Disrespectful care towards mothers giving birth at selected hospital in Kigali/Rwanda
Bibliographic record
Abstract
BACKGROUND: Over the past decade, global public health has increasingly focused on studying the mistreatment towards women during facility-based childbirth. However, in Rwanda, research on disrespectful and abusive care experienced by mothers during childbirth remains limited. This study aimed to assess disrespect and abuse experienced by women during their recent childbirth at a selected district hospital in Kigali, Rwanda. METHODS: We conducted a cross-sectional study in a selected urban district hospital in Kigali, Rwanda. We employed systematic random sampling to select 246 mothers who recently delivered at the study site and had been discharged from the hospital but were still on the premises. We utilised descriptive statistics and calculated a summation score of nine items of disrespect and abuse to determine our outcome of interest. Subsequently, we dichotomised the outcome. Additionally, we employed chi-square analysis and logistic regression to identify predictors of disrespect and abuse. RESULTS: The prevalence of disrespect and abuse was 67.48%. During the follow-up questions, 28.86% of participants reporting experiencing disrespect and abuse once and 32.52% reporting experiencing it two to eight times. Participants experienced disrespect and abuse between one and eight times. The most prevalent forms of disrespect and abuse experienced were; abandonment (n = 77), undignified care (n = 76), and lack of information on received care (n = 65). The unadjusted logistic analysis indicated that gravida 3 was significantly associated with disrespect and abuse, with a P-value of 0.022 and a crude odds ratio of 3.2 (95% CI: 1.18-9.08). However, after adjusting for other variables, this association was no longer statistically significant, as reflected by an adjusted odds ratio with P-value of 0.061. CONCLUSION: Our study revealed the high rate of disrespect and abuse towards women during labour and childbirth. Disrespect and abuse remains a significant issue in our study setting, emphasising the need for interventions to mitigate this problem by enhancing accountability mechanisms among healthcare providers working in maternity services.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| 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".