Formative assessment of the communication skills related to drug delivery systems on standardized patients through group objective structured clinical encounters in second year medical students
Bibliographic record
Abstract
Background: Choosing an appropriate Drug Delivery System (DDS) influences the acceptability, adherence and better outcome of the therapy in the patients. The present study was planned to evaluate the second year MBBS students on standardized patients (SP) using Group Objective Structured Clinical Encounters (GOSCE) after content delivery by traditional power point class versus experiential teaching methodology.Methods: DDS practical class was held in two larger groups after adding two odd sub-groups (1+3) as ‘A’ (64 students) and even sub-groups (2+4) as ‘B’ (66 students). The formative GOSCE evaluation was done 2 weeks after the classes by the trained physician examiners as per the Medical Council of Canada pre-determined scoring instruments.Results: The average magnitude of change in GOSCE scoring is extremely statistical significant on t-test (P< 0.0001) in favour of experiential teaching methodology for all the skills. The statistical significant percentage of students were able to extract the treatment history in respect of eliciting problem, reasons for non-compliance, methods of intake, explain the technique and showed the courteous professional behaviours.Conclusions: The clinical cases as SP in pharmacology teaching for developing competency based communication skills and GOSCE are the appropriate methodology for evaluation of large student group for experiential DDS training.
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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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".