Social Media Use Among Orthopedic and Trauma Surgeons in Germany: Cross-Sectional Survey Study
Bibliographic record
Abstract
BACKGROUND: Social media (SM) has gained importance in the health care sector as a means of communication and a source of information for physicians and patients. However, the scope of professional SM use by orthopedic and trauma surgeons remains largely unknown. OBJECTIVE: This study presents an overview of professional SM use among orthopedic and trauma surgeons in Germany in terms of the platforms used, frequency of use, and SM content management. METHODS: We developed a web-based questionnaire with 33 variables and 2 separate sections based on a review of current literature. This study analyzed the first section of the questionnaire and included questions on demographics, type of SM used, frequency of use, and SM content management. Statistical analysis was performed using SPSS (version 26.0). Subgroup analysis was performed for sex, age groups (<60 years vs ≥60 years), and type of workplace (practice vs hospital). Differences between groups were assessed with a chi-square test for categorical data. RESULTS: A total of 208 participants answered the questionnaire (166/208, 79.8% male), of whom 70.2% (146/208) were younger than 60 years and 77.4% (161/208) worked in a practice. All participants stated that they use SM for private and professional purposes. On average, participants used 1.6 SM platforms for professional purposes. More than half had separate SM accounts for private and professional use. The most frequently used SM platforms were messenger apps (119/200, 59.5%), employment-oriented SM (60/200, 30%), and YouTube (54/200, 27%). All other SM, including Facebook and Instagram, were only used by a minority of the participants. Women and younger participants were more likely to use Instagram (P<.001 and P=.03, respectively). The participants working in a hospital were more likely to use employment-oriented SM (P=.02) and messenger apps (P=.009) than participants working in a practice. In a professional context, 20.2% (39/193) of the participants produced their own content on SM, 24.9% (48/193) used SM daily, 39.9% (77/193) used SM during work, and 13.8% (26/188) stated that they checked the number of followers they had. Younger participants were more likely to have participated in professional SM training and to have separate private and professional accounts (P=.04 and P=.02, respectively). Younger participants tended toward increased production of their own content (P=.06). CONCLUSIONS: SM is commonly used for professional purposes by orthopedic and trauma surgeons in Germany. However, it seems that professional SM use is not exploited to its full potential, and a structured implementation into daily professional work routines is still lacking. SM can have a profound impact on medical practices and communication, so orthopedic and trauma surgeons in Germany should consider increasing their SM presence by actively contributing to SM.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".