Evaluation of the quality of life of women with obstetric fistula in Kinshasa
Bibliographic record
Abstract
Background-Obstetric fistula is a major maternal health problem that significantly affects women both physically and mentally. The objective of the study was to assess the quality of life of women with obstetric fistula and to identify the socio-demographic factors. Methods - We used a survey method supported by the McGill Quality of Life Scale, which we administered to a sample of 56 women with obstetric fistula managed at the Fistula Clinic in Kinshasa. Results -In terms of socio-demographic variables, the study sample consisted of 20 women under the age of 30, 15 aged 30-39 and 21 aged 40-49. There are also 6 illiterate women, 20 state graduates, 16 graduates (baccalaureate +3) and 14 bachelor graduates (baccalaureate+5). In terms of marital status, there are 30 married women, 16 divorced women and 10 single women. Finally, there are 7 women who have not had a caesarean section, 40 who have had a caesarean section and 9 who have had two caesareans. The variables age and marital status each influenced one dimension of quality of life (p < 0.05). Women with obstetric fistula show a high level of general unhappiness (Mean = 1.00; SD = 0.00) and a feeling of psychological unhappiness (Mean = 2.40; SD = 1.15). They have a strong sense of physical (Mean = 2.68; SD =0.77), existential (Mean = 2.80; SD =1.06) and social well-being (Mean = 3.10; SD =0.92). Conclusion -obstetric fistula negatively affects the general and psychological wellbeing of women treated at the Fistula Clinic in Kinshasa.
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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 | 0.002 |
| 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 | 0.001 |
| 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".