Digital Media Coverage of Respiratory Syncytial Virus-Related News in India: Mixed Methods Content Analysis of Disease Burden and Intervention
Bibliographic record
Abstract
Background: Respiratory syncytial virus (RSV) is a leading cause of lower respiratory tract infections in children younger than 5 years of age. Given the high morbidity and mortality associated with RSV in India, the introduction of a vaccine against RSV will potentially reduce the disease's burden. However, vaccine acceptance is influenced by public perception, which is shaped by information disseminated through media sources. This study aims to explore the landscape of RSV-related news coverage in India's digital media. Objective: This study aims to conduct a comprehensive content analysis to explore the landscape of RSV-related news coverage in India's digital media. Methods: Media content analysis was retrospectively conducted by a digital search for all related news pieces in the trustworthy brands of 4 trusted newspapers (Hindustan Times, The Hindu, The Indian Express, and The Times of India) and 3 news channel websites (India Today, NDTV news, and News 18), between November 1, 2022, and October 31, 2023. A total of 58 news pieces were retrieved using selected keywords, with inclusion criteria encompassing English-language news pieces with RSV-specific content. Two reviewers compiled, coded, and analyzed the content. Quantitative data were analyzed descriptively, while qualitative content analysis assessed the emotional tone and sentiment of the pieces. Results: The findings revealed significant digital media coverage on RSV infection and the potential vaccines. The majority of news pieces (53/58, 91%) discussed RSV signs and symptoms, with 64% (37/58) addressing the disease severity and 36% (21/58) highlighting its seasonal surge. However, only 5% (3/58) focused on diagnostic aids. Additionally, 41% (24/58) of news pieces discussed RSV in the context of COVID-19. Regarding the vaccine, 29% (17/58) of news pieces mentioned it, with 26% (15/58) highlighting manufacturers such as Pfizer and GlaxoSmithKline (GSK). Positive sentiment was found in 35% (20/58) of news pieces, while 43% (25/58) exhibited negative sentiment, often related to the disease burden and severity. Emotional tone analysis revealed that 74% (43/58) of news pieces contained emotional elements, with 58% (25/43) expressing negative emotions (eg, concern and anxiety), particularly about hospitalizations and deaths. In contrast, a positive tone was emulated in the frequent mentions of the RSV vaccines as safe, effective, and approved. Conclusions: The analysis revealed significant coverage of RSV-related news in India's digital media, with a focus on disease severity and hospitalizations. While positive sentiment was expressed in coverage of the RSV vaccine, negative sentiments dominated discussions on the disease burden. However, considering the limited number of news pieces, the study highlights the need for improved media coverage to raise awareness about the disease and its preventive strategies. Further research should explore the implications of the overlap between RSV and COVID-19 in media coverage and the limited focus on RSV diagnostics, with a focus on understanding how these factors impact public health outcomes.
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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 | 0.004 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".