Examining obstetric interventions and respectful maternity care in Hungary: Do informal payments for continuity of care link to quality?
Bibliographic record
Abstract
BACKGROUND: In Hungary, 60% of women pay informally to secure continuity with a "chosen" provider for prenatal care and birth. It is unclear if paying informally influences quality of maternity care. This study examined associations between incentivized continuity care models and obstetric procedures and respectful care. METHODS: This is a cross-sectional survey of a representative sample of Hungarian women (N = 589) in 2014. We calculated descriptive statistics comparing experiences among women who paid informally for continuity with a chosen provider with those who received care in the public health system. After adjusting for social and clinical covariates, we used logistic regression to estimate the odds of obstetric procedures and disrespectful care and linear regression to estimate the level of autonomy (MADM scale). RESULTS: Of women in our sample, 317 (53%) saw a chosen doctor, 68 (11%) a chosen midwife, and 204 (33%) had care in the public system. Women who paid an obstetrician informally had the highest rates of cesarean (49.5%), induction of labor (31.2%), and epidural (15%), and reported lower rates of disrespectful care (41%) compared to public care (64%). Paying for continuity with an obstetrician significantly predicted cesarean (aOR 1.61 [95%CI 1.00-2.58]), episiotomy (2.64, [1.39-5.03]), and epidural (3.15 [1.07-9.34]), but not induction of labor (1.59 [0.99-2.57]). Informal payment continuity models predicted increased autonomy scores (doctor: 3.97, 95% CI 2.39-5.55; midwife: 7.37, 95% CI 5.36-9.34) and reduced odds of disrespectful care. There were no differences in the prevalence of scheduled cesareans or inductions performed without a medical indication. CONCLUSIONS: Continuity models secured with informal payments significantly increased both women's experience of respectful care and rates of obstetric procedures. Intervention rates exceed global standards, and women do not choose elective procedures to preserve continuity.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".