Skip to main content

Advertisement

SpringerLink
Log in

Simulation platforms to assess laparoscopic suturing skills: a scoping review

  • Review Article
  • Published:
Surgical Endoscopy Aims and scope Submit manuscript

Abstract

Background

Laparoscopic suturing (LS) has become a common technique used in a variety of advanced laparoscopic procedures. However, LS is a challenging skill to master, and many trainees may not be competent in performing LS at the end of their training. The purpose of this review is to identify simulation platforms available for assessment of LS skills, and determine the characteristics of the platforms and the LS skills that are targeted.

Methods

A scoping review was conducted between January 1997 and October 2018 for full-text articles. The search was done in various databases. Only articles written in English or French were included. Additional studies were identified through reference lists. The search terms included “laparoscopic suturing” and “clinical competence.”

Results

Sixty-two studies were selected. The majority of the simulation platforms were box trainers with inanimate tissue, and targeted basic suturing and intracorporeal knot-tying techniques. Most of the validation came from internal structure (rater reliability) and relationship to other variables (compare training levels/case experience, and various metrics). Consequences were not addressed in any of the studies.

Conclusion

We identified many types of simulation platforms that were used for assessing LS skills, with most being for assessment of basic skills. Platforms assessing the competence of trainees for advanced LS skills were limited. Therefore, future research should focus on development of LS tasks that better reflect the needs of the trainees.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Similar content being viewed by others

References

  1. Palter VN, Orzech N, Aggarwal R, Okrainec A, Grantcharov TP (2010) Resident perceptions of advanced laparoscopic skills training. Surg Endosc 24:2830–2834

    Article  PubMed  Google Scholar 

  2. Rattner DW, Apelgren KN, Eubanks WS (2001) The need for training opportunities in advanced laparoscopic surgery. Surg Endosc 15:1066–1070

    Article  CAS  PubMed  Google Scholar 

  3. Enani G, Watanabe Y, McKendy KM, Bilgic E, Feldman LS, Fried GM, Vassiliou MC (2017) What are the training gaps for acquiring laparoscopic suturing skills? J Surg Educ 74:656–662

    Article  PubMed  Google Scholar 

  4. Nepomnayshy D, Alseidi AA, Fitzgibbons SC, Stefanidis D (2016) Identifying the need for and content of an advanced laparoscopic skills curriculum: results of a national survey. Am J Surg 211:421–425

    Article  PubMed  Google Scholar 

  5. Mattar SG, Alseidi AA, Jones DB, Jeyarajah DR, Swanstrom LL, Aye RW, Wexner SD, Martinez JM, Ross SB, Awad MM, Franklin ME, Arregui ME, Schirmer BD, Minter RM (2013) General surgery residency inadequately prepares trainees for fellowship: results of a survey of fellowship program directors. Ann Surg 258:440–449

    Article  Google Scholar 

  6. Ghaderi I, Manji F, Park YS, Juul D, Ott M, Harris I, Farrell TM (2015) Technical skills assessment toolbox: a review using the unitary framework of validity. Ann Surg 261:251–262

    Article  Google Scholar 

  7. Downing S (2003) Validity: on meaningful interpretation of assessment data. Med Educ 37:830–837

    Article  PubMed  Google Scholar 

  8. Leeds SG, Wooley L, Sankaranarayanan G, Daoud Y, Fleshman J, Chauhan S (2017) Learning curve associated with an automated laparoscopic suturing device compared with laparoscopic suturing. Surg Innovat 24:109–114

    Article  Google Scholar 

  9. Sánchez-Margallo JA, Sánchez-Margallo FM, Oropesa I, Enciso S, Gómez EJ (2016) Objective assessment based on motion-related metrics and technical performance in laparoscopic suturing. Int J Comput Assist Radiol Surg 12:1–8

    Article  Google Scholar 

  10. Kowalewski KF, Hendrie JD, Schmidt MW, Garrow CR, Bruckner T, Proctor T, Paul S, Adigüzel D, Bodenstedt S, Erben A, Kenngott H, Erben Y, Speidel S, Müller-Stich BP, Nickel F (2016) Development and validation of a sensor- and expert model-based training system for laparoscopic surgery: the iSurgeon. Surg Endosc 31:1–11

