“You’re Not Alone”: How Adolescents Share Dysmenorrhea Experiences Through Vlogs
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Many adolescents experience severe pain during menstruation, yet their attempts to receive medical attention to alleviate or manage this pain are often met with dismissal or disbelief. In light of these barriers to care, many adolescents turn to social media to share their experiences with menstruation and pain, as well as hear from other members of their community. In this study, we investigated how adolescents present their experiences with menstruation in vlogs (or “video blogs”). Using critical qualitative methods and a four-column analysis structure, we transcribed and thematically analyzed the audio and video content of 17 YouTube vlogs wherein adolescents described their experiences with menstrual pain. We found that stylistically, the vloggers modulated between a polished documentary style and an intimate storytime style of video production. We additionally found that vloggers spoke about their menstrual pain experiences from three perspectives: as a Patient managing and diagnosing physical symptoms, as a Self considering how the pain affects their life and ambitions, and as a Teacher educating their audience. Considering both the visual and audio data, we discuss how healthcare providers can use these findings to inform their approach to discussing menstrual pain with adolescents. We further discuss possible future directions for research into health story sharing on social media.
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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 | 0.008 | 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 | 0.003 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.004 |
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 it