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Record W4403020415 · doi:10.2196/55275

Evaluating Reaction Videos of Young People Watching Edutainment Media (MTV Shuga): Qualitative Observational Study

2024· article· en· W4403020415 on OpenAlexvenueno aff
Venetia Baker, Sarah Mulwa, David Khanyile, Georgia Arnold, Simon Cousens, Cherie Cawood, Isolde Birdthistle

Bibliographic record

VenueJMIR Formative Research · 2024
Typearticle
Languageen
FieldArts and Humanities
TopicMedia Influence and Health
Canadian institutionsnot available
Fundersnot available
KeywordsPreprintObservational studyQualitative researchVisual artsPsychologyComputer scienceArtSociologyWorld Wide WebMedicineAnthropology

Abstract

fetched live from OpenAlex

BACKGROUND: Mass media campaigns, particularly edutainment, are critical in disseminating sexual health information to young people. However, there is limited understanding of the authentic viewing experience or how viewing contexts influence engagement with media campaigns. Reaction videos, a popular format in web-based culture in which users film themselves reacting to television shows, can be adapted as a research method for immediate and unfiltered insights into young people's engagement with edutainment media. OBJECTIVE: We explored how physical and social context influences young people's engagement with MTV Shuga, a dramatic television series based on sexual health and relationships among individuals aged 15 to 25 years. We trialed reaction videos as a novel research method to investigate how young people in South Africa experience the show, including sexual health themes and messages, in their viewing environments. METHODS: In Eastern Cape, in 2020, purposively selected participants aged 18 to 24 years of an evaluation study were invited to take part in further research to video record themselves watching MTV Shuga episodes with their COVID-19 social bubble. To guide the analysis of the visual and audio data, we created a framework to examine the physical setting, group composition, social dynamics, coinciding activities, and viewers' spoken and unspoken reactions to the show. We identified patterns within and across groups to generate themes about the nature and role of viewing contexts. We also reflected on the utility of the method and analytical framework. RESULTS: In total, 8 participants recorded themselves watching MTV Shuga episodes in family or friendship groups. Viewings occurred around a laptop in the home (living room or bedroom) and outside (garden or vehicle). In same-age groups, viewers appeared relaxed, engaging with the content through discussion, comments, empathy, and laughter. Intergenerational groups experienced discomfort, with older relatives' presence causing embarrassment and younger siblings' distractions interrupting the engagement. Scenes featuring physical intimacy prompted some viewers to hide their eyes or leave the room. While some would prefer watching MTV Shuga alone to avoid the self-consciousness experienced in group settings, others valued the social experience and the lively discussions it spurred. This illustrates varied preferences for consuming edutainment and the factors influencing these preferences. CONCLUSIONS: The use of reaction videos for research captured real-time verbal and nonverbal reactions, physical environments, and social dynamics that other methods cannot easily measure. They revealed how group composition, dynamics, settings, and storylines can maximize engagement with MTV Shuga to enhance HIV prevention education. The presence of parents and the camera may alter young people's behavior, limiting the authenticity of their viewing experience. Still, reaction videos offer a unique opportunity to understand audience engagement with media interventions and promote participatory digital research with young people.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.071
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.515
GPT teacher head0.572
Teacher spread0.057 · 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 teacher head, not a consensus.

Study designQualitative
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

Citations2
Published2024
Admission routes1
Has abstractyes

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