    Google Scholar 

  11. Deal SB, Lendvay TS, Haque MI, Brand T, Comstock B, Warren J, Alseidi A (2016) Crowd-sourced assessment of technical skills: an opportunity for improvement in the assessment of laparoscopic surgical skills. Am J Surg 211:398–404

    Article  PubMed  Google Scholar 

  12. Chang OH, King LP, Modest AM, Hur HC (2016) Developing an objective structured assessment of technical skills for laparoscopic suturing and intracorporeal knot tying. J Surg Educ 73:258–263

    Article  PubMed  Google Scholar 

  13. Stefanidis D, Gardner C, Paige JT, Korndorffer JR Jr, Nepomnayshy D, Chapman D (2015) Multicenter longitudinal assessment of resident technical skills. Am J Surg 209:120–125

    Article  PubMed  Google Scholar 

  14. Escamirosa FP, Flores RM, Garcia IO, Vidal CR, Martinez AM (2015) Face, content, and construct validity of the EndoViS training system for objective assessment of psychomotor skills of laparoscopic surgeons. Surg Endosc 29:3392–3403

    Article  PubMed  Google Scholar 

  15. Buckley CE, Kavanagh DO, Nugent E, Ryan D, Traynor OJ, Neary PC (2015) Zone calculation as a tool for assessing performance outcome in laparoscopic suturing. Surg Endosc 29:1553–1559

    Article  PubMed  Google Scholar 

  16. Trejos AL, Patel RV, Malthaner RA, Schlachta CM (2014) Development of force-based metrics for skills assessment in minimally invasive surgery. Surg Endosc 28:2106–2119

    Article  PubMed  Google Scholar 

  17. Stefanidis D, Grewal H, Paige JT, Korndorffer JR, Scott DJ, Nepomnayshy D, Edelman DA, Sievers C (2014) Establishing technical performance norms for general surgery residents. Surg Endosc 28:3179–3185

    Article  PubMed  Google Scholar 

  18. Romero P, Brands O, Nickel F, Muller B, Gunther P, Holland-Cunz S (2014) Intracorporal suturing–driving license necessary? J Pediatr Surg 49:1138–1141

    Article  CAS  PubMed  Google Scholar 

  19. Lusch A, Bucur PL, Menhadji AD, Okhunov Z, Liss MA, Perez-Lanzac A, McDougall EM, Landman J (2014) Evaluation of the impact of three-dimensional vision on laparoscopic performance. J Endourol 28:261–266

    Article  PubMed  Google Scholar 

  20. Kowalewski TM, White LW, Lendvay TS, Jiang IS, Sweet R, Wright A, Hannaford B, Sinanan MN (2014) Beyond task time: automated measurement augments fundamentals of laparoscopic skills methodology. J Surg Res 192:329–338

    Article  PubMed  Google Scholar 

  21. Steinemann DC, Limani P, Clavien PA, Breitenstein S (2013) Internal retraction in single-port laparoscopic cholecystectomy: initial experience and learning curve. Minim Invasive Ther Allied Technol 22:171–176

    Article  PubMed  Google Scholar 

  22. Hennessey IA, Hewett P (2013) Construct, concurrent, and content validity of the eoSim laparoscopic simulator. J Laparoendosc Adv Surg Tech A 23:855–860

    Article  PubMed  Google Scholar 

  23. Boza C, Varas J, Buckel E, Achurra P, Devaud N, Lewis T, Aggarwal R (2013) A cadaveric porcine model for assessment in laparoscopic bariatric surgery–a validation study. Obes Surg 23:589–593

    Article  PubMed  Google Scholar 

  24. Palter VN, Graafland M, Schijven MP, Grantcharov TP (2012) Designing a proficiency-based, content validated virtual reality curriculum for laparoscopic colorectal surgery: a Delphi approach. Surgery 151:391–397

    Article  Google Scholar 

  25. Pagador JB, Sanchez-Margallo FM, Sanchez-Peralta LF, Sanchez-Margallo JA, Moyano-Cuevas JL, Enciso-Sanz S, Uson-Gargallo J, Moreno J (2012) Decomposition and analysis of laparoscopic suturing task using tool-motion analysis (TMA): improving the objective assessment. Int J Comput Assist Radiol Surg 7:305–313

