'A morass of considerations': exploring attitudes towards ethnicity-based haemoglobinopathy-carrier screening in primary care
Bibliographic record
Abstract
BACKGROUND: The Netherlands does not have a national haemoglobinopathy (HbP)-carrier screening programme aimed at facilitating informed reproductive choice. HbP-carrier testing for those at risk is at best offered on the basis of anaemia. Registration of ethnicity has proved controversial and may complicate the introduction of a screening programme if based on ethnicity. However, other factors may also play a role. OBJECTIVE: To explore perceived barriers and attitudes among GPs and midwives regarding the registration of ethnicity and ethnicity-based HbP-carrier screening. METHODS: Six focus groups in Dutch primary care, with a total of 37 GPs (n = 9) and midwives (n = 28) were conducted, transcribed and content analysed using Atlas-ti. RESULTS: Both GPs and midwives struggled with correctly identifying ethnicities at risk for HbP. Ethical concerns regarding privacy seemed to originate from World War II experiences, when ethnic and religious registration facilitated deportation of Jewish citizens, coupled with the political climate at the time focus groups were held. Some respondents thought the ethnicity question might undermine the relationship with their clients. Software programmes prevented GPs from registering ethnicity of patients at risk. Financial implications for patients were also a concern. Despite this, respondents seemed positive about screening and were familiar with identifying ethnicity and used this for individual patient care. CONCLUSIONS: Although health professionals are generally positive about screening, ethical, financial and practical issues surrounding ethnicity-based HbP-carrier screening need to be clarified before introducing such a programme. Primary care professionals can be targeted through professional organizations but they need national policy support.
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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 | 0.010 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".