Evaluating the Role of Supervised Early Operative Exposure in Improving Surgical Confidence and Patient Outcomes in Junior Orthopedic Residents

Summary

This protocol presents structured, supervised early operative exposure model for junior orthopedic residents. It outlines standardized resident allocation, direct faculty supervision, and stepwise progression of operative responsibilities. The protocol also includes monitoring of operative performance and outcomes to support safe skill development, competency-based surgical training, and improved technical proficiency during early residency.

Abstract

This prospective multicenter controlled cohort study evaluated whether structured supervised early operative exposure improves educational and clinical outcomes among junior Orthopedic residents. The goal of this protocol is to describe a structured, competency-based approach for implementing supervised early operative exposure in orthopedic residency training and evaluating its educational and clinical impact. Ninety-six first and second-year residents across three tertiary teaching hospitals were allocated to early exposure or traditional training and followed for 12 months. Residents receiving early supervised exposure demonstratedprocedures andincrease in surgical confidence (mean change 2.4 points; 95% CI 1.9–2.9; p < 0.001), reduced operative duration by approximately 20% in common procedures, and maintained low complication rates within accepted clinical benchmarks. Patient satisfaction and functional recovery outcomes remained high and improved in parallel with resident development. Surgical confidence showed a strong positive correlation with supervisor-rated technical skill (r = 0.81). These findings indicate that competency-based supervised early operative participation enhances resident performance and patient outcomes without compromising safety, supporting its integration into Orthopedic residency training.

Introduction

The acquisition of surgical competence and confidence among junior Orthopedic residents is a critical determinant of both trainee progression and patient outcomes¹. Early supervised operative participation has been associated with accelerated skill development, improved clinical judgment, and greater preparedness for independent practice^2,3 By enabling residents to translate theoretical knowledge into real operative performance under expert guidance, structured supervision offers a balanced pathway between progressive autonomy and patient safety^4,5. Orthopedic surgery requires advanced psychomotor coordination, intraoperative decision-making, and adaptive responses to procedural complexity⁶. Educational strategies such as simulation-based training, mastery learning, and virtual reality platforms have therefore been increasingly incorporated into residency curricula to support early technical development and reduce intraoperative error risk⁷. These approaches provide safe environments for deliberate practice and competency assessment; however, simulation alone may not fully replicate the cognitive, interpersonal, and situational demands of live surgical care⁸. Supervised participation in real operative settings remains an essential component of professional formation, particularly for developing judgment under stress, team communication, and context-dependent decision-making^9,10. A persistent challenge in Orthopedic training is achieving an appropriate balance between safeguarding patients and ensuring sufficient early operative exposure for residents. Limited access to operative cases during the initial years of residency due to work-hour regulations, scheduling structures, or institutional practice patterns may delay technical competence, reduce confidence, and postpone readiness for independent responsibility¹¹. In addition, variability in supervision quality and case distribution across institutions contributes to heterogeneous training experiences and inconsistent competency outcomes among graduates^12,13,14,15. These concerns highlight the need for structured, reproducible models of early operative exposure that maintain safety while promoting efficient skill acquisition^{14,15,16,17,18,19,20}. To address this need, the goal of this article is to present a standardized and reproducible protocol for implementing structured supervised early operative exposure in junior orthopedic residency training. The protocol outlines resident allocation procedures, defined supervision structures, graduated autonomy thresholds, inter-institutional calibration strategies, and outcome monitoring processes to support safe, consistent, and reproducible implementation across training institutions.

