Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You and Your Team.

Learn More →

Retention of Mastoidectomy Skills After Virtual Reality Simulation Training

Retention of Mastoidectomy Skills After Virtual Reality Simulation Training Abstract Importance The ultimate goal of surgical training is consolidated skills with a consistently high performance. However, surgical skills are heterogeneously retained and depend on a variety of factors, including the task, cognitive demands, and organization of practice. Virtual reality (VR) simulation is increasingly being used in surgical skills training, including temporal bone surgery, but there is a gap in knowledge on the retention of mastoidectomy skills after VR simulation training. Objectives To determine the retention of mastoidectomy skills after VR simulation training with distributed and massed practice and to investigate participants’ cognitive load during retention procedures. Design, Setting, and Participants A prospective 3-month follow-up study of a VR simulation trial was conducted from February 6 to September 19, 2014, at an academic teaching hospital among 36 medical students: 19 from a cohort trained with distributed practice and 17 from a cohort trained with massed practice. Interventions Participants performed 2 virtual mastoidectomies in a VR simulator a mean of 3.2 months (range, 2.4-5.0 months) after completing initial training with 12 repeated procedures. Practice blocks were spaced apart in time (distributed), or all procedures were performed in 1 day (massed). Main Outcomes and Measures Performance of the virtual mastoidectomy as assessed by 2 masked senior otologists using a modified Welling scale, as well as cognitive load as estimated by reaction time to perform a secondary task. Results Among 36 participants, mastoidectomy final-product skills were largely retained at 3 months (mean change in score, 0.1 points; P = .89) regardless of practice schedule, but the group trained with massed practice took more time to complete the task. The performance of the massed practice group increased significantly from the first to the second retention procedure (mean change, 1.8 points; P = .001), reflecting that skills were less consolidated. For both groups, increases in reaction times in the secondary task (distributed practice group: mean pretraining relative reaction time, 1.42 [95% CI, 1.37-1.47]; mean end of training relative reaction time, 1.24 [95% CI, 1.16-1.32]; and mean retention relative reaction time, 1.36 [95% CI, 1.30-1.42]; massed practice group: mean pretraining relative reaction time, 1.34 [95% CI, 1.28-1.40]; mean end of training relative reaction time, 1.31 [95% CI, 1.21-1.42]; and mean retention relative reaction time, 1.39 [95% CI, 1.31-1.46]) indicated that cognitive load during the virtual procedures had returned to the pretraining level. Conclusions and Relevance Mastoidectomy skills acquired under time-distributed practice conditions were retained better than skills acquired under massed practice conditions. Complex psychomotor skills should be regularly reinforced to consolidate both motor and cognitive aspects. Virtual reality simulation training provides the opportunity for such repeated training and should be integrated into training curricula. Introduction Surgical training is undergoing a paradigm shift from traditional apprenticeship to increased use of simulation-based training. Patient safety issues, constraints on working hours, and productivity demands contribute to limited training opportunities under the traditional apprenticeship. Still, safe performance of high-risk surgery requires extensive and high-quality training,1 and the complex psychomotor skills needed to perform surgery must be developed both efficiently and reliably. Virtual reality (VR) simulation-based surgical skills training has been demonstrated in a range of different surgical fields to improve performance and transfer newfound skills to the operating room.2 In temporal bone surgery, VR simulation is primarily used to supplement other training modalities, such as cadaveric dissection, and current evidence supports the effectiveness of VR simulation in training of novices to perform mastoidectomy.3-9 However, performance during practice is often the only reported outcome in these studies. Nevertheless, measurement of the retention of acquired skills is a better indicator of actual learning than is performance during practice because consolidated skills and consistency of performance are the goals of surgical training.10 In other words, retention tests “attempt to remove the effects of temporary modulators on performance such as fatigue, and rely only on the retrieval of skills from memory.”10(p405) To some extent, complex psychomotor skills acquired in a VR simulation environment seem to be retained for several months.10-14 However, surgical skills are retained heterogeneously and depend on the procedure, the task studied, and time elapsed since training. In addition, several other factors affect the retention and transfer of skills training, including deliberate practice, training in a subset of skills relating to the overall task, task variability, and overlearning after reaching proficiency.15 There is also evidence that heavier demands on cognitive functions during acquisition of motor skills negatively affect retention.13,15 Highly complex motor skills could cause substantial cognitive load owing to the limitations of working memory and thereby inhibit the capacity for learning.16 Several instructional designs can modify the cognitive load17; studies have previously demonstrated that organizing training as distributed practice (practice sessions spaced in time) rather than massed practice (all sessions in 1 day) provides superior learning curves18 and reduces cognitive load.19 However, there is a gap in knowledge on whether such an improvement in performance and reduction in cognitive load during performance of the procedure are sustained after the training period. Based on this finding, we hypothesized that different training strategies affect the retention of surgical motor skills and cognitive load during retention performance. The aims of this study were to determine the retention of mastoidectomy skills after VR simulation training with distributed and massed practice and to investigate the cognitive load in the retention procedures, with the purpose of informing the optimal organization of temporal bone skills training. Box Section Ref ID Key Points Question Do different training strategies affect the retention of virtual reality simulation mastoidectomy skills? Findings In this prospective, nonrandomized, 3-month follow-up study on the performance of novices in a virtual reality temporal bone simulator, mastoidectomy skills were largely retained regardless of practice condition, but the group trained in a massed practice condition took more time to complete the procedure to compensate for less-consolidated skills. Meaning Mastoidectomy skills acquired in a time-distributed practice condition were superiorly retained. Methods The ethics committee for the Capital Region of Denmark waived approval for this study as it was an educational study. All trainees provided written informed consent; participation was voluntary, and participants did not receive financial compensation. VR Simulation Platform The Visible Ear Simulator is a personal computer–based temporal bone simulator featuring 