Women's decision‐making autonomy and utilization of antenatal, natal and post‐natal healthcare services: Insights from Tajikistan's national surveys
Bibliographic record
Abstract
BACKGROUND: The purpose of this article is to investigate the link between women's autonomy and their utilization of antenatal, natal and post-natal healthcare services in Tajikistan. Previous studies focused only on a single dimension of such services, for instance, utilization of antenatal care. By contrast, we explore antenatal, natal and post-natal healthcare services utilization using the number of indicator for each of the dimensions. METHODS: Data come from two national surveys that were conducted in 2012 and 2017. The target population is women of reproductive age (16-49) who were married or cohabitating with a partner (N = 7540). Several regression models were estimated to quantify association between women's autonomy and the utilization. RESULTS: Lack of women's autonomy is associated with a lower probability of: (a) having had at least four antenatal check-ups during pregnancy, (b) beginning first antenatal check-up early, (c) delivering in a healthcare facility, (d) having the skilled attendance during pregnancy, (e) having a mother post-delivery check-up, and (f) having a child post-delivery check-up. The size effect of women's autonomy is stronger than that of well-developed precursors of utilization such as poverty and mothers' education. CONCLUSION: Women autonomy should be improved to achieve higher rates of child and maternal healthcare utilization. Studies of maternal and child healthcare utilization should control explicitly for women's autonomy.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".