The influence of social media on young risk perception of acquiring HIV: scope review
Bibliographic record
Abstract
Life connected to the internet and social media makes young people a vulnerable population group at risk of contracting HIV. This is because the media facilitate sex with people who meet over the internet, multiple sexual partnerships, inconsistent condom use and alcohol and/or drugs. It is therefore necessary to understand how these young people perceive themselves at risk for HIV when using social media. The aim of this study was to analyze the influence of social media on young people's perception of risk of acquiring HIV. This is a scoping review developed according to JBI recommendations. The Population, Concept and Context (PCC) mnemonic resulted in the research question: “What is the influence of social media on young people’s perception of risk of acquiring HIV?” The Descriptors in Health Sciences/ Medical Subject Headings (DeCS/MeSH) selected were: HIV; “Acquired Immunodeficiency Syndrome”; Adolescent; tenager; Young; “Social Networking”; “Social media”; Internet; “Health Risk” and “Risk Perception”. The search was carried out in the following data sources: Elsevier SciVerse Scopus; US National Library of Medicine - NLM, Web of Science, Science Direct, Scientific Electronic Library Online, Latin American and Caribbean Literature in Health Sciences, Spanish Bibliographic Index of Health Sciences, Catalog of Theses and Dissertations of CAPES, Digital Library of Theses and Dissertations of the University of São Paulo, Open Access Scientific Repositories of Portugal; DART-Europe; Trove from the National Library of Australia; Theses Canada; and Google Scholar. Original and review articles, theses and dissertations were included, available in full, without time limit, in any language. For analysis, a synthesis matrix that included the extracted information. A total of 11,691 publications were identified, of which 37 were read in full, 22 of which were excluded and 15 studies made up the final sample. The cell phone/smartphone was the most used tool to access social media, several times or hours a day, to find sexual partners. The media found in the studies were: those who used the internet to access websites and websites, media and social networks in general, online social networking sites, digital games and smartphone applications. As risk behaviors: inconsistent use or non-use of condoms during sexual practice; relate to multiple partners; having unprotected anal sex and sex with partners or under the influence of drugs and/or alcohol. The absence/reduction of young people's perception: not having a permanent sexual partner; perceive as unlikely or minimal the chances of contracting HIV by the way they relate; practitioners of a religion perceive themselves to be less exposed and, without knowledge, young people are unable to perceive the risk of acquiring HIV. Social media, therefore, constitute an innovative technology capable of directly influencing the risk perception of young people of acquiring HIV/Aids, when used as an intervention tool, whether through digital games, location-based applications, microblogs, social networks, real-time messaging platforms and other media; to promote awareness/prevention and promotion, improvement of risk behaviors, thus impacting the control of the HIV/Aids epidemic.
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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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".