3D-stereo graphics, force feedback for drilling using the Geomagic Touch (3D Systems) haptic device, and the option of simulator-integrated tutoring with highlighting of the volume to be drilled in each step of an anatomical mastoidectomy.20,21 The simulator software is academic freeware that can be downloaded from our group’s website22 and is currently in use at many training institutions worldwide. Participants This study was designed as a 3-month follow-up on a study of the learning curves of distributed and massed practice18 from February 6 to September 19, 2014. Participants were medical students from the Faculty of Health and Medical Sciences, University of Copenhagen, Denmark, and were novices regarding temporal bone surgery. Participants volunteered for the VR simulation training as an extracurricular activity. Study Design In the initial study, 2 cohorts of medical students who had not performed mastoidectomy before completed self-directed training with either distributed or massed practice of 12 identical mastoidectomy procedures in the Visible Ear Simulator (Figure 1). For each of the repeated procedures, participants were allowed 30 minutes to perform a complete mastoidectomy with entry into the antrum and a posterior tympanotomy. In distributed training, practice blocks consisted of 2 repeated procedures, and the 6 practice blocks were spaced by at least 3 days. In massed practice, all 12 repetitions of the procedure were completed in a single practice block. Participants in both groups were further randomized for initial simulator-integrated tutoring and thereby an identical tutoring intervention. However, by the end of the study, the effect of initial tutoring had faded, and end-of-training performances were similar. For this study, participants who had completed training in the previous study were invited back for retention testing after 3 months. Thirty-six participants accepted the invitation for this follow-up study: 19 of 21 participants in the distributed practice cohort and 17 of 19 participants in the massed practice cohort completed the retention procedures. None of the participants had practiced the procedure in the intervening period. The follow-up retention testing was scheduled at the convenience of the participant and consisted of 2 mastoidectomy procedures identical to the 30-minute procedures in the initial study. During retention testing, participants had access to the standard on-screen instructions and received no other assistance. Outcomes The virtual mastoidectomy was automatically saved by the simulator every 10 minutes, and performances were later assessed by 2 masked expert raters (P.C.-T. and M.S.S.) using final-product analysis with a modified Welling Scale.23 In addition, participants were tested on their reaction time while performing a secondary task provided by the simulator at baseline and several times during the procedure to estimate the cognitive load by the increase in reaction time during simulation relative to baseline measurements.19 The outcomes (final-product performance and relative reaction time for cognitive load estimation) were analyzed as previously described18 to ensure comparability with previous studies. Supplemental analyses of the volume removed during VR simulation sessions were performed for this study. Statistical Analysis The mean scores and mean reaction times of the 2 retention procedures (sessions 13 and 14) and the last 2 procedures (end-of-training procedures; sessions 11 and 12) of the initial study were compared. Data were analyzed using SPSS (SPSS, Inc), version 22 for MacOS X with analysis of variances, paired samples 2-tailed t tests, and Pearson r for correlations. Results Two participants in the distributed practice cohort (10%) and 2 participants in the massed practice cohort (11%) were unavailable for follow-up. Participant characteristics were therefore similar to those reported in the initial study: individuals in the distributed practice group were significantly older, more often male, and had a higher frequency of playing video games than participants in the massed practice group (Table 1). As in the initial study, these factors could not be demonstrated to be associated with the outcomes. The mean number of days between the end-of-training sessions in the initial study and the retention sessions in this follow-up study were comparable for the 2 practice groups (Table 1). In addition, the number of the days until follow-up was not associated with final-product performance or relative reaction time performance. For both practice groups, the difference in mean final-product performances of the end-of-training sessions and the retention sessions were not statistically significant (Table 2). The slightly lower performance during retention procedures was related to the anatomical boundaries of the procedure, such as adequately removing cells in the sinodural angle, along the tegmen, and in the mastoid tip; not overexposing the facial nerve; and expanding the facial recess. We also found that the final-product performance of the massed practice group increased significantly from the first to the second retention procedure (mean change, 1.8 points; P = .001), whereas the performance of participants in the distributed practice group remained unchanged during the retention procedures (Figure 2). The 2 groups had equal mean retention final-product performances (mean change, 0.1 points; P = .89). A different pattern was observed for the relative reaction time (Figure 3): both groups had an increase in relative reaction time when comparing retention sessions with end-of-training sessions, even though this increase was only statistically significant for the distributed practice group (P < .01), and both practice groups had equal mean reaction times in the retention sessions (Table 2). We performed a supplemental analysis of the total volume removed during the VR simulation sessions to explore whether the fixed 30-minute time frame masked differences between the groups in time needed to complete the task. This analysis demonstrated that the distributed practice group consistently removed more bone than did the massed practice group in both the end-of-training sessions and the retention sessions (eFigure 1 in the Supplement), consistent with the higher final-product performance of the distributed practice group. Also mirroring the final-product performance, a decrease in the total volume removed was found in the first retention session. Finally, the massed practice group removed significantly more bone during the last 10 minutes of the first retention session (session 13) than in their last end-of-training session (session 12) (P < .002) (eFigure 2 in the Supplement) while retaining total volume removed, reflecting time compensation. Discussion In this follow-up study on the retention of mastoidectomy training in a VR simulator with distributed and massed practice of the procedure, we found that, regardless of the organization of training, final-product performance did not deteriorate significantly during a 3-month period in which the participants did not practice their skills. In contrast to this finding, the cognitive load estimated by reaction time measurement had returned to pretraining levels (distributed practice group: mean pretraining relative reaction time, 1.42 [95% CI, 1.37-1.47]; and massed practice group: mean pretraining relative reaction time, 1.34 [95% CI, 1.28-1.40]).19 Moreover, the