Treatment decisions: insights from people with asthma or COPD and their healthcare providers on disease and treatment decisions
Bibliographic record
Abstract
Ruth Tal-Singer1, Miguel Román-Rodríguez2,3, Ilona McMullan4, Michelle Warner4, Christopher Compton4, Jean Orlow5, MeiLan K Han6 1Global Allergy and Airways Patient Platform, Vienna, Austria; 2Centro de Salud Dra. Teresa Pique, Mallorca, Spain; 3Instituto de Investigación Sanitaria de las Islas Baleares (IdISBa), Mallorca, Spain; 4GSK, London, UK; 5COPD patient and COPD Foundation community member; 6University of Michigan School of Medicine, Ann Arbor, MI, USA Plain Language Summary What is this summary about? This research gathered insights on the physical, mental, and emotional impact of asthma or chronic obstructive pulmonary disease (COPD) on people. It also looked at how these lung diseases impacted diagnosis, disease management, and health outcomes. What are the key takeaways? In our research, we found that patients often delay seeking medical help until symptoms impact their daily lives including, for example, issues with sleep, exercise, work, relationships, and mental health. A need for better understanding of how to correctly use medications was observed. In this research, patients wanted to know how long it takes to feel improvements after taking a medication. If they have other medical conditions, patients and caregivers want to know about possible side effects. They often used social media or consulted their healthcare providers (HCPs) to improve their understanding and empower themselves in managing their health. What were the main conclusions reported by the researchers? The research concludes that improved access to reliable, trusted information couldimprove patients’ understanding of their disease. This understanding could also improve patients’ communication and partnership with HCPs, helping make informed treatment decisions (shared decision making). What is the purpose of this plain language summary? The purpose of this plain language summary is to help you understand the findings from recent research. The results of this research may differ from those of other studies. HCPs should make treatment decisions based on all available evidence, not on the results of a single study. This is an abstract of the Plain Language Summary of Publication article. To read the full Plain Language Summary of this article, click here to view the PDF. Link to original article here
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.050 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".