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The Barrow Biomimetic Spine: Face, Content, and Construct Validity of a 3D-Printed Spine Model for Freehand and Minimally Invasive Pedicle Screw Insertion

Version 2 2019-08-08, 12:08
Version 1 2019-02-06, 16:01
Posted on 2019-08-08 - 12:08
Study Design:

Description and evaluation of a novel surgical training platform.

Objectives:

The purpose of this study was to investigate the face, content, and construct validity of 5 novel surgical training models that simulate freehand and percutaneous (minimally invasive surgery [MIS]) pedicle screw placement.

Methods:

Five spine models were developed by residents: 3 for freehand pedicle screw training (models A-C) and 2 for MIS pedicle screw training (models D and E). Attending spine surgeons evaluated each model and, using a 20-point Likert-type scale, answered survey questions on model face, content, and construct validity. Scores were statistically evaluated and compared using means, standard deviations, and analysis of variance between models and between surgeons.

Results:

Among the freehand models, model C demonstrated the highest overall validity, with mean face (15.67 ± 5.49), content (19.17 ± 0.59), and construct (18.83 ± 0.24) validity all measuring higher than the other freehand models. For the MIS models, model D had the highest validity scores (face, content, and construct validity of 11.67 ± 3.77, 18.17 ± 2.04, and 17.00 ± 3.46, respectively). The 3 freehand models differed significantly in content validity scores (P = .002) as did the 2 MIS models (P < .001). The testing surgeons’ overall validity scores were significantly different for models A (P = .005) and E (P < .001).

Conclusions:

A 3-dimensional-printed spine model with incorporated bone bleeding and silicone rubber soft tissue was scored as having very high content and construct validity for simulating freehand pedicle screw insertion. These data has informed the further development of several surgical training models that hold great potential as educational adjuncts in surgical training programs.

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AUTHORS (12)

Michael A. Bohl
Rohit Mauria
James J. Zhou
Michael A. Mooney
Joseph D. DiDomenico
Sarah McBryan
Claudio Cavallo
Peter Nakaji
Steve W. Chang
Juan S. Uribe
Jay D. Turner
U. Kumar Kakarla
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