skills of the massed practice group were less consolidated, and the participants in this group seemed to use more time within the allowed timeframe during retention testing to achieve a similar performance. During the retention procedures, the participants in general had a poorer performance compared with end-of-training procedures in adequately defining the outer boundaries of the procedure, often violating the facial nerve, and not exposing the facial recess sufficiently, suggesting that these items could be emphasized in future instructions. In VR laparoscopic simulation skills training, participants’ performance deteriorated in the immediate period following training, but no further skills were lost when retention was tested at a mean of 7 months after training.14 Similarly, novices retained skills in another laparoscopic simulator for 6 months.11 However, at 18 months, skills had returned to pretraining levels.11 A limitation to our study is, therefore, that retention was tested only at a relative early point after training (3 months), which might explain why final-product skills at performing mastoidectomy were largely retained in our follow-up study. Also, the participants had access to the simulator’s built-in onscreen instructions on the procedure so as to have similar and comparable conditions during training and retention procedures and support self-directed practice with directed, self-regulated learning.24 Nonetheless, this access would also help increase performance during the retention procedures and compensate for possible differences between the 2 practice groups. Other limitations to our study are the small sample size and a nonrandomized study design. Sample size calculations for learning curves are not well defined; for the original study, we aimed at having the number of participants in each practice group be similar to that in other studies.10,11 Based on the data on the end-of-training sessions and the included number of participants, a change in final-product score of 2.5 points would be needed to find a statistically significant difference between performance in the end-of-training and retention procedures. A type 2 error is therefore a possibility, and our study could be underpowered to detect smaller changes in performance between the end-of-training and retention sessions. In the previously mentioned studies on VR laparoscopic simulation training, practice was organized in a distributed schedule. The retention of surgical skills in distributed vs massed practice has been studied for physical simulation models in surgery: distributed practice groups significantly outperformed massed practice groups when tested for retention at 1 month or 1 year.10,25 Surgical skills learned under distributed practice settings are therefore suggested to be more robust.10 Although we found that final-product mastoidectomy skills were retained regardless of practice organization, our supplemental analyses substantiate that time compensation was a factor: only about 5% to 15% of the total volume was removed during the last 10 minutes of the procedure in end-of-training and retention procedures for both groups except for the first retention procedure of the massed practice group (session 13). This finding corroborates that the improvement gained in time to completion during repeated training was not retained in the massed practice group and explains why final-product performance did not deteriorate markedly. When considering both the final-product performance and time to completion, our findings support that distributed practice is superior to massed practice for retention of mastoidectomy skills. In this study, we performed retention testing using 2 repetitions to reveal retention and not refamiliarization with the simulator, which led to another interesting finding supporting the case for distributed practice being a superior method: the performance of the massed practice group increased significantly from the first to the second retention procedure. Also considering that the performance at the end of initial training was significantly lower for the massed practice group than for the distributed practice group, this finding suggests that the massed practice group still had potential for additional learning, whereas the distributed practice group had already reached an initial plateau during training and did not improve further during the retention testing. A similar pattern was found in a study on VR laparoscopic simulation12: one group that had not trained repeatedly to a consistent performance in initial training also improved during retention testing, indicating that some degree of overlearning is beneficial for retention. Even though time spacing of practice is essential for learning, we found that it is possible to continue learning even after a considerable period of nonpractice. This finding is in agreement with a study on VR simulation training of endoscopic sinus surgery in which novices resumed to follow their learning curves after 11 to 60 days of not training.26 In a study exploring the retention of skills at analyzing electrocardiograph results (a mainly cognitive skill) following a massed practice training course, approximately half of the performance gained during the course was lost after 2 weeks.27 In contrast to this finding, motor skills are consistently found to be less susceptible to decay over longer periods of time than are cognitive skills,15 and basic motor skills in VR laparoscopic simulation are better retained than are complex motor skills that placed heavier cognitive demands.13 In our initial study, we found that cognitive load decreased with repeated and distributed practice and not with massed practice.19 In the present study, we also measured retention of the performance on a secondary reaction time test. The relative reaction time reflects the cognitive load during the procedure, and we found that the cognitive load during the retention procedure had returned almost to the level of the first procedure. In agreement with current knowledge, this finding suggests that the reduction in cognitive demands with repeated practice of complex psychomotor skills is not retained as reliably as the acquired motor skills. This finding could have implications for surgical skills training, such as mastoidectomy training, because the aspect of cognitive learning also should be considered. Training toward cognitive automaticity of a surgical procedure requires substantially more training than training toward simulator proficiency alone.28 Conclusions Mastoidectomy skills were largely retained at 3 months after self-directed VR simulation training when practice was organized with time distribution between practice sessions. The learning curve could, however, be resumed for the massed practice group because they had not reached their full learning potential during initial training. For both practice groups, the cognitive load during the retention procedures returned to the level of the first procedure. This finding substantiates that cognitive skills deteriorate more rapidly and that this factor should be considered in the organization of surgical skills training. Surgical skills should be reinforced regularly with a frequency that is sufficient to maintain acquired motor as well as cognitive skills. Back to top Article Information Accepted for Publication: February 25, 2016. Corresponding Author: Steven Arild Wuyts Andersen, MD, Department of