Reasons for high prevalence of contraceptive withdrawal in Tehran, Iran
Bibliographic record
Abstract
This study explores reasons for withdrawal use that is highly prevalent in Iran. A face-to-face semi-structured survey questionnaire was designed and 79 married women aged 15-49, who were only using withdrawal when attending five primary healthcare centers in Tehran during September-October 2021 were interviewed. Results showed that withdrawal mostly was chosen by the couple (67%), and partly by the woman alone (19%) or by the husband alone (14%). Participants evaluated withdrawal positively that has no side effect and cost, is easy to use and accessible, and increases sexual pleasure and intimacy. Most women agreed that husbands use withdrawal to protect their wife's health (76%). Women obtained contraceptive information primarily from gynecologists (42%), the internet (21%), midwives in public health centers (19%), and social networks (18%). "Side effects of modern methods" (37%), "fear of side effects" (16%), and "reduction in sexual pleasure" (14%) were the major reasons reported for using withdrawal. While 'side effects' was given mostly by women who alone or with their husband chose withdrawal (52%, 38%), 'reduction in sexual pleasure' and 'fear of side effects' were mostly reported by women whose husband was the sole decision maker in choosing withdrawal (28%, 25%). The 'fear of side effects' was reported mostly by women who had lower education (21%), used the internet for contraceptive information (23%), and whose husband alone chose withdrawal (25%). Cost of modern methods was a trivial reason for using withdrawal. Most withdrawal users (75%) would not switch to modern methods even if they were freely accessible. More educated women and their husbands would be less likely to switch to modern methods even they were provided freely (OR 0.28, CI 0.10-0.80; OR 0.20, CI 0.07-0.59). However, women who were using modern methods before, and those who alone chose withdrawal would be more likely to switch to modern methods (OR 6.4, CI 2.0-20.2; OR 3.4, CI 1.1-11.2). Access to regular contraceptive counselling and public health campaigns could help women to deal with fears of side effects of modern methods, learn their proper use, and to receive education on how to use withdrawal more effectively to avoid unintended pregnancies.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".