<p>Health care professionals dealing with hemophilia: insights from the international qualitative study of the HERO initiative</p>
Bibliographic record
Abstract
Background: Assessing the viewpoints of health care professionals concerning their work with chronic patients is a relatively new research topic, widely overlooked in the literature. However, understanding their subjective work experience is highly relevant for identifying problems and perceived resources, enhancing health service organisation, improving relationships or communication with patients, and maintaining well-being. Purpose and method: Qualitative data from the “Haemophilia Experience, Results and Opportunities” Initiative – a research program aimed at investigating the psychosocial aspects of hemophilia – were used to evaluate the experiences of 62 professionals from seven countries around the world. Semi-structured interviews were submitted to thematic analysis of elementary contexts with the aid of T-Lab software. Results: Five dominant themes emerged, identifying the main challenges that professionals have to deal with in their everyday work practice: caring for impaired adult patients; handling policies and stakeholders; providing counselling on diagnosis and reproductive choices; considering the role of family dynamics; coping with adolescent patients. Conclusion: The outcomes of the study provide an opportunity to develop the area of the non-technical skills in the core curriculum of those who work with chronic illnesses by focusing on cross-professional competences and by improving a comprehensive care model for hemophilia patients. Keywords: health care professionals, subjective experience, chronic illness, hemophilia, cross-cultural
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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 | 0.013 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.008 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".