Global Application of the Assessment of Communication Skills of Paediatric Endocrinology Fellows in the Management of Differences in Sex Development Using the ESPE E-Learning.Org Portal
Bibliographic record
Abstract
BACKGROUND: Information sharing in chronic conditions such as disorders of/differences in sex development (DSD) is essential for a comprehensive understanding by parents and patients. We report on a qualitative analysis of communication skills of fellows undergoing training in paediatric endocrinology. Guidelines are created for the assessment of communication between health professionals and individuals with DSD and their parents. METHODS: Paediatric endocrinology fellows worldwide were invited to study two interactive online cases (www.espe-elearning.org) and to describe a best practice communication with (i) the parents of a newborn with congenital adrenal hyperplasia and (ii) a young woman with 46,XY gonadal dysgenesis. The replies were analysed regarding completeness, quality, and evidence of empathy. Guidelines for structured assessment of responses were developed by 22 senior paediatric endocrinologists worldwide who assessed 10 selected replies. Consensus of assessors was established and the evaluation guidelines were created. RESULTS: The replies of the fellows showed considerable variation in completeness, quality of wording, and evidence of empathy. Many relevant aspects of competent clinical communication were not mentioned; 15% (case 1) and 17% (case 2) of the replies were considered poor/insufficient. There was also marked variation between 17 senior experts in the application of the guidelines to assess communication skills. The guidelines were then adjusted to a 3-level assessment with empathy as a separate key item to better reflect the qualitative differences in the replies and for simplicity of use by evaluators. CONCLUSIONS: E-learning can play an important role in assessing communication skills. A practical tool is provided to assess how information is shared with patients with DSD and their families and should be refined by all stakeholders, notably interdisciplinary health professionals and patient representatives.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.018 | 0.038 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".