Assessment of labor room communication skills among postgraduate students of obstetrics and gynecology
Bibliographic record
Abstract
Background: “Communication with patients” is an important skill needed for every physician in their clinical practice. These soft skills are required in dealing with patients at every step which include history taking from the patients, explaining them the diagnosis, the prognosis of the disease with associated complications. Dealing with empathy, taking informed consent, explaining the operative procedure and the complications associated with surgery, the art of breaking bad news are the mandatory skills for a good clinician. Labouring women like other patients also require special attention and empathy. So, the residents working in labor room need commitment to develop these soft skills in order to improve the labor room experience of expectant mothers. Objective of this study was to analyse role of a formal training in labor room communication skills among post graduate students of the department of obstetrics and gynecology.Methods: Faculty and students’ sensitization was done after approval from institutional ‘ethics committee’ for conducting this study. Pre-workshop assessment of residents for communication skills attitude and effective communication was done through ‘communication skill attitude scale’ (CSAS) and ‘GAP-KALAMAZOO scale’. Workshop for communication skills on the framework of Calgary Cambridge patient interview model and online teaching of students through what’s app videos, role-play demonstrations was followed by reassessment of the residents through above used scales.Results: Results depicted both improvements in attitude and effective communication skills among residents. 100% of the students were convinced and opined that good communication skills necessary for perfect clinical practice.Conclusions: The skill to communicate with patients is a fine art and needs to be mastered to be a good clinician. A formal training in effective communication skills is absolutely necessary to bring professionalism in medical practice.
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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 | 0.001 | 0.053 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".