Content Quality of YouTube Videos About Metastatic Breast Cancer in Young Women: Systematic Assessment
Bibliographic record
Abstract
BACKGROUND: Young women with metastatic breast cancer (MBC) are part of a digitally connected generation yet are underserved in terms of information needs. YouTube is widely used to find and identify health information. The accessibility of health-related content on social media together with the rare and marginalized experiences of young women with MBC and the digital media practices of younger generations imply a considerable likelihood that young women with MBC will seek information and community on the internet. OBJECTIVE: This study aims to assess the content quality of MBC YouTube videos and to identify themes in the experiences of young women with MBC based on YouTube videos. METHODS: A systematic assessment of MBC YouTube videos using the search term "metastatic breast cancer young" was conducted in August 2021. The search was performed in an incognito browser and with no associated YouTube or Google account. Search results were placed in order from most to least views. Title, date uploaded, length, poster identity, number of likes, and number of comments were collected. Understandability and actionability were assessed using the Patient Education Materials Assessment Tool (PEMAT); information reliability and quality were assessed with DISCERN. Themes, sponsorships, and health care professionals' and patients' narratives were reported. RESULTS: A total of 101 videos were identified. Of these, 78.2% (n=79) included sponsorships. The mean PEMAT scores were 78.8% (SD 15.3%) and 43.1% (SD 45.2%) for understandability and actionability, respectively. The mean DISCERN score was 2.44 (SD 0.7) out of 5. Identified themes included treatment (n=67, 66.3%), family relationship (n=46, 45.5%), and motherhood (n=38, 37.6%). CONCLUSIONS: YouTube videos about young women with MBC are highly understandable but demonstrate moderate rates of actionability, with low reliability and quality scores. Many have a commercial bias. While web-based materials have limitations, their potential to provide patient support is not fully developed. By acknowledging their patients' media habits, health care professionals can further develop a trusting bond with their patients, provide a space for open and honest discussions of web-based materials, and avoid any potential instances of confusion caused by misleading, inaccurate, or false web-based materials.
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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 | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".