Psychology of Abortion: A Qualitative Exploration of Women’s Quality of Life after Termination of Pregnancy Service Provision
Bibliographic record
Abstract
Background: Although safe abortion is a human right, some research indicates that abortion can be considered a life event that could trigger an adverse psychological reaction, including mental ill health, particularly in vulnerable women. Unplanned pregnancies and abortions affect women's mental and physical health while increasing psychological risk; hence, measures are needed to improve the quality of life (QoL) of women post termination of pregnancy (ToP). The purpose of this study was to explore the psychological effects of abortion on women provided with this service in Rwanda, and factors surrounding QoL after service provision. Methods: An interpretive description design was used. Focus group discussions were used to hear the voices of 30 women and girls who had sought ToP services. The six steps of interpretive description together with framework analysis guided the analysis. Results: From responses provided by the participants with experience of ToP services five themes and six sub-themes were generated, (1) Ambivalence with mixed feelings and uncertainty, anger, wonder, and frustration; (2) Insecurity and abortion stigma, with judgement and inadequacy; (3) Personalized care with respectful care and dignity and self-reliance; (4) Lack of connection with relationships, coping, and a sense of belonging; (5) Wellness and preferences for care with hope and positive physical health. Conclusion: The lack of psychological support post ToP negatively affects QoL and indicates an opportunity to include a psychological support package in the ToP service provision, which is the predictor of positive mental health to improve QoL in Rwanda.
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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 | 0.008 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".