Preferences of Australian healthcare providers regarding education on long-term health after hypertensive disorders of pregnancy: a qualitative study
Bibliographic record
Abstract
OBJECTIVES: To explore Australian healthcare providers' (HCPs') preferred content, format and access to education regarding long-term health after hypertensive disorder of pregnancy (HDP), in order to guide the development of education programmes. DESIGN AND SETTING: A qualitative study using a framework analysis was undertaken. Registered HCP who were practising in Australia and previously completed a survey about long-term health after HDP were invited to participate. PARTICIPANTS: Twenty HCP were interviewed, including midwives, specialist obstetrician/gynaecologists, general practitioners with a diploma in obstetrics and gynaecology, and cardiologists. PRIMARY AND SECONDARY OUTCOME MEASURES: Exploration of preferred content, format and distribution of educational material post-HDP. RESULTS: Twenty HCP were interviewed in April to May 2020. Four main categories were identified. 'Obtaining evidence-based information for own learning' addressing own learning with preference for multi-disciplinary education, preferably endorsed or facilitated by professional organisations. 'Optimising the referral process from hospital to community health services' was about the need for structured long-term follow-up to transition from hospital to community health and align with HDP guidelines. 'Facilitating women's health literacy' addressed the need for evidence-based, print or web-based material to assist risk discussions with women. 'Seizing educational opportunities' addressed the responsibility of all HCP to identify education opportunities to initiate key health discussions with women. CONCLUSIONS: HCP provided ideas on content, format and access of education regarding long-term health post-HDP within the parameters of the Australian healthcare context. This evidence will guide educational developments for HCP on post-HDP health to ensure they can better care for women and families.
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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 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| 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".