The present study was designed to evaluate the effectiveness of a structured, supervised early operative exposure program implemented across three tertiary teaching hospitals and focused on junior Orthopedic residents. Specifically, the study examines whether early hands-on participation under direct supervision is associated with improvements in surgical confidence, technical performance, operative efficiency, complication rates, and postoperative patient-reported outcomes. The investigation also seeks to clarify how graduated autonomy can be operationalized to optimize learning while preserving patient safety within routine clinical training environments^21,22,23,24. This work introduces a standardized operational protocol that integrates structured case allocation, continuous attending supervision, clearly defined autonomy thresholds, inter-site calibration procedures, and competency-guided progression within a unified training framework. The protocol emphasizes consistent supervision practices, stepwise resident responsibility, and standardized calibration across training sites to ensure safe skill acquisition and uniform implementation of competency-based orthopedic surgical training. Prior studies have frequently evaluated either trainee confidence or clinical endpoints in isolation, have focused on simulation or general surgical populations, or have lacked longitudinal follow-up and standardized supervision models^25,26,27. By integrating supervised early operative exposure with measurable educational and clinical indicators, the present study aims to provide evidence to inform competency-based curriculum design and to support more consistent training standards across institutions^28,29,30. This protocol is designed for tertiary or high-volume training centers with structured orthopedic residency programs and continuous attending supervision. It is most applicable to institutions with established surgical training infrastructure, where junior residents can participate in operative procedures under direct supervision. Institutions implementing this method should have defined case logging systems, standardized evaluation tools, and sufficient operative volume to support graduated autonomy progression under direct oversight. In addition, the presence of experienced supervising surgeons and a structured monitoring system for resident performance is essential to ensure patient safety and effective competency-based skill development.

Before outlining the methodological steps, it is important to note that the following section presents the operational details required for implementing this training framework in clinical practice. The following protocol details the step-by-step implementation of this structured supervised early operative exposure model, including allocation procedures, supervision standards, competency progression criteria, and standardized outcome assessment methods. Despite growing attention to simulation, mentorship, and competency-based progression in surgical education, important knowledge gaps remain. In particular, limited evidence exists regarding how early supervised operative exposure in Orthopedic residency influences both resident development and patient outcomes over time, or how supervision structures and timing of exposure should be standardized for reproducibility. Addressing these gaps is essential for guiding evidence-based reform in Orthopedic surgical training and for ensuring that educational innovation translates into safe, high-quality patient care.

Protocol

Ethics statement
This study protocol was approved by the Institutional Review Board (IRB) of Xuanwu Hospital Capital Medical University (Approval ID: [2018] 083) and was conducted in accordance with the ethical standards of the Helsinki Declaration. Informed consent was obtained from all participating residents and patients prior to data collection.

1. Study design and setting

1. Implement a prospective randomized controlled cohort multi-center study over 12 consecutive months (January–December 2025).
2. Select three tertiary teaching hospitals in China based on: Annual Orthopedic surgical volume > 1,500 cases, availability of structured residency training programs, electronic medical record (EMR) systems enabling outcome extraction.
3. Assign each hospital a unique study code (Hospital A, B, and C) for anonymized analysis.

2. Participant recruitment and cohort allocation

1. Eligibility screening
   1. Screen all first- and second-year Orthopedic residents at participating institutions.
   2. Include residents who are enrolled in accredited orthopedic residency programs, who have no prior independent-operative experience before residency and who are ready to provide written informed consent.
   3. Exclude residents who are in postgraduate year ≥ 3 or take extended medical leave (>4 weeks) during the study period or previously completed orthopedic fellowship or equivalent formal surgical training.
2. Perform cohort allocation by assigning eligible residents to either the early operative exposure cohort or the traditional training cohort.
   NOTE: The traditional training cohort follows the conventional residency model, where junior residents mainly observe surgeries and assist in minor tasks, with direct operative participation introduced gradually at later stages of training.
   1. Perform allocation using block randomization stratified by hospital and training year with a 1:1 ratio.
   2. Prepare sequentially numbered opaque envelopes containing cohort assignments by an independent statistician to ensure allocation concealment. Due to the nature of the training protocol, residents and supervising faculty are not blinded to cohort allocation; however, outcome assessors and data analysts remain blinded to group assignments during evaluation and statistical analysis.
   3. Target a total sample size of 96 residents (n = 48 per cohort).

