Disrespectful Care in Family Planning Services Among Youth and Adult Simulated Clients in Public Sector Facilities in Malawi.
Bibliographic record
Abstract
Abstract Background Provision of high-quality family planning (FP) services improves access to contraceptives. Negative experiences in maternal health have been documented worldwide and likely occur in other services including FP. This study aims to quantify disrespectful care for adult and adolescent women accessing FP in Malawi. Methods We used simulated clients (SCs) to measure disrespectful care in a census of public facilities in six districts of Malawi in 2018. SCs visited one provider in each of the 112 facilities: two SCs visits (one adult and one adolescent case scenario) or 224 SC visits total. We measured disrespectful care using a quantitative tool and field notes and report the prevalence and 95% confidence intervals for the indicators and by SC case scenarios contextualized with quotes from the field notes. Results Some SCs (12%) were refused care because they did not agree to receive a HIV test or vaccination, or the clinic was closed during operating hours. Over half (59%) of the visits did not have privacy. The SCs were not asked their contraceptive preference in 57% of the visits, 28% reported they were not greeted respectfully, and 20% reported interruptions. In 18% of the visits the SCs reported humiliation such as verbal abuse. Conclusions We documented instances of refusal of care, lack of privacy, poor client centered care and humiliating treatment by providers. We recommend continued effort to improve quality of care with an emphasis on client treatment, regular quality assessments that include measurement of disrespectful care, and more research on practices to reduce it.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".