The Use of Social Media for Dissemination of Research Evidence to Health and Social Care Practitioners: Protocol for a Systematic Review (Preprint)
Bibliographic record
Abstract
BACKGROUND Effective dissemination of research to health and social care practitioners enhances clinical practice and evidence-based care. Social media use has potential to facilitate dissemination to busy practitioners. OBJECTIVE This is a protocol for a systematic review that will quantitatively synthesize evidence of the effectiveness of social media, compared with no social media, for dissemination of research evidence to health and social care practitioners. Social media platforms, formats, and sharing mechanisms used for effective dissemination of research evidence will also be identified and compared. METHODS Electronic database searches (MEDLINE, PsycINFO, CINAHL, ERIC, LISTA, and OpenGrey) will be conducted from January 1, 2010, to January 10, 2023, for studies published in English. Randomized, nonrandomized, pre-post study designs or case studies evaluating the effect of social media on dissemination of research evidence to postregistration health and social care practitioners will be included. Studies that do not involve social media or dissemination or those that evaluate dissemination of nonresearch information (eg, multisource educational materials) to students or members of the public only, or without quantitative data on outcomes of interest, will be excluded. Screening will be carried out by 2 independent reviewers. Data extraction and quality assessment, using either the Cochrane tool for assessing risk of bias or the Newcastle-Ottawa Scale, will be completed by 2 independent reviewers. Outcomes of interest will be reported in 4 domains (reach, engagement, dissemination, and impact). Data synthesis will include quantitative comparisons using narrative text, tables, and figures. A meta-analysis of standardized pooled effects will be undertaken, and subgroup analyses will be applied, if appropriate. RESULTS Searches and screening will be completed by the end of May 2023. Data extraction and analyses will be completed by the end of July 2023, after which findings will be synthesized and reported by the end of October 2023. CONCLUSIONS This systematic review will summarize the evidence for the effectiveness of social media for the dissemination of research evidence to health and social care practitioners. The limitations of the evidence may include multiple outcomes or methodological heterogeneity that limit meta-analyses, potential risk of bias in included studies, and potential publication bias. The limitations of the study design may include potential insensitivity of the electronic database search strategy. The findings from this review will inform the dissemination practice of health and care research. CLINICALTRIAL PROSPERO CRD42022378793; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=378793 INTERNATIONAL REGISTERED REPORT DERR1-10.2196/45684
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 | 0.158 | 0.233 |
| Meta-epidemiology (narrow) | 0.009 | 0.010 |
| Meta-epidemiology (broad) | 0.021 | 0.018 |
| Bibliometrics | 0.018 | 0.020 |
| Science and technology studies | 0.006 | 0.008 |
| Scholarly communication | 0.011 | 0.012 |
| Open science | 0.007 | 0.008 |
| Research integrity | 0.011 | 0.012 |
| Insufficient payload (model declined to judge) | 0.113 | 0.021 |
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".