ReCAP: Social Media Use Among Physicians and Trainees: Results of a National Medical Oncology Physician Survey
Why this work is in the frame
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Bibliographic record
Abstract
QUESTION ASKED: To what extent, and for what purpose, do oncology physicians and physicians-in-training use Web-based social media? SUMMARY ANSWER: Despite the ability of social media to enhance collaboration and knowledge dissemination among health care providers, this cohort survey study identified an overall low use of social media among oncologists, and significant generational gaps and differences in patterns of use. METHODS: A nine-item survey was designed using a survey-generating Web site (SurveyMonkey) and was distributed securely via weekly e-mail messages to 680 oncology physicians and physicians-in-training from July 2013 through September 2013. All responses were received anonymously. Results were analyzed and are reported using descriptive statistics. RESULTS: Of 680 surveys sent, 207 were completed, for a response rate of 30.4%. Social media were used by 72% of our survey respondents (95% CI, 66% to 78%; Table 1 ). Results were cross tabulated by age, which revealed a significant difference in social media use by age group, with 89% of trainees, 93% of fellows, and 72% of early-career oncologists reporting social media use, compared with only 39% of mid-career oncologists (P < .05). Respondents reported using each social media platform for either personal or professional purposes, but rarely both. When respondents were questioned regarding barriers to social media use and their hesitations around joining a medically related social media site, the majority (59%) answered, “I don't have enough time.” [Table: see text] BIAS, CONFOUNDING FACTOR(S), DRAWBACKS: This study was conducted online, via e-mail. Therefore, respondents may represent a subpopulation of individuals who already prefer using Web-based technologies and may be more inclined to use social media, compared with individuals who do not use e-mail and were, by default, excluded from the study. We assumed, in designing this study, that the proportion of practicing oncology physicians who do not use e-mail is low. Although our sample size is small, it does represent one third of all registered medical oncologists in Canada. Finally, the high percentage of medical oncologist respondents and the concomitantly low fraction of respondents from other specialties may mean these results are more telling of social media habits in the aforementioned demographic rather than other oncology specialties. REAL-LIFE IMPLICATIONS: Our study revealed that oncology physicians and physicians-in-training who participate in Web-based social networking are largely within the younger age cohorts, whereas mid-career oncologists (age 45 to 54 years) are largely absent from the social media scene. Gaps in social networking use between younger physicians and trainees and older generations of physicians may result in critical gaps in communication, collaboration, and mentorship between these demographics. It is hoped that with further research into understanding patterns of use and limitations, medical professionals and trainees may increase their use of social media for networking, education, mentorship, and improved patient care.
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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 | 0.015 | 0.281 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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