Facebook Support Groups in Systemic Lupus Erythematosus: A Content Analysis
Bibliographic record
Abstract
Background: There are many disease-specific groups on Facebook, which offer a convenient way to exchange information and support. This may be particularly helpful for patients affected with uncommon diseases, such as systemic lupus erythematosus (SLE). The content of SLE-related Facebook support groups, however, has yet to be explored and evaluated. Objective: The objective of this study was to analyze the content of Facebook support groups related to SLE, specifically evaluating the nature of the information shared and the pattern of use. Methods: Two independent investigators searched for the term “lupus” on Facebook’s native search function, from 10/08/2011 to 01/04/2012. Groups related to SLE, operating in English and/or French, and publicly accessible, were included for analysis. Information regarding the purpose of the group, its administrator, as well as the number and type of user-generated contributions were extracted. The content of support groups were then analyzed using a previously developed coding scheme. Results: We found 173 SLE groups on Facebook containing a total of 42,240 members. Roughly half (53%) of the groups were created for support, while 33% were for disease awareness, and 14% for fundraising. The largest group included 30,972 members and was intended for raising awareness. 3,469 members were found in support groups, representing 8% of the overall membership (but 31% of the overall membership when excluding the largest group). The median number of members was 11 (interquartile range, IQR, 39). The most frequent locations of support groups were the United States (44%), Canada (10%), and United Kingdom (10%). In support groups, the total number of user-generated contributions was 1932, including wall posts (54%), comments (32%), discussion posts (10%), and discussion threads (4%), while the median number of user-generated contributions was 5 (IQR 20). Conclusions: Support groups for SLE patients represent a substantial proportion of Facebook groups dedicated to SLE. Given their convenience, accessibility, and potential audience, Facebook support groups might represent an efficient way to reach patients with SLE who are internet users and improve their health-related quality of life. Further research is needed to evaluate the effects of this type of support groups on patients with SLE. Keywords: Systemic lupus erythematosus, lupus, support groups, Facebook. Read more →
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How this classification was reachedexpand
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".