Social Media for the Dissemination of Cochrane Child Health Evidence: Evaluation Study
Bibliographic record
Abstract
BACKGROUND: Health care providers value ready access to reliable synthesized information to support point-of-care decision making. Web-based communities, facilitated by the adoption of social media tools such as Facebook, Twitter, and YouTube, are increasingly being used for knowledge dissemination, bridging the gap between knowledge generation and synthesis and knowledge implementation. OBJECTIVE: Our objective was to implement and evaluate a structured social media strategy, using multiple platforms, to disseminate Cochrane Child Health evidence to health care providers caring for children. METHODS: Our social media strategy had three components: daily "tweets" using the Cochrane Child Health Twitter account, weekly WordPress blog posts, and a monthly journal club on Twitter ("tweet chat"). Each tweet, blog, and journal club shared Cochrane evidence on a child health topic. We evaluated the strategy through (1) Twitter and blog site analytics, (2) traceable link (Bitly) statistics, (3) Altmetric.com scores for promoted evidence, and (4) participant feedback. We also tracked the resources required to write the blog, tweet content, and manage the strategy. RESULTS: The 22-week social media strategy ran between November 2014 and April 2015. We created 25 blog posts, sent 585 tweets, and hosted 3 tweet chats. Monthly blog visits and views and Twitter account followers increased over time. During the study period, the blog received 2555 visitors and 3967 page views from a geographically diverse audience of health care providers, academics, and health care organizations. In total, 183 traceable Bitly links received 3463 clicks, and the Twitter account gained 469 new followers. The most visited and viewed blog posts included gastrointestinal topics (lactose avoidance), research on respiratory conditions (honey for cough and treatments for asthma), and maternal newborn care (skin-to-skin contact). On Twitter, popular topics were related to public health (vaccination) and pain management. We collected Altmetric.com scores for 61 studies promoted during the study period and recorded an average increase of 11 points. Research staff (n=3) contributed approximately 433 hours to promotion activities and planning (6.5 hours each per week) to implement the social media strategy, and study investigators reviewed all content (blog posts and tweets). CONCLUSIONS: This study provides empirical evidence on the use of a coordinated social media strategy for the dissemination of evidence to professionals providing health services to children and youth. The results and lessons learned from our study provide guidance for future knowledge dissemination activities using social media tools.
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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 | 0.109 | 0.396 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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; 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".