model by Inovus Medical (Saint Helens, England, UK) attached on a platform providing limited stability to the model, which simulates sufficiently complexities in surgical practise.

Literature describing a direct comparison between 3D-enhanced and standard 3D training models of LapPass basic and advanced laparoscopic tasks is absent, despite the potential of fast-tracking laparoscopic skills acquisition in novices. We postulate that the use of 3D-enhanced training models at the onset of laparoscopic skills training of novices could accelerate the adaptation to indirect cues related to depth perception, as well as other core skills of laparoscopic skills training, enhancing performance. The aim of this study is to determine if laparoscopic technical skills acquisition will be superior with the use of 3D-enhanced training models in novice medical students when compared to the standard 3D LapPass training models in two distinct laparoscopic tasks.

PICOS criteria

• Population = Novice medical students from Year 1-5 including intercalating students
• Intervention = 3D-enhanced training models for polo manipulation and suturing tasks
• Comparator = Standard 3D LapPass training models for polo manipulation and suturing tasks
• Outcomes = Laparoscopic skill acquisition (GOALS score, Task completion time, Errors, Survey data)
• Setting = Simulation lab in Barts Cancer Institute

Inclusion Criteria:

• (1) Medical students from Year 1 to Year 5 including intercalating students
• (2) Novices in laparoscopic surgery defined as having no formal laparoscopic skills training beyond camera navigation

Exclusion Criteria:

• (1) Undertaken at least one session of laparoscopic skills training
• (2) Uncommitted to the completion of the study

Study Protocol, Informed Consent, Surveys and Study Report

Anonymised participant data will be retained for a period of at least 10 years from the date of any publication which is based upon it, as specified in the QMUL Records Retention schedule. After this period all data will be destroyed.

On request