Otorhinolaryngology–Head and Neck Surgery, Rigshospitalet, Blegdamsvej 9, DK-2100 Copenhagen Ø, Denmark (stevenarild@gmail.com). Published Online: April 28, 2016. doi:10.1001/jamaoto.2016.0454. Author Contributions: Dr Andersen had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Study concept and design: Andersen, Konge, Sørensen. Acquisition, analysis, or interpretation of data: Andersen, Cayé-Thomasen, Sørensen. Drafting of the manuscript: Andersen. Critical revision of the manuscript for important intellectual content: All authors. Statistical analysis: Andersen, Sørensen. Obtained funding: Sørensen. Administrative, technical, or material support: Konge, Sørensen. Study supervision: Konge, Cayé-Thomasen, Sørensen. Conflict of Interest Disclosures: Dr Andersen reported receiving an unrestricted grant from the Oticon Foundation for PhD studies. No other disclosures were reported. Funding/Support: The development of the Visible Ear Simulator software was financially supported by the Oticon Foundation. Role of the Funder/Sponsor: The funding source had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. Additional Contributions: Peter Trier Mikkelsen, MSc, Alexandra Institute, developed the experimental version of the Visible Ear Simulator. He was not compensated for his contribution. References 1. Spruit EN, Band GP, Hamming JF, Ridderinkhof KR. Optimal training design for procedural motor skills: a review and application to laparoscopic surgery. Psychol Res. 2014;78(6):878-891.PubMedGoogle ScholarCrossref 2. Dawe SR, Pena GN, Windsor JA, et al. Systematic review of skills transfer after surgical simulation-based training. Br J Surg. 2014;101(9):1063-1076.PubMedGoogle ScholarCrossref 3. Sewell C, Morris D, Blevins NH, et al. Validating metrics for a mastoidectomy simulator. Stud Health Technol Inform. 2007;125:421-426.PubMedGoogle Scholar 4. Zirkle M, Roberson DW, Leuwer R, Dubrowski A. Using a virtual reality temporal bone simulator to assess otolaryngology trainees. Laryngoscope. 2007;117(2):258-263.PubMedGoogle ScholarCrossref 5. Zhao YC, Kennedy G, Yukawa K, Pyman B, O’Leary S. Improving temporal bone dissection using self-directed virtual reality simulation: results of a randomized blinded control trial. Otolaryngol Head Neck Surg. 2011;144(3):357-364.PubMedGoogle ScholarCrossref 6. Wiet GJ, Stredney D, Kerwin T, et al. Virtual temporal bone dissection system: OSU virtual temporal bone system: development and testing. Laryngoscope. 2012;122(suppl 1):S1-S12.PubMedGoogle ScholarCrossref 7. Khemani S, Arora A, Singh A, Tolley N, Darzi A. Objective skills assessment and construct validation of a virtual reality temporal bone simulator. Otol Neurotol. 2012;33(7):1225-1231.PubMedGoogle ScholarCrossref 8. Nash R, Sykes R, Majithia A, Arora A, Singh A, Khemani S. Objective assessment of learning curves for the Voxel-Man TempoSurg temporal bone surgery computer simulator. J Laryngol Otol. 2012;126(7):663-669.PubMedGoogle ScholarCrossref 9. Andersen SA, Foghsgaard S, Konge L, Cayé-Thomasen P, Sørensen MS. The effect of self-directed virtual reality simulation on dissection training performance in mastoidectomy [published online October 9, 2015]. Laryngoscope. doi:10.1002/lary.25710.PubMedGoogle Scholar 10. Moulton CA, Dubrowski A, Macrae H, Graham B, Grober E, Reznick R. Teaching surgical skills: what kind of practice makes perfect? a randomized, controlled trial. Ann Surg. 2006;244(3):400-409.PubMedGoogle Scholar 11. Maagaard M, Sorensen JL, Oestergaard J, et al. Retention of laparoscopic procedural skills acquired on a virtual-reality surgical trainer. Surg Endosc. 2011;25(3):722-727.PubMedGoogle ScholarCrossref 12. Bjerrum F, Maagaard M, Led Sorensen J, et al. Effect of instructor feedback on skills retention after laparoscopic simulator training: follow-up of a randomized trial. J Surg Educ. 2015;72(1):53-60.PubMedGoogle ScholarCrossref 13. Sinha P, Hogle NJ, Fowler DL. Do the laparoscopic skills of trainees deteriorate over time? Surg Endosc. 2008;22(9):2018-2025.PubMedGoogle ScholarCrossref 14. Stefanidis D, Korndorffer JR Jr, Sierra R, Touchard C, Dunne JB, Scott DJ. Skill retention following proficiency-based laparoscopic simulator training. Surgery. 2005;138(2):165-170.PubMedGoogle ScholarCrossref 15. Arthur W Jr, Bennett W Jr, Stanush PL, McNelly TL. Factors that influence skill decay and retention: a quantitative review and analysis. Hum Perform. 1998;11(1):57-101. doi:10.1207/s15327043hup1101_3. Google ScholarCrossref 16. Sweller J. Cognitive load during problem solving: effects on learning. Cogn Sci. 1988;12(2):257-285. doi:10.1207/s15516709cog1202_4.Google ScholarCrossref 17. van Merriënboer JJ, Sweller J. Cognitive load theory in health professional education: design principles and strategies. Med Educ. 2010;44(1):85-93.PubMedGoogle ScholarCrossref 18. Andersen SA, Konge L, Cayé-Thomasen P, Sørensen MS. Learning curves of virtual mastoidectomy in distributed and massed practice. JAMA Otolaryngol Head Neck Surg. 2015;141(10):913-918.PubMedGoogle Scholar 19. Andersen SA, Mikkelsen PT, Konge L, Cayé-Thomasen P, Sørensen MS. Cognitive load in distributed and massed practice in virtual reality mastoidectomy simulation. Laryngoscope. 2016;126(2):E74-E79.PubMedGoogle ScholarCrossref 20. Trier P, Noe KO, Sørensen MS, Mosegaard J. The visible ear surgery simulator. Stud Health Technol Inform. 2008;132:523-525.PubMedGoogle Scholar 21. Sorensen MS, Mosegaard J, Trier P. The visible ear simulator: a public PC application for GPU-accelerated haptic 3D simulation of ear surgery based on the visible ear data. Otol Neurotol. 2009;30(4):484-487.PubMedGoogle ScholarCrossref 22. Alexandra Institute. The visible ear simulator. http://ves.cg.alexandra.dk. Accessed September 25, 2015. 23. Andersen SA, Cayé-Thomasen P, Sørensen MS. Mastoidectomy performance assessment of virtual simulation training using final-product analysis. Laryngoscope. 2015;125(2):431-435.PubMedGoogle ScholarCrossref 24. Brydges R, Dubrowski A, Regehr G. A new concept of unsupervised learning: directed self-guided learning in the health professions. Acad Med. 2010;85(10)(suppl):S49-S55.PubMedGoogle ScholarCrossref 25. Spruit EN, Band GP, Hamming JF. Increasing efficiency of surgical training: effects of spacing practice on skill acquisition and retention in laparoscopy training. Surg Endosc. 2015;29(8):2235-2243.PubMedGoogle ScholarCrossref 26. Uribe JI, Ralph WM Jr, Glaser AY, Fried MP. Learning curves, acquisition, and retention of skills trained with the endoscopic sinus surgery simulator. Am J Rhinol. 2004;18(2):87-92.PubMedGoogle Scholar 27. Rolskov Bojsen S, Räder SB, Holst AG, et al. The acquisition and retention of ECG interpretation skills after a standardized web-based ECG tutorial—a randomised study. BMC Med Educ. 2015;15:36.PubMedGoogle ScholarCrossref 28. Stefanidis D, Scerbo MW, Sechrist C, Mostafavi A, Heniford BT. Do novices display automaticity during simulator training? Am J Surg. 2008;195(2):210-213.PubMedGoogle ScholarCrossref http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png JAMA Otolaryngology - Head & Neck Surgery American Medical Association

Retention of Mastoidectomy Skills After Virtual Reality Simulation Training

Loading next page...
 
/lp/american-medical-association/retention-of-mastoidectomy-skills-after-virtual-reality-simulation-Zvl0ZUoAnT
Publisher
American Medical Association
Copyright
Copyright © 2016 American Medical Association. All Rights Reserved.
