Teaching communications skills to medical students: Introducing the fine art of medical practice
Bibliographic record
Abstract
INTRODUCTION: Like many other people based professions, communications skills are essential to medical practice also. Traditional medical teaching in India does not address communication skills which are most essential in dealing with patients. Communication skills can be taught to medical students to increase clinical competence. OBJECTIVE: To teach basic communication and counseling skills to fourth-year undergraduate students to increase their clinical competence. METHODOLOGY: A total of 48, fourth-year MBBS students participated in the study. They were given training in basic communication and counseling skills and taught the patient interview technique according to Calgary-Cambridge guide format. Improvement in communication was assessed by change in pre- and post-training multiple choice questions, clinical patient examination, and Standardized Patient Satisfaction Questionnaire (SPSQ) scores. RESULTS AND ANALYSIS: About 88% of the students in the sample were convinced of the importance of learning communication skills for effective practice. Almost 90% students were communicating better after training, as tested by improved SPSQ. As judged by Communication Skill Attitude Scale, student's positive attitude toward learning communication skill indicated that there is a necessity of communication skill training during undergraduate years. CONCLUSION: The ability to communicate effectively is a core competency for medical practitioners. Inculcating habits of good communications skill during formative years will help the medical students and future practitioners. Regular courses on effective communication should be included in the medical school curriculum.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".