3. Structured supervised early operative exposure intervention

1. Scheduling of operative exposure
   1. Schedule residents in the early-exposure cohort for a minimum of two supervised operative sessions per week through the departmental surgical roster coordinated by the residency program coordinator.
   2. Ensure exposure to four procedure categories—trauma fixation, joint arthroplasty, arthroscopy, and elective reconstructive surgery—by distributing residents across relevant surgical lists according to weekly case schedules.
   3. Record procedure type, operative duration, supervising surgeon, and resident role (observer, assistant, primary operator under supervision) in a standardized operative logbook or electronic case-logging system immediately after each procedure.
2. Supervision framework
   1. Ensure the continuous in-room presence of an attending orthopedic surgeon during all resident operative participation.
   2. Provide step-by-step verbal and technical guidance throughout procedures.
   3. Prevent unsupervised independent operating during the study period.
3. Graduated autonomy progression
   1. Assign resident intraoperative role according to predefined competency thresholds:
      Level 1: Observation only
      Level 2: Assisted participation
      Level 3: Partial procedural lead under direct supervision
      Level 4: Independent performance with attending scrubbed and supervising
   2. Advance residents only after completion of ≥ 10 assisted cases in the same procedure category, attending surgeon competency score ≥ 4 on a 5-point global rating scale and after no major intraoperative safety concerns.
4. Standardization across centers
   1. Implement a faculty-approved procedural training checklist at all hospitals.
   2. Conduct monthly inter-institutional calibration meetings to harmonize supervision and scoring practices.
   3. Audit 10% of operative logs randomly for protocol adherence.

4. Outcome assessment

NOTE: The primary outcome of this protocol is the technical skill performance of residents, measured using a validated global rating scale by blinded attending surgeons. Secondary outcomes include resident surgical confidence, perioperative patient clinical outcomes, and patient-reported outcomes associated with resident operative participation.

1. Surgical confidence
   1. Administer the Self-Efficacy in Surgical Skills (SESS) questionnaire: At baseline (month 0), Midpoint (month 6), and Completion (month 12).
   2. Deliver questionnaires electronically via secure survey software.
   3. Calculate total confidence score according to validated scoring guidelines.
   4. Export SESS questionnaire responses from the electronic survey system to statistical software (e.g., SPSS or R).
   5. Score each item on a 5-point Likert scale (1–5) and sum all item scores to obtain the total confidence score for each resident at each time point.
   6. Apply multiple imputations if ≤ 10% items are missing.
   7. Handle ≤ 10% missing questionnaire items using multiple imputation.
   8. Apply multiple imputations for missing clinical and patient-reported outcomes when ≤ 10% data are missing; otherwise perform outcome-specific complete-case analysis.
2. Technical skill evaluation
   1. Require two blinded attending surgeons to independently evaluate resident technical performance using the Objective Structured Assessment of Technical Skills (OSATS) Global Rating Scale. Assess seven domains: respect for tissue, time and motion, instrument handling, knowledge of instruments, flow of operation, use of assistants, and knowledge of the procedure. Each domain is scored on a 5-point Likert scale (1 = poor, 5 = excellent).
   2. Calculate inter-rater reliability using the intraclass correlation coefficient (ICC) with a two-way random-effects model for absolute agreement (ICC [2,1]).
   3. Perform analysis in statistical software (e.g., SPSS or R) using scores from both raters for each resident assessment. Report ICC value with 95% confidence intervals.
   4. Use the mean score of both raters for statistical analysis of resident technical performance outcomes.
3. Patient clinical outcomes
   1. Extract perioperative variables from EMRs: Operative duration, complication occurrence, length of hospital stays, time to functional recovery.
   2. Review postoperative records and classify complications using the Clavien–Dindo grading system according to the intervention required (Grade I–V).
   3. Record whether the resident served as: Assistant, Partial lead, Primary supervised operator.
4. Patient-reported outcomes
   1. Collect postoperative pain and functional recovery scores at: Hospital discharge and at 30-day follow-up.
   2. Assign a unique anonymized identifier to each surgical case and corresponding resident.
   3. Record resident participation level (assistant, partial lead, or primary supervised operator) in the operative log using this identifier.
   4. Link patient-reported outcome data to the same identifier to associate outcomes with the resident’s participation level while maintaining patient and resident confidentiality.

5. Data management

1. Assign one trained site coordinator per hospital.
2. Enter collected data into a centralized encrypted research database within 48 h of collection.
3. Record the following variables: resident identifier, cohort allocation, procedure type, operative duration, resident participation level, technical skill scores (OSATS), surgical confidence scores (SESS), perioperative clinical outcomes, complication grade (Clavien–Dindo), and patient-reported outcome scores.
   Note: Use anonymized identifiers for residents and patients to maintain confidentiality.
   Caution: Verify data accuracy before entry and restrict database access to authorized research personnel
4. Perform weekly automated range and consistency checks.
5. Remove all direct identifiers (e.g., patient name, hospital ID, date of birth, contact details) from the dataset and replace them with unique coded study numbers generated for each participant. Maintain a separate, password-protected linkage file that maps the original identifiers to the coded study numbers for authorized study personnel only.
6. Compile the final dataset after scoring key variables: SESS confidence score (sum of item responses), OSATS technical skill score (mean of two raters), and clinical outcomes (operative duration, complication grade, hospital stay, patient-reported pain/recovery).
7. Verify data completeness and store the coded dataset on password-protected institutional servers accessible only to the analysis team.