    Article  CAS  PubMed  Google Scholar 

  26. Yamaguchi S, Yoshida D, Kenmotsu H, Yasunaga T, Konishi K, Ieiri S, Nakashima H, Tanoue K, Hashizume M (2011) Objective assessment of laparoscopic suturing skills using a motion-tracking system. Surg Endosc 25:771–775

    Article  PubMed  Google Scholar 

  27. Strickland A, Fairhurst K, Lauder C, Hewett P, Maddern G (2011) Development of an ex vivo simulated training model for laparoscopic liver resection. Surg Endosc 25:1677–1682

    Article  Google Scholar 

  28. Hiemstra E, Chmarra MK, Dankelman J, Jansen FW (2011) Intracorporeal suturing- economy of instrument movements using a box trainer model. J Minim Invasive Gynecol 18:494–499

    Article  PubMed  Google Scholar 

  29. Zheng B, Cassera MA, Martinec DV, Spaun GO, Swanstrom LL (2010) Measuring mental workload during the performance of advanced laparoscopic tasks. Surg Endosc 24:45–50

    Article  PubMed  Google Scholar 

  30. Lin DW, Romanelli JR, Kuhn JN, Thompson RE, Bush RW, Seymour NE (2009) Computer-based laparoscopic and robotic surgical simulators: performance characteristics and perceptions of new users. Surg Endosc 23:209–214

    Article  PubMed  Google Scholar 

  31. Kroeze SG, Mayer EK, Chopra S, Aggarwal R, Darzi A, Patel A (2009) Assessment of laparoscopic suturing skills of urology residents: a pan-European study. Eur Urol 56:865–872

    Article  PubMed  Google Scholar 

  32. Botden SM, de Hingh IH, Jakimowicz JJ (2009) Meaningful assessment method for laparoscopic suturing training in augmented reality. Surg Endosc 23:2221–2228

    Article  PubMed  PubMed Central  Google Scholar 

  33. Zheng B, Denk PM, Martinec DV, Gatta P, Whiteford MH, Swanstrom LL (2008) Building an efficient surgical team using a bench model simulation: construct validity of the Legacy Inanimate System for Endoscopic Team Training (LISETT). Surg Endosc 22:930–937

    Article  CAS  PubMed  Google Scholar 

  34. Dayan AB, Ziv A, Berkenstadt H, Munz Y (2008) A simple, low-cost platform for basic laparoscopic skills training. Surg Innov 15:136–142

    Article  PubMed  Google Scholar 

  35. Stefanidis D, Scerbo MW, Korndorffer JR Jr, Scott DJ (2007) Redefining simulator proficiency using automaticity theory. Am J Surg 193:502–506

    Article  PubMed  Google Scholar 

  36. Dubrowski A, Larmer JC, Leming JK, Brydges R, Carnahan H, Park J (2006) Quantification of process measures in laparoscopic suturing. Surg Endosc 20:1862–1866

    Article  CAS  PubMed  Google Scholar 

  37. Broe D, Ridgway PF, Johnson S, Tierney S, Conlon KC (2006) Construct validation of a novel hybrid surgical simulator. Surg Endosc 20:900–904

    Article  CAS  PubMed  Google Scholar 

  38. Van Sickle KR, McClusky DA 3rd, Gallagher AG, Smith CD (2005) Construct validation of the ProMIS simulator using a novel laparoscopic suturing task. Surg Endosc 19:1227–1231

    Article  PubMed  Google Scholar 

  39. Duffy AJ, Hogle NJ, McCarthy H, Lew JI, Egan A, Christos P, Fowler DL (2005) Construct validity for the LAPSIM laparoscopic surgical simulator. Surg Endosc 19:401–405

    Article  CAS  PubMed  Google Scholar 

  40. Moorthy K, Munz Y, Dosis A, Bello F, Chang A, Darzi A (2004) Bimodal assessment of laparoscopic suturing skills: construct and concurrent validity. Surg Endosc 18:1608–1612

    CAS  PubMed  Google Scholar 

  41. Figert PL, Park AE, Witzke DB, Schwartz RW (2001) Transfer of training in acquiring laparoscopic skills. J Am Coll Surg 193:533–537

    Article  CAS  PubMed  Google Scholar 

  42. Poursartip B, LeBel ME, Patel R, Naish M, Trejos AL (2017) Analysis of energy-based metrics for laparoscopic skills assessment. IEEE Trans Biomed Eng 65:1532–1542

