YouTube videos as health decision aids for the public: An integrative review.
Bibliographic record
Abstract
OBJECTIVE: To determine the potential value of YouTube videos as health decision aids for the public. METHODS: An integrative review was performed to explore 3 questions: 1) What is the validity of health-related YouTube videos created for the public? 2) Are YouTube videos an effective tool for supporting the public in decision making regarding the treatment, prevention, and diagnosis of disease? 3) How can health professionals ensure their videos will be readily accessible to those searching online for health-related information? Systematic searches of PubMed, CINAHL, and Web of Science were conducted. The returns were screened using inclusion and exclusion criteria and studies found were critically appraised. RESULTS: Fifty-eight studies assessed the validity of videos on given topics and 9 studies examined the effectiveness of videos in supporting decision making. These studies demonstrated that the majority of health-related YouTube videos lack validity. However, evidence-based videos do exist and have the potential to be an effective instrument in supporting the public in making health decisions. Ten studies examined ways to increase the accessibility of such videos to the public. DISCUSSION: Creators of evidence-based videos must take into consideration content and content-agnostic factors to improve the accessibility of their videos to searchers. Recommendations to support creators in making their evidence-based health videos readily accessible to the public are provided. CONCLUSIONS: By exploiting appropriate content and content-agnostic factors, video creators can ensure that valid health information is readily accessible to information seekers.
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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 | 0.012 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".