Health information use by patients with systemic lupus erythematosus (SLE) pre and during the COVID-19 pandemic
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
OBJECTIVE: We conducted an international survey of patients with SLE to assess their access, preference and trust in various health information sources pre-COVID-19 and during the COVID-19 pandemic. METHODS: Patients with SLE were recruited from 18 observational cohorts, and patients self-reporting SLE were recruited through five advocacy organisations. Respondents completed an online survey from June 2020 to December 2021 regarding the sources of health information they accessed in the 12 months preceding (pre-11 March 2020) and during (post-11 March 2020) the pandemic. Multivariable logistic regressions assessed factors associated with accessing news and social media post-11 March 2020, and self-reporting negative impacts from health information accessed through these sources. RESULTS: Surveys were completed by 2111 respondents; 92.8% were female, 76.6% had postsecondary education, mean (SD) age was 48.8 (14.0) years. Lupus specialists and family physicians were the most preferred sources pre-11 March 2020 and post-11 March 2020, yet were accessed less frequently (specialists: 78.5% pre vs 70.2% post, difference -8.3%, 95% CI -10.2% to -6.5%; family physicians: 57.1% pre vs 50.0% post, difference -7.1%, 95% CI -9.2% to -5.0%), while news (53.2% pre vs 62.1% post, difference 8.9%, 95% CI 6.7% to 11.0%) and social media (38.2% pre vs 40.6% post, difference 2.4%, 95% CI 0.7% to 4.2%) were accessed more frequently post-11 March 2020 vs pre-11 March 2020. 17.2% of respondents reported negative impacts from information accessed through news/social media. Those outside Canada, older respondents or with postsecondary education were more likely to access news media. Those in Asia, Latin America or younger respondents were more likely to access social media. Those in Asia, older respondents, males or with postsecondary education in Canada, Asia or the USA were less likely to be negatively impacted. CONCLUSIONS: Physicians, the most preferred and trusted sources, were accessed less frequently, while news and social media, less trusted sources, were accessed more frequently post-11 March 2020 vs pre-11 March 2020. Increasing accessibility to physicians, in person and virtually, may help reduce the consequences of accessing misinformation/disinformation.
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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