Sharing content about HIV/AIDS through networks and social media in scientific literature: a scoping review
Bibliographic record
Abstract
Social media and social networkds an important role in the dissemination of information about HIV/AIDS. The objective of the study was to map the content on HIV/AIDS shared through social networks and media in scientific materials. This is a scoping review developed in accordance with the recommendations of the Joanna Briggs Institute (JBI) and SCR Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and produced in five stages: 1) identification of the research question; 2) identification of relevant studies; 3) selection of studies; 4) data extraction, separation, summarization and reporting of results; and 5) communication of results. The mnemonic Participant, Concept and Context was applied to construct the research question, in which Participant corresponds to HIV, Concept to dissemination of information and Context to “social networks” and “social media”. The guiding question was defined as: “What are the main types of content on HIV/AIDS shared through social networks and media in the scientific literature?”. The searches were conducted in the following data sources/libraries/databases/academic search engines: Scopus, U.S. National Library of Medicine, Web of Science, Scientific Electronic Library Online, Virtual Health Library (BVS), Catalog of Theses and Dissertations of the Coordination for the Improvement of Higher Education Personnel (CAPES), Cinahl, Digital Library of Theses and Dissertations of the University of São Paulo (USP), Open Access Scientific Repositories of Portugal (RCAAP), DARTEurope, Trove of the National Library of Australia and Theses Canada. Original and review articles, theses and dissertations, available in full, without time limit, in any language were included. For analysis, a synthesis matrix was created that included the extracted information. A total of 3,485 publications were identified, of which 156 were read in full, 117 were excluded and 39 studies comprised the final sample. Among the media and social networks most mentioned in the studies, Twitter (currently X) and Facebook stood out as the most cited platforms with 33.33%. As for content about HIV on networks and social media, it was possible to identify a variety of topics. Pre-Exposure Prophylaxis (PrEP) was the most cited content among the studies, followed by HIV testing, diagnosis, social support, treatment, HIV risk factors, condom use and PEP. The importance of networks and social media in disseminating information about HIV/AIDS is undeniable, however, there are challenges, such as misinformation and stigmatization, which reinforces the need to share evidence-based content. In addition, ongoing training of health professionals is essential to guide the public in the search for reliable sources.
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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 | 0.055 | 0.180 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.055 | 0.049 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".