Assessing Health Information Seeking Behaviors Among Targeted Social Media Users Using an Infotainment Video About a Cancer Clinical Trial: Population-Based Descriptive Study
Bibliographic record
Abstract
BACKGROUND: Lack of information, awareness, and misconceptions about clinical trials are major barriers to cancer clinical trial participation. Digital and social media are dominant sources of health information and offer optimal opportunities to improve public medical awareness and education by providing accurate and trust-worthy sources of health information from reliable sources. Infotainment, material intended to both entertain and inform, is an effective strategy for engaging and educating audiences that can be easily disseminated using social media and may be a novel way to improve awareness of and recruitment in clinical trials. OBJECTIVE: The purpose of this study was to evaluate whether an infotainment video promoting a clinical trial, disseminated using social media, could drive health information seeking behaviors. METHODS: As part of a video series, we created an infotainment video focused on promotion of a specific cancer clinical trial. We instituted a dissemination and marketing process on Facebook to measure video engagement and health information seeking behaviors among targeted audiences who expressed interest in breast cancer research and organizations. To evaluate video engagement, we measured reach, retention, outbound clicks, and outbound click-through rate. Frequencies and descriptive statistics were used to summarize each measure. RESULTS: The video substantially increased health information seeking behavior by increasing viewership from 1 visitor one month prior to launch to 414 outbound clicks from the video to the clinical trial webpage during the 21-day social media campaign period. CONCLUSIONS: Our study shows that digital and social media tools can be tailored for specific target audiences, are scalable, and can be disseminated at low cost, making it an accessible educational, recruitment, and retention strategy focused on improving awareness of clinical trials. CLINICALTRIAL: ClinicalTrials.gov NCT03418961.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".