    Article  PubMed  Google Scholar 

  43. Botden SM, Buzink SN, Schijven MP, Jakimowicz JJ (2007) Augmented versus virtual reality laparoscopic simulation: what is the difference? A comparison of the ProMIS augmented reality laparoscopic simulator versus LapSim virtual reality laparoscopic simulator. World J Surg 31:764–772

    Article  PubMed  PubMed Central  Google Scholar 

  44. Kobayashi SA, Jamshidi R, O’Sullivan P, Palmer B, Hirose S, Stewart L, Kim EH (2011) Bringing the skills laboratory home: an affordable webcam-based personal trainer for developing laparoscopic skills. J Surg Educ 68:105–109

    Article  PubMed  Google Scholar 

  45. Trudeau MO, Nasr A, Carrillo B, Gerstle JT, Azzie G (2015) Construct validity and educational role for motion analysis in a laparoscopic trainer. Surg Endosc 29:2491–2495

    Article  PubMed  Google Scholar 

  46. Sharma M, Macafee D, Pranesh N, Horgan AF (2012) Construct validity of fresh frozen human cadaver as a training model in minimal access surgery. JSLS 16:345–352

    Article  PubMed  PubMed Central  Google Scholar 

  47. Kowalewski K-F, Hendrie JD, Schmidt MW, Garrow CR, Bruckner T, Proctor T, Paul S, Adiguzel D, Bodenstedt S, Erben A, Kenngott H, Erben Y, Speidel S, Muller-Stich BP, Nickel F (2017) Development of a sensor-and expert model based training device for suturing and knot tying in laparoscopic surgery. Surg Endosc 31:2155–2165

    Article  PubMed  Google Scholar 

  48. Horeman T, Rodrigues SP, Jansen FW, Dankelman J, Van Den Dobbelsteen JJ (2010) Force measurement platform for training and assessment of laparoscopic skills. Surg Endosc Other Interv Tech 24:3102–3108

    Article  Google Scholar 

  49. Rosser JC Jr, Liu X, Jacobs C, Choi KM, Jalink MB, Ten Cate Hoedemaker HO (2017) Impact of Super Monkey Ball and Underground video games on basic and advanced laparoscopic skill training. Surg Endosc 31:1544–1549

    Article  PubMed  Google Scholar 

  50. Zdichavsky M, Krautwald M, Feilitzsch MV, Wichmann D, Konigsrainer A, Schurr MO (2016) Laparoscopic gastro-jejunal anastomosis using novel r2 deflectable instruments in an ex vivo model. Minim Invasive Ther Allied Technol 25:91–98

    Article  PubMed  Google Scholar 

  51. Uemura MYM, Tomikawa M, Obata S, Souzaki R, Ieiri S, Ohuchida K, Matsuoka N, Katayama T, Hashizume M (2015) Objective assessment of the suture ligature method for the laparoscopic intestinal anastomosis model using a new computerized system. Surg Endosc 29(2):444–452

    Article  PubMed  Google Scholar 

  52. Veneziano D, Poniatowski LH, Reihsen TE, Sweet RM (2016) Preliminary evaluation of the SimPORTAL major vessel injury (MVI) repair model. Surg Endosc 30:1405–1412

    Article  PubMed  Google Scholar 

  53. Keyser EJ, Derossis AM, Antoniuk M, Sigman HH, Fried GM (2000) A simplified simulator for the training and evaluation of laparoscopic skills. Surg Endosc 14:149–153

    Article  CAS  PubMed  Google Scholar 

  54. Xeroulis G, Dubrowski A, Leslie K (2009) Simulation in laparoscopic surgery: a concurrent validity study for FLS. Surg Endosc 23:161–165

    Article  PubMed  Google Scholar 

  55. Bahsoun AN, Malik MM, Ahmed K, El-Hage O, Jaye P, Dasgupta P (2013) Tablet based simulation provides a new solution to accessing laparoscopic skills training. J Surg Educ 70:161–163

    Article  PubMed  Google Scholar 

  56. Oostema JA, Abdel MP, Gould JC (2008) Time-efficient laparoscopic skills assessment using an augmented-reality simulator. Surg Endosc 22:2621–2624

