A Framework for Describing the Influence of Service Organisation and Delivery on Participation in Fetal Anomaly Screening in England
Bibliographic record
Abstract
Objective. The aim of this research was to explore the influence of service organisation and delivery on providers and users’ interactions and decision-making in the context of Down’s syndrome screening.Methods. A qualitative descriptive study involving online interviews conducted with a purposive sample of 34 community midwives, 35 pregnant women, and 15 partners from two maternity services in different health districts in England. Data were analysed using a combination of grounded theory principles and content analysis and a framework was developed.Results. The main emerging concepts were organisational constraints, power, routinisation, and tensions. Providers were concerned about being time-limited that encouraged routine, minimal information-giving and lacked skills to check users’ understanding. Users reported their participation was influenced by providers’ attitudes, the ambience of the environment, asymmetric power relations, and the offer and perception of screening as a routine test. Discordance between the national programme’s policy of nondirective informed choice and providers’ actions of recommending and arranging screening appointments was unexpected. Additionally, providers and users differing perceptions of emotional effects of information, beliefs, and expectations created tensions within them, between them, and in the antenatal environment.Conclusions. A move towards a social model of care may be beneficial to empower service users and create less tension for providers and users.
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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 | 0.025 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.008 | 0.024 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.003 |
| 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".