Social media use as a predictor of higher body mass index in persons living with HIV
Bibliographic record
Abstract
Social media tools have been touted as an approach to bring more democratic communication to health care. We conducted a multi-site cross-sectional study among persons living with HIV (PLWH) to desrcibe technology use among PLWH in the US and the association between social media use and body-mass index (BMI). Our primary predictor variable was social media use. Our primary outcome was BMI measured through height and weight. Descriptive statistics were used to describe the demographic profiles of the study participants and linear regression models were used to analyze associations between the outcome and predictor variables controlling for demographic characteristics. Study participants (N = 606) across 6 study sites in the United States were predominately 50–74 years old (67%). Thirty-three percent of study participants had a normal weight (BMI 18.5–25), 33% were overweight (BMI 25–30), and 32% were obese (BMI > 30). Participants used several social media sites with Facebook (45.6%) predominating. Social media use was associated with higher BMI in study participants (p < .001) and this effect persisted, although not as strongly, when limiting the analysis to those who only those who used Facebook (p = .03). Further consideration of social factors that can be ameliorated to improve health outcomes is timely and needed.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".