    Article  PubMed  Google Scholar 

  57. Sleiman Z, Atallah E, Rassi E, Sarkis R, Khazzaka A (2017) Validation study of a portable home trainer using a pad for laparoscopic practice. Surg Innov 24:284–288

    Article  PubMed  Google Scholar 

  58. Yeung C, Carrillo B, Pope V, Hosseinpour S, Gerstle JT, Azzie G (2017) Video assessment of laparoscopic skills by novices and experts: implications for surgical education. Surg Endosc 31:3883–3889

    Article  PubMed  Google Scholar 

  59. Anton NE, Sawyer JM, Korndorffer JR Jr, DuCoin CG, McRary G, Timsina LR, Stefanidis D (2018) Developing a robust suturing assessment: validity evidence for the intracorporeal suturing assessment tool. Surgery 163:560–564

    Article  PubMed  Google Scholar 

  60. Bilgic E, Takao M, Kaneva P, Satoshi E, Takao T, Watanabe Y, McKendy KM, Feldman LS, Vassiliou MC (2018) Development of a model for the acquisition and assessment of advanced laparoscopic suturing skills using an automated device. Surg Innov 25:286–290

    Article  PubMed  Google Scholar 

  61. Bilgic E, Watanabe Y, Nepomnayshy D, Gardner A, Fitzgibbons S, Ghaderi I, Alseidi A, Stefanidis D, Paige J, Seymour N, McKendy KM, Birkett R, Whitledge J, Kane E, Anton NE, Vassiliou MC, Simulation Committee of the Association for Surgical E (2017) Multicenter proficiency benchmarks for advanced laparoscopic suturing tasks. Am J Surg 213:217–221

    Article  PubMed  Google Scholar 

  62. McKendy KM, Watanabe Y, Bilgic E, Enani G, Munshi A, Lee L, Feldman LS, Fried GM, Vassiliou MC (2017) Establishing meaningful benchmarks: the development of a formative feedback tool for advanced laparoscopic suturing. Surg Endosc 31:5057–5065

    Article  PubMed  Google Scholar 

  63. Nepomnayshy D, Whitledge J, Birkett R, Delmonico T, Ruthazer R, Sillin L, Seymour NE (2015) Evaluation of advanced laparoscopic skills tasks for validity evidence. Surg Endosc 29:349–354

    Article  PubMed  Google Scholar 

  64. Poursartip B, Lebel ME, Patel RV, Naish MD, Trejos AL (2018) Analysis of energy-based metrics for laparoscopic skills assessment. IEEE Trans Biomed Eng 65:1532–1542

    Article  PubMed  Google Scholar 

  65. Sawyer JM, Anton NE, Korndorffer JR Jr, DuCoin CG, Stefanidis D (2018) Time crunch: increasing the efficiency of assessment of technical surgical skill via brief video clips. Surgery 163:933–937

    Article  PubMed  Google Scholar 

  66. Takayasu K, Yoshida K, Mishima T, Watanabe M, Matsuda T, Kinoshita H (2018) Upper body position analysis of different experience level surgeons during laparoscopic suturing maneuvers using optical motion capture. Am J Surg 21:12–16

    Google Scholar 

  67. Watanabe Y, McKendy KM, Bilgic E, Enani G, Madani A, Munshi A, Feldman LS, Fried GM, Vassiliou MC (2016) New models for advanced laparoscopic suturing: taking it to the next level. Surg Endosc 30:581–587

    Article  PubMed  Google Scholar 

  68. Wee J, Azzie G, Drake J, Gerstle JT (2018) Proof of concept study: investigating force metrics of an intracorporeal suturing knot task. J Laparoendosc Adv Surg Tech A 28:899–905

    Article  PubMed  Google Scholar 

  69. Yamaguchi T, Nakamura R (2018) Laparoscopic training using a quantitative assessment and instructional system. Int J Comput Assist Radiol Surg 13:1453–1460

    Article  CAS  PubMed  Google Scholar 

  70. Vassiliou MC, Ghitulescu GA, Feldman LS, Stanbridge D, Leffondré K, Sigman HH, Fried GM (2006) The MISTELS program to measure technical skill in laparoscopic surgery: evidence for reliability. Surg Endosc 20:744–747

    Article  CAS  PubMed  Google Scholar 

  71. Ritter ME, Scott DJ (2007) Design of a proficiency-based skills training curriculum for the fundamentals of laparoscopic Surgery. Surg Innov 14:107–112

