Professional Social Media Use Among Orthopedic and Trauma Surgeons in Germany: Cross-Sectional Questionnaire-Based Study
Bibliographic record
Abstract
BACKGROUND: Social media (SM) has been recognized as a professional communication tool in the field of orthopedic and trauma surgery that can enhance communication with patients and peers, and increase the visibility of research and offered services. The specific purposes of professional SM use and the benefits and concerns among orthopedic and trauma surgeons, however, remain unexplored. OBJECTIVE: This study aims to demonstrate the specific uses of different SM platforms among orthopedic and trauma surgeons in Germany as well as the advantages and concerns. METHODS: A web-based questionnaire was developed on the use of SM in a professional context by considering the current literature and the authors' topics of interest. The final questionnaire consisted of 33 questions and was distributed among German orthopedic and trauma surgeons via the mail distributor of the Berufsverband für Orthopädie und Unfallchirurgie (Professional Association of Orthopaedic Surgeons in Germany). The study was conducted between June and July 2022. A subgroup analysis was performed for sex (male vs female), age (<60 years vs ≥60 years), and type of workplace (practice vs hospital). RESULTS: A total of 208 participants answered the questionnaire (male: n=166, 79.8%; younger than 60 years: n=146, 70.2%). In total, all of the participants stated that they use SM for professional purposes. In contrast, the stated specific uses of SM were low. Overall, the most used platforms were employment-oriented SM, messenger apps, and Facebook. Instagram emerged as a popular choice among female participants and participants working in hospital settings. The highest specific use of SM was for professional networking, followed by receiving and sharing health-related information. The lowest specific use was for education and the acquisition of patients. Conventional websites occupied a dominating position, exceeding the use of SM across all specific uses. The key benefit of SM was professional networking. Under 50% of the participants stated that SM could be used to enhance communication with their patients, keep up-to-date, or increase their professional visibility. In total, 65.5% (112/171) of participants stated that SM use was time-consuming, 43.9% (76/173) stated that they lacked application knowledge, and 45.1% (78/173) stated that they did not know what content to post. Additionally, 52.9% (91/172) mentioned medicolegal concerns. CONCLUSIONS: Overall, SM did not seem to be used actively in the professional context among orthopedic and trauma surgeons in Germany. The stated advantages were low, while the stated concerns were high. Adequate education and information material are needed to elucidate the possible professional applications of SM and to address legal concerns.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".