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Record W4391777402 · doi:10.2196/44111

Evaluating the Intensity of Exposure to MTV Shuga, an Edutainment Program for HIV Prevention: Cross-Sectional Study in Eastern Cape, South Africa

2024· article· en· W4391777402 on OpenAlexvenueno aff
Sarah Mulwa, Venetia Baker, Cherie Cawood, David Khanyile, Dominique O’Donnell, Sophie Sarrassat, Simon Cousens, Isolde Birdthistle

Bibliographic record

VenueJMIR Formative Research · 2024
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsnot available
Fundersnot available
KeywordsLogistic regressionConfoundingMedicineHuman immunodeficiency virus (HIV)Cross-sectional studyEnvironmental healthCapeFamily medicinePsychologyGeographyInternal medicinePathology

Abstract

fetched live from OpenAlex

BACKGROUND: MTV Shuga is an edutainment campaign designed to equip young people with knowledge, motivation, and informed choices to protect themselves from HIV infection. From 2019 to 2020, a total of 10 episodes of a new dramatic series, MTV Shuga "Down South 2" (DS2), were broadcast via television and the internet, alongside complementary media activities. OBJECTIVE: This study aims to investigate whether the intensity of DS2 exposure was linked with positive HIV prevention outcomes in a setting with high HIV prevalence and relatively low levels of HIV testing. METHODS: We analyzed data from a web-based survey of participants aged 15 to 24 years in South Africa in 2020. The survey was promoted via social media platforms of schools, universities, and communities in Eastern Cape, South Africa. The primary exposure of interest was the intensity of exposure to DS2, measured by the number of episodes of DS2 watched on the television or the internet or listened to on the radio (out of 10 episodes). Individuals who had not watched or listened to any DS2 episode were classified according to other MTV Shuga content that they had accessed. We estimated associations between the intensity of DS2 exposure and HIV-related outcomes, including knowledge of HIV status, awareness of HIV self-testing (HIVST) and pre-exposure prophylaxis (PrEP), uptake of HIVST, and demand for HIVST and PrEP, adjusting for potential confounders using multivariable logistic regression. RESULTS: Among the 3431 survey participants, 827 (24.1%) were exposed to DS2. Specifically, 18.1% (622/3431) watched or listened to only 1 DS2 episode, and 2.4% (82/3431), 1.7% (58/3431), and 1.8% (62/3431) watched or listened to 2 to 4, 5 to 7, and 8 to 10 DS2 episodes, respectively. Increasing the exposure to DS2 was associated with improvements in most outcomes. Exposure to multiple episodes (eg, 2-4, 5-7, and 8-10) was associated with successively higher odds of knowing one's HIV status, awareness of PrEP and HIVST, and uptake of HIVST compared with no MTV Shuga exposure, albeit with statistical uncertainty around some estimates. The interest in using HIVST or PrEP was high overall (>80%), with no measurable differences by DS2 intensity. CONCLUSIONS: We found evidence consistent with a dose-response relationship between MTV Shuga DS2 exposure and outcomes, including knowledge of HIV status, awareness and uptake of HIVST, and awareness of PrEP among young people in Eastern Cape. This indicates that greater engagement with a youth-focused edutainment campaign can improve HIV testing and prevention options in a setting and population with high need. However, only a few participants accessed multiple DS2 episodes despite its availability on multiple media platforms. We conclude that there is potential to benefit more young people by increasing access to and interest in the show.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.074

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.219
GPT teacher head0.554
Teacher spread0.335 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2024
Admission routes1
Has abstractyes

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