The Women’S Perceptions About Unwanted Pregnancy: A Qualitative Study in Iran
Bibliographic record
Abstract
BACKGROUND: Unwanted pregnancy has affected different aspects of our life. Researchers point out if a child's birth is unwanted, an increase in maternal issues can be observed. The aim of this study was to describe the women's viewpoints regarding unwanted pregnancy. METHOD: This qualitative study using content analysis was employed in Shiraz University in 2013-2014. 20 women with unwanted pregnancy were chosen using purposeful sampling. Data were gathered through semi-structured interviews and trustworthiness of them was evaluated. RESULTS: Findings of this study, according to the participants' experience, revealed maternal emotions like embarrassment for getting pregnant, mother's own negative affection, concerns about missing family and other children, and terminating the pregnancy through illegal abortion, the husband's disagreement about the termination, blaming themselves for thinking about abortion or illegal abortion, and concern about their guilt feeling. Another finding was family problems like husband's behavior and his negative outlook towards his child and fetus. The next category belonged to anxiety about the future of their child, including economic, social and relational problems, and suppression of the children's logical expectations. The last finding was the lack of maternal emotional support. CONCLUSIONS: Unwanted pregnancy's effects on the mothers and infants' health are considerable. A closer observation by family and health care providers for unwanted pregnancies and its results is recommended; therefore, they should be taken care of as high risk pregnancies, requiring family support.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".