Storytelling as a communication tool for health consumers: development of an intervention for parents of children with croup. Stories to communicate health information
Bibliographic record
Abstract
BACKGROUND: Stories may be an effective tool to communicate with and influence patients because of their ability to engage the reader. The objective of this paper is to describe the development of a story-based intervention for delivery of health evidence to parents of children with croup for use in a randomized controlled trial. METHODS: A creative writer interviewed parents of children with croup presenting to the pediatric emergency department (ED) and drafted stories. We revised the stories based on written participant feedback and edited the stories to incorporate research evidence and health information. An illustrator and graphic designer developed story booklets which were evaluated through focus groups. RESULTS: Ten participants provided feedback on the five stories drafted by the creative writer. Participants liked the concept but found the writing overly sophisticated and wanted more character development and more medical/health information. Participants highlighted specific story content that they liked and disliked. The revised stories were evaluated through focus groups involving eight individuals. Feedback was generally positive; one participant questioned the associated costs. Participants liked the graphics and layout; felt that they could identify with the stories; and felt that it was easier to get information compared to a standard medical information sheet. Participants provided feedback on the story content, errors and inconsistencies, and preferences of writing style and booklet format. Feedback on how to package the stories was provided by attendees at a national meeting of pediatric emergency researchers. CONCLUSIONS: Several challenges arose during the development of the stories including: staying true to the story versus being evidence based; addressing the use of the internet by consumers as a source of health information; balancing the need to be comprehensive and widely applicable while being succinct; considerations such as story length, reading level, narrative mode, representation of different demographics and illness experiences, graphics and layout. The process was greatly informed by feedback from the end-user group. This allowed us to shape our products to ensure accuracy, credibility, and relevance. Our experience is valuable for further work in the area of stories and narratives, as well as more broadly for identifying and developing communication strategies for healthcare consumers.
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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 | 0.008 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".