“It’s just so bloody hard”: recommendations for improving health interventions and maternity support services for disabled women
Bibliographic record
Abstract
PURPOSE: Little is known about the barriers and facilitators to pregnancy, birth and motherhood for disabled women within the New Zealand context. Our study explored this deficit with the aim of improving health care interventions and support for disabled mothers. METHODS: This paper reports on the third phase of a mixed-methods study. The first two phases used semi-structured individual and focus group interviews with disabled women, and health professionals, involved in maternity and postnatal care and has been reported elsewhere. Phase 3 utilised a modified Delphi technique with both groups of participants to seek consensus on the prioritisation of recommendations from the study. This article focuses on the disabled women's recommendations. RESULTS: In all, 20 disabled women took part in the Delphi phase of the study (28% of the cohort from Phase 1). In total, 11 key recommendations were identified by the disabled women, with the top seven discussed in detail here. CONCLUSIONS: Health professionals and health systems could, and arguably should, utilise a matrix of these recommendations to facilitate a review of service responsiveness to disabled women. Implications for Rehabilitation Becoming a mother is a potentially relevant and important rehabilitation issue for women of childbearing age who come into contact with rehabilitation services. Disabled women encounter a range of economic, attitudinal and knowledge barriers in relation to becoming mothers. Centralised sites/sources of information have potential to provide accessible and useful information for disabled women and health professionals.
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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 | 0.037 | 0.070 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.010 | 0.008 |
| Insufficient payload (model declined to judge) | 0.014 | 0.003 |
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".