The relationship between Facebook behaviour and e‐professionalism: A questionnaire‐based cross‐sectional study among Greek dental students
Why this work is in the frame
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Bibliographic record
Abstract
INTRODUCTION: The social media attitude of health science students might affect patients' opinion about the health profession and have negative impact on e-professionalism. The aim of this study is to investigate the behaviour of Greek dental students on Facebook, focusing on potentially unprofessional posts and the online student-patient relationship. MATERIALS AND METHODS: Five hundred and twelve dental students in Greece answered an anonymous, 23-item questionnaire including multiple-choice questions about various topics, including Facebook profile settings and content shared by dental students, student-patient relationship via Facebook; and students' perception about the impact of their online behaviour. RESULTS: 93.2% of responders had a Facebook profile and 80.5% admitted that their online attitude might affect patients' opinion about dental profession. However, 71.7% posted pictures from holidays, 41.5% from nightclubs, and 26.2% photographs wearing swimwear/underwear, while 12.8% expressed online political party predilection. One quarter of students in clinical years were Facebook friends with patients and 58% and 30% of them had online discussion about topics related or not to dentistry, respectively, while 6.8% of dental students had posted defamatory comments about the dental school, faculty members or academic staff on Facebook. DISCUSSION: In accordance with studies in other countries, most Greek dental students had a Facebook profile and, although the majority realised the impact of Facebook behaviour on e-professionalism, a considerable percentage posted unprofessional content. CONCLUSION: Dental students might fall into pitfalls when it comes to e-professionalism. As social media are becoming an integral part of life, there is need to include e-professionalism in dental education curriculum.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it