Young women’s social support networks during pregnancy in Soweto, South Africa
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Although studies from high-income countries have examined social support during pregnancy, it remains unclear what type of support is received by expectant mothers from low- and middle-income country settings. AIM: To explore young women's social support networks during pregnancy in Soweto, South Africa. SETTING: This study was undertaken in an academic hospital based in the Southwestern Townships (Soweto), Johannesburg, in Gauteng province, South Africa. METHODS: An exploratory descriptive qualitative approach was employed. Eighteen (18) young pregnant women were recruited using a purposive sampling approach. In-depth interviews were conducted, and data were analysed using inductive thematic analysis. RESULTS: Analysis of the data resulted in the development of two superordinate themes namely; (1) relationships during pregnancy and (2) network involvement. Involvement of the various social networks contributed greatly to the young women having a greater sense of potential parental efficacy and increased acceptance of their pregnancies. Pregnant women who receive sufficient social support from immediate networks have increased potential to embrace and give attention to pregnancy-related changes. CONCLUSION: Focusing on less-examined characteristics that could enhance pregnant women's health could help in the reduction of deaths that arise because of pregnancy complications and contribute in globally accelerating increased accessibility to adequate reproductive health.Contribution: This study's findings emphasise the necessity for policymakers and healthcare providers to educate the broader community about the importance of partner, family and peer support to minimise risks that may affect pregnancy care and wellbeing of mothers.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it