BACKGROUND: Virtual-reality and cadaveric simulations are expensive and not readily accessible. Innovative and accessible training adjuncts are required to help to meet training needs. Cognitive task analysis has been used extensively to train pilots and in other surgical specialties. However, the use of cognitive task analyses within orthopaedics is in its infancy. The purpose of this study was to evaluate the effectiveness of a novel cognitive task analysis tool to train novice surgeons in diagnostic knee arthroscopy in high-fidelity, phantom-limb simulation. METHODS:Three expert knee surgeons were interviewed independently to generate a list of technical steps, decision points, and errors for diagnostic knee arthroscopy. A modified Delphi technique was used to generate the final cognitive task analysis. A video and a voiceover were recorded for each phase of this procedure. These were combined to produce the Imperial Knee Arthroscopy Cognitive Task Analysis (IKACTA) tool that utilizes written and audiovisual stimuli to describe each phase of a diagnostic knee arthroscopy. In this double-blinded, randomized controlled trial, a power calculation was performed prior to recruitment. Sixteen novice orthopaedic trainees who performed ≤10 diagnostic knee arthroscopies were randomized into 2 equal groups. The intervention group (IKACTA group) was given the IKACTA tool and the control group had no additional learning material. They were assessed objectively (validated Arthroscopic Surgical Skill Evaluation Tool [ASSET] global rating scale) on a high-fidelity, phantom-knee simulator. All participants, using the Likert rating scale, subjectively rated the tool. RESULTS: The mean ASSET score (and standard deviation) was 19.5 ± 3.7 points in the IKACTA group and 10.6 ± 2.3 points in the control group, resulting in an improvement of 8.9 points (95% confidence interval, 7.6 to 10.1 points; p = 0.002); the score was determined as 51.3% (19.5 of 38) for the IKACTA group, 27.9% (10.6 of 38) for the control group, and 23.4% (8.9 of 38) for the improvement. All participants agreed that the cognitive task analysis learning tool was a useful training adjunct to learning in the operating room. CONCLUSIONS: To our knowledge, this is the first cognitive task analysis in diagnostic knee arthroscopy that is user-friendly and inexpensive and has demonstrated significant benefits in training. CLINICAL RELEVANCE: The IKACTA will provide trainees with a demonstrably strong foundation in diagnostic knee arthroscopy that will flatten learning curves in both technical skills and decision-making.
RCT Entities:
BACKGROUND: Virtual-reality and cadaveric simulations are expensive and not readily accessible. Innovative and accessible training adjuncts are required to help to meet training needs. Cognitive task analysis has been used extensively to train pilots and in other surgical specialties. However, the use of cognitive task analyses within orthopaedics is in its infancy. The purpose of this study was to evaluate the effectiveness of a novel cognitive task analysis tool to train novice surgeons in diagnostic knee arthroscopy in high-fidelity, phantom-limb simulation. METHODS: Three expert knee surgeons were interviewed independently to generate a list of technical steps, decision points, and errors for diagnostic knee arthroscopy. A modified Delphi technique was used to generate the final cognitive task analysis. A video and a voiceover were recorded for each phase of this procedure. These were combined to produce the Imperial Knee Arthroscopy Cognitive Task Analysis (IKACTA) tool that utilizes written and audiovisual stimuli to describe each phase of a diagnostic knee arthroscopy. In this double-blinded, randomized controlled trial, a power calculation was performed prior to recruitment. Sixteen novice orthopaedic trainees who performed ≤10 diagnostic knee arthroscopies were randomized into 2 equal groups. The intervention group (IKACTA group) was given the IKACTA tool and the control group had no additional learning material. They were assessed objectively (validated Arthroscopic Surgical Skill Evaluation Tool [ASSET] global rating scale) on a high-fidelity, phantom-knee simulator. All participants, using the Likert rating scale, subjectively rated the tool. RESULTS: The mean ASSET score (and standard deviation) was 19.5 ± 3.7 points in the IKACTA group and 10.6 ± 2.3 points in the control group, resulting in an improvement of 8.9 points (95% confidence interval, 7.6 to 10.1 points; p = 0.002); the score was determined as 51.3% (19.5 of 38) for the IKACTA group, 27.9% (10.6 of 38) for the control group, and 23.4% (8.9 of 38) for the improvement. All participants agreed that the cognitive task analysis learning tool was a useful training adjunct to learning in the operating room. CONCLUSIONS: To our knowledge, this is the first cognitive task analysis in diagnostic knee arthroscopy that is user-friendly and inexpensive and has demonstrated significant benefits in training. CLINICAL RELEVANCE: The IKACTA will provide trainees with a demonstrably strong foundation in diagnostic knee arthroscopy that will flatten learning curves in both technical skills and decision-making.
Authors: Bradley P Richey; Matthew Jordan Deal; Alexandra Baker; Eric M Mason; Ibrahim Mamdouh Zeini; Daryl Christopher Osbahr; Benjamin C Service Journal: Arthrosc Sports Med Rehabil Date: 2020-10-23
Authors: Matthew J J Anderson; Alirio J deMeireles; David P Trofa; David Kovacevic; Christopher S Ahmad; Thomas S Lynch Journal: J Am Acad Orthop Surg Glob Res Rev Date: 2021-03-10