Levels of Empathy among Dental Students at CMH Lahore Medical College and Institute of Dentistry (NUMS ) Lahore Pakistan
Bibliographic record
Abstract
Objectives: To measure levels of empathy among undergraduate dental students in Pakistani Dentistry Institute and to find the difference with respect to gender and academic year in the dental college. Methods: This cross-sectional study was conducted at CMHLMC and IOD in Pakistan, from December 2018 to April 2019, and comprised dental students of all four years. A valid and reliable “The Toronto empathy questionnaire” was used for the collection of data. Responses were indicated on a four-point Likert scale and total scores ranged from 0-64, with higher values indicating higher levels of empathy. Eight out of sixteen items were positively worded and the remaining eight items were negatively worded. Comparison of empathy scores across the year of study was analyzed using one-way ANOVA whereas a t-test was utilized for gender differences. SPSS version 20 was used for data analysis. Results: Questionnaire was returned by 281 students, with a 94% response rate. First-year dentistry students scored the highest mean score of 3.0, followed by second and third-year students by scoring 2.8 whereas the final year students obtained the lowest mean empathy score of 2.7. When mean empathy scores were compared among students of all 4 years by ANOVA test, it was found to be statistically significant, F=3.22, p=0.02. No significant differences in empathy scores were found with respect to gender (p ≥ 0.05). Conclusion: The present study reported a decline of empathy mean scores among dentistry students as the years of study progressed. This study reflects the need for early exposure to clinical training, educational programs and innovative teaching strategies in the undergraduate dentistry curriculum by emphasizing on dentists-patient communication skills, which in turn could encourage dentistry students to become empathetic health professionals.
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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 | 0.001 | 0.003 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".