Interactive Narrative–Based Digital Health Interventions for Vaccine Communication: Protocol for a Scoping Review
Bibliographic record
Abstract
BACKGROUND: Interactive narrative-based digital health interventions hold promise for effectively addressing the complex determinants of vaccine hesitancy and promoting effective communication across a wide range of settings and vaccine types. Synthesizing evidence related to the implementation and evaluation of these interventions could offer valuable perspectives for shaping future strategies in vaccine communication. Prior systematic and scoping reviews have examined narrative-based vaccine communication interventions but not the inclusion of interactivity in such interventions. OBJECTIVE: The overall objective of the scoping review is to summarize the evidence on the use of interactive narrative-based digital health interventions for vaccine communication. Specific research questions focus on describing the use of interactive narrative-based digital health interventions (RQ1), describing evaluations of the impact of interactive narrative-based digital health interventions on promoting vaccine uptake (RQ2), and factors associated with their implementation (RQ3). METHODS: A detailed search string will be used to search the following databases for records that are relevant to the review questions: PubMed, Embase, Scopus, Web of Science, CINAHL, and PsycINFO. Two reviewers will independently screen the titles and abstracts of identified records against the predefined eligibility criteria. Subsequently, eligible records will undergo comprehensive full-text screening by 2 independent reviewers to assess their relevance to review questions. A data charting tool will be developed and used to extract relevant information from the included articles. The extracted information will be analyzed following the review questions and presented as a narrative summary. Tabular or graphical representations will be used to display review findings, as relevant. RESULTS: Public health informationists were consulted to develop the detailed search strategy. The final search string comprised terms related to narrative communication, digital health, and vaccines. The search string was customized to each proposed publication database and implemented on April 18, 2023. A total of 4474 unique records were identified using the search strategy and imported into the Covidence (Veritas Health Innovation Ltd) review management software for title and abstract screening. Title and abstract screening of identified records are ongoing as of December 29, 2023. CONCLUSIONS: To our knowledge, this will be the first scoping review to investigate the features of interactive narrative-based digital health interventions and their role in vaccine communication. The goal of this study is to provide a comprehensive overview of the current research landscape and identify prevailing gaps in knowledge. The findings will provide insights for future research and development of novel applications of interactive narrative-based digital health vaccine communication interventions. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/51137.
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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 | 0.094 | 0.088 |
| Meta-epidemiology (narrow) | 0.005 | 0.006 |
| Meta-epidemiology (broad) | 0.010 | 0.012 |
| Bibliometrics | 0.015 | 0.013 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.005 | 0.008 |
| Research integrity | 0.009 | 0.008 |
| Insufficient payload (model declined to judge) | 0.125 | 0.028 |
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".