Social Media in Communicating Health Information: An Analysis of Facebook Groups Related to Hypertension
Why this work is in the frame
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Bibliographic record
Abstract
INTRODUCTION: We studied Facebook groups related to hypertension to characterize their objectives, subject matter, member sizes, geographical boundaries, level of activity, and user-generated content. METHODS: We performed a systematic search among open Facebook groups using the keywords "hypertension," "high blood pressure," "raised blood pressure," and "blood pressure." We extracted relevant data from each group's content and developed a coding and categorizing scheme for the whole data set. Stepwise logistic regression was used to explore factors independently associated with each group's level of activity. RESULTS: We found 187 hypertension-related Facebook groups containing 8,966 members. The main objective of most (59.9%) Facebook groups was to create hypertension awareness, and 11.2% were created primarily to support patients and caregivers. Among the top-displayed, most recent posts (n = 164), 21.3% were focused on product or service promotion, whereas one-fifth of posts were related to hypertension-awareness information. Each Facebook group's level of activity was independently associated with group size (adjusted odds ratio [AOR], 1.02; 95% confidence interval [CI], 1.01-1.03), presence of "likes" on the most recent wall post (AOR, 3.55, 95% CI, 1.41-8.92), and presence of attached files on the group wall (AOR, 5.01, 95% CI, 1.25-20.1). CONCLUSION: The primary objective of most of the hypertension-related Facebook groups observed in this study was awareness creation. Compared with the whole Facebook community, the total number of hypertension-related Facebook groups and their users was small and the groups were less active.
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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 | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| 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