ISSN
2168-6181
eISSN
2168-619X
DOI
10.1001/jamaoto.2016.0454
Publisher site
See Article on Publisher Site

Abstract

Abstract Importance The ultimate goal of surgical training is consolidated skills with a consistently high performance. However, surgical skills are heterogeneously retained and depend on a variety of factors, including the task, cognitive demands, and organization of practice. Virtual reality (VR) simulation is increasingly being used in surgical skills training, including temporal bone surgery, but there is a gap in knowledge on the retention of mastoidectomy skills after VR simulation training. Objectives To determine the retention of mastoidectomy skills after VR simulation training with distributed and massed practice and to investigate participants’ cognitive load during retention procedures. Design, Setting, and Participants A prospective 3-month follow-up study of a VR simulation trial was conducted from February 6 to September 19, 2014, at an academic teaching hospital among 36 medical students: 19 from a cohort trained with distributed practice and 17 from a cohort trained with massed practice. Interventions Participants performed 2 virtual mastoidectomies in a VR simulator a mean of 3.2 months (range, 2.4-5.0 months) after completing initial training with 12 repeated procedures. Practice blocks were spaced apart in time (distributed), or all procedures were performed in 1 day (massed). Main Outcomes and Measures Performance of the virtual mastoidectomy as assessed by 2 masked senior otologists using a modified Welling scale, as well as cognitive load as estimated by reaction time to perform a secondary task. Results Among 36 participants, mastoidectomy final-product skills were largely retained at 3 months (mean change in score, 0.1 points; P = .89) regardless of practice schedule, but the group trained with massed practice took more time to complete the task. The performance of the massed practice group increased significantly from the first to the second retention procedure (mean change, 1.8 points; P = .001), reflecting that skills were less consolidated. For both groups, increases in reaction times in the secondary task (distributed practice group: mean pretraining relative reaction time, 1.42 [95% CI, 1.37-1.47]; mean end of training relative reaction time, 1.24 [95% CI, 1.16-1.32]; and mean retention relative reaction time, 1.36 [95% CI, 1.30-1.42]; massed practice group: mean pretraining relative reaction time, 1.34 [95% CI, 1.28-1.40]; mean end of training relative reaction time, 1.31 [95% CI, 1.21-1.42]; and mean retention relative reaction time, 1.39 [95% CI, 1.31-1.46]) indicated that cognitive load during the virtual procedures had returned to the pretraining level. Conclusions and Relevance Mastoidectomy skills acquired under time-distributed practice conditions were retained better than skills acquired under massed practice conditions. Complex psychomotor skills should be regularly reinforced to consolidate both motor and cognitive aspects. Virtual reality simulation training provides the opportunity for such repeated training and should be integrated into training curricula. Introduction Surgical training is undergoing a paradigm shift from traditional apprenticeship to increased use of simulation-based training. Patient safety issues, constraints on working hours, and productivity demands contribute to limited training opportunities under the traditional apprenticeship. Still, safe performance of high-risk surgery requires extensive and high-quality training,1 and the complex psychomotor skills needed to perform surgery must be developed both efficiently and reliably. Virtual reality (VR) simulation-based surgical skills training has been demonstrated in a range of different surgical fields to improve performance and transfer newfound skills to the operating room.2 In temporal bone surgery, VR simulation is primarily used to supplement other training modalities, such as cadaveric dissection, and current evidence supports the effectiveness of VR simulation in training of novices to perform mastoidectomy.3-9 However, performance during practice is often the only reported outcome in these studies. Nevertheless, measurement of the retention of acquired skills is a better indicator of actual learning than is performance during practice because consolidated skills and consistency of performance are the goals of surgical training.10 In other words, retention tests “attempt to remove the effects of temporary modulators on performance such as fatigue, and rely only on the retrieval of skills from memory.”10(p405) To some extent, complex psychomotor skills acquired in a VR simulation environment seem to be retained for several months.10-14 However, surgical skills are retained heterogeneously and depend on the procedure, the task studied, and time elapsed since training. In addition, several other factors affect the retention and transfer of skills training, including deliberate practice, training in a subset of skills relating to the overall task, task variability, and overlearning after reaching proficiency.15 There is also evidence that heavier demands on cognitive functions during acquisition of motor skills negatively affect retention.13,15 Highly complex motor skills could cause substantial cognitive load owing to the limitations of working memory and thereby inhibit the capacity for learning.16 Several instructional designs can modify the cognitive load17; studies have previously demonstrated that organizing training as distributed practice (practice sessions spaced in time) rather than massed practice (all sessions in 1 day) provides superior learning curves18 and reduces cognitive load.19 However, there is a gap in knowledge on whether such an improvement in performance and reduction in cognitive load during performance of the procedure are sustained after the training period. Based on this finding, we hypothesized that different training strategies affect the retention of surgical motor skills and cognitive load during retention performance. The aims of this study were to determine the retention of mastoidectomy skills after VR simulation training with distributed and massed practice and to investigate the cognitive load in the retention procedures, with the purpose of informing the optimal organization of temporal bone skills training. Box Section Ref ID Key Points Question Do different training strategies affect the retention of virtual reality simulation mastoidectomy skills? Findings In this prospective, nonrandomized, 3-month follow-up study on the performance of novices in a virtual reality temporal bone simulator, mastoidectomy skills were largely retained regardless of practice condition, but the group trained in a massed practice condition took more time to complete the procedure to compensate for less-consolidated skills. Meaning Mastoidectomy skills acquired in a time-distributed practice condition were superiorly retained. Methods The ethics committee for the Capital Region of Denmark waived approval for this study as it was an educational study. All trainees provided written informed consent; participation was voluntary, and participants did not receive financial compensation. VR Simulation Platform The Visible Ear Simulator is a personal computer–based temporal bone simulator featuring 3D-stereo graphics, force feedback