How reliable are post-mastectomy breast reconstruction videos on YouTube?
Bibliographic record
Abstract
Background Social media platforms are a significant source of information for young women with breast cancer (YWBC) undergoing post-mastectomy breast reconstruction (PMBR). The emphasis on visual storytelling and building community in online spaces renders YouTube to be a common platform for discussions of BR. This study aims to assess the quality of YouTube videos about PMBR, identify themes related to the PMBR experience, and quantify suggestions of BR as an option PM. Methods YouTube was searched incognito with terms "young women breast cancer reconstruction" in 08/2022, in order from most to least viewed. Title, upload date, length, poster identity, number of likes and comments were collected. The Patient Education Materials Assessment Tool for audiovisual materials (PEMAT A/V) was used to evaluate understandability and actionability. DISCERN assessed quality and reliability. Presence of sponsorship, intended audience, patient and healthcare professional narratives, and suggestions of PMBR were collected. Reviewers noted whether PMBR was shown and how. Themes were collected inductively and deductively for thematic analysis. Results 193 videos were identified. Mean video length was 14.6 min (SD 20.0 min). 87.1 % included sponsorships. 95.9 % of videos were posted by an organization. 60.6 % were information-based; 45.6 % experience-based. Mean PEMAT scores for understandability and actionability were 71.3 % (SD 13.4) and 35.7 % (SD 41.8), respectively. Mean DISCERN was 2.6/5 (SD 1.2). Patient narrative was present in 52.6 % and healthcare professionals' in 68.4 %. PMBR was visually presented 22.8 % of the time. 13.5 % of videos explicitly recommended PMBR. 2.6 % explicitly discouraged it. Patients (77.7 %) represented the majority of the intended audience. Most common deductively identified themes included treatment (87.1 %), family relationship (17.1 %), motherhood (15.5 %), fertility (11.9 %). Inductively identified subthemes included differentiating between various options for PMBR surgery, BRCA genetic testing, psychosocial effects of breast cancer and PMBR, and recovery from surgery. Conclusion YouTube is a platform wherein various PMBR options are widely discussed and explained. PMBR videos are highly understandable but have moderate levels of actionability, quality, and reliability. Videos are highly sponsored, demonstrating significant institutional bias. Themes are overwhelmingly treatment and surgery-based. Personal themes were present but not dominant.
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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 | 0.001 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.003 |
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".