Assessing Clinical Competence of Postgraduate Dental Specialty Trainees: A Scoping Review
Bibliographic record
Abstract
BACKGROUND: Assessment is essential to ensure that trainees meet competency standards in delivering patient care. However, a comprehensive summary of the literature on clinical assessment in postgraduate dental education is largely absent. Filling this gap is essential for developing effective assessment processes to help support competency-based education at the postgraduate level. To address this gap, this scoping review aims to map the published literature on the assessment of clinical competence for postgraduate dental specialty trainees to identify knowledge gaps and future research areas. METHODS: Guided by Arskey and O'Malley's framework, a comprehensive search was conducted across four databases (MEDLINE, EMBASE, SCOPUS and Google Scholar) from 2005 until March 2025. The search was focused on subheadings related to assessment and postgraduate dental specialty training. Two researchers independently screened the literature for eligibility using inclusion/exclusion criteria, extracted key data and analysed data thematically. The research report strategy followed the most recent PRISMA guidelines for scoping reviews. RESULTS: Thirty-three articles met the inclusion criteria, with almost equal distribution between Asia, the United States and Canada and Europe. The articles covered diverse aspects of assessment in postgraduate dental specialty training, such as individual assessment tools, WBA, assessment systems, EPA and assessment format. The number of published articles on this topic increased over fourfold in the 2015-2025 decade compared to the previous decade. Qualitatively, four themes were identified in the analysis: (1) assessment concept: the why, what and who? (2) methods and tools used in assessment; (3) challenges, opportunities and areas for future research and (4) users' perceptions of assessment. CONCLUSION: Research on clinical competence assessment in postgraduate dental education is currently limited, particularly in terms of synthesis of assessment information for making progression decisions on individual trainees. Future research should focus on assessment systems that align with competency-based education principles, leverage digital enhancements and are contextually relevant. This review underscores the complexities involved in designing and implementing a competency-based assessment system within a clinical context and the need for user involvement and feedback to improve the effective utility of assessments and ensure engagement of all stakeholders.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".