for drilling using the Geomagic Touch (3D Systems) haptic device, and the option of simulator-integrated tutoring with highlighting of the volume to be drilled in each step of an anatomical mastoidectomy.20,21 The simulator software is academic freeware that can be downloaded from our group’s website22 and is currently in use at many training institutions worldwide. Participants This study was designed as a 3-month follow-up on a study of the learning curves of distributed and massed practice18 from February 6 to September 19, 2014. Participants were medical students from the Faculty of Health and Medical Sciences, University of Copenhagen, Denmark, and were novices regarding temporal bone surgery. Participants volunteered for the VR simulation training as an extracurricular activity. Study Design In the initial study, 2 cohorts of medical students who had not performed mastoidectomy before completed self-directed training with either distributed or massed practice of 12 identical mastoidectomy procedures in the Visible Ear Simulator (Figure 1). For each of the repeated procedures, participants were allowed 30 minutes to perform a complete mastoidectomy with entry into the antrum and a posterior tympanotomy. In distributed training, practice blocks consisted of 2 repeated procedures, and the 6 practice blocks were spaced by at least 3 days. In massed practice, all 12 repetitions of the procedure were completed in a single practice block. Participants in both groups were further randomized for initial simulator-integrated tutoring and thereby an identical tutoring intervention. However, by the end of the study, the effect of initial tutoring had faded, and end-of-training performances were similar. For this study, participants who had completed training in the previous study were invited back for retention testing after 3 months. Thirty-six participants accepted the invitation for this follow-up study: 19 of 21 participants in the distributed practice cohort and 17 of 19 participants in the massed practice cohort completed the retention procedures. None of the participants had practiced the procedure in the intervening period. The follow-up retention testing was scheduled at the convenience of the participant and consisted of 2 mastoidectomy procedures identical to the 30-minute procedures in the initial study. During retention testing, participants had access to the standard on-screen instructions and received no other assistance. Outcomes The virtual mastoidectomy was automatically saved by the simulator every 10 minutes, and performances were later assessed by 2 masked expert raters (P.C.-T. and M.S.S.) using final-product analysis with a modified Welling Scale.23 In addition, participants were tested on their reaction time while performing a secondary task provided by the simulator at baseline and several times during the procedure to estimate the cognitive load by the increase in reaction time during simulation relative to baseline measurements.19 The outcomes (final-product performance and relative reaction time for cognitive load estimation) were analyzed as previously described18 to ensure comparability with previous studies. Supplemental analyses of the volume removed during VR simulation sessions were performed for this study. Statistical Analysis The mean scores and mean reaction times of the 2 retention procedures (sessions 13 and 14) and the last 2 procedures (end-of-training procedures; sessions 11 and 12) of the initial study were compared. Data were analyzed using SPSS (SPSS, Inc), version 22 for MacOS X with analysis of variances, paired samples 2-tailed t tests, and Pearson r for correlations. Results Two participants in the distributed practice cohort (10%) and 2 participants in the massed practice cohort (11%) were unavailable for follow-up. Participant characteristics were therefore similar to those reported in the initial study: individuals in the distributed practice group were significantly older, more often male, and had a higher frequency of playing video games than participants in the massed practice group (Table 1). As in the initial study, these factors could not be demonstrated to be associated with the outcomes. The mean number of days between the end-of-training sessions in the initial study and the retention sessions in this follow-up study were comparable for the 2 practice groups (Table 1). In addition, the number of the days until follow-up was not associated with final-product performance or relative reaction time performance. For both practice groups, the difference in mean final-product performances of the end-of-training sessions and the retention sessions were not statistically significant (Table 2). The slightly lower performance during retention procedures was related to the anatomical boundaries of the procedure, such as adequately removing cells in the sinodural angle, along the tegmen, and in the mastoid tip; not overexposing the facial nerve; and expanding the facial recess. We also found that the final-product performance of the massed practice group increased significantly from the first to the second retention procedure (mean change, 1.8 points; P = .001), whereas the performance of participants in the distributed practice group remained unchanged during the retention procedures (Figure 2). The 2 groups had equal mean retention final-product performances (mean change, 0.1 points; P = .89). A different pattern was observed for the relative reaction time (Figure 3): both groups had an increase in relative reaction time when comparing retention sessions with end-of-training sessions, even though this increase was only statistically significant for the distributed practice group (P < .01), and both practice groups had equal mean reaction times in the retention sessions (Table 2). We performed a supplemental analysis of the total volume removed during the VR simulation sessions to explore whether the fixed 30-minute time frame masked differences between the groups in time needed to complete the task. This analysis demonstrated that the distributed practice group consistently removed more bone than did the massed practice group in both the end-of-training sessions and the retention sessions (eFigure 1 in the Supplement), consistent with the higher final-product performance of the distributed practice group. Also mirroring the final-product performance, a decrease in the total volume removed was found in the first retention session. Finally, the massed practice group removed significantly more bone during the last 10 minutes of the first retention session (session 13) than in their last end-of-training session (session 12) (P < .002) (eFigure 2 in the Supplement) while retaining total volume removed, reflecting time compensation. Discussion In this follow-up study on the retention of mastoidectomy training in a VR simulator with distributed and massed practice of the procedure, we found that, regardless of the organization of training, final-product performance did not deteriorate significantly during a 3-month period in which the participants did not practice their skills. In contrast to this finding, the cognitive load estimated by reaction time measurement had returned to pretraining levels (distributed practice group: mean pretraining relative reaction time, 1.42 [95% CI, 1.37-1.47]; and massed practice group: mean pretraining