Learning Outcomes and Educational Effectiveness of Social Media as a Continuing Professional Development Intervention for Practicing Surgeons: A Systematic Review and Narrative Synthesis
Bibliographic record
Abstract
Objective: The objective of this systematic review was to assess the learning outcomes and educational effectiveness of social media as a continuing professional development intervention for surgeons in practice. Background: Social media has the potential to improve global access to educational resources and collaborative networking. However, the learning outcomes and educational effectiveness of social media as a continuing professional development (CPD) intervention are yet to be summarized. Methods: We searched MEDLINE and Embase databases from 1946 to 2022. We included studies that assessed the learning outcomes and educational effectiveness of social media as a CPD intervention for practicing surgeons. We excluded studies that were not original research, involved only trainees, did not evaluate educational effectiveness, or involved an in-person component. The 18-point Medical Education Research Study Quality Instrument (MERSQI) was used for quality appraisal. Learning outcomes were categorized according to Moore's Expanded Outcomes Framework (MEOF). Results: A total of 830 unique studies revealed 14 studies for inclusion. The mean MERSQI score of the included studies was 9.0 ± 0.8. In total, 3227 surgeons from 105 countries and various surgical specialties were included. Twelve studies (86%) evaluated surgeons' satisfaction (MEOF level 2), 3 studies (21%) evaluated changes in self-reported declarative or procedural knowledge (MEOF levels 3A and 3B), 1 study (7%) evaluated changes in self-reported competence (MEOF level 4), and 5 studies (36%) evaluated changes in self-reported performance in practice (MEOF level 5). No studies evaluated changes in patient or community health (MEOF levels 6 and 7). Conclusions: The use of social media as a CPD intervention among practicing surgeons is associated with improved self-reported declarative and procedural knowledge, self-reported competence, and self-reported performance in practice. Further research is required to assess whether social media use for CPD in surgeons is associated with improvements in higher level and objectively measured learning outcomes.
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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 | 0.018 | 0.085 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.008 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".