Endometriosis Influencers on Instagram: Who Are They and What Are They Posting?
Bibliographic record
Abstract
STUDY OBJECTIVE: To examine endometriosis-related content on Instagram, a platform increasingly used for health communication, to understand: 1) the identity of Instagram content creators; 2) themes, tones, and emotions evoked from posts; and 3) accuracy of educational information. The relevance of this study lies in its potential to inform healthcare providers on how to better engage with social media to support individuals with endometriosis. DESIGN: This mixed methods cross-sectional observational study was performed on June 6, 2021. Instagram content was collected via two approaches: 1) searching hashtags related to endometriosis from a list of 30 hashtags and analyzing the top 20 and 10 most recent posts and 2) searching endometriosis-related terms under accounts to examine the first 30 accounts retrieved. Posts were categorized into themes and evaluated for tone and emotion, with educational posts also evaluated for accuracy. SETTING: Publicly available data on Instagram. PARTICIPANTS: None. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: The study analyzed 768 Instagram posts and 228 accounts. Of these, 59.9% of posts and 92.1% of accounts contained endometriosis-related content. Most posts (55.4%) and accounts (59.0%) were authored by people with endometriosis. Accounts owned by people with endometriosis were significantly more active and had more followers compared to those who identified as healthcare providers (mean difference of total # of posts = 714.4, p < .001, mean difference of total # of followers = 27,194.7, p < .001, respectively). Social support was the most common theme (67.2%). Many posts had a negative tone (43.7%) and evoked sadness (57.6%). Objective educational posts contained 85.0% accurate information. Allied healthcare providers were most likely to post accurate educational information compared to all other content creators (p < .001). CONCLUSION: Instagram is widely used by people with endometriosis, with posts predominantly centered around social support and personal narratives. Healthcare providers can use this information better understand the experiences of people with endometriosis, and to engage more effectively on Instagram.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".