Needs and challenges among physicians and researchers in thrombosis and hemostasis: Results from an international study
Bibliographic record
Abstract
BACKGROUND: Specialty societies, such as the International Society on Thrombosis and Haemostasis (ISTH), are a key source of support for clinical and scientific communities, through the provision of educational activities, tools, and resources to support evidence-based care and high-quality, relevant basic science and clinical research. OBJECTIVE: The aim of this study was to identify areas where the thrombosis and hemostasis (T&H) community is facing challenges and could benefit from the support of ISTH. METHODS: A 3-phase, mixed-methods study consisting of semistructured individual interviews (phase 1), an online survey (phase 2), and discussion groups (phase 3) was conducted on the challenges experienced by the T&H community. Participants included physicians, clinical and basic science researchers, residents, fellows, students, and industry representatives. Qualitative data were analyzed using thematic analysis. Quantitative data were analyzed using frequency tables and chi-squares. RESULTS: The study included 468 participants in interviews (n = 45), surveys (n = 404), and discussion groups (n = 19). Nine themes emerged that describe areas where the T&H community may benefit from additional support. Three areas were related to diagnosis and testing: thrombosis risk assessment, genetic testing, and diagnosis of von Willebrand disease (VWD). Another 3 were related to treatment decision making: use of anticoagulants with certain patients, preventive treatments in bleeding disorders, and VWD treatment. The remaining 3 were related to research: collaboration with/among researchers, collaboration between teams to collect data from human subjects, and promotion of basic science research. CONCLUSIONS: This study provides a comprehensive picture of priorities within the T&H community, which should inform the ISTH in its future interventions, including educational offerings and networking opportunities.
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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 | 0.049 | 0.075 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.009 | 0.006 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".