Early adopters or laggards? Attitudes toward and use of social media among urologists
Bibliographic record
Abstract
OBJECTIVE: To understand the attitudes and practices of urologists regarding social media use. Social media services have become ubiquitous, but their role in the context of medical practice is underappreciated. SUBJECTS AND METHODS: A survey was sent to all active members of the Canadian Urological Association by e-mail and surface mail. Likert scales were used to assess engagement in social media, as well as attitudes toward physician responsibilities, privacy concerns and patient interaction online. RESULTS: Of 504 surveys delivered, 229 were completed (45.4%). Urologists reported frequent or daily personal and professional social media use in 26% and 8% of cases, respectively. There were no differences between paper (n = 103) or online (n = 126; P > 0.05) submissions. Among frequent social media users, YouTube (86%), Facebook (76%), and Twitter (41%) were most commonly used; 12% post content or links frequently to these sites. The most common perceived roles of social media in health care were for inter-professional communication (67%) or as a simple information repository (59%); online patient interaction was endorsed by 14% of urologists. Fewer than 19% had read published guidelines for online patient interaction, and ≤64% were unaware of their existence. In all, 94.6% agreed that physicians need to exercise caution personal social media posting, although 57% felt that medical regulatory bodies should 'stay out of [their] personal social media activities', especially those in practice <10 years (P = 0.001). In all, 56% agreed that social media integration in medical practice will be 'impossible' due to privacy and boundary issues; 73% felt that online interaction with patients would become unavoidable in the future, especially those in practice >20 years (P = 0.02). CONCLUSION: Practicing urologists engage infrequently in social media activities, and are almost universal in avoiding social media for professional use. Most feel that social media is best kept to exchanges between colleagues. Emerging data suggest an increasing involvement is likely in the continuing professional development space.
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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 | 0.002 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 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".