The Use of Social Media in Interprofessional Education: Systematic Review
Bibliographic record
Abstract
BACKGROUND: The implementation of interprofessional education (IPE) activities into health care education is a challenge for many training programs owing to time and location constraints of both faculty and learners. The integration of social media into these IPE activities may provide a solution to these problems. OBJECTIVE: This review of the published literature aims to identify health care IPE activities using social media. METHODS: The authors searched 5 databases (from the beginning coverage date to May 27, 2017) using keywords related to IPE and social media. Teams of 2 authors independently reviewed the search results to identify peer-reviewed, English language papers reporting on IPE activities using social media. They assessed the study quality of identified papers using the Medical Education Research Study Quality Instrument. RESULTS: A total of 8 studies met the review's inclusion criteria. Of these 8 papers, 3 had single-group, posttest-only study design; 4 had single-group, pre- and posttest design; and 1 had nonrandomized 3-group design. Qualitative and quantitative outcome measures showed mixed results with the majority of student feedback being positive. CONCLUSIONS: Despite a need for additional research, this review suggests that the use of social media may aid the implementation of health care IPE.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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; both teacher heads agree on what is shown here.
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".