I Would Never Take Preventive Medication! Perspectives and Information Needs of People Who Underwent Predictive Tests for Rheumatoid Arthritis
Bibliographic record
Abstract
OBJECTIVE: Little is known about the experiences, values, and needs of people without arthritis who undergo predictive biomarker testing for the development of rheumatoid arthritis (RA). Our study aimed to explore the perspectives of these individuals and describe their information needs. METHODS: A qualitative, multicenter interview study with a thematic analysis was conducted in Austria, Germany and the UK. Individuals were interviewed who underwent predictive biomarker testing for RA and had a positive test result but no diagnosis of any inflammatory joint disease. Participants included patients with arthralgia and asymptomatic individuals. Information and education needs were developed from the qualitative codes and themes using the Arthritis Educational Needs Assessment Tool as a frame of reference. RESULTS: Thematic saturation was reached in 34 individuals (76% female, 24 [71%] with arthralgia, and 10 [29%] asymptomatic individuals). Thirty-seven codes were summarized into 4 themes: 1) decision-making around whether to undergo initial predictive testing, 2) willingness to consider further predictive tests, and/or 3) preventive interventions, including medication, and 4) varying reactions after receiving a positive test result. Individuals with arthralgia were more likely to be willing to take preventive action, undergo further testing, and experience psychological distress than asymptomatic individuals. All participants expressed the need for tailored, patient-understandable information. CONCLUSION: Individuals at risk of RA are currently the subjects of research aimed at developing better predictive strategies and preventive approaches. Their perceptions and needs should be addressed to inform the future development of interventions combined with education.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 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 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".