316 - Urinary incontinence discussions on Instagram: A hashtag analysis of top posts and reels
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
Hypothesis / aims of study Social media use has skyrocketed. With more than half of the world’s population participating in social media, these platforms have become spaces for individuals to seek information, share experiences, and engage in discussions about health-related topics. With over 1.4 billion users, Instagram is one of the most widely used platforms with user-generated content. This platform’s interactive nature may encourage users to share personal experiences, engage with educational resources and explore treatment options while providing a sense of anonymity, enabling individuals to openly discuss stigmatized health conditions. Given Instagram’s role in health communication, this study aimed to explore how UI is represented on Instagram and to understand the role it might play in awareness, education, and discourse surrounding UI. Study design, materials and methods A list of eighteen hashtags was developed with expert consultation and Instagram’s related-search functionalities. The 28 Instagram-generated top posts and reels under each hashtag were analyzed. Posts or reels before 2019 were not included to ensure recency of data, and content not in English was excluded. Data were gathered from July to August, 2024, to minimize algorithmic updates or changes in engagement trends. Quantitative data were gathered for each post, including likes, comments, views (for reels), and the number of followers of the post creator. Details such as media type (static post or video), captions, content description, posting date, creator's username, and authorship background were recorded for analysis. Engagement rates were examined and compared across categories to identify the most popular and engaging type of content by calculating the mean likes in each content category. Posts and reels were categorized into content categories including advertisements (promotional content for products or services), educational content (informative posts including management and treatment tips), personal stories (user-shared experiences about living with or managing UI), humor (jokes or memes about UI), research/academia (including posts about panel discussions and published articles), and unrelated to UI (posts under relevant hashtags, but not addressing UI). Furthermore, authorship categories included healthcare professionals, wellness instructors, businesses and other. Results Categories of content included education (46%, n=207), advertisements (41%, n=182), humour (6%, n=27), personal stories (3%, n=13), research/academia (3%, n=14), and unrelated to UI (1%, n=6). Healthcare professionals contributed 56% of the educational content (116 of 207 posts). The authorship categories included businesses (19%, n=82), healthcare professionals (40%, n=177), wellness instructors (10%, n=45), and other (31%, n=139). The median likes for each category were advertisements (n=22), educational (n=49), humor (n=59), personal stories (n=74), academia/research (n=16), and unrelated to UI (n=335). Interpretation of results Results indicated that Instagram is a likely significant platform for UI-related education. Education and advertisements were the most common categories of content, revealing Instagram’s role in informing and promoting. Engagement data suggested discomfort with UI, an interest in “personal stories”, and the effect of humor in capturing attention. The high engagement with personal stories suggests that users value firsthand experiences, reinforcing the importance of patient narratives in health discussions. Concluding message Instagram is a pertinent tool for disseminating information on UI. Healthcare professionals’ engagement with this platform may add to the credibility of posts, while focusing on engaging content to improve outreach. Given trends, efforts to increase patient narratives and destigmatize UI through social media campaigns could prove highly effective in enhancing public awareness and education. Download: Download high-res image (64KB) Download: Download full-size image Figure 1 . Download: Download high-res image (223KB) Download: Download full-size image Figure 2 . Funding None Clinical Trial No Subjects None
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 it