6. Statistical analysis

All statistical analyses were performed using SPSS (version 26.0). Continuous variables were expressed as mean ± SD and categorical variables as frequencies (%). Appropriate parametric tests, regression analyses, and correlation analyses were applied as described below, with statistical significance set at p < 0.05.

1. Perform statistical analyses using SPSS (version 26) or equivalent software.
   1. To perform descriptive Analysis, summarize demographic variables using Mean ± SD for continuous variables, frequency (%) for categorical variables.
   2. Set two-tailed statistical significance at p < 0.05.
   3. Report 95% confidence intervals for all primary estimates.
   4. Perform independent-samples t-tests to compare continuous baseline variables between cohorts.
   5. Perform chi-square (χ²) tests to compare categorical baseline variables.
2. Longitudinal confidence changes
   1. Conduct repeated-measures ANOVA to evaluate within-resident confidence score changes across time points.
   2. Test sphericity using Mauchly’s test and apply Greenhouse–Geisser correction if violated.
3. Between-group comparisons
   1. Use mixed-effects linear regression with:
      1. Fixed effects: cohort, time, hospital and time (treated as a categorical variable: baseline, 6 months, and 12 months).
      2. Random effect: resident ID
4. Patient outcomes associations
   1. Perform multivariable regression analysis adjusting for: Patient age, Comorbidities, Procedure complexity, Hospital site.
5. Operative performance analysis
   1. Use paired-samples t-tests to compare operative duration before and after supervised exposure.
   2. Calculate effect sizes using Cohen’s d.
6. Reliability and correlation analysis
   1. Evaluate inter-rater reliability of OSATS scores using the intraclass correlation coefficient (ICC) with a two-way random-effects model for absolute agreement.
   2. Assess associations between surgical confidence and technical skill using Pearson correlation analysis and report correlation coefficients (r) with 95% confidence intervals.

Results

Participant characteristics and baseline comparability
A total of 112 junior orthopedic residents were screened for eligibility. Of these, 16 residents were excluded (8 did not meet inclusion criteria and 8 declined participation). The remaining 96 residents were randomized into two groups: 48 residents in the early operative exposure cohort and 48 residents in the traditional training cohort. During follow-up, 3 residents from the early exposure cohort and 4 from the traditional cohort were lost to ...

Discussion

This multi-center investigation found that structured, supervised early operative exposure for junior orthopedic residents was associated with higher surgical confidence, faster technical skill acquisition, and improved patient outcomes without compromising procedural safety. Critical to the success of this protocol is the consistent application of structured supervision, clearly defined autonomy thresholds, and standardized inter-institutional calibration procedures. Variability in supervision intensity, case allocation...

Materials

List of materials used in this article

Name	Company	Catalog Number	Comments
Data Quality Monitoring Checklist	Study-specific	N/A	Used by site coordinators to ensure accuracy, completeness, and standardization.
Electronic Medical Record (EMR) System	Hospital-specific vendors	N/A	Used to extract perioperative data, complications, and recovery outcomes.
Resident Procedural Log System	Hospital/institution	N/A	Tracks case volumes, roles (assistant, operator), and exposure type.
Secure Central Research Database (for anonymized data storage)	Institution-approved provider	N/A	Receives encrypted, de-identified data from each site coordinator.
Self-Efficacy in Surgical Skills (SESS) Questionnaire	N/A (validated academic instrument)	N/A	Used to assess surgical confidence at baseline, 6 months, and 12 months.
Standardized Operative Training Checklist	Developed internally by faculty	N/A	Consensus-based checklist used across all three hospitals to standardize supervision and evaluation.
Statistical Analysis Software	IBM  SPSS	21.0	Used for ANOVA, mixed-effects models, and multivariate regression.
Surgical Skill Assessment Tools (e.g., rating forms, global rating scales)	Internal orthopedic residency curriculum	N/A	Used during supervised operative exposure to score technical ability.