relative reaction time, 1.34 [95% CI, 1.28-1.40]).19 Moreover, the skills of the massed practice group were less consolidated, and the participants in this group seemed to use more time within the allowed timeframe during retention testing to achieve a similar performance. During the retention procedures, the participants in general had a poorer performance compared with end-of-training procedures in adequately defining the outer boundaries of the procedure, often violating the facial nerve, and not exposing the facial recess sufficiently, suggesting that these items could be emphasized in future instructions. In VR laparoscopic simulation skills training, participants’ performance deteriorated in the immediate period following training, but no further skills were lost when retention was tested at a mean of 7 months after training.14 Similarly, novices retained skills in another laparoscopic simulator for 6 months.11 However, at 18 months, skills had returned to pretraining levels.11 A limitation to our study is, therefore, that retention was tested only at a relative early point after training (3 months), which might explain why final-product skills at performing mastoidectomy were largely retained in our follow-up study. Also, the participants had access to the simulator’s built-in onscreen instructions on the procedure so as to have similar and comparable conditions during training and retention procedures and support self-directed practice with directed, self-regulated learning.24 Nonetheless, this access would also help increase performance during the retention procedures and compensate for possible differences between the 2 practice groups. Other limitations to our study are the small sample size and a nonrandomized study design. Sample size calculations for learning curves are not well defined; for the original study, we aimed at having the number of participants in each practice group be similar to that in other studies.10,11 Based on the data on the end-of-training sessions and the included number of participants, a change in final-product score of 2.5 points would be needed to find a statistically significant difference between performance in the end-of-training and retention procedures. A type 2 error is therefore a possibility, and our study could be underpowered to detect smaller changes in performance between the end-of-training and retention sessions. In the previously mentioned studies on VR laparoscopic simulation training, practice was organized in a distributed schedule. The retention of surgical skills in distributed vs massed practice has been studied for physical simulation models in surgery: distributed practice groups significantly outperformed massed practice groups when tested for retention at 1 month or 1 year.10,25 Surgical skills learned under distributed practice settings are therefore suggested to be more robust.10 Although we found that final-product mastoidectomy skills were retained regardless of practice organization, our supplemental analyses substantiate that time compensation was a factor: only about 5% to 15% of the total volume was removed during the last 10 minutes of the procedure in end-of-training and retention procedures for both groups except for the first retention procedure of the massed practice group (session 13). This finding corroborates that the improvement gained in time to completion during repeated training was not retained in the massed practice group and explains why final-product performance did not deteriorate markedly. When considering both the final-product performance and time to completion, our findings support that distributed practice is superior to massed practice for retention of mastoidectomy skills. In this study, we performed retention testing using 2 repetitions to reveal retention and not refamiliarization with the simulator, which led to another interesting finding supporting the case for distributed practice being a superior method: the performance of the massed practice group increased significantly from the first to the second retention procedure. Also considering that the performance at the end of initial training was significantly lower for the massed practice group than for the distributed practice group, this finding suggests that the massed practice group still had potential for additional learning, whereas the distributed practice group had already reached an initial plateau during training and did not improve further during the retention testing. A similar pattern was found in a study on VR laparoscopic simulation12: one group that had not trained repeatedly to a consistent performance in initial training also improved during retention testing, indicating that some degree of overlearning is beneficial for retention. Even though time spacing of practice is essential for learning, we found that it is possible to continue learning even after a considerable period of nonpractice. This finding is in agreement with a study on VR simulation training of endoscopic sinus surgery in which novices resumed to follow their learning curves after 11 to 60 days of not training.26 In a study exploring the retention of skills at analyzing electrocardiograph results (a mainly cognitive skill) following a massed practice training course, approximately half of the performance gained during the course was lost after 2 weeks.27 In contrast to this finding, motor skills are consistently found to be less susceptible to decay over longer periods of time than are cognitive skills,15 and basic motor skills in VR laparoscopic simulation are better retained than are complex motor skills that placed heavier cognitive demands.13 In our initial study, we found that cognitive load decreased with repeated and distributed practice and not with massed practice.19 In the present study, we also measured retention of the performance on a secondary reaction time test. The relative reaction time reflects the cognitive load during the procedure, and we found that the cognitive load during the retention procedure had returned almost to the level of the first procedure. In agreement with current knowledge, this finding suggests that the reduction in cognitive demands with repeated practice of complex psychomotor skills is not retained as reliably as the acquired motor skills. This finding could have implications for surgical skills training, such as mastoidectomy training, because the aspect of cognitive learning also should be considered. Training toward cognitive automaticity of a surgical procedure requires substantially more training than training toward simulator proficiency alone.28 Conclusions Mastoidectomy skills were largely retained at 3 months after self-directed VR simulation training when practice was organized with time distribution between practice sessions. The learning curve could, however, be resumed for the massed practice group because they had not reached their full learning potential during initial training. For both practice groups, the cognitive load during the retention procedures returned to the level of the first procedure. This finding substantiates that cognitive skills deteriorate more rapidly and that this factor should be considered in the organization of surgical skills training. Surgical skills should be reinforced regularly with a frequency that is sufficient to maintain acquired motor as well as cognitive