Dimitrios Stefanidis

Background: The shortage of practitioners trained to provide essential surgical care remains among the most stubborn contributors to the global burden of disease, particularly in resource‐constrained settings where expert trainers are scarce. The Surgical Education Learners Forum (SELF) is a global community of practice developing cost‐effective, scalable, open‐access training modules that let clinicians anywhere learn, practice, and evaluate procedural skills independently. This fifth and final article in the SELF series reports expert opinion from the 2023 SELF Symposium on a pathway to scale, addressing evidence generation, digital delivery platforms, and the barriers and actions needed to achieve widespread adoption. Methods: An interprofessional group of surgeons, trauma and critical care practitioners, academics, educators, technologists, and learner representatives participated in three facilitated working sessions on evidence generation and reporting, platforms, and a theory of change. Each session used structured small‐group discussions guided by common prompts, thematic clustering of responses on shared working walls, and individual voting to prioritize recommendations. Responses were subsequently consolidated, re‐sorted by theme, and returned to participants to verify accuracy. Results: In the evidence generation session, participants prioritized setting SELF standards and definitions—chiefly defining study types and the level of evidence required for each. For platforms, credibility and transparency, findability, and accessibility emerged as the dominant learner and developer concerns, with minimizing bandwidth and enabling offline use of the top‐ranked best practice; the leading calls to action were to construct a supporting community of practice and convene a standards group. In the theory of change session, participants ranked individual factors highest, with engaging influential champions and senior gatekeepers who drive organizational decisions receiving the most votes overall, followed by language and communication, organizational, and economic and legal factors. Conclusions: Together, these sessions chart a practical way forward for low‐cost, open‐access, self‐assessed procedural skills simulation, emphasizing rigorous evaluation, credible and accessible delivery platforms, and coordinated engagement with key stakeholders. High‐quality training materials must be matched by equally rigorous studies evaluating them, and by sustained, methodical efforts to overcome barriers to acceptance.

Introduction: Since its initial inception, robotic‐assisted minimally invasive surgery (RAMIS) is continually being applied to a wider array of procedures. However, there are significant limitations in current surgical subsystems, including a large learning curve, lack of effective haptic feedback, decreased surgical intuition, and decreased dexterity. Methods: A narrative review of the literature was conducted to provide an overview of key developments in the field. Relevant articles were identified through searches of PubMed, IEEE, Google Scholar, and EMBASE, along with manual screening of references. Results: A selection of representative articles covering topics including teleoperation, kinematics, dynamics, and haptic feedback is discussed to highlight major themes and recent advances. Conclusions: Despite recent advances, limitations to operator experience remain. Numerous strategies and approaches are currently being proposed and explored to further advance surgical subsystems, improving dexterity, haptic feedback, movement time delay, and learning curve.

Surgical video interpretation is a promising medical artificial intelligence application. However, no existing video annotation method preserves the spatiotemporal complexity of surgeon reasoning. Here we show that verbal reasoning and visual attention can be converted into structured, machine-actionable records of intraoperative behaviours. Our method decomposes transcribed verbal commentary into video-anchored semantic feedback chunks, which are classified via a large language model, with spatial grounding to surgical scenes via eyegaze or cursor tracking. We demonstrate method validity and scalability on structured and unstructured annotation tasks. For quality feedback on full-length colorectal procedures, the method reached near-human fidelity for chunking (cosine similarity: 0.95±0.01) and semantic classification across observations (Cohen’s κ: 0.71±0.07) and evaluative triggers (Cohen’s κ: 0.67±0.14), with excellent usability ratings. For structured critical view of safety assessment in laparoscopic cholecystectomy, implicit annotation yielded excellent agreement with explicit reviewer ratings (Cohen’s κ: 0.83, 0.49 and 0.81 across three criteria). We anticipate this method will advance surgical data science by enabling scalable construction of meaningfully annotated surgical video datasets.

Background: Feedback on faculty teaching is essential for faculty development and education quality. Often in surgical training programs, this feedback is provided through resident evaluations of faculty. The content and quality of faculty teaching evaluations being used are, however, unknown as no standardized tool exists. The aim of this study was to identify the characteristics and evaluation domains of faculty teaching evaluation tools used in surgical residency programs. Methods: Using convenience sampling, blank faculty teaching evaluation forms completed by residents were collected from university-based surgery residency programs across multiple U.S. geographic regions, including large public and private academic medical centers. A document analysis was performed using a mixed-methods approach to conduct a quantitative analysis to characterize the tools’ design features using descriptive statistics and perform a qualitative analysis of all question items using inductive content analysis to determine the evaluation domains. Results: Fourteen faculty teaching evaluation forms from thirteen U.S. surgery departments met the sampling criteria and were included in the final analysis. Quantitative analysis showed that the mean number of questions per evaluation was 14.7 (median 13; range 4–23), composed of rating questions (median 10.5; range 0–20), free text comments (median 3; range 1–12), and checklist questions (median 0.5; range 0–2). The analysis also identified five styles of response anchors to each question including sequential, agreement, frequency, binary, and open-ended, and three performance levels for assessed faculty traits or behaviors including below expected performance, at expected performance, and above expected performance. Qualitative analysis of 206 question items revealed four major evaluation domains including teaching effectiveness (53.8% of codes), professionalism (25.5%), clinical performance (11.6%), and overall performance (9.1%) from the faculty teaching evaluation tools. Conclusions: Surgical faculty teaching evaluations vary widely in design and frequently conflate teaching with professionalism and clinical performance. This domain mixing poses challenges for score interpretation and threatens construct validity if evaluations are used to assess teaching effectiveness exclusively. The findings suggest a consensus-based approach to defining core teaching domains and evidence-informed design principles, while allowing flexibility for local implementation. This study demonstrates the value of document analysis for critically examining assessment tools and provides empirical groundwork to inform future faculty evaluation efforts in surgical education.

Robotic surgery has become ubiquitous across a variety of surgical specialties including bariatric surgery. Application of this new technology to bariatric surgery requires some modifications to the traditional laparoscopic technique to accomplish the procedures effectively and efficiently. In this technical report, we describe our approach to robotic Roux-en-Y gastric bypass, outline potential benefits over laparoscopy, and highlight technical variations in the conduct of this operation that may be helpful to practicing bariatric surgeons, especially those who plan to adopt robotic surgery to their practice. We present handsewn vs. stapled gastrojejunostomy creation, omega loop technique vs. traditional construction of the jejunojejunostomy, and other technical variations. Each method has its own advantages and disadvantages which we have highlighted throughout this article. We also discuss pre- and postoperative management. When compared to traditional laparoscopic gastric bypass, robotic approaches remain less often used in current practice but are expected to surpass laparoscopy in just a few years. A robotic approach offers unique benefits for gastric bypass while still proving to be a safe and effective procedure for surgical weight loss.