    Article  PubMed  Google Scholar 

  72. Fried GM, Feldman LS, Vassiliou MC, Fraser SA, Stanbridge D, Ghitulescu G, Andrew CG (2004) Proving the value of simulation in laparoscopic surgery. Ann Surg 240:518–528

    Article  PubMed  PubMed Central  Google Scholar 

  73. Fried GM (2008) FLS assessment of competency using simulated laparoscopic tasks. J Gastrointest Surg 12:210–212

    Article  PubMed  Google Scholar 

  74. Mason JD, Ansell J, Warren N, Torkington J (2013) Is motion analysis a valid tool for assessing laparoscopic skill? Surg Endosc 27:1468–1477

    Article  PubMed  Google Scholar 

  75. Chmarra MK, Grimbergen CA, Dankelman J (2007) Systems for tracking minimally invasive surgical instruments. Minim Invasive Ther Allied Technol 16:328–340

    Article  CAS  PubMed  Google Scholar 

  76. Pugh CM, Arafat FO, Kwan C, Cohen ER, Kurashima Y, Vassiliou MC, Fried GM (2015) Development and evaluation of a simulatoin-based continuing medical education course: beyond lectures and credit hours. Am J Surg 210:603–609

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

We would like to thank the members of the Henry K.M. DeKuyper Education Centre, Steinberg-Bernstein Centre for Minimally Invasive Surgery and Innovation, and Steinberg Centre for Simulation and Interactive Learning for their help in conducting this study.

Funding

There was no funding or financial support for this work.

Author information

Authors and Affiliations

  1. Steinberg Centre for Simulation and Interactive Learning, McGill University, Montreal, QC, Canada

    Elif Bilgic

  2. Steinberg-Bernstein Centre for Minimally Invasive Surgery and Innovation, McGill University Health Centre, 1650, Cedar Avenue, L9. 313, Montreal, QC, H3G 1A4, Canada

    Elif Bilgic, Motaz Alyafi, Tomonori Hada, Gerald M. Fried & Melina C. Vassiliou

  3. Montreal General Hospital Medical Library, McGill University Health Centre, Montreal, QC, Canada

    Tara Landry

Authors
  1. Elif Bilgic
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Motaz Alyafi
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Tomonori Hada
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Tara Landry
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Gerald M. Fried
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Melina C. Vassiliou
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Melina C. Vassiliou.

Ethics declarations

Disclosures

The Steinberg-Bernstein Centre for Minimally Invasive Surgery and Innovation received an unrestricted educational grant from Medtronic Canada. Elif Bilgic, Motaz Alyafi, Tomonori Hada, Tara Landry, Gerald M Fried, and Melina C Vassiliou have no relevant conflicts of interest or financial ties to disclose.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Appendix 1: Medline search strategy

Appendix 1: Medline search strategy

  1. 1.

    Exp Laparoscopy/ (90382)

  2. 2.

    Suture Techniques/ (43044)

  3. 3.

    Sutures/ (16421)

  4. 4.

    2 or 3 (54604)

  5. 5.

    1 and 4 (2898)

  6. 6.

    ((Extracorporeal or extra-corporeal or intracorporeal or intra-corporeal or laparo*) adj3 (sutur* or knot*)).tw,kf. (2117)

  7. 7.

     5 or 6 (4242)

  8. 8.

    ed.fs. (261740)

  9. 9.

    Education, medical, graduate/ (26742)

  10. 10.

    “Internship and residency”/ (44310)

  11. 11.

    Exp Teaching/ (80605)

  12. 12.

    Exp Learning/ (362731)

  13. 13.

    (Curricul* or educat* or instruct* or learn* or teach* or train* or tuition).tw,kf. (1305770)

  14. 14.

    or/8-13 (1650389)

  15. 15.

    7 and 14 (747)

  16. 16.

    Limit 15 to English (696)

  17. 17.

    Remove duplicates from 16 (653)

  18. 18.

    Limit 17 to yr=”2000 Current” (607)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Bilgic, E., Alyafi, M., Hada, T. et al. Simulation platforms to assess laparoscopic suturing skills: a scoping review. Surg Endosc 33, 2742–2762 (2019). https://doi.org/10.1007/s00464-019-06821-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00464-019-06821-y

Keywords

Search

Navigation