skills. Back to top Article Information Accepted for Publication: February 25, 2016. Corresponding Author: Steven Arild Wuyts Andersen, MD, Department of Otorhinolaryngology–Head and Neck Surgery, Rigshospitalet, Blegdamsvej 9, DK-2100 Copenhagen Ø, Denmark (stevenarild@gmail.com). Published Online: April 28, 2016. doi:10.1001/jamaoto.2016.0454. Author Contributions: Dr Andersen had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Study concept and design: Andersen, Konge, Sørensen. Acquisition, analysis, or interpretation of data: Andersen, Cayé-Thomasen, Sørensen. Drafting of the manuscript: Andersen. Critical revision of the manuscript for important intellectual content: All authors. Statistical analysis: Andersen, Sørensen. Obtained funding: Sørensen. Administrative, technical, or material support: Konge, Sørensen. Study supervision: Konge, Cayé-Thomasen, Sørensen. Conflict of Interest Disclosures: Dr Andersen reported receiving an unrestricted grant from the Oticon Foundation for PhD studies. No other disclosures were reported. Funding/Support: The development of the Visible Ear Simulator software was financially supported by the Oticon Foundation. Role of the Funder/Sponsor: The funding source had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. Additional Contributions: Peter Trier Mikkelsen, MSc, Alexandra Institute, developed the experimental version of the Visible Ear Simulator. He was not compensated for his contribution. References 1. Spruit EN, Band GP, Hamming JF, Ridderinkhof KR. Optimal training design for procedural motor skills: a review and application to laparoscopic surgery. Psychol Res. 2014;78(6):878-891.PubMedGoogle ScholarCrossref 2. Dawe SR, Pena GN, Windsor JA, et al. Systematic review of skills transfer after surgical simulation-based training. Br J Surg. 2014;101(9):1063-1076.PubMedGoogle ScholarCrossref 3. Sewell C, Morris D, Blevins NH, et al. Validating metrics for a mastoidectomy simulator. Stud Health Technol Inform. 2007;125:421-426.PubMedGoogle Scholar 4. Zirkle M, Roberson DW, Leuwer R, Dubrowski A. Using a virtual reality temporal bone simulator to assess otolaryngology trainees. Laryngoscope. 2007;117(2):258-263.PubMedGoogle ScholarCrossref 5. Zhao YC, Kennedy G, Yukawa K, Pyman B, O’Leary S. Improving temporal bone dissection using self-directed virtual reality simulation: results of a randomized blinded control trial. Otolaryngol Head Neck Surg. 2011;144(3):357-364.PubMedGoogle ScholarCrossref 6. Wiet GJ, Stredney D, Kerwin T, et al. Virtual temporal bone dissection system: OSU virtual temporal bone system: development and testing. Laryngoscope. 2012;122(suppl 1):S1-S12.PubMedGoogle ScholarCrossref 7. Khemani S, Arora A, Singh A, Tolley N, Darzi A. Objective skills assessment and construct validation of a virtual reality temporal bone simulator. Otol Neurotol. 2012;33(7):1225-1231.PubMedGoogle ScholarCrossref 8. Nash R, Sykes R, Majithia A, Arora A, Singh A, Khemani S. Objective assessment of learning curves for the Voxel-Man TempoSurg temporal bone surgery computer simulator. J Laryngol Otol. 2012;126(7):663-669.PubMedGoogle ScholarCrossref 9. Andersen SA, Foghsgaard S, Konge L, Cayé-Thomasen P, Sørensen MS. The effect of self-directed virtual reality simulation on dissection training performance in mastoidectomy [published online October 9, 2015]. Laryngoscope. doi:10.1002/lary.25710.PubMedGoogle Scholar 10. Moulton CA, Dubrowski A, Macrae H, Graham B, Grober E, Reznick R. Teaching surgical skills: what kind of practice makes perfect? a randomized, controlled trial. Ann Surg. 2006;244(3):400-409.PubMedGoogle Scholar 11. Maagaard M, Sorensen JL, Oestergaard J, et al. Retention of laparoscopic procedural skills acquired on a virtual-reality surgical trainer. Surg Endosc. 2011;25(3):722-727.PubMedGoogle ScholarCrossref 12. Bjerrum F, Maagaard M, Led Sorensen J, et al. Effect of instructor feedback on skills retention after laparoscopic simulator training: follow-up of a randomized trial. J Surg Educ. 2015;72(1):53-60.PubMedGoogle ScholarCrossref 13. Sinha P, Hogle NJ, Fowler DL. Do the laparoscopic skills of trainees deteriorate over time? Surg Endosc. 2008;22(9):2018-2025.PubMedGoogle ScholarCrossref 14. Stefanidis D, Korndorffer JR Jr, Sierra R, Touchard C, Dunne JB, Scott DJ. Skill retention following proficiency-based laparoscopic simulator training. Surgery. 2005;138(2):165-170.PubMedGoogle ScholarCrossref 15. Arthur W Jr, Bennett W Jr, Stanush PL, McNelly TL. Factors that influence skill decay and retention: a quantitative review and analysis. Hum Perform. 1998;11(1):57-101. doi:10.1207/s15327043hup1101_3. Google ScholarCrossref 16. Sweller J. Cognitive load during problem solving: effects on learning. Cogn Sci. 1988;12(2):257-285. doi:10.1207/s15516709cog1202_4.Google ScholarCrossref 17. van Merriënboer JJ, Sweller J. Cognitive load theory in health professional education: design principles and strategies. Med Educ. 2010;44(1):85-93.PubMedGoogle ScholarCrossref 18. Andersen SA, Konge L, Cayé-Thomasen P, Sørensen MS. Learning curves of virtual mastoidectomy in distributed and massed practice. JAMA Otolaryngol Head Neck Surg. 2015;141(10):913-918.PubMedGoogle Scholar 19. Andersen SA, Mikkelsen PT, Konge L, Cayé-Thomasen P, Sørensen MS. Cognitive load in distributed and massed practice in virtual reality mastoidectomy simulation. Laryngoscope. 2016;126(2):E74-E79.PubMedGoogle ScholarCrossref 20. Trier P, Noe KO, Sørensen MS, Mosegaard J. The visible ear surgery simulator. Stud Health Technol Inform. 2008;132:523-525.PubMedGoogle Scholar 21. Sorensen MS, Mosegaard J, Trier P. The visible ear simulator: a public PC application for GPU-accelerated haptic 3D simulation of ear surgery based on the visible ear data. Otol Neurotol. 2009;30(4):484-487.PubMedGoogle ScholarCrossref 22. Alexandra Institute. The visible ear simulator. http://ves.cg.alexandra.dk. Accessed September 25, 2015. 23. Andersen SA, Cayé-Thomasen P, Sørensen MS. Mastoidectomy performance assessment of virtual simulation training using final-product analysis. Laryngoscope. 2015;125(2):431-435.PubMedGoogle ScholarCrossref 24. Brydges R, Dubrowski A, Regehr G. A new concept of unsupervised learning: directed self-guided learning in the health professions. Acad Med. 2010;85(10)(suppl):S49-S55.PubMedGoogle ScholarCrossref 25. Spruit EN, Band GP, Hamming JF. Increasing efficiency of surgical training: effects of spacing practice on skill acquisition and retention in laparoscopy training. Surg Endosc. 2015;29(8):2235-2243.PubMedGoogle ScholarCrossref 26. Uribe JI, Ralph WM Jr, Glaser AY, Fried MP. Learning curves, acquisition, and retention of skills trained with the endoscopic sinus surgery simulator. Am J Rhinol. 2004;18(2):87-92.PubMedGoogle Scholar 27. Rolskov Bojsen S, Räder SB, Holst AG, et al. The acquisition and retention of ECG interpretation skills after a standardized web-based ECG tutorial—a randomised study. BMC Med Educ. 2015;15:36.PubMedGoogle ScholarCrossref 28. Stefanidis D, Scerbo MW, Sechrist C, Mostafavi A, Heniford BT. Do novices display automaticity during simulator training? Am J Surg. 2008;195(2):210-213.PubMedGoogle ScholarCrossref

Journal

JAMA Otolaryngology - Head & Neck SurgeryAmerican Medical Association

Published: Jul 1, 2016

Keywords: simulation training,virtual reality,mastoidectomy,simulators,surgical procedures, operative

References